Reviewerly/exHarmony huggingface dataset:
Cloud mobile display and interaction framework of virtual reality 3D scenes

We propose a framework for cloud mobile virtual reality (VR) applications on smart phone web browsers. It combines cloud rendering and panoramic stereo imaging technology to realize interactive high-quality 3D scene display on smart phones. The images of the VR 3D scenes are transmitted in the manner of video stream, and the interactive data is processed by the proposed anti-jitter algorithm (AJA). A web-side lightweight rendering approach is also realized in our framework. Use of our framework can both reduce the computational cost of displaying VR 3D scenes on smart phones, meanwhile eliminating the need of installing plug-ins or dedicated APPs. Our framework can interactively display VR 3D scenes on a smart phone web browser and provide satisfactory immersive experience for observers with the help of VR glasses.
Gray Scale Image Colorization for Human Faces

Image colorization is an eclectic topic of research. Former approaches to the gray scale image colorization problem rely on manual methods with human intervention that produced some de-saturated results that are not likely to be true colorizations. To fully automate the process of colorization, enormous amount of computation power and datasets are required which is daunting. This paper proposes an approach to fully automate the task using an autoencoder model restricting our domain to just colorizing human faced images. This can be useful in colorizing old black and white pictures and movie snapshots. We used Convolution Neural Network (CNN) for colorization because of its ability to deal with image datasets. This approach includes pre-processing input images, model generation, training and post processing of output. The experimental results demonstrated that this method outperforms the state of art technique as far as human faces are concerned.
ANALISIS POLA PEMBELIAN KONSUMEN MENGGUNAKAN ALGORITMA APRIORI PADA AL BAROKAH MART

ABSTRACTThe application of apriori algotrihm data mining system with is very useful for searching consumen buying patterns. Al barokah mart is a minimarket uses computerized system for selling goods such as foods, drinks and household products. In this study case, author has collected transactions data from Al Barokah Mart, before started, the interview and observation to research object has been done. After that, data was sorted by random sampling then made into tabulation data, determined data with minimum value of support and confidence. Data will be tested using data mining software, the result comes out through apriori algorithm method. The highest results with minimal support value 12.24% and confidence value 92.31% which are snack, lighter, cigarette. With the application of this method, the layout of goods is more selective and the procurement of goods is updated after knowing the results.
An Improved Grey Wolf Optimizer with Hyperbolic Tangent Updating Mechanism for Solving Optimization Problems

The original algorithm of Grey Wolf Optimizer (GWO) has a common problem which is too soon to trap in local optima. This paper presents the Improved Grey Wolf Optimizer (IGWO) by modifying the updating mechanism of the original GWO. The main idea of the new improvement is by introducing a nonlinear updating mechanism based on the hyperbolic tangent function to improve the efficiency of the exploration and the exploitation phase and to decrease the probability of trapping in local optima. The effectiveness of the new approach is evaluated on 30 well-known benchmark functions, and the results are compared with the original GWO. The preliminary findings show that the IGWO algorithm is able to obtain very competitive results in terms of objective functions minimization compared to original GWO algorithms.
A Analyzing and Implementing Metaheuristic GWO and FF Algorithms aiming to develop a Fault-Tolerant Hybrid GWOFF Algorithm: introduction, state of art, contribution and implementation, conclusion and future work, references

The approach adopted to handle hard problems is known as metaheuristics. The problem is considered as hard if discovering the optimal solution for it may not be always possible within the stipulated time. Discovering a single solution to a problem is easy and can be accomplished extremely fast, but finding the best possible solution to the same problem is very long. Optimization algorithms are intended to bridge this gap. The research paper aims at solving the problems for finding the optimal solution for two popular metaheuristic algorithms, GWO (Grey Wolf Optimization) and FF (Firefly) algorithms. Both the metaheuristics algorithms, GWO and FF algorithms are studied and implemented. The two technical features comprised of metaheuristic algorithms are exploration and exploitation. The optimal solution has been evaluated alongside Makespan and Utilization Rate for both GWO and FF algorithms. The lower value of the Makespan and higher Utilization Rate is always desirable. Both the algorithms have been modified via using mathematical functions to enhance the readings concerning performance evaluation parameters. The GWO is been modified via developing a hybrid version comprising GWO and PSO (Particle Swarm Optimization) algorithms denoted as the Hybrid Modified GWOPSO algorithm. The FF algorithm too has been modified and is denoted as a Modified FF algorithm. The conducted modifications have been measured via different performance evaluation parameters. Finally, the fault tolerance factor is considered and the modified versions Hybrid Modified GWOPSO and Modified FF are hybridized to develop a new hybrid algorithm Hybrid GWOFF (Hybrid Grey Wolf Firefly) algorithm and its performance have been evaluated with and without fault tolerance.
DEVELOPMENT OF PROJECT-BASED WORKSHEETS ON THE UTILIZATION OF RED DRAGON LEATHER (Hylocereus costaricensis) FOR NATURAL COLOR OF PERCA FABRIC

This study aims to analyze the validation test results and describe project-based worksheet products' appearanceon the utilization of red dragon fruit peel (Hylocereus costaricensis) waste for natural dye patchwork. The researchmethod used is Design-Based Research (DBR). The stages of this DBR method use the ADDIE design, whichconsists of 1) Analysis, 2) Design, 3) Development, 4) Implementation, and 5) Evaluation. The instruments usedwere worksheets, worksheet grids, validation sheets, and validation questionnaires filled in by three validators.The validation test percentage in this study was 86%, with a value of 0.86 obtained. Thus it can be concluded,learning media using project-based worksheets is declared valid.
Что такое искусство: современные смыслы и вызовы

This article presents a search for an answer to the question “what is art?” in the changed conditions of our time. The author does not aim to develop a modernized definition of such a polysemantic concept as art, but at the same time the relevance of rethinking and clarifying individual definitions is obvious. There are many objects and projects at modern exhibitions that position themselves as works of art cause a lot of controversy among viewers and critics. Finding markers that make it possible to separate genuine works from “various types of art” (Yu.M. Lotman) is a difficult and urgent task. Initially, the author examines the stages of formation of the “art” concept and its functions,  tested  by  time,  briefly  reveals  the  importance of  the  main  functions  (aesthetic,  cognitive-heuristic, communicative,  educational,  etc.).  Further,  it  is  noted that such fundamental criteria as aesthetic qualities and skill, the professionalism of the performance of a work in the XX–XXI centuries in many artistic practices have lost their significance. Almost any activity aimed at creating projects that do not carry a functional load has received the  right  to  be  called  art.  However,  art  is  a figurative assimilation  of  reality,  therefore,  using  new  materials and trying to saturate his creation with actual meanings, a modern artist will only remain in the field of art when his  work  has  deep  artistic  imagery.  In  the  traditional way of development of art, the sensual, aesthetic material for  creating  an  artistic  image  dominates,  in  postmodern trends – contexts and associations. In the conclusion, the need for the responsibility of art to society and society to art is emphasized.
The Analysis of Computer Crimes Act 1997 in the Circumvention and Prevention of Computer Crimes in Malaysia

Computer Crimes Act 1997 (CCA 1997) was conceded by Malaysia’s legislative body in 1997 and the Act was enforced in June 2000. The purpose of CCA 1997 is to provide for offences related to misuse of computers such as hacking, cracking and phishing. CCA 1997 was modelled after United Kingdom’s Computer Misuses Act 1990 as a response to the emerging computer crimes. This legislation is divided into three parts and 12 Sections. The first part outlines preliminary matters that include short title and relevant definitions, second part provides for the offenses related to misuse of computers and specifies penalties for each offences, and the last part deals with ancillary provisions such as jurisdictional and investigational issues of cybercrime. The main objective of this paper is to discuss the development of computer crimes and its deterrence in Malaysia. Specific sections of CCA 1997 will be analysed in details and detail assessment on the prevention and prosecution of computer crimes in Malaysia will be accessed to determine whether CCA 1997 is so far adequate in preventing computer crimes in Malaysia.
МЕТОДИЧЕСКИЕ ВОЗМОЖНОСТИ ПРИМЕНЕНИЯ МОБИЛЬНЫХ ОБУЧАЮЩИХ ТЕХНОЛОГИЙ В БИОЛОГИЧЕСКОМ ОБРАЗОВАНИИ

The impact of new technologies on education is growing every day, in particular, distance learning, online contests and trainings, video conferences and webinars, mobile learning, electronic and digital educational resources, etc. Mobile teaching technologies have become key components of innovative achievements. Сurrently, the use of mobile learning technologies in the education system is an urgent issue. The article deals with the role and trends, methodological possibilites of using mobile learning technologies in education. The terms of mobile learning are explained, the issues of using mobile technologies in education and the course of their study are outlined. Several mobile applications used in biology teaching are taken as the object of analysis.
IMPROVING STUDENTS’ WRITING ABILITY THROUGH TEAMS-GAMES-TOURNAMENT (TGT) ON PROCEDURE TEXT OF THE THIRD GRADE AT SMP PAB 2 HELVETIA

The objective of this research was to improve students' writing ability through teams games tournaments on procedure text. This research was conducted at SMP PAB 2 Helvetia, the amount of participants who following this research were 32 students. The researcher using Class Action Research (CAR) to know the appropriate data. The appropriate data showed that the total were 81,25% students who succeed the Minimum Mastery Criteria (KKM) >75. The appropriate data come of Cycle I and Cycle II. In the Cycle I using pre-test I the total of students who succeed were 6 students in the third class (9-7) totally 18,75%. Then in the Cycle II using pre-test II, the total of students who succeed were 16 students s in the third class (9-7) totally 50%, and the last the post-test II the total of students who succeed were 26 students  in the third class (9-7) totally 81.25%.
Security Issues in Cloud Computing: A holistic view

In recent years, cloud computing has developed into one of the fastest growing areas in the IT industry and a key driver for achieving an organization’s mission. Some examples of cloud computing are: Google apps, data centre services, infrastructure, software, virtualization and platform-as-a-service. Microsoft, HPE, IBM, Amazon Web Services, Google, SalesForce, NetSuite, and VMware are some of the leading cloud computing companies. Despite the numerous benefits of cloud computing, it presents many unique security issues and challenges due to which companies are concerned about the security of their data once it leaves the firewall. Nowadays, security is a top concern for IT professionals worldwide and want to ensure their cloud data to be prevented from being leaked, stolen or deleted. This article seeks to present a comprehensive picture of cloud computing security, as well as identify and analyse the most vulnerable security concerns and cloud computing threats, so that end users and service providers are aware of the important security concerns and threats associated with cloud computing.
IMPROVING STUDENTS’ PRONUNCIATION BY USING MESSAGE IN THE BOTTLE AT THE EIGHT GRADE STUDENTS OF SMP BINA SATRIA MEDAN

The research of aim was to improve pronunciation ability by using message in the bottle . This kind of research was Class room research consist of two cycles. The subject of this study was 30 students’ eight grade students at SMP Swasta Bina Satria Medan. The instrument used data quantitative (Sound Production Test) and data qualitative (Observation Sheet). Based on the record of the test, the students' score improved in every test. In The first cycle, the students' score was 40% and in the second cycle the students' score was 80 %. Based on the data observation, it was found that teaching learning process ran well. After the students' did treatment by message in the bottle, the students’ achievement in pronouncing English words improved. The result of the research showed that the used of Message in the bottle in teaching English is effective to improve the students’ pronunciation.
Noisy-MAPPO: Noisy Credit Assignment for Cooperative Multi-agent Actor-Critic methods

Multi-Agent Reinforcement Learning (MARL) has seen revolutionary breakthroughs with its successful application to multi-agent cooperative tasks such as robot swarms control, autonomous vehicle coordination, and computer games. Recent works have applied the Proximal Policy Optimization (PPO) to the multi-agent tasks, called Multi-agent PPO (MAPPO). However, the MAPPO in current works lacks a theory to guarantee its convergence; and requires artificial agent-specific features, called MAPPO-agent-specific (MAPPO-AS). In addition, the performance of MAPPO-AS is still lower than the finetuned QMIX on the popular benchmark environment StarCraft Multi-agent Challenge (SMAC). In this paper, we firstly theoretically generalize PPO to MAPPO by a approximate lower bound of Trust Region Policy Optimization (TRPO), which guarantees its convergence. Secondly, since the centralized advantage value function in vanilla MAPPO may mislead the learning of some agents, which are not related to these advantage values, called \textit{The Policies Overfitting in Multi-agent Cooperation(POMAC)} problem. We propose the noisy credit assignment methods (Noisy-MAPPO and Advantage-Noisy-MAPPO) to solve it. The experimental results show that the average performance of Noisy-MAPPO is better than that of finetuned QMIX; Noisy-MAPPO is the first algorithm that achieves more than 90\% winning rates in all SMAC scenarios. We open-source the code at \url{this https URL}.
Matching User Interfaces to Assess Simple Web Applications (Short Paper).

This paper presents ongoing research aiming at the automatic assessment of simple web applications, like those used in introductory web technologies courses. The distinctive feature of the proposed approach is a web interface matching procedure. This matching procedure verifies if the web interface being assessed corresponds to that of a reference application; otherwise, provides detailed feedback on the detected differences. Since web interfaces are event-driven, this matching is instrumental to assess the functionality. After mapping web interface elements from two applications, these can be targeted with events and property changes can be compared. This paper details the proposed matching algorithm and the current state of its implementation. It also discusses future work to embed this approach in a web environment for solving web application exercises with automatic assessment.
Feature Fused Human Activity Recognition Network (FFHAR-Net)

With the advances in smart home technology and Internet of Things (IoT), there has been keen research interest in human activity recognition to allow service systems to understand human intentions. Recognizing human objectives by these systems without user intervention, results in better service, which is crucial to improve the user experience. Existing research approaches have focused primarily on probabilistic methods like Bayesian networks (for instance, the CRAFFT algorithm). Though quite versatile, these probabilistic models may be unable to successfully capture the possibly complex relationships between the input variables. To the best of our knowledge, a statistical study of features in a human activity recognition task, their relationships, etc., has not yet been attempted. To this end, we study the domain of human activity recognition to improve the state-of-the-art and present a novel neural network architecture for the task. It employs early fusion on different types of minimalistic features such as time and location to make extremely accurate predictions with a maximum micro F1-score of 0.98 on the Aruba CASAS dataset. We also accompany the model with a comprehensive study of the features. Using feature selection techniques like Leave-One-Out, we rank the features according to the information they add to deep learning models and make further inferences using the ranking obtained. Our empirical results show that the feature Previous Activity Performed is the most useful of all, surprisingly even more than time (the basis of activity scheduling in most societies). We use three Activities of Daily Living (ADL) datasets in different settings to empirically demonstrate the utility of our architecture. We share our findings along with the models and the source code.
PERANCANGAN APLIKASI INVENTARIS BARANG BERBASIS WEB DENGAN PENGUJIAN MENGGUNAKAN PEMODELAN NIELSEN

The development of technology is increasingly fast and developing, so the need for a technology is one of the webs-based software technology, with this web being used to make difficultwork easy, the purpose of this research is to design and build an inventory application for Islamic boarding schools Miftahul Jannad. in the survey village by applying the Nielsen modeling. The research method used is the method of observation, interviewsand literature studies, the approach method is the Nielsen modeling method, where Nielsen's modeling consists of learnability, efficiency, memorability, few errors, satisfaction, the results of Nielsen's modeling are obtained to test the validity of learnability with counted r counts. 0.868, 0.845, 0.736, 0.619, Efficiency with r count 0.813, 0.461.0.636, 0.557, for Memorability is 0.773, 0.830, 0.814, 0.578 for memorability with the calculated r value of 0.773, 0.830, 0.814, 0.578, then for few errors obtained a value of 0.621, 0.765, 0.704, 0.653, then for satisfaction with a value of 0.732, 0.559, 0.662, 0.652, which means that with the calculated r value is more r table, where the r table is obtained 0.320, the data in the Nielsen modeling is valid, while for the reliability test it is stated that the results of the Nielsen modeling test are reliable.Keywords :learnability, efficiency, memorability, few errors, satisfaction
The Impact of Blockchain Technology on Consumer Behaviour: A Multi-Method Study

Blockchain is a ground-breaking technology that is transforming supply chain management. This study aims to empirically investigate the impacts of blockchain technology on consumer behaviour. We conduct this research in collaboration with a Chinese e-commerce company who has introduced a blockchain platform for tracing. We use a multi-method design by combining natural experiment and case study methods. First, we collected data from four industries (i.e., milk powder, seafood, alcohol and nutrient) to conduct the experiment and the findings reveal that firms that adopted the blockchain tracing system have an increase in product sales and a decrease in product returns compared to those who did not. Second, we conducted a multiple case study with four cases from the four industries. The findings reveal that the adoption of the blockchain tracing system improves supply chain transparency and process management which then enhance consumer service and trust. This study contributes to the literature by providing empirical evidence that adopting blockchain technology can improve firms’ marketing performance. The findings also reveal that how the adoption of blockchain technology affects consumer behaviour.
Implementasi Algoritma Zhu Takaoka Pada Aplikasi Sinopsis Film Bioskop Berbasis Mobile

Cinema is a place for people to enjoy film shows, where the audience devotes all their feelings to the living picture being witnessed. The audience will witness a story that seems real in front of them. Cinema is one of the many alternatives for someone to have a recreation. The sharpness and sound effects of the cinema also greatly determine the satisfaction of the public who is watching a film show as personal entertainment. A cinema film synopsis is a summary that becomes a picture of a cinema film. Synopsis of cinema films can be an attraction for cinema lovers before watching cinema films because the summary of cinema films in the synopsis, cinema lovers can find out the information on films that will be screened on a bisokop. Based on time, many new cinema films will be shown in a cinema. This makes the synopsis of cinema films more and more and makes it difficult for the public to find a synopsis of a particular cinema in a short and precise time in order to find information on the title of the movie theaters are looking for
Associative learning of new word forms in a first language and haptic features in a single-day experiment

Author(s): Yang, Yutao; Yan, Yan; Ando, Misa; Liu, Xinyi; Kambara, Toshimune | Abstract: This study focused on associative learning for new words in the first language and haptic stimuli. In the first, healthy Japanese participants made nine subjective evaluations of haptic stimuli using five-point semantic differential scales (e.g., regarding stickiness, scored from 1 [not sticky] to 5 [sticky]). In the second and third, the participants carried out two learning tasks for associative pairs of a new word in Japanese and haptic stimulus (H), or new words only (W). In the fourth one, after each learning task, participants performed recognition and free recall tasks. The results of the recognition tasks showed that the accuracy rates of W were better than those of H, whereas the response times of W were faster than those of H. Further, preference of haptic features negatively correlated with free recall scores of H; however, there was no significant difference between the free recall scores of H and W.
Using Machine Learning Algorithm to Enhance Phishing Emails Classification

Phishing emails are becoming a more dangerous problem in online bank truncation processing problem, as well as social networking sites such as Facebook, Twitter, and Instagram. Phishing is typically carried out by imitating an email or embedding content in the email body, which prompts consumers to submit their credentials. &nbsp;Training on the phishing strategy is not so much effective since users forget their training tricks and warning messages after a while. It is entirely dependent on the user's activity, which will be taken at a specific time in response to software warning messages while operating any URL. On the basis of the Spam base dataset, this paper improves phishing email classification using J48, Nave Bayes, and decision tree. J48 performs the best classification on spam basis, with a true positive rate of 97 percent and a false negative rate of 0.025 percent. Random forest work best on small dataset that is up to 5000 and number of feature are 34. However, when the dataset size is increased and the number of features is reduced, Nave Bayes works faster.