Formula For Rank Research Articles

Some New Algebraic Method Developments in the Characterization of Matrix Equalities

Algebraic expressions and equalities can be constructed arbitrarily in a given algebraic framework according to the operational rules provided, and thus it is a prominent and necessary task in mathematics and applications to construct, classify, and characterize various simple general algebraic expressions and equalities. As an update to this prominent topic in matrix algebra, this article reviews and improves upon the well-known block matrix methodology and matrix rank methodology in the construction and characterization of matrix equalities. We present a collection of fundamental and useful formulas for calculating the ranks of a wide range of block matrices and then derive from these rank formulas various valuable consequences. In particular, we present several groups of equivalent conditions in the characterizations of the Hermitian matrix, the skew-Hermitian matrix, the normal matrix, etc.

On the rank of two-dimensional simplicial distributions

Simplicial distributions provide a framework for studying quantum contextuality, a generalization of Bell’s non-locality. Understanding extremal simplicial distributions is of fundamental importance with applications to quantum computing. We introduce a rank formula for twisted simplicial distributions defined for 2-dimensional measurement spaces and provide a systematic approach for describing extremal distributions.

HUBUNGAN POLA KOMUNIKASI PENYULUH PERTANIAN DENGAN PENINGKATAN PENGETAHUAN PETANI SAYURAN DI KELURAHAN TOBUUHA KECAMATAN PUUWATU KOTA KENDARI

The process of delivering information carried out by agricultural extension workers to vegetable farmers requires an appropriate communication pattern to increase the level of knowledge of target farmers. The purpose of this study was to determine the relationship between communication patterns of agricultural extension workers and vegetable farmers in Tobuuha Village. The study population consisted of all vegetable farmers in Tobuuha Village, which amounted to 20 farmers and one field agricultural extension worker. The research sample was determined by the census method, resulting in a sample size of 21 individuals. Data were collected through survey techniques, interviews, and the use of documentation, with the assistance of media in the form of questionnaires. This study is a quantitative research study. The data were processed using descriptive analysis through the use of the class interval formula and correlation analysis through the Spearman Rank formula, with the help of SPSS Software Version 26. The research findings indicate that the communication patterns of agricultural extension workers with vegetable farmers in Tobuuha Village encompass one-way, two-way, and multi-directional communication patterns. One-way communication patterns and multi-way communication patterns are classified as medium, while two-way communication patterns are classified as high. The level of knowledge of vegetable farmers is classified as medium based on indicators of understanding, application, and analysis. While the level of knowledge of vegetable farmers based on indicators of knowing is in the low category, the relationship between communication patterns of agricultural extension workers and the level of knowledge of vegetable farmers is statistically significant (0.046) and positive (0.691). This indicates that the more effective the communication patterns employed by agricultural extension workers, the greater the likelihood of increased knowledge among vegetable farmers.

Computational prediction of new therapeutic effects of probiotics

Probiotics are living microorganisms that provide health benefits to their hosts, potentially aiding in the treatment or prevention of various diseases, including diarrhea, irritable bowel syndrome, ulcerative colitis, and Crohn’s disease. Motivated by successful applications of link prediction in medical and biological networks, we applied link prediction to the probiotic-disease network to identify unreported relations. Using data from the Probio database and International Classification of Diseases-10th Revision (ICD-10) resources, we constructed a bipartite graph focused on the relationship between probiotics and diseases. We applied customized link prediction algorithms for this bipartite network, including common neighbors, Jaccard coefficient, and Adamic/Adar ranking formulas. We evaluated the results using Area under the Curve (AUC) and precision metrics. Our analysis revealed that common neighbors outperformed the other methods, with an AUC of 0.96 and precision of 0.6, indicating that basic formulas can predict at least six out of ten probable relations correctly. To support our findings, we conducted an exact search of the top 20 predictions and found six confirming papers on Google Scholar and Science Direct. Evidence suggests that Lactobacillus jensenii may provide prophylactic and therapeutic benefits for gastrointestinal diseases and that Lactobacillus acidophilus may have potential activity against urologic and female genital illnesses. Further investigation of other predictions through additional preclinical and clinical studies is recommended. Future research may focus on deploying more powerful link prediction algorithms to achieve better and more accurate results.

Forum Text Processing and Summarization

Frequently Asked Questions (FAQs) are extensively studied in general domains like the medical field, but such frameworks are lacking in domains such as software engineering and open-source communities. This research aims to bridge this gap by establishing the foundations of an automated FAQ Generation and Retrieval framework specifically tailored to the software engineering domain. The framework involves analyzing, ranking, performing sentiment analysis, and summarization techniques on open forums like StackOverflow and GitHub issues. A corpus of Stack Overflow post data is collected to evaluate the proposed framework and the selected models. Integrating state-of-the-art models of string-matching models, sentiment analysis models, summarization models, and the proprietary ranking formula proposed in this paper forms a robust Automatic FAQ Generation and Retrieval framework to facilitate developers' work. String matching, sentiment analysis, and summarization models are evaluated, and F1 scores of 71.31%, 74.90%, and 53.4% were achieved. Given the subjective nature of evaluations in this context, a human review is used to further validate the effectiveness of the overall framework, with assessments made on relevancy, preferred ranking, and preferred summarization. Future work includes improving summarization models by incorporating text classification and summarizing them individually (Kou et al, 2023), as well as proposing feedback loop systems based on human reinforcement learning. Furthermore, efforts will be made to optimize the framework by utilizing knowledge graphs for dimension reduction, enabling it to handle larger corpora effectively

The Relationship Between Parental Support and Learning Outcomes For Social Studies Package B At SPNF SKB Bukittinggi City

The background to this research is the low social studies learning outcomes of residents studying package B. The aim of this research is to see a picture of the family environment of study residents, see a picture of social studies learning outcomes of residents studying package B, and see a picture of social studies learning outcomes of residents studying package B. The relationship between the family environment and Social Sciences learning results package B at SPNF SKB Bukittinggi City. This research uses a correlational quantitative approach. The population of this study was residents studying package b at SPNF SKB Bukittinggi City, totaling 45 people. Meanwhile, samples were taken from 60% of the population, namely 27 people, using a cluster random sampling technique. Data collection techniques using questionnaires. Data analysis techniques using percentage formulas and Spearman rank formulas. The research results show (1) the family environment is still not good, (2) student learning outcomes are still relatively low, (3) there is a relationship between the family environment and social studies learning outcomes package b, this relationship is declared significant because it is categorized as very strong. It is recommended that parents provide support in education in the family environment in order to optimize student learning outcomes. The SPNF SKB Institute is able to provide motivational support to learning residents and be creative in using learning media so that learning enthusiasm can increase among learning residents. Future researchers can identify characteristics or other variables that have not been examined in this research for further follow-up. Keywords: Family Environment, Learning Outcomes

Comparison of predictors under constrained general linear model and its future observations

. This study deals with some basic inference problems about future observations in a general linear model (GLM) with linear parameter constraints, known as a constrained general linear model (CGLM). Combining the CGLM and its future observations, the author turns the model into a reparameterized form. Using some quadratic matrix optimization methods, the author derives analytical formulas for calculating the best linear unbiased predictors (BLUPs) of all unknown parameter matrices under a CGLM and its future observations. In particular, the author next gives a comprehensive search on the comparison of dispersion matrices of BLUPs of unknown vectors by establishing various equalities and inequalities for dispersion matrices of BLUPs under the model by using elementary block matrix operations and some formulas of rank and inertia of block matrices.

Improving Ranking Using Hybrid Custom Embedding Models on Persian Web

Ranking plays a crucial role in information retrieval systems, especially in the context of web search engines. This article presents a new ranking approach that utilizes semantic vectors and embedding models to enhance the accuracy of web document ranking, particularly in languages with complex structures like Persian. The article utilizes two real-world datasets, one obtained through web crawling to collect a large-scale Persian web corpus, and the other consisting of real user queries and web documents labeled with a relevancy score. The datasets are used to train embedding models using a combination of static Word2Vec and dynamic BERT algorithms. The proposed hybrid ranking formula incorporates these semantic vectors and presents a novel approach to document ranking called HybridMaxSim. Experiments conducted indicate that the HybridMaxSim formula is effective in enhancing the precision of web document ranking up to 0.87 according to the nDCG criterion.

The rank of the numbers of the A-function

The famous Indian mathematician D. Kaprekar came up with a method for obtaining new numbers K(n) = n + S(n) where S(n) is the sum of the digits of a number n in decimal notation. Following D. Kaprekar, the paper presents a new way to obtain numbers It is proved that the function A(n) is non-decreasing. Similarly to the function K(n), the concepts of a-generated and a-self-generated numbers are defined. The rank of numbers is investigated and it is proved that the rank function is non-decreasing. The rank formula for the numbers n = 10S

SUBSTANTIATION OF CONCEPTS OF SUBGRADE’S STRENTHENING IN UKRAINE AND THE EUROPEAN UNION

Purpose. Substantiating the concepts of subgrade’s strengthening in Ukraine and the European Union. In the work, based on the experience gained in the field of increasing the strength and stability of objects constructed from the soil, based on the ranking of parameters, the hypothesis about the greatest effectiveness of vertical strengthening elements, unlike all others, in the case of transition to a combined track (1520/1435 mm) is proven. Methodology. The options for strengthening the subgrade with geotextile or geogrid, as well as a rigid layer, are considered, as regulated by CP-0204 "Rules for the arrangement of the main subgrade site during major repair and modernization of the track". Three concepts of strengthening developed and implemented in the European Union with the help of: 1) geosynthetic materials; 2) vertical piles or micropiles; 3) combinations of geosynthetic materials with piles (Geosynthetic-Reinforced-Pile-Supported) are analyzed. Findings. The ranking of the methods of strengthening the subgrade was carried out according to positive and negative parameters that characterize the situation of placement of reinforcement elements in the soil matrix. Reinforcement parameters are divided into positive (reduction of horizontal and vertical deformations) and negative (technology parameters). It was determined that the maximum value of the positive impact on the reduction of vertical deformations is provided by options of vertical piles or micropiles created on the basis of Boring and Mixing Technology or Jet-grouting. Originality. For the first time, on the basis of the ranking formulas for positive and negative parameters, the justification of the concepts of subgrade’s strengthening in Ukraine and the European Union was performed. Practical value. Any method of strengthening can be ranked before its practical implementation. That is, its efficiency and rationality can be determined during implementation in specific situations of railway operation, with subgrade that needs strengthening.

UniLoc: Unified Fault Localization of Continuous Integration Failures

Continuous integration (CI) practices encourage developers to frequently integrate code into a shared repository. Each integration is validated by automatic build and testing such that errors are revealed as early as possible. When CI failures or integration errors are reported, existing techniques are insufficient to automatically locate the root causes for two reasons. First, a CI failure may be triggered by faults in source code and/or build scripts, whereas current approaches consider only source code. Second, a tentative integration can fail because of build failures and/or test failures, whereas existing tools focus on test failures only. This article presents UniLoc, the first unified technique to localize faults in both source code and build scripts given a CI failure log, without assuming the failure’s location (source code or build scripts) and nature (a test failure or not). Adopting the information retrieval (IR) strategy, UniLoc locates buggy files by treating source code and build scripts as documents to search and by considering build logs as search queries. However, instead of naïvely applying an off-the-shelf IR technique to these software artifacts, for more accurate fault localization, UniLoc applies various domain-specific heuristics to optimize the search queries, search space, and ranking formulas. To evaluate UniLoc, we gathered 700 CI failure fixes in 72 open source projects that are built with Gradle. UniLoc could effectively locate bugs with the average mean reciprocal rank value as 0.49, mean average precision value as 0.36, and normalized discounted cumulative gain value as 0.54. UniLoc outperformed the state-of-the-art IR-based tool BLUiR and Locus. UniLoc has the potential to help developers diagnose root causes for CI failures more accurately and efficiently.

A Decision-Making Model for Professional Drivers Selection: A Hybridized Fuzzy–AROMAN–Fuller Approach

Professional drivers play a crucial role in many businesses and the lives of people. They are responsible for transferring people and goods between distant points, enabling safe and efficient flows. The road traffic death rate is from 8.3 to 27.5 per 100,000 inhabitants in the countries globally. Because professional drivers spend a significant amount of time on the road, their appropriate selection may contribute to general traffic safety. In addition, an adequate selection of candidates significantly impacts the financial costs of the employing company. However, the recruitment procedure is a very complex task where multiple criteria should be considered. By its nature, this is a typical multi-criteria decision-making problem. The purpose of this paper is twofold: to contribute to the methodological, as well as to the professional field. Considering the professional, we propose a decision-making tool in the procedure of professional driver selection. There are several methodological contributions. By reviewing the literature, we identified 14 criteria for candidate selection. In the proposed model, by using expert opinion and implementing DEMATEL and Fuller’s pairwise comparisons, we ranked these criteria and determined the seven most important for further calculation procedure. Here, we introduced an original approach for measuring the reliability of obtained answers. Then, to rank the candidates, the fuzzy AROMAN approach is applied for the first time in the literature. The input data were obtained in the form of a survey, where the experts evaluated the importance of criteria and their interrelation. We used MS Excel and MATLAB for data processing. An additional methodological contribution of this study is an advancement of the AROMAN method by the proposal of an algorithm for the calculation of parameter λ used in the final ranking formula. To illustrate the applicability of the proposed model, a case study is provided. Based on the results, we can conclude that the new methodological approaches can be successfully used in the procedure of professional driver selection, as well as in solving other multi-criteria decision-making problems.

An inequality for non-microstates free entropy dimension for crossed products by finite abelian groups

For certain generating sets of the subfactor pair M\subset M\rtimes G where G is a finite abelian group we prove an approximate inequality between their non-microstates free entropy dimension, resembling the Schreier formula for ranks of finite index subgroups of free groups. As an application, we give bounds on free entropy dimension of generating sets of crossed products of the form M\rtimes(\mathbb{Z}/2\mathbb{Z})^{\oplus\infty} for a large class of algebras M .

Hubungan Self Efficacy Dengan Pelaksanaan Mobilisasi Dini Pasien Apendektomi Di Ruang Bedah RSUD H. Boejasin Pelaihari

One of the nursing interventions in recovery and healing the appendectomy wounds is early mobilization exercises. One of the factors that influence the success of early mobilization is to increase self-efficacy. This research want to determine the correlation of self-efficacy and early mobilization among appendectomy patients in surgery room at H. Boejasin Pelaihari Hospital. The study conducted by utilizing quantitative research with cross sectional approach. There are 20 respondents involved in the study that selected using accidental sampling. The analysis use an spearman rank formula to determine the correlation between two variables. The results showed that the self-efficacy of patients after appendectomy. There are 12 respondents (60%) showed their self-efficacy level in moderate level. 11 respondents (55%) had a good mobilization exercise. Analysis of Spearman Rank correlation found that there was a strong significant relationship between self-efficacy and mobilization among appendectomy patient where the value of p = 0.000.

Ranking researchers: Evidence from Indonesia

In the span of three years, Indonesia went from being the second worst to the top producer of scientific journal articles in Southeast Asia. We investigate whether a transparent system of ranking every single researcher in the country based on publications and citations (SINTA) contributed to this turnaround. Using panel data from over 200,000 Indonesian researchers (and comparing to researchers from Thailand and the Philippines), we show that the implementation of SINTA coincides with changes in the production of publications by Indonesian researchers consistent with the weights used in the ranking formula. Although we see modest improvements in publication rates in top-ranked journals, 62 % of the observed increase in total publications is from conference proceedings. Because SINTA was launched around the same time as other policies that focused on increasing publications, isolating the precise impact of SINTA remains challenging. Nevertheless, after accounting for such policies, our results imply that a ranking and evaluation system for researchers can contribute to overall improvements in scientific capacity in low- and middle-income countries.

Optimised U-Net for Land Use–Land Cover Classification Using Aerial Photography

Convolutional Neural Networks (CNN) consist of various hyper-parameters which need to be specified or can be altered when defining a deep learning architecture. There are numerous studies which have tested different types of networks (e.g. U-Net, DeepLabv3+) or created new architectures, benchmarked against well-known test datasets. However, there is a lack of real-world mapping applications demonstrating the effects of changing network hyper-parameters on model performance for land use and land cover (LULC) semantic segmentation. In this paper, we analysed the effects on training time and classification accuracy by altering parameters such as the number of initial convolutional filters, kernel size, network depth, kernel initialiser and activation functions, loss and loss optimiser functions, and learning rate. We achieved this using a well-known top performing architecture, the U-Net, in conjunction with LULC training data and two multispectral aerial images from North Queensland, Australia. A 2018 image was used to train and test CNN models with different parameters and a 2015 image was used for assessing the optimised parameters. We found more complex models with a larger number of filters and larger kernel size produce classifications of higher accuracy but take longer to train. Using an accuracy-time ranking formula, we found using 56 initial filters with kernel size of 5 × 5 provide the best compromise between training time and accuracy. When fully training a model using these parameters and testing on the 2015 image, we achieved a kappa score of 0.84. This compares to the original U-Net parameters which achieved a kappa score of 0.73.

Looking back to inform the future: a review of published paramedicine research

ObjectiveParamedicine has evolved in ways that may outpace the science informing these changes. Examining the scholarly pursuits of paramedicine may provide insights into the historical academic focus, which may inform future endeavors and evolution of paramedicine. The objective of this study was to explore the existing discourse in paramedicine research to reflect on the academic pursuits of this community.MethodsWe searched Medline, Embase, CINAHL, Google Scholar and Web of Science from January, 2006 to April, 2019. We further refined the yield using a ranking formula that prioritized journals most relevant to paramedicine, then sampled randomly in two-year clusters for full text review. We extracted literature type, study topic and context, then used elements of qualitative content, thematic, and discourse analysis to further describe the sample.ResultsThe initial search yielded 99,124 citations, leaving 54,638 after removing duplicates and 7084 relevant articles from nine journals after ranking. Subsequently, 2058 articles were included for topic categorization, and 241 papers were included for full text analysis after random sampling. Overall, this literature reveals: 1) a relatively narrow topic focus, given the majority of research has concentrated on general operational activities and specific clinical conditions and interventions (e.g., resuscitation, airway management, etc.); 2) a limited methodological (and possibly philosophical) focus, given that most were observational studies (e.g., cohort, case control, and case series) or editorial/commentary; 3) a variety of observed trajectories of academic attention, indicating where the evolution of paramedicine is evident, areas where scope of practice is uncertain, and areas that aim to improve skills historically considered core to paramedic clinical practice.ConclusionsIncluded articles suggest a relatively narrow topic focus, a limited methodological focus, and observed trajectories of academic attention indicating where research pursuits and priorities are shifting. We have highlighted that the academic focus may require an alignment with aspirational and direction setting documents aimed at developing paramedicine. This review may be a snapshot of scholarly activity that reflects a young medically directed profession and systems focusing on a few high acuity conditions, with aspirations of professional autonomy contributing to the health and social well-being of communities.

Code smell prioritization in object‐oriented software systems: A systematic literature review

AbstractCode smells indicate poor design and imperfection in coding style. They increase maintenance costs and degrade software quality. Detecting and mitigating these code smells reduce the effects of flaws present in the software design. However, to save time and effort, it is a good practice to prioritize critical code smells and resolve them first. There have been various empirical studies on code smell prioritization in the last decades. Although the research community has been continuously working on the prioritization of code smells, yet a systematic mapping of all these studies would provide a panorama of research work. With this motivation, we selected 39 primary studies published between May 2011 and May 2022 and classified them based on seven factors: (i) code smells, (ii) factors, (iii) evaluation techniques, (iv) tools, (v) ranking formulas, (vi) data sets used, and (vii) measurements used for validating the research work. This paper aims to outline and discuss the prioritization procedure for code smells in object‐oriented software systems. The issues and recommendations for every question act as input for the researchers and industrialists for further research. Some issues for further investigation are less coverage of architecture smells, limited ranking formulas, lack of automated evaluation techniques, and so forth.

Some algebraic properties on rough neutrosophic matrix and its application to multi-criteria decision-making

<abstract><p>Rough set theory is a method of information processing for database systems. The neutrosophic matrix is a generalization of the fuzzy matrix, especially in handling indeterminacy situations. The concept of matrix theory and its energy in the neutrosophic environment help to determine the value of the uncertain matrix. In this paper, we correlate the rough set theory with the neutrosophic matrix theory to introduce the rough neutrosophic matrix (RNM). In this structure, lower and upper approximation neutrosophic matrices are used to deal with uncertain situations. We demonstrate that the given matrix plays a different role in decision-making situations and defined the proposed matrix's determinant, adjoint, algebraic properties and operations. Finally, derived the ranking function for a rough neutrosophic matrix's energy. The new multi-criteria decision-making (MCDM) approach was presented with the ranking formula, which was utilized to rank the alternatives, and numerical examples were provided to show how the proposed matrix and its energy could be applied to an MCDM problem.</p></abstract>

Pemanfaatan Internet Terhadap Kinerja Penyuluh Pertanian Padi Sawah Di Kecamatan Angata Kabupaten Konawe Selatan

This study aims to determine the use of the internet by agricultural instructors to improve the performance of rice agricultural instructors in Angata District, South Konawe Regency. This research was conducted in Angata District in July-August 2021 and used quantitative research methods. The results of this study indicate that the relationship between the use of the internet and the performance improvement of agricultural instructors in Angata sub-district has a significant relationship which is calculated using the Spearman Rank formula. This can be seen from the high use of the internet by agricultural extension workers which is calculated using the interval analysis formula, while the performance of agricultural instructors is in the good category which is calculated based on the Minister of Agriculture of the Republic of Indonesia No. 91 of 2013 concerning Guidelines for Evaluation of Agricultural Extension Performance. Based on the results of the Spearman rank analysis, the elements of internet use consisting of Situation Analysis, Improving Knowledge, Problem Awareness, Decision Making, and Motivation and Skills have a significant relationship with the performance of agricultural instructors in Angata sub-district.