Reviewerly/exHarmony huggingface dataset:
Sample-Efficient Unsupervised Domain Adaptation of Speech Recognition Systems A case study for Modern Greek

Modern speech recognition systems exhibits rapid performance degradation under domain shift. This issue is especially prevalent in data-scarce settings, such as low-resource languages, where diversity of training data is limited. In this work we propose M2DS2, a simple and sample-efficient finetuning strategy for large pretrained speech models, based on mixed source and target domain self-supervision. We find that including source domain self-supervision stabilizes training and avoids mode collapse of the latent representations. For evaluation, we collect HParl, a $120$ hour speech corpus for Greek, consisting of plenary sessions in the Greek Parliament. We merge HParl with two popular Greek corpora to create GREC-MD, a test-bed for multi-domain evaluation of Greek ASR systems. In our experiments we find that, while other Unsupervised Domain Adaptation baselines fail in this resource-constrained environment, M2DS2 yields significant improvements for cross-domain adaptation, even when a only a few hours of in-domain audio are available. When we relax the problem in a weakly supervised setting, we find that independent adaptation for audio using M2DS2 and language using simple LM augmentation techniques is particularly effective, yielding word error rates comparable to the fully supervised baselines.
Milchbot: App to Support the Process of Feeding and Caring for Dairy Cows in Peru

At present, Peru's agricultural sector has a shortfall of professionals, so livestock producers cannot be provided with relevant and reliable information to ensure good nutrition and care for dairy cows, which affects productivity. Milchbot is a chatbot that answers queries about the feeding and care of dairy cows based on reliable documentation. To do so, a chatbot model was designed to cover the topics of feeding, care, news and frequently asked questions for the planning, feeding and care processes about dairy cows. The model consists of a friendly interface, a dialog engine and a search engine that allows you to find and provide information from a document storage. This model was implemented employing Watson Assistant and Discovery. Milchbot was used and evaluated by 6 livestock producers and 7 zootechnicians. The results of the usability and satisfaction surveys show a high rating for both livestock producers and zootechnicians, and it should be noted that zootechnicians gave very high ratings on satisfaction.
MFRRI:Research on multi-feature joint recommendation algorithm based on graph neural network

Abstract With the rapid development of Internet technology and the comprehensive popularity of Internet applications, online activities have gradually become an indispensable part of people's daily life. Internet activities are becoming an indispensable part of people's daily life. How to help users quickly find valuable information from the huge amount of data has become a great challenge for the Internet industry. The traditional recommendation system based on collaborative filtering can take advantage of big data because it can well find users with the most similar interests and recommend the items they are interested in, showing a good recommendation effect and has been the main direction of recommendation algorithm research. In recommender systems, most of the information has a graph structure, and the graph neural network GNN technique can capture the relevance of graphs through message passing between graph nodes, so GNNs are often used to generate embedded representations of users/items. However, traditional GNN-based recommendation algorithms are only able to handle regular topological graphs composed of a single type of node, while the data in the current network is not composed of only a single type of node. the main content of this paper is the GNN-based knowledge graph recommendation model. The model can effectively capture the potential interest of users through the user relationship graph for the recommendation. A joint multi-feature representation method is proposed. For user-item interaction, the representation of node features in the case of sparse network connectivity is enhanced by using multi-order topological structure information in information networks. The model in this paper was verified to perform significantly better than the baseline approach by conducting experiments on public datasets.
PENGARUH PERSEPSI DAN PENGALAMAN TERHADAP KEPUTUSAN MEMILIH UNIVERSITAS MUHAMMADIYAH PALEMBANG

These objectives of this study were to find out whether or not there were any significant effects of perception and experience on the decision making to choose Muhammadiyah University of Palembang. The type of this study was an associative, with the variables used were perception, experience and decision making. The sample chosen were 100 respondents, with the data collection method using a questionnaire. The analysis technique in this study used multiple linear regression analysis. The results of simultaneous hypothesis testing showed the value of Fcount &gt; Ftable, which meant that there was a significant effect of perception and experience on the decision making to choose Muhammadiyah University of Palembang. The results of the partial hypothesis test showed the value of tcount &gt; tcount, which meant there was a significant effect of perception on the decision making to choose Muhammadiyah University of Palembang, and there was a significant effect of experience on the decision making to choose Muhammadiyah University of Palembang. The value of the coefficient of determination showed that the variables of perception and experience were able to contribute to the ups and downs of the decision making to choose Muhammadiyah University of Palembang, by number 33.2%.
Investigating Factors that Impact Employee Turnover in the Medical Device Industry in the United Arab Emirates

The United Arab Emirates (UAE) has established itself as the medical device industry&amp;rsquo;s preferred regional center. Major multinational corporations either have a regional subsidiary or are planning to open up a principal office in the UAE to expand their business. Employees in the industry are in high demand as new opportunities open up frequently and that causes challenges to companies, namely employee turnover. This research helps bridge the gap found in the literature by investigating the factors that impact employee turnover in the medical device industry in the UAE. These factors were tested with their subsequent sub-factors. Using a quantitative approach, the study surveyed 230 participants from 47 medical device companies in the UAE. The result of one-way ANOVA demonstrated a significant relationship between employee salary and employee turnover. The linear regression analysis was statistically significant between perceived external prestige, location, flextime, organizational justice, job satisfaction, organizational commitment, extrinsic rewards, career advancement, lack of alternatives, constituent attachments, and employee turnover. These findings indicate the need for a strategy utilizing these factors for existing and new medical device companies in the UAE to prevent high employee turnover or limit it at least.
Focus Web Crawler on Drug Herbs Interaction Patterns

The types of pharmaceutical products include cosmetics and drugs. Some of the pharmaceutical products comprise a mix of drugs and herbs without considering their interaction effects. Drug-herb interactions (DHIs) refer to the interactions between conventional drugs and herb medicines. However, the available information on DHIs are scattered because it has heterogeneous databases and website resources, apart from some of the paid or subscribed databases. Easy access to information on DHIs would allow researchers to explore more. Therefore, this study proposes improvements in the focus web crawler to collect DHIs information from the heterogeneous resources on the Internet, present priority levels of a resource link through anchor text and URLs, and traversing the link with the aid of depth. The improved focused crawler was tested on two algorithms namely the Breadth-First Search (BFS) and PageRank. Information of DHIs crawled 4,744 herbals from the focus web crawler. The accuracy values for Chinese Med Digital Projects and MedlinePlus were 98% for PageRank and 71% for BFS. Additionally, a focused web crawler may gather more relevant web pages in the same amount of time as a wide crawler. Hence, the proposed crawler may successfully gather DHIs on the web in response to the user queries.
A News Recommender System: Implementation and Analysis

In the past few years, the need of prediction has increased rapidly. Predicting the purchase, reading of news, buying food items are a few popular interests of researchers and marketing people as well. Newspapers are quite essential to urge information concerning recent activity and general awareness for all age groups. Varied solutions are being developed to convert paper News systems to digital news and it has become a standard for all news companies. A recommendation system has been proposed and developed for suggestions to the user. Researchers have developed many algorithms for developing the recommendation system. Each approach has its pros and cons. In this paper, we have studied different approaches for news recommendation systems and developed a content-based filtering model for recommending news articles to the user. The articles with more euclidean similarity have higher chances of suggesting to the user.
Trust Management Techniques and their Challenges in Cloud Computing: A Review

.Cloud computing is a way to handle tasks like development, production, and maintenance done on the web. This domain is evolving. It uses a pay-per-use system like an electric bill and can be used to run virtual machines. Customers are rapidly adopting and shifting the companies that provide such services due to the presence of numerous service providers. It is also customizable as per users' requirements but poses several security risks. It is dynamic and can be updated to meet the needs of both the client and the service provider. It is a significant feature of such distributed computing platforms. However, this undermines trust and credibility and generates security, protection, individuality, and authenticity problems. Consequently, selecting an appropriate service provider is the most critical test in the cloud environment. The Trust system is an essential part of how QoS and feedback ratings are judged to evaluate the service. Even so, the executive's plan for observing and evaluating QoS still needs to get past several tests. This paper examines the current impediments to trust in the existing trust framework. This report includes a systematic review of various high-quality articles published on trust management between 2010 and July 2022. To do this, some strategies for managing trust are put into four groups: SLA, suggestion, feedback, and prediction. This article also compares the pros and cons, evaluation methods, tools, and simulation settings of different management models.
A Novel Trust Negotiation Protocol for Analysing and Approving IoT Edge Computing Devices Using Machine Learning Algorithm

In this paper, we come up with an effective approach for the management of security using machine learning, and we derive a solution for problems with privacy and security in Internet of Things devices. Recent apps' connections to numerous IoT devices, use of edge computing, and use of fog computing cause numerous DDoS attacks to be launched against the servers of the dynamic network. For computing on the edge of the Internet of Things, the upgraded Trust Negotiation Protocol is used, making use of better period data. The application of security management is used to maintain the automation, minimize the risk level, and reduce the complexity of the system. The fundamental objective of this system is to enable user-level security in all edge computing devices related to the Internet of Things. Using Machine Learning techniques, a proposed model is utilized to develop a secure environment for E2E IoT security at the user level. A low-cost solution is obtained using machine-learning-based security management techniques. The Enhanced Trust Negotiation Protocol is simulated, and the experiment results demonstrate that the suggested model is superior to the current one in terms of the efficiency with which security management approaches may be implemented.
An Insight into Forensic Accounting

Forensic accounting comes under the category of relatively new profession that utilizes various methodologies andimplementation of various techniques. This field of forensic science is structured and constructed by keeping inmind the world’s economy, society and legislation. With the increasing number in financial accounting deceptionsand frauds in the global economy, forensic accounting has become the field tagged as savior for the safety forthe financial administration process of academic, research and commercial institutions. The total combination ofaccounting, auditing and investigative skills signify this specific field. Just as forensic science has been implementedto capture the criminals for long, forensic accounting is fast emerging in the arena of corporate accounting fraudsto play a similar role. The purpose of this study is to develop an innovative approach of combating economic crimeusing the forensic accounting techniques by reviewing the previous studies made on this field of forensic science.
Federated Learning for Education Data Analytics

Federated learning techniques aim to train and build machine learning models based on distributed datasets across multiple devices, avoiding data leakage. The main idea is to perform training on remote devices or isolated data centers without transferring data to centralized repositories, thus mitigating privacy risks. Data analytics in education, in particular learning analytics, is a promising scenario to apply this approach to address the legal and ethical issues related to processing sensitive data. Indeed, given the nature of the data to be studied (personal data, educational outcomes, data concerning minors), it is essential to ensure that the conduct of these studies and the publication of the results provide the necessary guarantees to protect the privacy of the individuals involved and the protection of their data. In addition, the application of quantitative techniques based on the exploitation of data on the use of educational platforms, student performance, use of devices, etc., can account for educational problems such as the determination of user profiles, personalized learning trajectories, or early dropout indicators and alerts, among others. This paper presents the application of federated learning techniques to two learning analytics problems: dropout prediction and unsupervised student classification. The experiments allow us to conclude that the proposed solutions achieve comparable results from the performance point of view with the centralized versions, avoiding centralizing the data for training the models.
Marketing Mentality of the Modern Age: Digital Marketing

Technological developments, especially in the period from the 1990s until today, have caused many changes in the field of marketing as well as in many other fields.Considering today's conditions, it is an undeniable fact that the internet is widely used and covers an important part of modern life with the concept of digitalization.Not only businesses have been affected by the concept of digitalization brought about by developing technology, but this has made it possible for consumer perception and marketing activities to be transformed as well.The change in the understanding of marketing with the effect of technological advances has revealed the concept of digital marketing.Especially since the internet and digital media are widely used in today's marketing environment, consumers' attitudes and desires have also kept up with this change.Consumers of the modern age, who have become more conscious, demand to research the goods or services they are considering buying, to compare them with each other and to have much more detailed information about the products.It is extremely critical for businesses trying to get used to this situation to transform their marketing activities to adapt to the new order.Today, it is seen that the internet is widely used, and digital platforms are increasingly diversified day by day.It is very important to reach consumers who are actively involved in digital environments quickly.In this context, many businesses that want to stand out from their competitors and gain competitive advantage aim to be successful by using different digital marketing methods.In this study, the concept of digital marketing, which is revealed by the changing marketing understanding in the modern marketing environment, where the internet plays a very important role in every field, is discussed from a conceptual point of view.In this context, various aspects of digital marketing, especially current issues such as the definition, scope, advantages, and 16 disadvantages of digital marketing, have been discussed and domestic and foreign studies on digital marketing have been included so far.
Colombian Prototype of a Spirometer, From Classroom to Practice

Design technological tools from basic sciences would be an excellent way for students to learn about Science, Technology, Engineering, and Mathematics (STEM) applications. Nowadays, young people are more connoisseurs of computer tools and gadgets than other generations. They could use those aptitudes with correct stimulation and orientation to generate new knowledge or improve technological applications in developing countries like Colombia. Designing or improving technology starting from basic knowledge and developing cheap technology is essential for the development of a society. We used a case study in this work, due to COVID 19 pandemic, we propose the design and creation of a prototype of a spirometer started from a class activity to put into practice the knowledge acquired in theoretical class and let students observe and implement physics applications. As a result, elemental physics course students achieve testing it on real people and compare it with known results. The students' spirometer prototype was made with inexpensive implements starting with the knowledge learned in the classroom. With it, students tried it on actual patients, letting them get measurable data consistent with known results from the literature. These experiences increased students' interest in science and its applications. This work shows us that applying STEM methodology from basic levels to practical uses could motivate young people to learn and improve their skills in those topics and see science as a way of life.
PEMBELAJARAN BAHASA INDONESIA MENGGUNAKAN METODE INQUIRY BASED LEARNING DI SEKOLAH DASAR

This study aims to: 1. To apply inquiry based learning learning methods to Indonesian language subjects in elementary schools, especially in the current 21st century technology era, 2. To improve student achievement in the 21st century technology era, 3. Train students so that they are ready and able to adapt themselves in learning along with the times. This research is qualitative in nature by using the literature study method, namely data collection techniques by reviewing various sources of books, notes, literature, and various kinds of reports related to the theme. The results obtained in this study are that the inquiry learning learning model can be implemented by good in learning Indonesian in elementary school. The inquiry learning model is very effective and efficient to be applied in Indonesian language learning, where this inquiry learning model uses a student centered approach so that students are trained to think critically, creatively, and innovatively and the teacher is only a facilitator for their students, so it can be concluded that the method Inquiry based learning is very effective and efficient to apply in Indonesian language learning and can also be applied to other subjects, especially in the current 21st century technology era.
Arithmetic on generalized Hessian curves using compression function and its applications to the isogeny-based cryptography

In this paper, we present formulas for differential addition and doubling using the compression function fGH,2(P ) = xP + yP of degree 2 on a generalized Hessian curve EGH : x 3 + y 3 + a = dxy, where P = (xP , yP ).We use in this context elementary algebra methods.Moreover, we also present formulas for 2, 3-isogeny, and general ℓ-isogeny evaluation, using this function.It is worth noting that for the compression function fGH,2, such formulas have not been presented before.On the other hand, we also use elementary algebra methods for obtaining differential addition and doubling formulas using the compression function fGH,6(P ) = xP yP of degree 6, and we present formulas for 2 and general ℓ-isogeny evaluation using this function.
IMPROVING READING COMPREHENSION SKILL THROUGH LANGUAGE GAMES AT VII GRADE OF JUNIOR HIGH SCHOOL

This research is aimed at improving the students’ reading comprehension at grade seven of SMP Negri 4 Praya in the academic year of 2022/2023. The teaching reading skill of seven grade students of SMP Negri 4 Praya was through language games. To achieve the objective, collaborative work involving the researcher, the English teacher, the principal, and the students of grade seven was conducted. This study was action research study consisting of two cycles. The steps of the research were: planning, action observation, and reflection. The data were obtained by observing the teaching and learning process during the implementation of the actions, interviewing the English teacher and the students of seven grade students, and holding discussions with the English teacher. The instruments for gathering the data were a recorder, a camera, and interview guidelines. The data analyses were in the forms of field notes, recordings, interview transcripts, and photographs. The result showed that in Cycle 1 the implementation of language games was successful in improving the students’ reading comprehension and their interest in reading during the teaching and learning process. However, the language games which was implemented through group work was not successful because there were some students who were not actively engaged in the group work. Therefore, the researcher improved that action by applying pair work and giving reward. Meanwhile, it was shown in Cycle II that the implementations of language games were successful in improving the students’ reading comprehension and interest in reading during the teaching learning process. From the two cycles, the implementations of language games were effective to improve students’ reading comprehension.