Reviewerly/exHarmony huggingface dataset:
Dynamic Estimation Method of Construction Cost Based on Particle Swarm Optimization Algorithm

The dynamic estimation method of project cost based on Particle swarm optimization algorithm is a new method of project cost evaluation. This method mainly introduces Particle swarm optimization algorithm into the process of project cost evaluation to optimize the parameters and weight distribution of the evaluation model, so as to improve the accuracy and reliability of the evaluation results. The main feature of this method is its dynamism, as it can adjust the evaluation model in real-time according to different engineering changes to achieve more accurate dynamic cost estimation. Therefore, this method can better cope with the complexity and variability of engineering construction. The specific realization of this method is to introduce the Particle swarm optimization algorithm, set the optimization model according to the estimation goal and range, and calculate and adjust the optimization goal of each parameter as the objective function. This method can be solved through multiple iterations to obtain the optimal solution, thereby achieving accurate calculation of dynamic estimation of engineering costs. In a word, the dynamic estimation method of project cost based on Particle swarm optimization algorithm can provide more accurate cost estimation results of buildings and related projects, and solve the problem that there is a large deviation between the accuracy of cost estimation and the actual cost in the industry. This method can not only improve the accuracy of engineering budgets, but also improve the efficiency and quality of construction, making positive contributions to the sustainable development of the construction industry.
Internet of Things (IoT): Resilience as a key Parameter in Security Management

Internet of Things (IoT) has significantly impacted the energy sector to improve energy efficiency, reduce costs and enhance operational performance. Such an adoption of technology in the energy sector presents significant security challenges that needs to be addressed to ensure the safe and secure operation of critical infrastructure. This paper reviews the literature available on the application of IoT in energy sector. This paper studies the key challenges in securing the IoT devices in the energy sector. The paper highlights the importance of a strong security framework that includes encryption and authentication techniques, effective access control mechanisms and continuous monitoring of the IoT network. This paper presents details of some of the available solutions in the market to address these challenges in the best possible way.
A Secured Framework for Metaverse Applications

Recent times have observed the popularity of metaverse platforms grow continuously, so does the increase in need for reliable and secure frameworks to provide user with privacy, data integrity and a trustworthy environment. This paper presents a secured framework that integrates both private and public Blockchain. Considering previous research in the field of Blockchain security, the framework incorporates decentralized authentication, layered protective protocols, Smart-contract based access control along with consensus mechanism to ensure the integrity of metaverse transactions and prevent unauthorized access. Furthermore, the framework support measures to protect user data and prevent data breaches. The proposed framework addresses key challenges related to security, privacy and data distribution within a metaverse.
Dynamic obstacle avoidance of a mobile robot using AR markers

For the mobile robot to move to the target position, it is necessary to safely avoid collisions with surrounding objects. In this study, we propose a new dynamic obstacle avoidance algorithm for mobile robots using AR markers and cameras. The proposed method predicts the trajectory from the change in the position information of the dynamic obstacle, and controls the velocity of the mobile robot so that the mobile robot keeps a certain distance from the dynamic obstacle and avoids collision. Simulation and experiments demonstrate the effectiveness of the proposed method.
A Study on the Classification of OT Security Risk Mitigation Measures

It is an emergent issue that countermeasures against cyber-attacks on operational technology (OT) systems such as critical infrastructures and control systems. The principal of the countermeasures is based on a risk analysis is performed for each asset to be protected in the OT system. And appropriate risk mitigation measures are prepared to reduce the risk to an acceptable level. The risk is determined by the damage caused by the attack and the probability of its occurrence. Thus, risk reduction measures include attack avoidance, probability reduction, damage control, and quick recovery, only IT security technology is often discussed today. We can get effective security measures by appropriately combining various risk reduction measures, not only IT security. This paper considers the classification and arrangement of security risk mitigation measures for effective OT security solution construction.
Identification and Authentication using Clavicles

In recent years, wireless devices have become smaller and more portable. In addition, it is thought that personal identification and authentication will be necessary when they are used as independent terminals similar to smartphones. In this study, we focus on a neck-mounted earphone and propose personal identification and authentication using the acoustic characteristics of the clavicle, taking advantage of the fact that the clavicle touches the device when it is worn. Active acoustic sensing was used to measure the acoustic characteristics of the clavicle and extract its acoustic features. The accuracy was 98.8%, and the EER was 4.0% in five persons.
FORMATION OF EDUCATIONAL INDEPENDENCE AS A CONDITION FOR ACADEMIC PERFORMANCE

Introduction. Improving the academic performance of students is one of the urgent problems of modern higher education, since academic activity is a determining indicator of the readiness of university graduates for professional activities. Academic achievement depends on many factors, among which the authors emphasize the ability and desire to study as the basis of educational independence.&#x0D; The purpose of the study. The purpose of the study is to examine the degree of influence of the formation of the motivational sphere and skills of independent work, determining the educational independence, on the academic performance.&#x0D; Materials and methods. The following methods were used to achieve the research objectives: questioning, testing, comparative and correlation analysis. The results were processed by methods of mathematical statistics in SPSS Statistics 26.&#x0D; Results. The results obtained allow us to conclude that the formation of independent work skills has a relationship with academic performance, while strong positive relationships were identified between the indicators for all five blocks of independent work skills, as well as internal and external positive motivation. Practical recommendations on maintaining the optimal motivation of students are presented.&#x0D; Practical implications. The results can be used to further investigate the factors that influence academic performance and find ways to improve it.&#x0D; Conclusion. After analyzing the results, the authors concluded that the important conditions for academic performance are the formation of the structure of independent educational activities of students, as well as the leading role of their internal and external positive motivation. Higher educational achievements are possible only with high levels of formation of the structure of students’ own educational activities and their positive motivation. From here follow two main directions related to the prevention of academic failure and dropout of students: the formation of optimal ways for them to independently solve educational, and in the future, professional problems and, in addition, high positive motivation at all its hierarchical levels.
POSSIBILITIES OF DIGITAL EDUCATIONAL TECHNOLOGIES AS A WAY OF ORGANIZING A DIGITAL EDUCATIONAL ENVIRONMENT

The article reveals the concepts of digital technologies and digital educational technologies as a way of organizing a digital educational environment and a means of forming students’ universal skills that will be applicable in their future professional and personal growth.&#x0D; The purpose of the article is to identify the possibilities of digital educational technologies, as well as the classification of digital resources and tools that contribute to improving the effectiveness of schoolchildren’s learning.&#x0D; Methodology. The basis of the research is formed by the methods of studying and analyzing scientific publications that study aspects of the problem under study, summarizing one’s own experience in the use of digital educational technologies in the educational process, as well as systematizing the studied information.&#x0D; Results. The possibilities of digital educational technologies in the educational process are described as a way of organizing a digital educational environment. It was revealed that digital educational technologies in close connection with digital educational resources in the educational process give the educational process dynamism, activating mental, cognitive, communicative and educational functions in the classroom.&#x0D; Practical implications. The results obtained can be applied in the didactics of higher and secondary schools.
ENHANCEMENT OF PROFESSIONAL COMPETENCE OF EDUCATIONAL PROFESSIONALS IN THE CONTEXT OF ORGANIZING METHODOLOGICAL SUPPORT

The article is dedicated to the issues of improving the professional competencies of educational professionals through the organization of methodological support within the framework of creating a unified system of professional development and implementing the “Modern School” federal project.&#x0D; The authors disclose the specifics of methodological support for educators aimed at identifying professional deficits, employing individual educational route technologies, and developing competence enhancement programs. The authors present a model of organizing methodological support for educational professionals, including a component for future educators, thereby proving the importance of organizing methodological interaction with practicing educators to shape a new type of university graduate capable of continuous professional growth. The authors are convinced that involving educators and students, i.e. future educators, in scientific and methodological events, including joint planning, contributes to the development of analytical skills and methodological culture, enhances professional mastery, fosters the establishment of conscious professional positions, and improves communication formats. Special attention is given by the authors to the application of normative and legal foundations for the organization of a multi-level methodological support system involving various methodological structures, professional communities, and subject associations.&#x0D; The article is addressed to the faculty and staff of the supplementary professional education system, research workers, doctoral students, teachers, and students of educational institutions, as well as those interested in educational issues in the field of improving the professional competence of educational professionals.
A Hybrid Photorealistic Architecture Based on Generating Facial Features and Body Reshaping for Virtual Try-on Applications

&#x0D; &#x0D; &#x0D; Online shopping using virtual try-on technology is becoming popular and widely used for digital transformation because of sustainably sourced materials and enhancing customers’ experience. For practical applicability, the process is required for two main factors: (1) accuracy and reliability, and (2) the processing time. To meet the above requirements, we propose a state-of-the-art technique for generating a user’s visualization of model costumes using only a single user portrait and basic anthropometrics. To start, this research would summarize different methods of most virtual try-on clothes approaches, including (1) Interactive simulation between the 3D models, and (2) 2D Photorealistic Generation. In spite of successfully creating the visualization and feasibility, these approaches have to face issues of their efficiency and performance. Furthermore, the complexity of input requirements and the users’ experiments are leading to difficulties in practical application and future scalability. In this regard, our study combines (1) a head-swapping technique using a face alignment model for determining, segmenting, and swapping heads with only a pair of a source and a target image as inputs (2) a photorealistic body reshape pipeline for direct resizing user visualization, and (3) an adaptive skin color models for changing user’s skin, which ensures remaining the face structure and natural. The proposed technique was evaluated quantitatively and qualitatively using three types of datasets which include: (1) VoxCeleb2, (2) Datasets from Viettel collection, and (3) Users Testing to demonstrate its feasibility and efficiency when used in real-world applications&#x0D; &#x0D; &#x0D;
Initial Coin Offering Prediction Comparison Using Ridge Regression, Artificial Neural Network, Random Forest Regression, and Hybrid ANN-Ridge

&#x0D; &#x0D; &#x0D; Can machine learning take a prediction to win an investment in ICO (Initial Coin Offering)? In this research work, our objective is to answer this question. Four popular and lower computational demanding approaches including Ridge regression (RR), Artificial neural network (ANN), Random forest regression (RFR), and a hybrid ANN-Ridge regression are compared in terms of accuracy metrics to predict ICO value after six months. We use a dataset collected from 109 ICOs that were obtained from the cryptocurrency websites after data preprocessing. The dataset consists of 12 fields covering the main factors that affect the value of an ICO. One-hot encoding technique is applied to convert the alphanumeric form into a binary format to perform better predictions; thus, the dataset has been expanded to 128 columns and 109 rows. Input data (variables) and ICO value are non-linear dependent. The Artificial neural network algorithm offers a bio-inspired mathematical model to solve the complex non-linear relationship between input variables and ICO value. The linear regression model has problems with overfitting and multicollinearity that make the ICO prediction inaccurate. On the contrary, the Ridge regression algorithm overcomes the correlation problem that independent variables are highly correlated to the output value when dealing with ICO data. Random forest regression does avoid overfitting by growing a large decision tree to minimize the prediction error. Hybrid ANN-Ridge regression leverages the strengths of both algorithms to improve prediction accuracy. By combining ANN’s ability to capture complex non-linear relationships with the regularization capabilities of Ridge regression, the hybrid can potentially provide better predictive performance compared to using either algorithm individually. After the training process with the cross-validation technique and the parameter fitting process, we obtained several models but selected three of the best in each algorithm based on metrics of RMSE (Root Mean Square Error), R2 (R-squared), and MAE (Mean Absolute Error). The validation results show that the presented Ridge regression approach has an accuracy of at most 99% of the actual value. The Artificial neural network predicts the ICO value with an accuracy of up to 98% of the actual value after six months. Additionally, the Random forest regression and the hybrid ANN-Ridge regression improve the predictive accuracy to 98% actual value. &#x0D; &#x0D; &#x0D;
AI? Predictive Media. Art

In this paper, I shall explore the relationship between predictive text2image technology and art. To do this, I shall navigate the discursive landscape that facilitates the consideration of this cultural phenomenon within a rational framework. This is necessary because public discourse is mostly dominated by unrealistic expectations resulting from identifying this technology as “Artificial Intelligence.” The theoretical frame is posthumanism, which affords us the necessary intellectual tools to scrutinise the genesis of what Manovich calls “predictive media.” Equipped with the appropriate terminology, I will explore the process of the creation of images with a special focus on prompt engineering and curation to showcase the collaborative effort of the artist and the application. Furthermore, I shall refer to the competitions (Sony, Főfotó) wherein this technology plays a consequential role, to traditional art forms that share some crucial features with this technology, and some concerns related to predictive media will be raised. Through this analysis, I argue that contrary to early responses, predictive media applications bear the hallmark of art, and their creators rightfully merit the designation of artists.
EMERGENCY CALL APPLICATION

An application for calling emergency services has been developed. The application was devel-oped using the integrated Android Studio development environment in conjunction with the Ko-tlin programming language. The app runs on mobile devices running Android 8 and above
Examination of Awareness among University Students in Compliance with Loan Application Requirements in the Northern Zone of Tanzania

This study examined awareness among university students in compliance with loan application requirements in the Northern zone of Tanzania. The study was guided by the human capital theory by Gary Backer (1964). The study employed a convergent design under a mixed-methods research approach. The target population of the study was 11 universities, 3000 Second year undergraduate university students, 5 HESLB Personnel, 11 loan Officers represented HESLB at each university used in the study, and 11 Ministers of finance from the students' government from selected universities in the Northern Zone of Tanzania. Probability and non-probability sampling techniques were employed to obtain a sample of 300 second-year undergraduate students, 4 universities/colleges, 4 Ministers of Finances from the Student Government, and 3 loan officers who represent the HESLB in each University used in the study. The study engaged questionnaires, a document analysis guide, and an interview guide to collect data for the study. Content and face validity were ensured by MWECAU research experts. The reliability of questionnaires for Likert-type items was estimated using Cronbach's Alpha Coefficient, whereby r= 0.757 from students, whereas qualitative data were established through peer debriefing and triangulation. Descriptive statistics with the aid of the (SPSS) version 22 was used to analyze quantitative data and qualitative data were analyzed thematically by transcribing the information, coding, and themes supported with direct quotations. The study found that the criteria employed by HESLB had been achieved to a low extent in informing students about loan application requirements. The study concludes that the majority of university students had limited awareness of loan application requirements, possessing knowledge only about a few specific aspects of loan application requirements. The study recommended that HESLB should conduct a comprehensive review of the loan eligibility criteria to address diverse concerns among university students.
An Exploration of Key Success Factors for Enterprises Implementing Online Education Training Based on the Unified Theory of Acceptance and Use of Technology

Abstract The key factor in achieving a competitive advantage for businesses lies in the talents that cannot be easily replicated. In the face of economic changes and the post-pandemic era, leveraging technology to accelerate learning scenarios and enhance employee competitiveness becomes paramount in corporate management. Due to technological advancements, online learning, characterized by its freedom from temporal and spatial constraints, has emerged as one of the forms for corporate education and training. Past empirical studies on the effectiveness of online education have yielded mixed results. Therefore, this study seeks to explore the reasons behind these discrepancies, serving as a reference for formulating educational training programs and providing assistance to relevant industries in evaluating the implementation of online education and training. The researcher employs the Integrated Technology Acceptance and Use Model as the foundation. In the first phase, relevant literature is collected, leading to the identification of four dimensions and 14 indicators. In the second phase, a Likert five-point scale is employed to extract the top three indicators for each of the four dimensions. Finally, a survey using the Fuzzy Analytic Hierarchy Process questionnaire is conducted to obtain the relative weights for the four dimensions and twelve indicators, with the dimensions ranked in the following order: hedonic motivation, habit, price value, and personal innovativeness. The study concludes with five propositions, aiming to provide crucial reference points for companies implementing online education and training, ultimately speeding up adoption and enhancing the intention to use online education. JEL classification numbers: C83, I25, M53, O15. Keywords: Unified Theory of Acceptance and Use of Technology (UTAUT), employee training, online learning, Key Success Factor (KSF).
The research of prediction of future violent crime rate

Crime is a destabilizing factor in our society. However, if the government could understand how the violent crime rate would change, they could enact proper policy to cope with it. In this case, this research will predict the future violent crime rate based on the data from 1991 to 2020 since 1991 is an important turning point of American crime rate. With R-Studio, this research analyzes the effectiveness of the average method, nave method, drift method, linear model, and autoregressive moving average model (Arima model) in the prediction and selects the best one with the smallest residuals and negligible autocorrelation. Based on the analysis, the Arima (0, 2, 0), which is one type of Arima model, does the greatest job in the prediction. According to the model this research eventually uses, the violent crime rate will start to increase from 2021 to 2025, showing that the violent crime condition may get worse. As a result, the government should pay more attention to violent crime to maintain the social security.