Reviewerly/exHarmony huggingface dataset:
Early Diagnosis Expert System Hepatitis Using Naive Bayes Method: Early Diagnosis Expert System Hepatitis Using Naive Bayes Method

Public health activities for the control of viral hepatitis have increased during the last three decades. In 2010, there is growing public awareness about the public health burden of viral hepatitis. However, there are major gaps in the response and increased mortality. Five virus responsible for most cases of viral hepatitis are hepatitis A, B, C, D, and E. All hepatitis viruses can cause acute hepatitis. However, only HBV, HCV and HDV frequent cause of chronic hepatitis, which can cause progressive scarring of the liver and primary liver cancer. Of these, HBV and HCV causes 96% of deaths from hepatitis virus, So the need for special treatment for hepatitis, with the creation of an expert system for diagnosis of hepatitis using Naive Bayes method that aims to diagnose the onset of hepatitis disease is expected to help users who still lay on knowledge as well as related information from hepatitis. Based on test results using 10 samples of data to get the value of accuracy of 90%. Ketikakuratan 10% is due at the time of the calculation method that uses a Naive Bayes highest value for the results obtained and if the same value system will take the value of the list of the first order for the results to a user
Early Warning Leakage Detection for Pneumatic Systems on Heavy Duty Vehicles : Evaluating Data Driven and Model Driven Approach

Modern Heavy Duty Vehicles consist of a multitude of components and operate in various conditions. As there is value in goods transported, there is an incentive to avoid unplanned breakdowns. For t ...
A secure and privacy-preserving key agreement and mutual authentication scheme

The development of manufacturing, communication, and computing technologies has promoted convergence of different network architectures, aiming to make full use of all resources to create valuable information. While heterogeneous integrated networks play a key role in providing highly effective and efficient solutions for medical users, they also raise various security and privacy issues. Strengthen the security and privacy protection and efficiency before transmitting sensitive data is a primary challenge to be addressed. Traditional authentication methods fail to differentiate the privacy sensitivity difference between data collected by distinct devices. We propose a secure and efficient key management scheme based on a key-exposure resistant chameleon hash function. Through adopting the devices' privacy sensitivity and users' attribute credential as two factors to establish trust between different entities, we proposed a secure and anonymous authentication protocol. The security analyses indicate that the proposed protocol can satisfy security requirements.
Intruder Insinuation and Smart Surveillance Using Face Detection and Mask Detection

A surveillance system uses Raspberry Pi, PIR sensor and mobile devices to provide security at nighttimes against any intrusion and theft in shopping malls, jewelry shops and other places which holds valuable items. The main objective of the proposed system is to provide security to shops in the closed times. The proposed system uses Haar cascade algorithm for face detection to detect the unknown faces and own object detection method to detect masked faces. The proposed system comprises PIR sensor, GSM equipment and any type of good-quality camera. GSM system will send alert messages to the owner and nearby police station when there is any intrusion detected. The PIR sensor and camera, all of the equipment are controlled by the Raspberry Pi system. The camera captures the image, whenever any motion is detected through remote sensing by PIR sensor. When any human face is detected through the captured image, the camera will stay turned on; otherwise, it will go to standby mode. If any unknown and unauthorized face is detected from the image, camera will continuously capture images. Finally, if the system has detected only unknown faces, then the owner, security and nearby police station will receive the alert messages.
Info-Communicative and Protective Function of the State as Combating Fraud using Sberbank Bank Cards

Financial crimes are defined as unfair activities that have become widespread in banking structures. The activities of financial fraudsters often have negative consequences before public rules are created that prohibit them. Intensive transformation processes in financial markets, their automation and virtualisation, the spread of remote interaction between banks and their clients, the influence of unauthorised persons on the software and hardware systems of banks, an increase in the number of cases and trading volumes determine the relevance of clarifying the essence of this phenomenon and the peculiarities of its manifestation in banking structures. The novelty of the study is determined by the fact that financial violations can be represented both in the structure of the current activities of banks and the process of interaction with clients and in the structure of expanding the list of services provided. The leading method to study this problem is the method of analysis, which allows to identify and comprehensively consider ways to counter financial crimes in banks to improve the level of financial security. The authors show that structurally, one should take into account, first of all, countermeasures on the part of customers, which often serve as a source of obtaining personal data. In this case, the state function is considered only as a security function for the purpose of possible punishment for fraudulent actions. The practical significance of the study is determined by the possibilities of structural implementation of combating financial fraudulent actions in the context of the development of the information society.
Retooling our anti-corruption arsenals: exploring the potential use of CAQDAS in corruption investigation

Purpose This paper aims to explore the potential of computer-assisted qualitative data analysis software (CAQDAS) to be used as a corruption investigation tool to help investigators in carrying out their investigative works. Design/methodology/approach By reviewing the literature on qualitative research and fraud investigation, this exploratory study identifies similarities between the two types of inquiries and thus proposing the use of CAQDAS as an innovation in the field of corruption investigation. To demonstrate how a QDA application can support corruption investigators, NVivo is used as a case study from which various key analytical tools are discussed to highlight their potential in supporting a corruption investigation. Findings As a fundamental part of anti-corruption practice in a country, corruption investigation must be planned and executed professionally and adequately. This paper highlights various stages in fraud investigation to identify areas that can be improved with the use of a CAQDAS. Based on the discussion in this paper, the author concludes that the capability of a CAQDAS to assist users in data reduction and data display has the potential to increase the effectiveness and efficiency in various stages of a corruption investigation. Research limitations/implications Based on a self-funded study, this paper only uses a simulation case with a fictitious company to illustrate how a CAQDAS application can be used to support a corruption investigation process. Future studies may benefit from using actual corruption cases in illustrating how such an application can support the investigation process. Practical implications This paper contributes to the innovation in anti-corruption practice by proposing a new framework and tool to develop corruption investigation capacity. Originality/value This paper brings a new perspective into the field of anti-corruption to stimulate innovation in the area of corruption investigation.
CosSGD: Nonlinear Quantization for Communication-efficient Federated Learning.

Federated learning facilitates learning across clients without transferring local data on these clients to a central server. Despite the success of the federated learning method, it remains to improve further w.r.t communicating the most critical information to update a model under limited communication conditions, which can benefit this learning scheme into a wide range of application scenarios. In this work, we propose a nonlinear quantization for compressed stochastic gradient descent, which can be easily utilized in federated learning. Based on the proposed quantization, our system significantly reduces the communication cost by up to three orders of magnitude, while maintaining convergence and accuracy of the training process to a large extent. Extensive experiments are conducted on image classification and brain tumor semantic segmentation using the MNIST, CIFAR-10 and BraTS datasets where we show state-of-the-art effectiveness and impressive communication efficiency.
Context-Aware Recommender System for Adaptive Ubiquitous Learning

The use of context-aware recommender systems for adaptive ubiquitous learning has become a promising and interesting research direction in recent years, both as a result of the vast use of ubiquitous devices in our day-to-day lives and because of students' increasing desire to learn with ease anytime and anywhere without restriction. This paper implements an RFID-based context-aware technology and recommender system for adaptive ubiquitous learning that will help learners to achieve personalised learning goals and greater learning efficiency. Our context-aware recommender suggests courseware to students based on their location, surrounding noise level and time of day. Radio Frequency Identification (RFID) technology was used to acquire context awareness, and fuzzy logic was employed to develop courseware recommendations. The front end of the system was developed using Android Studio. Experimental results were obtained from selected students from different disciplines who evaluated the system.
Out-Of-Distribution Detection With Subspace Techniques And Probabilistic Modeling Of Features.

This paper presents a principled approach for detecting out-of-distribution (OOD) samples in deep neural networks (DNN). Modeling probability distributions on deep features has recently emerged as an effective, yet computationally cheap method to detect OOD samples in DNN. However, the features produced by a DNN at any given layer do not fully occupy the corresponding high-dimensional feature space. We apply linear statistical dimensionality reduction techniques and nonlinear manifold-learning techniques on the high-dimensional features in order to capture the true subspace spanned by the features. We hypothesize that such lower-dimensional feature embeddings can mitigate the curse of dimensionality, and enhance any feature-based method for more efficient and effective performance. In the context of uncertainty estimation and OOD, we show that the log-likelihood score obtained from the distributions learnt on this lower-dimensional subspace is more discriminative for OOD detection. We also show that the feature reconstruction error, which is the $L_2$-norm of the difference between the original feature and the pre-image of its embedding, is highly effective for OOD detection and in some cases superior to the log-likelihood scores. The benefits of our approach are demonstrated on image features by detecting OOD images, using popular DNN architectures on commonly used image datasets such as CIFAR10, CIFAR100, and SVHN.
Penerapan Penilaian Berbasis Kelas dan Penilaian Portofolio dalam Menumbuhkan Minat Baca di SDN Daan Mogot 1 Tangerang Kecamatan Tangerang

This article discusses the use of class and portfolio assessments in developing students’ interest in reading. The research method used is a description of portfolio instruments, observation, and interviews. The study was conducted at Daan Mogot 1 School in Tangerang, from Juli 2020. Portfolios of twenty-eight of 6th-grade students were used. In addition to using portfolios, data were also obtained from library staff and teachers. The data in the study were the titles of books read by the students, the titles they wanted, and the efforts made by schools and teachers in increasing reading interest. The results show that students' interest in reading was good. The average number of books read in the past year is 6 titles consisting of various books, commonly storybooks, or stories. The program conducted to develop reading interest is visiting the school library every Monday from 1 to 2.30 pm. However, the data taken from the last two months reveal that students’ interest in visiting the library is not satisfying, only 7 students came to visit and read in the library.
IMPLEMENTASI WEB SERVICE UNTUK INTEGRASI DATA BIMBINGAN SKRIPSI MAHASISWA PADA FAKULTAS TEKNIK UNIVERSITAS JABAL GHAFUR

The final project or thesis is a final assignment that must be completed by a student who will graduate with a bachelor's degree or diploma at the University of Jabal Ghafur, currently the process of conducting thesis guidance is still done manually. Students and lecturers must provide face-to-face guidance, then determine an appointment schedule that is suitable for both, in addition to requiring a long time this is also less effective, to overcome these problems, it is necessary to design a Liaison Application to help student thesis guidance with lecturers by applying technology Web Service that provides online thesis guidance services that work like face-to-face thesis guidance. Therefore, an online thesis guidance application was designed at Jabal Ghafur University in the Engineering faculty. This application is designed with the PHP programming language assisted by the CodeIgniter framework, and the MySQL Database Management System (DBMS) as data collection software. The results of this application are in the form of data reports from student thesis guidance with their supervisors. Keywords : Web service, Web, guidance application, PHP, MySQL
플립드러닝 기반 코칭식 수업이 대학생의 영어 능력과 학업적 자기효능감에 미치는 영향

The purpose of this article is to verify the effects on the cognitive and emotional achievement of college students by using coaching techniques based on flipped learning. This study was conducted for 15 weeks on two divisions consisting of first-year university students taking a liberal art English course, among which the experimental group (N=32) was given flipped learning-based coaching lesson, and the control group (N=31) flipped learning-based teaching lesson. As a result, the analysis of reading and writing, which are cognitive factors, showed that a flipped learning-based coaching group performed better than a regular flipped learning group. Meanwhile, the academic self-efficacy was more effective for the control group. The implication of this study is that it is necessary to develop a convergence learning model based on the current trend of flipped learning. In addition, follow-up research should continue so that learners can actively adapt to the era of consilience and create synergy effect between subjects.
A Study on the Policy Priorities of MICE Industry using the AHP - Focused on Jeju Special Self-Governing Province -

Purpose - The purpose of this study was to identify the policy priorities of MICE Industry and to provide quality services tailored to each MICE section so that Jeju could become a MICE advanced city. Design, data, and methodology - Due to lack of previous studies on MICE policy by CVB(Convention & Visitors Bureau), detailed items of policy research model for CVB were drawn through interviews with officials of 14 CVBs in Korea. The priority was derived through the importance and weight of detailed items such as the upper concept, the middle concept, and the lower concept of MICE section in the CVB through the pair comparison bridge using AHP for 21 MICE experts in Jeju Result - Through this study, we obtained the results of the overall policy priority analysis of MICE industry in Jeju, and we were able to present the policy direction for the detailed attributes of each MICE section. Conclusions - I propose customized marketing for each MICE section by presenting systematic policy directions for the Jeju MICE industry, and further to propose additional study on the overall Korea MICE industry targeting Korean MICE experts.
SMARTSDK - A FIWARE-Based Software Development Kit for Smart Applications for the Needs of Europe and Mexico

We present the goals, development and results of the SmartSDK project, a FIWARE initiative that aims to create a sustainable FIWARE ecosystem between Europe and Mexico by leveraging on existing FIWARE outcomes and building reference standards for common challenges, providing ready-to-use bundles to simplify the creation of Smart Software Services.
A Security Framework for Application Instance Data to Enhance the Privacy in Decentralized Cloud Environment

Due to new-age technology enhancements in various domains, there is a rapid increase in the volume of essential data getting stored in the cloud. Storing of data in the cloud has made it convenient for a large number of applications to deploy more modules in lite manner. Especially to name a few, the mobile and virtual applications are much benefited using cloud storage. At the same time, since the data is stored on remote machines, there is a huge concern and challenge on the security and privacy of these applications data. In this paper, we have given a detailed survey of various security methods and the importance of mobile and virtual application data privacy. In continuation to this, we have proposed a novel framework called Seclogmon2, which will address various concerns and challenges of application data security.
Building a quantum computer (invited)

Quantum computing has leapt from concept to commercial enterprise in four decades and now the complexities of computer hardware apply to quantum computing but with the added challenge that computer fundamentals are radically different.
Updating a web page

Devices connect to a wireless local area network (WLAN) with Wi-Fi communication (see Chapter 7 (Wireless local area network)). A router connected to an Internet Service Provider (ISP), through a telephone line using DSL (Digital Subscriber Line) technology, provides access to the Internet (see Figure 8-1). The Internet is formed by interconnected computer networks using the Internet Protocol suite, consisting of the Transmission Control Protocol and the Internet Protocol (TCP/IP), to globally link devices. The World Wide Web (WWW) identifies information resources by URLs (Uniform Resource Locators). The client or web browser, such as Google Chrome or Mozilla Firefox, sends an HTTP (HyperText Transfer Protocol) request to the server device hosting the resource to retrieve information at the web address defined by the URL. The server responds to the client HTTP request, and the client displays the requested web page information on the Android tablet or mobile phone. The client must request web page information from the server, as the server cannot impose updates on the client. The exception is WebSocket, as discussed in Chapter 9.
Toward fully automatic earthquake detection and processing for tomography in the Hengill area

This thesis focuses on the automation of seismic data analysis, in particular, event detection, quality assessment of detected events, and preparation of an earthquake catalogue for seismic tomogra ...
Methods of Forming and Evaluating Logical Universal Educational Actions when Teaching Russian

The importance of secondary school students’ proficiency in universal learning activities (ULA), including functional literacy, in order to socialize successfully makes the search for appropriate means relevant. However, it is no less important to diagnose the formation of ULA and identify problems within their acquirement. Understanding the importance of this problem led to the idea of using existing pedagogical methods in teaching the Russian language paying attention to their adaptation. The purpose of the article is to show how existing methods can be adapted in order to be used in the formation and assessment of the logical ULA during Russian language lessons. The study was based on the methods of analysis and synthesis when describing the problem of formation and assessment of ULA among schoolchildren; in the development of diagnostics – on the methods of analysis, abstracting, and constructing. In addition, a systemic method was used. Statistical data of the conducted research and their interpretation are presented to substantiate the need for the creation and adaptation of methods for the ULA formation and assessment. The study reveals the pedagogical diagnostic methods, which, with a certain adaptation, can be used for the logical ULA formation and assessment during teaching the Russian language. The research presents the adapted methods, which will allow organizing systematic work on the formation of logical ULA for secondary school students when studying the “Lexicology” section and assessing their formation among schoolchildren.
Multi-period Infrared Image Generation Based on Multi-conditional Cycle Generative Adversarial Networks

Since the number of most infrared image samples is too small, many deep learning networks don’t work well on these infrared datasets. In this paper, we propose a Multi-conditional Cycle Generative Adversarial Network, which can derive multi-time infrared images from some fixed-time infrared images, and can be used to augment the small infrared image dataset. By taking several different time periods as multi-condition constraints, the model we proposed, which is based on generative adversarial network (GAN), can derive infrared images in different time periods. In order to improve the quality of derived infrared images, this paper introduces L1 norm and Wasserstein distance to construct the objective function, which make it easier to stabilize the training of the network, and the model can learn more useful features. The small infrared images dataset in our experiment is built by our team own. The experiments show that the method proposed in this paper can derive multi-period infrared images. Compared with the CGAN, our model can learn the feature mapping between the original images and the derived images more accurately, and the generated infrared images are richer in details and more realistic by vision.
Maths and children's literature: Implementing the narrative-first approach

At the beginning of 2018 I moved into the Year 5/6 team, which meant I was about to start working with a new group of teachers. As we approached the first day back, I knew that I wanted problem solving to be a focus of our planning and I began to think about the best way to get the rest of the senior team on board with this plan. Luckily, I had a fresh and exciting idea to bring to our team's first planning session.
Organization of group work at informatics lessons in primary school

The use of group forms of work in organizing the educational process at school has great potential for the formation of motivation to study, the development of reflexive skills, the acquisition of subject knowledge, the formation of communication skills. The novelty of the social situation of education at school for a younger pupil, his age, the specificity of the subject "Informatics" determine a number of features of the use of group forms of education in primary school. Among such features, the authors consider the need to create situations of the need for the use of knowledge in informatics in solving various educational and life tasks, ensuring the competitive nature of group work, dividing group members by roles, creating conditions for gaining experience in reflexive activity.