Reviewerly/exHarmony huggingface dataset:
An Investigation Of Factors Influencing The Implementation Of Cloud Computing By SMEs

Cloud Computing has emerged as a groundbreaking technology with widespread impact, bringing ad- vantages such low initial costs, cost-effectiveness for intermittent use, ease of management, scalability, device and location independence, and rapid innovation to businesses of various scales. Despite the benefits of implementing Cloud Computing, SMEs are yet to fully embrace it. To increase cloud implementation rate there is the need to investigate the key factors that influence its implementation by SMEs. The study employed the TOE framework to identify factors that have great influence in cloud implementation through a literature review and a survey of selected SMEs. A closed ended questionnaire was developed to ascertain these factors within the context of Bolgatanga by engaging key stakeholders, including ICT managers, CEOs/General Managers, and Admin/Accounts personnel, of selected SMEs to provide insights into the study. The study reveals that relative advantage holds the most significant influence among various factors, such as compatibility, top management support, competitive pressure, and regulatory support, across technological, organizational, and environmental categories in the cloud implementation process. This underscores the importance for SMEs to prioritize effective communication especially the benefits of cloud technology to stakeholders. This would pose a great deal for SMEs to implement cloud thereby enhancing business operations.
Anemia detection through non-invasive analysis of lip mucosa images

This paper aims to detect anemia using images of the lip mucosa, where the skin tissue is thin, and to confirm the feasibility of detecting anemia noninvasively and in the home environment using machine learning (ML). Data were collected from 138 patients, including 100 women and 38 men. Six ML algorithms: artificial neural network (ANN), decision tree (DT), k-nearest neighbors (KNN), logistic regression (LR), naive bayes (NB), and support vector machine (SVM) which are widely used in medical applications, were used to classify the collected data. Two different data types were obtained from participants' images (RGB red color values and HSV saturation values) as features, with age, sex, and hemoglobin levels utilized to perform classification. The ML algorithm was used to analyze and classify images of the lip mucosa quickly and accurately, potentially increasing the efficiency of anemia screening programs. The accuracy, precision, recall, and F-measure were evaluated to assess how well ML models performed in predicting anemia. The results showed that NB reported the highest accuracy (96%) among the other ML models used. DT, KNN and ANN reported an accuracies of (93%), while LR and SVM had an accuracy of (79%) and (75%) receptively. This research suggests that employing ML approaches to identify anemia will help classify the diagnosis, which will then help to create efficient preventive measures. Compared to blood tests, this noninvasive procedure is more practical and accessible to patients. Furthermore, ML algorithms may be created and trained to assess lip mucosa photos at a minimal cost, making it an affordable screening method in regions with a shortage of healthcare resources.
Conclusion

In this book, we have delved into the intersection of artificial intelligence (AI), biometrics, and cybersecurity, exploring the advancements, challenges, and applications in these fields. Throughout the 12 chapters, we have provided a comprehensive exploration of various topics, offering insights into the integration of AI techniques with biometric authentication systems and their impact on cybersecurity.
Role of AI in social cybersecurity: real-world case studies

The rapid advancement of artificial intelligence (AI) has significantly influenced the field of social cybersecurity, addressing the challenges of protecting individuals and communities in the digital realm. This chapter explores the role of AI in social cybersecurity through real-world case studies, showcasing its application and impact in various contexts. The abstract delves into the practical implementations of AI technologies, such as machine learning and natural language processing, to detect and prevent cyber threats, identify malicious activities, and safeguard sensitive information. The case studies highlight how AI-powered solutions have improved the efficiency and effectiveness of cybersecurity measures, leading to enhanced threat intelligence, faster incident response, and proactive defense mechanisms. Moreover, ethical considerations and privacy concerns associated with AI in social cybersecurity are examined, emphasizing the need for responsible and transparent practices. This chapter concludes by discussing the potential future developments and challenges in the field, calling for continuous innovation, collaboration, and adaptation to ensure the resilient protection of individuals and societies in the face of evolving cyber threats.
MEGI'S BOOK AS AN ATTEMPT TO INCREASE KNOWLEDGE AND REDUCE PLAQUE SCORE FOR CHILDREN WITH INTELLECTUAL DISABILITIES

Background: Intellectual disabilities is a term used to refer to children who experience limitations in their intellectual functioning. Such limitations in the learning process can affect their dental and oral hygiene. A total of 22 children with intellectual disabilities at Cineam State Special Elementary School (SDLB), Tasikmalaya Regency, underwent OHI-S (Simplified oral hygiene index) assessment based on specific criteria. Objective: This study aims to identify the impact of the using of scheduled diary media containing pictures of brushing teeth (MEGI) on the level of knowledge and dental and oral hygiene in children with intellectual disabilities. The research method used is quasi-experimental research with a one group pre-post test design. 33 samples of children with intellectual disabilities were selected using the purposive sampling method. After that, an oral hygiene index (OHI-S) was checked and a questionnaire was distributed to measure their level of knowledge. The collected data was analyzed using the Wilcoxon test with the help of the SPSS application. Results: The results of statistical analysis (p &lt; 0.005), showed a significant influence between counseling and the level of knowledge and dental and oral hygiene of respondents. Conclusion: The media of megi book”s ith pictures of brushing teeth have a positive influence on increasing knowledge and dental and oral hygiene in children with intellectual disabilities.
Cloud Computing a key to Supply Chain Management: Embracing the Cloud Advantage

Cloud-based Supply Chain Management (SCM) is a rapidly evolving approach which uses cloud computing to improve the efficacy and efficiency of supply chain operations. There are numerous methods for managing supply chains, including employing Excel spreadsheets and web-based programmes.
TranSpec3D: A Novel Measurement Principle to Generate A Non-Synthetic Data Set of Transparent and Specular Surfaces without Object Preparation

Estimating depth from images is a common technique in 3D perception. However, dealing with non-Lambertian materials, e.g., transparent or specular, is still nowadays an open challenge. However, to overcome this challenge with deep stereo matching networks or monocular depth estimation, data sets with non-Lambertian objects are mandatory. Currently, only few real-world data sets are available. This is due to the high effort and time-consuming process of generating these data sets with ground truth. Currently, transparent objects must be prepared, e.g., painted or powdered, or an opaque twin of the non-Lambertian object is needed. This makes data acquisition very time consuming and elaborate. We present a new measurement principle for how to generate a real data set of transparent and specular surfaces without object preparation techniques, which greatly reduces the effort and time required for data collection. For this purpose, we use a thermal 3D sensor as a reference system, which allows the 3D detection of transparent and reflective surfaces without object preparation. In addition, we publish the first-ever real stereo data set, called TranSpec3D, where ground truth disparities without object preparation were generated using this measurement principle. The data set contains 110 objects and consists of 148 scenes, each taken in different lighting environments, which increases the size of the data set and creates different reflections on the surface. We also show the advantages and disadvantages of our measurement principle and data set compared to the Booster data set (generated with object preparation), as well as the current limitations of our novel method.
Digitalization and artificial intelligence in higher education (a social-philosophical opinion)

The purpose of this article is to analyze digitalization and artificial intelligence in higher education. The digital educational space is aimed at the development of creative thinking and creativity, the ability to make non-standard decisions and the education of a moral personality, socially responsible young professionals. The introduction of artificial intelligence into the educational process significantly changes the conditions and nature of its implementation. Artificial intelligence is able to analyze a large amount of data in real time, track human progress, automatically provide new materials, meet the needs of students in continuous learning, which contributes to the organization of a highly effective, personalized educational process.
Utilizing the potential of the Tebo River through innovative cendol squid processing

Lubuk Besar Village, especially the Tebo River, has abundant marine products, one of which is squid. However, the squid catch is sold directly to collectors. This is a problem because there is no innovation so it has not had an impact on improving the economy. The aim of this community service is to increase innovation in processing squid into squid sauce which will have an impact on wider marketing. The program method is in the form of counseling and assistance in the production and packaging processes for the Sungai Tebo MSME group, totaling 15 people. This program produces a new processed seafood product in the form of cendol squid with the name 'Samibo' which has been packaged in a good manner and is fit for distribution.
Trends in Media Literacy in Korea: Focusing on dissertations from 2000 to 2022

본 연구는 국내 미디어리터러시 관련 연구 주제 및 동향을 확인하고, 미디어리터러시 관련 연구가 어떤 방향으로 연구되어 왔는지 확인을 통해 앞으로 현장 적용의 필요성과 연구 방향성의 기초자료를 제시하고자 한다. 본 연구의 수집자료는 학술연구정보서비스(RISS), 누리미디어(DBpia), 학술교육원(E-article), 한국학술정보원(KISS)에서 제공하는 국내 석·박사 학위논문을 대상으로 한다. 검색어 ‘리터러시’,‘미디어리터러시’, ‘디지털 리터러시’를 입력하여 2000년부터 2022년 12월까지를 기준으로 발표된 643편의 논문을 수집한다. 수집한 논문 중 원문없음 49건, 작성언어 영어 8건을 제외하고 최종 586편의 논문을 테이터화하여 분석대상으로 한다. 본 연구에서 학위논문으로 정한 이유는 분석하고자 하는 연구연도와 연구대상, 연구방법 그리고 학문분야의 구분이 학술지보다 뚜렷한 경우가 더 많기 때문이다. 본 연구가 2000년부터 2022년까지 다소 긴 기간의 연구동향을 분석하는 연구이므로 다양하고 정확한 연구동향 논문을 대상으로 하는 것이 타당하다고 보았다. 이와 같은 결과를 바탕으로 미디어리터러시 연구의 시사점과 미디어리터러시 관련 연구 및 정책을 위한 제언을 하고자 한다.This study aims to present basic data on the necessity of field application and research direction in the future by identifying research topics and trends related to media literacy in Korea and in what direction media literacy research has been studied. The data collected in this study is domestic master's and doctoral theses provided by Academic Research Information Service (RISS), Nuri Media (DBpia), Academic Education Institute (E-article), and Korea Student Information Service (KISS). entering the search terms ‘literacy’, ‘media literacy’, and ‘digital literacy’, we collect 643 papers published from 2000 to December 2022. Among the collected papers, the final 586 papers are dataized and analyzed, excluding 49 without original text and 8 English written language. The reason why it was decided as a thesis in this study is that the distinction between the research year to be analyzed, the subject of study, the research method, and the academic field was more pronounced than the journal. Since this study analyzes research trends for a rather long period from 2000 to 2022, it was considered reasonable to target various research analysis and accurate research trend papers. Based on these results, the implications of media literacy research and suggestions for research and policies related to media literacy were made.
PENINGKATAN KOMPETENSI SISWA SMK GELORA JAYA NUSANTARA MELALUI PELATIHAN KONFIGURASI ROUTER DAN VLAN

This community service activity is an implementation of the tridharma of higher education to provide knowledge to students of SMK Gelora Jaya Nusantara, especially class XI students majoring in network computer engineering (TKJ). The material provided is router configuration and virtual LAN, this material is useful for participants, because it is one of the topics in the competency exam. This service activity starts from the preparation stage carried out by the team and is carried out on June 20, 2023 in the computer laboratory of SMK Gelora Jaya Nusantara. This service activity was carried out in collaboration with the Program Studi D3 Manajemen Informatika dan Komputerisasi Akuntansi with SMK Gelora Jaya Nusantara.
Ethical Analysis of the Possible Introduction of Chemical Castration as a Criminal Sanction

In this article, I will list the ethical considerations to be taken into account when examining the possible introduction of chemical castration as a criminal sanction, by looking at the international conventions and by comparing the pro and con arguments in several foreign journals and studies. However, it is not yet the purpose of this paper to answer the question of what the author thinks about the possibility of introduction on the basis of an examination of the ethical aspects. The present study aims only to give an overview of the difficulties of answering this question.
Pixel-Wise Reconstruction of Private Data in Split Federated Learning

This study investigates the security of split federated learning (SFL), a collaborative deep learning scheme that provides similar peak performance to federated learning while significantly reducing its computation time for multiple clients. We find that the basic security assumptions of SFL are flawed, in which the honest-but-curious server can easily conspire with a motivated client to break the security of SFL. More prominently, we show that the server can train an inversion model (DecodeNet) and perform an inference attack on clients’ private data. To support DecodeNet training, we implement a data-free training scheme to provide train data in the absence of the original training dataset. The experimental results demonstrate that our attack can reconstruct pixel-wise private images from clients on four different datasets and overcome the differential privacy protection mechanism in SFL.
Comparison and Prediction of Data Mining Models to Determine the Classification of Family Planning Program User Status

&lt;p class="JRPMAbstractBodyEnglish"&gt;Data mining is the process of analyzing a sample to determine the best performing algorithm. An easy way to extract information or insights from large amounts of data is by using the techniques involved in data mining. There are several methods of classification which can be used to determine the level of a certain acuity. In Indonesia, family planning program is the most common program in the government to control population growth. A decision tree, a logistic regression, a naive Bayes model, and a gradient boosted model are used in this study. To perform classification family planning program User Status in Mangunharjo sub-district, the variable used is the wife's age, age of the youngest child, stages of prosperous family, and number of children. The training data comparison testing is 70:30. This study was tested by using the AUC value and t-test. The best value for accuracy is the Decision Tree algorithm with a percentage of 94.2% and an AUC value of 0.939. From the results of this test, it can be concluded that for a comparison of all tests performed on the dataset, the Decision Tree algorithm model can be said to be better than the other three algorithm models.&lt;/p&gt;
Panoramic Video Surveillance: An Analysis of Burglary Detection Based on YOLO Framework in Residential Areas

Artificial Intelligence (AI) is a technique that incorporates human intelligence into mundane activities. And there is no question that AI is significantly affecting security and surveillance. Although relying on numerous resources, finding answers, and implementing technology for decades, our security and surveillance systems still have flaws. In every country around the globe, the use of video security and surveillance is becoming more widespread. Nonetheless, a wide range of businesses has made use of it, including hospitals, universities, and warehouses. Yet, as people are limited in their ability to vigilantly monitor live video streams, deep learning was developed to better fill the position. Unfortunately, there are other problems with images in the real world, including jitter or blurring caused by rotating objects, noise, and sharpness concerns. As a result, deep learning technology for surveillance has considerably improved in recent years. The main objective of this study is to detect burglars using deep learning technology. This system aims to take video surveillance of the residential environment as input and pass it into the Yolo model to increase the speed and accuracy of the system to detect burglars in the residential. This system mainly concentrates on object detection.
THE EFFECTS OF INTELLECTUAL CAPITAL ON ORGANISATIONAL AGILITY: THE ROLE OF KNOWLEDGE SHARING AS MEDIATION

This research aims to determine and to evaluate the moderating effects of the relationship between Intellectual Capital, Knowledge Sharing, and Organizational Agility. This study surveyed 146 consumers in the city of Semarang, Central Java, who met specific requirements, including being female and at least 17 years old. By visiting women's forums and groups and completing online (Google form) and offline (print out sheets) questionnaires, primary data was collected directly from the source. This study used Partial Least Square (PLS) 3.0 as its data analysis approach. Intellectual Capital has a significant, positive, and powerful effect on Knowledge Sharing. This implies that if Intellectual Capital increases, so does Knowledge Sharing. It is acknowledged that Intellectual Capital has a strong, positive, and significant effect on Knowledge Sharing. This implies that as Intellectual Capital increases, so will Knowledge Sharing. Organizational Agility has a strong, positive, and significant relationship with Knowledge Sharing. This implies that if Intellectual Capital increases, so does Knowledge Sharing. Knowledge Sharing mediates the relationship between Intellectual Capital and Organizational Agility to a moderate degree.
A Remote Sensing Image Dehazing Network Based On Dark Channel Attention Mechanism

Clear and haze-free remote sensing image is crucial for subsequent processing and application. We propose a new deep learning network based on the dark channel attention mechanism to enhance remote sensing image dehazing performance by combining prior knowledge with deep learning. The network features a parallel cascade structure of attention flow and dark channel prior (DCP) constraint flow. Additionally, edge loss is introduced to supervise the training network and preserve edge information in the image content. Experiments are conducted on both real and synthetic haze datasets, demonstrating that the proposed method effectively removes non-uniformly distributed haze and produces superior results in both qualitative and quantitative analyses.
Ontological Modeling of Climate Data to Improve Climate Analytics

Climate data is a valuable resource for understanding past weather patterns, assessing long-term climate trends, and conducting climate-related research. However, most existing knowledge graphs for climate data rely heavily on the standardized (per W3C recommendations) SOSA/SSN ontology, which can help improve general data accessibility, but typically overlooks the analytical applications of multisource climate data. To further enhance the accessibility of heterogeneous data for climate data analytics, this paper extends the CA ontology and implements a virtual knowledge graph for analytical applications. We emphasize the importance of incorporating observation metadata and geospatial representation into analytical applications. Through our study, we demonstrate the applicability of the proposed ontological model in deriving the ETCCDI indices. An example of the formation of the annual maximum daily temperature is given. Furthermore, we showcase the potential of LinkedGeoData in providing a more comprehensive geographical context for accessing climate data within the knowledge graph, leveraging the proposed ontological modeling and linked data principles.
How to build Conda packages?

As mentioned, packages can be installed directly from our conda channel. You may however want to build your own package at some point in the future or you may want to fix some of ours by submitting a Pull Request on github (You are more welcome to do so...) The following goes through the steps of building a conda package for Badlands which contains Python and Fortran code. This is relatively advanced but not really difficult.
Research on the intelligent retrieval system of massive academic literature resources based on the ontology

This paper expounds the key technologies of the ontology, focuses on the overall structure design, system function, ontology construction and retrieval process of the system, and finally discusses the key problems to be solved in the system design: ontology management and service, information resource acquisition and document pre-processing, etc.
How to build Conda packages?

As mentioned, packages can be installed directly from our conda channel. You may however want to build your own package at some point in the future or you may want to fix some of ours by submitting a Pull Request on github (You are more welcome to do so...) The following goes through the steps of building a conda package for Badlands which contains Python and Fortran code.