Reviewerly/exHarmony huggingface dataset:
Perbandingan Kinerja Model Convolutional Neural Network pada Klasifikasi Kanker Kulit

Skin cancer is one of the diseases that greatly affects the quality of human life and can be potentially bad if not detected and treated quickly. In an effort to improve the early detection and accuracy of skin cancer diagnosis, this study aims to design a skin cancer classification system using deep learning. The research method involves the use of deep learning-based artificial neural networks, especially convolutional neural networks (CNN), which have been proven effective in image processing. The images in the dataset include various types of skin cancer, including melanoma and basal cell carcinoma. In this study, a skin cancer classification system was built using The-HAM10000 Dataverse, utilizing the CNN algorithm and the performance of the system was modeled using InceptionV3, and EfficientNetB0. The results of these two methods on the dataset show that InceptionV3 has an accuracy of 0.7681, and EfficientNetB0 of 0.9809, the results of this accuracy make the EfficientNetB0 system better for skin cancer detection, so this finding makes that the accuracy at this level will classify as much as 327 data only, therefore the data trained and tested will produce an accuracy and error from its validation which makes EfficientNetB0 an option for classification based on the CNN method.
Development and Application of Artificial Intelligence Image Recognition Technology for Innovation in Retail Services

In demographic shifts, changes in consumer patterns, and heightened uncertainty, traditional retail enterprises are experiencing a sense of crisis. Nevertheless, innovative business models and digital transformations have propelled some retail enterprises to achieve remarkable growth and success by maximizing customer convenience and enhancing operational efficiency through diverse technologies. This study aims to develop partial image recognition technology applicable to the situation of unmanned convenience store kiosks, grounded in the Retail Tech paradigm. To address limitations in previous research concerning the technical and empirical approaches to partial image matching, this study proposes deep learning-based partial image matching technology utilizing semantic matching and cross-verification to improve the accuracy of image recognition technology. The developed algorithm achieves a accuracy of over 95% in various visual scenarios, contributing significantly to the advancement of image processing and recognition technologies. In addition, the developed technology, designed to consider most noise situations in the application process of image recognition technology, is applicable to various situations, including the logistics/distribution field where this study was conducted.
Multi-View 3D Human Pose Estimation Based on Transformer

The technology of Three-dimensional human posture estimation is used in sports, motion recognition, and special effects of video media. Among various methods for this, multi-view 3D human pose estimation is essential for precise estimation even in complex real-world environments. But Existing models for multi-view 3D human posture estimation have the disadvantage of high order of time complexity as they use 3D feature maps. This paper proposes a method to extend an existing monocular viewpoint multi-frame model based on Transformer with lower time complexity to 3D human posture estimation for multi-viewpoints. To expand to multi-viewpoints our proposed method first generates an 8-dimensional joint coordinate that connects 2-dimensional joint coordinates for 17 joints at 4-vieiwpoints acquired using the 2-dimensional human posture detector, CPN(Cascaded Pyramid Network). This paper then converts them into 17×32 data with patch embedding, and enters the data into a transformer model, finally. Consequently, the MLP(Multi-Layer Perceptron) block that outputs the 3D-human posture simultaneously updates the 3D human posture estimation for 4-viewpoints at every iteration. Compared to Zheng[5]'s method the number of model parameters of the proposed method was 48.9%, MPJPE(Mean Per Joint Position Error) was reduced by 20.6 mm (43.8%) and the average learning time per epoch was more than 20 times faster.
IMPACT OF ETHICAL LEADERSHIP OVER WORK ENGAGEMENT AND EMOTIONAL EXHAUSTION: THE MEDIATING ROLE OF SELF-EFFICACY AND PSYCHOLOGICAL EMPOWERMENT

Based on social exchange theory, current study aimed to examine the Impact of ethical leadership over work engagement and emotional exhaustion. The mediating role of self-efficacy and psychological empowerment is examined between ethical leadership and work engagement as well. The sample size was 250 and 221bank officers is being selected. For testing the model, SPSS 21 version, has been used for data analysis. Preacher and Hayes method was used for mediation analysis. The results of this study revealed significant positive association between Ethical Leadership and employee’s well-being(work engagement and emotional exhaustion). The Mediation role of Self efficacy and Psychological empowerment in the relationship between Ethical Leadership and employee’s well-being was also found significant. Accordingly, the recommendations and implications are provided to banking sector. The findings of this research suggest that banking officers should be more sensitized while dealing with their personnel, because it will create a harmonious work environment which stronger the interpersonal relationships, which in turn, will reduce work place, stress. Thus, banking sector is in need to take some effective measures so bank managers will be able to ensure the wellbeing of their employees.
Layanan Berbasis Cloud Untuk Infrastruktur Jaringan Mobile First – Iot – Cloud Native Versi Aruba

The presence of industry 4.0, of course, has a huge impact on various industrial sectors, whose infrastructure is now being developed with the concept of cloud-based services for Mobile Network Infrastructure First - IoT - Cloud Native which is intended for large companies, campuses and data center services. employed remotely or known as the company's network infrastructure. This study aims to determine the extent to which the network technology developed by Aruba with a Cloud service model is able to provide the enterprise segment and has the freedom to choose and run cloud-based components. This study uses qualitative methods, with a research approach to the analysis of natural object concepts, with data collection techniques, explanations from resource persons and literature with natural data and describes all technological services implemented by Aruba, and uses techniques Data analysis used in this research is to use analysis in the form of documentation in the form of writing and organize the data into categories, describing it into units. The results of this study indicate that with the presence of ARUBA with cloud-based services for Mobile Network Infrastructure First - IoT - Cloud Native is able to provide and provide various kinds of solutions and is able to provide cloud services to large companies, campus data center services so that can increase business value by using the service concept offered by Aruba.
A study on Korean perception of Vietnamese production of Korean stop consonants

The purpose of this paper is to investigate the perception patterns of Koreans regarding the production of Korean stop consonants by Vietnamese Korean language learners. For this purpose, an experiment was conducted on Koreans' perception of Vietnamese learners’ production of Korean stop consonants.&#x0D; The results of the experiment show that when the presentation sound is located at the beginning of the word, the correct answer rate was ‘/ㅌ/ 89%) &gt; /ㅋ/(88%) &gt; /ㅍ/=/ㅂ/(84%) &gt; /ㄱ/=/ㄸ/(74%) ) &gt; /ㄷ/(72%) &gt; /ㅃ/(65%) &gt; /ㄲ/(61%)', and in the case of word-medial onset consonants, ’/ㅍ/, /ㅋ/(91%) &gt; /ㅌ /(88%) &gt; /ㄷ/(68%) &gt; /ㅂ/(61%) &gt; /ㄸ/(60%) &gt; /ㄲ/(51%) &gt; /ㅃ/(46%) &gt; /ㄱ/(40%)’. Except for the case of /ㄸ/ in word-initial and /ㄱ/ in word-medial, accuracy was found to be high in the order of aspirated consonants &gt; plain consonants &gt; tense consonants for both word-initial and word-medial positions. The percentage of correct responses in the word-initial environment was higher than that in the word-medial environment, and this was revealed more clearly through matrix analysis. In both word-initial and word-medial environments, when the target sound was ‘plain’, it was confused with ‘tense’, when it was ‘tense’ it was confused with ‘aspirated’, and when it was ‘aspirated’ it was confused with ‘plain’. Looking at the correct rate for each following vowel, except for the word-medial plain consonant (/ㅣ/ &gt; /ㅜ/ &gt; /ㅏ/), in all other cases, the correct rate was high in the order of /ㅣ/ &gt; /ㅏ/ &gt; /ㅜ/. This result shows that the correct response rate for the following vowels decreases as the vowels move from the front vowels to the back vowels.
A Study on the Method of Teaching by Connecting Reading·Debate·Writing

The purpose of this article is to provide education in connection with reading·debate·writing as a way to maximize the advantages and compensate for segmental education. The following is a summary of the research content and a conclusion based on it. First, segmental education is efficient to strengthen the foundations and basics, but it lacks flexibility to contain the nature and results of flexible thinking activities, so linkage education is needed to strengthen language use skills by strengthening the link between functions. Second, linkage education can be conducted around the composition of sub-units, and sub-units can be composed like ‘reading→reading‧debate→reading‧writing→reading‧debate‧writing’, ‘writing→writing‧debate→writing‧reading→reading‧debate‧writing’, ‘debate→debate‧reading→debate‧writing→reading‧debate‧writing’. Third, when selecting a book, the goal of the class, the stage of the learner’s development, and the learner’s interest must be considered. Forth, the points that should be used for the association activites that are the basis for each language function are follows. In the case of reading, intellectual action should be performed in consideration of the reader’s background, the nature of the reading material, and the criteria for performing the task. in the case of writing, we should follow the rules in consideration of the purpose writing and do systematic writing activities through appropriate division of labor. Do it. In the case of debate, you should use reading and writing at the same time to have a debate, but clarify the method and direction of the debate.
Examining the potential issues and risks associated with the integration of AI and blockchain technology in telehealth systems

There has been significant improvement in telehealth with the development of blockchain and artificial intelligence (AI) technologies in recent years. AI enables intelligent decision-making and automation in healthcare, while blockchain offers decentralized and secure data management. However, the integration of these technologies introduces a set of challenges and risks that need to be carefully addressed. The interoperability and integration of AI and blockchain within telehealth systems present technical challenges. AI algorithms require a large amount of data, which may be stored on distributed blockchain networks. Ensuring seamless interaction between AI models and blockchain infrastructure poses data access, sharing, and computation challenges. AI-driven diagnosis and treatment decisions may lead to errors or biases, requiring transparent accountability and liability framework. Blockchain&apos;s immutability raises questions about the right to be forgotten and data privacy regulations, as personal health information stored on the blockchain may be challenging to delete or modify. The cybersecurity risks associated with integrating AI and blockchain cannot be overlooked because blockchain decentralized nature provides robust security against data tempering. However, vulnerabilities in smart contracts or AI algorithms could be exploited. Moreover, the vast amount of data exchanged in telehealth systems creates opportunities for data breaches and unauthorized access. To mitigate these issues and risks, stakeholders in telehealth systems must collaborate to develop robust technical standards, governance mechanisms, and regulatory frameworks. Transparent and explainable AI models, privacy-preserving mechanisms, and secure blockchain protocols should be designed and implemented. Interdisciplinary research involving healthcare, technology, law, and ethics experts is crucial to address the challenges and maximize the advantages of incorporating AI and blockchain in telehealth systems. While integrating AI and blockchain technology systems offers numerous benefits, it also presents a range of potential issues and risks. By acknowledging and addressing these challenges, stakeholders can harness the transformative power of AI and blockchain technologies to create more efficient, secure, and ethical telehealth systems.
Mitigating cyber threats in healthcare systems: the role of artificial intelligence and machine learning

As we move further into the digital era, the importance of cybersecurity becomes increasingly apparent, especially in the healthcare industry, where sensitive patient data is stored and transmitted through various technological systems. The advancement of technology makes safeguarding healthcare systems from cyber threats more critical than ever. Cybercriminals target patient information, financial data, and medical records, resulting in severe consequences like reputational damage, loss of trust, financial losses, legal consequences, and potential harm to patients. Despite attempts to regulate healthcare cybersecurity, the rising number of cyberattacks remains an important challenge. To tackle this issue, the adoption of artificial intelligence (AI) and machine learning (ML) has shown promise. AI can detect and prevent real-time cyberattacks, providing an additional layer of security. ML algorithms can predict and thwart future attacks by analyzing cybercriminal behaviors and patterns. Additionally, secure communication channels are vital for healthcare systems to protect sensitive data. Encrypted communication methods, such as secure messaging systems and virtual private networks, significantly enhance healthcare system security. This book chapter provides an overview of the importance of cybersecurity in healthcare, exploring various cyber threats faced by healthcare systems, including malware attacks, ransomware attacks, and social engineering attacks. It also examines the impact of these threats on healthcare, such 370as patient privacy breaches, financial losses, and reputational damage. Furthermore, the chapter delves into the regulatory and legal requirements that healthcare organizations must adhere to in order to safeguard patient privacy and security. It outlines various cybersecurity measures that healthcare organizations can adopt, such as risk assessments, staff training, network segmentation, access controls, and incident response plans. Lastly, the chapter discusses emerging technologies like blockchain and AI, demonstrating their potential to enhance cybersecurity in healthcare systems.
Location information privacy protection method considering human presence probability

The rapid expansion of services that collect personal information and location data to implement machine learning techniques is an emerging trend. In circumstances such as those experienced during the COVID-19 pandemic, it becomes pivotal for the healthcare system to ascertain individual attributes, symptoms, and geographical locations. Nonetheless, in the pursuit of statistical data analysis, rigorous measures must be implemented to safeguard against the potential identification of individuals. Even when personally identifiable information is not acquired directly, various sensitive details, e.g., a person&apos;s home or workplace, can be exposed via location data. A range of techniques that leverage federated learning and blockchain technology have been proposed to protect location-based privacy; however, sole reliance on such technologies may fall short in terms of providing adequate privacy safeguards. Thus, the incorporation of differential privacy methods into these strategies has been proposed. However, privacy measures via differential privacy can impact the user experience. Thus, excessive protections should be avoided. As a result, we propose a method to mitigate SQL, which is quantifiable indicator of user convenience, by considering the probability of human presence.
Architectural design criteria for AI and blockchain technology in telehealth systems

Telehealth systems have become increasingly popular due to their potential to improve the accessibility of healthcare services through effective remote quality care provision. However, the need to provide architectural design criteria that would integrate artificial intelligence (AI) and blockchain technology exists. In this chapter, we explore the integration of AI and blockchain technology into the telehealth system. While AI techniques employ machine learning algorithms to analyze patient data with the utmost confidentiality in real time, blockchain technology improves data security and integrity and makes data sharing transparent. To achieve these, we discuss the implementation of four design criteria such as the development of secure blockchain networks, the use of smart contracts to automate the processing of transactions, the development of user-friendly interfaces to facilitate control of patient data, and the consideration of ethical and legal issues in the overall system design framework. The implementation of this framework following key design considerations with an algorithm is simulated in the results.
Model Kolaboratif Interaktif Readaloud untuk Mendukung Literasi Membaca di Sekolah Dasar

This study is based on the urgency in understanding of the text presented. The aim of this research is to produce a collaborative interactive read aloud learning model as an effort to create understanding of the text. The model applied includes: 1) Designing; 2) Forming; 3) Facilitating; 4) Evaluating. This research was carried out by adapting McKenny &amp; Reeves through the stages of EDR development research procedures which include: 1) Problem Identification; 2)Design and Construction; 3) Evaluation and Reflection. Data collection techniques were carried out by interviews and observation. The research subjects involved teachers and students at SDN Karangsambung, Tasikmalaya City. The conclusions of this research indicate that the collaborative interactive read aloud model can be implemented in reading learning to support elementary school students' reading comprehension
Implementasi Metode Rapid Application Development pada Sistem Informasi Harga Barang Berbasis Web di Perusahaan Cipta Warna Digital Printing Boyolali

Cipta Warna Digital Printing is a printing company located in Boyolali city, this company provides various printing needs. Based on the results of interviews with the owner of the company, Cipta Warna Digital Printing has a problem, namely that it does not yet have a website, so it is difficult for the company to provide information about products, especially the available products and product prices. Based on these problems, the authors build a web-based system that is able to provide information about companies, products and allows customers to calculate product prices independently. This system is designed with Unified Modeling Language (UML) using CMS Wordpress and Rapid Application Development (RAD) method. The results of testing using Blackbox Testing show that the system runs according to its function without any errors.
Design of English Information Resource System and Application in English Teaching

To research the requirement of English course sharing among different regions, a comprehensive platform design of course resource information was proposed for the construction of the classroom course information storage function and platform to complete the hardware solution of the information management platform. By designing the platform environment and database and conducting function development for the comprehensive management platform, a new teaching resource management platform was constructed for sharing course information resources and was found to be better than the conventional classroom resource network systems.
Random Simulation Analysis and Application of Intelligent Multidimensional Computers

With intelligent multi-dimensional computer random simulation and big data analysis techniques, the steps and methods of intelligent multi-dimensional random simulation, as well as the random simulation analysis and application of intelligent multi-dimensional computers in oilfield development, were deeply explored.
Autonomous Insulator Cleaning using Aiming System-based UAV

We developed a high-voltage tower insulator cleaning system. The system adopted Generative Adversarial Networks (GANs) and computer vision algorithms for insulator segmentation and detection respectively. Projective geometry was used for back-propagation of the insulator position to 3D world coordinates, and a cleaner algorithm provided real-time movement control for a dual-axis servo spraying water gun system. The accuracy of the insulator image detection system was higher than 95%. This system predicted the insulator’s position in space and locked the target in world coordinates. Therefore, the servo motor angles were calculated using a deterministic method based on the current drone position. The entire system was designed to run on an Nvidia Jetson Xavier NX, using less than half of the total computational power available on both CPU and GPU. With the growing use of drones in the industry for difficult tasks, the proposed system represented a significant advancement in insulator cleaning for high-voltage towers.
Bibliometric Analysis of International Publications Trend on The Taliban

This research aims to navigate the result of international publication trends regarding the Taliban for 27 years, starting from 1994 to 2021, utilizing a bibliometric analysis study that analyzed trends in international publications based on quantitative data sources obtained through one of the Scopus data search engines. In addition, bibliometric analysis in this study employed a data visualization software VOSviewer to analyze keywords that often appear in research data regarding the trend of international publications of the Taliban. The findings in this bibliometric analysis study indicated three outcomes. Firstly, numerous international publications on the Taliban as a research topic were navigated, accounting for 1,538 publication documents based on the Scopus data search engine with the keyword "Taliban". Secondly, the results of data visualization on VOSviewer show that the largest keywords visualization are Afghanistan and the Taliban. Lastly, the trend of international publications regarding the Taliban indicated that the highest trend of international publications was in 2010-2011 with publication documents are mainly conducted by researchers in western countries, along with the most funding sponsors were the United States and the United Kingdom. This study concluded that the results of international publication trends regarding the Taliban were influenced by the activities executed by the Taliban receiving global attention throughout time. Hence, the novelty of this study lies in the implementation of bibliometric analysis, presenting a dynamic topic about the Taliban and the data search tools used.