Query: Subjectivity and Sentiment Analysis of Modern Standard Arabic

Relevant passages:
Sentiment Analyzer: Extracting Sentiments about a Given Topic using Natural Language Processing Techniques <=SEP=> We present Sentiment Analyzer (SA) that extracts sentiment (or opinion) about a subject from online text documents. Instead of classifying the sentiment of an entire document about a subject, SA detects all references to the given subject, and determines sentiment in each of the references using natural language processing (NLP) techniques. Our sentiment analysis consists of 1) a topic specific feature term extraction, 2) sentiment extraction, and 3) (subject, sentiment) association by relationship analysis. SA utilizes two linguistic resources for the analysis: the sentiment lexicon and the sentiment pattern database. The performance of the algorithms was verified on online product review articles (“digital camera” and “music” reviews), and more general documents including general webpages and news articles.

Recognizing Contextual Polarity: An Exploration of Features for Phrase-Level Sentiment Analysis <=SEP=> Many approaches to automatic sentiment analysis begin with a large lexicon of words marked with their prior polarity (also called semantic orientation). However, the contextual polarity of the phrase in which a particular instance of a word appears may be quite different from the word's prior polarity. Positive words are used in phrases expressing negative sentiments, or vice versa. Also, quite often words that are positive or negative out of context are neutral in context, meaning they are not even being used to express a sentiment. The goal of this work is to automatically distinguish between prior and contextual polarity, with a focus on understanding which features are important for this task. Because an important aspect of the problem is identifying when polar terms are being used in neutral contexts, features for distinguishing between neutral and polar instances are evaluated, as well as features for distinguishing between positive and negative contextual polarity. The evaluation includes assessing the performance of features across multiple machine learning algorithms. For all learning algorithms except one, the combination of all features together gives the best performance. Another facet of the evaluation considers how the presence of neutral instances affects the performance of features for distinguishing between positive and negative polarity. These experiments show that the presence of neutral instances greatly degrades the performance of these features, and that perhaps the best way to improve performance across all polarity classes is to improve the system's ability to identify when an instance is neutral.

Recognizing subjectivity: a case study in manual tagging <=SEP=> In this paper, we describe a case study of a sentence-level categorization in which tagging instructions are developed and used by four judges to classify clauses from the Wall Street Journal as either subjective or objective. Agreement among the four judges is analyzed, and, based on that analysis, each clause is given a nal classiication. To provide empirical support for the classiications, correlations are assessed in the data between the subjective category and a basic semantic class posited by Quirk et al. (1985).

Determining the Sentiment of Opinions <=SEP=> Identifying sentiments (the affective parts of opinions) is a challenging problem. We present a system that, given a topic, automatically finds the people who hold opinions about that topic and the sentiment of each opinion. The system contains a module for determining word sentiment and another for combining sentiments within a sentence. We experiment with various models of classifying and combining sentiment at word and sentence levels, with promising results.

The Penn Arabic Treebank : Building a Large-Scale Annotated Arabic Corpus <=SEP=> From our three year experience of developing a large-scale corpus of annotated Arabic text, our paper will address the following: (a) review pertinent Arabic language issues as they relate to methodology choices, (b) explain our choice to use the Penn English Treebank style of guidelines, (requiring the Arabic-speaking annotators to deal with a new grammatical system) rather than doing the annotation in a more traditional Arabic grammar style (requiring NLP researchers to deal with a new system); (c) show several ways in which human annotation is important and automatic analysis difficult, including the handling of orthographic ambiguity by both the morphological analyzer and human annotators; (d) give an illustrative example of the Arabic Treebank methodology, focusing on a particular construction in both morphological analysis and tagging and syntactic analysis and following it in detail through the entire annotation process, and finally, (e) conclude with what has been achieved so far and what remains to be done.

Algorithms for continuous queries: A geometric approach <=SEP=> Algorithms for Continuous Queries: A Geometric

Mapping the U.S. Political Blogosphere: Are Conservative Bloggers More Prominent? <=SEP=> Weblogs are now a key part of online culture, and social scientists are interested in characterising the networks formed by bloggers and measuring their extent and impact in areas such as politics. However, researchers wishing to conduct quantitative social science analysis of the blogging phenomenon are faced with the challenge of using new methods of data collection and analysis largely derived from fields outside of the social sciences, such as the information sciences. This paper presents an overview of one new approach for collecting and analysing weblog data, and illustrates this approach in the context of a preliminary quantitative analysis of online networks formed by a sample of North-American “A-list” political bloggers. There are two aims to this paper. First is to assess (using different data and methods) the conclusion of Adamic and Glance (2005) that there are significant differences in the behaviour of liberal and conservative bloggers, with the latter forming more dense patterns of linkages. We find broad support for this conclusion, and empirically assess the implications of differences in conservative/liberal linking behaviour for the online visibility of different political messages or ideologies. The second aim is to highlight the role of web mining and data visualisation in the analysis of weblogs, and the opportunities and challenges inherent in this new field of research.

Semantic Facial Expression Editing using Autoencoded Flow <=SEP=> High-level manipulation of facial expressions in images — such as changing a smile to a neutral expression — is challenging because facial expression changes are highly non-linear, and vary depending on the appearance of the face. We present a fully automatic approach to editing faces that combines the advantages of flow-based face manipulation with the more recent generative capabilities of Variational Autoencoders (VAEs). During training, our model learns to encode the flow from one expression to another over a low-dimensional latent space. At test time, expression editing can be done simply using latent vector arithmetic. We evaluate our methods on two applications: 1) single-image facial expression editing, and 2) facial expression interpolation between two images. We demonstrate that our method generates images of higher perceptual quality than previous VAE and flow-based methods.

Reliability of measurements of muscle tone and muscle power in stroke patients. <=SEP=> OBJECTIVES
to establish the reliability of the modified Ashworth scale for measuring muscle tone in a range of muscle groups (elbow, wrist, knee and ankle; flexors and extensors) and of the Medical Research Council scale for measuring muscle power in the same muscle groups and their direct antagonists.


DESIGN
a cross-sectional study involving repeated measures by two raters. We estimated reliability using the kappa statistic with quadratic weights (Kw).


SETTING
an acute stroke ward, a stroke rehabilitation unit and a continuing care facility.


SUBJECTS
people admitted to hospital with an acute stroke-35 patients, median age 73 (interquartile range 65-80), 20 men and 15 women.


RESULTS
inter- and intra-rater agreement for the measurement of power was good to very good for all tested muscle groups (Kw = 0.84-0.96, Kw = 0.70-0.96). Inter- and intra-rater agreement for the measurement of tone in the elbow, wrist and knee flexors was good to very good (Kw = 0.73-0.96, Kw = 0.77-0.94). Inter- and intra-rater agreement for the measurement of tone in the ankle plantarflexors was moderate to good (Kw = 0.45-0.51, Kw = 0.59-0.64).


CONCLUSIONS
the Medical Research Council scale was reliable in the tested muscle groups. The modified Ashworth scale demonstrated reliability in all tested muscle groups except the ankle plantarflexors. If reliable measurement of tone at the ankle is required for a specific purpose (e.g. to measure the effect of therapeutic intervention), further work will be necessary.

Microservice Ambients: An Architectural Meta-Modelling Approach for Microservice Granularity <=SEP=> Isolating fine-grained business functionalities byboundaries into entities called microservices is a core activityunderlying microservitization. We define microservitization asthe paradigm shift towards microservices. Determining theoptimal microservice boundaries (i.e. microservice granularity) is among the key microservitization design decisions thatinfluence the Quality of Service (QoS) of the microservice applicationat runtime. In this paper, we provide an architecturecentricapproach to model this decision problem. We build onambients — a modelling approach that can explicitly capturefunctional boundaries and their adaptation. We extend the aspect-oriented architectural meta-modelling approach of ambients—AMBIENT-PRISMA — with microservice ambients. A microservice ambient is a modelling concept that treatsmicroservice boundaries as an adaptable first-class entity. Weuse a hypothetical online movie subscription-based systemto capture a microservitization scenario using our aspectorientedmodelling approach. The results show the ability ofmicroservice ambients to express the functional boundary of amicroservice, the concerns of each boundary, the relationshipsacross boundaries and the adaptations of these boundaries. Additionally, we evaluate the expressiveness and effectivenessof microservice ambients using criteria from ArchitectureDescription Language (ADL) classification frameworkssince microservice ambients essentially support architecturedescription for microservices. The evaluation focuses on thefundamental modelling constructs of microservice ambientsand how they support microservitization properties such asutility-driven design, tool heterogeneity and decentralised governance. The evaluation highlights how microservice ambientssupport analysis, evolution and mobility/location awarenesswhich are significant to quality-driven microservice granularityadaptation. The evaluation is general and irrespective of theparticular application domain and the business competenciesin that domain.

Action Anticipation with RBF Kernelized Feature Mapping RNN <=SEP=> We introduce a novel Recurrent Neural Network-based algorithm for future video feature generation and action anticipation called feature mapping RNN . Our novel RNN architecture builds upon three effective principles of machine learning, namely parameter sharing, Radial Basis Function kernels and adversarial training. Using only some of the earliest frames of a video, the feature mapping RNN is able to generate future features with a fraction of the parameters needed in traditional RNN. By feeding these future features into a simple multilayer perceptron facilitated with an RBF kernel layer, we are able to accurately predict the action in the video. In our experiments, we obtain 18% improvement on JHMDB-21 dataset, 6% on UCF101-24 and 13% improvement on UT-Interaction datasets over prior stateof-the-art for action anticipation.

Chip Level Techniques for EMI Reduction in LCD Panels <=SEP=> This paper presents chip level techniques to improve electro-magnetic interference (EMI) characteristics of LCD-TV panels. A timing controller (TCON) uses over-driving algorithms to improve the response time of liquid crystals (LC). Since this algorithm needs previous frame data, external memory such as double data rate synchronous DRAM (DDR SDRAM) is widely used as a frame buffer. A TTL interface between the TCON and memory is used for read and write operations, generating EMI noise. For reduction of this EMI, three methods are described. The first approach is to reduce the driving current of data I/O buffers. The second is to adopt spread spectrum clock generation (SSCG), and the third is to apply a proposed algorithm which minimizes data transitions. EMI measurement of a 32" LCD-TV panel shows that these approaches are very effective for reduction of EMI, achieving 20dB reduction at 175MHz.

A Two-Stage Iterative Decoding of LDPC Codes for Lowering Error Floors <=SEP=> In iterative decoding of LDPC codes, trapping sets often lead to high error floors. In this work, we propose a two-stage iterative decoding to break trapping sets. Simulation results show that the error floor performance can be significantly improved with this decoding scheme.

Strategic Directions in Artificial Intelligence <=SEP=> —constructing intelligent machines, whether or not these operate in the same way as people do; —formalizing knowledge and mechanizing reasoning, both commonsense and refined expertise, in all areas of human endeavor; —using computational models to understand the psychology and behavior of people, animals, and artificial agents; and —making working with computers as easy and as helpful as working with skilled, cooperative, and possibly expert people.

The digital platform: a research agenda <=SEP=> As digital platforms are transforming almost every industry today, they are slowly finding their way into the mainstream information systems (IS) literature. Digital platforms are a challenging research object because of their distributed nature and intertwinement with institutions, markets and technologies. New research challenges arise as a result of the exponentially growing scale of platform innovation, the increasing complexity of platform architectures, and the spread of digital platforms to many different industries. This paper develops a research agenda for digital platforms research in IS. We recommend researchers seek to (1) advance conceptual clarity by providing clear definitions that specify the unit of analysis, degree of digitality and the sociotechnical nature of digital platforms; (2) define the proper scoping of digital platform concepts by studying platforms on different architectural levels and in different industry settings; and (3) advance methodological rigour by employing embedded case studies, longitudinal studies, design research, data-driven modelling and visualization techniques. Considering current developments in the business domain, we suggest six questions for further research: (1) Are platforms here to stay?; (2) How should platforms be designed?; (3) How do digital platforms transform industries?; (4) How can data-driven approaches inform digital platforms research?; (5) How should researchers develop theory for digital platforms?; and (6) How do digital platforms affect everyday life?

Theory and Application of Magnetic Flux Leakage Pipeline Detection <=SEP=> Magnetic flux leakage (MFL) detection is one of the most popular methods of pipeline inspection. It is a nondestructive testing technique which uses magnetic sensitive sensors to detect the magnetic leakage field of defects on both the internal and external surfaces of pipelines. This paper introduces the main principles, measurement and processing of MFL data. As the key point of a quantitative analysis of MFL detection, the identification of the leakage magnetic signal is also discussed. In addition, the advantages and disadvantages of different identification methods are analyzed. Then the paper briefly introduces the expert systems used. At the end of this paper, future developments in pipeline MFL detection are predicted.

Automatic detection of incomplete requirements via symbolic analysis <=SEP=> The usefulness of a system specification depends in part on the completeness of the requirements. However, enumerating all necessary requirements is difficult, especially when requirements interact with an unpredictable environment. A specification built with an idealized environmental view is incomplete if it does not include requirements to handle non-idealized behavior. Often incomplete requirements are not detected until implementation, testing, or worse, after deployment. Even when performed during requirements analysis, detecting incomplete requirements is typically an error prone, tedious, and manual task. This paper introduces Ares, a design-time approach for detecting incomplete requirements decomposition using symbolic analysis of hierarchical requirements models. We illustrate our approach by applying Ares to a requirements model of an industry-based automotive adaptive cruise control system. Ares is able to automatically detect specific instances of incomplete requirements decompositions at design-time, many of which are subtle and would be difficult to detect, either manually or with testing.

Internet-based peer support for parents: a systematic integrative review. <=SEP=> OBJECTIVES
The Internet and social media provide various possibilities for online peer support. The aim of this review was to explore Internet-based peer-support interventions and their outcomes for parents.


DESIGN
A systematic integrative review.


DATA SOURCES
The systematic search was carried out in March 2014 in PubMed, Cinahl, PsycINFO and Cochrane databases.


REVIEW METHODS
Two reviewers independently screened the titles (n=1793), abstracts and full texts to decide which articles should be chosen. The inclusion criteria were: (1) an Internet-based community as an intervention, or at least as a component of an intervention; (2) the participants in the Internet-based community had to be mothers and/or fathers or pregnant women; (3) the parents had to interact and communicate with each other through the Internet-based community. The data was analysed using content analysis. When analysing peer-support interventions only interventions developed by researchers were included and when analysing the outcomes for the parents, studies that focused on mothers, fathers or both parents were separated.


RESULTS
In total, 38 publications met the inclusion criteria. Most of the studies focused on Internet-based peer support between mothers (n=16) or both parents (n=15) and seven focused on fathers. In 16 studies, the Internet-based interventions had been developed by researchers and 22 studies used already existing Internet peer-support groups, in which any person using the Internet could participate. For mothers, Internet-based peer support provided emotional support, information and membership in a social community. For fathers, it provided support for the transition to fatherhood, information and humorous communication. Mothers were more active users of Internet-based peer-support groups than fathers. In general, parents were satisfied with Internet-based peer support. The evidence of the effectiveness of Internet-based peer support was inconclusive but no harmful effects were reported in these reviewed studies.


CONCLUSIONS
Internet-based peer support provided informational support for parents and was accessible despite geographical distance or time constraints. Internet-based peer support is a unique form of parental support, not replacing but supplementing support offered by professionals. Experimental studies in this area are needed.

A Rule-Based Framework of Metadata Extraction from Scientific Papers <=SEP=> Most scientific documents on the web are unstructured or semi-structured, and the automatic document metadata extraction process becomes an important task. This paper describes a framework for automatic metadata extraction from scientific papers. Based on a spatial and visual knowledge principle, our system can extract title, authors and abstract from scientific papers. We utilize format information such as font size and position to guide the metadata extraction process. The experiment results show that our system achieves a high accuracy in header metadata extraction which can effectively assist the automatic index creation for digital libraries.

Battery-Draining-Denial-of-Service Attack on Bluetooth Devices <=SEP=> We extend the Xen virtual machine monitor with the ability to host a hundred of virtual machines on a single physical node. Similarly to a demand paging of virtual memory, we page out idle virtual machines making them available on demand. Paging is transparent. An idle virtual machine remains fully operational. It is able to respond to external events with a delay comparable to a delay under a medium load. To achieve desired degree of consolidation, we identify and leave in memory only a minimal working set of pages required to maintain the illusion of running VM and respond to external events. To keep the number of active pages small without harming performance dramatically, we build a correspondence between every event and its working set. Reducing a working set further, we implement a copy-on-write page sharing across virtual machines running on the same host. To decrease resources occupied by a virtual machine’s file system, we implement a copy-on-write storage and golden imaging.

Real-time motion planning methods for autonomous on-road driving: State-of-the-art and future research directions <=SEP=> Currently autonomous or self-driving vehicles are at the heart of academia and industry research becauseof itsmulti-faceted advantages that includes improved safety, reduced congestion, lower emissions and greater mobility. Software is the key driving factor underpinning autonomy within which planning algorithms that are responsible for mission-critical decision making hold a significant position. While transporting passengers or goods from a givenorigin to agivendestination,motionplanningmethods incorporate searching for apath to follow, avoiding obstacles and generating the best trajectory that ensures safety, comfort and efficiency. A range of different planning approaches have beenproposed in the literature. Thepurpose of this paper is to reviewexisting approaches and then compare and contrast different methods employed for the motion planning of autonomous on-road driving that consists of (1)findingapath, (2) searching for the safestmanoeuvre and (3)determining themost feasible trajectory. Methods developed by researchers in each of these three levels exhibit varying levels of complexity and performance accuracy. This paper presents a critical evaluation of each of these methods, in terms of their advantages/disadvantages, inherent limitations, feasibility, optimality, handling of obstacles and testing operational environments. Based on a critical review of existingmethods, research challenges to address current limitations are identified and future research directions are suggested so as to enhance the performanceofplanningalgorithmsat all three levels. Somepromising areasof future focushave been identified as the use of vehicular communications (V2V and V2I) and the incorporation of transport engineering aspects in order to improve the look-ahead horizon of current sensing technologies that are essential for planning with the aim of reducing the total cost of driverless vehicles. This critical reviewon planning techniques presented in this paper, along with theassociateddiscussions on their constraints and limitations, seek to assist researchers in accelerating development in the emerging field of autonomous vehicle research. Crown Copyright 2015 Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

MonoPerfCap : Human Performance Capture from Monocular Video WEIPENGXU , AVISHEKCHATTERJEE , MICHAELZOLLHÖFER , HELGERHODIN , DUSHYANTMEHTA <=SEP=> We present the first marker-less approach for temporally coherent 3D performance capture of a human with general clothing from monocular video. Our approach reconstructs articulated human skeleton motion as well as medium-scale non-rigid surface deformations in general scenes. Human performance capture is a challenging problem due to the large range of articulation, potentially fast motion, and considerable non-rigid deformations, even from multi-view data. Reconstruction from monocular video alone is drastically more challenging, since strong occlusions and the inherent depth ambiguity lead to a highly ill-posed reconstruction problem. We tackle these challenges by a novel approach that employs sparse 2D and 3D human pose detections from a convolutional neural network using a batch-based pose estimation strategy. Joint recovery of per-batch motion allows to resolve the ambiguities of the monocular reconstruction problem based on a low dimensional trajectory subspace. In addition, we propose refinement of the surface geometry based on fully automatically extracted silhouettes to enable medium-scale non-rigid alignment. We demonstrate state-of-the-art performance capture results that enable exciting applications such as video editing and free viewpoint video, previously infeasible from monocular video. Our qualitative and quantitative evaluation demonstrates that our approach significantly outperforms previous monocular methods in terms of accuracy, robustness and scene complexity that can be handled.

A linguistic theory of translation : an essay in applied linguistics <=SEP=> It's coming again, the new collection that this site has. To complete your curiosity, we offer the favorite linguistic theory of translation an essay in applied linguistics book as the choice today. This is a book that will show you even new to old thing. Forget it; it will be right for you. Well, when you are really dying of linguistic theory of translation an essay in applied linguistics, just pick it. You know, this book is always making the fans to be dizzy if not to find.

A theory of formal synthesis via inductive learning <=SEP=> Formal synthesis is the process of generating a program satisfying a high-level formal specification. In recent times, effective formal synthesis methods have been proposed based on the use of inductive learning. We refer to this class of methods that learn programs from examples as formal inductive synthesis. In this paper, we present a theoretical framework for formal inductive synthesis. We discuss how formal inductive synthesis differs from traditional machine learning. We then describe oracle-guided inductive synthesis (OGIS), a framework that captures a family of synthesizers that operate by iteratively querying an oracle. An instance of OGIS that has had much practical impact is counterexample-guided inductive synthesis (CEGIS). We present a theoretical characterization of CEGIS for learning any program that computes a recursive language. In particular, we analyze the relative power of CEGIS variants where the types of counterexamples generated by the oracle varies. We also consider the impact of bounded versus unbounded memory available to the learning algorithm. In the special case where the universe of candidate programs is finite, we relate the speed of convergence to the notion of teaching dimension studied in machine learning theory. Altogether, the results of the paper take a first step towards a theoretical foundation for the emerging field of formal inductive synthesis.

NAVSTAR: Global positioning system&#8212;Ten years later <=SEP=> With the award of one of the first multiyear procurements to be authorized by the Congress, the Department of Defense celebrates the tenth anniversary of a major Joint-Service / Agency program that promises to revolutionize the art and science of navigation. This contract, totaling 1.17 billion dollars, will result in delivery by the end of this decade of 28 satellites that are to become the heart of the NAVSTAR Global Positioning System (GPS). This paper traces the history of this program from its inception, identifying and discussing the major technologies that made it all possible. In so doing, the concept of operations of the entire system, including the satellites, their associated ground-based control network, and the family of user equipment being developed and tested to meet the broad scope of Department of Defence positioning and navigation requirements is introduced.

Culture and Institutions <=SEP=> A growing body of empirical work measuring different types of cultural traits has shown that culture matters for a variety of economic outcomes. This paper focuses on one specific aspect of the relevance of culture: its relationship to institutions. We review work with a theoretical, empirical, and historical bent to assess the presence of a two-way causal effect between culture and institutions. 1 We thank Benjamin Friedman and Andrei Shleifer for useful conversations and Janet Currie, Steven Durlauf, and six anonymous referees for excellent comments.

Bayesian Grasp Planning <=SEP=> We present a Bayesian framework for grasp planning that takes into account uncertainty in object shape or pose, as well as robot motion error. When trying to grasp objects based on noisy sensor data, a common problem is errors in perception, which cause the geometry or pose of the object to be uncertain. For each hypothesis about the geometry or pose of the object to be grasped, different sets of grasps can be planned. Of the resulting grasps, some are likely to work only if particular hypotheses are true, but some may work on most or even all hypotheses. Likewise, some grasps are easily broken by small errors in robot motion, but other grasps are robust to such errors. Our probabilistic framework takes into account all of these factors while trying to estimate the overall probability of success of each grasp, allowing us to select grasps that are robust to incorrect object recognition as well as motion error due to imperfect robot calibration. We demonstrate our framework while using the PR2 robot to grasp common household objects.

Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization. <=SEP=> An iterative algorithm, based on recent work in compressive sensing, is developed for volume image reconstruction from a circular cone-beam scan. The algorithm minimizes the total variation (TV) of the image subject to the constraint that the estimated projection data is within a specified tolerance of the available data and that the values of the volume image are non-negative. The constraints are enforced by the use of projection onto convex sets (POCS) and the TV objective is minimized by steepest descent with an adaptive step-size. The algorithm is referred to as adaptive-steepest-descent-POCS (ASD-POCS). It appears to be robust against cone-beam artifacts, and may be particularly useful when the angular range is limited or when the angular sampling rate is low. The ASD-POCS algorithm is tested with the Defrise disk and jaw computerized phantoms. Some comparisons are performed with the POCS and expectation-maximization (EM) algorithms. Although the algorithm is presented in the context of circular cone-beam image reconstruction, it can also be applied to scanning geometries involving other x-ray source trajectories.

Iterative Adaptive Approaches to MIMO Radar Imaging <=SEP=> Multiple-input multiple-output (MIMO) radar can achieve superior performance through waveform diversity over conventional phased-array radar systems. When a MIMO radar transmits orthogonal waveforms, the reflected signals from scatterers are linearly independent of each other. Therefore, adaptive receive filters, such as Capon and amplitude and phase estimation (APES) filters, can be directly employed in MIMO radar applications. High levels of noise and strong clutter, however, significantly worsen detection performance of the data-dependent beamformers due to a shortage of snapshots. The iterative adaptive approach (IAA), a nonparametric and user parameter-free weighted least-squares algorithm, was recently shown to offer improved resolution and interference rejection performance in several passive and active sensing applications. In this paper, we show how IAA can be extended to MIMO radar imaging, in both the negligible and nonnegligible intrapulse Doppler cases, and we also establish some theoretical convergence properties of IAA. In addition, we propose a regularized IAA algorithm, referred to as IAA-R, which can perform better than IAA by accounting for unrepresented additive noise terms in the signal model. Numerical examples are presented to demonstrate the superior performance of MIMO radar over single-input multiple-output (SIMO) radar, and further highlight the improved performance achieved with the proposed IAA-R method for target imaging.

You Cannot Sense My PINs: A Side-Channel Attack Deterrent Solution Based on Haptic Feedback on Touch-Enabled Devices <=SEP=> In this paper, we introduce a novel and secure solution to mitigate side-channel attacks to capture the PINs like touchID and other credentials of touch-enabled devices. Our approach can protect haptic feedback enabled devices from potential direct observation techniques such as cameras and motion sense techniques including such as accelerometers in smart-watch. Both attacks use the concept of shoulder surfing in social engineering and were published recently (CCS'14 and CCS'15). Hand-held devices universally employ small vibration motors as an inexpensive way to provide haptic feedback. The strength of the haptic feedback depends on the brand and the device manufacturer. They are usually strong enough to produce sliding movement and make audible noises if the device is resting on the top of a desk when the vibration motor turns. However, when the device is held in the hand the vibration can only be sensed by the holder; it is usually impossible or uncertain for an observer to know when the vibration motor turns. Our proposed solution uses the haptic feedback to inform the internal state of the keypad to the user and takes advantage of the fact that the effect of haptic feedback can be easily cloaked in such a way that direct observation techniques and indirect sensing techniques will fail. We develop an application on Android cell phones to demonstrate it and invite users to test the code. Moreover, we use real smart-watch to sense the vibration of Android cell phones. Our experimental results show that our approach can mitigate the probability of sensing a 4-digit or 6-digit PINs using smart-watch to below practical value. Our approach also can mitigate the probability of recognizing a 4-digit or 6-digit PINs using a camera within 1 meter to below practical value because the user does not need to move his or her hand during the internal states to input different PINs.