Reviewerly/exHarmony huggingface dataset:
HGAR: Hybrid Granular Algorithm for Rating Recommendation

Recommendation algorithms based on collaborative filtering show products which people might like and play an important role in personalized service. Nevertheless, the most of them just adopt explicit information feedback and achieve low recommendation accuracy. In recent years, deep learning methods utilize non-linear network framework to receive feature representation of massive data, which can obtain implicit information feedback. Therefore, many algorithms are designed based on deep learning to improve recommendation effects. Even so, the results are unsatisfactory. The reason is that they never consider explicit information feedback. In this paper, we propose a Hybrid Granular Algorithm for Rating Recommendation (HGAR), which is based on granulation computing. The core idea is to explore the multi-granularity of interaction information for both explicit and implicit feedback to predict the users ratings. Thus, we used Singular Value Decomposition model to get explicit information and implicit information can be received by multi-layer perception of deep learning. In addition, we fused the two part information when the two models are jointly trained. Therefore, HGAR can explore the multi-granularity of interaction information which learned explicit interaction information and mined implicit information in different information granular level. Experiment results show that HGAR significantly improved recommendation accuracy compared with different recommendation models including collaborative filtering and deep learning methods.
PENGEMBANGAN MEDIA PENDIDIKAN UNTUK INOVASI PEMBELAJARAN DI PESANTREN

The increasingly dynamic development of information technology has implications for the world of education, especially learning activities. One of them by using media for helping the easy learning process that is very receive as benefit. Learning media can enhance student learning help to create joyful learning. But is not all learning media that can be applied in every learning environments, because learning media has advantages and disadvantages in several aspect. For the example is classical learning methods such as wetonan and bandongan become a characteristic teaching and learning activities in pesantren. Because of that, require a efforts to develop educational media suitably with the learning and the needs of students. Learning media development procedures iclude are potential and problems, data collection, product design, design validation, revision, small-field trials, revision, large-field trials, revision, massive production
Examining redundancy in the context of safe machine learning

This paper describes a set of experiments with neural network classifiers on the MNIST database of digits. The purpose is to investigate naive implementations of redundant architectures as a first step towards safe and dependable machine learning. We report on a set of measurements using the MNIST database which ultimately serve to underline the expected difficulties in using NN classifiers in safe and dependable systems.
Design of Psk Based Trusted Dtls for Smart Sensor Nodes

Background: RSA based key exchange is a heavy and time-consuming process, as it involves numerous message exchange between a client and the server. Pre-shared key (PSK) based handshake process attempts to reduce the messages while the key exchange between a client and the server. Method: This paper extends the TEE enabled dtls handshake design based on RSA to the TEE enabled pre-shared key based handshake. A dtls client and the server installs the pre-shared key in advanced so that the message exchanges can be reduced while session key generation. Result: In this article, the authors have significantly reduced this penalty by fine-tuning of the tdtls algorithm for psk based handshake. On average, this gain is over 2 ms (50% - from 3.5 ms to 1.5 ms) across various cipher-suites. Conclusion: The tdtls approach increases the security of the session key and its intermediate keying materials which is a huge gain as compared to minor handshake time increase. The algorithm ensures an end-to-end security to the PSK based session key as well as its keying materials between a dtls client and a server.
Using a Non-player Character to Improve Training Outcomes for Submarine Electronic Warfare Operators

Previous research has shown that adaptive training (AT) is an effective tool for improving training outcomes relative to non-adaptive approaches. Taking a value-added perspective, in this study we sought to determine whether the presence of an embedded non-player character (NPC) served to improve performance outcomes relative to AT alone. To support this research, we utilized the Submarine EW Adaptive Trainer (SEW-AT) as our testbed, which is a scenario-based AT system that simulates a trip to periscope depth. The submarine EW operator's role is to monitor the radio frequency signals in the environment and submit reports of the contact picture at prescribed intervals (i.e., scheduled reports) and irregular intervals as the environment changes (i.e., unscheduled reports) to the Officer of the Deck (OOD). Sixty-eight U.S. Navy EW operators completed training with one of two versions of SEW-AT: one with an NPC OOD and one without. The NPC OOD was designed carefully to provide realistic immediate feedback to the trainee while also minimizing distraction from the task. In general, all EW operators improved their performance using SEW-AT, but those using SEW-AT with the NPC OOD displayed significantly greater improvement in scheduled report timeliness than those who used SEW-AT without the NPC OOD. These results suggest that the addition of the NPC OOD to provide immediate feedback added an overall benefit over AT alone.
Toward a Semantic Graph of Scientific Publications: A Bibliometric Study

The term "scientific publication" includes several types of scientific communications and digital broadcasts that scientific researchers make of their work towards their peers and an audience of specialists.These publications describe in detail the studies or experiments carried out and the conclusions drawn from them by the authors.They undergo an examination of the value of the results and the rigor of the scientific method used for the work carried out.In this paper we evaluated the quality of a scientific article on the subject (topic), based on its citations and where is it cited, we based on the Topic modeling theme with the choice of LDA algorithms applied to the corpus Nips for detecting all subjects of each paper and there citations in a first step then on the citations of each article of the corpus and on the Sentiment Analysis using a lexical based approaches.Then we created a csv file containing the link of each paper with the other cited papers (relation cited-citing), and finally generated a semantic graph between these publications.
Simulation of multi-agent interaction between mobile operators and users

Abstract Game-theoretic models for two classes of players are considered in this paper. The first class will consist of mobile operators, who, based on information about competitors’ actions, will plan changes in prices for services. The second class will consist of dedicated user cohorts who, depending on the current situation, will plan their actions, namely, change or not change the operator. The presented models solve the problem of maximizing the income of mobile operators and minimizing the cost of communication by users. A turn-based game is considered where a possible strategy for a first-class player will be considered a non-zero price vector for the provided communication services. A possible strategy for a second-class player will be considered the sequence of choosing a mobile operator for each of the services. The payoff function of both classes players will be built at each stage. According to the winnings, there is a compromise solution for different classes of players.
Time Slot Modeling of Life Habits in the Elderly for Decision-Making Support

This article investigates new steps for the implementation and the utilization of presence indicators to identify displacement activities of a person and to model their life habits. This modeling is based on preliminary measures of displacement rate variations over a period of time. A possible time slot division of activities is highlighted by the analysis of these measures, slight variations of slot boundaries could appear from day to day, from person to person. On this basis, we show how to build three new indicators by working from time slot to time slot, in order to detect alerts or drifts from “normal” behavior as soon as possible and in a more reliable way. These indicators include start and end times of time slots, displacement rate and duration of each time slot. The algorithm we propose has been tested in real situations to show its use and relevance. Results are finally integrated in a more ambitious process of detection and automatic decision-making support through the conception of a web interface.
Determining the More Adequate Web Page Node for Advertising Placement

For many web sites, money earning is crucial for keeping the content production. Advertisingis one of the most common strategies for web content monetization. To determine where is the more appropriate place for ad location is an essential task to get a gentle introduction of the commercial information. There are algorithms based on keywords appearing within text; however we consider that implicit meaningis more adequate for a better harmony between contentad vertising. In this work, we present a formal method that determines the best place for advertising location. For this, we explore the underlying tree-like structure of a web page, we extract the text from each (X) HTML node and compute the semantic similarity (by employing latent semantic analysis) w.r.t., the advertising source text. We introduce a unique formula for the numerical calculation of the web page node relevance. We think it could beused for measuring the concordance among web page nodes and the commercial information and for the design of dynamic ads insertion methods.
Investigating Factors Affecting the Adoption of Smartphone Technology by Elderly People In Iraq

The smartphone is now essential part of daily life (business and personal) across all age bounds. The usage of it can play a part in helping the elderly in several ways in terms of healthcare information. This paper aims at developing a model for identifying substantial factors that affect elderly people's intention toward adopt smartphones. A questionnaire instrument is developed to define factors that influence smartphones adoption via elderly people. The questionnaires are distributed in terms of paper-based questionnaires individually in Iraq. 225 completed questionnaires are gathered. Using a Cronbach Alpha, the test of reliability is conducted on the obtained data. The result indicates that four factors (socioeconomic influence, facilitating conditions, performance expectancy and effort expectancy) affect older people's intention to embrace smartphones.
Criminal Face Recognition Using GAN

Forensics and security at present often use low technological resources. Security measures often fail to update with the upcoming technology. This project is based on implementing an automatic face recognition of criminals or specific targets using machine-learning approach. Given a set of features to a Generative Adversarial Network(GAN), the algorithm generates an image of the target with the specified feature set. The input to the machine can either be a given set of features or a set of portraits varying from frontals to side profiles from which these features can be extracted. The accuracy of the system is directly proportional to the number of epochs trained in the network. The generated output image can vary from primitive, low resolution images to high quality images where features are more recognizable. This is then compared with a predefined database of existing people. Thus, the target can immediately be recognized with the generation of an artificial image with the given biometric feature set, which will be again compared by a discriminator network to check the true identity of the target.
Authenticated QKD Protocol Based on Single-Photon Interference

As is known, quantum key distribution (QKD) can provide information-theoretic security under some preconditions, one of which is that the identity of each participant has been authenticated. And quantum identity authentication (QIA) can achieve this precondition effectively. However, the adversary still can implement man-in-the-middle attacks on QKD protocols in some situations, such as the protocol in [Quant. Inf. Process, 18, 137 (2019)]. In the above paper, the authors claimed that, after their QIA protocol based on GV95 system (GV95-QIA protocol), the participants could perform GV95-QKD protocol to update and extend the authentication keys. However, this method is not secure in the sense that the adversary could wait for the participants to complete GV95-QIA protocol and then perform the man-in-the-middle attack on the QKD process. In this paper, we solve this problem by mixing GV95-QIA process and GV95-QKD process randomly. Specifically, two authenticated QKD protocols are proposed based on the above idea. The proposed protocols can be used to provide secure identity authentication to GV95-QKD protocol, and also can be used to extend the authentication keys for GV95-QIA protocol.
The EFL Learners’ Perspectives on the Online English Course Conducted through WhatsApp Group Interactions

This study aims at highlightingthe EFL learners’ perspectives on Kulwap– online English course conducted through WhatsApp Group Interactions.This is an exploratory research project employing a qualitative method. The data of the study were gained through informal semi-structured interview and students’ written testimonies. The research findings show that conducting English online course through kulwap proposes advantages as well as challenges that must be consider for the future instructional process. The benefits of Kulwap include the accessibility, simplicity, convenience, and flexibility the students got during the instructional process if English course. On the other hand, the challenges faced by the students regarding the online course through Kulwap cover the problems of internet connectivity, and other technical things including the eye strain, students’ lack motivation, and limited response from the lecturer during the online instructional process.
Deep Learning Autoencoder Approach: Automatic Recognition of Artistic Arabic Calligraphy Types

Recognition of Arabic calligraphy types is a challenging problem. Difficulties include similarities among different types, overlap between letters, and letters that assume different shapes. In this study, a deep learning approach to recognizing artistic Arabic calligraphy types is presented. Autoencoder is a deep learning approach with the capability of reducing data dimensions in addition to extract features. Autoencoders could be stacked with several layers. The system is composed of three layers consisting of two encoder layers to extract features and a one soft max layer for the recognition stage. The font can be recognized in a collective manner based on the words or segments the exist in the font images. The input of the system consists of individual words or segment images that compose the font image, and the output is the recognized font type. The approach was evaluated on local and public datasets, and the achieved recognition rates were 92.1% and 99.5%, respectively.
Patient Monitoring using Internet of Things

Nowadays IoT is playing an important role in health care systems, which is not only helpful for monitoring the health parameters but also helpful for communicating, storing and displaying the monitored data.The main aim of the project is to design and implement effective health care patient monitoring system.The proposed system monitors the health parameters like Temperature, BP and Pulse rate etc. and then transmits the parameters wirelessly through wifi module technology.The transmitted data is displayed on the PC .This data gets updated into database continuously.From the database with the help of android application fetches all the updated data and displays it on doctor side personal mobile.This tells the doctor the current status of the patient in real time.If any parameter of a particular patient goes beyond a pre-assigned threshold value, then an automatic notification will send on doctors mobile using android mobile application.The system basically consists of hardware like sensors, microcontroller (ATmega16), LCD display,wifi module(ESP8266),MQTT protocol for sending data on cloud, android app etc.
Rancang Bangun Aplikasi Chatbot Sebagai Bentuk Pelayanan Prima Untuk Penerimaan Mahasiswa Baru

Excellent service is the best form of service to consumers to feel satisfied. The purpose of excellent service is that consumers or prospective consumers feel underserved and in terms of agencies or companies will increase consumer confidence. Muhammadiyah University Purworejo (UMP) as an educational institution has prospective consumers, namely the millennial generation. The habit of the millennial generation in accessing information is by digitally searching. To access more detailed information, they are accustomed to asking through the texting method via chat. Therefore, the University needs to provide a texting application that can answer questions anytime and with a short reply time.The chat application developed in the form of chatbots.The chat-bot application development begins with studying general questions that are often asked by prospective students. The combination of question words and keywords from each question. From the keywords that are prepared an automatic answer that contains information that the prospective student wants to access. In addition, in each answer a key for information related information will be provided. The results of the design and development of the Chatbot application, namely the implementation of Chatbot can be used as a substitute for the role of humans in providing excellent service. This chatbot can provide quick and complete answers. In terms of the excellent service factor, this Chatbot can fulfill the attitude, attention, action, ability and accountability factors.
A Virtual Machine Migration Mechanism Based on Firefly Optimization for Cloud Computing

Background: Cloud computing is one of the prominent technology revolutions around us. It is changing the ways the consumer expends services, changing the ways the organization develop and run applications and is completely reshaping the old business models in multiple industries. Cloud service providers need large-scale data centers for offering cloud resources to users, the electric power consumed by these data centers has become a concrete and prudential concern. Most of the energy is dissipated in these data centers due to under-utilized hosts, which also subsidies to global warming. The broadly adept technology is virtual machine migration in cloud computing, therefore, the main focus is to save energy. Objective: Virtual Machine (VM) migration can reap various objectives like load balancing, ubiquitous computing, power management, fault tolerance, server maintenance, etc. This paper presents an energy-oriented mechanism for VM migration based on firefly optimization that reduces energy consumption and the number of VM migrations to a great extent. Method: A Firefly Optimization (FFO) oriented VM migration mechanism has been proposed, which allocates tasks to the physical machines in cloud data centers. It strives to migrates high loaded VMs from one physical node to another, which induces minimum energy consumption after VM migration. Results: The empirical result shows that the FFO based mechanism, implemented in the CloudSim simulator, performs better in terms of the number of hosts saved up to 13.91% in contrast to the First Fit Decreasing (FFD) algorithm and 8.21% as compared to Ant Colony Optimization (ACO). It reduced energy consumption up to 12.76% as compared to FFD and 7.78% as compared to ACO and, ultimately lesser number of migrations up to 52.49% when compared to FFD and 44.51% as compared to ACO. Conclusion: The proposed scheme performs better in terms of saving hosts, reducing energy consumption, and decreasing the number of migrations in contrast to FFD and ACO techniques. The research paper also presents challenges and issues in cloud computing, VM migration process, VM migration techniques, their comparative review as well.
«Stepka-Rastrepka» in the minutes of the meeting of the Library Commission of the Society for the promotion of preschool education (based on materials from the archive of the Demonstration childhood reading library)

“Stepka-rastrepka” in the Minutes of the Meeting of the Library Commission of the Society for the Promotion of Preschool Education (based on Materials from the Archive of the Demonstration Childhood Reading Library) The article is devoted to the publication of the minutes of the meeting of the Library Commission of the Society for the promotion of preschool education, reflecting a lively exchange of views on “Stepka-Rastrepka”. On the one hand, “Stepka-Rastrepka” was banned for a long time by teachers, who categorically refused to recognize its literary and educational value. On the other hand, professional writers and artists (A. Blok, Z. Gippius, A. Remizov, A. Benoit, A. Ostroumova-Lebedeva) spoke out in defense of “Stepka-Rastrepka” and urged not to deprive children of such fun and entertaining reading. The article also provides brief information about the activities of the Society for the promotion of preschool education and the work of its Library Commission, which discussed a wide range of issues related to literature for preschool children. The original protocols are stored in the Fundamental library of the Herzen State Pedagogical University and are available to all categories of researchers. Keywords: Stepka-Rastrepka, children’s literature, children’s reading circle, Society for the promotion of preschool education, Library Commission, children’s literature library, Demonstration library for children’s reading, discussion about children’s literature, criticism of children’s literature
REDUCING COMPLEXITY OF GRAPH ISOMORPHISM PROBLEM

Graph isomorphism has been discussed in the literature as NP-hard problem.It has applications in various areas.Work done earlier in this area employs backtracking for identifying isomorphism between given two graphs as a result with the increase in size of the graph the time to solve the problem becomes exponential.The proposed work presents a polynomial time algorithm (PTGI) which tries to solve graph isomorphism between given two directed graphs.Some distinguishing features associated with each vertex are stored.These features are exploited in dividing the vertices of the graph into equivalence classes from which canonical representation of the graph is generated.Comparing these features of the vertices of the given two graphs solves isomorphism in polynomial time.