Reviewerly/exHarmony huggingface dataset:
Self-Service Technology Berbasis Android Menggunakan RestFul Web Service Pada Bisnis Restoran

The process of ordering food and beverage menus at the Meatzilla restaurant still uses paper and stationery. Constraints that are often encountered are when restaurant visitors are crowded, but waiters are limited, often mistaken of orders and loss and order of paper orders and various other obstacles. This can cause feelings of disappointment and negative impressions which will certainly result in reduced customer satisfaction. This study aims to produce mobile device software that can support the running of food and beverage ordering systems at Meatzilla Restaurant self-service so that orders arrive quickly and right desires. This system is made using XML and java programming language with android studio tools version 3.5.3. Research in the form of case studies, software design methods using extreme programming models and system modeling tools using Unified Modeling Language (UML). This system is connected to the internet network where the admin, cashier, kitchen and customers are integrated with a restful web service. The final result of this study is a food and beverage ordering system consisting of 4 (four) parts, namely customer and admin software that is accessed by using a smartphone and the cashier and kitchen which is accessed by a PC / laptop. this system is very helpful in facilitating the management of customer orders.
A Game Model for Incentive Mechanism of Distributed Nodes in Supply Chains

This study aims to solve the credit problems in the supply chain commodity and currency circulation links from the perspective of the ledger, while the game model method has been adopted. The research firstly reviews the relationship between distributed ledger technology and the essential functions of currency. Then, by constructing two-agent single-period and multi-period game models in the entire supply chain, the researchers analysed the incentive mechanism and equilibrium solution of distributed nodes of Central Bank Digital Currency (CBDC). The results of this study include the incentive mechanism and optimization of distributed nodes based on licensed distributed ledger technology, which is an important issue that CBDC faces when performing currency functions. The implications of this study mainly cover the limitations of the underlying technology of the public chain and its reward mechanism in the supply chain management and provide support for the rationality of the CBDC issuance mechanism based on state-owned commercial banks, which provides a reference for the CBDC practice. The main value of the research not only serves the decision-making department of the CBDC issuance but also provides ideas on the operation mode of digital currency for the field of digital currency research.
Image Watermarking Approach Using LSB and Laplacian Filter

Abstract With the growth of information technologies, E-industry safety has recently become the mutual attention of education and business firms. Digital image watermarking is a technique that refers to the security of multimedia data. It is a process referred to the security and authentication of a digital image, video, and audio by embedding a watermark. Watermarking technique applies a number of variable editions to the host content, where the addition is related to embed information. In the past, researchers develop multiple simple watermarking techniques, today race is to find a region where the watermark is imperceptible and have a high payload. In this paper, an invisible image watermarking technique based on the least significant bit (LSB) and laplacian filter is proposed. The original image is divided into blocks and the laplacian filter is applied on each block. Laplacian is a derivative filter that uses the second derivate to find out the area of rapid changes in the image and the least significant bit is a technique to embed a watermark into the bit positions. Watermark is embedded on these regions which is favourable in achieving high desirable properties. This technique shows strong robustness against image processing and geometrical attacks. In evaluation with state of art methods, the proposed technique shows satisfactory progress.
A randomized block policy gradient algorithm with differential privacy in Content Centric Networks

Policy gradient methods are effective means to solve the problems of mobile multimedia data transmission in Content Centric Networks. Current policy gradient algorithms impose high computational cost in processing high-dimensional data. Meanwhile, the issue of privacy disclosure has not been taken into account. However, privacy protection is important in data training. Therefore, we propose a randomized block policy gradient algorithm with differential privacy. In order to reduce computational complexity when processing high-dimensional data, we randomly select a block coordinate to update the gradients at each round. To solve the privacy protection problem, we add a differential privacy protection mechanism to the algorithm, and we prove that it preserves the [Formula: see text]-privacy level. We conduct extensive simulations in four environments, which are CartPole, Walker, HalfCheetah, and Hopper. Compared with the methods such as important-sampling momentum-based policy gradient, Hessian-Aided momentum-based policy gradient, REINFORCE, the experimental results of our algorithm show a faster convergence rate than others in the same environment.
Vehicles detection based on their seismic surface waves using classification techniques

PreviousNext No AccessSixth International Conference on Engineering Geophysics, Virtual, 25–28 October 2021Vehicles detection based on their seismic surface waves using classification techniquesAuthors: Ahmad Bahaa AhmadTakeshi TsujiHakim SaibiAbdelkader Nasreddine BelkacemAhmad Bahaa AhmadKyushu UniversitySearch for more papers by this author, Takeshi TsujiKyushu UniversityKyushu UniversitySearch for more papers by this author, Hakim SaibiUnited Arab Emirates UniversitySearch for more papers by this author, and Abdelkader Nasreddine BelkacemUnited Arab Emirates UniversitySearch for more papers by this authorhttps://doi.org/10.1190/iceg2021-063.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Current vehicle classification techniques have depended on the information of photos or videos. However, these techniques usually face criticism because the techniques invade drivers' privacy and expose their identity. Also, the vehicle identification based on seismic ambient noise signals was difficult because of various noises. In this paper, we consider the time series data similarities between vehicles based on the seismic signal. We have applied different Artificial Intelligence (AI) techniques to construct the training model using raw data of three different sizes of vehicles (bus/truck, car, motorcycle) and surrounding noise. This study investigates the decoding performance of Logistic Regression (LR), Support Vector Machine (SVM), and Naïve Bayes (NB) to classify vehicles by using vertical component data. The 2-class classifiers were trained on 600s and tested on 100s for each class. The Naïve Bayes has shown high classification accuracy during training for all binary classification scenarios. AI-based decoding algorithm with high performance can be used for traffic monitoring and security purposes, covering large areas without intruding on drivers' privacy, and it is more efficient and lowers cost. Keywords: machine learning, surface wave, artificial intelligence, algorithm, amplitudePermalink: https://doi.org/10.1190/iceg2021-063.1FiguresReferencesRelatedDetails Sixth International Conference on Engineering Geophysics, Virtual, 25–28 October 2021ISSN (online):2159-6832Copyright: 2021 Pages: 341 publication data© 2021 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 24 Dec 2021 CITATION INFORMATION Ahmad Bahaa Ahmad, Takeshi Tsuji, Hakim Saibi, and Abdelkader Nasreddine Belkacem, (2021), "Vehicles detection based on their seismic surface waves using classification techniques," SEG Global Meeting Abstracts : 244-247. https://doi.org/10.1190/iceg2021-063.1 Plain-Language Summary Keywordsmachine learningsurface waveartificial intelligencealgorithmamplitudePDF DownloadLoading ...
Flow architecture for sustainable homes, office buildings, community centers and museums: In memory of Professor Mihály Csikszentmihalyi and poet Géza Szőcs

This trend research article accounts on a unique interdisciplinary collaboration of two highly creative personalities: psychologist Mihály Csikszentmihályi, Distinguished Professor of Psychology and Management at Claremont Graduate University and poet Géza Szőcs, President of the Hungarian Pen Club. Guidelines of Flow architecture were set: a new building should create dynamic spaces, sustain departure and return, bridge timeframes, create balance between lights and colors, and contain elements that surprise people.
Design and Research of a Foul Detector for Long Jump Stepping on a Jump Line Based on the Wireless Sensor Network

In view of the problems of the judgment of the referee in international long jump competition, such as the omission and wrong judgment, a real-time, accurate, and effective detection instrument is designed. The sensor carried on the athlete is used as the detection element of the foul, which ensures the accuracy and timely information acquisition and effectively prevents the wrong judgment and the missed judgment. The system data is transmitted by the wireless sensor network, which is highly safe and reliable. The experimental results show that compared with the traditional artificial judgment results, the long jump crossover line foul detector based on the wireless sensor network can realize the accurate detection of the number of fouls. The judgment error is lower than the requirements of track and field rules for detection tools, which has great practical value and economic significance.
Gamification as a New Format of Projects Method in Blended Learning Conditions Studying Disciplines of the Pedagogical Cycle

The paper discusses the main issues of organizing the learning process based on the gamification. The publication analyzes the main provisions of the application of elements of gamification in the process of teaching students. The study proposes to consider gamification as a new format of the project method in the context of blended learning in the study of disciplines of the pedagogical cycle by students of humanitarian and natural specialties. We analyzed the main didactic Classcraft platform capabilities. Developed by students within the framework of the “Pedagogy” discipline a brief structure of the “Adventurers” quest was present. The algorithm of the students' work included following steps: choosing a project theme (name of the game); composition of the game (stages); development of the game as a digital product (elements); analysis of the implementation of the game as a digital product (difficulties and prospects); analysis of the results of joint digital project activities of students, indicating positive and negative aspects. We considered the positive aspects of using digital applications and platforms to improve teacher skills. The conclusions provide consolidated proposals for the use of gamification, such as: its implementation in the educational process is aimed at the development of intellectual, social, emotional, technological segments of the personal development of students; the use of gamification has a positive impact on the development of students and teachers soft skills and helps to improve their professional skills.
Solving game problems using recursion

The article describes the methodology to game problems of Olympiads in informatics using recursive numbers generation. The study is based on the sequential solution of increasingly complex tasks. For each task, the following materials are given: the condition of the task, the idea of the solution with a proposal to come up with an independent implementation, the solution in the Pascal programming language. Distance learning system DL.GSU.BY is the effective technical base for teaching. It allows offer the student a condition of the task; send the solution for review; get a verdict from the system — a correct or incorrect solution; for incorrect solutions, the number of the test on which the solution did not pass is indicated. A student can take a test (input and output data), on which his solution did not pass, figure out what the error is in his program, correct and send the solution again. In addition, for each problem there is a link on it to the topic in the forum at site, where you can ask a question on solving this problem and / or read the answer if the questions have already been asked before.
Augmenting the City: The Photo-Realistic Animation of a Historic Building and its influence on spatial perception and meaning

Augmented Reality (AR), defined as the holographic overlay of physical space with virtual objects in real time (Azuma, 1997), can be considered a prime example of mediatization. This development is particularly evident in the public space of the “mediatised city” (Hepp, Simon &amp; Sowinska, 2018), being a focal point of the latest media technologies already overlaid with a multitude of AR content. But how does AR change the perception and meaning of urban space? And how can researchers capture methodically the appropriation of complex, large-scaled AR content experienced via high-tech AR glasses? To answer these questions, a historical building, that had been destroyed during the Second World War, was reconstructed as a holographic animation on a public city square. In order to resurrect this building in AR, old photographs, paintings and postcards were evaluated and used to create a virtual model in the original size and place it at its original location. The test subjects were then able to view the hologram from various different angles using AR glasses (Microsoft HoloLens 2), move freely around the square and even enter it. Combining quantitative, before-and-after questionnaires and qualitative thinking-aloud protocols, our results show that the holographic animation of a historical building can influence both the sensual-aesthetic perception and the personal meaning of a public square for city dwellers. Specifically, our test subjects perceived differences in its accessibility, coherence and aesthetics, simplicity, atmosphere and legibility. The meaning of the square was altered with regard to personal memories (= the self), typical groups of people (= others) and certain opportunities (= environment) associated with it by city dwellers.
Research on Chinese Short Text Segmentation for New Media Comments

With the development of new media industry, comments based user interaction is now fairly routine in live broadcasting. User comments usually appear in the form of short text with freestyle and cyber new words. The general word segmentation methods could not adapt to Chinese short text in new media comments. This paper proposes a novel method of Chinese short text segmentation to solve the problem of word segmentation granularity self-adaption. A New Media Comment Short Text Dataset(NMCD) is built for our researches, a word vector text containing cyber new words and entity words as well. Our optimized bidirectional Long Short Term Memory(LSTM) model based on attention mechanism and transfer learning could make number and its unit together after the word segmentation. The experiment results show that the Fl-score is improved by 21.43%. The word segmentation method in this paper could be efficiently applied to the new media comments analysis system later.
A Study on the Effects That SMEs’ Response to Non-Tariff Barriers Exerts on Export Performance: Focusing on Technical Barriers to Trade

Purpose &#8211; This study analyzes the effects that the response to the technical barriers to trade (TBT), which are used by various countries as means to restrict imports, exerts on exports at a time when protectionism is emerging in the face of a global economic downturn. TBT has been widely used in developed countries for the safety and protection of their people. Recently, the use of TBT as a tool of protectionism has increased considerably in developing countries as well. Therefore, this study analyzes the South Korean SMEs’ response and export performance. Design/methodology &#8211; To analyze SMEs’ response to TBT and their export performance, this study conducted empirical analysis through statistical analysis. To this end, the research established a theory based on previous research and designed its hypothesis and research model. To verify the hypothesis and research model, factor analysis addressing validity and reliability was performed using SPSS 25 and AMOS 26, and the structural equation model was analyzed. Findings &#8211; This study found the causal relationship between the independent variable, the mediating variable, and the dependent variable adopted against the theoretical background to have little or no effect, in contrast with previous studies. In a break from previous studies, all hypotheses were rejected for innovation strategic competencies, one of the sub-factors of the independent variable, which is believed to be a result of the lack of practical research related to TBT. Originality/value &#8211; Previous studies performed analysis using trade statistics or macro data. A number of such studies analyzed the relationship between technical regulation and trade volume. This study differs from previous studies in some respects, because it analyzed the export performance of companies by establishing a hypothesis and implementing a research model with the factors analyzed in previous studies. In addition, a new attempt has been made by classifying the TBT response factors into technology competencies, human resource competencies, and innovation strategic competencies, and utilizing technology innovation and the export support system as mediating effects.
Misbehavior Detection based on Multi-Head Deep Learning for V2X Network Security

Misbehavior detection in vehicular networks is an important field of research that focuses on designing and developing mechanisms to detect anomalous behaviors pertaining to vehicle movement, data transmission. Misbehavior detection systems help to protect vehicular networks from insider attacks that are generated within the vehicular network system and avoid dangerous situations on time. In this paper, we propose a deep learning based misbehavior detection architecture in vehicular networks. The proposed architecture consists of a multi-head convolutional neural network (CNN) and long short-term memory (LSTM) network. The simulation results demonstrate that our proposed method is more effective to detect misbehaviors as compared to previous methods in terms of accuracy.
Ecological Education by Means of Literature at School

The relevance of the article is due to the urgent need to improve the ecological education of schoolchildren in connection with active human intervention in nature and causing irreparable harm to it. Now it has become obvious that the knowledge gained by students in the study of natural sciences is not enough to foster a sense of responsibility for the state of nature. This deficiency can be filled with fiction, which clearly reflects the interaction of man and nature in different epochs of the development of society. However, in the existing methods and technologies for studying literature at school, insufficient attention is paid to the formation of the ecological culture of students. The work on environmental education in the study of works of art is carried out irregularly, the methodology of conducting a lesson, taking into account environmental education, needs further development. The purpose of the article is to form a respectful attitude towards nature and awareness of its indispensability for humans as an environment in students by means of fiction. The research is based on the concept of humanistic pedagogy, ecological and value-orientational approaches. The main research methods were the theoretical method, the axiomatization method, and the modification method. Based on the work done, it has been established that fiction containing ecological material contributes to the awareness of students of the inextricable connection between man and nature, reveals the beauty of the natural environment, evokes a sense of responsibility for its condition, awakens a protest against the predatory attitude towards it. It has been proved that ecological education by means of literature should be carried out along with moral, patriotic, aesthetic education, relying on the methodology of studying a work of art, using methods and techniques that are most appropriate to the material being studied. Among them, both traditional ones - the word of the teacher, conversation, independent work, creative reading, the heuristic method - which have been tested by many years of pedagogical practice, and new ones - the design-research method, the method of concepts. It has been determined that an indispensable condition for the successful ecological education of students, along with the use of the means of school subjects, is their involvement in active practical ecological activity.
Ownership protection for light-field 3D images: HDCT watermarking

Watermarking plays an important role in ownership protection. The embedding strength of the watermark determines the robustness of the watermark and affects the imperceptibility of the watermark. Setting appropriate embedding parameters can balance the robustness and imperceptibility of the watermark. Considering the high-dimensional characteristics of the light-field 3D image, we decide to extract more features from the light-field image to control the embedding parameters accurately to improve the visual quality of the watermark. Therefore, in this paper, we present a method of ownership protection for the light-field image based on high-dimensional color transform (HDCT) watermarking. Our paper introduces an HDCT space to unify multiple different color spaces, rather than selecting a specific color space for processing. By mapping low-dimensional RGB colors into high-dimensional color space, in which the feature vectors can separate the salient region from the background linearly, and extract the embedding parameters accurately. The experimental results show the superiority of the proposed algorithm compared with the existing light-field watermarking algorithm, from the two aspects of imperceptibility and robustness.