Reviewerly/exHarmony huggingface dataset:
APPLICATION OF CLUSTERING GROUPS IN DETERMINING LAND SUITABILITY

The problem of the suitability of planting land for planting types of plants is still a lot of unresolved farmers. land at the beginning of land selection is very decisive. This is to determine whether the land is productive or not. in the future is the result that farmers will experience considerable losses if this is not estimated, therefore a model is needed to know and estimate accurately whether the land or land is suitable for planting crops or not. The purpose of this study is that farmers do not experience losses and losses on land when planting crops on available land. So that it can improve the quality of food in Aceh and can improve the welfare of farmers. The result of the research is that it can be found a Clustering model or grouping of plant stock types using the k-medoid model, finally the application of this clustering model is able to provide a solution for the Office. Based on calculations using the K-Medoids method obtained for land compliance in North Aceh Regency is Corn with an adjustment of 53.6%, Peanuts 17.9%, Soybeans 14.3%, Bulbs 10.7% and the suitability for rice is 3 ,6%.
A Research Paper on React News - API

Abstract: This abstract discusses the use of News API, a web service that provides access to news articles from various sources, with React, a popular front-end framework. With News API, developers can quickly retrieve news articles from over 30,000 sources and customize the API response format to their needs. React provides a powerful and efficient way to create user interfaces, making it an ideal framework for building news applications. By using React with News API, developers can create a user-friendly and responsive news application that can be tailored to the user's requirements. This research paper provides an overview of News API and its features, discusses how to use News API with React, and includes an example code snippet. Developers can make use of the News API and React to create innovative and feature-rich news applications that can cater to a diverse range of users.
Enforcement of Minimal Size and Area Constraints before and while Mining Patterns in Fuzzy Tensors

Fuzzy tensors, i. e., n-way tensors with values in [0, 1], indicate to what extent n-tuples satisfy a Boolean predicate. In that very general context, the multidupehack algorithm mines itemset-like patterns. They are sub-tensors with values "close to 1" and can be further constrained. In particular, the analyst usually wants to focus on large-enough patterns and specifies minimal numbers of elements every pattern must contain in some of its n dimensions and/or a minimal number of n-tuples inside the pattern. Not only constraints filter out irrelevant patterns, they lower the time multidupehack takes to discover the relevant ones too. This article aims to further lower that time when minimal size/area constraints are enforced. Two algorithms are proposed. Both discard elements that no large-enough pattern can involve, i. e., they losslessly reduce the pattern space. The first algorithm runs before mining the patterns with multidupehack or with another algorithm that similarly defines them. The second algorithm, less effective but more efficient, is used while mining the patterns. Experiments on real-world fuzzy tensors show that the two algorithms sometimes divide by more than 80,000 the time multidupehack takes to discover the valid patterns.
How do we arrive at constraints? Articulating limits for computing

Computing within Limits invites considerations of limits and constraints in design practice.We compare two projects which integrate constraints, the reduction of academic air travel and a solar powered internet, to show a distinction between two approaches to arriving at constraints.In the case of reducing academic air travel, the problem which greenhouse gas emissions pose for business-as-usual academic travel is addressed by proposing constraints on future flying.Constraints in the Flight project can be understood as a process of commensuration, of comparing that which is to be constrained according to a common metric.This gives rise to a future of academic travel understood in relation to CO2 emissions and reduction targets.In the second case, we have explored the solar internet as a specific way to introduce constraints in the context of the rising electricity use associated with internet infrastructure.In the Solar Internet project, constraints have been approached relationally and iteratively, in reconfigurations of internet use practices and design practices, including the solar internet imaginary and the scale of battery and power supply.We compare these two approaches, drawing on vocabulary from Sociology of Quantification and Science and Technology Studies, to help articulate their respective implications, while also acknowledging what they have in common, e.g. the ability to expand the frame of what is made relevant for design practice.The case of the Flight project suggests that constraints as a process of commensuration can be fruitful when pursuing a unified future, intervening over time with a trajectory towards a quantifiable target.On the other hand, when trying to account for indirect effects and the future as multiple, the introduction of constraints can better be understood as con-figurations, with a future negotiated iteratively in design practice.Rather than thinking about constraints as essentially requiring one or the other approach, we suggest that problems and the introduction of constraints may be more or less amenable to either approach at a specific time.
Large Language Models and the Legacy System

&lt;p&gt;We describe a general technique to create an NLP interface to legacy systems by applying large language models. Usability of the legacy system is increased while the problem of hallucination with LLM is avoided. &lt;/p&gt;
Hand Gesture Recognition and Cursor Control

Abstract: Convolutional neural network in this process to overcome the issue, use the network AutoGesNet for the gesture recognition task that creating effectiveneural network architecture is challenging. To be more precise, we first combine and preprocess three sets of gesture recognition data. The AutoGesNet search space and general architecture are then designed. Additionally, we employ transfer learning and reinforcement learning techniques to automatically create the intricate AutoGesNet architecture. Finally, the searched neural network is adjusted and retrained for two alternative input sizes. The retrained model performs accurately on both our data set and the NUS Hand Posture Dataset II, according to experiments. network that performs wellin terms of recognition accuracy. We will contrast andmerge AutoGesNet in further work
A Conceptual Insight Into Achieving Interoperability Between Heterogeneous Blockchain Enabled Interconnected Smart Microgrids

&lt;p&gt;Blockchain technology (BCT) has emerged as a game-changer for many industries since its inception in 2008. Its application in the energy industry as blockchain enabled interconnected smart microgrids (BSMG) is on the rise as it can execute energy trading, automate the market operations, manage the grid, and facilitate real-time payments. With the increase in usage of BSMGs, different types of BCT will emerge, making the system heterogeneous in nature. BCT is also limited currently due to its scalability and low transaction rate. Interoperability between heterogeneous BSMGs can counteract the drawbacks and improve the functionality and, thereby, adoption of BCT in energy. This paper recognises the need for interoperability and thoroughly reviews the different methods of interoperability that currently exist (i.e., notary mechanism, relay or side chains, hashed time-locked contracts, and blockchain routers). Two relay mechanisms - Polkadot and Cosmos with Inter Blockchain Communication Protocol (IBC) are reviewed further to determine the usability of the protocols. Finally, a conceptual architecture of interconnection of heterogeneous BSMGs is proposed. Conceptual solution to connecting Ethereum and Hyperledger Fabric to the Cosmos Hub through IBC is explored. While interoperability between heterogeneous users is addressed in Decentralized Finance (DeFi), it has not yet been addressed in energy. A conceptual solution is provided for this research gap for the first time in energy domain. &lt;/p&gt;
Extending Implications of Ambient-Latent Space Approach with Lagrange Multiplier Method

&lt;p&gt;Recent study approach with Ambient-Latent Space resembles a new possibility of simulating dynamics with more accuracy. This paper aims to suggest idea also by adding temporary dimension(like in case of SVM) in learning given dynamics by optimization in additional to the recent study.&lt;/p&gt;
Malaria Survey in Rural Villages of Anger Gute Area of Gida Ayana District, Western Ethiopia

Background: Active malaria detection is required, for efficient identification of malaria cases or clusters of cases to eliminate malaria. Objective of this study was to explore prevalence of asymptomatic parasite carriage and active malaria cases among rural residents of Anger Gute area. Methods: Community based cross-sectional survey was done among 413 individuals of two villages of Anger Gute area from 14 to 29, August 2020. Malaria infection was screened using RDT from finger-prick blood specimens. Data analysis was performed using SPSS version 20.0 and descriptive statistics was done using logistic regression. P values of less or equal to 0.05 were considered significant. Result: prevalence of Plasmodium infection was 2.7 (11/413) as determined by RDT. Of these, 91% (10/11) were infected with Plasmodium falciparum and 9% (1/11) with Plasmodium vivax. 98.1% of study participants were asymptomatic upon clinical examination of malaria. Prevalence of malaria among asymptomatic individuals was 1.73% (7/405). 4 active malaria cases were detected from 8 febrile individuals (body temperature≥37.5°C). Malaria parasite infection was not associated with area of residence, age categories and ethnic group of study participants (P>0.05). But Plasmodium infection were more detected among males as compared with female (AOR=23.6, P=0.041). Out of total 413 respondents, 254(62.7%) had got malaria before this survey and majority of them did not know the type of malaria they diseased. 83.3% of respondents sleep under LLINs the night before the survey. Conclusion and Recommendation: Overall prevalence of Plasmodium infection in this survey was 2.7%. Prevalence of malaria parasite among asymptomatic individuals was 1.73%. 4 active malaria cases were detected from 8 febrile individuals during community-based survey. Malaria parasites were more detected among males than females. 62.7% of respondents had got malaria before this survey. Molecular Techniques should be used to detect low density infections in this low transmission settings to accurately know prevalence of malaria parasite.
USE OF SIMILARITY METRICS IN ROBUST TIME DELAY ESTIMATION

This paper addresses the task of time delay and direction of arrival estimation for a source of the wideband signal using two sensors with fixed displacement. The peculiarity of the task statement is that a limited time of signal observation is supposed and additive noise is assumed non-Gaussian with a heavy-tail distribution. This leads to a high probability of abnormal estimates for the conventional signal processing method based on cross-correlation. To decrease this probability, it is proposed to reformulate the task of cross-correlation processing to the task of similarity estimation between two data arrays. This allows using different similarity metrics, particularly those that have less sensitivity to outliers in data (impulse noise), and, thus, provide better robustness for non-Gaussian environments typical for several applications of time delay estimation. More than ten different similarity metrics are considered for the model of the symmetric α-stable distribution describing noise properties. It is shown that some metrics including cosine distance, Hellinger, and some others are able to provide sufficiently better accuracy of time delay estimation both in the sense of less RMSE of normal estimates and probability of abnormal estimates for typical values of α and a wide range of γ values for symmetric α-stable distribution.
Digital culture in health facilities

This article examines digital culture as a special environment that has a formative influence on society. Interactive behavior and hypertextuality in digital culture form clip perception, prompting the emergence of new patterns of thinking. The result of this phenomenon may be a deep gap between cultural codes.
Test Case Design Of Security Threats Through State Machine OCL

Software testing is one activity for Software Quality Assurance (SQA). One way to test is through Black box test cases at design level. Since UML is a de-facto design language and is one of the most used design language now a day. Therefore, there is need to design black box test cases using UML behavioral diagrams. Object Constraint Language (OCL) is a formal language to write constraints on UML diagrams as it is unambiguous. Although test cases against robustness have been designed through OCL expressions but no test cases as yet have been designed against security specific authentication, access control and availability. Specification and testing of security specific authentication, access Control and availability through OCL. An experiment is performed with a hypothesis ‘if Security Specific Authentication, Access Control and Availability is specified through OCL in state diagram then Test cases can be designed’. We have specifiedsecurity in OCL then same OCL expressions are used to model security in UML state diagram. Furthermore, mutation testing is performed on OCL expressions. Then ECP is done using same extracted mutants. Security specific authentication, access control and availability is specified in OCL and then test cases are designed using a black box testing technique Equivalence Class Partitioning. Hypothesis results shows that one can design test cases through OCL. This thesis shows that Specification and Testing of Security specific authentication, access control and availability through OCL.
Techy Tennis–A Game Beyond Reality

The concept is to create a game based on augmented reality and use object tracking as the primary function for recognizing objects using a camera. The key goal is to design an atmosphere that not only satisfies a person's desire to play video games but also lowers their stress levels in a manner that is both cost-effective and makes less use of flashy devices and cutting-edge technology. The environment produced in this way will use a camera that can identify objects and carry out a series of activities that have been preset according to their functions.
Analysis of modern tools for penetration testing

Penetration testing is a security audit performed by an organization in which an expert attempts to find, penetrate, and exploit weaknesses in an organization's computer system or networks. The main goal is to find any potential weakness. It also helps organizations maintain and adhere to established standards for protecting the privacy of their customers. The article explores software tools that can be used to perform penetration testing.
Cognitive Mapping and Framing Bias on Decision Making

The purpose of this study is to test and provide empirical evidence regarding causal cognitive mapping techniques in reducing framing bias in decision making. In this study, the bias that occurs can be measured through the risk preferences of decision makers, namely the tendency to be risk averse or risk seeking. This study used a 2x2 between subjects’ experimental design. The results of the research show that both hypotheses are supported. When information is presented in positive framing, the decision maker's risk preference tends to be risk averse, whereas if information is presented in negative framing, the decision maker's risk preference tends to be risk seeking. The study shows that the causal cognitive mapping technique's ability to reduce or reduce bias due to framing (information framing) of available decision alternatives. The implication is that decision makers should think harder in processing the available information. Causal cognitive mapping technique can assist decision makers in connecting various factors that are considered relevant in a problem.
Flash Damage Expert System Using the Dempster Shafer Method

The rapid development of technology makes it easy to solve problems and get satisfactory results for the lives of many people. An expert system is a branch of artificial intelligence that is designed by embedding the knowledge of an expert in a computer. Expert systems can replace the role of an expert by using a computer that can provide definite solutions like an expert. In writing this thesis it is explained how a computer can detect damage from a flashdisk and the solution to the resulting damage like an expert using the Dempster Shafer calculation method. This expert system program is implemented using the Microsoft Visual Basic 2010 programming language with SQL Server 2008 database as the storage medium.
“Big Data” of the Digital Archive: A Dialogue with a Raster Manuscript

The article reflects the current trends in working with the digital heritage of Russian literature, examines the process of forming virtual archives as a gradual accumulation of the “big data” of scientific research, i. e. unrecognized information array of raster documents containing tens of thousands of images. The research analyzes the specifics of scientific work in the field of ego-documentary heritage that arose at the turn of the 20th – 21st centuries (a corpus of diary entries, workbooks, notebooks, correspondence), the principles of publication and modern standards of digitization of archival heritage. The study and practicing of the three most promising virtual resources on the history of Russian literature of the mid-19th – first half of the 20th centuries allows to formulate specific tasks and methods of visualization of a large corpus of raster images of archival documents, as well as previously untapped possibilities of search engine automation. Much attention is paid to the transition from the graphical elements of the raster image of the manuscript to semantic ones, which allow the use of data mining elements for an unrecognized data array.
The Impact of Bilingual Education on Children's Language Development

Bilingual education on children's language development is a heated topic in the area of second language acuquistion. This paper reviews the definition of bilingual monolingual children and the definition of trilingual hyperlingual and dialect for bilingualism.By analyzing their impact on bilingual children, the researchers tried to find out which aspect has the greatest impact on bilingual children In this study, the main influences were divided into positive and negative feedback from three aspects: school, family, and government. The researchers analyzed the impact of these aspects and some factors that may affect children's language development.Also it is important to analyze how to get children interested in language learning.This paper contributes to the teachers and parents who want to know about the bilingual education.Inspire parents to choose their childrens education method.
The Influence of Emerging Media and Mainstream Media on Audience Communication

In the modern era, there are many channels for information dissemination, and when significant events necessitate credible and authoritative media to become the dominant source of social information, in-depth analysis can only serve to increase the influence of media. As a result, the process of information transmission and reception can result in little derogation. Under this context, this paper studies the influence of emerging media and mainstream media on audience communication by describing the variations between news and poetry text genres, elucidating listeners own accepting flaws with a contrast of common language and official media, and highlighting the value of official media for legal communication and its veracity. In conclusion, by enhancing the accuracy of the content and actively seeking the information they require, communication with new media typically results in little message degradation. Strong communication has a favorable impact on audience awareness, which leads to societal transformation. News and opinions are disseminated and guided by the media, so it is important to describe the influencing mechanism of media in detail utilizing communication effectiveness theory and the findings of media effectiveness research.
Cyberbullying on Weibo and the Ineffectiveness of Its Anti-cyberbullying Policies in Prevention and Regulation of CyberbullyingInvestigation into Liu Xuezhous Case

Social media platforms policies aim to restrict cyberbullying. However, there is little study on whether these policies are effective. The primary aim of this paper is to investigate the effectiveness of the Weibo policy between 2012-2022 against cyberbullying and find a way to strengthen its effectiveness. We studied the Case of Liu Xuezhou, which is a typical example of cyberbullying. By studying the case and analyzing how relevant policies of Weibo worked or failed in preventing the case, this research found that although Weibo does have a policy to prevent cyberbullying, they are delayed and ineffective. Thus, when netizens encounter cyberbullying, the policies against cyber violence have little power in preventing its happening or help reducing the harm suffered by victims. Weibo, as one of the biggest social media platforms in China, should strengthen the prevention and regulation of cyberbullying by increasing the effectiveness of these policies' terminology and enforcement. Meanwhile, netizens should improve their ability to distinguish between right and wrong and participate in the prevention of cyberbullying themselves.
Current Situation Analysis of Alcohol Use Disorder within College students

Because the ratio of college patients with alcohol use disorders increased in recent years and college students alcohol abuse becomes a serious problem affecting their daily life, the essay tries to explore the causes and consequences of college students heavy drinking. Based on a bunch of previous research and experiments, the paper focuses on the current situation of alcohol abuse among college students and tries to analyze potential environmental and personal factors that lead to college students' alcohol use disorder. The transition period to college, peer influence and selection, perceived norms, and parental influence can influence college students attitudes toward alcohol use differently. Students internal drinking motives and previous alcohol use also affect their drinking behaviors after college. After analyzing external and internal inducing factors related to heavy drinking among college students, the paper summarizes some general and specific short-term and long-term effects associated with college students binge drinking and provides some effective treatments for alcohol use disorder.