Reviewerly/exHarmony huggingface dataset:
Big Data Direct Search Algorithm Based on Linear Programming

In some optimization problems, the expression of the objective function is more complex or difficult to express with an obvious analytical formula, so it is difficult or impossible to obtain its derivative, and only some calculations are required for the value of the objective function. The derivative method of the objective function is not involved. The purpose of this work is to study a direct search algorithm for big data based on linear programming. Analysis of market friction factors will be studied separately. In the empirical analysis of this work, the simulation analysis method is used to calculate the actual efficiency of the investment portfolio from the eligibility reduction model, and then the DEA model is used to carry out a modular evaluation of the effectiveness of the investment portfolio, and the correlation calculates the sum of the two return values. Taking into account the conscience constraints, the DEA model is used to evaluate the rationality and efficiency of portfolio efficiency. After sorting the portfolio DEA efficiency and real return ranking, the average correlation coefficient at K = 3 is 0.998, which is quite high.
A Local-Pattern Related Look-Up Table

This paper describes a Relevance-Zone pattern table (RZT) that can be used to replace a traditional transposition table. An RZT stores exact game values for patterns that are discovered during a Relevance-Zone-Based Search (RZS), which is the current state-of-the-art in solving life-and-death (L&D) problems in Go. Positions that share the same pattern can reuse the same exact game value in the RZT. The pattern matching scheme for RZTs is implemented using a radix tree, taking into consideration patterns with different shapes. To improve the efficiency of table lookups, we designed a heuristic that prevents redundant lookups. The heuristic can safely skip previously queried patterns for a given position, reducing the overhead to 10% of the original cost. We also analyze the time complexity of the RZT both theoretically and empirically. Experiments show the overhead of traversing the radix tree in practice during lookup remain flat logarithmically in relation to the number of entries stored in the table. Experiments also show that the use of an RZT instead of a traditional transposition table significantly reduces the number of searched nodes on two data sets of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$7 \times 7$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$19 \times 19$</tex-math></inline-formula> L&D Go problems.
Influence of Mobile SMS Bill Query Application on Service Delivery by NAWASSCO AND NAIVAWASCO Water Utilities in Nakuru County

Water utilities play a critical role in providing safe and reliable water services to the public.However, ensuring efficient service delivery can be challenging, especially in areas with limited resources and inadequate infrastructure.In recent years, the use of mobile technology has emerged as a potential solution to address some of these challenges.This study examines the influence of a mobile SMS bill query application on the service delivery of two water utilities, NAWASSCO and NAIVAWASCO, in Nakuru County.This study aimed to determine the influence of mobile SMS bill query applications on service delivery by NAWASSCO and NAIVAWASCO water utilities in Nakuru County.Delone and McLean's IS success model, derived from the information systems (IS) theory, guided the study.A cross-sectional survey research design was adopted to achieve this, and data were collected using a structured questionnaire.Purposive sampling was used to select 33 and 24 staff in NAWASSCO and NAIVAWASCO water utilities, respectively.The Census method was employed since the target population was less than 100.Descriptive and inferential statistics were used to analyze the data.OLS regression analysis was used to test the hypotheses at a 0.05 significance level.The OLS regression analysis revealed that mobile SMS bill query applications significantly influenced water service delivery in water utility companies (β = 0.212, p < 0.05).Water utility companies in Nakuru County should continue investing in and promoting the mobile SMS bill query application.
A Novel Revesible Data Hiding based on Improved Pixel Value Ordering Method

Reversible data hiding based on the preservationof sorted pixel value ordering (PVO) technique has beenresearched and expanded recently due to its high embeddingcapacity and good image quality. secret data is always embedded in the largest or smallest pixel of the sub-block. Thus,each sub-block will embed two bits. The more blocks an imagehas, the higher the embedding potential. In this paper, to havemore sub-blocks, the paper divides the image into sub-blockswith 3 pixels and embeds 2 bits in the maximum value and1 bit in the minimum value. Therefore, each sub-block of theproposed embedding scheme is able to hide three bits insteadof the two bits as in the original scheme. The experimentalresults also show that the proposed scheme has a significantlyhigher embedding capacity.
“ALIMENTAL, QUERIDO WATSON”: SOLVING MYSTERIOUS CASES WHILE LEARNING NUTRITION – DEVELOPMENT AND RESULTS OF A DIGITAL EDUCATIONAL ESCAPE ROOM

“ALIMENTAL, QUERIDO WATSON”: SOLVING MYSTERIOUS CASES WHILE LEARNING NUTRITION – DEVELOPMENT AND RESULTS OF A DIGITAL EDUCATIONAL ESCAPE ROOM
The Western Great Basin Has an Arsenic Problem—Blame Its Geology

A new study links geological factors such as faulting and geothermal activity to an elevated risk of arsenic contamination in private wells across the Great Basin.
Construction of VR/AR Smart Cloud Space based on 5G Network Environment in Education

With the emergence of the “5G+education” era, research on its application is mostly theoretical and lacks practical depth, making application research costly. This study aims to integrate school, third-party enterprises, and other resources to explore the joint building of specific application scenarios for “5G+education” in schools. The 5G VR/AR smart cloud space is a smart education experience scene that combines relevant teaching resources with teaching scenes through cloud rendering using virtual reality technology (VR) and augmented reality technology (AR). The high-speed and low-delay features of the 5G network and the support of cloud rendering technology enable students to experience virtual reality scenes through VR head-mounted displays while in the classroom, enhancing learning engagement. This study explores the application of 5G technology in primary school financial literacy education, studying its impact on environmental construction, resource application, curriculum development, and learning modes. Through theoretical and practical research, this study promotes education informatization development at the school and regional levels, benefiting students and teachers alike.
La struttura informativa e la sua codifica nel binomio tedesco-italiano

As unit of a speech act, each utterance must encode a certain amount of information, whose structure has to be defined according to the communicative purpose and the shared knowledge of the participants. Therefore, it is crucial how the sender evaluates the current knowledge level of the receiver in order to establish which information has to be emphasized or selected as new. This article provides a contrastive German-Italian analysis of the most important formal means and encoding strategies that both languages employ to package information.
Is Artificial Intelligence Capable of Writing a Law Journal Article?

In this article, we explore the potential of artificial intelligence (AI), in particular, ChatGPT based in GPT 4.0 model, to create articles in the field of legal studies. We analyze the pros and cons of employing AI in jurisprudence, specifically focusing on its capacity to adapt to intricate legal terminology, evolving legislation, and nuanced argumentation. The primary emphasis is placed on potential inaccuracies that may emerge in AI-generated text, as well as the underlying causes and subsequent ramifications. Furthermore, we discuss the copyright implications for works created via AI and propose possible solutions. In conclusion, we outline the current limitations and future prospects for leveraging AI in both legal practice and scholarly research. A substantial portion of the article is entirely generated by AI.
Face Recognition Technique using YOLO V5 Algorithm

In today’s date real world application like human-machine interaction, security surveillance face recognition has made its great importance. For face recognition the steps to be followed are data collection, preprocessing, Feature Extraction, Training Evaluation and finally testing. One of the best Algorithms used for face recognition is Viola-Jones Algorithm. Viola Jones Algorithm is highly accepted because of its fast processing time and high detection rate. The other detection Algorithms which can be used are HOG Algorithm (Histogram Oriented Gradient), Deep Learning CNN (Convolution Neural Network) Algorithm, Haar cascade Algorithm and MTCNN Algorithm. In this Paper we will discuss about all this Algorithms and compare the detection rate of facial points among various methods for the datasets. YOLO V5 algorithm is another algorithm which can be used for face recognition technique. Face recognition can be achieved by combining the YOLO V5 algorithm with additional technique such as deep face recognition models like face net, which can recognize and compare facial features to identify individuals.YOLOV5 can identify facial features such as eyes, mouth, and nose, making it useful for a variety of face recognition applications.
Implementation of Early Warning System in Kampung Jenagor, Kuala Berang as an Effort to Increase Human Resilience Towards Flood Disaster

Residents living downstream of Kenyir dam (Stesen Janaelektrik Sultan Mahmud) are at risk of being flooded due to overflow through spillway, or worst, dam breaks. The nearest community to Kenyir dam is Kampung Jenagor (Kampung Jenagor) residents. A disaster preparedness action plan was proposed to equip the residents with essential knowledge on how to respond to such disaster and how to safely evacuate to designated safe havens. This paper presents one key element of the mentioned action plan, which is to develop and install a flood disaster early warning system. The system is aimed to effectively disseminate warning to Kampung Jenagor residents and ensure that there is a constant state of preparedness. The paper discusses the fundamentals of effective warning dissemination and basic design of Kampung Jenagor’s early warning system.
Comparative tests between actual and simulated digital mammography images for new computer schemes evaluation database

Computer-aided diagnostic schemes have been developed with the primary aim of supporting diagnostic accuracy in the investigation of mammography images. A robust mammograms database is a priority requirement to assist in testing the effectiveness of techniques associated with these schemes. However, such datasets–with information on radiological and biopsy reports, different types of findings and good quality images-are difficult to be available, mainly due to restrictions of different radiology centers and hospitals or limited to the research team involved. Aiming to overcome these issues, we are developing an alternative based on images of a structured breast phantom, previously developed in our group. Although having been validated in terms of their physical characteristics, the investigation on the images produced from this phantom exposure on a digital mammography system is an important task with regard to their appearance compared to actual breasts images. For this purpose, a software was developed for managing comparative tests between images from actual breasts and from this phantom, considering internal regions of interest. The intention is to evaluate how much the simulated and real images are confused according to the human visual perception of different observers, seeking to validate the use of this breast phantom for structuring a new mammography images database aimed at evaluation tests of CAD schemes in mammography. Results were promising showing a variation of 50-60% in the rate of correct answers among observers, indicating a reasonable level of confusion between the two types of images.
ICPE'23 PFAIR Workshop Chairs Introduction

It is our great pleasure to welcome you to the 2023 ACM Practically FAIR - PFAIR 2023. This workshop builds upon the popular FAIR data principles to investigate and share best practices for adopting FAIR principles in practice. The FAIR proposal only covers some computing and science domains while leaving many unconsidered and also does not prescribe how to achieve the standards in the ideal. As researchers and practitioners begin to meet these standards, we, as a community, need to agree upon what constitutes meeting the principles and how it can be validated. We had a call for research and experience papers and received one submission that met our peer review standards and will fill out our program with a keynote as well as a panel and open discussion.
POSSIBILITIES OF ENVIRONMENTAL EDUCATION IN ELIMINATING RISKY BEHAVIOR OF PUPILS IN CONNECTION WITH AIR POLLUTION

Environmental education is one of the cross-cutting topics in the school system of the Slovak Republic. Cross-cutting topics have a globally and socially significant character, and schools must educate students about these topics either by implementing them into the content of compulsory subjects (e.g. language teaching, mathematics, history...), or by cross-cutting topics can also be taught as separate subjects. Environmental education focuses primarily on how to teach students a positive approach to the environment and its protection. Within individual activities, students learn not only how to protect the environment, but also how to motivate others to do so. Preventive activities can also eliminate negative attitudes of students and their negative behavior. One of the key thematic units of environmental education in schools is the prevention of air pollution and thus the prevention of pupils' risky behavior in this direction. Topics such as the ability to understand the importance of air as a necessary need for humanity and life on our planet are also emphasized within the environmental education curriculum; the importance of air for living organisms, air pollution by human activity (industry, transport, household), the negative impact of polluted air on the environment and human health. Protection of air from pollution. Every student can also participate in school projects related to environmental protection, such as earth day, and cleaning the classroom and school surroundings.
A Network Analysis of the News Trends on College Admission Fairness

The purpose of this study is to explore the reporting trend of the Korean media by analyzing the contents of articles related to college admission fairness. From January 1, 1990 to December 31, 2022, keywords and topics were extracted from 6,006 articles and compared by period and media company. While the exam-centric news trend has declined since the introduction of the admissions officer system, the college admission fairness issue temporarily rose in 2019. As sensationalism existed before the issue became a public agenda, the focus has shifted from the admissions officer system to the investigation of personal corruption in entrance exams. Political partisanship was found from difference in the keywords network. The core network of the group of Dong-A and JoongAng included names related to the Cho Kuk scandal and the Moon Jae In regime, whereas the core network of Kyunghyang and Hankyoreh consisted of social issues instead of names except for Lee Myung-bak.
Movie 5 from HER2 Isoforms Uniquely Program Intratumor Heterogeneity and Predetermine Breast Cancer Trajectories During the Occult Tumorigenic Phase

&lt;p&gt;d16HER2 mammary intraepithelial neoplasm. d16HER2 shown in magenta. Krt14 antibody staining shown in green.&lt;/p&gt;
Heuristics for Multi-objective Service System Designing

This paper brings a short overview of heuristics developed for solving the problem of multi-objective service system designing. Even though there are plenty of effective exact and approximate solving tools for different mathematical models, they are usually not able to manage more than one objective function simultaneously. Furthermore, multi-criteria optimization assumes producing a set of non-dominated solutions instead of one resulting center deployment. Since obtaining the complete Pareto front of non-dominated solutions is extremely demanding, the development of efficient heuristics is necessary from the practical point of view. In this paper, the quality of the resulting set of solutions is studied together with the dynamics of the heuristic itself. All suggested approaches are experimentally verified making use of a dataset from real world.
Fake News Detection Using Machine Learning Algorithm

Information overflow is a concern today due to the increased number of information sources available on the internet. One of the most obvious types of cybercrime has emerged: fake news, commonly known as a hoax. Hoax news spreads harm to the social community by instilling hatred in both individuals and groups. The purpose of this paper is to distinguish between hoaxes and true news using the Extreme Gradient Boosting (XGBoost) method. The dataset used is kaggle train datasets The study included 20799 news records, including individual false and actual news stories, which were split into 80 percent training data and 20 percent test data. According to the findings of this study, the machine learning model constructed using XGBoost has an accuracy of 91 percent, a precision of 90 percent, and a recall of 80 percent. As a result, we created a webapp that uses the Flask API to determine whether or not news is bogus.
Hash learning with approximate distance

Hash-based method is important in large-scale image retrieval method, since it can greatly reduce the cost of storage and retrieval. The main idea of hash method is to map data into hash codes that preserve the original data information. In recent years, many unsupervised hash methods pay attention to the adjacency of different distance metric and aim at keeping the adjacency in the hash code and original space consistent. Euclidean distance is the most common distance metric. The nearest neighbor relationship in Euclidean distance has become the focus of many unsupervised hash methods. However, many hash codes generated under Euclidean distance will lose a lot of information so that have low ability to learn the nearest neighbor relationship. To solve the problem, an approximate distance formula is designed in this paper. Theoretically, approximate distance formula can make up for information loss caused by quantization functions, so that the nearest neighbor relationship under the Euclidean distance can be better preserved. The experiment also verifies that the hash methods using the approximate distance formula have better ability of nearest neighbor search.
Research on the Performance Evaluation Method of Specialized English Course Based on CH-SPOC Mode

In order to solve the performance evaluation problem existed in the CH-SPOC mode specialized English course, process evaluation was combined with summative evaluation to design a specialized English course performance evaluation index system, in view of the characteristics of CH-SPOC mode and specialized English course teaching and the importance of different evaluation indexes.The evaluation index system was then applied to teaching practice.The research shows that this performance evaluation method not only reflects students' learning results, but also pays attention to students' learning process and the concept of collaborative learning in CH-SPOC mode, which can better stimulate learning enthusiasm and improve teaching effect.
Attitude of Lagos Editors towards Use of Artificial Intelligence in News Management

This study aimed to discover and suggest feasible steps towards integrating artificial intelligence (AI) into news gathering in Nigeria.Traditionally, news gathering starts from the Newsroom, goes through several processes before it gets to the reader in print or on air.This entire process has been radically transformed by modern technology.In contemporary news management, the involvement of humans in the news management process is being increasingly reduced and in many cases, replaced with machines.In the present study, the researchers investigated the preparedness of print and online media editors in Nigeria to use Artificial Intelligence (AI) in news management.The ground tour questions in the research were: To what extent are editors prepared for use of AI in news management; and what is the major challenge that Nigerian editors face in integrating AI in their news management process?The Diffusion of Innovation (DOI) theory provided theoretical undermining for the study.Editors of leading online and print newspaper editors selected from Lagos, the media hub of Nigeria, were interviewed after completing a structured questionnaire.Results show most of the editors are not adequately prepared for the challenges of infusing AI into their Newsroom management.
Computer-based Music Solfeggio Teaching Resource Database System under Big Data

With the development of computer and multimedia technology, especially the development of digital music, it is urgent to change the traditional music education mode and education system.According to the national teaching content and teaching style, exploring the library of singing teaching materials and effectively promoting the development of high-quality music education has become the focus of current research.This paper designs the music solfeggio teaching resource database system under big data.This paper first introduces the design principles and business processes of the solfeggio teaching resource database system, and then studies the design methods of the solfeggio teaching resource database system, including the system objectives and composition, knowledge point settings, system framework, and system implementation.At last, it carries out experiments on the role of the solfeggio teaching resource database system.The experimental results show that before the use of the music solfeggio teaching resource database system, the efficiency of music solfeggio teaching is below 80%, and the satisfaction of music solfeggio teaching is below 90%.After the use of the music solfeggio teaching resource database system, the teaching efficiency and teaching satisfaction are greatly improved, indicating that the music solfeggio teaching resource database system is of great help to the music solfeggio teaching.