Reviewerly/exHarmony huggingface dataset:
Researching Displaced Persons During COVID-19

Coronavirus disease 2019 (COVID-19) has created additional barriers to human interactions. For those conducting research with displaced persons, the barriers posed by COVID-19 add up to the existing linguistic, cultural, geographical and ethical obstacles that this type of research involves. In most cases, researchers have resorted to technological solutions to bridge the communication gap caused by the pandemic. However, the heterogeneous profiles and disadvantaged circumstances of displaced persons require further considerations and planning. This paper examines the experiences of researchers conducting research with displaced persons during COVID. It outlines the special considerations taken and provides recommendations for those conducting research in similar contexts. The communities that engaged in this research were based in Greece, Poland, Italy, Lebanon and Spain. While the focus of the study is displaced persons, the insights presented can be of benefit to those conducting research with other vulnerable groups. Lay summary The COVID-19 pandemic has affected human interaction. Research often involves face-to-face contact with participants and other agents, which COVID-19 prevented. The mobility restrictions and safety regulations have difficulted data collection. Many processes have been moved online, but not everybody can interact successfully with technology i.e., some people do not have access to devices or internet, others do not have the skills required. Other barriers can be linguistic or cultural. Researchers must ensure that the research is safe and accessible to participants. This study presents how researchers working with migrants in the field of Media Accessibility have adapted their studies during COVID-19. The study reports on the results of a questionnaire distributed among researchers working on three projects conducted in European countries and Lebanon. The results show that more time was invested in data collection, and that flexibility and innovation were key to the success of the projects. The paper explains how researchers made data collection tools accessible to participants to ensure that participants could take part in the study. The considerations taken could be applied beyond the pandemic as it is adaptable to other research contexts, testing environments, diverse audiences, and disciplines.
BioFors: A Large Biomedical Image Forensics Dataset

Research in media forensics has gained traction to combat the spread of misinformation. However, most of this research has been directed towards content generated on social media. Biomedical image forensics is a related problem, where manipulation or misuse of images reported in biomedical research documents is of serious concern. The problem has failed to gain momentum beyond an academic discussion due to an absence of benchmark datasets and standardized tasks. In this paper we present BioFors -- the first dataset for benchmarking common biomedical image manipulations. BioFors comprises 47,805 images extracted from 1,031 open-source research papers. Images in BioFors are divided into four categories -- Microscopy, Blot/Gel, FACS and Macroscopy. We also propose three tasks for forensic analysis -- external duplication detection, internal duplication detection and cut/sharp-transition detection. We benchmark BioFors on all tasks with suitable state-of-the-art algorithms. Our results and analysis show that existing algorithms developed on common computer vision datasets are not robust when applied to biomedical images, validating that more research is required to address the unique challenges of biomedical image forensics.
Optimal Clustering Scheme for Cloud Operations Management Over Mobile Ad Hoc Network of Crop Systems

Subsequent to the grouping of mobile Cloud computing and ad-hoc networks, these two play key roles in IoTs. MANETS is a category of wireless network that is instinctively connected in decentralized systems. Each device of the MANET moves openly from one place to other. The IoT's Cloud-MANETS framework of clever device collected to IoTs Cloud computing and MANETS. Security is seen as the main hindrance to embracing the Cloud model of web authentication. The data and software the business executives might keep in the Cloud are open to theft unless there is a secure Cloud environment that helps stem the worries across Cloud computing shortcomings, security dangers, and challenges to its full use by business. The Cloud creator fundamentally puts in sufficient checks and balances to direct the business concerns from difficulties and challenges identified with security, dependability, protection, and accessibility of the Cloud to administering user requirements from the Cloud perspective. This commitment of the Cloud service provider is further necessitated when there is a need to guarantee secure communication with a 5G organization of savvy gadgets utilizing the web. The methodology of the paper utilizes the ideal visualization of an exact and successful re-enactment of Cloud computing in ad-hoc networks provided to an IoT framework. Cloud computing is to use applications provided on infrastructures with data storage on remote servers that is accessed through the Internet. An effective implementation of the Cloud is in the agricultural sector.
APPLICATION OF ARTIFICIAL INTELLIGENCE-BASED IMAGE ANALYSIS IN BIOINFORMATICS

The collection of image data is an extremely common procedure in clinical practice today. Many of the diagnostic approaches generate such data – computed tomography (CT), X-ray radiography, magnetic resonance imaging (MRI), and others. This data collection process allows for the use of computer vision approaches to be applied with the goal of analysis and diagnostics. Artificial Intelligence (AI) based algorithms have repeatedly been shown to be the best performing computer vision algorithms, in many fields including medicine. AI-based – or more precisely machine learning (ML) based, algorithms have capabilities which allow them to learn the patterns contained in the data from the data itself. Among the best performing algorithms are artificial neural networks (ANNs), or more precisely convolutional neural networks (CNNs). Their pitfall is the need for the large amounts of data – but as it has been previously mentioned, the amount of data collected in today’s clinical practice is large and ever increasing. This allows for the development of Smart Diagnostic systems which are meant to serve as support systems to the health professionals. In this paper first, the standard practices and review of the field is given – with the focus on challenges and best practices. Then, multiple examples of the research applying AI-based algorithm analysis are given – including diagnostics of various cancer types (bladder and oral) as well as COVID-19 severity diagnostics and image quality determination.
Factor That Affect Turnover Intention in Millennial Employees

The biggest challenge for companies today is thinking about various strategies in retaining millennial generation employees in order to reduce turnover intention, in which turnover intention is the reaction of employees to what is felt in the company. Factors such as strong organizational culture and employee motivation are expected to retain employees to reduce turnover intention. Therefore, the purpose of this study is to see whether organizational culture and motivation are factors that can affect turnover intention of millennial employees who are in Jabodetabek. This research is quantitative in nature, conducted by survey using a questionnaire. Data were analyzed using Structural Equation Model (SEM). The results of the first study indicate that there is an influence between organizational culture on employee motivation. Second, there is an influence between organizational culture on employee turnover intention. Third, there is an influence between motivation on employee turnover intention. Furthermore, the four motivations mediate between organizational culture and employee turnover intention in Jabodetabek
Status of internet usage among adolescents: A study of locale differences

The present study entitled ‘Status of internet usage among rural and urban adolescents was undertaken in the Ludhiana and Kapurthala districts of Punjab state. The study was designed to assess the usage of internet among rural and urban adolescents. The sample for the present study comprised of 480 adolescents within the age group of 16- 18 years equally distributed over gender and locale (boys (n=120) and girls (n=120) from rural (n=120) as well as urban area (n=120). Internet Usage Scale by Saini and Kaur (2017) was used to assess the patterns/trends of internet usage among adolescents. This scale assessed the internet usage by the adolescents with the help of 20 items. Results revealed that more number of rural respondents were at high level of internet usage as compared to urban respondents. Overall more number of urban respondents used internet than rural respondents.
Distributed Graph Algorithms for Multiple Vector Engines of NEC SX-Aurora TSUBASA Systems

This paper describes the world-first attempt to develop distributed graph algorithm implementations, aimed for modern NEC SX-Aurora TSUBASA vector systems. Such systems are equipped with up to eight powerful vector engines, which are capable to significantly accelerate graph processsing and simultaneously increase the scale of processed input graphs. This paper describes distributed implementations of three widely-used graph algorithms: Page Rank (PR), Bellman-Ford Single Source Shortest Paths (further referred as SSSP) and Hyperlink-Induced Topic Search (HITS), evaluating their performance and scalability on Aurora 8 system. In this paper we describe graph partitioning strategies, communication strategies, programming models and single-VE optimizations used in these implementations. The developed implementations achieve 40, 6.6 and 1.3 GTEPS performance on PR, SSSP and HITS algorithm on 8 vector engines, at the same time achieving up to 1.5x, 2x and 2.5x acceleration on 2, 4 and 8 vector engines of Aurora 8 systems. Finally, this paper describes an approach to incorporate distributed graph processing support into our previously developed Vector Graph Library (VGL) framework – a novel framework for graph analytics on NEC SX-Aurora TSUBASA architecture.
Evaluasi Pelayanan Terpadu Satu Pintu (PTSP) Menggunakan Decision Tree

Various ways are carried out by each agency to win the trust of the public, among others, by increasing customer satisfaction. One of the government agencies that is committed to increasing customer satisfaction is the Regional Office of the Ministry of Religion of Central Java Province. This study aims to measure the suitability of service quality and recommend alignment of the gap between public perception and management perception which is then used as material for evaluating service quality at the Regional Office of the Ministry of Religion of Central Java Province using Decision Tree with the ID3 algorithm. Attributes of customer satisfaction input in this study using Servqual, including tangibility, reliability, responsiveness, assurance and empathy. In this study, it was found that there is a gap between the perception of service users and the perception of management. Where the improvement of service quality that must be prioritized is the assurance attribute. This research is expected to assist the management in finding the weaknesses of their services and increase customer satisfaction to maintain and increase public trust in government agencies
Dynamic hand gesture recognition of sign language using geometric features learning

In the sign language alphabet, several hand signs are in use. Automatic recognition of dynamic hand gestures could facilitate several applications such as people with a speech impairment to communi...
A New Method for Web Service Recommendation Based on QoS Prediction

As service-oriented architecture gains in popularity and grows in popularity, Web service recommendation and composition have become more important topics for research. Accurately predicting individualized QoS recommendations for recommending web services is a difficult task because of the inconsistency of the Internet and the scarcity of information regarding QoS history. Our team suggests a new framework for QoS values’ prediction and also presents two methods for clustering, User_BC and Service_BC, to support QoS prediction accuracy. Hierarchical clustering is used, based on the QoS dataset of PlanetLab1 (that) contains 200 service-user response time values, with 1,597 service values overall. In our research, we've found that our clustering-based methods beat other popular algorithms in detailed experimental comparisons and analyses.
USING SVM (SUPPORT VECTOR MACHINE) METHOD TO PREDICT BEST SELLER BOOK IN AMAZON

Amazon is an American multinational technology company based in Seattle, Washington, which focuses on e-commerce, cloud computing, digital streaming, and the Big Four artificial intelligence along with Google, Apple, and Facebook. Therefore this company must have many and varied sales data. One of them is book sales data. In this study, the author is interested in analyzing best-selling book sales by implementing data mining using the SVM algorithm, where the data is taken at Kaggle.com in the form of a data set.
Chapter 2. The OCOL Platform

Chapter 2 of Library Technology Reports (vol. 56, no. 7), “One Country One Library,” explains the OCOL platform in terms of its technological background and its unique features and functionalities. It highlights what distinguishes the platform from the others on the market, including, for example, the absence of reviews and ratings, the role of public marginalia, the role of Profiles within the platform, the role of analytics, and ways in which user privacy is guarded at all times. The chapter also explains why all content within the platform is classified as one of the following: licensed content, open access, public domain, or self-published.
Stress Conceptualizing In Students Of Different Cultures

The first year of the university study is stressful for most students.In the context of open education, this problem is exacerbated, since the understanding of stress and how to cope with it among students of different cultures differ.There are studies on the differences in the perception of Stress between students of Eastern and Western cultures, individualistic and collectivist cultures.But the question arises whether there are differences in the Stress perception among students of the same cultural group.The goal of the study was to reveal the peculiarities of notions about Stress among Russians, Armenians, Tatars, Turks, and Chinese.More than 700 first-year university students were invited to participate in the study.Research methods included the analysis of dictionaries, directed associative experiment (Stimulus was word Stress), the pictographic technique (Stress image).The findings testified significant differences in the sensory, emotional, and temporal modalities of Stress perceptions among students of Eastern cultures (ANOVA, p = 0.000; multiple comparisons).The notions of Stress among Russian students are pronounced in sensory, emotional, and temporal modalities.The dominant emotional perception of Stress is characteristic of the Tatars.The Armenians and Chinese are distinguished by the severity of the spatial-temporal modality of Stress perception.The notions of Stress among Turkish freshmen are concrete and low-emotional.The data obtained are important to adapting the freshman and maintaining their psychological well-being.
Advances in Intelligent Assistive Technologies (IAT) for persons with dementia

Advances in technologies and innovations over the past decade have sought solutions to ease the burden on caregivers and help persons with dementia live more independently and improve their overall wellbeing. Intelligent Assistive Technologies (IAT) for persons with ADRD encompass technologies that range from simple manual devices up to complex life monitoring and safety tracking GPS systems.
THE EFFECT OF E-LEARNING ON STUDENTS’ ACHIEVEMENT IN UNIVERSITAS POTENSI UTAMA

It is believed that internet helps people to do better and faster. It has been used globally in almost every aspects of life. In education, internet is known as the golden key to intelligence, since it offers unlimited resource. It can be learning media in the classroom or while self-learning. Considered as an international language, English is used as main tool of communication on internet. It acts as the language of the instructions and language of the users. It is interesting to analyze its use by students in a developing country like Indonesia. In fact, Indonesia is one of the countries with millions internet users. As a result, e-learning becomes an option to deal with teaching learning process, especially for students of English department. By using internet, they can master certain topics and English themselves better. This study is quantitative research using pre-experimental design. It is aimed to analyze the effect of e-learning on achievement of students in Universitas Potensi Utama. The research result of this study was calculated by using Wilcox on test in which p-value is 0.462 and p&gt; 0.05 which means the Null hypothesis is accepted. So it is concluded that there is no significant difference between e-learning and traditional learning. However, students have positive perceptions on e-learning because they argue that it can make them highly motivated to learn more about the subject.
한국군 공병부대의 앙골라 PKO 파병활동 고찰

It is 15 months that Engineer Unit of ROK(Republic of Korea) Forces had been in Huambo, Angola as a PKO(Peacekeeping Operations) troops of United Nation Angola Verification Mission(UNAVEM) Ⅲ from October 1995 to December 1996. 3(1st, 2nd, or 3rd) echelons restored and rebuilt 8 bridges, and let Angolan know the ROK. ROK Forces Engineer Unit had to do not only tasks of UN Mandates and supporting Angolan people but also activities of enhancing for national interest. And each echelon with 198 soldiers confronted its’ own situation respectively. How was it possible to get win-win effects with the limitations of time and capability?The results of this study show that each echelon of ROK Forces’ Engineer Unit had its’ own character. The comparative larger portion of activities for 1st echelon was the troop deployment and tasking UN Mandates. The 2nd kept focusing on the balance of PKO’s 3 axes(mandates, beneficent activities, and enhancing national interest). And the 3rd focused on enhancing national interest and troop repatriation. Flexibilities according to the situations, setting the priority of tasks, positive cooperation with Angolan local people, and adequate public relation activities were the important reasons to achieve the reciprocal win-win effects over the dispatch operations of ROK Forces for UNAVEM Ⅲ, Angola and ROK.
Why Access to Data Matters and What We Can Do to Improve Access and Reusability

Earth and Space Science Open Archive Presented WorkOpen AccessYou are viewing the latest version by default [v1]Why Access to Data Matters and What We Can Do to Improve Access and ReusabilityAuthorsDeniseHillsStephenDiggsSee all authors Denise HillsCorresponding Author• Submitting AuthorGeological Survey of Alabama,University of Alabamaview email addressThe email was not providedcopy email addressStephen DiggsUniversity of California San Diego Scripps Institution of Oceanographyview email addressThe email was not providedcopy email address
A framework for medical image segmentation based on measuring diversity of pixels intensity utilizing interval approach

Segmentation of medical image is one of the most challenging tasks in analysis of medical image.It classifies the organs pixels or lesions from medical images background like MRI or CT scans, that is to provide critical information about the human organ's volumes and shapes.In scientific imaging field, medical imaging is considered one of the most important topics due to the rapid and continuing progress in computerized medical image visualization, advances in analysis approaches and computer-aided diagnosis.Digital image processing becomes more important in healthcare field due to the growing use of direct digital imaging systems for medical diagnostics.Due to medical imaging techniques, approaches of image processing are now applicable in medicine.Generally, various transformations will be needed to extract image data.Also, a digital image can be considered an approximation of a real situation includes some uncertainty derived from the constraints on the process of vision.Since information on the level of uncertainty will influence an expert's attitude.To address this challenge, we propose novel framework involving interval concept that consider a good tool for dealing with the uncertainty, In the proposed approach, the medical images are transformed into interval valued representation approach and entropies are defined for an image object and background.Then we determine a threshold for lower-bound image and for upper-bound image, and then calculate the mean value for the final output results.To demonstrate the effectiveness of the proposed framework, we evaluate it by using synthetic image and its ground truth.Experimental results showed how performance of the segmentation-based entropy threshold can be enhanced using proposed approach to overcome ambiguity.
Data Hiding under QR Code using Visual Secret Sharing and Advanced Partitioning Based on Specific Relationship

The Visual Secret Sharing is the technique in which secret information is hidden in the form image which then divided into shares and these shares are used to decrypt the secret information. The number of shares required is given by the creator of the secret. Minimum those many shares are needed in order to decrypt the secret. If a single share is missing then the secret cannot be decrypted. The Quick Response (QR) code gives quick access to the information contained in it. QR code is 2D representation of the barcode which has capability to store information and can be easily read by machine. Due to easy access to the information stored in it, it is necessary to use some encryption or other protection to the data. Proposed approach to visual secret sharing scheme divides a secret QR code into different shares. In addition, the secret message is recovered by using XOR operation of the shares. This can effortlessly be achieved with the use of smartphones or different QR scanning gadgets. Using optimal partitioning methods the decryption of the message is made difficult to the hackers giving additional security to the data. The message accuracy can be checked by comparing the original message with shared message using hashing techniques. Because the QR code are small in size and has high data storage capacity, it is also resistant to damage so that is information is not lost even if some portion of the QR code is damaged it is best image to be used in visual secret sharing. The proposed approach reduces the risk of data transmission attacks.