Reviewerly/exHarmony huggingface dataset:
Miss-placement Prediction of Multiple On-body Devices for Human Activity Recognition

Nowadays, in industrial applications, automatic human activity recognition plays a central role. Especially human-centered activity recognition methods using on-body devices (OBDs) address situations where the identity has to be protected. However, practitioners strongly assume that end-users use OBDs correctly at deployment. In reality, this is hardly the case. Thus, there is a need for a robust activity-recognition system, either at the recording stage or at recognition stage. This contribution addresses a combination of both stages. It proposes a miss-placement recognition of OBDs on the human body when performing an activity. We deploy a limb-oriented temporal convolutional neural network to either recognize a miss-placement occurring or the type of miss-placement. Primarily results on a proposed dataset suggest that miss-placement classification is possible, which can be used for end-user feedback during recording or leveraged in data post-processing.
Guidance and Counseling Media to Develop Children's Language Creativity at Elementary Level

Creativity is an important element in the development of an individual's potential. However, in the current conditions, the development of creativity still cannot be carried out optimally. Minimal creativity development can result in an ineffective teaching and learning process. A way that is seen as being able to develop creativity is to provide facilities to students through guidance services that have direction and purpose. Guidance and counseling media always consist of two important elements, namely the elements of equipment or hardware (hardware) and the elements of the message they carry (message/software). Software is the information or guidance and counseling material itself that will be conveyed to the counselee, while the hardware is the means or equipment used to present the guidance and counseling message/material. Creativity requires both novelty and benefit which implies that an idea or concept may be new but if there is any use it cannot be termed as creative and vice versa. Creativity is the ability to create new forms, new cognitive structures, and new products, which may be physical, such as technology, or symbolic. This type of research in this paper uses qualitative research methods with a case study approach with a case study type. Collecting data through observation, and documentation of interviews conducted by Elementary Schools. The data obtained from various sources were then analyzed using descriptive analysis methods. Research results found that in communication, there are often barriers that prevent messages or information from being conveyed precisely and accurately. Therefore, the counseling teacher needs an intermediary in the form of guidance and counseling media. The ability to communicate, express what we think, and also catch the message conveyed by our interlocutor. Language can be a method of developing children's creativity because language is considered a way for children to be able to express what they experience and feel.
Poster: SigRec - Automatic Recovery of Function Signatures in Smart Contracts

Millions of contracts deployed onto Ethereum provide various services that can be invoked. For this purpose, blockchain users need to know and specify the function signature of a callee, which includes its function id and the parameter types. Function signatures are crucial in several applications, such as recognizing the services that contracts provide. In this poster, we propose a novel solution that leverages how functions are handled by Ethereum virtual machine (EVM) to automatically recover function signatures from contract bytecode, without the need of source code and function signature databases. The extensive experimental results show that our solution outperforms all existing tools, achieving an unprecedented 98.7% accuracy within 0.074 seconds. We further demonstrate the usefulness of our solution in attack detection, fuzzing and reverse engineering of contract bytecode.
B4B.World Demo: Influencer Marketing Cross-Chain Platform

This demo addresses the challenges of creating influencer marketing campaigns, including difficulties in measuring campaign performance and payment risks. Blockchain technology can provide a solution by offering reliable influencer profile generation, transparent reputation models, and template escrow payments. However, communication and processing of payments across ecosystems remain a challenge for Web3 projects. The paper presents B4B.World, an influencer marketing platform that utilizes cross-chain smart contract calls and supports payments in multiple blockchains. The platform offers reputation-based rewards for influencers and allows advertisers to make campaigns using crypto assets or project-based NFTs. B4B.World is the winner both The Illuminate/22 Hack by Moonbeam and BNB Chain Hackathon 23 in Georgia and utilizes the Axelar platform for cross-chain interaction.
PELATIHAN BAHASA INGGRIS UNTUK PEREMPUAN WIRAUSAHA DI KAMPUNG HERITAGE KAJOETANGAN, KOTA MALANG

City tourism is one of the attractions that can be visited by local and foreign tourists. City tourismhas various types of attractions, one of which is a tourist village. Tourism villages can improve thelocal community's economy and have the competitiveness to become the leading tourism in a city.Kajoetangan Heritage Village, which is located in Malang City, has tourism potential because it hasthe characteristics of a row of houses with Dutch colonial architecture that are still original andwell preserved. In addition, in this tourist village there are also entrepreneurs who are dominatedby women. This business has the potential to boost the economy by selling superior products andservices to tourists. This training aims to improve the English language skills of womenentrepreneurs in offering and selling their products to foreign tourists. As a result, participants areable to demonstrate skills in conducting conversations in English to sell and offer products andservices.&#x0D; &#x0D;
The Prediction of Douyin Live Sales based on Neural Network Algorithms

This paper aims to optimize neural network algorithms in order to improve their predictive performance and meet the demand for Douyin live sales forecasting. The Douyin live data of Florasis between January 2022 and June 2022 were collected from Huitun data and preprocessed. Using the Pearson correlation coefficient, six factors that are highly correlated with live sales were selected for subsequent prediction. This paper briefly introduces the back-propagation neural network (BPNN) algorithm and analyzes its parameter optimization methods, including particle swarm optimization (PSO), the artificial bee colony (ABC) algorithm, and the beetle antler search (BAS) algorithm. Then, an improved beetle antennae search (IBAS) algorithm was developed by introducing inertia weight and used to construct an IBAS-BPNN model for predicting sales volume in Douyin live streaming. The results showed that compared with the BPNN, PSO-BPNN, and ABC-BPNN algorithms, the IBAS-BPNN algorithm had better prediction performance, with a root-mean-square error of 335.6694, a mean absolute percentage error of 0.0532%, an equilibrium coefficient of 0.9889, and a shorter training time of 90.07 s. The experimental results demonstrate the reliability of the IBAS-BPNN algorithm for predicting sales volume in Douyin live streaming, providing new insights into parameter optimization of BPNN and offering references for further research on BPNN parameter optimization. It also provides an effective method with both timeliness and high accuracy for predicting sales volume in Douyin live streaming in practical applications. Doi: 10.28991/HIJ-2023-04-02-09 Full Text: PDF
Price Prediction Of Basic Material Using ARIMA Forecasting Method Through Open Data Sumedang District

In the era of Industry 4.0, characterized by the abundance of data, there are many opportunities to carry out various data-related processes. One of these is the data forecasting process which has been widely used. By analyzing data, we can make predictions and make decisions automatically. For example, one of the problems that decision-makers, especially in Kabupaten Sumedang, must solve is the changes in the prices of basic commodities that are essential for society's consumption. The prices of these commodities in the market tend to fluctuate in the short or long term. By analyzing the available data, we can predict the direction of changes in the prices of basic commodities in the market. In this study, the ARIMA model is used, which is one of the time series models that can be used to predict the possibility of an increase or decrease in the prices of basic commodities in the market in Kabupaten Sumedang. The ARIMA model uses the previous day's price data as a benchmark to predict the prices of basic commodities in the future. After being analyzed, the results of the model will be in several ARIMA model forms. An efficient ARIMA model will be used to model the prices of basic food commodities. This research produced the three best ARIMA models, namely ARIMA(1-1-1) for broiler chicken meat, ARIMA(0-1-1) for shallots, and ARIMA(0-1-1) for garlic. The accuracy test results percentage error for the best model using MAPE show an average value below 10%. Keywords: Food staples, Forecasting, Time Series, ARIMA, MAPE
PROSPECTS FOR THE DEVELOPMENT OF SMART EDUCATION IN UKRAINE

Innovative educational technologies: European experience and its application in training in economics and management : Proceedings of scientific and pedagogical internship (February 13 – March 26, 2023, Riga, Latvia). Riga, Latvia : “Baltija Publishing”, 2023.
ANALISIS IMPACT LEADERSHIP STYLE OF THE FOUNDER ON THE EFFECTIVENESS OF BOARD IN NONPROFIT ORGANIZATIONS

Innovative educational technologies: European experience and its application in training in economics and management : Proceedings of scientific and pedagogical internship (February 13 – March 26, 2023, Riga, Latvia). Riga, Latvia : “Baltija Publishing”, 2023.
Role of federated learning in edge computing: A survey

&lt;p&gt;This paper explores various approaches to enhance federated learning (FL) through the utilization of edge computing. Three techniques, namely Edge-Fed, hybrid federated learning at edge devices, and cluster federated learning, are investigated. The Edge-Fed approach implements the computational and communication challenges faced by mobile devices in FL by offloading calculations to edge servers. It introduces a network architecture comprising a central cloud server, an edge server, and IoT devices, enabling local aggregations and reducing global communication frequency. Edge-Fed offers benefits such as reduced computational costs, faster training, and decreased bandwidth requirements. Hybrid federated learning at edge devices aims to optimize FL in multi-access edge computing (MAEC) systems. Cluster federated learning introduces a cluster-based hierarchical aggregation system to enhance FL performance. The paper explores the applications of these techniques in various domains, including smart cities, vehicular networks, healthcare, cybersecurity, natural language processing, autonomous vehicles and smart homes. The combination of edge computing (EC) and federated learning (FL) is a promising technique gaining popularity across many applications. EC brings cloud computing services closer to data sources, further enhancing FL. The integration of FL and EC offers potential benefits in terms of collaborative learning.&lt;/p&gt;
Improving The Performance of the K-Nearest Neighbor Algorithm in the Selection of KIP Scholarship Recipients

Law 12 of 2012 mandates that the government increase access to higher education for high achievers and underprivileged people. One of the efforts to realize this is by providing KIP Lectures. To ensure that beneficiaries are indeed eligible for KIP scholarships, it is necessary to classify scholarship recipients with data mining classification techniques correctly. The classification technique chosen is k-Nearest Neighbor (K-NN). K-NN is a classification method that relies heavily on the k parameter in carrying out classification. K-NN was applied to the KIP Scholarship applicant dataset at UIN Malang in 2022. The test scenario in this research is to compare the k-odd and k-even parameters to find the most optimal k value in K-NN. The highest accuracy value obtained by k-odd is 0.71 or 71% when k=9, and the highest for k-even is 0.67 or 67% when k=10. Using optimal k parameters is proven to improve k-NN performance. The K-NN algorithm with k-odd parameters, namely k=9, is the best method for classifying KIP scholarship recipients in this research. The results of this research can be considered in determining KIP scholarship recipients worthy of using K-NN.
SOCIAL PARTNERSHIP AS A CONDITION FOR SUPPORTING PROFESSIONAL ORIENTATION AT SCHOOL

The article discusses the methodology and technology of the social partnership model in terms of network interaction when organising career guidance in the “rural lyceum – flagship university” dyad, its practical application in the context of a particular territorial entity. The authors study the organisational, structural and content changes in the partnership support of students of the Korkatovsky Lyceum in the Republic of Mari El .
Analisis Kebutuhan Pengguna pada Pengembangan Malang Virtual Tourism dengan Ambience Lingkungan Terintegrasi

The use of VR in the tourism business continues to increase. The use of VR for tourism is known as virtual tourism. virtual tourism can simulate tourist destinations using a virtual environment (VE). Virtual tourism is expected to enhance the experience for tourists and attract new markets to tourist destinations. Malang City is one of the tourist destinations in East Java, and is always visited by both domestic and foreign tourists. However, Malang City is still not a major destination in tourism, compared to Batu City (Kota Batu) and Malang Regency (Kabupaten Malang), this is due to the lack of vigorous promotion. In order to provide a pleasant experience for its users, Malang Virtual Tourism must be developed based on user needs. Based on these problems, a virtual reality application will be developed that can provide immersive experiences to users related to tourist destinations in Malang City. At the requirement analysis stage, a specification design of the system to be made includes functional and non-functional requirements needed for the development of the system in this research will be carried out. The requirement analysis process involves potential users of the system. We were identifying the requirements by numbering each requirement that has been made with a Use case diagram and Use case Scenario. This step generates a general description and system requirements. The results of this stage get five functional requirements and one non-functional, usability.
The High School Student Study Pre-parents’ Perceptions About Childcare Education of Infants and Toddlers

The purpose of this study was to investigate the perception of parents of prospective high school students on the education of their children in early childhood. The subjects of the study were 245 high school students enrolled in G Metropolitan High School. The research questionnaire consisted of the number of children expected, the gender of the desired child, the reason why the child is needed, the desired form of education for infants and toddlers, the most important points when educating infants and toddlers, the education that should be given the most priority to infants and toddlers, the best way to educate infants and toddlers about basic lifestyle habits and personality, the cost of education for infants and toddlers for one month, the future hope that our child will become the most, and the most influential for infants and toddlers to grow. As a result of the analysis using SPSS 23.0, the respondents showed a tendency to expect two children and want them regardless of gender, and emphasized bonding and a sense of creation and achievement as reasons for needing children. The desired form of education for children in early childhood appeared to be parents, and character education was considered the most important. In addition, personality education and basic lifestyle habits were shown to be the education that should be given the highest priority, and the opinion that it should be carried out naturally at home was emphasized. The monthly cost of children's education was less than 50 to 1 million won, and the children's future hopes were mainly what the children wanted, and the parents' education and upbringing methods had a great influence on the growth of children. This study will be used as an important basic data for the education of infants and toddlers in Korea.
Analyze the Hot Spots, Development Process and Development Context of AI Research With the WoS Database of the American Institute of Scientific Information

Artificial intelligence has been studied for 70 years since the 1950s. In recent years, artificial intelligence technology has been widely used in various fields of society and has made great contributions to the country
Security Testing With Python Scripts

Cyber security is one of the main issues that is discussed today everywhere in the world. The development of technology has grown rapidly and it is important that this development should be done simultaneously with the increase in security. When we talk about the network, we must also consider its "Security". On the other hand, Python is a language which, especially in recent times, has received a great development and now we can say that it enjoys such a wide community. Our goal in this article is the advantages that this programming language offers in cases of cyber security issues. It has everything that cyber security professionals need to protect against cyber vulnerabilities and threats. It allows developers to do anything that relates to cyber security by detecting threats to system fixes. Python is a high-level, general-purpose, interpreted programming language for analyzing small networks. So, the implications of the study are for cybersecurity professionals and developers. They use the NetworkX grid tools imported into python. NetworkX provides many functions and generation facilities to read and write graphics in many formats. By analyzing these network nodes graphs, are identified the nodes that can be "bad". With Python scripts, you can scan ports and compromised device. In order to achieve this, we have obtained two concrete dataset which were obtained respectively from a public and a private network. After analyzing the graphs, the weaknesses of the network and unidentified devices in the network are identified, creating the possibility of taking appropriate measures to protect against cyber-attacks.
An Automatic Recommendation Process to Generate Learning Paths Based on Learner Preferences

In the last few years, recommendation systems have become very important and nowadays represent a huge opportunity for e-commerce, social networks and especially e-learning. In particular, it is a commercial tool that increases the revenue of companies, it facilitates the life of users by offering suitable products or services to all Internet users. Moreover, the interest of recommender systems in the context of learning, and in particular distance learning, is that they transform the normal learning system into a personalized learning system. In this paper, we present a new learning path recommendation system based on both the coefficients and scores we have assigned to each topic included in a learning path and on the scores assigned by learners to each topic, expressing their level of interest in a specific area. This system processes a set of input data that are composed on the one hand: parameters resulting from the profiles of the learners, these parameters are scores assigned by each user to each topic, and on the other hand, data related to the learning paths, which show the score or a coefficient that we have assigned to each subject included in the learning path. The objective of this work is to have a system that returns results in the form of appropriate recommendations to each learner who wishes to take courses on a given topic. The results obtained will allow us to have an overview of the preferences and characteristics of the learners in order to better guide them in their educational adventure in each learning path. In fact, this demonstrates the effectiveness and importance of our presented methodology.
Secured Face Recognition System Based on Blockchain with Machine Learning

Face recognition system has become an integral part of the security mechanisms used in the IoT applications. Smart cities and industries started deploying face recognition applications for security purposes through surveillance cameras and biometric systems. In computer vision, facial recognition has been a widely studied area and has become mature. Recent developments in hardware and deep learning usage for face recognition techniques improve accuracy and considerably reduce the processing time after training the model. This chapter proposes a face recognition system with blockchain for a secured and tamper-free facial recognition. The face recognition system uses VGG19 to train image data to identify the face in the image or in the video. VGG19 model is utilized to reduce training time and reduce the sample size. This system uses sample image data to train the model for recognizing the face. With blockchain, the data stored in the database for face recognition, is secured, and prevents unauthorized alteration in the data from hackers or any malicious activities.
Satisfacción estudiantil respecto a las actividades y contenidos curriculares de la educación en línea ecuatoriana

Student satisfaction has a direct impact on issues such as student training, permanence in the career and motivation, among others.This work seeks to know the degree of satisfaction that students of the Initial and Basic Education careers of the Technical University of Manabí-Ecuador have, in relation to the activities and curricular contents developed during their online modality studies.The research is quantitative, descriptive and transversal.The study population was considered to be 595 students from the first and second semester.The survey was used as an information collection technique, materialized through an estimation scale.The instrument was validated by experts, obtaining a Kendall W Concordance coefficient of 0.9124 and a Cronbach's Alpha reliability coefficient of 0.869.The results obtained, taking the subject variable as a reference for analysis, show a high degree of student satisfaction in different subjects of the curricula of the careers investigated.Therefore, it is concluded that the students of the Initial Education and Basic Education careers feel a high level of satisfaction with the contents and study activities in the online careers of the Technical University of Manabí-Ecuador.