Reviewerly/exHarmony huggingface dataset:
ON THE SMOOTHED PARAMETRIC ESTIMATION OF MIXING PROPORTION UNDER FIXED DESIGN REGRESSION MODEL

Abstract The present paper revisits an estimator proposed by Boes (1966) – James (1978), herein called BJ estimator, which was constructed for estimating mixing proportion in a mixed model based on independent and identically distributed (i.i.d.) random samples, and also proposes a completely new (smoothed) estimator for mixing proportion based on independent and not identically distributed (non-i.i.d.) random samples. The proposed estimator is nonparametric in true sense based on known “kernel function” as described in the introduction. We investigated the following results of the smoothed estimator under the non-i.i.d. set-up such as (a) its small sample behaviour is compared with the unsmoothed version (BJ estimator) based on their mean square errors by using Monte-Carlo simulation, and established the percentage gain in precision of smoothed estimator over its unsmoothed version measured in terms of their mean square error, (b) its large sample properties such as almost surely (a.s.) convergence and asymptotic normality of these estimators are established in the present work. These results are completely new in the literature not only under the case of i.i.d., but also generalises to non-i.i.d. set-up.
Emotional Design and Virtual Reality in Product Lifecycle Management (PLM)

As the potentials of technology grow, the embedding of IT advances in different fields and applications increases. A recent example is virtual reality and in particular the virtual product. The possibility of having a product in a virtual form allows creators and designers to efficiently manage the cycle of a product generation and evolution. The key advantage of the “virtual” is to have the product in advance, even in the conceptualization phase, with clear benefits in terms of consumptions of resources and, hence, sustainability. A potential customer could thus interact with a product-to-be and provide feedback about its look and feel, its usability, and, most of all, give an emotional response. In this context, the interaction between the virtual product and the future customer becomes a core point for the new approaches related to user-centred and user experience design, giving birth to a design methodology called “emotional design”. In particular, the study of facial expressions seems to be the more reliable and attractive aspect of it.
Does a Character’s Visual Style Affect Audience Empathy and Sympathy?

A believable virtual character is able to interact with the audience emotionally. To achieve believability, every component of the character from its movement to appearance must be designed carefully so that the character will elicit emotional responses such as empathy and sympathy from the viewers. However, to date, few studies have investigated what visual factors of a character trigger people’s empathetic and sympathetic responses. The purpose of this experimental study was to examine the effect of visual styles of three-dimensional animated characters on audience empathy and sympathy responses. In the study, 71 participants watched three animations of three characters whose visual styles differed in the degree of stylization (i.e., lead, stylized, and iconic). In each animation, the characters showed happy, angry, and sad emotions. After viewing each character’s animation, participants responded to a survey that measured their empathy and sympathy levels. Findings showed that the character’s visual style did not have a significant effect on reported audience empathy and sympathy.
Comparative analysis of NTRUEncrypt modified post-quantum cryptographic system and standard RSA cryptosystem

Introduction. The NTRUEncrypt cryptographic system, the calculation of the algorithmic complexity of the development of the NTRUEncrypt cryptosystem and its modifications are considered. The study objectives are to develop NTRUEncrypt, an efficient post-quantum cryptographic algorithm, which has high cryptographic resistance to quantum computer attacks, to work out a modification of the proposed algorithm, to analyze and experimentally validate its advantages. Materials and Methods . A description of the NTRUEncrypt encryption system is proposed. The modification of the considered algorithm is studied; the block diagram of the implementation of the software based on it is presented. An example of the software operation and its characteristic is given. The reliability of the results is proved using the Mann-Whitney U test. During the experiment, the third-party software implementation of the RSA cryptosystem was used. A Stopwatch class element was introduced in the source code of all three programs of NTRUEncrypt, RSA, and NTRUEncrypt modifications. This class provides a set of methods and properties that can be used for the precise measurement of the execution time. Thus, it became possible to record the results of the time spent on all three basic stages: key creation, encryption and decryption of the message. Research Results . The advantages of the developed cryptosystems in terms of the performance characteristics are proved. An experimental comparison of the implemented NTRUEncrypt algorithm and its modification is performed. All advantages of the latter are indicated. Discussion and Conclusions. The advantage of using the NTRUEncrypt algorithm modification is experimentally validated. The new application is 25% faster to perform general work on key generation, encryption and decryption. In addition, the internal memory usage is optimized through reducing the weight of the source program file and the size of the secret key. When attempting to crack a ciphertext, cryptographic robustness and complexity of using quantum algorithms are shown.
A Parallel Algorithm for Subgraph Isomorphism (Brief Announcement)

Subgraph isomorphism is a fundamental property of graphs that requires checking whether the network structure of one graph can be found (embedded) within another graph. It has numerous applications and is a computationally challenging problem: it is NP-complete and known algorithms explore an exponentially large search space. Even though it has been studied extensively, relatively little is known about whether subgraph isomorphism accepts a theoretically and practically efficient parallel solution. In this paper, we present our ongoing work on designing a parallel algorithm for the subgraph (and graph) isomorphism problem, which addresses challenges commonly faced when attempting to obtain a parallel algorithm for isomorphism. Our algorithm appears to scale well up to the 70 cores of our empirical machine.
Multigradient-based Convolutional Neural Network

The convolutional neural network (CNN) is a promising algorithm for artificial intelligence. Although it was developed for image classification, much research is currently in progress in various fields, such as object detection and image processing. The basic principle of the CNN, especially for classification, is to adopt a loss function and minimize it in an iterative way. In this paper, a multigradient-based training algorithm is proposed for image classification. The proposed algorithm defines an object function based on multigradients and trains the CNN by maximizing the corresponding objective function. When applied to open access databases, the proposed algorithm performed better than conventional back-propagation based CNN methods.
Intelligent Visual Analysis in Employee Fraud Detection

The objective of this paper is to discover and prevent organized financial crimes among various entities such as applicants, guarantors, customers, staff, portfolio managers, beneficiaries, agencies, experts and services. A sophisticated visual analysis solution can help users to detect conspicuous links between different entities. Most of the institutions have been using business intelligence or reporting tools to examine employee fraud which are insufficient to discover and analyze organized crime. In this paper, we propose a visual analytics approach to this problem. A web based application is developed which works with on-demand data and enable users to navigate on the graph and move objects in order to make the complex relationships clearer. The users can also zoom-in and zoom-out and dynamically expand nodes to discover hidden relationships at deeper levels. Intelligence Visual Analysis solution is a sub module of end-to-end Internal Fraud Management solution. It is also a stand-a-alone solution which can be integrated to other fraud management solutions.
Git-Based Integrated Uncertainty Manager

Nowadays, many software systems are required to be updated and delivered in a short period of time. It is important for developers to make software embrace uncertainty, because user requirements or design decisions are not always completely determined. This paper introduces iArch-U, an Eclipse-based uncertainty-aware software development tool chain, for developers to properly describe, trace, and manage uncertainty crosscutting over UML modeling, Java programming, and testing phases. Integrating with Git, iArch-U can manage why/when/where uncertain concerns arise or are fixed to be certain in a project. In this tool demonstration, we show the world of uncertainty-aware software development using iArch-U. Our tool is open source software released from http://posl.github.io/iArch/.
The What-To-Ask Problem for Ontology-Based Peers

The issue of cooperation, integration, and coordination between information peers has been addressed over the years both in the context of the Semantic Web and in several other networked environments, including data integration, Peer-to-Peer and Grid computing, service-oriented computing, distributed agent systems, and collaborative data sharing. One of the main problems arising in such contexts is how to exploit the mappings between peers in order to answer queries posed to one peer. We address this issue for peers managing data through ontologies and in particular focus on ontologies specified in logics of the DL-Lite family. Our goal is to present some basic, fundamental results on this problem. In particular, we focus on a simplified setting based on just two interoperating peers, and we investigate how to solve the so-called “What-To-Ask” problem: find a way to answer queries posed to a peer by relying only on the query answering service available at the queried peer and at the other peer. We show both a positive and a negative result. Namely, we first prove that a solution to this problem always exists when the ontology is specified in $$\textit{DL-Lite}_{\mathcal {R}} $$ , and we provide an algorithm to compute it. Then, we show that for the case of $$\textit{DL-Lite}_{\mathcal {F}} $$ the problem may have no solution. We finally illustrate that a solution to our problem can still be found even for more general networks of peers, and for any language of the DL-Lite family, provided that we interpret mappings according to an epistemic semantics, rather than the usual first-order semantics.
A Quantitative Analysis of the Effect of Human Detection and Segmentation Quality in Person Re-identification Performance

Person re-identification, a problem of person identity association across camera views at different locations and times, is the second step in two-steps system for automatic video surveillance: person detection, tracking and person re-identification. However, most of the reported person Re-ID methods deal with the human regions of interest (ROIs) which are extracted manually with well-aligned bounding boxes. They mainly focus on designing discriminative feature descriptors and relevant metric learning on these manually-cropped human ROIs. This paper aims at answering two questions: (1) Do human detection and segmentation affect the performance of person re-identification?; (2) How to overcome the effect of human detection and segmentation with the state of the art method for person re-identification? To answer these two question, quantitative evaluations have been performed for both single-shot and multishot scenarios of person re-identification. Different state-of-the-art methods for human detection and segmentation have been evaluated on two benchmark datasets (VIPeR and PRID2011). The obtained results allow to give some suggestions for developing fully automatic video surveillance systems.
Automated Socio-psycho-economic Knowledge Behavior Classified in E-Commerce Applying Various Machine Learning Techniques

Nowadays, the Web is a fundamental instrument of the search for a great many people. Vijayaragavan, P. The Web returns a massive number of pages of result for every single search element. The Internet is an active medium for correspondence among personal computers and gets to on thePonnusamy, R. Web records, yet it is not an instrument for finding or sorting out data. Tools like WebArrmuthan, M. indexes help clients in finding data. The measure of information every day seeks on the network is vast, and the assignment of receiving intriguing and necessary outcomes rapidly turns out to be exceptionally taxing. The utilization of a programmed site folio classifier can improve the procedure through helping the Internet searcher in receiving relevant outcomes. The Web pages can exhibit unique and various data relying upon the attributes of its substance. The idea of Web content presents extra difficulties to site page arrangement when contrasted with conventional content characterization; yet, the interconnected concept of hypertext additionally includes and can help the process. The proposed system efficiently classifies the data applying various machine learning techniques like SVM and confusion matrix, K-mean clustering and aspect extraction. Machine learning procedures are of great significance, and it will be utilized to build the classifiers.
An Ontological Approach for Knowledge Representation of Dental Extraction Forceps

Tooth extraction is a common surgical procedure in the dental field. If the procedure is carried out without proper knowledge about the tooth and the extracting instruments, it may lead to complexity on extraction procedure or even cause damages to the patients’ jaws. Therefore, the information and knowledge must be provided in a structured and complete way and in a context specific manner. Initially, information regarding the dental extraction forceps were gathered from the experts in the field, considering the importance of sharing the knowledge on dental extraction. Subsequently, an ontology on dental extraction forceps was developed. Next, the developed ontology was evaluated by ontology experts in an iterative approach. Finally, a knowledge sharing portal was developed and validated. We strongly believe that our dental extraction knowledge sharing portal can support the dental students, dentists as well as their assistants to improve the sharing of knowledge and learning practices.
A Multi-agent System with Self-optimization for Automated Clustering (MASAC)

Multi-agent Systems (MAS) offer an alternative to handling large quantities of data with the added advantage that control is not centralized, and consequently, such systems are endowed with robustness and versatility. This paper describes a Multi-agent System for Automated Clustering with self-optimization (MASAC). The framework comprises six categories of agents: information updater agent, document uploader agent, parser agent, convertor agent, clustering agent, and subset extractor agent. A novelty and feature of MASAC is that it supports self-optimization allowing for the enhancement of the initial clusters configuration in real time, and not only after running a cluster validation agent, as in other MAS presented in the literature.
Police Activity of 4th Industrial Revolution Era: utilization for the Security Information of Hyper-connected Era

이 연구의 목적은 초연결 시대로의 진입에 따른 치안정보의 수집과 활용에 대한 치안 전략의 한계점 및 향후 정책적 방안을 제시하는 것이다. 근래에 들어 초연결 시대가 본격적으로 시작됨에 따라 정보의 활용과 가치가 매우 높아졌으며, 치안정보에서 또한 적극적으로 활용되기 시작했다. 이 때문에 수집되는 치안정보의 성격과 그 범위 또한 초연결 사회와 관련해 논의되어야 할것이다. 미국의 경우 이미 초연결 사회 진입에 따른 범죄예방 프로그램을 개발하여 경찰활동을 수행하고 있으며, 중국 또한 초연결사회의 치안정보와 관련해 경찰활동을 전개하고 있다. 이에 따라, 이 연구에서는 경찰행정이슈의 새로운 동향과 정책적 과제로 초연결 사회로의 진입에 따른 치안정보의 활용방안과 치안전략의 수립과정에서 다루어져야 할 논제를 중심으로 다룬다. 분석을 위해 경찰기관의 초연결 환경을 활용한 경찰활동 경향, 경찰정보 공개현황, 각국의 초연결 환경을 통한 치안활동 사례를 통하여 실태를 분석했다. 그 결과 첫째, 치안정보에 대한 공공의 합의(국민과 사회적 협의) 둘째, 민감한 정보의 코드화를 통한 정보공개와 민간분석의 활용 셋째, 민간분석의 활용을 위한 표준화된 자료 수집과 제공, 마지막으로 자동수집 및 자동연결 시스템 구축과 공공 규제기관 (Regulator)을 통한 규제 오용방지 방안 등을 제시하였다.The purpose of this research is to propose the utilization strategy for the Security Information of Police Organization and the political plan in accordance with the Hyper-connected Era. The utilization and value of information became very high as the 4th Industrial Revolution has been brought about. The Security Information also becomes to be utilized actively as the Hyper-connected Era is commenced. Because of this, the character of collected Security Information and the range also should be discussed in relation to the Hyper-connected Society. In case of United States, the Police Activity has been being performed by developing the crime prevention program in accordance with the entrance to the Hyper-connected Society already; China also is deploying the Police Activity in relation to the Security Information of Hyper-connected Society. The thesis to be treated in the utilization plan of Security Information in accordance with the entrance to the Hyper-connected Society and the establishment process of Security Strategy as the new trend and political assignment of Police Administration Issue is treated in this research. The actual state has been analyzed through the example of Security Activity through the tendency of Police Activity utilizing the Hyper-connected Environment of Police Institution, the current status for the disclosure of Police Information and the Hyper-connected Environment of each nation for the analysis. As a result, the prevention plan, etc. of regulation misuse has been proposed through the first, the public agreement for the Security Information (social discussion with the nation), second, the information disclosure and utilization of private analysis through the codification of sensitive information, third, the standardized data collection and provision for the utilization of private analysis and lastly, the system building of automatic collection and automatic connection and the public Regulator.
Research on the Motion Control and the Coordination Method of the Autonomous Mobile Robots

With the continuous development of the automation technology in the modern society, the robotic equipment has been more and more widely used in all aspects of the current society. The autonomous mobile robot is one of the most advanced modern robotic devices, which has obvious characteristics of the intelligence and automation. In the practical application process of the autonomous mobile robot, in order to make its functions better realized and its functions better developed, it is necessary to design its motion control reasonably so as to better serve the current social production and people’s life.
Person Detection by Low-rank Sparse Aggregate Channel Features

Human detection in the video has several applications in security and surveillance. Human detection using video is desired to be robust against illumination, occlusions, scale, translation and view angle variations. In this paper, we develop an approach which can improve the performance of the aggregate channel feature for a high view angle. The foreground is estimated using a frame differences approach to identify the location of moving objects in the static camera scene. The sparse basis is included in the aggregate channel feature vector to describe the foreground region of each frame of the video. This approach provides better miss rate versus false positive per image as compared to the existing aggregate channel feature and histogram of the oriented gradient.
Multimodal Assessment on Teaching Skills in a Virtual Rehearsal Environment

In the training programs for student teachers, the opportunity to practice teaching skills is often limited due to the lack of resources in preparing a rehearsal environment. We are developing a virtual rehearsal environment for teaching practicing with multiple virtual students. In order to provide feedbacks to the student teachers and allow them to improve their skills, automatic assessment on their performance is required. However, it is hard to assess on teaching because the assessment is subjective and often depends on the tacit knowledge of experienced teacher trainers. In this work, we proposed an automatic assessment model based on human assessment done by experienced high school teachers.
Preliminary Study of Computer Aided Diagnosis Methodology for Modeling and Visualization the Respiratory Deformations of the Breast Surface

Minimally invasive therapy of breast cancer is an important issue in modern medicine. This paper presents a methodology which allows acquisition of breast respiratory motion. The proposed methodology consists of: stereo camera, Time-of-Flight camera and ultrasound machine. All devices were calibrated to allows data acquisition and breast surface reconstruction in common coordinate system. The proposed me- thodology obtains the median Fiducial Registration Error of Time-of-Flight and stereo vision of 7.44 mm for inhale and 8.74 mm for exhale surfaces rigid registration. The average amplitude for the breast movement was for the markers and clouds of surface points of 3.34 and 3.81 mm, respectively. The obtained amplitude values for both tracked markers and breast surface points are comparable, which allows us to positively verify the method based on the Time-of-Flight camera as a non-invasive method of measuring movements of the breast surface. The obtained values indicate that the breathing motion factor cannot be neglected during modeling of deformation of the breast surface.
Constructural Software Documentation

Software projects capture information in artifacts that include production code, test suites, and documentation. Because different artifacts serve different purposes, some artifacts can include redundant information, encoded in different formats. To mitigate this redundancy, we propose an approach to explicitly encode in unit tests information that will be automatically extracted and added to the documentation of the software. We implemented this approach in the form of an Eclipse plug-in that binds unit tests written with JUnit to the header comments of the tested methods.
Social Recommendations: Have We Done Something Wrong?

In this Demo we wish to demonstrate that it is not possible to evaluate a recommender’s ability on the basis of how good it is in carrying out the task we are interested in. On the contrary, a recommender should be evaluated as such. Although this mechanism is often used in literature, it unavoidably leads to incorrect results.
Research on Modulation Algorithm Based on Physical Layer Encryption

Communication has become a very important part of people’s work and life. Wireless communication technology has the characteristics of low cost, good scalability, and easy use, but it is vulnerable to eavesdropping and other security threats, and eavesdroppers illegally receive through wireless channels. Traditional wireless communication system security methods need to be implemented at the upper layer through authentication and cryptographic techniques. In recent years, as an important complement to traditional security mechanisms, information theory security principles, transmission signal security technologies, spread spectrum and frequency hopping encryption technologies, and channel coding Research on physical layer security technologies such as encryption technology and modulation encryption can effectively protect information during wireless transmission and prevent eavesdroppers from illegally receiving information.