Reviewerly/exHarmony huggingface dataset:
A CASE STUDY OF A GERMAN LANGUAGE LEARNING PERCEPTIONS OF LEARNERS ON ANDROID SYSTEMS AT THE SCHOOL OF FOREIGN LANGUAGES, EASTERN MEDITERRANEAN UNIVERSITY

At the present time, with the advancement of technology in mobile phones and tablets which have equipped people with mobile computers, and because of students’ preferences for convenient and low-cost approach of learning, the idea of using mobile applications for educational purposes is gradually getting stronger. Hence, it is essential to investigate about the benefits and drawbacks of using applications in education and develop this idea in order to improve and prosper the future of pedagogy and expand it beyond classrooms. The aim of this research is to analyze the viewpoint of the Eastern Mediterranean University (EMU) students, who are registered to the German Language Learning course (ELT502) which is given by the School of Foreign Languages. In this research, a quantitative approach was used, and the required data was gathered through questionnaires which were responded to by the students at the School of Foreign Languages and has been analyzed by SPSS 25. The results of this research illustrated that students were satisfied by using this type of education and are willing to utilize it again in order to improve their language learning skills. Along with the results, this research has provided some recommendations like applying the efficient methods in M-Learning in order to improve the learners’ language learning process.
Exploring the Uses of Bilingual Dictionaries among the Safaliba in Ghana and the Gorontalo in Indonesia

This chapter describes how teachers in one ethnolinguistic community (Safaliba, in Ghana) and parents in another (Gorontalo, in Indonesia) use pedagogical learner dictionaries. Local activists in the province of Gorontalo have produced a bilingual dictionary and corresponding app in Gorontalo, and English, with pictures. Similarly, Safaliba teacher-activists and their allies have produced their own bilingual dictionary. We ask how teacher-activists and parents bring language learning alive with dictionaries for their different situated contexts. With respect to Safaliba, we describe the use of a dictionary to write acrostic poems, make bilingual crossword puzzles, play jumbled word games, and engage with spot-the-difference two-way information gap tasks with matrices and culturally relevant drawings from a Safaliba artist. With respect to Gorontalo, we examine how parents use the dictionary app with their children, including interviews about the perceived effectiveness of the dictionary app for language learning. With the Covid-19 pandemic, families have been in quarantine in their homes together; hence, we ask how they can promote language learning in the home while utilising these materials.
A survey on geometric shape representation of objects based on medial axis transform

&lt;div&gt;&lt;p&gt;Geometric shape representation algorithms are key technologies in the fields of computer graphics and geometric modeling. The Medial Axis Transform (MAT) is an important geometric model description tool that provides a simplified representation of complex geometric shapes while ensuring accurate descriptions of geometric shape and topology. Therefore, it can meet the requirements of many modern research fields, including geometric modeling, pattern recognition, model segmentation, model deformation, physical simulation, path planning, and more. This paper first introduces the basic concept of the medial axis transform, including the definition of the medial axis transform and the concept of medial axis primitives. It then describes the extraction algorithms for the medial axis transform, specific research on the medial axis transform in computer vision and computer graphics, potential applications of the medial axis transform, and medial axis transform datasets. Finally, the disadvantages and advantages of the medial axis transform are discussed, and some suggestions on possible future research directions are presented.&lt;/p&gt;&lt;/div&gt;
Smart Voting Platform (Secured Digital Voting System) Uses Blockchain Technology and Biometric Authentication

At present, the development of information technology has invaded all the fields of the world.Among them, blockchain technology holds a special place and it is currently used in areas that require high security.Also, the election process is an area that needs a very high level of security.When the present.there are lots of online voting applications available in the world.But developing countries like Sri Lanka did not use online platforms for the public election process until they used the paper-based voting method for the general election.Because online platforms have many issues and will be based on countries inside situations.Therefore, through this research, we are trying to find solutions to those issues and develop a new platform for the electronic voting process by using blockchain technology.
Computational pathology for nephropathology

Digitisation of pathology enables computational pathology. Due to their excellent performance, deep learning-based systems are used primarily. In computational nephropathology, the focus of many studies is on large-scale extraction of comprehensible quantitative data from histological structures. The resulting data can be used for various downstream analyses, including prediction of the disease course. Such systems could significantly support nephropathological diagnostics in the future.
Predicting the Effectiveness of Blockchain Bug Bounty Programs

Bug bounty programs have proven to be an effective means for organizations to incentivize ethical hackers to report security vulnerabilities in their software. As the use of blockchain-based applications has grown, bug bounty programs have been established to identify vulnerabilities in these applications, such as smart contracts. However, bug bounty programs face unique challenges in encouraging ethical hackers. In this study, we collected data from about 200 bug bounty programs related to blockchain software from multiple bug bounty platforms. We analyzed the content of these programs and examined the involvement of ethical hackers, with the aim of examining the effectiveness of the current bug bounty programs for blockchain software. Additionally, we extracted various features from the content and format of the bug bounty programs and utilized them to construct a regression model that predicts the effectiveness of a program in drawing in ethical hackers. Our work is a fundamental step towards developing effective strategies for incentivizing ethical hackers in the blockchain domain.
Pelatihan Penggunaan Mendeley dalam Menulis Sitasi dan Daftar Pustaka bagi Mahasiswa Uniflor dalam Penulisan Tugas Akhir

Readers can verify the information or read more about the topic. The bibliography also allows the author to retrace the steps that have been taken and find information that the author has used for the assignment and find further views or ideas discussed by the author. In fact, students have not been able to use the Mendeley application in writing citations and making a bibliography, whereas nowadays students are required to write articles that will be published in national journals before graduation. Therefore, Mendeley training is needed for fluency in article preparation, because all national journals demand to use of the Mendeley application in citation writing and making a bibliography. The purpose of this training is for students to be able to write good and correct citations and bibliography. Implementation Method The approach method used is direct training on proposals that have been prepared by students who are programming the final project. This training was carried out at the University of Flores for 8th-semester students of the mathematics education study program who programmed their final project. The total number of students who participated in the training was 20 people, requiring participants to bring their own laptops and proposals. The method is used in the form of lectures, practice question sessions, and answers. Participants are enthusiastic and motivated to take part in the training because the knowledge gained from this training will greatly assist participants in writing final assignments and articles. More than 80% of students are able to install applications and plug-in Ms. Word independently. However, some students still have difficulty registering the application using email. Students are expected to carry out continuous exercises so that they can apply Mendeley in the life of the scientific community.
Kombinasi Metode Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) dan Pembobotan Rank Order Centroid (ROC) dalam Pemilihan Tablet PC Terbaik

Tablet PC which is one part of technological developments in the field of communication that aims to meet the needs of users where these needs are not found on smartphones or laptops, is an option that can be an alternative communication tool that can meet needs involving a smartphone. such as designing, playing games, and working. related to the many models of tablet PCs in the world of communication causes the selection of the best tablet PC to be a problem for the users themselves. One of them is if the user chooses the wrong type of tablet PC according to their needs, the tablet PC does not make it easier, instead it hinders the activities of the user himself. therefore data from the types of tablet PCs are collected from 5 criteria and 7 alternatives where the criteria have been determined including screen size, memory capacity, memory type, hard disk capacity and price. From these criteria, the use of ROC can be used to giving weight to each criterion which is then determined using the MOORA method included in the decision that can give the maximum and accurate final preference value, so this study determines the best tablet pc choice option is alternative A1 brand apple ipad air with a final value of 0.054 as the best alternative.
Optical micro-phase-shift dropvolume in a diffractive deep neural network

To provide a desirable number of parallel subnetworks as required to reach a robust inference in an active modulation diffractive deep neural network, a random micro-phase-shift dropvolume that involves five-layer statistically independent dropconnect arrays is monolithically embedded into the unitary backpropagation, which does not require any mathematical derivations with respect to the multilayer arbitrary phase-only modulation masks, even maintaining the nonlinear nested characteristic of neural networks, and generating an opportunity to realize a structured-phase encoding within the dropvolume. Further, a drop-block strategy is introduced into the structured-phase patterns designed to flexibly configure a credible macro–micro phase dropvolume allowing for convergence. Concretely, macro-phase dropconnects concerning fringe griddles that encapsulate sparse micro-phase are implemented. We numerically validate that macro–micro phase encoding is a good plan to the types of encoding within a dropvolume.
Exploring a Forensic Methodology for Identifying Cyber Frauds Within the Indian Banking System

Heave in online banking usage has resulted in a growth in frauds and scams. Somewhat scams or frauds in banks have an extensive impact. Fraud has far-reaching consequences that go beyond economic loss. Fraud influences organizations, individuals, businesses group, businesses, services, and the entire ecosystem. Units can make better decisions if they understand and assess the overall effect of fraud. Any fraud, whether committed by opportunistic individuals or major and organized crime groups, can have significant consequences.
A Study on Eye Tracking Techniques using Wearable Devices

The eye tracking technology is widespread all around the society, and is demonstrating great performances in both preciseness and convenience. Hereby we can glimpse new possibility of an interface’s conduct without screen-touching. This technology can become a new way of conversation for those including but not limited to the patients suffering from Lou Gehrig’s disease, who are paralyzed each part by part of the body and finally cannot help but only moving eyes. Formerly in that case, the patients were given nothing to do but waiting for the death, even being unable to communicate with there families. A new interface that harnesses eyes as a new means of communication, although it conveys great difficulty, can be helpful for them. There surely are some eye tracking systems and equipment for their exclusive uses on the market. Notwithstanding, several obstacles including the complexity of operation and their high prices of over 12 million won($9,300) are hindering universal supply to people and coverage for the patients. Therefore, this paper suggests wearable-type eye tracking device that can support minorities and vulnerable people and be occupied inexpensively and study eye tracking method in order to maximize the possibility of future development across the world, finally proposing the way of designing and developing a brought-down costed eye tracking system based on high-efficient wearable device.
Implementation of monitoring system for availability of Hyperledger Indy

Hyperledger Indy is an open-source implementation of DID, a decentralized identity verification technology. Hyperledger Indy uses the RBFT consensus algorithm, and if there is a lack of consensus with more than a certain number of problem nodes in the pool, data is not added. This problem can be prevented in advance by adding a node, and a node monitoring system was implemented to operate automatically. The node monitoring system continuously checks the status of the pool and automatically adds nodes when there are more than a certain number of problematic nodes to prevent consensus problems from occurring. This proposed method can increase the availability of Hyperledger Indy and is a study that can be referenced in various blockchain services that use consensus algorithms.
Androz Chatbot for Alzheimer’s Patients

Abstract: Chatbots are computer programs that automatically respond to messages and can be configured to respond the same way every time, to respond differently to messages with specific keywords, and even to use machine learning to adapt their responses to the situation. Users can communicate with artificial intelligence using a text or voice interface using chatbots. Alzheimer's is a chronic neurological illness whose root cause is unclear. Since there is no recognized cure, patient care is mostly focused on creating a comfortable atmosphere for them and supporting the caretakers. In the proposed model, we have redesigned the chatbot's architecture to be able to follow the patient's movement with location and if the patient wanders or moves away from their house, voice notes-based guidance and navigation is used to help them. The system's main job is to carry out memory training operations using names and information of well-known people, locations, and events that may be dynamically
A LABORATORY VALIDATION OF SELF-COLLECTED NASAL SWAB AND RHINOSWAB FOR THE DETECTION OF SARS-COV-2

Intro: Antibiotic resistance has become a major problem due to excessive and inadequate use of these drugs over the years.The awareness of the severity of this issue to society is necessary to promote health literacy.Furthermore, the awareness is essential to fight misinformation among the population and to ensure prevention.However, sometimes it is difficult to pass a simple, nonetheless accurate, message to the general public.This project is aimed at students, health professionals, and the public general to raise awareness at young ages and educate the general population about antibiotic resistance.Methods: It was developed a comic strip about antibiotic resistance entitled "Fighting Bacterial Resistance".Comics for pedagogical purposes are a very common and effective means of dissemination, considering their transversality.This cartoon was intended to demonstrate that bacteria can acquire defense mechanisms against antibiotics, such as genetic modifications, thus becoming resistant.Consequently, resistance genes can be spread among bacteria.Moreover, it was shown some bacteria are multidrug-resistant which makes the treatment a challenge.Findings: The comic strip was presented to both health professionals and general public.Both targets were very pleased and showed enthusiasm reading it.Conclusion: A comic strip showed to be a effective way the reach different kinds of public since it creates a bonding with the public, no matter the level of education
IMPLICATIONS OF THE DANISH DEFINITENESS ALTERNATION FOR CONCORD IN NANOSYNTAX

The Danish definiteness alternation presents two challenges for Nanosyntax. First, it displays structural allomorphy of the definiteness marker between a suffix and prenominal article; second, there is concord between the definiteness marker and noun gender. I show that Nanosyntax can address both issues, explaining the suffix-article alternation by virtue of its spellout algorithm and the lexical overlap between suffix and article. This account provides a deeper explanation for the structural allomorphy than the Distributed Morphology analysis proposed by Hankamer &amp; Mikkelsen (2018). The existing proposal for concord in Nanosyntax (Caha, 2019) cannot handle this combination of gender concord and allomorphy, so I propose a simple copying mechanism which handles concord more flexibly. This new proposal, however, is substantially less restrictive than Caha’s framework, paving the way for future work to balance restrictiveness with empirical coverage of prefix/suffix alternations and concord across languages.
On the Privacy of Elementary Matrices Masking-Based Verifiable (Outsourced) Computation

Privacy-preserving Verifiable (outsourced) Computation (PVC) for face recognition is a significant research topic in the information security community. Recently, an efficient elementary matrices masking-based PVC protocol for face recognition has been published in IEEE Transactions on Dependable and Secure Computing [2]. In this paper, we analyze the privacy property of this protocol, and demonstrate that the output distribution of the problem generation algorithm in this protocol is not computationally indistinguishable from the uniform distribution over a matrix set, which breaks the original consequence (see Theorem 1). We introduce a formal definition of a privacy model for a PVC protocol and prove that the targeted PVC protocol does not hold privacy under this model. We then present our experimental results to support our theoretical analyses.
The Effect of Online Game Addiction on Violent Behavior in High School Students

Addictive behavior online games the point where teenagers become dependent and lose control. Habits play game online in adolescents lead to changes in character such to become aggressive. Aggressive behavior not only in physical but also take of aggression anger and hostility can hurt people. This study to determine relationship between addictive behavior online games with aggressive behavior of High School students. Type research quantitative cross sectional approach. Population all students of class X-XI of SMAN at Tambun Utara. Sample using total sampling. Instrument used instrument by Chen and Chang (2008) for level online game addiction and the Buss-Perry Aggression Questionnaire Scale (BPAQ) for level aggressive behavior. Analysis data used descriptive statistical and chi-square. The results, it is known characteristics respondents are dominated by boy (63.1%) coming from class XI (64.1%) and 17 years old (47.6%), the type of online game most often played is Mobile Legend (62.1%) with playing duration for 3 hours (62.1%), high online game addiction (52.4%), and high aggressive behavior (57.3%). And results chi square test obtained that p-value of p= 0.001 with = 0.05 (p-value &lt;α ), can be concluded that there is a significant relationship between game addiction and aggressive behavior in students.
GIL: a python package for designing custom indexing primers

Abstract Summary Generate Indexes for Libraries (GIL) is a software tool for generating primers to be used in the production of multiplexed sequencing libraries. GIL can be customized in numerous ways to meet user specifications, including length, sequencing modality, color balancing, and compatibility with existing primers, and produces ordering and demultiplexing-ready outputs. Availability and implementation GIL is written in Python and is freely available on GitHub under the MIT license: https://github.com/de-Boer-Lab/GIL and can be accessed as a web-application implemented in Streamlit at https://dbl-gil.streamlitapp.com.
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Cyber-lawyer Scott Shapiro believes there is more to beating hackers than getting better at programming. He tells David Adam why online security is as much about humans as technology and how understanding both can keep us safer online
CUCN: continuously updated connection network for low-light image enhancement

Low-light (LL) images make subsequent computer vision tasks difficult due to its low contrast. To solve this problem, the LL image enhancement problem is regarded as narrowing the gap between LL images and normal-light images in the process of iterative learning. A continuously updated connection network (CUCN) that is inspired by the recent development of convolutional neural networks is proposed. The proposed CUCN is composed of a continuously updated 4-units module (CU4UM), a feature fusion module (FFM), and a color enhancement module (CEM). The CU4UM adopts a connection method to combine four U-shaped structures with continuously updated parameters. To retain the global and local details while brightening an image, the FFM effectively combines the features of different layers in different U-shaped structures and assigns appropriate weights to each channel. The CEM takes the residuals of multiple features of different scales and performs iterative weighting to obtain more natural color information. The proposed method is evaluated on different public datasets, and the results show that the proposed CUCN method is superior to other state-of-the-art methods in terms of both subjective and objective metrics.
In-Hospital Cancer Mortality Prediction by Multimodal Learning of Non-English Clinical Texts

Predicting important outcomes in patients with complex medical conditions using multimodal electronic medical records remains challenge. We trained a machine learning model to predict the inpatient prognosis of cancer patients using EMR data with Japanese clinical text records, which has been considered difficult due to its high context. We confirmed high accuracy of the mortality prediction model using clinical text in addition to other clinical data, suggesting applicability of this method to cancer.