Reviewerly/exHarmony huggingface dataset:
Application of image recognition based on neural network algorithm in multimedia dance teaching

Abstract Neural network recognition algorithm is a deep learning-based convolutional neural network, which has been applied to target detection, image recognition, sound recognition and other fields. Although the recognition technology of convolutional neural network has been gradually stabilized, it is mainly implemented in single machine serial mode. Therefore, there will be problems such as too long training time and insufficient memory capacity. According to the previous work, this paper has carried out related research and obtained some useful results. This paper focuses on the introduction of image recognition technology based on neural network algorithm. At the same time, this paper proposes a fast real-time image recognition algorithm, which has high recognition accuracy. In this paper, the existing algorithms mentioned in the paper are analyzed, the characteristics and shortcomings of all algorithms are summarized, and the appropriate combination of algorithms is selected for specific problems. On this basis, the acceleration method of artificial neural network is used to improve the algorithm of convolutional neural network image recognition technology. With the continuous development of education and the increase of the number of students year by year, the effect of classroom teaching becomes particularly important. Therefore, modern information technology is used to transfer the classroom teaching mode to the network and realize a new method of online remote online dance teaching. According to the actual situation of dance teaching, the advantages of multimedia dance teaching are analyzed. The software of multimedia dance teaching system is tested comprehensively, from the aspects of computer system memory occupancy rate and temperature, to test whether the activities of B/S mode multimedia dance teaching system meet the expected goals and requirements of each core module of multimedia dance teaching system.
The Institutionalisation of Information Security Management Practices in selected Organisations in Uganda

The study aimed at examining the extent to which information security management practices were institutionalised in corporate organisations. Evidence shows that failure by organisations to entrench the information security management practices (ISMPs) into organisations’ structures opens the gateway for attacks, threat actors and information breaches to cause harm to information assets with ease. The study explored the phenomenon in its social setting hence the adoption of descriptive research design as the research methodology. The institutional theory was adopted as a new dimension in examining information security management in organisations. This theory suggests that control gears like coercive, normative, mimetic and management commitment could be used to effectively entrench security guidelines in organisations. Methodical scrutiny of the institutionalisation process: development, implementation and maintenance, and evaluation were also carried out. The researcher relied on human experience to make sense of the institutionalised processes. Extant literature was reviewed, and survey questionnaires were developed based on the eleven ISMPs and administered to purposively selected respondents from the two organisations. The eleven ISMPs covered include state of information security policy, asset management, secure information sharing, supply chain security, access management, network security controls, portable and removable media security, remote access security, protective monitoring of information systems, implementation of information security back-ups, and security accreditation by professional bodies. Data analysis was done using SPSS. Findings indicate that organisations have not fully incorporated all the eleven ISMPs covered as best practices and standards. Based on the results from the field, answers to the research questions were partly realised. Recommendations like the implementation of ISMPs to check deficiencies identified, customisation of security guidelines to protect information assets and institutionalisation of security practices at all levels were suggested. Overall, the study was a positive step towards the institutionalisation process of ISMPs in organisations
Land Registration &amp; Transfer of Entitlement using Blockchain

Abstract: This project report aims to explore the potential of using blockchain technology for land registration. Land registration is a critical process that involves the transfer of ownership of land and property rights, which is often time consuming and prone to errors. Blockchain technology offers a secure and transparent method of recording land registration transactions that can significantly reduce the time and cost associated with traditional land registration systems. The report first provides an overview of blockchain technology, its characteristics, and how it works. It then discusses the current land registration systems and the challenges associated with them, such as fraud, corruption, and inefficiency.
Handwritten Digit Prediction Using CNN

Abstract: For many years, numerous methods have been used in extensive research on handwriting recognition. The capacity to create an effective algorithm that can recognise handwritten digits given by users via scanner, tablet, and other digital devices is at the core of the issue. The automatic processing of bank checks, postal addresses, and other sorts of data already makes substantial use of handwritten digit recognition. Computational intelligence methods like artificial neural networks used by several current systems. CNN and the MNIST data set will be used to complete this. Handwriting Recognition, Deep Learning, CNN, and Computational Intelligence are key terms.
The development of interactive chemistry lessons on the topic: «Mineral fertilizers»

The main methodological innovations today are the use of interactive learning technologies, involving each student in the learning process, i.e. in the process of cognition. The introduction of modern interactive learning technologies creates conditions for improving the quality of the training session, as well as methods of teaching chemistry. Each teacher uses new learning technologies to ensure that classes are systematic, high-quality, interesting, and effective. It is known that students have different ways of thinking and when conducting lessons, performing tasks with the help of illustrations, video materials, animation, and games increases interest in the subject. In this paper, interactive apps identified and described that contribute to increasing the activity of students and the effectiveness of the learning process in lower secondary school, as well as interactive chemistry lessons on the topic "Mineral fertilizers" are developed. In implementing the developed interactive lessons, such teaching methods as interactive lectures, interactive exercises, and didactic games were used. A relatively small sample size limited this study, but the results obtained have essential data for the professional development of teachers and the development of modern interactive lessons using ICT. The results obtained after a survey of students, in which 100 students participated, indicate that interactive lessons support learning and increase students' motivation, and this has a positive effect on their attitude to the subject
Design and Manufacturing of Medicine Reminder Bottle

Abstract: Our project main aim is to make a Smart medicine bottle for those users who regularly take medicines and the prescription of their medicine is very long as it is hard to remember for patients and also for their caregivers. Also, Old age patients suffer from problems of forgetting to take pills at the proper time which causes certain health issues for patients having Permanent diseases like diabetes, thyroid, blood pressure, breathing problem, heart problems, and cancer diseases. We saw these problems in hospitals &amp; people around us who have such kinds of diseases and thus based on these two problems we made smart medicine bottles that solve these problems by setting time schedule of prescribed medicines through push buttons as given in the prescription. (1).
Digital Evidence Security System Design Using Blockchain Technology

Digital evidence plays an essential role in meeting the forensic need to uncover cybercrime and search for trace information of perpetrators.Digital evidence is vulnerable to system changes, human error, theft, deletion, and data manipulation, requiring security efforts to maintain authenticity.This study offers optimization of the chain of custody systems to maintain digital evidence integrity using authentication applications connected to the website server database.The design of the chain of custody system uses blockchain technology and K-means clustering algorithm.This research process consists of two stages.The first stage is the prototype of blockchain-based user access authentication applications.The second stage is the implementation of K-means clustering to determine the place of data storage according to its classification.The results of this study are the maximum security for blockchain-based chain of custody with the efficiency value of this application of 94.73% and the system load value of 0.223%.The total cost of deploying the application is 0.026702786 ETH.Based on this research can help to secure digital evidence information.
ICRAIC 2022-Preface

Recent years have seen exciting new research and developments in Robotics, Automation and Intelligent Control. Computer and control technology, intelligent control, robotics and automation are changing many aspects of our productive lives. Thanks to computers and control algorithms brought by intelligent control and artificial intelligence, machines are becoming smarter. ICRAIC 2022 focused on the development and integration of robotics, digitalization, automation and artificial intelligence technologies. Therefore, the 2nd International Conference on Robotics, Automation and Intelligent Control (ICRAIC 2022) took place on December 9th-11th, 2022 in Changsha. ICRAIC 2022 has brought together leading academic scientists, researchers and research scholars to exchange their experience and research results in the field of intelligent robotics and systems and share their discoveries, insight and lessons learned, and take home exciting new ideas to perform further state of the art research to make mind-blowing collaborations and innovations. ICRAIC 2022 accepted 50 full papers which was divided into 3 tracks, including Robotics, Automation and Intelligent Control. And all submissions were peer-reviewed through a single-blind review process by an international panel of expert referees, and decisions were taken based on the criteria. Thanks to the ICRAIC 2022 Committee for their efforts in preparing the conference and ensuring its smooth running.: List of General Chairs, Program Chairs, Technical Chairs, Technical Program Committee, Organizers, Co-Organizer, Editors are available in this pdf
Comparative analysis of code execution time by C and Python based on selected algorithms

The article deals with a comparative analysis of the speed of code execution written in the C language and Python. In order to determine whether a scripting language can match the performance of a compiled language, a comparison of the languages was made using the following algorithms: the algorithm for solving the Hanoi tower problem, the Huffman encoding algorithm and the algorithm for converting numbers into text. Each of the listed algorithms was implemented in both languages. Then the execution time of the programs was measured and the results were obtained, which prove that the C language achieves better performance in most cases.
Fraud Apps Detection Using Sentiment Analysis and Spam Filtering

Abstract: In the mobile app industry, ranking fraud is the practice of engaging in dishonest or deceitful behavior with the intention of artificially boosting an App's position on a popularity list. In fact, ranking fraud by app developers is becoming more and more common. These practices include inflating their apps' sales or uploading fake app reviews. Although the significance of preventing ranking fraud has long been understood, little knowledge and research have been done in this field. In order to do this, we present a comprehensive analysis of fraud app detection using sentiment analysis and spam filtering in this study and suggest a system for detecting it in mobile apps.
Factors Determining the Optimization of Digital Technology in Rural Schools

Digital technology greatly benefits rural areas by providing access to information, education, and communication resources.For example, internet access can connect people in rural areas to online educational resources, job opportunities, and social networks.However, implementing digital technology in rural areas can be challenging due to myriad factors.In exploring the challenges and struggles of technology among students in rural areas, this research explores factors that contributed to the optimization of technology in rural localities.A quantitative descriptive and correlational study was employed on 231 fourth-grade secondary school students at the selected public schools in the eastern part of Malaysia.A set of questionnaires was developed and distributed on-field.Four variables were tested in this research: (a) knowledge, (b) motivation, (c) attitude, and (d) technology readiness.The findings demonstrated that knowledge of using digital technology was the prominent indicator depicting technology readiness among the studied population.Further discussions elaborated in this article promotes the better implementation of digital technology to rural school students which eventually prosper a meaningful learning ecosystem and embark nations' strategic planning on digitization effort.
Behavioural and Organisational Factors Determining Blockchain Adoption

Aims: To explore and describe behavioural and organisational factors playing a role in the adoption of blockchain technology in the supply network, next to technical aspects.&#x0D; Research Questions: (1) “Why would companies use it and insert information considered as strategic?” (2) “Why would customers use it and consumers trust it?” (3) “Is it suitable for every firm?”.&#x0D; Study Design/Methodology: A literature review combined with mind mapping describes potentially promising strong aspects and vulnerabilities. Limitations in present blockchain use are considered before moving towards a research method that observes, explains and predicts relevant human decision behaviour. A mixed methods approach of qualitative research applying Atlas.ti uses participative observations next to narratives and interviews with selected interviewees. This Step Wise Two Stage MiniDelphi approach was used, resulting in the opinions of experts in Supply Chain Management, fashion, food, HRM and IT.&#x0D; Theoretical Framework: A Grounded Theory based methodology is used; various types of Institutional Isomorphism form the main theoretical framework, next to the Resource Based View and Resource Dependence Theory. The behavioural and organisational factors relevant in actual decision making are captured in a hypothetical LISREL model.&#x0D; Findings: Blockchain technology has the potential to facilitate secure information transfer, meeting demands of transparency, traceability, confidentiality, security, integrity and availability. However, it expires that adoption not so much is determined by technical aspects. The willingness to insert strategic information satisfying downstream actors, is balancing the trust downstream actors have in upstream actors. Factors that make upstream actors decide to adopt are (1) price and total costs versus perceived additional revenue, reputation and competitiveness; (2) coercion, mimetic behaviour, following the industry norms, regulation or other external drivers. Using block chain as marketing tool for only part of the total volume of goods occurs. Volatile and momentary supply networks are less suitable; so are situations where the supplier has no choice but to use the buyer’s supply network, controlled by the buyer.
Enhancing Image Quality through Convolutional Neural Networkbased Image Denoising

Enhancing Image Quality through Convolutional Neural Networkbased Image Denoising
Analysis of Language Defense in Youtube Content Boy William National Examination (UNBW)

Politeness is basically the speaker's way of communicating so that the speech partner does not feel pressured, cornered, or offended. Communication is a process that occurs in social life. At this time, almost all Indonesian people use social media and the biggest user is YouTube social media. Youtube is a social media that is watched by all people and all ages. Youtube contains various types of content, one of which is Boy William's YouTube channel entitled Boy William's National Examination (UNBW). This series discusses Youtube content for Boy William's National Examination (UNBW) with actresses Ayu Ting-Ting and Anwar. Politeness in language on Youtube social media functions to fence off Youtube users as polite loudspeakers. Conversations during UNBW will be the object of language politeness analysis with a review based on Leech's theory. The politeness theory put forward by Leech (1983: 132) is known as maxims which describe the realization of linguistic politeness, and further elaborates the linguistic politeness strategy into 6 maxims namely: 1) tact maxim, 2) generosity maxim , 3) approbation maxim, 4) modesty maxim, 5) agreement maxim, and 6) sympathy maxim. After reviewing the data, I pointed out that the conversation on UNBW's Youtube content for the Ayu vs Anwar series contains language that is impolite for other people to watch but is still considered polite if this conversation is only for Boy William, Ayu Ting-Ting, and just Anwar.
Aesthetics Assessment of Automobile Headlights Based on Image Aesthetic Network

Abstract Automatically learned aesthetic assessment for images can provide auxiliary value for the fields of art and design. In this study, we explore the aesthetics assessment methods on the visual esthetics of automobile headlamp images, and compare the feasibility of the calculation method of artificial aesthetic degree evaluation. We take the Image Aesthetics Assessment Network using Graph Attention (AAGN) for the automobile headlamps dataset calibration. To enable testing the effectiveness of AAGN, we apply the method of artificial aesthetics degree calculation and entropy weight, as well as assessment methods based on deep Convolutional Neural Network. The results show that the feasibility of the image aesthetic assessment method based on graph attention network is more suitable for users’ subjective aesthetic needs than artificial aesthetics degree calculation.
The impact of ICT on inter-organizational knowledge sharing for SMEs growth

It is common knowledge that information and communication technologies (ICTs) have made continuous inroads in the knowledge management field; thus, this study is modeled to examine the impact of ICTs on inter-organizational knowledge sharing (IOKS) and its subsequent effect on the growth of small and medium-sized enterprises (SMEs). The study adopts a descriptive survey design, using the quantitative research approach. Using the simple random sampling technique, a web-based questionnaire was used to collect data from 187 respondents. Results showed that IOKS among SMEs is not carried out to a great extent, which means that it is not a common practice among SMEs. Findings showed that less than half of the SMEs used training programs, internship programs, research collaboration and workshops for IOKS. It further showed that IOKS enhances sales, productivity, profit, organizational assets and equity. This study provides evidence of how ICT systems/tools have been used in IOKS and their impact on the growth of SMEs.
LEARNING MOTIVATION OF FOREIGN LANGUAGE AMONG NON-LINGUISTIC SPECIALTIES’ STUDENTS

The article deals with the issue of the foreign language learning’s motivation among students of non-linguistic specialties. The relevance of the research is due to the ambiguous attitude of non-linguistic specialties’ students to the foreign language subject. We investigate that this is one of the main psychological and pedagogical problems in the framework of the research of psychological and pedagogical conditions for forming a foreign language learning motivation, based on analysis of the learning motivation. There are also noted the classification of motivation, and reasons contributing to a decrease in the motivation of learning. The article reveals evidence that allows us to determine the development level of the foreign language learning motivation among students of non-linguistic specialties, and its dependence on the psychological and pedagogical activity of the teacher during the educational process. Some of the study’s result, that firstly, show the process of forming a learning motivation, which is related to the implementation of different approaches; and secondly, some important factors affecting the students’ interest in the studied subject are summarized in the article.
Adaptive Bayesian Denoising for General Gaussian Distributed Partial Discharge Signals in 11 kV Stator Coil using Wavelet Transform

Noise removal from Partial discharge signal which is corrupted with Gaussian white noise, using Wavelet Transform (WT) based Bayes estimation is presented.Such corrupted partial discharge signal is considered to exhibit Generalized Gaussian Distribution (GGD).Denoising of partial discharge (PD) signals is one of the prime pre-processing stages which help in analyzing the effect of PD on insulation by studying its characteristics and features.The pre-and post-processing of PD signal can be performed significantly using wavelet transform.The WT based adaptive thresholding and coefficients modeling methods for denoising provides a better chance to reduce interferences.The estimation of BayesShrink based estimation of the denoised signal is performed from its noisy wavelet coefficients for the signals with Gaussian distribution.The BayesShrink threshold is independent of the coefficient distribution and is a function of noise and noiseless signal variance.BayesShrink is the most effective thresholding method providing threshold value by reducing the Bayes risk.The coefficient estimation based on Bayes method for GGD signals performs well in removing white noise from the corrupted PD signal.The PD signals are collected by conducting the experiment on damaged 11 kV stator coil which has mica as insulation.The collected signal is processed using WT based Bayes estimation.The result indicate that the optimum Bayes estimator with GGD behave similar to soft thresholding method.