Dual-Band Loop-Dipole Composite Unidirectional Antenna for Broadband Wireless Communications. The design of a novel dual-band loop-dipole composite unidirectional antenna for broadband wireless applications is proposed. First, design guidelines of the antenna are presented, and then, a step-by-step derivation of the antenna geometry is drawn. The antenna's operation principle is analyzed by carrying out parametric studies of surface current distribution, impedance and radiation patterns. The reflection coefficient, radiation patterns and gain of the antenna are numerically and experimentally studied to verify the operation principle and the design approach. It is demonstrated that two pass-bands, from 1.54 to 3.24 and from 4.88 to 6.80 GHz, of reflection coefficient smaller than -10 dB are obtained. The antenna has stable and unidirectional radiation pattern with low cross polarization within its pass-bands. The average gain of the antenna is 6.7 dBi at low frequency band and 6.5 dBi at high frequency band.

Question: What is the dual-band loop-dipole composite unidirectional antenna for broadband wireless communications?


From turtles to Tangible Programming Bricks: explorations in physical language design. This article provides a historical overview of educational computing research at MIT from the mid-1960s to the present day, focusing on physical interfaces. It discusses some of the results of this research: electronic toys that help children develop advanced modes of thinking through free-form play. In this historical context, the article then describes and discusses the author's own research into tangible programming, culminating in the development of the Tangible Programming Bricks system—a platform for creating microworlds for children to explore computation and scientific thinking.

Question: What is the history of educational computing research at MIT?


Using Lexical Resources for Irony and Sarcasm Classification. The paper presents a language dependent model for classification of statements into ironic and non-ironic. The model uses various language resources: morphological dictionaries, sentiment lexicon, lexicon of markers and a WordNet based ontology. This approach uses various features: antonymous pairs obtained using the reasoning rules over the Serbian WordNet ontology (R), antonymous pairs in which one member has positive sentiment polarity (PPR), polarity of positive sentiment words (PSP), ordered sequence of sentiment tags (OSA), Part-of-Speech tags of words (POS) and irony markers (M). The evaluation was performed on two collections of tweets that had been manually annotated according to irony. These collections of tweets as well as the used language resources are in the Serbian language (or one of closely related languages --Bosnian/Croatian/Montenegrin). The best accuracy of the developed classifier was achieved for irony with a set of 5 features -- (PPR, PSP, POS, OSA, M) -- acc = 86.1%, while for sarcasm the best results were achieved with the set (R, PSP, POS, OSA, M) -- acc = 72.8.

Question: What is the best accuracy of the developed classifier?


Aggressive driving with model predictive path integral control. In this paper we present a model predictive control algorithm designed for optimizing non-linear systems subject to complex cost criteria. The algorithm is based on a stochastic optimal control framework using a fundamental relationship between the information theoretic notions of free energy and relative entropy. The optimal controls in this setting take the form of a path integral, which we approximate using an efficient importance sampling scheme. We experimentally verify the algorithm by implementing it on a Graphics Processing Unit (GPU) and apply it to the problem of controlling a fifth-scale Auto-Rally vehicle in an aggressive driving task.

Question: What is a model predictive path integral control algorithm?


Torque-Maximizing Design of Double-Stator, Axial-Flux, PM Machines Using Simple Non-Linear Magnetic Analysis. This paper presents a torque-maximizing design of a double-stator, axial-flux PM machine using a simple non-linear magnetic analysis. The proposed analysis consists of a geometric- flux-tube-based equivalent-magnetic-circuit model. The model can take into account not only the magnetic saturation but also the three-dimensional(3D) flux distribution. The proposed analysis has realized a dramatic reduction in the computation time compared to 3D-FEA, keeping reasonable analytical accuracy. At first, the validity of the proposed analysis is examined for the various design parameters. After verifying the accuracy of the torque computation of the proposed analysis through the comparisons with 3D-FEA, an 8-pole axial-flux PM machine with double-stator-single-rotor is optimally designed. The performance of the optimized motor are finally verified by 3D-FEA.

Question: How does the proposed analysis reduce the computation time?


The Other Side of the Coin: A Framework for Detecting and Analyzing Web-based Cryptocurrency Mining Campaigns. Mining for crypto currencies is usually performed on high-performance single purpose hardware or GPUs. However, mining can be easily parallelized and distributed over many less powerful systems. Cryptojacking is a new threat on the Internet and describes code included in websites that uses a visitor's CPU to mine for crypto currencies without the their consent. This paper introduces MiningHunter, a novel web crawling framework which is able to detect mining scripts even if they obfuscate their malicious activities. We scanned the Alexa Top 1 million websites for cryptojacking, collected more than 13,400,000 unique JavaScript files with a total size of 246 GB and found that 3,178 websites perform cryptocurrency mining without their visitors' consent. Furthermore, MiningHunter can be used to provide an in-depth analysis of cryptojacking campaigns. To show the feasibility of the proposed framework, three of such campaigns are examined in detail. Our results provide the most comprehensive analysis to date of the spread of cryptojacking on the Internet.

Question: What is a cryptojacking campaign?


SAF: Strategic Alignment Framework for Monitoring Organizations. Reaching a Strategic Alignment is a crucial aspect for any organization. The alignment can be achieved by controlling, through monitoring probes, the coherency of the Business Processes with the related Business Strategy. In this paper we present SAF, a powerful framework for those organizations that aim at a superior business performance and want to keep monitored the organization's alignment. SAF has been applied to a real case study and it has also been compared with GQM Strategy [2] and Process Performance Indicators Monitoring Model [16].

Question: What is a business process?


QuizRDF: search technology for the semantic Web. An information-seeking system is described which combines traditional keyword querying of WWW resources with the ability to browse and query against RDF annotations of those resources. RDF(S) and RDF are used to specify and populate an ontology and the resultant RDF annotations are then indexed along with the full text of the annotated resources. The resultant index allows both keyword querying against the full text of the document and the literal values occurring in the RDF annotations, along with the ability to browse and query the ontology. We motivate our approach as a key enabler for fully exploiting the semantic Web in the area of knowledge management and argue that the ability to combine searching and browsing behaviours more fully supports a typical information-seeking task. The approach is characterised as "low threshold, high ceiling" in the sense that where RDF annotations exist they are exploited for an improved information-seeking experience but where they do not yet exist, a search capability is still available.

Question: What is the canadian armed forces?


Higher-Order Pooling of CNN Features via Kernel Linearization for Action Recognition. Most successful deep learning algorithms for action recognition extend models designed for image-based tasks such as object recognition to video. Such extensions are typically trained for actions on single video frames or very short clips, and then their predictions from sliding-windows over the video sequence are pooled for recognizing the action at the sequence level. Usually this pooling step uses the first-order statistics of frame-level action predictions. In this paper, we explore the advantages of using higherorder correlations, specifically, we introduce Higher-order Kernel (HOK) descriptors generated from the late fusion of CNN classifier scores from all the frames in a sequence. To generate these descriptors, we use the idea of kernel linearization. Specifically, a similarity kernel matrix, which captures the temporal evolution of deep classifier scores, is first linearized into kernel feature maps. The HOK descriptors are then generated from the higher-order cooccurrences of these feature maps, and are then used as input to a video-level classifier. We provide experiments on two fine-grained action recognition datasets, and show that our scheme leads to state-of-the-art results.

Question: What is the difference between first-order and higher-order pooling?


Dual-band bandpass filter using helical resonators. This paper demonstrates non-uniform pitch helical resonators for realization of dual-band bandpass filters. By modifying the pitch and coil diameter of conventional uniform pitch helical resonators, the desired dual-band frequencies can be obtained. The external coupling and inter-resonator coupling structure are also illustrated. A non-uniform pitch helical resonator was designed and fabricated with unloaded quality-factor (>900) for both passbands. A 2nd order Butterworth filter that has passbands at 840 MHz and 2590 MHz has been designed. The simulation results show that the filter has a good selectivity with 6% and 4.3% fractional bandwidth at the passbands, respectively. The good power handling capability also suggests that the filter is applicable for microcell/picocell LTE base stations.

Question: What is a dual-band bandpass filter?


Enhancement and bandwidth compression of noisy speech. Over the past several years there has been considerable attention focused on the problem of enhancement and bandwidth compression of speech degraded by additive background noise. This interest is motivated by several factors including a broad set of important applications, the apparent lack of robustness in current speech-compression systems and the development of several potentially promising and practical solutions. One objective of this paper is to provide an overview of the variety of techniques that have been proposed for enhancement and bandwidth compression of speech degraded by additive background noise. A second objective is to suggest a unifying framework in terms of which the relationships between these systems is more visible and which hopefully provides a structure which will suggest fruitful directions for further research.

Question: What is the unifying framework?


A comparative study of image classification algorithms for Foraminifera identification. Identifying Foraminifera (or forams for short) is essential for oceanographic and geoscience research as well as petroleum exploration. Currently, this is mostly accomplished using trained human pickers, routinely taking weeks or even months to accomplish the task. In this paper, a foram identification pipeline is proposed to automatic identify forams based on computer vision and machine learning techniques. A microscope based image capturing system is used to collect a labelled image data set. Various popular image classification algorithms are adapted to this specific task and evaluated under various conditions. Finally, the potential of a weighted cross-entropy loss function in adjusting the trade-off between precision and recall is tested. The classification algorithms provide competitive results when compared to human experts labeling of the data set.

Question: What is a foram?


An Unsupervised Approach to Recognizing Discourse Relations. We presentan unsupervisedapproachto recognizingdiscourserelationsof CONTRAST, EXPLANATION-EVIDENCE, CONDITION andELABORATION that hold betweenarbitraryspansof texts. We show that discourserelation classifierstrained on examples that are automaticallyextractedfrom massi ve amountsof text can be usedto distinguishbetweensomeof theserelationswith accuraciesashigh as 93%, even whenthe relationsarenot explicitly markedby cuephrases.

Question: What is an unsupervised approach to recognizing discourse relations?


Adaptive fuzzy PID temperature control system based on OPC and modbus/TCP protocol. In this paper, an adaptive fuzzy PID controller is designed to improve the control performance of the resistance furnace, and then is applied to a remote temperature control system based on modbus/TCP industrial Ethernet via OPC communication. The adaptive PID controller is developed by the fuzzy toolbox in Matlab. The data acquisition and devices driving are realized by PCAuto, a SCADA configuration software which is widely used in industry. The data exchange between Matlab and PCAuto is realized by OPC technology. The control process and results verify that the performance of resistance furnace temperature control system is satisfactory and the performance of OPC communication is very efficient and reliable.

Question: What is the temperature control system based on OPC and modbus/TCP protocol?


Graption: A graph-based P2P traffic classification framework for the internet backbone. 1 The authors thank CAIDA for providing this set of traffic traces. Additional information for these traces can be found in the DatCat, Internet Measurement Data Catalog [8], indexed under the label ''PAIX''. 1910 M. Iliofotou et al. / Computer Networks 55 (2011) 1909–1920 behavior. Flow-level and payload-based classification methods require per application training and will thus not detect P2P traffic from emerging protocols. Behavioral-host-based approaches such as BLINC [25] can detect traffic from new protocols [25], but have weak performance when applied at the backbone [26]. In addition, most tools including BLINC [25] require fine-tuning and careful selection of parameters [26]. We discuss the limitations of previous methods in more detail in Section 4. In this paper, we use the network-wide behavior of an application to assist in classifying its traffic. To model this behavior, we use graphs where each node is an IP address, and each edge represents a type of interaction between two nodes. We use the term Traffic Dispersion Graph or TDG to refer to such a graph [19]. Intuitively, with TDGs we enable the detection of network-wide behavior (e.g., highly connected graphs) that is common among P2P applications and different from other traffic (e.g., Web). While we recognize that some previous efforts [6,9] have used graphs to detect worm activity, they have not explored the full capabilities of TDGs for application classification. This paper is an extension of a workshop paper [18] and the differences will be clarified in the related work section (Section 4). We propose a classification framework, dubbed Graption (Graph-based classification), as a systematic way to combine network-wide behavior and flow-level characteristics of network applications. Graption first groups flows using flow-level features, in an unsupervised and agnostic way, i.e., without using application-spec

Question: What is the difference between a graph-based and a flow-based classification?


A Controlled Pilot-Outcome Study of Sensory Integration ( SI ) in the Treatment of Complex Adaptation to Traumatic Stress. This study tested whether sensory integration (SI) treatment combined with psychotherapy would improve symptom outcome over psychotherapy alone in the treatment of complex posttraumatic stress, as measured by the Disorders of Extreme Stress Not Otherwise Specified (DESNOS) clinical construct in a group of 10 adult patients with histories of childhood abuse. DESNOS symptoms were assessed at three time periods (T1, baseline; T2, after experimental group SI treatment; and T3, after wait-list control group SI treatment) using the Structured Interview for Disorders of Extreme Stress (SIDES). The Sensory Learning Program (SLP), developed by the Sensory Learning Institute of Boulder, Colorado, was used as the SI treatment modality. Results indicated significant differential improvement for the group treated with SLP in SIDES Total Score (T1/T2 and T2/T3), Self Perception (T1/T2 and T2/T3), Affect Regulation (T2/T3), and Alterations in Meaning (T1/T2).

Question: What is the difference between the Sensory Learning Program and the Sensory Integration Treatment?


Facebook, Twitter and Google Plus for Breaking News: Is There a Winner?. Twitter is widely seen as being the go to place for breaking news. Recently however, competing Social Media have begun to carry news. Here we examine how Facebook, Google Plus and Twitter report on breaking news. We consider coverage (whether news events are reported) and latency (the time when they are reported). Using data drawn from three weeks in December 2013, we identify 29 major news events, ranging from celebrity deaths, plague outbreaks to sports events. We find that all media carry the same major events, but Twitter continues to be the preferred medium for breaking news, almost consistently leading Facebook or Google Plus. Facebook and Google Plus largely repost newswire stories and their main research value is that they conveniently package multitple sources of information together.

Question: How do facebook, twitter and google plus report on breaking news?


Road traffic sign detection and classification. A vision-based vehicle guidance system for road vehicles can have three main roles: 1) road detection; 2) obstacle detection; and 3) sign recognition. The first two have been studied for many years and with many good results, but traffi c sign recognition is a less-studied field. Traffi c signs provide drivers with very valuable informatio n about the road, in order to make drivin g safer and easier. We think that traffi c signs must play the same role for autonomous vehicles. They are designed to be easily recognized by human driver s mainly because their color and shapes are very different from natural environments. The algorithm described in this paper takes advantage of these features. I t has two main parts. The first one, for the detection, uses color thresholding to segment the image and shape analysis to detect the signs. The second one, for the classification, uses a neural network. Some results from natural scenes are shown. On the other hand, the algorithm is valid to detect other kinds of marks that would tell the mobile robot to perform some task at that place.

Question: How to detect traffic signs?


The Acquisition , Transfer , and Depreciation of Knowledge in Service Organizations : Productivity in Franchises. Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at . http://www.jstor.org/page/info/about/policies/terms.jsp. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use.

Question: What is the difference between JSTOR and JSTOR archive?


A CNN-based segmentation model for segmenting foreground by a probability map. This paper proposes a CNN-based segmentation model to segment foreground from an image and a prior probability map. Our model is constructed based on the FCN model that we simply replace the original RGB-based three channel input layer by a four channel, i.e., RGB and prior probability map. We then train the model by constructing various image, prior probability maps and the groundtruths from the PASCAL VOC dataset, and finally obtain a CNN-based foreground segmentation model that is suitable for general images. Our proposed method is motivated by the observation that the classical graphcut algorithm using GMM for modeling the priors can not capture the semantic segmentation from the prior probability, and thus leads to low segmentation performance. Furthermore, the efficient FCN segmentation model is for specific objects rather than general objects. We therefore improve the graph-cut like foreground segmentation by extending FCN segmentation model. We verify the proposed model by various prior probability maps such as artifical maps, saliency maps, and discriminative maps. The ICoseg dataset that is different from the PASCAL Voc dataset is used for the verification. Experimental results demonstrates the fact that our method obviously outperforms the graphcut algorithms and FCN models.

Question: What is the difference between the PASCAL VOC dataset and the ICoseg dataset?


The Coherent Heart Heart – Brain Interactions , Psychophysiological Coherence , and the Emergence of System-Wide Order. This article presents theory and research on the scientific study of emotion that emphasizes the importance of coherence as an optimal psychophysiological state. A dynamic systems view of the interrelations between psychological, cognitive and emotional systems and neural communication networks in the human organism provides a foundation for the view presented. These communication networks are examined from an information processing perspective and reveal a fundamental order in heart-brain interactions and a harmonious synchronization of physiological systems associated with positive emotions. The concept of coherence is drawn on to understand optimal functioning which is naturally reflected in the heart's rhythmic patterns. Research is presented identifying various psychophysiological states linked to these patterns, with neurocardiological coherence emerging as having significant impacts on well being. These include psychophysiological as well as improved cognitive performance. From this, the central role of the heart is explored in terms of biochemical, biophysical and energetic interactions. Appendices provide further details and research on; psychophysiological functioning, reference previous research in this area, details on research linking coherence with optimal cognitive performance, heart brain synchronization and the energetic signature of the various psychophysiological modes.

Question: What is the role of the heart in the brain?


High-Resistivity SOI CMOS Cellular Antenna Switches. Results for cellular antenna switches using highresistivity silicon-on-insulator (SOI) CMOS technology are presented. The performance of SOI RF switch FETs is presented and compared to a production GaAs pHEMT technology. Data from prototype high-resistivity SOI RF switch designs is presented and compared to pHEMT based designs. Index Terms — RF CMOS, SOI, silicon-on-insulator, RF SOI, cellular switch, signal isolation

Question: What is the performance of high-resistivity SOI CMOS cellular antenna switches?


The urgency for effective user privacy-education to counter social engineering attacks on secure computer systems. Trusted people can fail to be trustworthy when it comes to protecting their aperture of access to secure computer systems due to inadequate education, negligence, and various social pressures. People are often the weakest link in an otherwise secure computer system and, consequently, are targeted for social engineering attacks. Social Engineering is a technique used by hackers or other attackers to gain access to information technology systems by getting the needed information (for example, a username and password) from a person rather than breaking into the system through electronic or algorithmic hacking methods. Such attacks can occur on both a physical and psychological level. The physical setting for these attacks occurs where a victim feels secure: often the workplace, the phone, the trash, and even on-line. Psychology is often used to create a rushed or officious ambiance that helps the social engineer to cajole information about accessing the system from an employee.  Data privacy legislation in the United States and international countries that imposes privacy standards and fines for negligent or willful non-compliance increases the urgency to measure the trustworthiness of people and systems. One metric for determining compliance is to simulate, by audit, a social engineering attack upon an organization required to follow data privacy standards. Such an organization commits to protect the confidentiality of personal data with which it is entrusted.  This paper presents the results of an approved social engineering audit made without notice within an organization where data security is a concern. Areas emphasized include experiences between the Social Engineer and the audited users, techniques used by the Social Engineer, and other findings from the audit. Possible steps to mitigate exposure to the dangers of Social Engineering through improved

Question: What is social engineering?


Implantable Myoelectric Sensors (IMESs) for Intramuscular Electromyogram Recording. We have developed a multichannel electrogmyography sensor system capable of receiving and processing signals from up to 32 implanted myoelectric sensors (IMES). The appeal of implanted sensors for myoelectric control is that electromyography (EMG) signals can be measured at their source providing relatively cross-talk-free signals that can be treated as independent control sites. An external telemetry controller receives telemetry sent over a transcutaneous magnetic link by the implanted electrodes. The same link provides power and commands to the implanted electrodes. Wireless telemetry of EMG signals from sensors implanted in the residual musculature eliminates the problems associated with percutaneous wires, such as infection, breakage, and marsupialization. Each implantable sensor consists of a custom-designed application-specified integrated circuit that is packaged into a biocompatible RF BION capsule from the Alfred E. Mann Foundation. Implants are designed for permanent long-term implantation with no servicing requirements. We have a fully operational system. The system has been tested in animals. Implants have been chronically implanted in the legs of three cats and are still completely operational four months after implantation.

Question: What is the appeal of implanted sensors for myoelectric control?


Warm-white light-emitting diode with yellowish orange SiALON ceramic phosphor.. A warm-white light-emitting diode (LED) without blending of different kinds of phosphors is demonstrated. An approach that consists of a blue LED chip and a wavelength-conversion phosphor is carried out. The phosphor is a newly developed yellowish orange CaEuSiAlON ceramic phosphor with high efficiency. The CIE1931 chromaticity coordinates (x, y) are (0.458, 0.414), the color temperature is 2750 K, and the luminous efficacy of this LED is 25.9 lm/W at room temperature and with a forward-bias current of 20 mA. The chromaticity of the assembled LED is more thermally stable than that of a LED with a conventional oxide phosphor (YAG:Ce) because of the better thermal stability of the oxynitride phosphor.

Question: What is the color temperature of this LED?


Advantages of thesaurus representation using the Simple Knowledge Organization System (SKOS) compared with proposed alternatives. The concept of thesaurus has evolved from a list of conceptually interrelated words to today's controlled vocabularies, where terms form complex structures through semantic relationships. This term comes from the Latin and has turn been derived from the Greek "θησαυρός", which means treasury according to the Spanish Royal Academy, in whose dictionary it is also defined as: 'name given by its authors to certain dictionaries, catalogues and anthologies'. The increase in scientific communication and productivity made it essential to develop keyword indexing systems. At that time, Howerton spoke of controlled lists to refer to concepts that were heuristically or intuitively related. According to Roberts (1984), Mooers was the first to relate thesauri to information retrieval systems; Taube established the foundations of post-coordination, while Luhn dealt, at a basic level, with the creation of thesauri using automatic techniques. Brownson (1957) was the first to use the term to refer to the issue of translating concepts and their relationships expressed in documents into a more precise language free of ambiguities in order to facilitate information retrieval. The ASTIA Thesaurus was published in the early 1960s (Currás, 2005), already bearing the characteristics of today's thesauri and taking on the need for a tool to administer a controlled vocabulary in terms of indexing, thereby giving rise to the concept of documentary language.

Question: What is thesaurus?


High power and high efficiency GaN-HEMT for microwave communication applications. Microwaves have been widely used for the modern communication systems, which have advantages in high bit rate transmission and the easiness of compact circuit and antenna design. Gallium Nitride (GaN), featured with high breakdown and high saturation velocity, is one of the promising material for high power and high frequency devices, and a kW-class output power has already been achieved [1]. We have developed the high power and high efficiency GaN HEMTs [2–5], targeting the amplifier for the base transceiver station (BTS). This presentation summarizes our recent works, focusing on the developments for the efficiency boosting and the robustness in high power RF operation.

Question: What is the power of the gallium nitride?


From ADHD to SAD: Analyzing the Language of Mental Health on Twitter through Self-Reported Diagnoses. Many significant challenges exist for the mental health field, but one in particular is a lack of data available to guide research. Language provides a natural lens for studying mental health – much existing work and therapy have strong linguistic components, so the creation of a large, varied, language-centric dataset could provide significant grist for the field of mental health research. We examine a broad range of mental health conditions in Twitter data by identifying self-reported statements of diagnosis. We systematically explore language differences between ten conditions with respect to the general population, and to each other. Our aim is to provide guidance and a roadmap for where deeper exploration is likely to be fruitful.

Question: What is the difference between ADHD and SAD?


Assigning bug reports using a vocabulary-based expertise model of developers. For popular software systems, the number of daily submitted bug reports is high. Triaging these incoming reports is a time consuming task. Part of the bug triage is the assignment of a report to a developer with the appropriate expertise. In this paper, we present an approach to automatically suggest developers who have the appropriate expertise for handling a bug report. We model developer expertise using the vocabulary found in their source code contributions and compare this vocabulary to the vocabulary of bug reports. We evaluate our approach by comparing the suggested experts to the persons who eventually worked on the bug. Using eight years of Eclipse development as a case study, we achieve 33.6% top-1 precision and 71.0% top-10 recall.

Question: How to assign bug reports to developers?


Hybrid crafting: towards an integrated practice of crafting with physical and digital components. With current digital technologies, people have large archives of digital media, such as images and audio files, but there are only limited means to include these media in creative practices of crafting and making. Nevertheless, studies have shown that crafting with digital media often makes these media more cherished and that people enjoy being creative with their digital media. This paper aims to open up the way for novel means for crafting, which include digital media in integrations with physical construction, here called 'hybrid crafting'. Notions of hybrid crafting were explored to inform the design of products or systems that may support these new crafting practices. We designed 'Materialise'—a building set that allows for the inclusion of digital images and audio files in physical constructions by using tangible building blocks that can display images or play audio files, alongside a variety of other physical components—and used this set in four hands-on creative workshops to gain insight into how people go about doing hybrid crafting; whether hybrid crafting is desirable; what the characteristics of hybrid crafting are; and how we may design to support these practices. By reflecting on the findings from these workshops, we provide concrete guidelines for the design of novel hybrid crafting products or systems that address craft context, process and result. We aim to open up the design space to designing for hybrid crafting because these new practices provide interesting new challenges and opportunities for future crafting that can lead to novel forms of creative expression.

Question: What is the design of a building set?


Finasteride for the treatment of hidradenitis suppurativa in children and adolescents.. IMPORTANCE Hidradenitis suppurativa (HS) is a chronic debilitating cutaneous disease for which there is no universally effective treatment. Patients typically present at puberty with tender subcutaneous nodules that can progress to dermal abscess formation. Antiandrogens have been used in the treatment of HS, and studies have primarily focused on adult patients.   OBSERVATIONS We present a case series of 3 pediatric patients with HS who were successfully treated with oral finasteride, resulting in decreased frequency and severity of disease flares with no significant adverse effects.   CONCLUSIONS AND RELEVANCE Finasteride is a therapeutic option that provides benefit for pediatric patients with HS. Further prospective data and randomized controlled studies will provide helpful information in the management of this disease.

Question: What is the treatment for hidradenitis suppurativa?


Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition. Recurrent Neural Networks (RNNs) and their variants, such as Long-Short Term Memory (LSTM) networks, and Gated Recurrent Unit (GRU) networks, have achieved promising performance in sequential data modeling. The hidden layers in RNNs can be regarded as the memory units, which are helpful in storing information in sequential contexts. However, when dealing with high dimensional input data, such as video and text, the input-to-hidden linear transformation in RNNs brings high memory usage and huge computational cost. This makes the training of RNNs very difficult. To address this challenge, we propose a novel compact LSTM model, named as TR-LSTM, by utilizing the low-rank tensor ring decomposition (TRD) to reformulate the input-to-hidden transformation. Compared with other tensor decomposition methods, TRLSTM is more stable. In addition, TR-LSTM can complete an end-to-end training and also provide a fundamental building block for RNNs in handling large input data. Experiments on real-world action recognition datasets have demonstrated the promising performance of the proposed TR-LSTM compared with the tensortrain LSTM and other state-of-the-art competitors.

Question: What is the tensor ring decomposition?


Better Key Sizes (and Attacks) for LWE-Based Encryption. We analyze the concrete security and key sizes of theoretically sound lattice-based encryption schemes based on the "learning with errors" (LWE) problem. Our main contributions are: (1) a new lattice attack on LWE that combines basis reduction with an enumeration algorithm admitting a time/success tradeoff, which performs better than the simple distinguishing attack considered in prior analyses; (2) concrete parameters and security estimates for an LWE-based cryptosystem that is more compact and efficient than the well-known schemes from the literature. Our new key sizes are up to 10 times smaller than prior examples, while providing even stronger concrete security levels.

Question: What is the concrete security of LWE-based encryption?


MC-HOG Correlation Tracking with Saliency Proposal. Designing effective feature and handling the model drift problem are two important aspects for online visual tracking. For feature representation, gradient and color features are most widely used, but how to effectively combine them for visual tracking is still an open problem. In this paper, we propose a rich feature descriptor, MC-HOG, by leveraging rich gradient information across multiple color channels or spaces. Then MC-HOG features are embedded into the correlation tracking framework to estimate the state of the target. For handling the model drift problem caused by occlusion or distracter, we propose saliency proposals as prior information to provide candidates and reduce background interference. In addition to saliency proposals, a ranking strategy is proposed to determine the importance of these proposals by exploiting the learnt appearance filter, historical preserved object samples and the distracting proposals. In this way, the proposed approach could effectively explore the color-gradient characteristics and alleviate the model drift problem. Extensive evaluations performed on the benchmark dataset show the superiority of the proposed method.

Question: How to effectively combine gradient and color features for visual tracking?


Major life changes and behavioral markers in social media: case of childbirth. We explore the harnessing of social media as a window on changes around major life events in individuals and larger populations. We specifically examine patterns of activity, emotional, and linguistic correlates for childbirth and postnatal course. After identifying childbirth events on Twitter, we analyze daily posting patterns and language usage before and after birth by new mothers, and make inferences about the status and dynamics of changes in emotions expressed following childbirth. We find that childbirth is associated with some changes for most new mothers, but approximately 15% of new mothers show significant changes in their online activity and emotional expression postpartum. We observe that these mothers can be distinguished by linguistic changes captured by shifts in a relatively small number of words in their social media posts. We introduce a greedy differencing procedure to identify the type of language that characterizes significant changes in these mothers during postpartum. We conclude with a discussion about how such characterizations might be applied to recognizing and understanding health and well-being in women following childbirth.

Question: What is the difference between a greedy differencing procedure and a regular differencing procedure?


PFC Cuk Converter-Fed BLDC Motor Drive. This paper deals with a power factor correction (PFC)-based Cuk converter-fed brushless dc motor (BLDC) drive as a cost-effective solution for low-power applications. The speed of the BLDC motor is controlled by varying the dc-bus voltage of a voltage source inverter (VSI) which uses a low frequency switching of VSI (electronic commutation of the BLDC motor) for low switching losses. A diode bridge rectifier followed by a Cuk converter working in a discontinuous conduction mode (DCM) is used for control of dc-link voltage with unity power factor at ac mains. Performance of the PFC Cuk converter is evaluated under four different operating conditions of discontinuous and continuous conduction modes (CCM) and a comparison is made to select a best suited mode of operation. The performance of the proposed system is simulated in a MATLAB/Simulink environment and a hardware prototype of the proposed drive is developed to validate its performance over a wide range of speed with unity power factor at ac mains.

Question: How does a PFC converter work?


Optimizing Space-Air-Ground Integrated Networks by Artificial Intelligence. It is widely acknowledged that the development of traditional terrestrial communication technologies cannot provide all users with fair and high quality services due to the scarce network resource and limited coverage areas. To complement the terrestrial connection, especially for users in rural, disasterstricken, or other difficult-to-serve areas, satellites, unmanned aerial vehicles (UAVs), and balloons have been utilized to relay the communication signals. On the basis, Space-Air-Ground Integrated Networks (SAGINs) have been proposed to improve the users' Quality of Experience (QoE). However, compared with existing networks such as ad hoc networks and cellular networks, the SAGINs are much more complex due to the various characteristics of three network segments. To improve the performance of SAGINs, researchers are facing many unprecedented challenges. In this paper, we propose the Artificial Intelligence (AI) technique to optimize the SAGINs, as the AI technique has shown its predominant advantages in many applications. We first analyze several main challenges of SAGINs and explain how these problems can be solved by AI. Then, we consider the satellite traffic balance as an example and propose a deep learning based method to improve the traffic control performance. Simulation results evaluate that the deep learning technique can be an efficient tool to improve the performance of SAGINs.

Question: How to optimize the SAGINs?


Toward machines that behave ethically better than humans do. With the increasing dependence on autonomous operating agents and robots the need for ethical machine behavior rises. This paper presents a moral reasoner that combines connectionism, utilitarianism and ethical theory about moral duties. The moral decision-making matches the analysis of expert ethicists in the health domain. This may be useful in many applications, especially where machines interact with humans in a medical context. Additionally, when connected to a cognitive model of emotional intelligence and affective decision making, it can be explored how moral decision making impacts affective behavior.

Question: What is the difference between a moral reasoner and a moral agent?


Immediate effect of a slow pace breathing exercise Bhramari pranayama on blood pressure and heart rate.. The study was carried out to evaluate the immediate effect Bhramari pranayama, a slow breathing exercise for 5 minutes on heart rate and blood pressure. Heart rate and blood pressure of volunteers were recorded. The subject was directed to inhale slowly up to the maximum for about 5 seconds and then to exhale slowly up to the maximum for about 15 sec keeping two thumbs on two external auditory canal, index and middle finger together on two closed eyes and ring finger on the two sides of the nose. During exhalation the subject must chant the word "O-U-Mmmma" with a humming nasal sound mimicking the sound of a humming wasp, so that the laryngeal walls and the inner walls of the nostril mildly vibrate (Bhramari pranayama, respiratory rate 3/min). After 5 minutes of this exercise, the blood pressure and heart rate were recorded again. Both the systolic and diastolic blood pressure were found to be'decreased with a slight fall in heart rate. Fall of diastolic pressure and mean pressure were significant. The result indicated that slow pace Bhramari pranayama for 5 minutes, induced parasympathetic dominance on cardiovascular system.

Question: What is the effect of Bhramari pranayama on blood pressure and heart rate?


PostBL: Post-mesh Boundary Layer Mesh Generation Tool. A boundary layer mesh is a mesh with dense element distribution in the normal direction along specific boundaries. PostBL is a utility to generate boundary layers elements on an already existing mesh model. PostBL supports creation of hexahedral, prism, quad and tri boundary layer elements. It is a part of MeshKit, which is an open-source library for mesh generation functionalities. Generally, boundary layer mesh generation is a pre-meshing process; in this effort, we start from a model that has already been meshed. Boundary layers elements can be generated along the entire skin, selected exterior or internal surface boundaries. MeshKit uses graph-based approach for representing meshing operations; PostBL is one such meshing operation. It can be coupled to other meshing operations like Jaal, NetGen, TetGen, CAMAL and custom meshing tools like RGG. Simple examples demonstrating generation of boundary layers on different mesh types and OECD Vattenfall T-Junction benchmark hexahedral-mesh are presented.

Question: How to generate boundary layer mesh?


Liquids permeation into HTV silicone rubber under AC/DC electric field. As shed and sheath materials, high temperature vulcanization (HTV) silicone rubber suffers from various types of environmental stresses in actual use. Liquids permeation, as a kind of silicone rubber aging factor, has been investigated by many researchers. However, most of the studies are conducted under the condition of no electric field. Since that composite insulators, especially the high voltage (HV) side, are under high electric field, it is worthy of attention on liquids permeation under AC/DC voltages. In this study, we utilized a new-designed liquids permeation test unit under AC/DC electric field to measure the weight of HTV silicone rubber specimens during the test process. Deionized water, as well as basic fuchsine ethanol solutions were used to verify the effects of electric field on liquids permeation. Besides, the influence of ATH content on the liquids permeation was involved.

Question: How to measure the weight of HTV silicone rubber specimens?


An image encryption scheme based on elliptic curve pseudo random and Advanced Encryption System. Elliptic curve cryptography (ECC) has proven to be an effective cryptography. ECC has its own advantages such as efficient key size compared to other public key infrastructures. This paper exploits the Elliptic curve random generator defined by National Institute of Standards and Technology (NIST) to generate a sequence of arbitrary numbers based on curves. The random generation phase is based on public shared key and a changing point G, which is a generator of a curve to obtain random sequences. Then, Advanced Encryption System is applied to these sequences acquiring arbitrary keys for encrypting image. Using AES alongside well distributed randoms provides a prominent encryption technique. Our experiments show that the proposed method fulfills the basics of cryptography including simpleness and correctness. Moreover, the results of the evaluation prove the effectiveness and security of the proposed method.

Question: What is the elliptic curve cryptography?


A new class of upper bounds on the log partition function. We introduce a new class of upper bounds on the log partition function of a Markov random field (MRF). This quantity plays an important role in various contexts, including approximating marginal distributions, parameter estimation, combinatorial enumeration, statistical decision theory, and large-deviations bounds. Our derivation is based on concepts from convex duality and information geometry: in particular, it exploits mixtures of distributions in the exponential domain, and the Legendre mapping between exponential and mean parameters. In the special case of convex combinations of tree-structured distributions, we obtain a family of variational problems, similar to the Bethe variational problem, but distinguished by the following desirable properties: i) they are convex, and have a unique global optimum; and ii) the optimum gives an upper bound on the log partition function. This optimum is defined by stationary conditions very similar to those defining fixed points of the sum-product algorithm, or more generally, any local optimum of the Bethe variational problem. As with sum-product fixed points, the elements of the optimizing argument can be used as approximations to the marginals of the original model. The analysis extends naturally to convex combinations of hypertree-structured distributions, thereby establishing links to Kikuchi approximations and variants.

Question: What is the log partition function?


Generating Single Subject Activity Videos as a Sequence of Actions Using 3D Convolutional Generative Adversarial Networks. Humans have the remarkable ability of imagination, where within the human mind virtual simulations are done of scenarios whether visual, auditory or any other senses. These imaginations are based on the experiences during interaction with the real world, where human senses help the mind understand their surroundings. Such level of imagination has not yet been achieved using current algorithms, but a current trend in deep learning architectures known as Generative Adversarial Networks (GANs) have proven capable of generating new and interesting images or videos based on the training data. In that way, GANs can be used to mimic human imagination, where the resulting generated visuals of GANs are based on the data used during training. In this paper, we use a combination of Long Short-Term Memory (LSTM) Networks and 3D GANs to generate videos. We use a 3D Convolutional GAN to generate new human action videos based on trained data. The generated human action videos are used to generate longer videos consisting of a sequence of short actions combined creating longer and more complex activities. To generate the sequence of actions needed we use an LSTM network to translate a simple input description text into the required sequence of actions. The generated chunks are then concatenated using a motion interpolation scheme to form a single video consisting of many generated actions. Hence a visualization of the input text description is generated as a video of a subject performing the activity described.

Question: How to generate a video of a subject performing an activity described in a text?


Effective Bug Triage Based on Historical Bug-Fix Information. For complex and popular software, project teams could receive a large number of bug reports. It is often tedious and costly to manually assign these bug reports to developers who have the expertise to fix the bugs. Many bug triage techniques have been proposed to automate this process. In this paper, we describe our study on applying conventional bug triage techniques to projects of different sizes. We find that the effectiveness of a bug triage technique largely depends on the size of a project team (measured in terms of the number of developers). The conventional bug triage methods become less effective when the number of developers increases. To further improve the effectiveness of bug triage for large projects, we propose a novel recommendation method called Bug Fixer, which recommends developers for a new bug report based on historical bug-fix information. Bug Fixer constructs a Developer-Component-Bug (DCB) network, which models the relationship between developers and source code components, as well as the relationship between the components and their associated bugs. A DCB network captures the knowledge of "who fixed what, where". For a new bug report, Bug Fixer uses a DCB network to recommend to triager a list of suitable developers who could fix this bug. We evaluate Bug Fixer on three large-scale open source projects and two smaller industrial projects. The experimental results show that the proposed method outperforms the existing methods for large projects and achieves comparable performance for small projects.

Question: What is the effectiveness of bug triage for large projects?


Improving Matching Models with Contextualized Word Representations for Multi-turn Response Selection in Retrieval-based Chatbots. We consider matching with pre-trained contextualized word vectors for multi-turn response selection in retrieval-based chatbots. When directly applied to the task, state-ofthe-art models, such as CoVe and ELMo, do not work as well as they do on other tasks, due to the hierarchical nature, casual language, and domain-specific word use of conversations. To tackle the challenges, we propose pre-training a sentence-level and a sessionlevel contextualized word vectors by learning a dialogue generation model from large-scale human-human conversations with a hierarchical encoder-decoder architecture. The two levels of vectors are then integrated into the input layer and the output layer of a matching model respectively. Experimental results on two benchmark datasets indicate that the proposed contextualized word vectors can significantly and consistently improve the performance of existing matching models for response selection.

Question: How do we improve the performance of matching models for response selection in retrieval-based chatbots?


Ancient Kaṭapayādi System Sanskrit Encryption Technique Unified. Computers today, generate enormous amount of data/information with each moment passing by. With the production of such huge amount of information comes its indispensable part of information security. Encryption Algorithms today drastically increase the file size. Hence the secure transmission of data requires extra bandwidth. Here in this paper we propose a system AKS - SETU, which is also the abbreviation to the title of this paper. Using the ancient technique of encryption from Sanskrit, AKS - SETU not only encrypts the information but also attempts on decreasing of the file size. AKS - SETU performs Sanskrit encryption, which we propose to be termed as Sanscryption.

Question: What is the title of the paper?


A Novel Economic Sharing Model in a Federation of Selfish Cloud Providers. This paper presents a novel economic model to regulate capacity sharing in a federation of hybrid cloud providers (CPs). The proposed work models the interactions among the CPs as a repeated game among selfish players that aim at maximizing their profit by selling their unused capacity in the spot market but are uncertain of future workload fluctuations. The proposed work first establishes that the uncertainty in future revenue can act as a participation incentive to sharing in the repeated game. We, then, demonstrate how an efficient sharing strategy can be obtained via solving a simple dynamic programming problem. The obtained strategy is a simple update rule that depends only on the current workloads and a single variable summarizing past interactions. In contrast to existing approaches, the model incorporates historical and expected future revenue as part of the virtual machine (VM) sharing decision. Moreover, these decisions are not enforced neither by a centralized broker nor by predefined agreements. Rather, the proposed model employs a simple grim trigger strategy where a CP is threatened by the elimination of future VM hosting by other CPs. Simulation results demonstrate the performance of the proposed model in terms of the increased profit and the reduction in the variance in the spot market VM availability and prices.

Question: What is the difference between a federation of cloud providers and a federation of cloud providers?


Tibial periosteal ganglion cyst: The ganglion in disguise. Soft tissue ganglions are commonly encountered cystic lesions around the wrist presumed to arise from myxomatous degeneration of periarticular connective tissue. Lesions with similar pathology in subchondral location close to joints, and often simulating a geode, is the less common entity called intraosseous ganglion. Rarer still is a lesion produced by mucoid degeneration and cyst formation of the periostium of long bones, rightly called the periosteal ganglion. They are mostly found in the lower extremities at the region of pes anserinus, typically limited to the periosteum and outer cortex without any intramedullary component. We report the case of a 62 year-old male who presented with a tender swelling on the mid shaft of the left tibia, which radiologically suggested a juxtacortical lesion extending to the soft tissue or a soft tissue neoplasm eroding the bony cortex of tibia. It was later diagnosed definitively as a periosteal ganglion in an atypical location, on further radiologic work-up and histopathological correlation.

Question: What is a periosteal ganglion?


Social Capital and Knowledge Integration in Digitally Enabled Teams. T understand the impact of social capital on knowledge integration and performance within digitally enabled teams, we studied 46 teams who had a history and a future working together. All three dimensions of their social capital (structural, relational, and cognitive) were measured prior to the team performing two tasks in a controlled setting, one face-to-face and the other through a lean digital network. Structural and cognitive capital were more important to knowledge integration when teams communicated through lean digital networks than when they communicated face-to-face; relational capital directly impacted knowledge integration equally, regardless of the communication media used by the team. Knowledge integration, in turn, impacted team decision quality, suggesting that social capital influences team performance in part by increasing a team's ability to integrate knowledge. These results suggest that team history may be necessary but not sufficient for teams to overcome the problems with the use of lean digital networks as a communication environment. However, team history may present a window of opportunity for social capital to develop, which in turn allows teams to perform just as well as in either communication environment.

Question: What is the impact of social capital on knowledge integration?


Fast and Accurate Closest Point Search on Triangulated Surfaces and its Application to Head Motion Estimation. The Iterative Closest Point (ICP) algorithm is widely used to register two roughly aligned surfaces. Its most expensive step is the search for the closest point. Many efficient variants have been proposed to speed up this step, however they do not guarantee that the closest point on a triangulated surface is found. Instead they might result in an approximation of the closest point. In this paper we present a method for the closest point search that is fast and exact. The method was implemented and used to evaluate the accuracy of head motion estimation using dense 3D data obtained from a stereo camera system. The results show that the accuracy of the estimated head motion is better than 1 mm for translational movements and better than 1 degree for rotations. Key-Words: Iterative Closest Point, 3D Registration, Stereo, Head Motion Estimation

Question: How accurate is the closest point search?


Selective separation of virgin and post-consumer polymers (PET and PVC) by flotation method.. More and more polymer wastes are generated by industry and householders today. Recycling is an important process to reduce the amount of waste resulting from human activities. Currently, recycling technologies use relatively homogeneous polymers because hand-sorting waste is costly. Many promising technologies are being investigated for separating mixed thermoplastics, but they are still uneconomical and unreliable. At present, most waste polymers cause serious environmental problems. Burning polymers for recycling is not practiced since poisonous gases are released during the burning process. Particularly, polyvinyl chloride (PVC) materials among waste polymers generate hazardous HCl gas, dioxins containing Cl, etc., which lead to air pollution and shorten the life of the incinerator. In addition, they make other polymers difficult to recycle. Both polyethylene terephthalate (PET) and PVC have densities of 1.30-1.35g /cm(3) and cannot be separated using conventional gravity separation techniques. For this reason, polymer recycling needs new techniques. Among these techniques, froth flotation, which is also used in mineral processing, can be useful because of its low cost and simplicity. The main objective of this research is to recycle PET and PVC selectively from post-consumer polymer wastes and virgin polymers by using froth flotation. According to the results, all PVC particles were floated with 98.8% efficiency in virgin polymer separation while PET particles were obtained with 99.7% purity and 57.0% efficiency in post-consumer polymer separation.

Question: What is the difference between virgin and post-consumer polymers?


Novelty and redundancy detection in adaptive filtering. This paper addresses the problem of extending an adaptive information filtering system to make decisions about the novelty and redundancy of relevant documents. It argues that relevance and redundance should each be modelled explicitly and separately. A set of five redundancy measures are proposed and evaluated in experiments with and without redundancy thresholds. The experimental results demonstrate that the cosine similarity metric and a redundancy measure based on a mixture of language models are both effective for identifying redundant documents.

Question: What is the difference between novelty and redundancy?


A 3 ppm 1.5 × 0.8 mm 2 1.0 µA 32.768 kHz MEMS-Based Oscillator. This paper describes the first 32 kHz low-power MEMS-based oscillator in production. The primary goal is to provide a small form-factor oscillator (1.5 × 0.8 mm 2 ) for use as a crystal replacement in space-constrained mobile devices. The oscillator generates an output frequency of 32.768 kHz and its binary divisors down to 1 Hz. The frequency stability over the industrial temperature range (-40 °C to 85 °C) is ±100 ppm as an oscillator (XO) or ±3 ppm with optional calibration as a temperature compensated oscillator (TCXO). Supply currents are 0.9 μA for the XO and 1.0 μA for the TCXO at supply voltages from 1.4 V to 4.5 V. The MEMS resonator is a capacitively-transduced tuning fork at 524 kHz. The circuitry is fabricated in 180 nm CMOS and includes low power sustaining circuit, fractional-N PLL, temperature sensor, digital control, and low swing driver.

Question: What is a 32 kHz oscillator?


Sex similarities and differences in preferences for short-term mates: what, whether, and why.. Are there sex differences in criteria for sexual relationships? The answer depends on what question a researcher asks. Data suggest that, whereas the sexes differ in whether they will enter short-term sexual relationships, they are more similar in what they prioritize in partners for such relationships. However, additional data and context of other findings and theory suggest different underlying reasons. In Studies 1 and 2, men and women were given varying "mate budgets" to design short-term mates and were asked whether they would actually mate with constructed partners. Study 3 used a mate-screening paradigm. Whereas women have been found to prioritize status in long-term mates, they instead (like men) prioritize physical attractiveness much like an economic necessity in short-term mates. Both sexes also show evidence of favoring well-rounded long- and short-term mates when given the chance. In Studies 4 and 5, participants report reasons for having casual sex and what they find physically attractive. For women, results generally support a good genes account of short-term mating, as per strategic pluralism theory (S. W. Gangestad & J. A. Simpson, 2000). Discussion addresses broader theoretical implications for mate preference, and the link between method and theory in examining social decision processes.

Question: What are the sex similarities and differences in preferences for short-term mates?


Modeling, Analysis and Testing of Autonomous Operation of an Inverter-Based Microgrid. The analysis of the small-signal stability of conventional power systems is well established, but for inverter based microgrids there is a need to establish how circuit and control features give rise to particular oscillatory modes and which of these have poor damping. This paper develops the modeling and analysis of autonomous operation of inverter-based microgrids. Each sub-module is modeled in state-space form and all are combined together on a common reference frame. The model captures the detail of the control loops of the inverter but not the switching action. Some inverter modes are found at relatively high frequency and so a full dynamic model of the network (rather than an algebraic impedance model) is used. The complete model is linearized around an operating point and the resulting system matrix is used to derive the eigenvalues. The eigenvalues (termed "modes") indicate the frequency and damping of oscillatory components in the transient response. A sensitivity analysis is also presented which helps identifying the origin of each of the modes and identify possible feedback signals for design of controllers to improve the system stability. With experience it is possible to simplify the model (reduce the order) if particular modes are not of interest as is the case with synchronous machine models. Experimental results from a microgrid of three 10-kW inverters are used to verify the results obtained from the model

Question: What is a microgrid?


Sensor observation streams within cloud-based IoT platforms: Challenges and directions. Observation streams can be considered as a special case of data streams produced by sensors. With the growth of the Internet of Things (IoT), more and more connected sensors will produce unbounded observation streams. In order to bridge the gap between sensors and observation consumers, we have witnessed the design and the development of Cloud-based IoT platforms. Such systems raise new research challenges, in particular regarding observation collection, processing and consumption. These new research challenges are related to observation streams and should be addressed from the implementation phase by developers to build platforms able to meet other non-functional requirements later. Unlike existing surveys, this paper is intended for developers that would like to design and implement a Cloud-based IoT platform capable of handling sensor observation streams. It provides a comprehensive way to understand main observation-related challenges, as well as non-functional requirements of IoT platforms such as platform adaptation, scalability and availability. Last but not the least, it gives recommendations and compares some relevant open-source software that can speed up the development process.

Question: What is the difference between a sensor and an observation stream?


Optimal Design of Energy-Efficient Multi-User MIMO Systems: Is Massive MIMO the Answer?. Assume that a multi-user multiple-input multiple-output (MIMO) system is designed from scratch to uniformly cover a given area with maximal energy efficiency (EE). What are the optimal number of antennas, active users, and transmit power? The aim of this paper is to answer this fundamental question. We consider jointly the uplink and downlink with different processing schemes at the base station and propose a new realistic power consumption model that reveals how the above parameters affect the EE. Closed-form expressions for the EE-optimal value of each parameter, when the other two are fixed, are provided for zero-forcing (ZF) processing in single-cell scenarios. These expressions prove how the parameters interact. For example, in sharp contrast to common belief, the transmit power is found to increase (not to decrease) with the number of antennas. This implies that energy-efficient systems can operate in high signal-to-noise ratio regimes in which interference-suppressing signal processing is mandatory. Numerical and analytical results show that the maximal EE is achieved by a massive MIMO setup wherein hundreds of antennas are deployed to serve a relatively large number of users using ZF processing. The numerical results show the same behavior under imperfect channel state information and in symmetric multi-cell scenarios.

Question: What is the optimal number of antennas for a MIMO system?