Reviewerly/exHarmony huggingface dataset:
A Fragment Matching Evaluation Method Based on Character Structure

Information recovery is an important research topic in the field of information security, and assessing the degree to which fragments match is a key step in recovery algorithm. In this study, based on a character's structure in real document fragments, a novel measurment function for fragment matching is presented that can evaluate the degree of correlation between the fragments. In addition, the function is used as the judgment basis in the fragment search algorithm to determine whether a found match is the global optimum. The experimental results show that the proposed method can effectively inhibit information damage and noise interference that exist in real document fragments, and that it accurately reflects the degree to which the fragments match. The information in document can be effectively restored by this method.
Using Sequence to Sequence Model to Transform Recognized ASL Words to Understandable Sentences

There was widespread agreement that Communication can be a struggle for some deaf and hearing impaired people. The big breakthrough is the development of sign language (SL) which has enabled this category of people to communicate. SL has enabled them to integrate into modern society, and access to education and work. Although sign language is very well documented and taught it does not allow them to interact with all people. It still hard for them to conduct a real life as the rest of the society, for example, participating in work meetings, reading any books, taking classes at the university, nor to use the available means of communication, such as video chatting and conferencing. With the recent development in artificial intelligence solutions began to appear on the horizon to accentuate the integration of deaf and dumb people. This paper attempts to answer a small corner of these needs. It presents a technique for transforming sign language into understandable sentences that can in turn be synthesized into speech or sent as it is by email or SMS. The aim is to allow the society understand SL without making a learning effort. In order to show the feasibility of this approach, a real-time prototype is developed by integrating an existing sign recognition model.
Reduction of Data Leakage Using Software Streaming

With the increase in threats to IoT devices, interest in protecting sensitive data within such devices has intensified. For devices holding sensitive data and intellectual property software, such as military equipment, leakage of the confidential data contained within the device can cause catastrophic damage. Therefore, it is important to prevent such leakage of sensitive data. In this paper, we propose a method for reducing data leakage from military devices by minimizing the quantity of data that exist within the non-volatile memory of the device. To achieve minimization of the data loaded in non-volatile memory, we run the software in a streaming manner. However, as the execution of software over a network can result in suspension of the software depending on the state of the network, this approach can have a critical impact on system stability. Therefore, we also present a scheme to apply multi-channel communication to reduce software suspensions caused by network delays when the software is run in a streaming manner for the purpose of mitigating damage to the data leakage.
A Comparative Analysis Between Crisp and Fuzzy Data Clustering Approaches for Traditional and Bioinspired Algorithms

Partitional data clustering algorithms produce a relationship matrix between data and clusters, named membership matrix, which clusters can be treated as mutually exclusive (crisp) or not (fuzzy), according to data clustering approach used. Moreover, a partition obtained by a crisp algorithm can be fuzzified and so, the relationship between data and clusters be relaxed, such as in fuzzy data clustering approach. However, algorithms have your own heuristic and, iteratively, the behavior of a crisp algorithm can be different of that respective fuzzy version and, in addition, fuzzifying a crisp partition can produce different result in relation to crisp and fuzzy clustering algorithms. Therefore, this paper proposes a comparative analysis among results produced by fuzzy data clustering algorithms and their respective crisp versions and fuzzified partitions. The proposal is identify whether a fuzzy clustering algorithm can be replaced by its respective crisp with fuzzified partition, in terms of result quality. The experiments were performed to two traditional partitional algorithms and two bioinspired algorithms.
Possibilities of Using the Scratch Programming Environment at the First Stage of School Education (to the Problem Statement)

The article discusses approaches to the use of the Scrath programming environment in the educational process of primary school. The methodological manuals of S.N. Tur, T.P. Bokuchava, O. N. Burtaeva, describing the methodology for teaching programming, and various educational programming environments: LightBot, Little Wizzard, RoboMind. The possibilities that open up when using the Scrath programming environment in solving the problems of forming information literacy of younger students, organizing their educational research activities, as well as positive socialization are evaluated.
Retracing the Flow of the Stream: Investigating Kodi Streaming Services

Kodi is of one of the world’s largest open-source streaming platforms for viewing video content. Easily installed Kodi add-ons facilitate access to online pirated videos and streaming content by facilitating the user to search and view copyrighted videos with a basic level of technical knowledge. In some countries, there have been paid child sexual abuse organizations publishing/streaming child abuse material to an international paying clientele. Open source software used for viewing videos from the Internet, such as Kodi, is being exploited by criminals to conduct their activities. In this paper, we describe a new method to quickly locate Kodi artifacts and gather information for a successful prosecution. We also evaluate our approach on different platforms; Windows, Android and Linux. Our experiments show the file location, artifacts and a history of viewed content including their locations from the Internet. Our approach will serve as a resource to forensic investigators to examine Kodi or similar streaming platforms.
Web-to-Information-Base Access Solutions

This chapter aims to assist managers of information systems programs who are interested in successful implementations of World Wide Web technology to access information bases, including databases and knowledge bases. It discusses case studies of Web applications in systems and research programs sponsored by the Department of Defense, and by universities as well as Web-based access products and services developed in private industry. Web solutions that enable information access are described in four case studies: Web-based data access, Web-based meta data access, Web-based knowledge access, and network-centric warfare. The University of Texas has demonstrated knowledge-base access using the Internet with its Knowledge-Base Infrastructure project. Some Web sites provide access to knowledge bases that are actually collections of databases or documents through a system of point-and-click queries. The Web provides access to meteorological and oceanographic data, meta data for modeling and simulation, knowledge base development tools, and commercially available knowledge bases.
Priority Scheduling based Dynamic Path Planning System with Motion Feedback

Mobile Robots have become an integral part of the environment and one of the main focus is on multiple robot coordination systems. This research article proposes a modified grid-based A* path planning algorithm that can be used for the simultaneous planning and motion of mobile robots in a dynamic environment. The algorithm includes priority-based scheduling of robots for practical applications. It also takes into account, the re-planning of the path of the robot using motion feedback from encoders, in the case where the robot leaves the configuration space due to dynamic obstacles. A multi-robot system is set up to verify the proposed method of path planning.
A New Pixel Value Decomposition based Image Steganography Method

In this paper, we present a high quality data hiding method using pixel value decomposition that generates higher number of bit-planes than that of the native number representation. Battisti et. al. discussed a data hiding method based on the Fibonacci number bit-plane decomposition. This scheme was further improved by Dey et. al. by using the prime and natural number decompositions. The approach based on natural number decomposition generates 23 bitplanes, requiring a look-up table of large size and the approach based on prime number decomposition generates 15 bit-planes. The weights assigned to the bit-planes increases according to prime numbers and natural numbers. Having large weight values creates large variations in pixel values after embedding the secret data that will result in higher image distortion. In our proposed method, we use a novel set of weights of decomposition, by carefully selecting the weights of decomposition that generates 10 bit-planes. The weights of the first five LSB bits increase slowly and the remaining, grow exponentially. By doing this, the variation in the pixel values after embedding the secret data is quite small and also, due to less number of bit planes the size of lookup table is considerably reduced. As a result, our proposed method maintains less distortion of the stego-image and at the same time has smaller size of the lookup table.
A Method of Lower Limb Gait Based on Multi-sensor Data Fusion for Rehabilitation Robot

A method of gait movement of lower limbs for a rehabilitation robot is proposed in this article. The gait detection system is established using acceleration sensors, gyroscopes and magnetometers as the attitude detection devices. According to the movement mechanism of human limbs, attitude sensors are respectively installed in the lateral middle position of the left and right thighs and calves, and the collected data is transmitted to a microprocessor through IIC communication. The processing terminal displays the data curve in real time while saving the collected data. Since the acceleration sensors, magnetometers and gyroscopes all have a certain degree of zero drift, ellipsoid fitting which based on least squares method is employed to calibrate, and then quaternion method is adopted to solve the attitude algorithm. The second-order Kalman filtering for attitude compensation is used in this research work. Finally, the simulation and real experimental results proved that the ellipsoid fitting can be well calibrated, in addition, second-order Kalman filtering is capable of performing good attitude fusion. Furthermore, during walking, the characteristic states such as turning and unstable walking can be collected, which is more obvious than the states collected by the three-dimensional gait analyzer.
A Game Theoretic Approach For Deploying Forensic Ready Systems

Cyber incidents are occurring every day using various attack strategies. Deploying security solutions with strong configurations will reduce the attack surface and improve the forensic readiness, but will increase the security overhead and cost. In contrast, using moderate or low security configurations will reduce that overhead, but will inevitably decrease the investigation readiness. To avoid the use of cost-prohibitive approaches in developing forensic-ready systems, we present in this paper a game theoretic approach for deploying an investigation-ready infrastructure. The proposed game is a non-cooperative two-player game between an adaptive cyber defender that uses a cognitive security solution to increase the investigation readiness and reduce the attackers’ untraceability, and a cyber attacker that wants to execute non-provable attacks with a low cost. The cognitive security solution takes its strategic decision, mainly based on its ability to make forensic experts able to differentiate between provable identifiable, provable non-identifiable, and non-provable attack scenarios, starting from the expected evidences to be generated. We study the behavior of the two strategic players, looking for a mixed Nash equilibrium during competition and computing the probabilities of attacking and defending. A simulation is conducted to prove the efficiency of the proposed model in terms of the mean percentage of gained security cost, the number of stepping stones that an attacker creates and the rate of defender false decisions compared to two different approaches.
A Research on the Influencing Factors of Industrial Designers’ Potential Traits on Career Planning

Industrial designers often play an important role in the development of new products for the company and create huge economic benefits for the company. Industrial designers need to spend a huge amount of time and expense in the learning and training process, as well as purchasing expensive personal equipment for professional skills training, but the salary of the employment environment is not high. Therefore, this research uses the in-depth interview method to interview two industrial designers who have been employed in the workplace for more than five years to understand their growth background and analyze their career satisfaction. It is found that the growth stages of industrial designers can be roughly divided into three periods; the first is the period of interest germination, the second is the period of career enlightenment, and the third is the period of ideal realization. The training process of industrial designers takes a lot of time, spirit, financial resources, and material resources, but it is not proportional to their social status and salary income. Supporting industrial designers to continue to work hard in the workplace, the main reason can be found in industry Designers have four characteristics: the discoverer of the problem, the solver of the problem, the inspirer of fashion, and the builder of a better society. Through this research, it can be found that students who possess the characteristics of industrial designers during their study period should receive professional training early to avoid wasting educational resources.
Confirmation Sampling for Exact Nearest Neighbor Search

Locality-sensitive hashing (LSH), introduced by Indyk and Motwani in STOC '98, has been an extremely influential framework for nearest neighbor search in high-dimensional data sets. While theoretical work has focused on the approximate nearest neighbor problem, in practice LSH data structures with suitably chosen parameters are used to solve the exact nearest neighbor problem (with some error probability). Sublinear query time is often possible in practice even for exact nearest neighbor search, intuitively because the nearest neighbor tends to be significantly closer than other data points. However, theory offers little advice on how to choose LSH parameters outside of pre-specified worst-case settings.
U15-Logos: Unconstrained Logo Dataset with Evaluation by Deep learning Methods

Detecting the appearance of logos in images is applied to many applications, such as brand recognition for marketing analysis and intellectual property protection. It is a challenging problem in the computer vision field, especially in unconstrained images with a complex background, difference in sizes, a number of logos per image, contextual diversity with uncontrolled illumination, and low-resolution. In this work, we tackle this problem by first introducing a newly collected datasets containing 15 well-known brands, namely, U15-Logos (unconstrained logos) with 15000 images. In order to ease experimental evaluation and consider model adaptation, we use our standard dataset called F15-Logos (fundamental logos) with 15042 images for a crossing evaluation between U15-Logos and F15-Logos. Finally, we provide an evaluation of the state of the art models based on Deep learning including YOLO, Faster RCNN, Mask RCNN, RetinaNet in order to illustrate how well these models overcome unconstrained conditions. Comparative evaluations demonstrate the best performance on U15-Logos is about 89,4%.
A new dual-objective CD-CAT item selection method based on the Gini index

response theory, IRT)的计 算机化自适应测验(computerized adaptive testing, CAT)以"量体裁衣"的方式能更高效地实施终结性 评估。形成性评价用一个离散向量 α (常称为潜在 认知模式或知识状态)来帮助教师了解每个学生的 潜在认知状态, 为教师提供教学反馈, 以便更好地 "因材施教", 这有利于学生学业和教师职业发展, 基于认知诊断理论(cognitive diagnostic theory, CDT) 的 CAT 以"个性化"测验方式快速诊断被试认知的 长处和短板。教学需要终结性评价与形成性评价相 互结合, 既关注结果又关注过程, 使学习过程和对 学习结果的评价达到和谐统一。IRT-CAT 关注终结 性评价, CD-CAT (cognitive diagnostic computerized adaptive testing, CD-CAT)关注形成性评价, 两者结 合 的 双 目 标 CD-CAT (dual objective CD-CAT, Dual-CAT)可以将它们的优势互补, 从而更好地完
Text Web Templates Considered Harmful

For the last decades text-based templates have been the primary option to build dynamic web pages. Until today, no other alternative has rebutted this approach. Yet, using text-based templates has several drawbacks including: 1. blocking resolution, 2. programming languages heterogeneity, 3. limited set of templating features and 4. opinionated idioms. In this paper we show how a domain specific language (DSL) for HTML (such as HtmlFlow, Kotlinx.html or React JSX) can suppress the text-based templates limitations and outperform state-of-the-art template engines (such as JSP, Handlebars, Thymeleaf, and others) in well known benchmarks. To that end, we use the Spring Framework and the sample application PetClinic to show how a DSL for HTML provides unopinionated web templates with boundless resolving features only ruled by the host programming language (such as Java, Kotlin or JavaScript).
Aggregate Authentication for Massive Internet of Things in 5G Networks

Massive Internet of Things (IoT) applications are characterized by a massive number of low-powered devices with small data storage. In those applications, authentication is very important to guarantee the origin of data produced by each device. With such characteristics, the authentication scheme needs to have small footprint and low complexity computation. Likewise, the number of authentication signaling needs to be significantly reduced to accommodate massive amount of IoT devices trying to connect to the network simultaneously, which is similar to Denial of Service (DoS) attacks. In 3GPP TR 33.899 V1.3.0, an architecture of the authentication system that consists of the aggregation nodes and the authenticators is proposed. The aggregation nodes receive the authenticated data from the devices and send the aggregated authenticated data to the authenticators. In this article, we discuss the possibility to implement more efficient authentication scheme for a massive Internet of Things (IoT) applications enabled in 5G networks. In particular, we analyze the performance of the system using some signature aggregation methods and identify the main research challenges in this area.
Fashion-Sketcher: A Model for Producing Fashion Sketches of Multiple Categories

Fashion sketches play a critical role in the initial stages of fashion product design. This situation has motivated the development of artificial intelligence (AI) techniques for automatically generating fashion sketches. We present Fashion-Sketcher, a hybrid deep generative model able to generate multi-class fashion sketches through two stages. At the first stage, we design a Contour Generation Network to synthesize contour images with a given categorical vector. At the second stage, we design a Sketch Translation Network to translate the contour images to the sketch images by extending the StyleGAN2 model to the conditional version. The quantitative and qualitative analysis demonstrates that our method is capable of synthesizing high-quality fashion sketches.
High Fidelity Virtual Representation of Object Surface Material Based on Compression Perception

The color and texture data used in traditional digitalization fields based on three primaries (RGB) have multiple non-linear editing, which causes color distortion and unable to meet demand of protection, utilization of cultural heritage. Whereas the digitalization approaches based on multi-spectral has aroused widespread interest by uniquely objectively expressing the material color of object surface. This project intends to use multi-spectral method (multi-spectral reflection rate and transmission rate of objects) to objectively express the material color of surface, beyond the limit of three primaries (RGB) expression, establishes equipment-free, environment-free color acquisition method and expression model combining compressive sensing technology. High-fidelity virtual reappearance algorithm based on multi-spectral data is studied, which is based on existing high-realistic rendering technology. The compressive sensing technology is utilized to speed up virtual appearance. The above approaches could resolve the distortion problem of the application fields requiring high color fidelity. A multi-spectral software and hardware prototype system for data acquisition, modeling, high-fidelity virtual appearance will be implemented based on above algorithm.
Pervasive Information Architecture in Service Design Blueprints: Walking Tours

As new scenarios bring new interaction possibilities, users create their experiences pervasively, blending physical and digital spaces of interaction and information. From the UX design perspective, the pervasive interaction is planned from digital space, creating connections to the physical context of use in mind. On the other hand, from the service design perspective, the experience is mostly planned from physical space and digital interactions are inserted as support processes to help actors build consumers’ experience. Independently of starting point (physical or digital), the full experience journey is put together by dynamic informational spaces, as many actors interfere and add content and context to the planned experience. This paper presents a low budget experiment of mapping touristic routes from service design perspective to further analysis of its informational spaces, in an attempt to discuss the integration of pervasive information architecture into service design.
Extensions in graph normal form

Abstract Graph normal form, introduced earlier for propositional logic, is shown to be a normal form also for first-order logic. It allows to view syntax of theories as digraphs, while their semantics as kernels of these digraphs. Graphs are particularly well suited for studying circularity, and we provide some general means for verifying that circular or apparently circular extensions are conservative. Traditional syntactic means of ensuring conservativity, like definitional extensions or positive occurrences guaranteeing exsitence of fixed points, emerge as special cases.