Practical recommendations for gradient-based training of deep architectures. Learning algorithms related to artificial neural networks and in particular for Deep Learning may seem to involve many bells and whistles, called hyperparameters. This chapter is meant as a practical guide with recommendations for some of the most commonly used hyper-parameters, in particular in the context of learning algorithms based on backpropagated gradient and gradient-based optimization. It also discusses how to deal with the fact that more interesting results can be obtained when allowing one to adjust many hyper-parameters. Overall, it describes elements of the practice used to successfully and efficiently train and debug large-scale and often deep multi-layer neural networks. It closes with open questions about the training difficulties observed with deeper architectures.

Question: How to train a deep neural network?


DFD: Efficient Functional Dependency Discovery. The discovery of unknown functional dependencies in a dataset is of great importance for database redesign, anomaly detection and data cleansing applications. However, as the nature of the problem is exponential in the number of attributes none of the existing approaches can be applied on large datasets. We present a new algorithm DFD for discovering all functional dependencies in a dataset following a depth-first traversal strategy of the attribute lattice that combines aggressive pruning and efficient result verification. Our approach is able to scale far beyond existing algorithms for up to 7.5 million tuples, and is up to three orders of magnitude faster than existing approaches on smaller datasets.

Question: What is the name of the algorithm?


65GHz Doppler Sensor with On-Chip Antenna in 0.18μm SiGe BiCMOS. A single-chip 65GHz Doppler radar transceiver with on-chip patch antenna is reported. Implemented in a production 0.18mum SiGe BiCMOS process, it features a differential output transmit power of 4.3dBm, 16.5dB single-ended down-conversion gain and a double-sideband noise figure of 12.8dB. The radar includes a 65GHz 2-stage cascode LNA with S 11<-15dB at 50-94GHz and 14dB gain at 65GHz, a double-balanced down-convert mixer, a SiGe HBT IF amplifier with low 1/f noise, a VCO and a 65GHz output buffer. The LO is provided by an integrated varactor-tuned 61-67GHz VCO optimized for low phase noise. The patch antenna is designed to be impedance-matched for dual-band operation at 62.8 and 64.6GHz. The use of lumped inductors in all blocks and a vertically-stacked transformer for single-ended to differential conversion in the receive path help reduce the transceiver area to 1mm times 1mm

Question: What is the area of the 65GHz radar?


Ethical theory, codes of ethics and IS practice. Ethical issues, with respect to computer-based information systems, are important to the individual IS practitioner. These same issues also have an important impact on the moral well-being of organizations and societies. Considerable discussion has taken place in the Information Systems (IS) literature on specific ethical issues, but there is little published work which relates these issues to mainstream ethical theory. This paper describes a range of ethical theories drawn from philosophy literature and uses these theories to critique aspects of the newly revised ACM Code of Ethics. Some in the IS field on problematic ethical issues which are not resolved by the Code are then identified and discussed. The paper draws some implications and conclusions on the value of ethical theory and codes of practice, and on further work to develop existing ethical themes and to promote new initiatives in the ethical domain.

Question: What is the difference between ethical theory and codes of ethics?


An 800-MHz–6-GHz Software-Defined Wireless Receiver in 90-nm CMOS. A software-defined radio receiver is designed from a low-power ADC perspective, exploiting programmability of windowed integration sampler and clock-programmable discrete-time analog filters. To cover the major frequency bands in use today, a wideband RF front-end, including the low-noise amplifier (LNA) and a wide tuning-range synthesizer, spanning over 800 MHz to 6 GHz is designed. The wideband LNA provides 18-20 dB of maximum gain and 3-3.5 dB of noise figure over 800 MHz to 6 GHz. A low 1/f noise and high-linearity mixer is designed which utilizes the passive mixer core properties and provides around +70 dBm IIP2 over the bandwidth of operation. The entire receiver circuits are implemented in 90-nm CMOS technology. Programmability of the receiver is tested for GSM and 802.11g standards

Question: What is a software defined radio?


Affinity Studies between Drugs and Clays as Adsorbent Material. Pharmaceuticals, with veterinary and human usage, have continuously been launched into the environment and their presence has been frequently detected in water bodies. The inefficacy of conventional water treatment processes for the removal of drugs, added to their potential adverse effects to human health and environment, suggest that new separation processes should be studied. Adsorption is highlighted as a promising method and the use of alternative adsorbents is encouraged due to the high costs of activated carbon. Different clay materials were evaluated in the present work for the removal of amoxicillin, caffeine, propranolol, and diclofenac sodium from aqueous solutions. The removal efficiency depended on the drug and adsorbent material used and varied between 23-98 % for amoxicillin, 21-89 % for caffeine, 29-100 % for propranolol, and 2-99 % for diclofenac sodium. The results showed that clays may be used successfully as alternative adsorbent material on the removal of selected emergent contaminants.

Question: What is the difference between adsorption and adsorption?


Convolutional Neural Network-Based Human Detection in Nighttime Images Using Visible Light Camera Sensors. Because intelligent surveillance systems have recently undergone rapid growth, research on accurately detecting humans in videos captured at a long distance is growing in importance. The existing research using visible light cameras has mainly focused on methods of human detection for daytime hours when there is outside light, but human detection during nighttime hours when there is no outside light is difficult. Thus, methods that employ additional near-infrared (NIR) illuminators and NIR cameras or thermal cameras have been used. However, in the case of NIR illuminators, there are limitations in terms of the illumination angle and distance. There are also difficulties because the illuminator power must be adaptively adjusted depending on whether the object is close or far away. In the case of thermal cameras, their cost is still high, which makes it difficult to install and use them in a variety of places. Because of this, research has been conducted on nighttime human detection using visible light cameras, but this has focused on objects at a short distance in an indoor environment or the use of video-based methods to capture multiple images and process them, which causes problems related to the increase in the processing time. To resolve these problems, this paper presents a method that uses a single image captured at night on a visible light camera to detect humans in a variety of environments based on a convolutional neural network. Experimental results using a self-constructed Dongguk night-time human detection database (DNHD-DB1) and two open databases (Korea advanced institute of science and technology (KAIST) and computer vision center (CVC) databases), as well as high-accuracy human detection in a variety of environments, show that the method has excellent performance compared to existing methods.

Question: What is a convolutional neural network?


Brain regions with mirror properties: A meta-analysis of 125 human fMRI studies. Mirror neurons in macaque area F5 fire when an animal performs an action, such as a mouth or limb movement, and also when the animal passively observes an identical or similar action performed by another individual. Brain-imaging studies in humans conducted over the last 20 years have repeatedly attempted to reveal analogous brain regions with mirror properties in humans, with broad and often speculative claims about their functional significance across a range of cognitive domains, from language to social cognition. Despite such concerted efforts, the likely neural substrates of these mirror regions have remained controversial, and indeed the very existence of a distinct subcategory of human neurons with mirroring properties has been questioned. Here we used activation likelihood estimation (ALE), to provide a quantitative index of the consistency of patterns of fMRI activity measured in human studies of action observation and action execution. From an initial sample of more than 300 published works, data from 125 papers met our strict inclusion and exclusion criteria. The analysis revealed 14 separate clusters in which activation has been consistently attributed to brain regions with mirror properties, encompassing 9 different Brodmann areas. These clusters were located in areas purported to show mirroring properties in the macaque, such as the inferior parietal lobule, inferior frontal gyrus and the adjacent ventral premotor cortex, but surprisingly also in regions such as the primary visual cortex, cerebellum and parts of the limbic system. Our findings suggest a core network of human brain regions that possess mirror properties associated with action observation and execution, with additional areas recruited during tasks that engage non-motor functions, such as auditory, somatosensory and affective components.

Question: What brain regions have mirror properties?


Mobile robot positioning: Sensors and techniques. Exact knowledge of the position of a vehicle is a fundamental problem in mobile robot applications. In search for a solution, researchers and engineers have developed a variety of systems, sensors, and techniques for mobile robot positioning. This paper provides a review of relevant mobile robot positioning technologies. The paper defines seven categories for positioning systems: 1. Odometry; 2. Inertial Navigation; 3. Magnetic Compasses; 4. Active Beacons; 5. Global Positioning Systems; 6. Landmark Navigation; and 7. Model Matching. The characteristics of each category are discussed and examples of existing technologies are given for each category. The field of mobile robot navigation is active and vibrant, with more great systems and ideas being developed continuously. For this reason the examples presented in this paper serve only to represent their respective categories, but they do not represent a judgment by the authors. Many ingenious approaches can be found in the literature, although, for reasons of brevity, not all could be cited in this paper. 1) (Corresponding Author) The University of Michigan, Advanced Technologies Lab, 1101 Beal Avenue, Ann Arbor, MI 48109-2110, Ph.: 313-763-1560, Fax: 313-944-1113. Email: johannb@umich.edu 2) Naval Command, Control, and Ocean Surveillance Center, RDT&E Division 5303, 271 Catalina Boulevard, San Diego, CA 92152-5001, Email: Everett@NOSC.MIL 3) The University of Michigan, Advanced Technologies Lab, 1101 Beal Avenue, Ann Arbor, MI 481092110, Email: Feng@engin.umich.edu 4) The University of Michigan, Dept. of Nuclear Engineering and Radiological Sciences, 239 Cooley Bldg., Ann Arbor, MI 48109, Email: dkw@umich.edu

Question: What is the size of the canadian military?


Robust Instance Recognition in Presence of Occlusion and Clutter. We present a robust learning based instance recognition framework from single view point clouds. Our framework is able to handle real-world instance recognition challenges, i.e, clutter, similar looking distractors and occlusion. Recent algorithms have separately tried to address the problem of clutter [9] and occlusion [16] but fail when these challenges are combined. In comparison we handle all challenges within a single framework. Our framework uses a soft label Random Forest [5] to learn discriminative shape features of an object and use them to classify both its location and pose. We propose a novel iterative training scheme for forests which maximizes the margin between classes to improve recognition accuracy, as compared to a conventional training procedure. The learnt forest outperforms template matching, DPM [7] in presence of similar looking distractors. Using occlusion information, computed from the depth data, the forest learns to emphasize the shape features from the visible regions thus making it robust to occlusion. We benchmark our system with the state-of-the-art recognition systems [9, 7] in challenging scenes drawn from the largest publicly available dataset. To complement the lack of occlusion tests in this dataset, we introduce our Desk3D dataset and demonstrate that our algorithm outperforms other methods in all settings.

Question: How to handle occlusion in instance recognition?


3D printing of microwave passive components by different additive manufacturing technologies. This paper presents an overview of the possibility offered by 3D plastic printers for a quick, simple and affordable manufacturing of working filters and other passive devices such as antennas. This paper thus goes through numerous examples of passive devices made with the Fused Deposition Modeling (FDM) and material jetting (Polyjet©) technologies and will highlight how they can now be considered as a solid companion to RF designers during an optimization process up to Ku and higher bands.

Question: What is the difference between additive manufacturing and subtractive manufacturing?


Current Mode Control Integrated Circuit with High Accuracy Current Sensing Circuit for Buck Converter. A current mode control integrated circuit with accuracy current sensing circuit ( CSC ) for buck converter is presented in this the proposed accurate integrated current sensed inductor with the internal ramp be used for DC-DC converter feedback proposed CSC doesn't need an op amp to implement, and has been fabricated with a standard 0.35 mum CMOS process. Simulation result show that the switching converter can be operated up to 1 MHZ. The supply is suitable for signal cell lithium-ion battery supply power efficiency is over 85% for supply voltage from 2.5 V to 5 V and output current is 200 mA. The performance of the proposed circuit is the good compared to the other circuits.

Question: What is the purpose of this circuit?


Scalable Gaussian Process Regression Using Deep Neural Networks. We propose a scalable Gaussian process model for regression by applying a deep neural network as the feature-mapping function. We first pre-train the deep neural network with a stacked denoising auto-encoder in an unsupervised way. Then, we perform a Bayesian linear regression on the top layer of the pre-trained deep network. The resulting model, Deep-Neural-Network-based Gaussian Process (DNN-GP), can learn much more meaningful representation of the data by the finite-dimensional but deep-layered feature-mapping function. Unlike standard Gaussian processes, our model scales well with the size of the training set due to the avoidance of kernel matrix inversion. Moreover, we present a mixture of DNN-GPs to further improve the regression performance. For the experiments on three representative large datasets, our proposed models significantly outperform the state-of-the-art algorithms of Gaussian process regression.

Question: How to scale Gaussian process regression?


Footwear bio-modelling: An industrial approach. There is a growing need within the footwear sector to customise the design of the last from which a specific footwear style is to be produced. This customisation is necessary for user comfort and health reasons, as the user needs to wear a suitable shoe. For this purpose, a relationship must be established between the user foot and the last with which the style will be made; up until now, no model has existed that integrates both elements. On the one hand, traditional customised footwear manufacturing techniques are based on purely artisanal procedures which make the process arduous and complex; on the other hand, geometric models proposed by different authors present the impossibility of implementing them in an industrial environment with limited resources for the acquisition of morphometric and structural data for the foot, apart from the fact that they do not prove to be sufficiently accurate given the non similarity of the foot and last. In this paper, two interrelated geometric models are defined, the first, a bio-deformable foot model and the second, a deformable last model. The experiments completed show the goodness of the model, with it obtaining satisfactory results in terms of comfort, efficiency and precision, which make it viable for use in the sector.

Question: What is the difference between a bio-deformable foot model and a deformable last model?


Data mining for yield enhancement in semiconductor manufacturing and an empirical study. During wafer fabrication, process data, equipment data, and lot history will be automatically or semi-automatically recorded and accumulated in database for monitoring the process, diagnosing faults, and managing manufacturing. However, in high-tech industry such as semiconductor manufacturing, many factors that are interrelated affect the yield of fabricated wafers. Engineers who rely on personal domain knowledge cannot find possible root causes of defects rapidly and effectively. This study aims to develop a framework for data mining and knowledge discovery from database that consists of a Kruskal–Wallis test, K-means clustering, and the variance reduction splitting criterion to investigate the huge amount of semiconductor manufacturing data and infer possible causes of faults and manufacturing process variations. The extracted information and knowledge is helpful to engineers as a basis for trouble shooting and defect diagnosis. We validated this approach with an empirical study in a semiconductor foundry company in Taiwan and the results demonstrated the practical viability of this approach. 2006 Elsevier Ltd. All rights reserved.

Question: What is the difference between a semiconductor foundry and a semiconductor manufacturing company?


A Two-Level Investigation of Information Systems Outsourcing. O UTSOURCING is the contracting of various systems to outside information systems (IS) vendors. Ever since the Eastman Kodak--IBM partnership was reported in 1989 [15], outsourcing has emerged and has been recognized as a key method of managing IS. In previous studies of outsourcing [4, 5, 12, 15, 17, 20], two gaps are noticeable. The first relates to the fact that requirements for outsourcing are not uniform, and managers have different approaches to the process. Yet most previous research studies have phrased their inquiries unidimensionally in terms of the extent or degree of outsourcing: either as a binary variable or as size of contract in terms of the percentage of total IS budget [5, 15]. Neither unidimensional gauge is sufficiently expressive; neither allows representation of diverse patterns of outsourcing. Second, even though the IS industry had not used the term "outsourcing" explicitly in the past, outsourcing is not a new concept and has existed for many years in one form or another. Even though firms have repetitively used outside vendors for years, researchers have neither considered prior relationships in their studies of IS outsourcing nor studied the intentions of client firms to continue the partnership with the outsourcing vendors in the future. In this study, IS outsourcing decisions are investigated at two levels. The first level deals with the initial outsourcing decision of client firms. The second level pertains to the intention to continue the relationships with current outsourcing vendors in the future. The following three research questions are explored at these two levels (in contrast to the singlelevel approach taken by most researchers): • What are the dimensions of outsourcing decisions? Two dimensions, extent of substitution by vendors and strategic impact of IS applications, are proposed in order to conceptualize the diverse types of outsourcing relationships between clie

Question: What are the dimensions of outsourcing decisions?


Suppression of acoustic noise in speech using spectral subtraction. A new technique for the modelling of perceptual systems called formal modelling is developed. This technique begins with qualitative observations about the perceptual system, the so-called perceptual symmetries, to obtain through mathematical analysis certain model structures which may then be calibrated by experiment. The analysis proceeds in two different ways depending upon the choice of linear or nonlinear models. For the linear case, the analysis proceeds through the methods of unitary representation theory. It begins with a unitary group representation on the image space and produces what we have called the fundamental structure theorem. For the nonlinear case, the analysis makes essential use of infinite-dimensional manifold theory. It ber ins with a Lie group action on an image manifold and produces the fundamental structure formula. These techniques will be used to study the brightness perception mechanism of the human visual system. Several visual groups are defined and their corresponding structures for visual system models are obtained. A new transform called the Mandala transform will be deduced from a certain visual group and its implications for image processing will be discussed. Several new phenomena of brightness perception will be presented. New facts about the Mach band illusion along with new adaptation phenomena will be presented. Also a new visual illusion will be presented. A visual model based on the above techniques will be presented. It will also be shown how use of statistical estimation theory can be made in the study of contrast adaptation.

Question: What is the Mandala transform?


Voting models in random networks. A crucial problem of Social Sciences is under what conditions agreement, or disagreement, emerge in a network of interacting agents. This topic has application in many contexts, including business and marketing decisions, with potential impact on information and technological networks. In this paper we consider a particular model of interaction between a group of individuals connected through a network of acquaintances. In the first model, a node waits an exponentially time with parameter one, and when it expires it chooses one of its neighbors' at random and adopts its decision. In the second one, the node chooses the opinion which is the most adopted by its neighbors (hence, majority rule). We show how different updating rule of the agent' state lead to different emerging patterns, namely, agreement and disagreement. In addition, in the case of agreement, we provide bounds on the time to convergence for various types of graphs.

Question: What is the time to convergence for the majority rule?


Integrating technology in the classroom: a visual conceptualization of teachers' knowledge, goals and beliefs. In this paper, we devise a diagrammatic conceptualization to describe and represent the complex interplay of a teacher's knowledge (K), goals (G) and beliefs (B) in leveraging technology effectively in the classroom. The degree of coherency between the KGB region and the affordances of the technology serves as an indicator of the teachers' developmental progression through the initiation, implementation and maturation phases of using technology in the classroom. In our study, two teachers with differing knowledge, goals and beliefs are studied as they integrated GroupScribbles technology in their classroom lessons over a period of 1 year. Our findings reveal that the transition between the teacher's developmental states (as indicated by coherency diagrams) is nonlinear, and thus the importance of ensuring high coherency right at the initiation stage. Support for the teacher from other teachers and researchers remains an important factor in developing the teacher's competency to leverage the technology successfully. The stability of the KGB region further ensures smooth progression of the teacher's effective integration of technology in the classroom.

Question: What is the difference between a teacher's knowledge, goals and beliefs?


Summarizing Contrastive Themes via Hierarchical Non-Parametric Processes. Given a topic of interest, a contrastive theme is a group of opposing pairs of viewpoints. We address the task of summarizing contrastive themes: given a set of opinionated documents, select meaningful sentences to represent contrastive themes present in those documents. Several factors make this a challenging problem: unknown numbers of topics, unknown relationships among topics, and the extraction of comparative sentences. Our approach has three core ingredients: contrastive theme modeling, diverse theme extraction, and contrastive theme summarization. Specifically, we present a hierarchical non-parametric model to describe hierarchical relations among topics; this model is used to infer threads of topics as themes from the nested Chinese restaurant process. We enhance the diversity of themes by using structured determinantal point processes for selecting a set of diverse themes with high quality. Finally, we pair contrastive themes and employ an iterative optimization algorithm to select sentences, explicitly considering contrast, relevance, and diversity. Experiments on three datasets demonstrate the effectiveness of our method.

Question: How to summarize contrastive themes?


Blockchain challenges and opportunities: a survey. Copyright © 2017 Inderscience Enterprises Ltd. 2 Blockchain has numerous benefits such as decentralization, persistency, anonymity and auditability. There is a wide spectrum of blockchain applications ranging from cryptocurrency, financial services, risk management, Internet of Things to public and social services. Although a number of studies focus on using the blockchain technology in various application aspects, there is no comprehensive survey on the blockchain technology in both technological and application perspectives. To fill this gap, we conduct a comprehensive survey on the blockchain technology. In particular, this paper gives the blockchain taxonomy, introduces typical blockchain consensus algorithms, reviews blockchain applications and discusses technical challenges as well as recent advances in tackling the challenges. Moreover, this paper also points out the future directions in the blockchain technology.

Question: What is the blockchain taxonomy?


Detection and Visualization of Android Malware Behavior. Malware analysts still need to manually inspect malware samples that are considered suspicious by heuristic rules. They dissect software pieces and look for malware evidence in the code. The increasing number of malicious applications targeting Android devices raises the demand for analyzing them to find where the malcode is triggered when user interacts with them. In this paper a framework to monitor and visualize Android applications' anomalous function calls is described. Our approach includes platformindependent application instrumentation, introducing hooks in order to trace restricted API functions used at runtime of the application. These function calls are collected at a central server where the application behavior filtering and a visualization take place. This can help Android malware analysts in visually inspecting what the application under study does, easily identifying such malicious functions.

Question: How to detect malware on android?


Nanoconnectomic upper bound on the variability of synaptic plasticity. Information in a computer is quantified by the number of bits that can be stored and recovered. An important question about the brain is how much information can be stored at a synapse through synaptic plasticity, which depends on the history of probabilistic synaptic activity. The strong correlation between size and efficacy of a synapse allowed us to estimate the variability of synaptic plasticity. In an EM reconstruction of hippocampal neuropil we found single axons making two or more synaptic contacts onto the same dendrites, having shared histories of presynaptic and postsynaptic activity. The spine heads and neck diameters, but not neck lengths, of these pairs were nearly identical in size. We found that there is a minimum of 26 distinguishable synaptic strengths, corresponding to storing 4.7 bits of information at each synapse. Because of stochastic variability of synaptic activation the observed precision requires averaging activity over several minutes.

Question: How much information can be stored at a synapse?


Human-Interactive Subgoal Supervision for Efficient Inverse Reinforcement Learning. Humans are able to understand and perform complex tasks by strategically structuring the tasks into incremental steps or subgoals. For a robot attempting to learn to perform a sequential task with critical subgoal states, such states can provide a natural opportunity for interaction with a human expert. This paper analyzes the benefit of incorporating a notion of subgoals into Inverse Reinforcement Learning (IRL) with a Human-In-The-Loop (HITL) framework. The learning process is interactive, with a human expert first providing input in the form of full demonstrations along with some subgoal states. These subgoal states define a set of subtasks for the learning agent to complete in order to achieve the final goal. The learning agent queries for partial demonstrations corresponding to each subtask as needed when the agent struggles with the subtask. The proposed Human Interactive IRL (HI-IRL) framework is evaluated on several discrete path-planning tasks. We demonstrate that subgoal-based interactive structuring of the learning task results in significantly more efficient learning, requiring only a fraction of the demonstration data needed for learning the underlying reward function with the baseline IRL model.

Question: What is the benefit of subgoal-based interactive structuring of the learning task?


Vehicle Number Plate Detection System for Indian Vehicles. An exponential increase in number of vehicles necessitates the use of automated systems to maintain vehicle information. The information is highly required for both management of traffic as well as reduction of crime. Number plate recognition is an effective way for automatic vehicle identification. Some of the existing algorithms based on the principle of learning takes a lot of time and expertise before delivering satisfactory results but even then lacks in accuracy. In the proposed algorithm an efficient method for recognition for Indian vehicle number plates has been devised. The algorithm aims at addressing the problems of scaling and recognition of position of characters with a good accuracy rate of 98.07%.

Question: What is the algorithm for vehicle number plate recognition?


Automatic common-centroid layout generation for binary-weighted capacitors in charge-scaling DAC. As the precision of the capacitance ratios among binary-weighted capacitors is the key to accuracy/performance of charge-scaling digital-to-analog converters, it is very important to generate a highly matched common-centroid layout with minimum routing-induced parasitics. However, most of the previous works only focused on common-centroid placement optimization with the consideration of random and systematic mismatch. This paper introduces a novel common-centroid capacitor layout generation approach to minimize the parasitic impact on circuit accuracy/performance. Experimental results show that, compared with the manual layout, the layout generated by the presented approach can achieve even smaller layout area and better circuit accuracy/performance within much shorter time.

Question: How to minimize the parasitic impact on circuit accuracy/performance?


Evidence for van der Waals adhesion in gecko setae.. Geckos have evolved one of the most versatile and effective adhesives known. The mechanism of dry adhesion in the millions of setae on the toes of geckos has been the focus of scientific study for over a century. We provide the first direct experimental evidence for dry adhesion of gecko setae by van der Waals forces, and reject the use of mechanisms relying on high surface polarity, including capillary adhesion. The toes of live Tokay geckos were highly hydrophobic, and adhered equally well to strongly hydrophobic and strongly hydrophilic, polarizable surfaces. Adhesion of a single isolated gecko seta was equally effective on the hydrophobic and hydrophilic surfaces of a microelectro-mechanical systems force sensor. A van der Waals mechanism implies that the remarkable adhesive properties of gecko setae are merely a result of the size and shape of the tips, and are not strongly affected by surface chemistry. Theory predicts greater adhesive forces simply from subdividing setae to increase surface density, and suggests a possible design principle underlying the repeated, convergent evolution of dry adhesive microstructures in gecko, anoles, skinks, and insects. Estimates using a standard adhesion model and our measured forces come remarkably close to predicting the tip size of Tokay gecko seta. We verified the dependence on size and not surface type by using physical models of setal tips nanofabricated from two different materials. Both artificial setal tips stuck as predicted and provide a path to manufacturing the first dry, adhesive microstructures.

Question: What is the size of a gecko seta?


Ensemble forecasting of species distributions.. Concern over implications of climate change for biodiversity has led to the use of bioclimatic models to forecast the range shifts of species under future climate-change scenarios. Recent studies have demonstrated that projections by alternative models can be so variable as to compromise their usefulness for guiding policy decisions. Here, we advocate the use of multiple models within an ensemble forecasting framework and describe alternative approaches to the analysis of bioclimatic ensembles, including bounding box, consensus and probabilistic techniques. We argue that, although improved accuracy can be delivered through the traditional tasks of trying to build better models with improved data, more robust forecasts can also be achieved if ensemble forecasts are produced and analysed appropriately.

Question: How can we improve the accuracy of species distribution models?


Imperative Functional Programming. We present a new model, based on monads, for performing input/output in a non-strict, purely functional language. It is composable, extensible, efficient, requires no extensions to the type system, and extends smoothly to incorporate mixed-language working and in-place array updates.

Question: What is imperative functional programming?


Arrested development? Reconsidering dual-systems models of brain function in adolescence and disorders. The dual-systems model of a ventral affective system, whose reactivity confers risks and liabilities, and a prefrontal control system, whose regulatory capacities buffer against these vulnerabilities, is an intuitive account that pervades many fields in the cognitive neurosciences--especially in the study of populations that differ from neurotypical adults, such as adolescents or individuals with affective or impulse regulation disorders. However, recent evidence that is inconsistent with dual-systems models illustrates the complexity of developmental and clinical variations in brain function. Building new models to account for this complexity is critical to progress in these fields, and will be facilitated by research that emphasizes network-based approaches and maps relationships between structure and function, as well as brain and behavior, over time.

Question: What is the dual-systems model of brain function?


Training neural nets with the reactive tabu search. In this paper the task of training subsymbolic systems is considered as a combinatorial optimization problem and solved with the heuristic scheme of the reactive tabu search (RTS). An iterative optimization process based on a "modified local search" component is complemented with a meta-strategy to realize a discrete dynamical system that discourages limit cycles and the confinement of the search trajectory in a limited portion of the search space. The possible cycles are discouraged by prohibiting (i.e., making tabu) the execution of moves that reverse the ones applied in the most recent part of the search. The prohibition period is adapted in an automated way. The confinement is avoided and a proper exploration is obtained by activating a diversification strategy when too many configurations are repeated excessively often. The RTS method is applicable to nondifferentiable functions, is robust with respect to the random initialization, and effective in continuing the search after local minima. Three tests of the technique on feedforward and feedback systems are presented.

Question: How to train neural nets with the reactive tabu search?


Heart rate variability reflects self-regulatory strength, effort, and fatigue.. Experimental research reliably demonstrates that self-regulatory deficits are a consequence of prior self-regulatory effort. However, in naturalistic settings, although people know that they are sometimes vulnerable to saying, eating, or doing the wrong thing, they cannot accurately gauge their capacity to self-regulate at any given time. Because self-regulation and autonomic regulation colocalize in the brain, an autonomic measure, heart rate variability (HRV), could provide an index of self-regulatory strength and activity. During an experimental manipulation of self-regulation (eating carrots or cookies), HRV was elevated during high self-regulatory effort (eat carrots, resist cookies) compared with low self-regulatory effort (eat cookies, resist carrots). The experimental manipulation and higher HRV at baseline independently predicted persistence at a subsequent anagram task. HRV appears to index self-regulatory strength and effort, making it possible to study these phenomena in the field as well as the lab.

Question: What is the difference between self-regulation and autonomic regulation?


Low-cost traffic analysis of Tor. Tor is the second generation onion router supporting the anonymous transport of TCP streams over the Internet. Its low latency makes it very suitable for common tasks, such as Web browsing, but insecure against traffic-analysis attacks by a global passive adversary. We present new traffic-analysis techniques that allow adversaries with only a partial view of the network to infer which nodes are being used to relay the anonymous streams and therefore greatly reduce the anonymity provided by Tor. Furthermore, we show that otherwise unrelated streams can be linked back to the same initiator Our attack is feasible for the adversary anticipated by the Tor designers. Our theoretical attacks are backed up by experiments performed on the deployed, albeit experimental, Tor network. Our techniques should also be applicable to any low latency anonymous network. These attacks highlight the relationship between the field of traffic-analysis and more traditional computer security issues, such as covert channel analysis. Our research also highlights that the inability to directly observe network links does not prevent an attacker from performing traffic-analysis: the adversary can use the anonymising network as an oracle to infer the traffic load on remote nodes in order to perform traffic-analysis.

Question: How does Tor work?


Qualitative Simulation. Qualitative simulation is a key inference process in qualitative causal reasoning. However, the precise meaning of the different proposals and their relation with differential equations is often unclear. In this paper, we present a precise definition of qualitative structure and behavior descriptions as abstractions of differential equations and continuously differentiable functions. We present a new algorithm for qualitative simulation that generalizes the best features of existing algorithms, and allows direct comparisons among alternate approaches. Starting with a set of constraints abstracted from a differential equation, we prove that the OSIM algorithm is guaranteed to produce a qualitative behavior corresponding to any solution to the original equation. We also show that any qualitative simulation algorithm will sometimes produce spurious qualitative behaviors: ones which do not correspond to any mechanism satisfying the given constraints. These observations suggest specific types of care that must be taken in designing applications of qualitative causal reasoning systems, and in constructing and validating a knowledge base of mechanism descriptions.

Question: What is qualitative simulation?


Markov Logic Networks for Natural Language Question Answering. Our goal is to answer elementary-level science questions using knowledge extracted automatically from science textbooks, expressed in a subset of first-order logic. Given the incomplete and noisy nature of these automatically extracted rules, Markov Logic Networks (MLNs) seem a natural model to use, but the exact way of leveraging MLNs is by no means obvious. We investigate three ways of applying MLNs to our task. In the first, we simply use the extracted science rules directly as MLN clauses. Unlike typical MLN applications, our domain has long and complex rules, leading to an unmanageable number of groundings. We exploit the structure present in hard constraints to improve tractability, but the formulation remains ineffective. In the second approach, we instead interpret science rules as describing prototypical entities, thus mapping rules directly to grounded MLN assertions, whose constants are then clustered using existing entity resolution methods. This drastically simplifies the network, but still suffers from brittleness. Finally, our third approach, called Praline, uses MLNs to align the lexical elements as well as define and control how inference should be performed in this task. Our experiments, demonstrating a 15% accuracy boost and a 10x reduction in runtime, suggest that the flexibility and different inference semantics of Praline are a better fit for the natural language question answering task.

Question: What is the difference between the first and the second approach?


Textural Features Corresponding to Visual Perception. Textural features corresponding to human visual perception are very useful for optimum feature selection and texture analyzer design. We approximated in computational form six basic textural features, namely, coarseness, contrast, directionality, line-likeness, regularity, and roughness. In comparison with psychological measurements for human subjects, the computational measures gave good correspondences in rank correlation of 16 typical texture patterns. Similarity measurements using these features were attempted. The discrepancies between human vision and computerized techniques that we encountered in this study indicate fundamental problems in digital analysis of textures. Some of them could be overcome by analyzing their causes and using more sophisticated techniques.

Question: What are the textural features corresponding to human visual perception?


Overview of the Stereo and Multiview Video Coding Extensions of the H.264/MPEG-4 AVC Standard. Significant improvements in video compression capability have been demonstrated with the introduction of the H.264/MPEG-4 advanced video coding (AVC) standard. Since developing this standard, the Joint Video Team of the ITU-T Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG) has also standardized an extension of that technology that is referred to as multiview video coding (MVC). MVC provides a compact representation for multiple views of a video scene, such as multiple synchronized video cameras. Stereo-paired video for 3-D viewing is an important special case of MVC. The standard enables inter-view prediction to improve compression capability, as well as supporting ordinary temporal and spatial prediction. It also supports backward compatibility with existing legacy systems by structuring the MVC bitstream to include a compatible "base view." Each other view is encoded at the same picture resolution as the base view. In recognition of its high-quality encoding capability and support for backward compatibility, the stereo high profile of the MVC extension was selected by the Blu-Ray Disc Association as the coding format for 3-D video with high-definition resolution. This paper provides an overview of the algorithmic design used for extending H.264/MPEG-4 AVC towards MVC. The basic approach of MVC for enabling inter-view prediction and view scalability in the context of H.264/MPEG-4 AVC is reviewed. Related supplemental enhancement information (SEI) metadata is also described. Various "frame compatible" approaches for support of stereo-view video as an alternative to MVC are also discussed. A summary of the coding performance achieved by MVC for both stereo- and multiview video is also provided. Future directions and challenges related to 3-D video are also briefly discussed.

Question: What is the difference between MVC and H.264/MPEG-4 AVC?


OCNet: Object Context Network for Scene Parsing. In this paper, we address the problem of scene parsing with deep learning and focus on the context aggregation strategy for robust segmentation. Motivated by that the label of a pixel is the category of the object that the pixel belongs to, we introduce an object context pooling (OCP) scheme, which represents each pixel by exploiting the set of pixels that belong to the same object category with such a pixel, and we call the set of pixels as object context. Our implementation, inspired by the self-attention approach, consists of two steps: (i) compute the similarities between each pixel and all the pixels, forming a socalled object context map for each pixel served as a surrogate for the true object context, and (ii) represent the pixel by aggregating the features of all the pixels weighted by the similarities. The resulting representation is more robust compared to existing context aggregation schemes, e.g., pyramid pooling modules (PPM) in PSPNet and atrous spatial pyramid pooling (ASPP), which do not differentiate the context pixels belonging to the same object category or not, making the reliability of contextually aggregated representations limited. We empirically demonstrate our approach and two pyramid extensions with state-ofthe-art performance on three semantic segmentation benchmarks: Cityscapes, ADE20K and LIP. Code has been made available at: https://github.com/PkuRainBow/ OCNet.pytorch.

Question: What is the context aggregation strategy for scene parsing?


Social trust and social reciprocity based cooperative D2D communications. Thanks to the convergence of pervasive mobile communications and fast-growing online social networking, mobile social networking is penetrating into our everyday life. Aiming to develop a systematic understanding of the interplay between social structure and mobile communications, in this paper we exploit social ties in human social networks to enhance cooperative device-to-device communications. Specifically, as hand-held devices are carried by human beings, we leverage two key social phenomena, namely social trust and social reciprocity, to promote efficient cooperation among devices. With this insight, we develop a coalitional game theoretic framework to devise social-tie based cooperation strategies for device-to-device communications. We also develop a network assisted relay selection mechanism to implement the coalitional game solution, and show that the mechanism is immune to group deviations, individually rational, and truthful. We evaluate the performance of the mechanism by using real social data traces. Numerical results show that the proposed mechanism can achieve up-to 122% performance gain over the case without D2D cooperation.

Question: How to improve the performance of the mechanism?


A clean slate 4D approach to network control and management. Today's data networks are surprisingly fragile and difficult to manage. We argue that the root of these problems lies in the complexity of the control and management planes--the software and protocols coordinating network elements--and particularly the way the decision logic and the distributed-systems issues are inexorably intertwined. We advocate a complete refactoring of the functionality and propose three key principles--network-level objectives, network-wide views, and direct control--that we believe should underlie a new architecture. Following these principles, we identify an extreme design point that we call "4D," after the architecture's four planes: decision, dissemination, discovery, and data. The 4D architecture completely separates an AS's decision logic from pro-tocols that govern the interaction among network elements. The AS-level objectives are specified in the decision plane, and en-forced through direct configuration of the state that drives how the data plane forwards packets. In the 4D architecture, the routers and switches simply forward packets at the behest of the decision plane, and collect measurement data to aid the decision plane in controlling the network. Although 4D would involve substantial changes to today's control and management planes, the format of data packets does not need to change; this eases the deployment path for the 4D architecture, while still enabling substantial innovation in network control and management. We hope that exploring an extreme design point will help focus the attention of the research and industrial communities on this crucially important and intellectually challenging area.

Question: What is the 4D architecture?


A Framework for Clustering Massive Text and Categorical Data Streams. Many applications such as news group filtering, text crawling, and document organization require real time clustering and segmentation of text data records. The categorical data stream clustering problem also has a number of applications to the problems of customer segmentation and real time trend analysis. We will present an online approach for clustering massive text and categorical data streams with the use of a statistical summarization methodology. We present results illustrating the effectiveness of the technique.

Question: What is a framework for clustering massive text and categorical data streams?


Design of 4-Bit Universal Shift Register Using Reversible Gates. Power dissipation is one of the important factor in digital circuit design. Landauer's principle states that logic computations which are not reversible necessarily generate KT*ln2 Joules of heat energy for every bit of information that is lost, where k is Boltzmann's constant and T the absolute temperature at which computation is performed. Reversibility is the property of digital circuits in which there is one-to-one mapping between the inputs and the output vectors that is for each input vector there is a unique output vector and vice-versa. Thus one of the primary motivations for adopting reversible logic lies in the fact that it can provide a logic design methodologies for designing low power dissipating circuits. Fredkin gate, Feynman Gate is popularly used reversible logic gate which are used to implement various sequential circuits which are basic for design of digital circuits.

Question: What is the difference between Fredkin and Feynman gates?


Predicting football match results with logistic regression. Many efforts has been made in order to predict football matches result and selecting significant variables in football. Prediction is very useful in helping managers and clubs make the right decision to win leagues and tournaments. In this paper a logistic regression model is built to predict matches results of Barclays' Premier League season 2015/2016 for home win or away win and to determine what are the significant variable to win matches. Our work is different from others as we use only significant variables gathered from researches in the same field rather than making our own guess on what are the significant variables. We also used data gathered from video game FIFA, as Shin and Gasparyan [8] showed us that including data from the video game could improve prediction quality. The model was built using variations of training data from 2010/2011 season until 2015/2016. Logistic regression is a classification method which can be used to predict sports results and it can gives additional knowledge through regression coefficients. The variables used are "Home Offense", "Home Defense", "Away Offense", and "Away Defense". We conducted experiments by altering seasons of training data used. Prediction accuracy of built model is 69.5%. We found our work improved significantly compared to the one Snyder [9] did. We concluded that the significant variables are "Home Defense", and "Away Defense".

Question: What is logistic regression?


Covariate Shift in Hilbert Space: A Solution via Sorrogate Kernels. Covariate shift is an unconventional learning scenario in which training and testing data have different distributions. A general principle to solve the problem is to make the training data distribution similar to that of the test domain, such that classifiers computed on the former generalize well to the latter. Current approaches typically target on sample distributions in the input space, however, for kernel-based learning methods, the algorithm performance depends directly on the geometry of the kernel-induced feature space. Motivated by this, we propose to match data distributions in the Hilbert space, which, given a pre-defined empirical kernel map, can be formulated as aligning kernel matrices across domains. In particular, to evaluate similarity of kernel matrices defined on arbitrarily different samples, the novel concept of surrogate kernel is introduced based on the Mercer's theorem. Our approach caters the model adaptation specifically to kernel-based learning mechanism, and demonstrates promising results on several real-world applications. Proceedings of the 30 th International Conference on Machine Learning, Atlanta, Georgia, USA, 2013. JMLR: W&CP volume 28. Copyright 2013 by the author(s).

Question: What is the difference between covariate shift and domain shift?


Introduction to Nonlinear Optimization - Theory, Algorithms, and Applications with MATLAB. introduction to nonlinear optimization theory algorithms introduction to nonlinear optimization theory algorithms introduction to nonlinear optimization theory algorithms introduction to nonlinear optimization theory algorithms chapter 16: introduction to nonlinear programming nonlinear programming: concepts, algorithms and applications theory, algorithms, and applications with matlab introduction to nonlinear optimization epubsam course: math 657|optimization theory time: spring 2016, 5 convex optimization: modeling and algorithms nonlinear programming 13 mit massachusetts institute an introduction to nonlinear optimization theory ebook nonlinear optimization lecture notes for the course mat a and trends in optimization with e applications solving optimization problems using the matlab siam bestsellers 2000–2015 order author title code 2015 optimization an introduction imperial college london [review published in siam review, vol. 58, issue 1, pp. 164.] nonlinear optimization and applications springer convex analysis and nonlinear optimization theory and examples appm 4720/5720 advanced topics in convex optimization lecture slides on nonlinear programming based on lectures convex optimization — boyd & vandenberghe

Question: What is the bestsellers list?


Intuitive visualization of Pareto Frontier for multi-objective optimization in n-dimensional performance space. A visualization methodology is presented in which a Pareto Frontier can be visualized in an intuitive and straightforward manner for an n-dimensional performance space. Based on this visualization, it is possible to quickly identify 'good' regions of the performance and optimal design spaces for a multi-objective optimization application, regardless of space complexity. Visualizing Pareto solutions for more than three objectives has long been a significant challenge to the multi-objective optimization community. The Hyper-space Diagonal Counting (HSDC) method described here enables the lossless visualization to be implemented. The proposed method requires no dimension fixing. In this paper, we demonstrate the usefulness of visualizing n-f space (i.e. for more than three objective functions in a multiobjective optimization problem). The visualization is shown to aid in the final decision of what potential optimal design point should be chosen amongst all possible Pareto solutions.

Question: How to visualize pareto frontier for multi-objective optimization in n-dimensional performance space?


Demand Response as a Load Shaping Tool in an Intelligent Grid With Electric Vehicles. As electric vehicles (EVs) take a greater share in the personal automobile market, their penetration will cause overload conditions at the distribution transformer. This paper focuses on the impacts of charging EVs on residential distribution networks including the transformer. The cost to accommodate a large-scale EV penetration by upgrading distribution transformers can be prohibitive. To alleviate the potential new load peaks with minimal infrastructure investments, a demand response strategy is proposed as a load shaping tool that allows improvement in distribution transformer usage. With the proposed strategy, consumers' preferences, load priorities, and privacy can be taken into account.

Question: What is the cost of upgrading distribution transformers?


5.2 Distributed system of digitally controlled microregulators enabling per-core DVFS for the POWER8TM microprocessor. Integrated voltage regulator modules (iVRMs) [1] provide a cost-effective path to realizing per-core dynamic voltage and frequency scaling (DVFS), which can be used to optimize the performance of a power-constrained multi-core processor. This paper presents an iVRM system developed for the POWER8™ microprocessor, which functions as a very fast, accurate low-dropout regulator (LDO), with 90.5% peak power efficiency (only 3.1% worse than an ideal LDO). At low output voltages, efficiency is reduced but still sufficient to realize beneficial energy savings with DVFS. Each iVRM features a bypass mode so that some of the cores can be operated at maximum performance with no regulator loss. With the iVRM area including the input decoupling capacitance (DCAP) (but not the output DCAP inherent to the cores), the iVRMs achieve a power density of 34.5W/mm2, which exceeds that of inductor-based or SC converters by at least 3.4× [2].

Question: What is the power density of the iVRM?


A PRAM and NAND flash hybrid architecture for high-performance embedded storage subsystems. NAND flash-based storage is widely used in embedded systems due to its numerous benefits: low cost, high density, small form factor and so on. However, NAND flash-based storage is still suffering from serious performance degradation for random or small size write access. This degradation mainly comes from the physical constraints of NAND flash: erase-before-program and different unit size of erase and program operations. To overcome these constraints, we propose to use PRAM (Phase-change RAM) which supports advanced features: fast byte access capability and no requirement for erase-before-program.  In this paper, we focus on developing a high-performance NAND flash-based storage system by maximally exploiting the advanced feature of PRAM, in terms of performance and wearing out. To do this, we first propose a new hybrid storage architecture which consists of PRAM and NAND flash. Second, we devise two novel software schemes for the proposed hybrid storage architecture; FSMS (File System Metadata Separation) and hFTL (hybrid Flash Translation Layer). Finally, we demonstrate that our hybrid architecture increases the performance up to 290% and doubles the lifespan compared to the existing NAND flash only storage systems.

Question: What is a hybrid storage architecture?


Composite Scale of Morningness: psychometric properties, validity with Munich ChronoType Questionnaire and age/sex differences in Poland.. The present study aimed at testing psychometric properties of the Composite Scale of Morningness (CSM) and validating it with mid sleep on free days (MSF) derived from the Munich ChronoType Questionnaire (MCTQ) in Poland, along with analyzing age and sex differences in the CSM and MSF. A sample of 952 Polish residents (62.6% females) aged between 13 and 46 was tested. Additionally, a sample of 33 university students were given MCTQ and filled in a sleep diary for 8 days. MSF derived from MCTQ was related to the one from sleep diary (r=.44). The study revealed good reliability of the CSM (α=.84) and its validity: greater morningness preference was associated with earlier MSF from MCTQ (r=-.52). CSM scores were distributed over its full range, with a mean of 34, and did not differ between sexes, although females were earlier than males by 23minutes in MSF. Regarding age, eveningness estimated with both CSM and MSF was greatest in subjects aged 16-18years, and a shift toward eveningness during puberty and a shift back toward morningness in older age was observed. The Polish version of the CSM consisted of two components of morningness. Cutoff scores were: for evening types (lower 10%) 24 or less, for morning types (upper 10%) 43 or more. The Polish CSM presents good psychometric properties, which are similar to those reported in other language versions, and also presents sex/age patterns similar to those found previously.

Question: What is the cutoff score for morningness?


Buccinator myomucosal flap: clinical results and review of anatomy, surgical technique and applications.. BACKGROUND The buccinator musculomucosal flap is an axial-pattern flap based on either the buccal or the facial artery. We present our experience with this flap and describe its surgical anatomy, the surgical techniques utilised to raise the flap and its clinical applications.   MATERIALS AND METHODS We retrospectively reviewed all patients who had had buccinator myomucosal flaps created at the Groote Schuur Hospital between 1999 and 2004. Patients were also recalled to assess flap sensation and to record reduction of mouth opening as a consequence of donor site scarring.   RESULTS Of the 14 patients who had had a buccinator myomucosal flap created, there was one flap failure. Sensation was present in 71 per cent of flaps, and there was no trismus due to donor site scarring.   CONCLUSIONS The buccinator myomycosal flap is a dependable flap with good functional outcome and low morbidity.

Question: What is the buccinator myomucosal flap?


Reynolds flocking in reality with fixed-wing robots: Communication range vs. maximum turning rate. The success of swarm behaviors often depends on the range at which robots can communicate and the speed at which they change their behavior. Challenges arise when the communication range is too small with respect to the dynamics of the robot, preventing interactions from lasting long enough to achieve coherent swarming. To alleviate this dependency, most swarm experiments done in laboratory environments rely on communication hardware that is relatively long range and wheeled robotic platforms that have omnidirectional motion. Instead, we focus on deploying a swarm of small fixed-wing flying robots. Such platforms have limited payload, resulting in the use of short-range communication hardware. Furthermore, they are required to maintain forward motion to avoid stalling and typically adopt low turn rates because of physical or energy constraints. The tradeoff between communication range and flight dynamics is exhaustively studied in simulation in the scope of Reynolds flocking and demonstrated with up to 10 robots in outdoor experiments.

Question: How to deploy a swarm of flying robots?


Inverse dynamics control of floating base systems using orthogonal decomposition. Model-based control methods can be used to enable fast, dexterous, and compliant motion of robots without sacrificing control accuracy. However, implementing such techniques on floating base robots, e.g., humanoids and legged systems, is non-trivial due to under-actuation, dynamically changing constraints from the environment, and potentially closed loop kinematics. In this paper, we show how to compute the analytically correct inverse dynamics torques for model-based control of sufficiently constrained floating base rigid-body systems, such as humanoid robots with one or two feet in contact with the environment. While our previous inverse dynamics approach relied on an estimation of contact forces to compute an approximate inverse dynamics solution, here we present an analytically correct solution by using an orthogonal decomposition to project the robot dynamics onto a reduced dimensional space, independent of contact forces. We demonstrate the feasibility and robustness of our approach on a simulated floating base bipedal humanoid robot and an actual robot dog locomoting over rough terrain.

Question: How to compute the inverse dynamics of a floating base robot?


gTRICLUSTER: A More General and Effective 3D Clustering Algorithm for Gene-Sample-Time Microarray Data. Clustering is an important technique in microarray data analysis, and mining three-dimensional (3D) clusters in gene-sample-time (simply GST) microarray data is emerging as a hot research topic in this area. A 3D cluster consists of a subset of genes that are coherent on a subset of samples along a segment of time series. This kind of coherent clusters may contain information for the users to identify useful phenotypes, potential genes related to these phenotypes and their expression rules. TRICLUSTER is the state-of-the-art 3D clustering algorithm for GST microarray data. In this paper, we propose a new algorithm to mine 3D clusters over GST microarray data. We term the new algorithm gTRICLUSTER because it is based on a more general 3D cluster model than the one that TRICLUSTER is based on. gTRICLUSTER can find more biologically meaningful coherent gene clusters than TRICLUSTER can do. It also outperforms TRICLUSTER in robustness to noise. Experimental results on a real-world microarray dataset validate the effectiveness of the proposed new algorithm.

Question: What is a 3D cluster?


The relationship among young adult college students' depression, anxiety, stress, demographics, life satisfaction, and coping styles.. Recent research indicates that young adult college students experience increased levels of depression, anxiety, and stress. It is less clear what strategies college health care providers might use to assist students in decreasing these mental health concerns. In this paper, we examine the relative importance of coping style, life satisfaction, and selected demographics in predicting undergraduates' depression, anxiety, and stress. A total of 508 full-time undergraduate students aged 18-24 years completed the study measures and a short demographics information questionnaire. Coping strategies and life satisfaction were assessed using the Brief COPE Inventory and an adapted version of the Brief Students' Multidimensional Life Satisfaction Scale. Depression, anxiety, and stress were measured using the Depression Anxiety and Stress Scale-21 (DASS-21). Multiple regression analyses were used to examine the relative influence of each of the independent variables on depression, anxiety, and stress. Maladaptive coping was the main predictor of depression, anxiety, and stress. Adaptive coping was not a significant predictor of any of the three outcome variables. Reducing maladaptive coping behaviors may have the most positive impact on reducing depression, anxiety, and stress in this population.

Question: What is the relationship between maladaptive coping and depression, anxiety, and stress?


Table 1 : A Comparison between Lean Construction and Agile Project. This paper briefly summarises the evolution of Agile Project Management (APM) and differentiates it from lean and agile production and 'leagile' construction. The significant benefits being realized through employment of APM within the information systems industry are stated. The characteristics of APM are explored, including: philosophy, organizational attitudes and practices, planning, execution and control and learning. Finally, APM is subjectively assessed as to its potential contribution to the pre-design, design and construction phases. In conclusion, it is assessed that APM offers considerable potential for application in predesign and design but that there are significant hurdles to its adoption in the actual construction phase. Should these be overcome, APM offers benefits well beyond any individual project.

Question: What is the difference between lean and agile construction?


A Nonlinear-Disturbance-Observer-Based DC-Bus Voltage Control for a Hybrid AC/DC Microgrid. DC-bus voltage control is an important task in the operation of a dc or a hybrid ac/dc microgrid system. To improve the dc-bus voltage control dynamics, traditional approaches attempt to measure and feedforward the load or source power in the dc-bus control scheme. However, in a microgrid system with distributed dc sources and loads, the traditional feedforward-based methods need remote measurement with communications. In this paper, a nonlinear disturbance observer (NDO) based dc-bus voltage control is proposed, which does not need the remote measurement and enables the important "plug-and-play" feature. Based on this observer, a novel dc-bus voltage control scheme is developed to suppress the transient fluctuations of dc-bus voltage and improve the power quality in such a microgrid system. Details on the design of the observer, the dc-bus controller and the pulsewidth-modulation (PWM) dead-time compensation are provided in this paper. The effects of possible dc-bus capacitance variation are also considered. The performance of the proposed control strategy has been successfully verified in a 30 kVA hybrid microgrid including ac/dc buses, battery energy storage system, and photovoltaic (PV) power generation system.

Question: What is a hybrid microgrid?


Replicating Milgram: Would people still obey today?. The author conducted a partial replication of Stanley Milgram's (1963, 1965, 1974) obedience studies that allowed for useful comparisons with the original investigations while protecting the well-being of participants. Seventy adults participated in a replication of Milgram's Experiment 5 up to the point at which they first heard the learner's verbal protest (150 volts). Because 79% of Milgram's participants who went past this point continued to the end of the shock generator's range, reasonable estimates could be made about what the present participants would have done if allowed to continue. Obedience rates in the 2006 replication were only slightly lower than those Milgram found 45 years earlier. Contrary to expectation, participants who saw a confederate refuse the experimenter's instructions obeyed as often as those who saw no model. Men and women did not differ in their rates of obedience, but there was some evidence that individual differences in empathic concern and desire for control affected participants' responses.

Question: Would people still obey today?


A 240 GHz ultra-wideband FMCW radar system with on-chip antennas for high resolution radar imaging. Nowadays emerging industrial radar applications demand for high-resolution, high-precision and at the same time low-cost radar sensors. Recent advances in semiconductor technology allow highly integrated radar sensors at frequencies up to several hundred GHz in mass-production suitable and cost-effective SiGe bipolar technologies. In this contribution, a SiGe MMIC-based 240 GHz radar sensor with more than 60GHz bandwidth is presented. It consists of a MMIC chip including the high-frequency components and a digital control module with the PLL stabilisation, ramp generation, and data acquisition. The antenna is realized by on-chip patch antennas, which are focused by using an additional dielectric lens. The radar allows fast and highly linear frequency sweeps from 204 GHz to 265 GHz with an maximum output power of ≈ -1dBm EIRP (patch only). A phase noise of <;-65 dBc/Hz (>1 kHz offset) is achieved over the complete tuning range. Additionally range profile, jitter and imaging measurements are presented to demonstrate the achieved system performance.

Question: What is a mmic?


Listen and Translate: A Proof of Concept for End-to-End Speech-to-Text Translation. HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Listen and Translate: A Proof of Concept for End-to-End Speech-to-Text Translation Alexandre Bérard, Olivier Pietquin, Laurent Besacier, Christophe Servan

Question: What is the name of the french archive?


A Comprehensive Survey of Technologies for Building a Hybrid High Performance Intrusion Detection System. Intrusion detection plays a vital role in maintaining the stability of any network. The major requirements for any intrusion detection system are speed, accuracy and less memory. Though various intrusion detection methods are available, they excel at some points while lack in the others. This paper presents a comprehensive survey of the technologies that are used for detecting intrusions. It analyzes the pros and cons of each technology and the literature works that utilizes these technologies. Challenges faced by the current IDS and the requirements for IDS in the current network scenario are discussed in detail. A detailed study on the datasets that can be used for effective building of an IDS is discussed. The research framework is proposed and a discussion of the various technologies that can be used for improving the efficiency of the IDS is provided.

Question: What is the size of the canadian military?


A 3.3-V single-poly CMOS audio ADC delta-sigma modulator with 98-dB peak SINAD and 105-dB peak SFDR. This paper presents a second-order /spl Delta//spl Sigma/ modulator for audio-band analog-to-digital conversion implemented in a 3.3-V, 0.5-/spl mu/m, single-poly CMOS process using metal-metal capacitors that achieves 98-dB peak signal-to-noise-and-distortion ratio and 105-dB peak spurious-free dynamic range. The design uses a low-complexity, first-order mismatch shaping 33-level digital-to-analog converter and a 33-level flash analog-to-digital converter with digital common-mode rejection and dynamic element matching of comparator offsets. These signal-processing innovations, combined with established circuit techniques, enable state-of-the art performance in CMOS technology optimized for digital circuits.

Question: What is a CMOS process?


Technochange management: using IT to drive organizational change. Using IT in ways that can trigger major organizational changes creates high-risk, potentially high-reward, situations that I call technochange (for technology-driven organizational change). Technochange differs from typical IT projects and from typical organizational change programs and therefore requires a different approach. One major risk in technochange—that people will not use information technology and related work practices—is not thoroughly addressed by the discipline of IT project management, which focuses on project cost, project schedule, and solution functionality. Organizational change management approaches are also generally not effective on their own, because they take as a given the IT ''solutions'' developed by a technical team. Consequently, the potential for the IT ''solution'' to be misaligned with important organizational characteristics, such as culture or incentives, is great. Merely combining IT project management and organizational change management approaches does not produce the best results, for two reasons. First, the additive approach does not effectively address the many failure-threatening problems that can arise over the lengthy sequential process of the typical technochange lifecycle. Second, the additive approach is not structured to produce the characteristics of a good technochange solution: a complete intervention consisting of IT and complementary organizational changes, an implementable solution with minimal misfits with the existing organization, and an organization primed to appropriate the potential bene¢ts of the technochange solution. With hard work and care, the combined IT project management plus organizational change approach can be made to work. However, an iterative, incremental approach to implementing technochange can be a better strategy in many situations. The essential characteristic of the technochange prototyping approach is that each phase invo

Question: What is the difference between IT project management and organizational change management?


MapReduce-based fuzzy c-means clustering algorithm: implementation and scalability. The management and analysis of big data has been identified as one of the most important emerging needs in recent years. This is because of the sheer volume and increasing complexity of data being created or collected. Current clustering algorithms can not handle big data, and therefore, scalable solutions are necessary. Since fuzzy clustering algorithms have shown to outperform hard clustering approaches in terms of accuracy, this paper investigates the parallelization and scalability of a common and effective fuzzy clustering algorithm named Fuzzy C-Means (FCM) algorithm. The algorithm is parallelized using the MapReduce paradigm outlining how the Map and Reduce primitives are implemented. A validity analysis is conducted in order to show that the implementation works correctly achieving competitive purity results compared to state-of-the art clustering algorithms. Furthermore, a scalability analysis is conducted to demonstrate the performance of the parallel FCM implementation with increasing number of computing nodes used.

Question: How to implement fuzzy clustering algorithm?


Muscular and postural synergies of the human hand.. Because humans have limited ability to independently control the many joints of the hand, a wide variety of hand shapes can be characterized as a weighted combination of just two or three main patterns of covariation in joint rotations, or "postural synergies." The present study sought to align muscle synergies with these main postural synergies and to describe the form of membership of motor units in these postural/muscle synergies. Seventeen joint angles and the electromyographic (EMG) activities of several hand muscles (both intrinsic and extrinsic muscles) were recorded while human subjects held the hand statically in 52 specific shapes (i.e., shaping the hand around 26 commonly grasped objects or forming the 26 letter shapes of a manual alphabet). Principal-components analysis revealed several patterns of muscle synergy, some of which represented either coactivation of all hand muscles, or reciprocal patterns of activity (above and below average levels) in the intrinsic index finger and thumb muscles or (to a lesser extent) in the extrinsic four-tendoned extensor and flexor muscles. Single- and multiunit activity was generally a multimodal function of whole hand shape. This implies that motor-unit activation does not align with a single synergy; instead, motor units participate in multiple muscle synergies. Thus it appears that the organization of the global pattern of hand muscle activation is highly distributed. This organization mirrors the highly fractured somatotopy of cortical hand representations and may provide an ideal substrate for motor learning and recovery from injury.

Question: What is the function of the hand?


Design and Analysis of Low-Power 11- Transistor Full Adder. Full adders are exigent components in applications such as digital signal processors (DSP) architectures and microprocessors. In this paper, we propose a technique to build a new 11-transistor FA .We have done HSPICE simulation runs the new design 11-T full adders .In CMOS integrated circuit design there is a tradeoff between static power consumption and technology scaling. Static power dissipation is a challenge for the circuit designer. So we reduce the static power dissipation. In order to achieve lower static power consumption, one has to scarifies design area and circuit performance. In this paper we propose a new circuit of 11-Transistor full adder in CMOS VLSI circuit.

Question: How to reduce static power consumption?


The history of RFID. Radio frequency identification (RFID) is an integral part of our life, which increases productivity and convenience. It is the term coined for short-range radio technology used to communicate mainly digital information between a stationary location and a movable object or between movable objects. This RFID system uses the principle of modulated backscatter where it can transfer the data from the tag to the reader. The tag generally reads its internal memory of stored data and changes the loading on the tag antenna in a coded manner corresponding to the stored data. RFID is a technology, which spans systems engineering, software development, encryption etc., and thus there are many engineers involved in the development and application of RFID and at present the shortage of technical and business people trained in RFID is hampering the growth of the industry.

Question: What is the history of RFID?


Evolutionary computation and evolutionary deep learning for image analysis, signal processing and pattern recognition. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). GECCO '18 Companion, July 15--19, 2018, Kyoto, Japan © 2018 Copyright held by the owner/author(s). 978-1-4503-57647/18/07...$15.00 DOI https://doi.org/10.1145/3205651.3207859

Question: What is the difference between evolutionary computation and evolutionary deep learning?


Searching for processes and threads in Microsoft Windows memory dumps. Current tools to analyze memory dumps of systems running Microsoft Windows usually build on the concept of enumerating lists maintained by the kernel to keep track of processes, threads and other objects. Therefore they will frequently fail to detect objects that are already terminated or which have been hidden by Direct Kernel Object Manipulation

Question: How to search for processes and threads in memory dumps?


Painting Outside the Box: Image Outpainting with GANs. The challenging task of image outpainting (extrapolation) has received comparatively little attention in relation to its cousin, image inpainting (completion). Accordingly, we present a deep learning approach based on [4] for adversarially training a network to hallucinate past image boundaries. We use a three-phase training schedule to stably train a DCGAN architecture on a subset of the Places365 dataset. In line with [4], we also use local discriminators to enhance the quality of our output. Once trained, our model is able to outpaint 128 × 128 color images relatively realistically, thus allowing for recursive outpainting. Our results show that deep learning approaches to image outpainting are both feasible and promising.

Question: How to paint outside the box?


A binary linear programming formulation of the graph edit distance. A binary linear programming formulation of the graph edit distance for unweighted, undirected graphs with vertex attributes is derived and applied to a graph recognition problem. A general formulation for editing graphs is used to derive a graph edit distance that is proven to be a metric, provided the cost function for individual edit operations is a metric. Then, a binary linear program is developed for computing this graph edit distance, and polynomial time methods for determining upper and lower bounds on the solution of the binary program are derived by applying solution methods for standard linear programming and the assignment problem. A recognition problem of comparing a sample input graph to a database of known prototype graphs in the context of a chemical information system is presented as an application of the new method. The costs associated with various edit operations are chosen by using a minimum normalized variance criterion applied to pairwise distances between nearest neighbors in the database of prototypes. The new metric is shown to perform quite well in comparison to existing metrics when applied to a database of chemical graphs

Question: What is a chemical information system?


Effects of gratitude meditation on neural network functional connectivity and brain-heart coupling. A sense of gratitude is a powerful and positive experience that can promote a happier life, whereas resentment is associated with life dissatisfaction. To explore the effects of gratitude and resentment on mental well-being, we acquired functional magnetic resonance imaging and heart rate (HR) data before, during, and after the gratitude and resentment interventions. Functional connectivity (FC) analysis was conducted to identify the modulatory effects of gratitude on the default mode, emotion, and reward-motivation networks. The average HR was significantly lower during the gratitude intervention than during the resentment intervention. Temporostriatal FC showed a positive correlation with HR during the gratitude intervention, but not during the resentment intervention. Temporostriatal resting-state FC was significantly decreased after the gratitude intervention compared to the resentment intervention. After the gratitude intervention, resting-state FC of the amygdala with the right dorsomedial prefrontal cortex and left dorsal anterior cingulate cortex were positively correlated with anxiety scale and depression scale, respectively. Taken together, our findings shed light on the effect of gratitude meditation on an individual's mental well-being, and indicate that it may be a means of improving both emotion regulation and self-motivation by modulating resting-state FC in emotion and motivation-related brain regions.

Question: How does gratitude meditation affect the brain?


LateralPaD: A surface-haptic device that produces lateral forces on a bare finger. The LateralPaD is a surface haptic device that generates lateral (shear) force on a bare finger, by vibrating the touch surface simultaneously in both out-of-plane (normal) and in-plane (lateral) directions. A prototype LateralPaD has been developed in which the touch surface is glass, and piezoelectric actuators drive normal and lateral resonances at the same ultrasonic frequency (~22.3 KHz). The force that develops on the finger can be controlled by modulating the relative phase of the two resonances. A 2DOF load cell setup is used to characterize the dependence of induced lateral force on vibration amplitude, relative phase, and applied normal force. A Laser Doppler Vibrometer (LDV) is used to measure the motion of glass surface as well as of the fingertip. Together, these measurements yield insight into the mechanism of lateral force generation. We show evidence for a mechanism dependent on tilted impacts between the LateralPaD and fingertip.

Question: What is a surface haptic device?


Averaging Expert Predictions. We consider algorithms for combining advice from a set of experts. In each trial, the algorithm receives the predictions of the experts and produces its own prediction. A loss function is applied to measure the discrepancy between the predictions and actual observations. The algorithm keeps a weight for each expert. At each trial the weights are first used to help produce the prediction and then updated according to the observed outcome. Our starting point is Vovk's Aggregating Algorithm, in which the weights have a simple form: the weight of an expert decreases exponentially as a function of the loss incurred by the expert. The prediction of the Aggregating Algorithm is typically a nonlinear function of the weights and the experts' predictions. We analyze here a simplified algorithm in which the weights are as in the original Aggregating Algorithm, but the prediction is simply the weighted average of the experts' predictions. We show that for a large class of loss functions, even with the simplified prediction rule the additional loss of the algorithm over the loss of the best expert is at most c ln n, where n is the number of experts and c a constant that depends on the loss function. Thus, the bound is of the same form as the known bounds for the Aggregating Algorithm, although the constants here are not quite as good. We use relative entropy to rewrite the bounds in a stronger form and to motivate the update.

Question: What is the average expert prediction?


Perceivable Light Fields: Matching the Requirements Between the Human Visual System and Autostereoscopic 3-D Displays. Recently, there has been a substantial increase in efforts to develop 3-D visualization technologies that can provide the viewers with a realistic 3-D visual experience. Various terms such as "reality communication" have been used to categorize these efforts. In order to provide the viewers with a complete and realistic visual sensation, the display or visualization system and the displayed content need to match the physiological 3-D information sensing capabilities of the human visual system which can be quite complex. These may include spatial and temporal resolutions, depth perception, dynamic range, spectral contents, nonlinear effects, and vergence accommodation effects. In this paper, first we present an overview of some of the 3-D display research efforts which have been extensively pursued in Asia, Europe, and North America among other areas. Based on the limitations and comfort-based requirements of the human visual system when viewing a nonnatural visual input from 3-D displays, we present an analytical framework that combines main perception and human visual requirements with analytical tools and principles used in related disciplines such as optics, computer graphics, computational imaging, and signal processing. Building on the widely used notion of light fields, we define a notion of perceivable light fields to account for the human visual system physiological requirements, and propagate it back to the display device to determine the display device specifications. This helps us clarify the fundamental and practical requirements of the 3-D display devices for reality viewing communication. In view of the proposed analytical framework, we overview various methods that can be applied to overcome the extensive information needed to be displayed in order to meet the requirements imposed by the human visual system.

Question: What is the difference between a light field and a 3-D display?


Super-resolution from image sequences-a review. Growing interest in super-resolution (SR) restoration of video sequences and the closely related problem of construction of SR still images from image sequences has led to the emergence of several competing methodologies. We review the state of the art of SR techniques using a taxonomy of existing techniques. We critique these methods and identify areas which promise performance improvements.

Question: What is the state of the art of super-resolution?


A DNA nanorobot functions as a cancer therapeutic in response to a molecular trigger in vivo. Nanoscale robots have potential as intelligent drug delivery systems that respond to molecular triggers. Using DNA origami we constructed an autonomous DNA robot programmed to transport payloads and present them specifically in tumors. Our nanorobot is functionalized on the outside with a DNA aptamer that binds nucleolin, a protein specifically expressed on tumor-associated endothelial cells, and the blood coagulation protease thrombin within its inner cavity. The nucleolin-targeting aptamer serves both as a targeting domain and as a molecular trigger for the mechanical opening of the DNA nanorobot. The thrombin inside is thus exposed and activates coagulation at the tumor site. Using tumor-bearing mouse models, we demonstrate that intravenously injected DNA nanorobots deliver thrombin specifically to tumor-associated blood vessels and induce intravascular thrombosis, resulting in tumor necrosis and inhibition of tumor growth. The nanorobot proved safe and immunologically inert in mice and Bama miniature pigs. Our data show that DNA nanorobots represent a promising strategy for precise drug delivery in cancer therapy.

Question: What is a DNA nanorobot?


Deep Representation Learning with Target Coding. We consider the problem of learning deep representation when target labels are available. In this paper, we show that there exists intrinsic relationship between target coding and feature representation learning in deep networks. Specifically, we found that distributed binary code with error correcting capability is more capable of encouraging discriminative features, in comparison to the 1-of-K coding that is typically used in supervised deep learning. This new finding reveals additional benefit of using error-correcting code for deep model learning, apart from its well-known error correcting property. Extensive experiments are conducted on popular visual benchmark datasets.

Question: What is the relationship between target coding and feature representation learning?


An Improved Design for a 1–18 GHz Double-Ridged Guide Horn Antenna. It is a well known fact that the traditional 1-18 GHz double ridge guide horn (DRGH) antenna suffers from pattern deterioration above 12 GHz. At these frequencies, instead of maintaining a single main lobe radiation pattern, the pattern splits up into four lobes. It was shown in the literature that higher order modes are causing the pattern breakup. A benchmark study is performed to establish the performance of typical current and historic 1-18 GHz DRGH antennas. The performance of the antennas are evaluated in terms of gain, VSWR and radiation patterns. An improved 1-18 GHz DRGH antenna is presented. The new design has better gain and VSWR performance without any pattern deterioration. It also consists of significantly fewer parts, reducing the possibility of performance deterioration due to gaps between parts. Two prototypes of the new design were manufactured and tested with excellent agreement between measured and simulated results. The aperture dimensions of the new design are identical to that of the traditional DRGH, making it the only 1-18 GHz DRGH without pattern breakup whose aperture dimensions comply with the requirements specified in MIL-STD-461F - 24.2 by 13.6 cm.

Question: What is the aperture dimensions of the new design?


ECG measurement on a chair without conductive contact. For the purpose of long-term, everyday electrocardiogram (ECG) monitoring, we present a convenient method of ECG measurement without direct conductive contact with the skin while subjects sat on a chair wearing normal clothes. Measurements were made using electrodes attached to the back of a chair, high-input-impedance amplifiers mounted on the electrodes, and a large ground-plane placed on the chair seat. ECGs were obtained by the presented method for several types of clothing and compared to ECGs obtained from conventional measurement using Ag-AgCl electrodes. Motion artifacts caused by usual desk works were investigated. This study shows the feasibility of the method for long-term, convenient, everyday use

Question: How to measure ECG without conductive contact?


Micro bubble manipulation towards single cell handling tool. We report a series of micro air bubble manipulations (transporting, merging and eliminating of air bubbles) in two-dimensional microchannels filled with a water solution. Air bubbles (~500 nano liters in volume) are driven by electrowetting-on-dielectric (EWOD) principle. By sequentially energizing an array of electrodes covered with dielectric layers, air bubbles can be transported along a programmed path, merged into a single larger one, and eliminated out of a bulk water solution. This bubble manipulation technique can be applied to efficiently handle micro objects. As a proof of concept, we successfully demonstrate in a millimeter scale that a fish egg and a sesame husk are attached to an air bubble and then driven by the bubble in a programmed way. The moving air bubble can push and pull the attached objects of which surface is hydrophilic or hydrophobic. This handling technique will bring a novel, versatile, cost-effective, high throughput tool, enabling us to efficiently transport, trap, and isolate individual micro bio-entities such as cells, functional particles and possibly molecules

Question: How to manipulate air bubbles?


Dynamic Reserve Prices for Repeated Auctions: Learning from Bids - Working Paper. A large fraction of online advertisements are sold via repeated second price auctions. In these auctions, the reserve price is the main tool for the auctioneer to boost revenues. In this work, we investigate the following question: Can changing the reserve prices based on the previous bids improve the revenue of the auction, taking into account the long-term incentives and strategic behavior of the bidders? We show that if the distribution of the valuations is known and satisfies the standard regularity assumptions, then the optimal mechanism has a constant reserve. However, when there is uncertainty in the distribution of the valuations and competition among the bidders, previous bids can be used to learn the distribution of the valuations and to update the reserve prices. We present a simple approximately incentive-compatible and optimal dynamic reserve mechanism that can significantly improve the revenue over the best static reserve in such settings.

Question: What is the optimal reserve price?