MetaLDA: A Topic Model that Efficiently Incorporates Meta Information. Besides the text content, documents and their associated words usually come with rich sets of meta information, such as categories of documents and semantic/syntactic features of words, like those encoded in word embeddings. Incorporating such meta information directly into the generative process of topic models can improve modelling accuracy and topic quality, especially in the case where the word-occurrence information in the training data is insufficient. In this paper, we present a topic model, called MetaLDA, which is able to leverage either document or word meta information, or both of them jointly. With two data argumentation techniques, we can derive an efficient Gibbs sampling algorithm, which benefits from the fully local conjugacy of the model. Moreover, the algorithm is favoured by the sparsity of the meta information. Extensive experiments on several real world datasets demonstrate that our model achieves comparable or improved performance in terms of both perplexity and topic quality, particularly in handling sparse texts. In addition, compared with other models using meta information, our model runs significantly faster.

Question: What is a topic model?


Voronoi treemaps for the visualization of software metrics. In this paper we present a hierarchy-based visualization approach for software metrics using Treemaps. Contrary to existing rectangle-based Treemap layout algorithms, we introduce layouts based on arbitrary polygons that are advantageous with respect to the aspect ratio between width and height of the objects and the identification of boundaries between and within the hierarchy levels in the Treemap. The layouts are computed by the iterative relaxation of Voronoi tessellations. Additionally, we describe techniques that allow the user to investigate software metric data of complex systems by utilizing transparencies in combination with interactive zooming.

Question: What is a Voronoi treemap?


Online EM for Unsupervised Models. The (batch) EM algorithm plays an important role in unsupervised induction, but it sometimes suffers from slow convergence. In this paper, we show that online variants (1) provide significant speedups and (2) can even find better solutions than those found by batch EM. We support these findings on four unsupervised tasks: part-of-speech tagging, document classification, word segmentation, and word alignment.

Question: What is the EM algorithm?


Bi-objective conflict detection and resolution in railway traffic management. Railway conflict detection and resolution is the daily task faced by railway managers that consists of adjusting train schedules whenever disturbances make the timetable infeasible. The main objective pursued by the infrastructure managers in this task is minimization of train delays, while train operating companies are also interested in other indicators of passengers dissatisfaction. The two objectives are conflicting whenever delay reduction requires cancellation of some connections between train services, which hampers passengers transfer. In fact, the infrastructure company and the train operating companies discuss on which connection to keep or drop in order to reach a compromise solution. In this paper we face the bi-objective problem of minimizing delays and missed connections to provide a set of feasible non-dominated schedules to support this decisional process. We use a detailed alternative graph model to ensure schedule feasibility and develop two heuristic algorithms to compute the Pareto front of non-dominated schedules. Our computational study, based on a complex and densely occupied Dutch railway network, shows that good coordination of connected train services is important to achieve real-time efficiency of railway services since the management of connections may heavily affect train punctuality. The two algorithms approximate accurately the Pareto front within a limited computational time.

Question: What is the objective of railway conflict detection and resolution?


A CNS-permeable Hsp90 inhibitor rescues synaptic dysfunction and memory loss in APP-overexpressing Alzheimer's mouse model via an HSF1-mediated mechanism. Induction of neuroprotective heat-shock proteins via pharmacological Hsp90 inhibitors is currently being investigated as a potential treatment for neurodegenerative diseases. Two major hurdles for therapeutic use of Hsp90 inhibitors are systemic toxicity and limited central nervous system permeability. We demonstrate here that chronic treatment with a proprietary Hsp90 inhibitor compound (OS47720) not only elicits a heat-shock-like response but also offers synaptic protection in symptomatic Tg2576 mice, a model of Alzheimer's disease, without noticeable systemic toxicity. Despite a short half-life of OS47720 in mouse brain, a single intraperitoneal injection induces rapid and long-lasting (>3 days) nuclear activation of the heat-shock factor, HSF1. Mechanistic study indicates that the remedial effects of OS47720 depend upon HSF1 activation and the subsequent HSF1-mediated transcriptional events on synaptic genes. Taken together, this work reveals a novel role of HSF1 in synaptic function and memory, which likely occurs through modulation of the synaptic transcriptome.

Question: What is the mechanism of action of the Hsp90 inhibitor?


Analysis of charge-pump phase-locked loops. In this paper, we present an exact analysis for third-order charge-pump phase-locked loops using state equations. Both the large-signal lock acquisition process and the small-signal linear tracking behavior are described using this analysis. The nonlinear state equations are linearized for the small-signal condition and the z-domain noise transfer functions are derived. A comparison to some of the existing analysis methods such as the impulse-invariant transformation and s-domain analysis is provided. The effect of the loop parameters and the reference frequency on the loop phase margin and stability is analyzed. The analysis is verified using behavioral simulations in MATLAB and SPECTRE.

Question: What is the difference between the impulse invariant transformation and the s-domain analysis?


Document Page Segmentation and Layout Analysis Using Soft Ordering. A document image is composed of a variety of physical entities or regions such as text blocks, lines, words, figures, tables, and background. We could also assign functional or logical labels such as sentences, titles, captions, author names, and addresses to some of these regions. The process of document structure and layout analysis tries to decompose a given document image into its component regions and understand their functional roles and relationships. The processing is carried out in multiple steps, such as preprocessing, page decomposition, structure understanding, etc. We will look into each of these steps in detail in the following sections. Document images are often generated from physical documents by digitization using scanners or digital cameras. Many documents, such as newspapers, magazines and brochures, contain very complex layout due to the placement of figures, titles, and captions, complex backgrounds, artistic text formatting, etc. (see Figure 1). A human reader uses a variety of additional cues such as context, conventions and information about language/script, along with a complex reasoning process to decipher the contents of a document. Automatic analysis of an arbitrary document with complex layout is an extremely difficult task and is beyond the capabilities of the state-of-the-art document structure and layout analysis systems. This is interesting since documents are designed to be effective and clear to human interpretation unlike natural images.

Question: How to segment a document into its component regions?


PUSHOVER ANALYSIS OF A MULTISTORIED BUILDING. To model the advanced behaviour of reinforced concrete analytically in its non-linear zone is difficult. This has led engineers in the past to believe heavily on empirical formulas that were derived from numerous experiments for the design of reinforced concrete structures. For structural design and assessment of reinforced concrete members, the nonlinear analysis has become a vital tool. The method can be used to study the behaviour of reinforced concrete structures as well as force redistribution. This analysis of the nonlinear response of RC structures to be distributed out in an exceedingly routine fashion. It helps within the investigation of the behaviour of the structure below completely different loading conditions and also the cracks pattern. In the present study, the non-linear response of RCC frame using the loading has been carried out with the intention to investigate the relative importance of many factors in the non-linear analysis of RCC frames. The structure was modelled and analyzed in STAAD Pro V8i, SAP2000 and designed manually. The description of the reinforcement was done in AutoCAD 2010. Keywordsmulti-storied building, STAAD PRO, Floor plan, SAP 2000, Push over analysis.

Question: What is the difference between STAAD PRO and SAP2000?


Development of Fire alarm system using Raspberry Pi and Arduino Uno. The proposed Fire alarm system is a real-time monitoring system that detects the presence of smoke in the air due to fire and captures images via a camera installed inside a room when a fire occurs. The embedded systems used to develop this fire alarm system are Raspberry Pi and Arduino Uno. The key feature of the system is the ability to remotely send an alert when a fire is detected. When the presence of smoke is detected, the system will display an image of the room state in a webpage. The system will need the user confirmation to report the event to the Firefighter using Short Message Service (SMS). The advantage of using this system is it will reduce the possibility of false alert reported to the Firefighter. The camera will only capture an image, so this system will consume a little storage and power.

Question: What is the raspberry pi?


Pseudo-analysis approach to nonlinear partial differential equations. An overview of methods of pseudo-analysis in applications on important classes of nonlinear partial differential equations, occurring in different fields, is given. Hamilton-Jacobi equations, specially important in the control theory, are for important models usually with non-linear Hamiltonian H which is also not smooth, e.g., the absolute value, min or max operations, where it can not apply the classical mathematical analysis. Using the pseudo-analysis with generalized pseudo-convolution it is possible to obtain solutions which can be interpreted in the mentioned classical way. Another important classes of nonlinear equations, where there are applied the pseudo-analysis, are the Burgers type equations and Black and Shole equation in option pricing. Very recent applications of pseudo-analysis are obtained on equations which model fluid mechanics (Navier-Stokes equation) and image processing (Perona and Malik equation).

Question: What is pseudo-analysis?


Game Theory in Signal Processing and Communications. 1Department of Mobile Communications, School of Electrical Engineering and Computer Sciences, Technical University of Berlin, Berlin, Germany 2Wireless Networking, Signal Processing and Security Lab, Department of Electrical and Computer Engineering, University of Houston, Houston, TX 77004, USA 3Division of Communication Systems, Department of Electrical Engineering (ISY), Linköping University, SE-581 83 Linköping, Sweden 4Communications Laboratory, Faculty of Electrical Engineering and Information Technology, Dresden University of Technology, 01062 Dresden, Germany

Question: What is the difference between signal processing and communications?


Comparison of perioperative outcomes between robotic and laparoscopic partial nephrectomy: a systematic review and meta-analysis.. CONTEXT Robotic partial nephrectomy (RPN) is rapidly increasing; however, the benefit of RPN over laparoscopic partial nephrectomy (LPN) is controversial.   OBJECTIVE To compare perioperative outcomes of RPN and LPN.   EVIDENCE ACQUISITION We searched Ovid-Medline, Ovid-Embase, the Cochrane Library, KoreaMed, KMbase, KISS, RISS, and KisTi from their inception through August 2013. Two independent reviewers extracted data using a standardized form. Quality of the selected studies was assessed using the methodological index for nonrandomized studies.   EVIDENCE SYNTHESIS A total of 23 studies and 2240 patients were included. All studies were cohort studies with no randomization, and the methodological quality varied. There was no significant difference between the two groups regarding complications of Clavien-Dindo classification grades 1-2 (p=0.62), Clavien-Dindo classification grades 3-5 (p=0.78), change of serum creatinine (p=0.65), operative time (p=0.35), estimated blood loss (p=0.76), and positive margins (p=0.75). The RPN group had a significantly lower rate of conversion to open surgery (p=0.02) and conversion to radical surgery (p=0.0006), shorter warm ischemia time (WIT; p=0.005), smaller change of estimated glomerular filtration rate (eGFR; p=0.03), and shorter length of stay (LOS; p=0.004).   CONCLUSIONS This meta-analysis shows that RPN is associated with more favorable results than LPN in conversion rate to open or radical surgery, WIT, change of eGFR, and shorter LOS. To establish the safety and effectiveness outcomes of robotic surgery, well-designed randomized clinical studies with long-term follow-up are needed.   PATIENT SUMMARY Robotic partial nephrectomy (PN) is more favorable than laparoscopic PN in terms of lower conversion rate to radical nephrectomy, a favorable renal function indexed estimated glomerular filtration

Question: What is the difference between robotic and laparoscopic partial nephrectomy?


Attribution versus persuasion as a means for modifying behavior.. The present research compared the relative effectiveness of an attribution strategy with a persuasion strategy in changing behavior. Study 1 attempted to teach fifth graders not to litter and to clean up after others. An attribution group was repeatedly told that they were neat and tidy people, a persuasion group was repeatedly told that they should be neat and tidy, and a control group received no treatment. Attribution proved considerably more effective in modifying behavior. Study 2 tried to discover whether similar effects would hold for a more central aspect of school performance, math achievement and self-esteem, and whether an attribution of ability would be as effective as an attribution of motivation. Repeatedly attributing to second graders either the ability or the motivation to do well in math proved more effective than comparable persuasion or no-treatment control groups, although a group receiving straight reinforcement for math problem-solving behavior also did well. It is suggested that persuasion often suffers because it involves a negative attribution (a person should be what he is not), while attribution generally gains because it disguises persuasive intent.

Question: What is the difference between attribution and persuasion?


Some Theoretical Considerations in Off-the-Shelf Text Analysis Software. This paper is concerned with theoretical considerations of commercial content analysis software, namely Linguistic Inquiry and Word Count (LIWC), developed by social psychologists at the University of Texas. LIWC is widely cited and forms the basis of many research papers from a range of disciplines. Here, LIWC is taken as an example of a context-independent, word-counting approach to text analysis, and the strengths and potential pitfalls of such a methodology are discussed. It is shown that text analysis software is constrained not only by its functions, but also by its underlying theoretical assumptions. The paper offers recommendations for good practice in software commercialisation and application, stressing the importance of transparency and acknowledgement of biases.

Question: What is the difference between a context-independent and a context-dependent approach to text analysis?


Frequency Response Analysis and Bandwidth Extension of the Doherty Amplifier. A complete frequency response analysis of the Doherty amplifier is presented with the conventional output combining network consisting of two quarter-wavelength (λ/4) transmission lines at a center frequency f0 . Expressions for output power and efficiency were derived over the whole dynamic range and at any frequency f. The analysis shows that the amount of efficiency enhancement, as well as the maximum output power, reduce as the deviation from f0 increases. For instance, the derived expressions show that a conventional Doherty amplifier has a drain efficiency of η ≥ 52.7%, which represents at least 13.4% efficiency enhancement over a class B amplifier, and up to 33.3% fractional bandwidth. A modified output combining network, using λ/4 lines with reduced impedance transformation ratio, is also analyzed, which results in a bandwidth extension of the Doherty amplifier when compared to the conventional design. To verify the derived analyses, three unsymmetrical GaN Doherty power amplifiers (DPAs) were designed and characterized; the first DPA was based on the conventional output combining network, while the second DPA was based on the proposed network. Measurements showed that the first DPA had, at 5-6-dB back-off, a drain efficiency of η ≥ 44% and over 28% fractional bandwidth (1.7-2.25 GHz), while the DPA with the proposed output combining network had a better wideband performance than the third reference conventional DPA, with a back-off drain efficiency of η ≥ 41%, and over 42% fractional bandwidth (1.7-2.6 GHz). To the best of authors' knowledge, the designed DPAs have the highest bandwidths reported thus far.

Question: What is the bandwidth of a Doherty amplifier?


A Spreadsheet Algebra for a Direct Data Manipulation Query Interface. A spreadsheet-like "direct manipulation" interface is more intuitive for many non-technical database users compared to traditional alternatives, such as visual query builders. The construction of such a direct manipulation interfacemay appear straightforward, but there are some significant challenges. First, individual direct manipulation operations cannot be too complex, so expressive power has to be achieved through composing (long) sequences of small operations. Second, all intermediate results are visible to the user, so grouping and ordering are material after every small step. Third, users often find the need to modify previously specified queries. Since manipulations are specified one step at a time, there is no actual queryexpression to modify. Suitable means must be provided to address this need. Fourth, the order in which manipulations are performed by the user should not affect the results obtained, to avoid user confusion. We address the aforementioned challenges by designing a new spreadsheet algebra that: i) operates on recursively grouped multi-sets, ii) contains a selectively designed set of operators capable of expressing at least all single-block SQL queries and can be intuitively implemented in a spreadsheet, iii) enables query modification by the notion of modifiable query state, and iv) requires no ordering in unary data manipulation operators since they are all designed to commute. We built a prototype implementation of the spreadsheet algebra and show, through user studies with non-technical subjects, that the resultant query interface is easier to use than a standard commercial visual query builder.

Question: What is a spreadsheet algebra?


IoT based smart surveillance security system using raspberry Pi. Communication mainly is the transfer of whatever thing or exchanging of data, so that the Internet of things is naught but the transferring or exchanging of anything with several other things. The using of internet authorized system or devices roughly calculated as that by 2020 there will be nearly about billions. The purpose of the paper is to define a safekeeping alert device spending little handling power by Internet of things which help out to observer plus alerts when gestures or else motion are there then send images to a cloud server. Besides, internet of things centered use can be used tenuously to observe the action as well as acquire warning when gestures or else indication are there. The images are showed straight to a cloud attendant, when the cloud attendant is not accessible at that time the records are put in storage close by on a Raspberry Pi. A credit card size Raspberry Pi with a advantage of Open Source Computer Vision (Open-CV) software knobs the image processing, control algorithms used for the attentiveness then shows taken images to concern persons email by the use of Wi-Fi module. The system uses ordinary webcam.

Question: What is IoT?


iPhone 3 GS Forensics : Logical analysis using Apple iTunes Backup Utility. The iPhone mobile is used worldwide due to its enhanced computing capabilities, increased storage capacity as well as its attractive touch interface. These characteristics made the iPhone a popular smart phone device. The increased use of the iPhone lead it to become a potential source of digital evidence in criminal investigations. Therefore, iPhone forensics turned into an essential practice for forensic and security practitioners today. This research aimed at investigating and examining the logical backup acquisition of the iPhone 3GS mobile device using the Apple iTunes backup utility. It was found that significant data of forensic value such as e-mail messages, text and multimedia messages, calendar events, browsing history, GPRS locations, contacts, call history and voicemail recording can be retrieved using this method of iPhone acquisition.

Question: How to retrieve data from an iPhone?


Game-Related Statistics that Discriminated Winning, Drawing and Losing Teams from the Spanish Soccer League.. The aim of the present study was to analyze men's football competitions, trying to identify which game-related statistics allow to discriminate winning, drawing and losing teams. The sample used corresponded to 380 games from the 2008-2009 season of the Spanish Men's Professional League. The game-related statistics gathered were: total shots, shots on goal, effectiveness, assists, crosses, offsides commited and received, corners, ball possession, crosses against, fouls committed and received, corners against, yellow and red cards, and venue. An univariate (t-test) and multivariate (discriminant) analysis of data was done. The results showed that winning teams had averages that were significantly higher for the following game statistics: total shots (p < 0.001), shots on goal (p < 0.01), effectiveness (p < 0.01), assists (p < 0.01), offsides committed (p < 0.01) and crosses against (p < 0.01). Losing teams had significantly higher averages in the variable crosses (p < 0.01), offsides received (p < 0. 01) and red cards (p < 0.01). Discriminant analysis allowed to conclude the following: the variables that discriminate between winning, drawing and losing teams were the total shots, shots on goal, crosses, crosses against, ball possession and venue. Coaches and players should be aware for these different profiles in order to increase knowledge about game cognitive and motor solicitation and, therefore, to evaluate specificity at the time of practice and game planning. Key pointsThis paper increases the knowledge about soccer match analysis.Give normative values to establish practice and match objectives.Give applications ideas to connect research with coaches' practice.

Question: What is the difference between a winning and losing team?


Music and Cognitive Abilities. Does music make you smarter? Music listening and music lessons have been claimed to confer intellectual advantages. Any association between music and intellectual functioning would be notable only if the benefits apply reliably to nonmusical abilities and if music is unique in producing the effects. The available evidence indicates that music listening leads to enhanced performance on a variety of cognitive tests, but that such effects are shortterm and stem from the impact of music on arousal level and mood, which, in turn, affect cognitive performance; experiences other than music listening have similar effects. Music lessons in childhood tell a different story. They are associated with small but general and long-lasting intellectual benefits that cannot be attributed to obvious confounding variables such as family income and parents' education. The mechanisms underlying this association have yet to be determined. KEYWORDS—music cognition; intelligence; cognitive development People's eagerness for quick fixes can be seen in the seemingly irrational appeal of crash diets, get-rich-quick schemes, and getsmart-fast programs. Is the claim of music as a route to enhanced intelligence yet another self-improvement fantasy? In the pages that follow, I outline the origins of the claim and evaluate the available evidence. Intellectual benefits of exposure to music would be noteworthy if (a) they extend to nonmusical abilities, (b) they are systematic and reliable, and (c) they are more likely to result from hearing or playing music than from other activities. Unlike in other cultures, where virtually everyone participates in music making, musical experiences in Western society typically involve listening and, only in some cases, lessons and performing. Music listening is ubiquitous, both purposefully (e.g., listening to the radio) and incidentally (e.g., background music in stores and restaurants). By contrast, relatively few individuals take

Question: What is the difference between music and music lessons?


TrustOTP: Transforming Smartphones into Secure One-Time Password Tokens. Two-factor authentication has been widely used due to the vulnerabilities associated with traditional text-based password. One-time password (OTP) plays an indispensable role on authenticating mobile users to critical web services that demand a high level of security. As the smartphones are increasingly gaining popularity nowadays, software-based OTP generators have been developed and installed into smartphones as software apps, which bring great convenience to the users without introducing extra burden. However, software-based OTP solutions cannot guarantee the confidentiality of the generated passwords or even the seeds when the mobile OS is compromised. Moreover, they also suffer from denial-of-service attacks when the mobile OS crashes. Hardware-based OTP tokens can solve these security problems in the software-based OTP solutions; however, it is inconvenient for the users to carry physical tokens with them, particularly, when there are more than one token to be carried. In this paper, we present TrustOTP, a secure one-time password solution that can achieve both the flexibility of software tokens and the security of hardware tokens by using ARM TrustZone technology. TrustOTP can not only protect the confidentiality of the OTPs against a malicious mobile OS, but also guarantee reliable OTP generation and trusted OTP display when the mobile OS is compromised or even crashes. It is flexible to integrate multiple OTP algorithms and instances for different application scenarios on the same smartphone platform without modifying the mobile OS. We develop a prototype of TrustOTP on Freescale i.MX53 QSB. The experimental results show that TrustOTP has small impacts on the mobile OS and its power consumption is low.

Question: What is the difference between software-based and hardware-based OTP solutions?


As time goes by : Evidence for two systems in processing space 4 ime metaphors. Temporal language is often couched in spatial metaphors. English has been claimed to have two space-time metaphoric systems: the ego-moving metaphor, wherein the observer's context progresses along the time-line towards the future, and the time-moving metaphor, wherein time is conceived of as a river or conveyor belt on which events are moving from the future to the past. In three experiments, we investigated the psychological status of these metaphors by asking subjects to carry out temporal inferences stated in terms of spatial metaphors. In Experiment 1, we found that subjects were slowed in their processing when the assertions shifted from one spatial metaphoric system to the other. In Experiment 2, we determined that this cost of shifting could not be attributed to local lexical factors. In Experiment 3, we again found this metaphor consistency effect in a naturalistic version of the study in which we asked commonsense time questions of passengers at an airport. The results of the three studies provide converging evidence that people use spatial metaphors in temporal reasoning. Implications for the status of metaphoric systems arc discussed.

Question: What is the difference between the ego-moving and time-moving metaphors?


Psychophysical magic: rendering the visible 'invisible'. What are the neural correlates of conscious visual awareness? Tackling this question requires contrasting neural correlates of stimulus processing culminating in visual awareness with neural correlates of stimulus processing unaccompanied by awareness. To produce these two neural states, one must be able to erase an otherwise visible stimulus from awareness. This article describes and assesses visual phenomena involving dissociation of physical stimulation and conscious awareness: degraded stimulation, visual masking, visual crowding, bistable figures, binocular rivalry, motion-induced blindness, inattentional blindness, change blindness and attentional blink. No single approach stands above the others, but those producing changing visual awareness despite invariant physical stimulation are clearly preferable. Such phenomena can help lead us ultimately to a comprehensive account of the neural correlates of conscious awareness.

Question: What are the neural correlates of conscious visual awareness?


A Randomized Controlled Trial Comparing the Attention Training Technique and Mindful Self-Compassion for Students With Symptoms of Depression and Anxiety. The Attention Training Technique (ATT) and Mindful Self-Compassion (MSC) are two promising psychological interventions. ATT is a 12-min auditory exercise designed to strengthen attentional control and promote external focus of attention, while MSC uses guided meditation and exercises designed to promote self-compassion. In this randomized controlled trial (RCT), a three-session intervention trial was conducted in which university students were randomly assigned to either an ATT-group (n = 40) or a MSC-group (n = 41). The students were not assessed with diagnostic interviews but had self-reported symptoms of depression, anxiety, or stress. Participants listened to audiotapes of ATT or MSC before discussing in groups how to apply these principles for their everyday struggles. Participants also listened to audiotapes of ATT and MSC as homework between sessions. Participants in both groups showed significant reductions in symptoms of anxiety and depression accompanied by significant increases in mindfulness, self-compassion, and attention flexibility post-intervention. These results were maintained at 6-month follow-up. Improvement in attention flexibility was the only significant unique predictor of treatment response. The study supports the use of both ATT and MSC for students with symptoms of depression and anxiety. Further, it suggests that symptom improvement is related to changes in attention flexibility across both theoretical frameworks. Future studies should focus on how to strengthen the ability for attention flexibility to optimize treatment for emotional disorder.

Question: What is the difference between ATT and MSC?


Regularized linear and kernel redundancy analysis. Redundancy analysis (RA) is a versatile technique used to predict multivariate criterion variables from multivariate predictor variables. The reduced-rank feature of RA captures redundant information in the criterion variables in a most parsimonious way. A ridge type of regularization was introduced in RA to deal with the multicollinearity problem among the predictor variables. The regularized linear RA was extended to nonlinear RA using a kernel method to enhance the predictability. The usefulness of the proposed procedures was demonstrated by a Monte Carlo study and through the analysis of two real data sets.

Question: What is a ridge type of regularization?


Bigrams of Syntactic Labels for Authorship Discrimination of Short Texts. We present a method for authorship discrimination that is based on the frequency of bigrams of syntactic labels that arise from partial parsing of the text. We show that this method, alone or combined with other classification features, achieves a high accuracy on discrimination of the work of Anne and Charlotte Brontë, which is very difficult to do by traditional methods. Moreover, high accuracies are achieved even on fragments of text little more than 200 words long. .................................................................................................................................................................................

Question: How to classify authorship of short texts?


Dermoscopy of cutaneous leishmaniasis.. BACKGROUND Dermoscopy has been proposed as a diagnostic tool in the case of skin infections and parasitosis but no specific dermoscopic criteria have been described for cutaneous leishmaniasis (CL).   OBJECTIVES To describe the dermoscopic features of CL.   METHODS Dermoscopic examination (using the DermLite Foto; 3Gen, LLC, Dana Point, CA, U.S.A.) of 26 CL lesions was performed to evaluate specific dermoscopic criteria.   RESULTS We observed the following dermoscopic features: generalized erythema (100%), 'yellow tears' (53%), hyperkeratosis (50%), central erosion/ulceration (46%), erosion/ulceration associated with hyperkeratosis (38%) and 'white starburst-like pattern' (38%). Interestingly, at least one vascular structure described in skin neoplasms was observed in all cases: comma-shaped vessels (73%), linear irregular vessels (57%), dotted vessels (53%), polymorphous/atypical vessels (26%), hairpin vessels (19%), arborizing telangiectasia (11%), corkscrew vessels (7%) and glomerular-like vessels (7%). Combination of two or more different types of vascular structures was present in 23 of 26 CL lesions (88%), with a combination of two vascular structures in 13 cases (50%) and three or more in 10 cases (38%).   CONCLUSIONS Characteristic dermoscopic structures have been identified in CL. Important vascular patterns seen in melanocytic and nonmelanocytic tumours are frequently observed in this infection.

Question: What are the dermoscopic features of cutaneous leishmaniasis?


The Internet of things.. Keynote David Rose The New Vanguard for Business: Connectivity, Design, and the Internet of Things The Internet of Things is the hottest topic of the moment a shift predicted to be as momentous as the impact of the internet itself. The internet has allowed us to share ideas and data largely input by humans. What about a world where data from objects as diverse as umbrellas, fridges, and gas tanks all flows through the internet?

Question: What is the internet of things?


Exploiting Software: How to Break Code. To be useful, software must respond to events in a predictable manner. The results can then be used as a window to the interior workings of the code, revealing some of the mechanisms of operations, which may be used to find ways to make it fail in a dangerous way. To some, the window is as clear as a six inch thick pane of lead, but to those with a high level of understanding it can be clear, or at the very least serve as a keyhole. This is an allusion to the old detective stories where someone looks through the keyhole to see what is behind the door. For these reasons, no software that interacts with humans can ever be considered completely secure, and human error in the development of the software can leave the equivalent of keyholes throughout the code.

Question: How to break code?


Microstrip Rectangular 4x1 Patch Array Antenna at 2.5GHz for WiMax Application. This paper presents the design of microstrip rectangular patch antenna with center frequency at 2.5GHz for WiMAX application. The array of four by one (4x1) patch array microstrip rectangular antenna with microstrip line feeding based on quarter wave impedance matching technique was designed and simulated using Computer Simulation Tool (CST) Microwave Environment software. The performance of the designed antenna was than compared with the single patch rectangle antenna in term of return loss, Voltage Standing Wave Ratio (VSWR), bandwidth, directivity, radiation pattern and gain. The array antenna was then fabricated on the substrate type FR-4 with dielectric constant of 4.9 and thickness of 1.6mm respectively. The array antenna was measured in the laboratory using Vector Network Analyzer (VNA) and the results show good agreement with the array antenna simulated performances.

Question: What is the difference between a microstrip patch antenna and a patch antenna?


Three-Dimensional Object Recognition from Single Two-Dimensional Images. A computer vision system has been implemented that can recognize threedimensional objects from unknown viewpoints in single gray-scale images. Unlike most other approaches, the recognition is accomplished without any attempt to reconstruct depth information bottom-up from the visual input. Instead, three other mechanisms are used that can bridge the gap between the two-dimensional image and knowledge of three-dimensional objects. First, a process of perceptual organization is used to form groupings and structures in the image that are likely to be invariant over a wide range of viewpoints. Second, a probabilistic ranking method is used to reduce the size of the search space during model based matching. Finally, a process of spatial correspondence brings the projections of three-dimensional models into direct correspondence with the image by solving for unknown viewpoint and model parameters. A high level of robustness in the presence of occlusion and missing data can be achieved through full application of a viewpoint consistency constraint. It is argued that similar mechanisms and constraints form the basis for recognition in human vision. This paper has been published in Artificial Intelligence, 31, 3 (March 1987), pp. 355–395.

Question: What is the name of the paper?


On Bayesian Upper Confidence Bounds for Bandit Problems. Stochastic bandit problems have been analyzed from two different perspectives: a frequentist view, where the parameter is a deterministic unknown quantity, and a Bayesian approach, where the parameter is drawn from a prior distribution. We show in this paper that methods derived from this second perspective prove optimal when evaluated using the frequentist cumulated regret as a measure of performance. We give a general formulation for a class of Bayesian index policies that rely on quantiles of the posterior distribution. For binary bandits, we prove that the corresponding algorithm, termed BayesUCB, satisfies finite-time regret bounds that imply its asymptotic optimality. More generally, Bayes-UCB appears as an unifying framework for several variants of the UCB algorithm addressing different bandit problems (parametric multi-armed bandits, Gaussian bandits with unknown mean and variance, linear bandits). But the generality of the Bayesian approach makes it possible to address more challenging models. In particular, we show how to handle linear bandits with sparsity constraints by resorting to Gibbs sampling.

Question: What is the Bayesian approach to bandit problems?


Guaranteed-Quality Mesh Generation for Curved Surfaces. For several commonly-used solution techniques for partial differential equations, the first step is to divide the problem region into simply-shaped elements, creating a mesh. We present a technique for creating high-quality triangular meshes for regions on curved surfaces. This technique is an extension of previous methods we developed for regions in the plane. For both flat and curved surfaces, the resulting meshes are guaranteed to exhibit the following properties: (1) internal and external boundaries are respected, (2) element shapes are guaranteed—all elements are triangles with angles between 30 and 120 degrees (with the exception of badly shaped elements that may be required by the specified boundary), and (3) element density can be controlled, producing small elements in "interesting" areas and large elements elsewhere. An additional contribution of this paper is the development of a practical generalization of Delaunay triangulation to curved surfaces.

Question: How to generate a mesh for a curved surface?


Songle: A Web Service for Active Music Listening Improved by User Contributions. This paper describes a public web service for active music listening,Songle, that enriches music listening experiences by using music-understanding technologies based on signal processing. Although various research-level interfaces and technologies have been developed, it has not been easy to get people to use them in everyday life. Songle serves as a showcase to demonstrate how people can benefit from music-understanding technologies by enabling people to experience active music listening interfaces on the web. Songle facilitates deeper understanding of music by visualizing music scene descriptions estimated automatically, such as music structure, hierarchical beat structure, melody line, and chords. When using music-understanding technologies, however, estimation errors are inevitable. Songle therefore features an efficient error correction interface that encourages people to contribute by correcting those errors to improve the web service. We also propose a mechanism of collaborative training for music-understanding technologies, in which corrected errors will be used to improve the music-understanding performance through machine learning techniques. We hope Songle will serve as a research platform where other researchers can exhibit results of their music-understanding technologies to jointly promote the popularization of the field of music information research.

Question: What is a web service for active music listening?


On the derivation of coseismic displacement fields using differential radar interferometry: The Landers earthquake. We present a map of the coseismic displacement field resulting from the Landers, California, June 28, 1992, earthquake derived using data acquired from an orbiting high-resolution radar system. We achieve results more accurate than previous space studies and similar in accuracy to those obtained by conventional field survey techniques. Data from the ERS 1 synthetic aperture radar instrument acquired in April, July, and August 1992 are used to generate a high-resolution, wide area map of the displacements. The data represent the motion in the direction of the radar line of sight to centimeter level precision of each 30-m resolution element in a 113 km by 90 km image. Our coseismic displacement contour map gives a lobed pattern consistent with theoretical models of the displacement field from the earthquake. Fine structure observed as displacement tiling in regions several kilometers from the fault appears to be the result of local surface fracturing. Comparison of these data with Global Positioning System and electronic distance measurement survey data yield a correlation of 0.96; thus the radar measurements are a means to extend the point measurements acquired by traditional techniques to an area map format. The technique we use is (1) more automatic, (2) more precise, and (3) better validated than previous similar applications of differential radar interferometry. Since we require only remotely sensed satellite data with no additional requirements for ancillary information, the technique is well suited for global seismic monitoring and analysis.

Question: How does differential radar interferometry work?


Disease and pest prediction IoT system in orchard: A preliminary study. Each species of diseases and pests is considered to be harmful to plants and has a great adverse effect on agriculture. In addition to decreasing crop productivity and quality, pesticides or fungicides which cause environmental pollution are needed to kill diseases and pests. Therefore, the IoT system is designed to reduce the frequent use of insecticides and fungicides and to predict when the pests appear in order to lower the appearance of pests. Therefore, weather stations near the orchard have been installed and used to analyze the correlation between pests and weather data that had a large effect on pests. The prediction models have been created utilizing correlation information. In other words, we proposed a system that provides disease and pest prediction information so that farmers can quickly control them.

Question: What is the correlation between pests and weather data?


Bayesian Modeling with Gaussian Processes using the GPstuff Toolbox. Gaussian processes (GP) are powerful tools for probabilistic modeling purposes. They can be used to define prior distributions over latent functions in hierarchical Bayesian models. The prior over functions is defined implicitly by the mean and covariance function, which determine the smoothness and variability of the function. The inference can then be conducted directly in the function space by evaluating or approximating the posterior process. Despite their attractive theoretical properties GPs provide practical challenges in their implementation. GPstuff is a versatile collection of computational tools for GP models compatible with Linux and Windows MATLAB and Octave. It includes, among others, various inference methods, sparse approximations and tools for model assessment. In this work, we review these tools and demonstrate the use of GPstuff in several models.

Question: What is a Gaussian process?


Auto-encoder bottleneck features using deep belief networks. Neural network (NN) bottleneck (BN) features are typically created by training a NN with a middle bottleneck layer. Recently, an alternative structure was proposed which trains a NN with a constant number of hidden units to predict output targets, and then reduces the dimensionality of these output probabilities through an auto-encoder, to create auto-encoder bottleneck (AE-BN) features. The benefit of placing the BN after the posterior estimation network is that it avoids the loss in frame classification accuracy incurred by networks that place the BN before the softmax. In this work, we investigate the use of pre-training when creating AE-BN features. Our experiments indicate that with the AE-BN architecture, pre-trained and deeper NNs produce better AE-BN features. On a 50-hour English Broadcast News task, the AE-BN features provide over a 1% absolute improvement compared to a state-of-the-art GMM/HMM with a WER of 18.8% and pre-trained NN hybrid system with a WER of 18.4%. In addition, on a larger 430-hour Broadcast News task, AE-BN features provide a 0.5% absolute improvement over a strong GMM/HMM baseline with a WER of 16.0%. Finally, system combination with the GMM/HMM baseline and AE-BN systems provides an additional 0.5% absolute on 430 hours over the AE-BN system alone, yielding a final WER of 15.0%.

Question: What is the difference between a bottleneck and an auto-encoder?


Ranging RFID Tags With Ultrasound. Indoor localization and tracking of persons and assets with centimeter-level accuracy for inventory, security, medical monitoring, and training, as well as gesture interfaces for domotics, is highly desirable in the framework of the emerging IoT paradigm. Low cost, tiny, battery, or batteryless operated position sensors are required. 3-D localization can be computed by combining three or more distance measurements between sensor and reference points. Our aim is to give the capability of measuring the distance from a reference point to radio frequency identification (RFID) tags. The main challenge is in the estimation of the distances with millimeter accuracy in presence of both size and power supply strict constraints, and thus with very limited computational power. An accurate ranging technique using cross-correlation and small RFID-based sensors is proposed. Its originality resides in moving the main computational efforts from the sensor to an external processing unit with sufficient computational and supply power, thus overcoming the sensor limits. The system is composed of a beacon that emits ultrasound chirps and RF sync signals, a RFID-based distance sensor, a commercial RFID reader, and a processing unit. Main advantages are the high miniaturization and low power consumption of the remote sensor, and its compatibility with existing RFID standards.

Question: How to measure the distance between two RFID tags?


A 5MHz, 24V-to-1.2V, AO2T current mode buck converter with one-cycle transient response and sensorless current detection for medical meters. With a stringent input-to-output conversion ratio (CR) of 20 (24V input and 1.2V output) for a DC-DC converter, two stage cascaded architectures are easy to implement, but suffer from poor efficiency and doubled number of power components. This paper presents a single-stage solution with a proposed Adaptive ON-OFF Time (AO2T) control. In steady state, the control works as an adaptive ON-time valley current mode control to accommodate the large CR. During load transient periods, both ON- and OFF-time are adaptively adjustable to instantaneous load change, in order to accomplish fast load transient response within one switching cycle. To facilitate the high speed current mode control, a sensorless current detection circuit is also proposed. Operating at 5MHz, the converter achieves a maximum efficiency of 89.8% at 700mA and an efficiency of 85% at 2A full load. During a load current slew rate of 1.8A/200ns, the undershoot/overshoot voltages at VO are 23mV and 37mV respectively.

Question: What is a cascaded architecture?


Learning Discriminative Projections for Text Similarity Measures. Traditional text similarity measures consider each term similar only to itself and do not model semantic relatedness of terms. We propose a novel discriminative training method that projects the raw term vectors into a common, low-dimensional vector space. Our approach operates by finding the optimal matrix to minimize the loss of the pre-selected similarity function (e.g., cosine) of the projected vectors, and is able to efficiently handle a large number of training examples in the highdimensional space. Evaluated on two very different tasks, cross-lingual document retrieval and ad relevance measure, our method not only outperforms existing state-of-the-art approaches, but also achieves high accuracy at low dimensions and is thus more efficient.

Question: What is the difference between a discriminative and a generative model?


Visual Graphs from Motion (VGfM): Scene understanding with object geometry reasoning. Recent approaches on visual scene understanding attempt to build a scene graph – a computational representation of objects and their pairwise relationships. Such rich semantic representation is very appealing, yet difficult to obtain from a single image, especially when considering complex spatial arrangements in the scene. Differently, an image sequence conveys useful information using the multi-view geometric relations arising from camera motions. Indeed, object relationships are naturally related to the 3D scene structure. To this end, this paper proposes a system that first computes the geometrical location of objects in a generic scene and then efficiently constructs scene graphs from video by embedding such geometrical reasoning. Such compelling representation is obtained using a new model where geometric and visual features are merged using an RNN framework. We report results on a dataset we created for the task of 3D scene graph generation in multiple views.

Question: What is the name of the dataset?


CredFinder: A real-time tweets credibility assessing system. Lately, Twitter has grown to be one of the most favored ways of disseminating information to people around the globe. However, the main challenge faced by the users is how to assess the credibility of information posted through this social network in real time. In this paper, we present a real-time content credibility assessment system named CredFinder, which is capable of measuring the trustworthiness of information through user analysis and content analysis. The proposed system is capable of providing a credibility score for each user's tweets. Hence, it provides users with the opportunity to judge the credibility of information faster. CredFinder consists of two parts: a frontend in the form of an extension to the Chrome browser that collects tweets in real time from a Twitter search or a user-timeline page and a backend that analyzes the collected tweets and assesses their credibility.

Question: What is a real-time tweets credibility assessing system?


Personality and the prediction of consequential outcomes.. Personality has consequences. Measures of personality have contemporaneous and predictive relations to a variety of important outcomes. Using the Big Five factors as heuristics for organizing the research literature, numerous consequential relations are identified. Personality dispositions are associated with happiness, physical and psychological health, spirituality, and identity at an individual level; associated with the quality of relationships with peers, family, and romantic others at an interpersonal level; and associated with occupational choice, satisfaction, and performance, as well as community involvement, criminal activity, and political ideology at a social institutional level.

Question: What is the relationship between personality and happiness?


Randomized, Placebo-Controlled Trial of Methyl B12 for Children with Autism.. OBJECTIVE Children with autism spectrum disorder (ASD) have been reported to have reduced ability to methylate DNA and elevated markers of oxidative stress. We sought to determine if methyl B12, a key metabolic cofactor for cellular methylation reactions and antioxidant defense, could improve symptoms of ASD.   METHODS A total of 57 children with ASD were randomly assigned to 8 weeks of treatment with methyl B12 (75 μg/kg) or saline placebo every 3 days in a subcutaneous injection. The primary outcome measure was overall improvement in symptoms of ASD as measured by the Clinical Global Impressions-Improvement (CGI-I) score. Secondary outcome measures included changes in the Aberrant Behavior Checklist (ABC) and the Social Responsiveness Scale (SRS). Laboratory measures of methionine methylation and antioxidant glutathione metabolism were assessed at baseline and 8 weeks.   RESULTS A total of 50 children (mean age 5.3 years, 79% male) completed the study. The primary outcome measure - the clinician rated CGI-I score - was statistically significantly better (lower) in the methyl B12 group (2.4) than in the placebo group (3.1) (0.7 greater improvement in the methyl B12 group, 95% CI 1.2-0.2, p = 0.005). Clinical improvement among children treated with methyl B12 was positively correlated with increases in plasma methionine (p = 0.05), decreases in S-adenosyl-l-homocysteine (SAH) (p = 0.007) and improvements in the ratio of S-adenosylmethionine (SAM) to SAH (p = 0.007), indicating an improvement in cellular methylation capacity. No improvements were observed in the parent-rated ABC or SRS.   CONCLUSIONS Methyl B12 treatment improved clinician-rated symptoms of ASD that were correlated with improvements in measures of methionine metabolism and cellular methylation capacity. Clinical Trial Registry: Efficacy Study of Subcutaneous Methyl B12 in Children with Autism: NCT01039792 ( clinicaltrials.g

Question: What is the difference between a randomized controlled trial and a placebo controlled trial?


A Low-energy, Multi-copy Inter-contact Routing Protocol for Disaster Response Networks. This paper presents a novel multi-copy routing protocol for disruption-tolerant networks whose objective is to minimize energy expended on communication. The protocol is designed for disaster-response applications, where power and infrastructure resources are disrupted. Unlike other delay-tolerant networks, energy is a vital resource in post-disaster scenarios to ensure availability of (disruption-tolerant) communication until infrastructure is restored. Our approach exploits naturally recurrent mobility and contact patterns in the network, formed by rescue workers, volunteers, survivors, and their (possibly stranded) vehicles to reduce the number of message copies needed to attain an adequate delivery ratio in the face of disconnection and intermittent connectivity. A new notion of inter-contact routing is proposed that allows estimating route delays and delivery probabilities, identifying more reliable routes and controlling message replication and forwarding accordingly. We simulate the scheme using a mobility model that reflects recurrence inspired by disaster scenarios, and compare our results to previous DTN routing techniques. The evaluation shows that the new approach reduces the resource overhead per message over previous approaches while maintaining a comparable delivery ratio at the expense of a small (bounded) increase in latency.

Question: What is a disaster-response network?


The impact of the MIT-BIH Arrhythmia Database. The MIT-BIH Arrhythmia Database was the first generally available set of standard test material for evaluation of arrhythmia detectors, and it has been used for that purpose as well as for basic research into cardiac dynamics at about 500 sites worldwide since 1980. It has lived a far longer life than any of its creators ever expected. Together with the American Heart Association Database, it played an interesting role in stimulating manufacturers of arrhythmia analyzers to compete on the basis of objectively measurable performance, and much of the current appreciation of the value of common databases, both for basic research and for medical device development and evaluation, can be attributed to this experience. In this article, we briefly review the history of the database, describe its contents, discuss what we have learned about database design and construction, and take a look at some of the later projects that have been stimulated by both the successes and the limitations of the MIT-BIH Arrhythmia Database.

Question: What is the history of the MIT-BIH Arrhythmia Database?


Merkle Tree Traversal in Log Space and Time. We present a technique for Merkle tree traversal which requires only logarithmic space and time. For a tree with N nodes, our algorithm computes sequential tree leaves and authentication path data in time Log2(N) and space less than 3Log2(N), where the units of computation are hash function evaluations or leaf value computations, and the units of space are the number of node values stored. Relative to this algorithm, we show our bounds to be necessary and sufficient. This result is an asymptotic improvement over all other previous results (for example, measuring cost = space ∗ time). We also prove that the complexity of our algorithm is optimal: There can exist no Merkle tree traversal algorithm which consumes both less than O(Log2(N)) space and less than O(Log2(N)) time. Our algorithm is especially of practical interest when space efficiency is required, and can also enhance other traversal algorithms which relax space constraints to gain speed.

Question: What is the merkle tree traversal?


Flawed Self-Assessment: Implications for Health, Education, and the Workplace.. Research from numerous corners of psychological inquiry suggests that self-assessments of skill and character are often flawed in substantive and systematic ways. We review empirical findings on the imperfect nature of self-assessment and discuss implications for three real-world domains: health, education, and the workplace. In general, people's self-views hold only a tenuous to modest relationship with their actual behavior and performance. The correlation between self-ratings of skill and actual performance in many domains is moderate to meager-indeed, at times, other people's predictions of a person's outcomes prove more accurate than that person's self-predictions. In addition, people overrate themselves. On average, people say that they are "above average" in skill (a conclusion that defies statistical possibility), overestimate the likelihood that they will engage in desirable behaviors and achieve favorable outcomes, furnish overly optimistic estimates of when they will complete future projects, and reach judgments with too much confidence. Several psychological processes conspire to produce flawed self-assessments. Research focusing on health echoes these findings. People are unrealistically optimistic about their own health risks compared with those of other people. They also overestimate how distinctive their opinions and preferences (e.g., discomfort with alcohol) are among their peers-a misperception that can have a deleterious impact on their health. Unable to anticipate how they would respond to emotion-laden situations, they mispredict the preferences of patients when asked to step in and make treatment decisions for them. Guided by mistaken but seemingly plausible theories of health and disease, people misdiagnose themselves-a phenomenon that can have severe consequences for their health and longevity. Similarly, research in education finds that students' assessments of

Question: What is the difference between a flawed self-assessment and a self-assessment?


Fully Integrated Startup at 70 mV of Boost Converters for Thermoelectric Energy Harvesting. This paper presents an inductive DC-DC boost converter for energy harvesting using a thermoelectric generator with a minimum startup voltage of 70 mV and a regulated output voltage of 1.25 V. With a typical generator resistance of 40 Ω, an output power of 17 μW can be provided, which translates to an end-to-end efficiency of 58%. The converter employs Schmitt-trigger logic startup control circuitry and an ultra-low voltage charge pump using modified Schmitt-trigger driving circuits optimized for driving capacitive loads. Together with a novel ultra-low leakage power switch and the required control scheme, to the best of the authors' knowledge, this enables the lowest minimum voltage with fully integrated startup.

Question: What is the minimum voltage required to start a thermoelectric generator?


08 67 0 v 1 [ cs . C V ] 2 3 M ar 2 01 8 Object Detection for Comics using Manga 109 Annotations. With the growth of digitized comics, image understanding techniques are becoming important. In this paper, we focus on object detection, which is a fundamental task of image understanding. Although convolutional neural networks (CNN)-based methods archived good performance in object detection for naturalistic images, there are two problems in applying these methods to the comic object detection task. First, there is no large-scale annotated comics dataset. The CNN-based methods require large-scale annotations for training. Secondly, the objects in comics are highly overlapped compared to naturalistic images. This overlap causes the assignment problem in the existing CNN-based methods. To solve these problems, we proposed a new annotation dataset and a new CNN model. We annotated an existing image dataset of comics and created the largest annotation dataset, named Manga109-annotations. For the assignment problem, we proposed a new CNN-based detector, SSD300-fork. We compared SSD300-fork with other detection methods using Manga109-annotations and confirmed that our model outperformed them based on the mAP score.

Question: What is the largest annotation dataset of comics?


Social Media Metrics — A Framework and Guidelines for Managing Social Media. Social media are becoming ubiquitous and need to be managed like all other forms of media that organizations employ to meet their goals. However, social media are fundamentally different from any traditional or other online media because of their social network structure and egalitarian nature. These differences require a distinct measurement approach as a prerequisite for proper analysis and subsequent management. To develop the right social media metrics and subsequently construct appropriate dashboards, we provide a tool kit consisting of three novel components. First, we theoretically derive and propose a holistic framework that covers the major elements of social media, drawing on theories from marketing, psychology, and sociology. We continue to support and detail these elements — namely 'motives,' 'content,' 'network structure,' and 'social roles & interactions' — with recent research studies. Second, based on our theoretical framework, the literature review, and practical experience, we suggest nine guidelines that may prove valuable for designing appropriate social media metrics and constructing a sensible social media dashboard. Third, based on the framework and the guidelines we derive managerial implications and suggest an agenda for future research. © 2013 Direct Marketing Educational Foundation, Inc. Published by Elsevier Inc. All rights reserved.

Question: What is the difference between social media and traditional media?


AUV SLAM using forward/downward looking cameras and artificial landmarks. Autonomous underwater vehicles (AUVs) are usually equipped with one or more optical cameras to obtain visual data of underwater environments. The camera can also be used to estimate the AUV's pose information, along with various navigation sensors such as inertial measurement unit (IMU), Doppler velocity log (DVL), depth sensor, and so on. In this paper, we propose a vision-based simultaneous localization and mapping (SLAM) of AUVs, where underwater artificial landmarks are used to help visual sensing of forward and downward looking cameras. Three types of landmarks are introduced and their detection algorithms are organized in a framework of conventional extended Kalman filter (EKF) SLAM to estimate both robot and landmark states. The proposed method is validated by an experiment performed in a engineering basin. Since DVL suffers from noises in a real ocean environment, we generated synthetic noisy data based on the real sensor data. With this data we verify that the proposed SLAM approach can recover from the erroneous dead reckoning position.

Question: How to estimate the pose of an underwater robot?


Monocyte emigration from bone marrow during bacterial infection requires signals mediated by chemokine receptor CCR2. Monocytes recruited to tissues mediate defense against microbes or contribute to inflammatory diseases. Regulation of the number of circulating monocytes thus has implications for disease pathogenesis. However, the mechanisms controlling monocyte emigration from the bone marrow niche where they are generated remain undefined. We demonstrate here that the chemokine receptor CCR2 was required for emigration of Ly6Chi monocytes from bone marrow. Ccr2−/− mice had fewer circulating Ly6Chi monocytes and, after infection with Listeria monocytogenes, accumulated activated monocytes in bone marrow. In blood, Ccr2−/− monocytes could traffic to sites of infection, demonstrating that CCR2 is not required for migration from the circulation into tissues. Thus, CCR2-mediated signals in bone marrow determine the frequency of Ly6Chi monocytes in the circulation.

Question: How does the chemokine receptor CCR2 regulate monocyte emigration from bone marrow?


Simulation of brake by wire system with dynamic force control. By wire technology is recently developed to improve the reliability, safety, and performance of vehicular drive technology. Brake system is the most important control system for vehicle safety. By wire technology development has encouraged the development of brake by wire systems to reduce traditional mechanical and hydraulic systems usage in automobiles. This paper proposes a novel brake by wire controller that uses a reaction force based bilateral motor controlling method. The proposed system uses two linear actuators with disturbance observer and reaction force observers to provide pedal force amplification and pedal retraction capabilities. The system includes a force controller to provide pedal feel to drivers. Electro mechanical brake position control is used to provide the brake force. The proposed system is simulated for different conditions to measure the performance and robustness. The simulation results provide evidence for robustness, force amplification, and pedal and brake retraction capabilities of the system.

Question: How does brake by wire work?


Cooperative Resource Management in Cloud-Enabled Vehicular Networks. Cloud-enabled vehicular networks are a new paradigm to improve the quality of vehicular services, which have drawn considerable attention in industry and academia. In this paper, we consider the resource management and sharing problem for bandwidth and computing resources to support mobile applications in cloud-enabled vehicular networks. In such an environment, cloud service providers (SPs) can cooperate to form coalitions to share their idle resources with each other. We propose a coalition game model based on two-sided matching theory for cooperation among cloud SPs to share their idle resources. As a result, the resources can be better utilized, and the QoS for users can be improved. Numerical results indicate that our scheme can improve resource utilization and increase by 75% the QoS of the applications compared with that without cooperation. Moreover, the higher service cost of cooperation brings negative effect on coalition formation. The higher cooperation willingness of cloud SPs and the lower service cost support more service applications.

Question: What is the difference between cloud computing and cloud storage?


White matter lesion extension to automatic brain tissue segmentation on MRI. A fully automated brain tissue segmentation method is optimized and extended with white matter lesion segmentation. Cerebrospinal fluid (CSF), gray matter (GM) and white matter (WM) are segmented by an atlas-based k-nearest neighbor classifier on multi-modal magnetic resonance imaging data. This classifier is trained by registering brain atlases to the subject. The resulting GM segmentation is used to automatically find a white matter lesion (WML) threshold in a fluid-attenuated inversion recovery scan. False positive lesions are removed by ensuring that the lesions are within the white matter. The method was visually validated on a set of 209 subjects. No segmentation errors were found in 98% of the brain tissue segmentations and 97% of the WML segmentations. A quantitative evaluation using manual segmentations was performed on a subset of 6 subjects for CSF, GM and WM segmentation and an additional 14 for the WML segmentations. The results indicated that the automatic segmentation accuracy is close to the interobserver variability of manual segmentations.

Question: How to segment brain tissue on MRI?


Prediction , operations , and condition monitoring in wind energy. Recent developments in wind energy research including wind speed prediction, wind turbine control, operations of hybrid power systems, as well as condition monitoring and fault detection are surveyed. Approaches based on statistics, physics, and data mining for wind speed prediction at different time scales are reviewed. Comparative analysis of prediction results reported in the literature is presented. Studies of classical and intelligent control of wind turbines involving different objectives and strategies are reported. Models for planning operations of different hybrid power systems including wind generation for various objectives are addressed. Methodologies for condition monitoring and fault detection are discussed. Future research directions in wind energy are proposed. 2013 Elsevier Ltd. All rights reserved.

Question: What is the wind speed prediction?


A review on the platform design, dynamic modeling and control of hybrid UAVs. This article presents a review on the platform design, dynamic modeling and control of hybrid Unmanned Aerial Vehicles (UAVs). For now, miniature UAVs which have experienced a tremendous development are dominated by two main types, i.e., fixed-wing UAV and Vertical Take-Off and Landing (VTOL) UAV, each of which, however, has its own inherent limitations on such as flexibility, payload, axnd endurance. Enhanced popularity and interest are recently gained by a newer type of UAVs, named hybrid UAV that integrates the beneficial features of both conventional ones. In this paper, a technical overview of the recent advances of the hybrid UAV is presented. More specifically, the hybrid UAV's platform design together with the associated technical details and features are introduced first. Next, the work on hybrid UAV's flight dynamics modeling is then categorized and explained. As for the flight control system design for the hybrid UAV, several flight control strategies implemented are discussed and compared in terms of theory, linearity and implementation.

Question: What is the difference between a fixed-wing UAV and a VTOL UAV?


Security Viewpoint in a Reference Architecture Model for Cyber-Physical Production Systems. Cyber-physical Production Systems (CPPS) are one of the technical driving forces behind the transformation of industrial production towards "digital factory of the future" in the context of Industry 4.0. Security is a major concern for such systems as they become more intelligent, interconnected, and coupled with physical devices. For various security activities from security analysis to designing security controls and architecture, a systematic and structured view and presentation of security-related information is required. Based on the draft standard of Reference Architecture Model for Industry 4.0 (RAMI 4.0), we propose a practical approach to establish a security viewpoint in the CPPS reference architecture model. We investigate the feasibility of using an architecture modeling tool to implement the concept and leverage existing work on models of layered architecture. We demonstrate the applicability for security analysis in two example case studies.

Question: What is the security viewpoint in a reference architecture model for cyber-physical production systems?


On the exploitation of a high-throughput SHA-256 FPGA design for HMAC. High-throughput and area-efficient designs of hash functions and corresponding mechanisms for Message Authentication Codes (MACs) are in high demand due to new security protocols that have arisen and call for security services in every transmitted data packet. For instance, IPv6 incorporates the IPSec protocol for secure data transmission. However, the IPSec's performance bottleneck is the HMAC mechanism which is responsible for authenticating the transmitted data. HMAC's performance bottleneck in its turn is the underlying hash function. In this article a high-throughput and small-size SHA-256 hash function FPGA design and the corresponding HMAC FPGA design is presented. Advanced optimization techniques have been deployed leading to a SHA-256 hashing core which performs more than 30% better, compared to the next better design. This improvement is achieved both in terms of throughput as well as in terms of throughput/area cost factor. It is the first reported SHA-256 hashing core that exceeds 11Gbps (after place and route in Xilinx Virtex 6 board).

Question: What is the area of a FPGA?


Logistic Regression and Collaborative Filtering for Sponsored Search Term Recommendation. Sponsored search advertising is largely based on bidding on individual terms. The richness of natural languages permits web searchers to express their information needs in myriad ways. Advertisers have difficulty discovering all the terms that are relevant to their products or services. We examine the performance of logistic regression and collaborative filtering models on two different data sources to predict terms relevant to a set of seed terms describing an advertiser's product or service.

Question: What is the performance of logistic regression and collaborative filtering on sponsored search?


3D face recognition: a survey. 3D face recognition has become a trending research direction in both industry and academia. It inherits advantages from traditional 2D face recognition, such as the natural recognition process and a wide range of applications. Moreover, 3D face recognition systems could accurately recognize human faces even under dim lights and with variant facial positions and expressions, in such conditions 2D face recognition systems would have immense difficulty to operate. This paper summarizes the history and the most recent progresses in 3D face recognition research domain. The frontier research results are introduced in three categories: pose-invariant recognition, expression-invariant recognition, and occlusion-invariant recognition. To promote future research, this paper collects information about publicly available 3D face databases. This paper also lists important open problems.

Question: What is the history of 3D face recognition?


Stochastic Models , Estimation and Control.

Question: What is stochastic models?


Anatomisation with slicing: a new privacy preservation approach for multiple sensitive attributes. An enormous quantity of personal health information is available in recent decades and tampering of any part of this information imposes a great risk to the health care field. Existing anonymization methods are only apt for single sensitive and low dimensional data to keep up with privacy specifically like generalization and bucketization. In this paper, an anonymization technique is proposed that is a combination of the benefits of anatomization, and enhanced slicing approach adhering to the principle of k-anonymity and l-diversity for the purpose of dealing with high dimensional data along with multiple sensitive data. The anatomization approach dissociates the correlation observed between the quasi identifier attributes and sensitive attributes (SA) and yields two separate tables with non-overlapping attributes. In the enhanced slicing algorithm, vertical partitioning does the grouping of the correlated SA in ST together and thereby minimizes the dimensionality by employing the advanced clustering algorithm. In order to get the optimal size of buckets, tuple partitioning is conducted by MFA. The experimental outcomes indicate that the proposed method can preserve privacy of data with numerous SA. The anatomization approach minimizes the loss of information and slicing algorithm helps in the preservation of correlation and utility which in turn results in reducing the data dimensionality and information loss. The advanced clustering algorithms prove its efficiency by minimizing the time and complexity. Furthermore, this work sticks to the principle of k-anonymity, l-diversity and thus avoids privacy threats like membership, identity and attributes disclosure.

Question: What is the difference between anatomization and slicing?


Real-time neuroevolution in the NERO video game. In most modern video games, character behavior is scripted; no matter how many times the player exploits a weakness, that weakness is never repaired. Yet, if game characters could learn through interacting with the player, behavior could improve as the game is played, keeping it interesting. This paper introduces the real-time Neuroevolution of Augmenting Topologies (rtNEAT) method for evolving increasingly complex artificial neural networks in real time, as a game is being played. The rtNEAT method allows agents to change and improve during the game. In fact, rtNEAT makes possible an entirely new genre of video games in which the player trains a team of agents through a series of customized exercises. To demonstrate this concept, the Neuroevolving Robotic Operatives (NERO) game was built based on rtNEAT. In NERO, the player trains a team of virtual robots for combat against other players' teams. This paper describes results from this novel application of machine learning, and demonstrates that rtNEAT makes possible video games like NERO where agents evolve and adapt in real time. In the future, rtNEAT may allow new kinds of educational and training applications through interactive and adapting games.

Question: What is the real-time neuroevolution of augmenting topologies?


The Multidimensional Knapsack Problem: Structure and Algorithms. Structure and Algorithms Jakob Puchinger NICTA Victoria Laboratory Department of Computer Science & Software Engineering University of Melbourne, Australia jakobp@csse.unimelb.edu.au Günther R. Raidl Institute of Computer Graphics and Algorithms Vienna University of Technology, Austria raidl@ads.tuwien.ac.at Ulrich Pferschy Department of Statistics and Operations Research University of Graz, Austria pferschy@uni-graz.at

Question: What is the multidimensional knapsack problem?


Design of a Direct-Driven Linear Actuator for a High-Speed Quadruped Robot, Cheetaroid-I. Several legged robots have been developed in recent years and proved that they are an effective transportation system on an uneven terrain. In particular, quadruped robots are regarded as a new trend in robotics due to their superior gait stability and robustness to disturbances. More recently, many robotics researchers are making their best efforts to improve the locomotion speed, as well as the stability and robustness, of quadruped robots. The high-speed locomotion creates various challenges in the development of actuators, mechanical design, and control algorithms of the robot. In this paper, a linear actuation system for the high-speed locomotion of a quadruped robot is introduced. The proposed actuator is designed based on the principle of brushed direct-current electric motor systems. For the minimal impedance and improved power capacity, the actuator is designed with dual layers of cores, which are aligned parallel to permanent magnets. The mechanical and electrical properties of the actuation system, such as back-drivability, controllability, and response time, are verified by experimental results. A robotic leg, which is the rear leg of a Cheetah-like robot, is designed with the proposed actuator, and experimental results for trajectory tracking performance are presented.

Question: What is a quadruped robot?


Improving Learning and Inference in a Large Knowledge-Base using Latent Syntactic Cues. Automatically constructed Knowledge Bases (KBs) are often incomplete and there is a genuine need to improve their coverage. Path Ranking Algorithm (PRA) is a recently proposed method which aims to improve KB coverage by performing inference directly over the KB graph. For the first time, we demonstrate that addition of edges labeled with latent features mined from a large dependency parsed corpus of 500 million Web documents can significantly outperform previous PRAbased approaches on the KB inference task. We present extensive experimental results validating this finding. The resources presented in this paper are publicly available.

Question: How to improve the coverage of a knowledge base?


Cybersecurity Games and Investments: A Decision Support Approach. In this paper we investigate how to optimally invest in cybersecurity controls. We are particularly interested in examining cases where the organization suffers from an underinvestment problem or inefficient spending on cybersecurity. To this end, we first model the cybersecurity environment of an organization. We then model non-cooperative cybersecurity control-games between the defender which abstracts all defense mechanisms of the organization and the attacker which can exploit different vulnerabilities at different network locations. To implement our methodology we use the SANS Top 20 Critical Security Controls and the 2011 CWE/SANS top 25 most dangerous software errors. Based on the profile of an organization, which forms its preferences in terms of indirect costs, its concerns about different kinds of threats and the importance of the assets given their associated risks we derive the Nash Equilibria of a series of control-games. These game solutions are then handled by optimization techniques, in particular multi-objective, multiple choice Knapsack to determine the optimal cybersecurity investment. Our methodology provides security effective and cost efficient solutions especially against commodity attacks. We believe our work can be used to advise security managers on how they should spend an available cybersecurity budget given their organization profile.

Question: How to optimally invest in cybersecurity controls?


Design of Metal Interconnects for Stretchable Electronic Circuits using Finite Element Analysis. In this work, the design of flexible and stretchable interconnections is presented. These interconnections are done by embedding sinuous electroplated metallic wires in a stretchable substrate material. A silicone material was chosen as substrate because of its low stiffness and high elongation before break. Common metal conductors used in the electronic industry have very limited elastic ranges; therefore a metallization design is crucial to allow stretchability of the conductors going up to 100%. Different configurations were simulated and compared among them and based on these results, a horseshoe like shape was suggested. This design allows a large deformation with the minimum stress concentration. Moreover, the damage in the metal is significantly reduced by applying narrow metallization schemes. In this way, each conductor track has been split in four parallel lines of 15 mum and 15 mum space in order to improve the mechanical performance without limiting the electrical characteristics. Compared with the single copper or gold trace, the calculated stress was reduced up to 10 times.

Question: What is the horseshoe like shape?


Real-Time Top-View People Counting Based on a Kinect and NVIDIA Jetson TK1 Integrated Platform. In this paper, we describe how to establish an embedded framework for real-time top-view people counting. The development of our system consists of two parts, i.e. establishing an embedded signal processing platform and designing a people counting algorithm for the embedded system. For the hardware platform construction, we use Kinect as the camera and exploit NVIDIA Jetson TK1 board as the embedded processing platform. We describe how to build a channel to make Kinect for windows version 2.0 communicate with Jetson TK1. Based on the embedded system, we adapt a water filling based scheme for top-view people counting, which integrates head detection based on water drop, people tracking and counting. Gaussian Mixture Model is used to construct and update the background model. The moving people in each video frame are extracted using background subtraction method. Additionally, the water filling algorithm is used to segment head area as Region Of Interest(ROI). Tracking and counting people are performed by calculating the distance of ROI center point before and after the frame. The whole framework is flexible and practical for real-time application.

Question: How to count people in a video?


General Survey on Security Issues on Internet of Things. Internet of Things is the integration of a variety of technologies. The Internet of Things incorporates transparently and impeccably large number of assorted end systems, providing open access to selected data for digital services. Internet of things is a promising research in commerce, industry, and education applications. The abundance of sensors and actuators motivates sensing and actuate devices in communication scenarios thus enabling sharing of information in Internet of Things. Advances in sensor data collection technology and Radio Frequency Identification technology has led large number of smart devices connected to the Internet, continuously transmitting data over time.In the context of security, due to different communication overloads and standards conventional security services are not applicable on Internet of Things as a result of which the technological loopholes leads to the generation of malicious data, devices are compromised and so on. Hence a flexible mechanism can deal with the security threats in the dynamic environment of Internet of Things and continuous researches and new ideas needs to be regulated periodically for various upcoming challenges. This paper basically tries to cover up the security issues and challenges of Internet of Things along with a

Question: What is the security issues of Internet of Things?


Accuracy of deception judgments.. We analyze the accuracy of deception judgments, synthesizing research results from 206 documents and 24,483 judges. In relevant studies, people attempt to discriminate lies from truths in real time with no special aids or training. In these circumstances, people achieve an average of 54% correct lie-truth judgments, correctly classifying 47% of lies as deceptive and 61% of truths as nondeceptive. Relative to cross-judge differences in accuracy, mean lie-truth discrimination abilities are nontrivial, with a mean accuracy d of roughly .40. This produces an effect that is at roughly the 60th percentile in size, relative to others that have been meta-analyzed by social psychologists. Alternative indexes of lie-truth discrimination accuracy correlate highly with percentage correct, and rates of lie detection vary little from study to study. Our meta-analyses reveal that people are more accurate in judging audible than visible lies, that people appear deceptive when motivated to be believed, and that individuals regard their interaction partners as honest. We propose that people judge others' deceptions more harshly than their own and that this double standard in evaluating deceit can explain much of the accumulated literature.

Question: How accurate are people at detecting lies?


Fragile online relationship: a first look at unfollow dynamics in twitter. We analyze the dynamics of the behavior known as 'unfollow' in Twitter. We collected daily snapshots of the online relationships of 1.2 million Korean-speaking users for 51 days as well as all of their tweets. We found that Twitter users frequently unfollow. We then discover the major factors, including the reciprocity of the relationships, the duration of a relationship, the followees' informativeness, and the overlap of the relationships, which affect the decision to unfollow. We conduct interview with 22 Korean respondents to supplement the quantitative results.  They unfollowed those who left many tweets within a short time, created tweets about uninteresting topics, or tweeted about the mundane details of their lives. To the best of our knowledge, this work is the first systematic study of the unfollow behavior in Twitter.

Question: What is the first large-scale Canadian peacekeeping mission?


Automatic detection and classification of diabetic retinopathy stages using CNN. A Convolutional Neural Networks (CNNs) approach is proposed to automate the method of Diabetic Retinopathy(DR) screening using color fundus retinal photography as input. Our network uses CNN along with denoising to identify features like micro-aneurysms and haemorrhages on the retina. Our models were developed leveraging Theano, an open source numerical computation library for Python. We trained this network using a high-end GPU on the publicly available Kaggle dataset. On the data set of over 30,000 images our proposed model achieves around 95% accuracy for the two class classification and around 85% accuracy for the five class classification on around 3,000 validation images.

Question: How to detect diabetic retinopathy?


How similar are fluid cognition and general intelligence? A developmental neuroscience perspective on fluid cognition as an aspect of human cognitive ability.. This target article considers the relation of fluid cognitive functioning to general intelligence. A neurobiological model differentiating working memory/executive function cognitive processes of the prefrontal cortex from aspects of psychometrically defined general intelligence is presented. Work examining the rise in mean intelligence-test performance between normative cohorts, the neuropsychology and neuroscience of cognitive function in typically and atypically developing human populations, and stress, brain development, and corticolimbic connectivity in human and nonhuman animal models is reviewed and found to provide evidence of mechanisms through which early experience affects the development of an aspect of cognition closely related to, but distinct from, general intelligence. Particular emphasis is placed on the role of emotion in fluid cognition and on research indicating fluid cognitive deficits associated with early hippocampal pathology and with dysregulation of the hypothalamic-pituitary-adrenal axis stress-response system. Findings are seen to be consistent with the idea of an independent fluid cognitive construct and to assist with the interpretation of findings from the study of early compensatory education for children facing psychosocial adversity and from behavior genetic research on intelligence. It is concluded that ongoing development of neurobiologically grounded measures of fluid cognitive skills appropriate for young children will play a key role in understanding early mental development and the adaptive success to which it is related, particularly for young children facing social and economic disadvantage. Specifically, in the evaluation of the efficacy of compensatory education efforts such as Head Start and the readiness for school of children from diverse backgrounds, it is impor

Question: What is the difference between fluid cognition and general intelligence?


It Makes Sense: A Wide-Coverage Word Sense Disambiguation System for Free Text. Word sense disambiguation (WSD) systems based on supervised learning achieved the best performance in SensEval and SemEval workshops. However, there are few publicly available open source WSD systems. This limits the use of WSD in other applications, especially for researchers whose research interests are not in WSD. In this paper, we present IMS, a supervised English all-words WSD system. The flexible framework of IMS allows users to integrate different preprocessing tools, additional features, and different classifiers. By default, we use linear support vector machines as the classifier with multiple knowledge-based features. In our implementation, IMS achieves state-of-the-art results on several SensEval and SemEval tasks.

Question: What is the best WSD system?


Design of Polarization Reconfigurable Antenna Using Metasurface. A planar polarization-reconfigurable metasurfaced antenna (PRMS) designed using metasurface (MS) is proposed. The PRMS antenna consists of a planar MS placed atop of and in direct contact with a planar slot antenna, both having a circular shape with a diameter of 78 mm (0.9 λ0), making it compact and low profile. By rotating the MS around the center with respect to the slot antenna, the PRMS antenna can be reconfigured to linear polarization, left-hand and right-hand circular polarizations. An equivalent circuit is used to explain the reconfigurability of the antenna. The PRMS antenna is studied and designed to operate at around 3.5 GHz using computer simulation. For verification of simulation results, the PRMS antenna is fabricated and measured. The antenna performance, in terms of polarization reconfigurability, axial-ratio bandwidth, impedance bandwidth, realized boresight gain and radiation pattern, is presented. Results show that the PRMS antenna in circular polarizations achieves an operating bandwidth of 3.3-3.7 GHz (i.e., fractional bandwidth 11.4%), a boresight gain of above 5 dBi and high-polarization isolation of larger than 15 dB. While the PRMS antenna in linear polarization achieves a gain of above 7.5 dBi with cross-polarization isolation larger than 50 dB.

Question: What is the polarization reconfigurable antenna?


Implementation of RSA 2048-bit and AES 256-bit with digital signature for secure electronic health record application. This research addresses the implementation of encryption and digital signature technique for electronic health record to prevent cybercrime problem such as robbery, modification and unauthorized access. In this research, RSA 2048-bit algorithm, AES 256-bit and SHA 256 will be implemented in Java programming. Secure Electronic Health Record Information (SEHR) application design is intended to combine given services, such as confidentiality, integrity, authentication, and non-repudiation. Cryptography is used to ensure the file records and electronic documents for detailed information on the medical past, present and future forecasts that have been given only for the patients. The document will be encrypted using an encryption algorithm based on NIST Standard. In the application, there are two schemes, namely the protection and verification scheme. This research uses black-box testing and white-box testing to test the software input, output, and code without testing the process and design that occurs in the system. We demonstrated the implementation of cryptography in Secure Electronic Health Record Information (SEHR). The implementation of encryption and digital signature in this research can prevent archive thievery which is shown on implementation and is proven on the test.

Question: How to implement encryption and digital signature in secure electronic health record?