Reviewerly/exHarmony huggingface dataset:
An Unsupervised Anomaly Detection Algorithm for Time Series Big Data

Many time series anomaly detection algorithms are hard to be applied in real scenarios for two reasons. Firstly some of them are supervised since training data is required to define the normal behavior, but it is expensive to annotate the normal part for large volume data. Secondly, many algorithms are parameter-laden, which are hard to be generalized to different dataset. This paper is motivated to overcome these disadvantages. It is believed that a normal behavior is a subsequence which is similar to some subsequences in a time series while an anomaly is a subsequence which is distinct from the others. In order to improve the efficiency of searching anomaly, we first select candidate anomalies rather than check all subsequences. We roughly distinguish the candidate anomalies from normal subsequences by transforming each subsequence into a string. If a string corresponds to only one subsequence, then it is a candidate anomaly. And the subsequences of the same string represent a kind of normal behavior. Secondly, similarity threshold is calculated according to the similarity between normal behaviors. If the similarity between a candidate anomaly and its nearest neighbor is lower than the threshold, then this candidate is determined to be anomalous. We conduct extensive experiments on benchmark datasets from diverse domains and compare our method with the state-of-the-art method. The empirical results show that our method can reach high detection rate in an unsupervised and parameter-lite manner.
Tuning parameters of the isochronous endpoint of a USB peripheral device in a multimedia system

Data exchange in the multimedia system between the camera and the computer can be realized via the USB communication interface. Applying the USB port requires tuning the port parameters in such systems to ensure the quality of the services (multimedia) provided. The tuning of the communication system depends on such selection of port parameters to optimize the imposed criteria. The authors proposed a quality criterion based on the USB isochronous interval. The paper briefly presents the quality measure and the transmission model of the data package. Next, the problem of tuning the USB port was presented based on the selected parameters (MaxPacketSize and MaxBurst) of the endpoint of the peripheral device. To assess the impact of the selected parameter on the quality of services in the system, a statistical test for homoscedasticity of empirical distributions of isochronous intervals, was used. Besides the results of the conducted experiments for the selected parameters presented in the paper, the authors also tried to explain the obtained results in relation to the specification of the USB port.
Creating an EMR system to support mobile clinics in Haiti

While mobile clinic services have been tremendously helpful to patients in the under-developed areas, they often suffer from poor quality of patient management due to lack of capability for continuity of care. Collaborating with VillageMED, a US-based nonprofit that provides periodic medical services to Haiti communities, we investigated implications for the design of an EMR to support mobile clinics. Key design considerations we found include: (1) simplicity and ease of use, (2) seamless support of the existing clinical workflow through feature segmentation, and (3) flexibility to accommodate organizational and operational variability. Using the findings, we designed and implemented, through an iterative process, an EMR suitable for use in mobile clinics. We conclude by discussing design implications to improve quality of care in mobile clinics.
Mobile Applications Used for Human Rights

A mobile application is a computer program or application developed to run on a small handheld mobile device such as mobile phones, smartphones, PDAs, and so on. Such devices are sold with several apps bundled as pre-installed software, such as a web browser, email client, calendar, mapping program, and an app for buying music or other media or more apps. Apps that are not preinstalled are usually available through distribution platforms called app stores such as the Apple App Store, Google Play, Windows Phone Store, and BlackBerry App World, etc. Usage of mobile apps has become increasingly prevalent across mobile phone users in the world. A recent study reported that during the previous quarter, more mobile subscribers used apps than browsed the web on their devices. Thus, a mobile application can aid in the prosecution of human rights violations, atrocities, human trafficking, and child laboring. In this chapter, authors provide a comprehensive study, design patterns, usage of several mobile applications designed for protecting human rights.
Toward Human Motion Sensing: Design and Performance Evaluation of a Minimized Wearable Platform Using Inertial and TOA Sensors

Wearable sensors based applications have been widely used in various applications, such as health care, security monitoring and human-computer interaction. Despite remarkable research efforts and many encouraging advances in the past decade, accurate recognition of the human motions is still a challenging task. The existing studies mostly face the problems of sensor drift errors and the assumption of independent body part movement. In this study, we take the geometrical relation among joints into consideration and a corresponding platform is designed to obtain potential parameters and perform human motion capturing. CRLB is derived to evaluate the performance of proposed platform. The lower bound of motion sensing accuracy shows apparent reduction with applying our method. The sensing accuracy has an obvious promotion in the experiment results.
A Markov Random Field and Adaptive Regularization Embedded Level Set Segmentation Model Solving by Graph Cuts

This paper presents a novel Markov random field (MRF) and adaptive regularization embedded level set model for robust image segmentation and uses graph cuts optimization to numerically solve it. Firstly, a special MRF-based energy term in the form of level set formulation is constructed for strong local neighborhood modeling. Secondly, a regularization constraint with adaptive properties is imposed onto the proposed model with the following purposes: reduce the influence of noise, force the power exponent of the regularization process to change adaptively with image coordinates, and ensure the active contour does not pass through the weak object boundaries. Thirdly, graph cuts optimization is used to implement the numerical solution of the proposed model to obtain extremely fast convergence performance. The extensive and promising experimental results on wide variety of images demonstrate the excellent performance of the proposed method in both segmentation accuracy and convergence rate.
Mining Anomalies in Graph Data

Mining graph data is an important data mining task due to its significance in network analysis and several other contemporary applications. With this backdrop, this chapter explores the potential applications of outlier detection principles in graph/network data mining for anomaly detection. One of the focus areas is to detect arbitrary subgraphs of the input graph exhibiting deviating characteristics. In this direction, graph mining methods developed based on latest algorithmic techniques for detecting various kinds of anomalous subgraphs are explored here. It also includes an experimental study involving benchmark graph data sets to demonstrate the process of anomaly detection in network/graph data.
Harnessing Cloud Scalability to Hadoop Clusters

Apache Hadoop is a popular technology that proved itself as an effective and powerful framework for Big Data analytics. It broke from many of its predecessors in the “computing at scale” space by being designed to run in a distributed fashion across large amounts of commodity hardware instead of a few expensive computers. Many organizations have come to rely on Hadoop for dealing with the ever-increasing quantities of Big Data that they gather. “Harnessing cloud scalability to Hadoop clusters” means running Hadoop clusters on resources offered by a cloud provider on demand.
Detection of material zones on the surface of a steel–aluminum hybrid component using reflection models and a monochromatic fringe projection profilometry system

The limits of traditional lightweight engineering are being extended by the development of hybrid components. Lightweight potential is especially high when using dissimilar materials, e.g., a friction-welded steel-aluminum combination. An important factor for the mechanical properties of such a combination is the geometry and location of the joining zone between the materials. The geometry of these objects can be reconstructed by optical triangulation techniques such as fringe projection profilometry. In this paper, we present a method to robustly detect the different material zones on the surface of a hybrid steel-aluminum component. We use reflection models and data from a fringe projection profilometry system. The intensity values and 3D geometry data from the fringe projection system are used to estimate material-specific reflection parameters for each 3D point and detect different material areas based on a global threshold.
Dongba Hieroglyphic Similarity Measure Algorithm Based on Grid Resolution

Dongba hieroglyph is a kind of very primitive picture hieroglyphs; it has a characteristic of pictograph to express meaning by using pictures, but also has a feature of modern word to express the meaning with simple strokes, therefore the research on it has been less. In the paper, we start with the structural elements of Dongba hieroglyphs. By analyzing the constituent elements, structural, and writing habits, we give a preprocessing and classification algorithm for Dongba hieroglyphs. Our algorithm is simple, low in complexity and easy to implement. It can quickly retrieve and recognize different types of Dongba hieroglyph, and has better scale and translation invariance. The algorithm provides strong technical support for the study of glyphic formation in Dongba hieroglyph and also gives an important reference for the research on the retrieval and recognition of other pictographs.
Automatic intersection extraction and building arrangement with StarCraft II maps

In StarCraft, buildings arrangement near the intersections is one of most the critical strategic decisions in the early stage. The high time complexity of the buildings arrangement makes it difficult for AI bot to make the real-time decision. This paper presents an approach to analyze the intersection in StarCraft II maps. We propose a radar-like algorithm to automatically detect the intersection and use a designed heuristic search algorithm to arrange the building for building the wall. Our method can obtain the optimal solution while meeting the real-time requirement.
Towards Smartphone Operating System Identification

Smartphone reconnaissance, the first step to launch security attacks to a target smartphone, enables an adversary to tailor attacks by exploiting the known vulnerabilities of the target system. In this paper we investigate smartphone OS identification with encrypted traffic. We propose four algorithms to do that, which are based on the spectral analysis of the encrypted traffic. The algorithms are designed for high identification accuracy by removing noise frequency components and for high efficiency in terms of computation complexity. We evaluate the identification algorithms with smartphone traffic collected over three months. The experiment results show that the algorithms can identify the smartphone OS accurately. The identification accuracy can reach 100% with only 30 seconds of smartphone traffic.
Research on the User Fatigue of Household Appliances Human-Computer Interaction Based on Wearable Devices and Bare-Hand Gesture Recognition

Based on the analysis of gesture types and gesture recognition technology, this paper divides the function of TV operation interface, designs two sets of gestures based on wearable devices and bare-hand. Using the method of subjective and objective testing, it tests the user fatigue of the two sets of gestures. Finally, experimental results showed that bare-hand gesture interaction technology with its emphasis on natural, comfortable advantage, would become the main way of future home appliance gesture interaction.
Near-Separable Non-negative Matrix Factorization Using L1-Optimization

In this paper we propose a new LP-based formulation to solve near separable non negative matrix factorization (NMF) problem using L1 norm optimization. We also present a comprehensive experimental evaluation of the existing methods to solve separable NMF problem and compare them with the proposed formulation. The evaluation of this formulation on synthetic data shows that our new formulation gives significantly better quality of factorization as compared to the existing methods.
Giraff Meets KOaLa to Better Reason on Sensor Networks

Recent technological advancementsAmedeo, Cesta in Internet of Things and Cyber-Physical systems are fostering the diffusion of smart environments relying on sensor networksLuca, Coraci. Indeed, large and heterogeneous amount of data can beGabriella, Cortellessa provided by sensors deployed in user environments providing valuable knowledge to addressRiccardo, De Benedictis different user needs and enabling more effective and reliable solutionsAndrea, Orlandini as well as ensuring personalizationAlessandra, Sorrentino and dynamic adaptation. This paper presents a recent research initiative whose aim isAlessandro, Umbrico to realize autonomous and socially interacting robots by integrating sensor data representation and knowledge reasoning with decision making functionalities within a cognitive control architecture, called Knowledge-based cOntinuous Loop (KOaLa).
Intelligent Correction Predictor

This paper describes the industrial application of fault localization. In this work, we propose an efficient way to optimize the fault localization and code correction in a sustenance engineering setup with large code base industrial applications. We are leveraging machine learning and natural language processing algorithms to recommend technical objects for a given engineering defect. The solution learns from the past data of customer tickets and published engineering solutions and applies multi-label one-vs-the-rest Logistic regression for learning. For a given defect, the tool recommends five technical objects for debugging, thereby reducing the initial analysis time of support engineer. This reduction of analysis time makes a huge impact on solving the customer ticket in an efficient and timely manner. The solution is currently under pilot testing with 150 engineers to calibrate its gains.
Trend of speed analysis in accident reconstruction

Motorization produced traffic accidents and its conflicts to be brought into the court of law. The field of accident reconstruction was born to cope with these litigations. Essentially, traffic accident is a crime of negligence. Punishment and insurance payment depend upon the assessment of the case. Vehicle speed plays an important role in the ratio of fault and plays an important role as a standard of fault authorization. An analysis method has been developed ever since. Now in Japan, traffic accident is punished with a special law independent from the existing penal code. Speed analysis has become a more important factor under this law. Therefore speed analysis has a long historical path and still plays an important field within forensic science. Fundamental method of speed analysis has been long based on the application of basic physics principles. Recent evolution of electrical devices brought another approach to the speed analysis. Images of CCTV, drive recorders, and vehicle mounted electrical data are offering a good chance to analyze vehicle speed. We would like to review the speed analysis of the traditional methods and overview the trend of recent methods of the new era.
Specifying Weak Constraints in Processable English

Processable English (PENG) is a controlled natural language designed to specify and conceptualize knowledge in a human-readable and machine-processable way. PENG specifications can be translated unambiguously into executable answer set programs (ASP). In this paper we suggest an extension of the language PENGASP so that weak constraints can be expressed in controlled natural language and processed as part of an ASP program. In contrast to strong constraints that have always to be satisfied and are already part of the controlled natural language, we introduce weak constraints that can be weighted and prioritised and should be satisfied whenever possible. The addition of weak constraints to the controlled natural language PENGASP makes it possible to specify optimisation problems in a natural way.
Study of Icon Design for Indian Market: Preliminary Investigation

Icons on a product effectively communicate the actual functionality of the design. A poorly designed icon which fails to help its users understand about its functions not only affects the usability of the product but also directly reduces its acceptance in the market. More icons representing multi-functionalities of smart refrigerators have resulted in some of them becoming redundant due to lack of understanding by its users. Thus, empathizing with the target user groups in order to understand their needs and wants is a necessity which many existing icon designs fail to do. The study aims to evaluate the level of comprehension about these icons and the need to redesign or discard some of them by analyzing data through comprehension, stereotype, and strength test. Many of the present smart refrigerators carry icon designs, considering mental models of Western nation’s users and do not relate entirely to users of India.
Interactive minutes generation system based on hierarchical discussion structure

This research leads to the development of a system that generates minutes while the system and user interactively structure and summarize the discussion. The system can look back on a meeting from a specific viewpoint or purpose by sending an inquiry to the minutes, receiving the result, and perfor ming a new operation. To improve the reusability of the minutes, it is necessary to understand the semantic relationships among utterances at a deep level. We therefore propose a novel tree structure called the discussion time-span tree for representing a hierarchical discussion based on the relative importance of utterances derived from the meeting. The discussion time-span tree is a binary tree, each leaf of which corresponds to an utterance. Adjacent relevant utterances are hierarchically grouped, and the most important utterance becomes a head. In this way, the tree represents the implicit meaning and intention contained in meeting records, and can be used for summarization. Our system aims to grasp the main point of the meeting by interactively manipulating this tree structure and giving different viewpoints to each system user. An evaluation of the important utterance extraction using the proposed system showed that the score of ROUGE-2 was higher than that of the existing document summarizing technique. In a subsequent user evaluation conducted with ten participants, we found that the system can be used to grasp conference contents efficiently. The results of both evaluations demonstrate the usefulness of the system.
Design Templates in Purposeful Games: A Case Study of a Creative Decision-Making Game

Designers often work in time-constrained situations during the design process. Among others, one strategy that they use to overcome such difficulty is by using design templates or patterns. A design template is a pre-defined structure of solution, which can be repurposed based on different problem scenarios. The major advantage of using such a template is that the designer does not have to start from scratch, which gives him/her a head start. In this paper, we discuss the use of design templates in game design, which is an under explored area. We also present a case study of how we repurposed the game design template to build a creative decision-making game for novice project managers.
A local optimal method on DSA guiding template assignment with redundant/dummy via insertion

As an emerging manufacture technology, block copolymer directed self-assembly (DSA) is promising for via layer fabrication. Meanwhile, redundant via insertion is considered as an essential step for yield improvement. For better reliability and manufacturability, in this paper, we concurrently consider DSA guiding template assignment with redundant via and dummy via insertion at post-routing stage. Firstly, by analyzing the structure property of guiding templates, we propose a building-block based solution expression to discard redundant solutions. Then, honoring the compact solution expression, we construct a conflict graph with dummy via insertion, and then formulate the problem to an integer linear programming (ILP). To make a good trade-off between solution quality and runtime, we relax the ILP to an unconstrained nonlinear programming (UNP). Finally, a line search optimization algorithm is proposed to solve the UNP. Experimental results verify the effectiveness of our new solution expression and the efficiency of our proposed algorithm.
Context-Aware Agents for IoT Services

Internet of things is assured that it is used to connect huge number of objects which are connected to Internet that can be embedded with sensor. Objects can connect and exchange the data. In this paper, we characterize a data representation (text, image) by using agent-based architecture that is enabled by the sensors to represent the data with resources which are used to make possible the resources to communicate with agents. Here agent is used to exchange the information form agent to applications (health care, logistics, transportation, etc.) then all the information will be stored in the cloud. IoT provides us lot of sensor data; however, the data by themselves do not provide value unless we can turn them into actionable or intelligence, contextualized information, so for that we will go for nature-inspired algorithm to get the better solution.
An Analysis About the Defects of Windows UAC Mechanism

In order to deeply understand Windows security and explore the flaws of Windows UAC mechanism, the origin of UAC mechanism is firstly introduced, and then its implementation principles are analyzed. After that, various current UAC bypass methods are classified and different types of UAC bypass methods are elaborated on. Based on the understanding of the existing bypassing methods, the defects of the current UAC mechanism are discussed in depth, and the improvement scheme of the UAC mechanism is proposed.
A Framework for Risk Management in AI System Development Projects

It has been well-known that the chance of successfully delivering a software project within an allocated time and budget is very low. Most of the researches in this area have concluded that “user's requirements” of the systems is one of the most difficult risks to deal with in this case. Interestingly, until today, regardless of amount of effort put into this area, the possibility of project failure is still very high. The issue with requirement can be significantly increased when developing an artificial intelligence (AI) system, where one would like the systems to autonomously behave. This is because we are not only dealing with user's requirements, but we must also be able to deal with “system's behavior” that, in many cases, do not even exist during software development. This chapter discusses a preliminary work on a framework for risk management for AI systems development projects. The goal of this framework is to help project management in minimizing risk that can lead AI software projects to fail due to the inability to finish the projects on time and within budget.