Reviewerly/exHarmony huggingface dataset:
Determinants of Corporate Name Change

[연구목적] 본 연구의 핵심 목적은 기업의 상호 변경 요인을 밝히는 것이다. 보다 구체적으로 재무제표 변수로 요약되는 기업의 경영성과가 향후 기업의 상호 변경 가능성에 미치는 영향을 분석하는 것이 목적이다. 이를 위해, 기업의 규모 및 매출액 증가율 등의 변수와 상호 변경 가능성 사이의 관계에 대해서 검토하였다.[연구방법] 본 연구는 2002년부터 2019년까지의 유가증권시장 및 코스닥 상장 기업의 재무제표 자료와 상호 변경 공시자료를 활용하여 기업의 규모, 수익성, 금융시장변수, 생산 요소 투입량이 향후 상호 변경 가능성에 미치는 영향을 로짓 모형을 활용하여 추정하였다.[연구결과] 기업의 규모가 작고 생산성이 높을수록 향후 상호 변경 가능성이 높은 것으로 나타났다. 또한 매출액 증가율이 낮고 부채 증가율이 높은 등 경영성과가 부진할수록 향후 상호 변경 가능성은 높은 것으로 나타났다.[연구의 시사점] 기존의 선행연구는 상호 변경이 외생적으로 이뤄진다는 암묵적인 가정하에 상호 변경의 원인이 아닌 결과에 대해 집중적으로 분석하고 있다. 본 연구는 상호변경의 원인을 분석하여 상호 변경 또한 기업의 전략적 결정의 일환임을 밝혔다. [Purpose] The primary objective of this study is to analyze the factors that affect corporate name changes. This study investigates how business performance－related variables affect the probability of corporate name change. We focus on how balance sheet variables affect the choice to change firms’ name.[Methodology] Using balance sheet data of Korean－listed firms, we estimate a logit model to examine how balance sheet variables affect the probability of firms’ name change.[Findings] Firms are more likely to change their name if their asset size is small and productivity grows faster. In addition, companies with poor business performance are more likely to change names.[Implications] Existing study focuses mostly on the consequences of name changes, assuming that the decision to change names is exogenous. In contrast, this research examines why corporations change their names.
Reviewing the Role of Block Chain in Securing Patient Data for Health Care Applications

Every day, there is an increasing need for healthcare applications. The patient data must still be stored securely. But in order to avoid security breaches, a variety of security measures may be used for the storage of patient data. However, these methods are out of date. Using block chain technology, security concerns should be alleviated. Health care data may be kept secure with the use of block chain, which promotes decentralization.
Cyber Security and Policy Making: An Analysis of Pakistan

The knowledge and technology era is currently in full swing. Political entities are constantly evolving, with advancements ranging from electronic utilities payment processing to modern infrastructure, the use of machine learning, advanced communication systems, and technological combat. Distances have shrunk the advancement of technology, but its use has also given rise to fresh dangers and anxieties. Cybercrimes, including stealing, criminal conspiracy, financial crimes, data breaches, matters of national security acquisition, and even dangers to essential systems, have evolved into modern-day forms of cyber warfare. These risks affect both wealthy and emerging nations, creating a national security problem. Pakistan is a nuclear-capable emerging nation that is particularly exposed to these dangers. It is more difficult for the government and lawmakers to control Pakistan's digital world because of its vast variety of internet users and poorly informed technology literacy. Nowadays, Pakistan has experienced significant cyber-attacks on vital governmental portals, and attackers have effectively breached the cyberspace of crucial infrastructure. Lawmakers in Pakistan have developed legal actions that don't fully and comprehensively address the concerns to keep this from happening. What is the status of Pakistan's policy alternatives to address significant cybersecurity challenges is the real cause of discussion. However, this study concentrates on the approach of cybersecurity framework in Pakistan. This paper highlights both primary and secondary sources as part of their qualitative research approach. Finally, a few suggestions for strengthening the nation's cyber security measures are also made. Keywords: Cyber Security, Policy Making, Pakistan, Technology
E-Monitoring of Student Engagement Level using Facial Gestures

Student engagement is a key element to ensure effective learning process. In this work, we presented an automatic system for monitoring engagement level from students’ facial gestures. In this way, the tutor can analyse the engagement level of students and improve the teaching method and strategies to enhance learning process. There has been extensive research on automated classification of engagement level, but most of these methods rely mainly on expensive eye trackers or physiological sensors in controlled settings. The proposed system monitors and classifies engagement level of student based on YOLO algorithm by determining facial gestures, where students move freely and respond naturally to lectures and surroundings. The proposed model gives a mean average precision (mAP) of 0.65 on a complex dataset where students were allowed to move freely during lecture.
MENINGKATKAN KEMAMPUAN LITERASI GURU SMA NEGERI 1 LIMBANGAN MELALUI FGD PENULISAN KARYA ILMIAH (CHAPTER BOOK)

In carrying out of duties as a teacher, in addition to teaching, a teacher also required to be able to make a good scientific work. Writing ability is one of main subject of the teacher when purpose a scientific work. But the reality, still faced some teachers that minus of ability on purpose a good scientific work. Using the latest version of application technology that improved purposes scientific work progress not fully handle as well by teachers on SMA N 1 Limbangan is one of issue for the present time. FGD (Focus Discussion Group) that doing by polimarin lectures and SMA N 1 Limbangan teachers expected can improve kowladge and ability of the teachers on literature skill and purposing scientific work (chapter book) as an obbilgation of the teachers on SMA N 1 Limbangan. The result of FGD is given knowledge and skill for the teachers for using Mendeley application as a tool for citation a reference. Aside from that given knowledge and skill for the teachers abaout paraphrase of the words, its have benefite for teacher for purposing scintifics work without doing plagiarism. And the last is given knowledge and skill about using application of electronic information system called SCI hub for downloading some journal as a reference for purposing scientific work for free.
PESSOAS COM DEFICIÊNCIA VISUAL E ACESSO À INFORMAÇÃO - UM ESTUDO NA BIBLIOTECA CENTRAL DA UFPA

The promotion of inclusive societies is among Europe's societal challenges.One of the goals of the United Nations is to guarantee the right to equal access to all levels of education.The realization of an inclusive society is anchored in guaranteeing inclusive education for students with special educational needs.At the same time, information and communication technologies offer important contributions to improving quality, accessibility and equity in educational systems, thus enabling adaptation to different learning needs.Aim: to identify the potential of information and communication technologies in promoting inclusive education for students with special educational needs in higher education.Methodology: theoretical systematization with descriptive and critical-reflexive analysis of the scientific literature.Results and Discussion: Information and communication technologies enable the development of higher order cognitive skills, especially critical thinking skills.Therefore, they act as promoters of more effective learning, and in reducing barriers to the teaching and learning process, especially social barriers.Due to its dynamic and interactive character, it enables learning at any and all times, in an adapted and individualized way to the needs of each student.Final Considerations: information and communication technologies in the educational environment provide favorable contexts for the adaptation, insertion and reintegration of students with special educational needs.In this way, they play the important role of permeating contexts that enable equality in learning, mainly by providing opportunities for a more rewarding life.However, for information and communication technologies to play their inclusive role, it is fundamental to adapt the educational environment, especially through teacher training, and in the development, improvement and active use of new digital educational resources.
Co-Designing a Website with and for Youth, so They Can Better Manage Their Health

Objective: To co-design a website aimed to empower youth to ask questions to encourage productive, meaningful conversations with their health care providers. Methods: The research team worked with two youth advisory boards consisting of adolescent stakeholders (ages 11- 17) who had at least one chronic medical condition. Youth participated in five co-design meetings to give input on website content and refinement over a two-and-a-half-year period. The youth reviewed the website in various stages of development. Results: Youth wanted a website with simple, straightforward language that would be understood by someone between the age of 11-17 years with a reputable URL. Website content includes ADHD, asthma, vaping/smoking, diabetes, seizures, anxiety, panic disorder, depression, addiction, stimulants, bullying, eating disorders, and sexually transmitted infections. Youth wanted general background content, helpful resources, question prompt lists, and videos encouraging youth involvement in care. Conclusions: A credible co-designed website with information on different health topics that contains question prompt lists and videos for utilization during health care visits has the potential to increase adolescent involvement in their care. Innovation: This website is an innovative intervention aimed at informing and encouraging teens to be more actively involved in their care across a range of healthcare conditions.
Real-time detection of transmission line insulator defects based on improved YOLOv5 model

Since insulators play an essential part in transmission lines, insulator defect detection could be an important assignments for intelligent inspection of high-voltage transmission lines. In this paper, an improved YOLOv5 algorithm for insulator defect detection task for aerial images with various backgrounds is proposed. We use collected aerial images of insulators with one or more defects in different scenarios, perform data augmentation of exposure and noise on the images to expand the sample (expanded to 2125 images), and establish a dataset by combining aerial images of normal working insulators. By adjusting the CSP(Cross-Stage-partial-connections) and CBL(Convalution-BatchNorm-Leaky_relu) modules in the YOLOv5 model to change the depth and width of the model, change model parameters, and build five different scale YOLOv5 models to further meet the real-time task. ResNet and DarkNet are used for the transfer learning of the YOLOv5 model, and various optimization methods are used in the Backbone structure, Neck structure and output of the model, then the established data set is trained and tested on each YOLOv5 model. Among them, the YOLOv5n model has the fastest detection speed, which can reach 10ms, and the precision also reaches 95%. The YOLOv5x model has the highest precision, reaching 97%, and the detection speed is 21ms. These models are all able to satisfy the accuracy and real-time mission in the process of aerial photography and analysis among which YOLOv5n can achieve lightweight tasks while being efficient enough.
Integrative Mixed Reality Sketching

In Architecture, Engineering and Construction (AEC), early design decisions have great impact.Sketching is a fast and immediate early design tool and means of communication.Communication with other professionals is challenging, because of varying professional languages.We propose a novel integrative sketching application to improve communication.Our application uses mixed reality interaction to allow sketching directly into 3D space, capture the process as temporal data, utilise animation in form-finding.We describe an exemplary workflow that integrates parametric geometry generation and digital manufacturing domain expert feedback into the early design phase of sketching via real-time data exchange.The workflow is evaluated by architectural design experts.Our findings indicate that the immediate domain expert feedback coupled with the novel 4D freehand sketching approach is a highly proficient way of aiding design decisions and streamlining AEC processes, improving communication between designers and mathematicians.
GiellaLT: an infrastructure for rule-based language technology tool development

Currently, machine learning is presented as the ultimate solution for language technology regardless of use case and application, however, it requires as a starting point a massive amount of curated linguistic data in electronic form that is expected to be high quality and representative of the kind of language usage that the tools will follow. For minority and indigenous languages, this can be an insurmountable task, as digital materials of the necessary sizes do not exist and can not easily be produced. In this article we present an approach we have successfully used for supporting indigenous languages to survive and grow in digital contexts for years, and describe the potential of our approach for African contexts. Our technological solution is a free and open-source infrastructure that enables language experts and users to cooperate on creating linguistic resources like dictionaries and grammatical descriptions. In addition we provide language-independent frameworks to build these into applications that are needed by the language community.
On the term rank partitions of matrices in

The weight of a partition is the sum of its nonzero coordinates. Let R and S be partitions of the same weight and A(R,S) be the class of all (0,1)-matrices with row sums R and column sums S. For a positive integer t, the t-term rank of a matrix A∈A(R,S), denoted ρt(A), is defined as the largest number of 1's in A with at most one 1 in each column and at most t 1's in each row. The term rank partition of A is the partition termρ(A):=(ρ1(A)−ρ0(A),ρ2(A)−ρ1(A),…,ρt(A)−ρt−1(A),…), where ρ0(A)=0. Let θ be a partition of weight equal to the number of nonzero coordinates of S. In this paper, we study conditions for the existence of a matrix C∈A(R,S) with termρ(C)=θ.
Towards Defending Adversarial Attacks with Temperature Regularization in Automatic Modulation Recognition

Deep learning has been shown to perform extremely well at various machine learning tasks. However, these same architectures are highly vulnerable to adversarial examples: malicious inputs carefully crafted by adversaries which can force a neural network to produce erroneous predictions with high confidence. This undermines the security of deep learning algorithms when apply to those security-sensitive applications. Existing works have shown that the Signal Modulation Recognition (SMR) solutions based on deep learning are also susceptible to adversarial attacks. In this paper, we propose a new approach called temperature regularization to defense a deep learning scheme against white-box attacks in signal modulation recognition. Specifically, we introduce different temperatures to the softmax layer during the training of the neural network. Experimental results show that training a neural network with an appropriate high temperature can significantly enhance its robustness to three white-box attacks.
Toward enhancement of deep learning techniques using fuzzy logic: a survey

&lt;p class="IEEEAbtract"&gt;&lt;span lang="EN-US"&gt;Deep learning has emerged recently as a type of artificial intelligence (AI) and machine learning (ML), it usually imitates the human way in gaining a particular knowledge type. Deep learning is considered an essential data science element, which comprises predictive modeling and statistics. Deep learning makes the processes of collecting, interpreting, and analyzing big data easier and faster. Deep neural networks are kind of ML models, where the non-linear processing units are layered for the purpose of extracting particular features from the inputs. Actually, the training process of similar networks is very expensive and it also depends on the used optimization method, hence optimal results may not be provided. The techniques of deep learning are also vulnerable to data noise. For these reasons, fuzzy systems are used to improve the performance of deep learning algorithms, especially in combination with neural networks. Fuzzy systems are used to improve the representation accuracy of deep learning models. This survey paper reviews some of the deep learning based fuzzy logic models and techniques that were presented and proposed in the previous studies, where fuzzy logic is used to improve deep learning performance. The approaches are divided into two categories based on how both of the samples are combined. Furthermore, the models' practicality in the actual world is revealed.&lt;/span&gt;&lt;/p&gt;
APPLICATIONS OF BLOCKCHAIN TECHNOLOGY IN THE BUSINESS ENVIRONMENT

Blockchain is a technology that has the potential to cause significant changes in our business environment and will have a significant impact over the next few decades.It has the potential to alter our perception of business processes and transform our economy.The majority of current Blockchain Technology research is focused on its application for cryptocurrencies such as Bitcoin, with only a small number of studies looking into the use of Blockchain Technology in other environments or sectors.Blockchain technology is more than just cryptocurrency; it can be used in government, finance and banking, accounting, and business process management.As a result, this study attempts to investigate and explore its opportunities and challenges for current or future Blockchain Technology applications.As a result, a large number of published studies were carefully reviewed and analysed based on their contributions to the body of knowledge on Blockchain.
Legitimacy problem of Indian crypto market deepens

Significance From an average closing value of INR30.6mn (around USD 374,000) in February 2022, the digital coin's value fell to an average of INR16.38mn by January 2023. This slump reflects the state of all such cryptocurrency tokens. It has also pushed players advocating cryptocurrencies to seek support from the government in the budget for fiscal year 2023/24 (April-March). Impacts India’s central bank digital currency project is advancing slowly, but once introduced, it will steer some users away from cryptos. Government scrutiny of corporate governance at crypto firms will intensify within and outside India. The failure of the crypto industry locally and globally to curb illicit activity hinders the mainstreaming of the industry. India will seek to align its crypto policy with that of other G20 economies, particularly the EU and the United States.
Blok Zincir Uygulamaları ile Kapalı Döngü Tedarik Zincirinde Bilgi Yönetiminin Değeri

Purpose: Rapidly developing information technology increases expectations for obtaining much more efficient structures by providing accurate, sufficient and secure information sharing in supply chains as well as in many other fields. Traceability is a critical element in supply chain management, especially in security-sensitive sectors such as food, medicine, etc. Blockchain is a decentralized record platform that provides traceability, transparency and security, and it shows promise in alleviating traditional supply chain management problems and making a positive contribution. This article aims to improve the relevant literature by revealing the level of impact of blockchain technology on supply chain management.Methodology: First of all, a traditional closed-loop supply chain (CLSC) network was designed and modeled. Then, the main model was developed by creating four more scenarios for different applications of the blockchain technology to the existing model and the application results were analyzed.Findings: This paper demonstrated the implementation of blockchain technology in forward and reverse flows activities coordination for effective and efficient supply chain management, and the resulting gains by developing appropriate models through explanatory scenarios. The implications showed that blockchain technology could significantly reduce supply chain costs.Originality: While blockchain technology is gaining attention, there are very few studies focused on its integration into the supply chain. Apart from the applications in the field of finance, the most important contribution and originality of the study is the application of the blockchain to CLSC from different aspects as partial, full, only forward flow and only reverse flow.
Real Time Indian Sign Language Recognition using Deep LSTM Networks

Abstract: On our planet, people with speech and hearing disabilities are part of society. Communication becomes difficult when it is necessary to interact with survivors and the general public. In some races, people with disabilities practice different sign languages for communication. For people with speech and hearing disabilities, sign language is a basic means of communication in everyday life. However, a large portion of our community is unaware of the sign languages they practice, so bringing them into the mainstream is an incredible challenge. Today, computer vision-based solutions are still well received for helping the general public understand sign language. Many analysts are trying out one of his computer vision-based sign language recognition solutions, Recognition of Hand Gesture. Lately it’s been a popular area of research in various vernacular languages being used across the world. Through this research work, we propose a solution to this problem using Keypoint identification and Neural Network architecture for real time sign language recognition. This architecture uses a Long Short Term Memory architecture (LSTM) giving the best accuracy of 91.5% in prediction of words as well as phrases of Indian Sign Language
Kaedah Main Peranan Dalam Pembelajaran Kemahiran Bertutur Subjek Bahasa

Speaking skills is an essential skill to be mastered, especially for students who are learning in language courses. Hence, an interactive and communicative approach needs to be applied in language learning classroom. One of the methods suggested is a role-play method whereas students are given a character to play based on given predetermined situation. Accordingly, the main focus of this study is to examine the effectiveness of role-play methods towards students speaking skills in language learning. In addition, this study is also to examine the effects of role-play towards students’ motivation in learning speaking skills in language subject. The findings of the study indicates that the role-play methods improve students’ achievement in speaking skills for language subjects. In addition, the study also found that role-play methods increase students’ motivation in learning speaking skills in language subjects. The results of this study can be used as a guidance for teachings in enhancing the effectiveness of the teaching process of speaking skills in language subjects.
Pembangunan Website dan Sarana Podcast UMKM Kampung Digital Sentra Kreasi Desa Pameungpeuk

Podcast content is increasingly being consumed by people in the world. As many as 32% of Indonesian internet users admit that they have listened to podcasts in the past week. Podcasts have become popular among young people in recent years, after platforms such as Spotify made it possible to explore digital content. Business and education topics are included in the top five podcast topic choices, as many as 67% of the 2,500 respondents in Indonesia are familiar with podcasts, and some of them are even loyal listeners. The UMKM Community in the Digital Sentra Kreasi Village is a place where Micro, Small and Medium Enterprises (MSMEs) in Pameungpeuk District and its surroundings gather. This community embraces business people with a variety of products produced. Seeing the potential of Podcasts as a place with quite a large number of listeners in Indonesia, to be used as education and marketing for MSMEs. The MSMEs Community of Kampung Digital Sentra Kreasi intends to build an MSMEs Podcast in collaboration with Telkom University's Ko+Lab and is planned to be held every month.