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Computational thinking is a way of thinking for problem solving and is one of the basic skills of the 21st century that is very important to be applied in science learning as an effort to prepare for disruption in the industrial era 4.0 and society 5.0. This study aims to find a new method that has proven its effectiveness to apply problem solving skills. The Research and Development (R and D) method with the ADDIE model (Analysis, Design, Develop, Implementation and Evaluation) was carried out to develop a Problem Project Based Learning (PPjBL) model with a Computational Thinking (CT) approach based on CoSpaces-Edu Paper Cube Augmented Reality. This research has produced a product in the form of a Problem Project Based Learning (PPjBL) model with a Computational Thinking (CT) approach based on CoSpaces-Edu Paper Cube Augmented Reality which has been validated by experts on very feasible and effective criteria to be applied as a science learning design. [ABSTRACT FROM AUTHOR]

Nowadays, there are numerous and wide variety of online learning platforms (OLP) available for students and educators. In order to make the online learning process run smoothly, educators need to be smart in choosing a good medium to use. Many factors should be considered concurrently during decision-making processes. As a result, Multi Criteria Decision-Making (MCDM) method, which seeks to pick the best option from a set of choices, can help decision makers in making suitable and unambiguous judgments in difficult situations. To evaluate such difficulties, this paper combines neutrosophic set with the Best-Worst Method (BWM) approach. The neutrosophic set is important in solving indeterminacy problems and it is more suitable to solve real-world decision-making problems. Besides, in the MCDM problem, similarity measures may be used to describe how different alternatives vary and are similar to one another. However, it appears that the existing similarity measures seem to have a few major weaknesses and inherent problems, such as producing unreasonable results in some cases. Therefore, to cater such problems, this paper introduced a novel single-valued neutrosophic best-worst method, SVN-BWM approach with improved similarity measures of the single-valued neutrosophic set (SVNS) model into a case study of selecting the best online learning platforms based on educators' preferences. The data are collected from six decision makers (DM) among Mathematics lecturers of Universiti Teknologi MARA (UiTM) Shah Alam. From the findings, it is found that Google Meet is the most preferred online learning platform. [ABSTRACT FROM AUTHOR]

This paper addresses the traditional manual process of finding the optimal proportion of raw materials in foundries to obtain a melted charge of required constituent element composition. This iterative process is time-consuming and prone to human error and cost inefficiency. To solve this problem, the paper proposes a computer application that automates and optimizes the selection and proportion of raw materials using Python programming language and related libraries. The proposed application employs Pulp and Pandas libraries to optimize raw material selection and proportion and read excel files, respectively, and Pysimple GUI for user interface. The paper reports that the proposed application has achieved the objective of reducing time and cost in a test conducted for calculating different element compositions. It has reduced the time and cost by 88 % and 13 % respectively. Overall, this study contributes to the automation and digitalization of foundry processes, improving efficiency and reducing the risk of human error and cost inefficiency. [ABSTRACT FROM AUTHOR]

In this Paper the authors made work on the field of Health Sector that is Blood Analysis. Analysis of Blood is playing a very vital role as it is a parameter for detection of several kinds of diseases. Blood analysis speaks of a Frame that comprises of several ingredients which are essentially symbol for specific Blood disease. In the current work we are focused on finding out or predicting the Disease with a parameter of care. We made a utilization of various ML models for the prediction of disease. ML is a very popular approach nowadays for solving variety of problems and thus we made this approach useable for solving our problem. The data set on which we conducted experiment is a self-generated dataset. The Accuracy of the Model comes after performing Training on around 402 Samples. The Data Set used is a Physician Consulted Data Set. We in this paper will observe by means of graphs and figures several aspects of the Data Set and the ML approach. The Comparative Analysis of the approaches is discussed in the Conclusion Section. [ABSTRACT FROM AUTHOR]

Line following is one of the most efficient and reliable techniques for mobile robots in indoor environments. Line-following robots can autonomously detect and follow designed paths. It is now commonly applied in transportation and assistance. In related research, ensuring success in complex line following tracks (right angles, sharp curves) and complex optical environments has been a challenge. This paper designs a line following vehicle is designed based on a microcontroller (Raspberry Pi), Pi camera, and image processing by OpenCV. The image processing in line following includes the application of RGB, GRAY, and HSV color models. The vehicle movement is controlled by the PID algorithm. Besides, this system incorporates a template matching module. The template matching module uses binarization, polygon approximation, perspective transformation, Gaussian blur, and similarity comparison. The designed vehicle can complete the line following a designed map and successfully matches the correct templates. A discussion on the effect of light reflection is presented in this paper. This effect is improved by an extra algorithm in line following and expending the threshold of binarization. Also, this paper solves the problem that the vehicle may run out of the track in line following. The experiment shows a satisfying result. This study has potential implications for the design of line-following robots. [ABSTRACT FROM AUTHOR]

Maze problem have been a classic problem and have been studied for many times. It inspired lots of mathematics to create new algorithm. This paper's purpose is to summarize the main solutions of the maze problem and states the advantage and disadvantage of each method. In addition, it will also provide an algorithm for creating a random maze. There are variable solutions for solving the maze problem like BFS, DFS and other solutions like biological algorithm. BFS figures out the shortest way but often required lots of storage place, while DFS finds out a often longer way and required more time to get the answer. The essay will also provide a short introduction of biological algorithm and state their strength and weaknesses. The paper focus on the advantage and disadvantage of the maze solutions and summarize two ways of creating a maze. The maze problem has a significant status in the development of algorithm, and it will also influence the development of algorithm in the future. [ABSTRACT FROM AUTHOR]

Finite difference technique has become a numerical tool that makes complex become easier for engineers to problems. The complex problems are difficult to solve in the normal way. In this paper, the application of a finite difference technique is used to solve the consolidation problem in the case of radial drainage to determining the reduction in pore water stress. Usually the application is on soils that are near to impermeable, but in this paper it is applied to semi-permeable soils that are silty sand and fine sand. In semi-permeable soils, increased pore water pressure is very shorter. In this study is the time of radial drain is discussed. The data used is taken from Air Tawar, Padang. The results shows that the 90% of increased 100unit pore pressure can be completed within about 126 seconds. The results also indicates this method can be used to solve the problem of a sudden increase in pore water in the soil. [ABSTRACT FROM AUTHOR]

This paper examines the dynamics of the spread of the BA4 and BA5 variants of the COVID-19 virus in DKI Jakarta Province using the SIR Model. The parameters contained in the model are assumed to change over time according to the daily case empirical data. Based on the available data, the value of these parameters is estimated using FIR filtering and viewed as an optimization problem solved by the ridge regression algorithm. The model formed is used to predict the number of cases of the spread of COVID-19 for the next few months. The results obtained indicate that the model can produce stable output and it is predicted that COVID-19 for BA4 and BA5 variants will subside for the next few months. [ABSTRACT FROM AUTHOR]

Regression analysis is a statistical method that can explain the causal relationship between one response variable and one or more predictor variables. In general, the response variables are continuous data and normally distributed. However, in some applications, the response variable to be analyzed is in the form of discrete data, so the Poisson regression model is used, with the assumption that the mean and variance are the same or is called equal dispersion. However, in some real data, there is often over dispersion so the researchers model the count data with negative binomial regression. For cases with two (discrete) count variables that are correlated and require joint estimation, a bivariate count data regression model is used. One of them is the bivariate Poisson regression model which is widely used for correlated and equidistant bivariate data and for the case of over dispersion using a bivariate negative binomial model. In decreasing the combined distribution of the negative bivariate binomial distribution, several approaches can be used, in this paper we will show the results of the negative bivariate binomial distribution using the Cheon Method. With the alternative combined distribution of the negative bivariate binomial distribution, it can provide a more effective solution in solving problems in negative bivariate binomial regression. [ABSTRACT FROM AUTHOR]

An analysis of droughts in upper northern Thailand using the standard precipitation index (SPI) and actual precipitation index (API) is the main focus of this paper. In this study, the summer rainfall data from 1991 to 2022 from three rain gauge stations, namely Nan, Phrae, and Phayao, are used to analyze drought. The gamma, lognormal, and Weibull distributions are applied to find the appropriate distribution for summer rainfall data. According to the results, the Weibull distribution could be the best fit for the summer rainfall data from Phrae and Phayao gauge stations, and the gamma distribution could be the best fit for the summer rainfall data from the Nan gauge station. The results of the comparison between API and SPI showed that both methods were able to detect the same extreme drought occurrences, with extreme droughts occurring at Nan station in 2013, Phrae station in 2010, and Phayao station in 1992. Consequently, from the results of this study, it can be concluded that the API provided a few different analyses than the SPI for drought assessment. Moreover, the API is for easy interpretation and application of the results to drought classification and monitoring. Therefore, the API can be beneficial for planning and solving the drought problem in Upper Northern Thailand. [ABSTRACT FROM AUTHOR]

In this paper, we find a solution to the "digital twin" problem i.e., how to completely or exactly represent an object so that we can represent it digitally, where the model behaves and looks like the real-world object. This solution not only addresses the digital twin problem but also enables a generic representation of the Universe. Once we solve this problem we dwell into the phenomenon of "Being" and quantify the quality of "Being" or "Existence". A theory is provided as to how the Universe originated from Nothingness. Furthermore, we represent the Universe through a matrix-based equation. The interpretation of this equation explains how "Existence", creates, sustains, destroys, and controls the Universe. Additionally, the law of action and reaction is explained, or the natural consequence of any action performed by a subject. [ABSTRACT FROM AUTHOR]

Diabetes is one of the leading global health emergencies of the 21st century. The threatening side effects proves it to be a dangerous epidemic. This paper proposes a model to solve the problem in the existing system by comparing various data mining techniques in order to cluster and classify them. The paper studies a huge sample of diabetic patients common to diabetes and cardiovascular disorders. The method adopted is to cluster the data into three prior categories of high, medium and low clusters. Once clustered, optimum algorithmic technique is implemented to classify the data into mild and severe fragments in order to determine the chances of occurrence of a heart disorder due to the impact of diabetes. The aim is to implement an algorithm that can classify the data collected in order to infer whether or not a diabetic patient is prone to a heart disorder or not. [ABSTRACT FROM AUTHOR]

Variable selection is an important topic in linear regression analysis. In practice, a large number of predictors are usually introduced at the initial stage of model construction to mitigate potential model biases. On the other hand, to enhance the ability to predict and select important variables, regularization techniques are one of the great and proven methods for dealing with a large number of variables. In previous years, statisticians made great efforts in developing regularization procedures to solve the problems of V.S. These actions automatically facilitate Variable selection (V.S) by setting specific coefficients to zero and reducing coefficient estimates, providing useful estimates even if the model contains a large number of variables. In this paper, two methods of regularization were proposed to estimate and select the appropriate variables at the same time in the multiple regression model, which are the Standard Error Adjusted Adaptive LASSO (SEA-LASSO) and Minim ax Concave Penalty (MCP) method and selection of the best. The paper problem focuses on using the best regularization method that works on estimation and appropriate selection of important variables at the same time and addressing the problem of multiple linearity using the SEA-LASSO and MCP method. To get the real model. This paper aims to evaluate the performance of the method (SEA-LASSO) and method (MCP) in terms of the process of estimation and appropriate selection of important variables and treatment the problem multicollinearity through the simulation study. A simulation study was conducted to compare between these two methods, which included different cases of the factors and testing the effect of the levels of these factors on the performance of these two ways, as well as determining the value of the control parameter () and the criterion for selecting the best value for it and the basis on which to evaluate the performance of the two methods. The simulation results showed that (SEA-LASSO) method is superior to (MCP) method in terms of percentage of operation to reach the real model measured by (PCT), and it is also better in terms of mean squares error (MSE) because it achieves less (MSE) in most cases. A simulation study was used with the program R. [ABSTRACT FROM AUTHOR]

Due to the importance, security, confidentiality, privacy, and progress of information at present due to the development in the field of information technology, sharing this information (text, image, audio, video) has become a critical problem due to the exposure of this information to penetration by attacking parties, and to solve the problem of penetration, many technologies have appeared to protect This information (text, image, audio, video) is cryptography algorithms and information steganography techniques. Steganography is a science that maintains the confidentiality of information (text, image, audio, video) between two communicating parties (the sender and the receiver), and it is a science that studies the invisible communication of information. In this paper, the researcher reviewed the most important techniques of previous studies for the last six years, such as LSB, PVD, DFT, DWT, DCT, Masking & Filtering, Distortion, and Statistical. In the science of hiding information, and analyzing it in terms of technical domain, invisibility, capacity, and complexity, all of these techniques can hide this information from hostile attacks. In this paper, the evaluation criteria for hiding the information (text, image, audio, video) were reviewed in terms of imperceptibility, robustness, capacity, and security. Also, the most important applications of hiding techniques (text, image, audio, video) were reviewed in this paper. [ABSTRACT FROM AUTHOR]

The paper examines the application of systematic and risk-based approaches to problem solving in the agro-industrial complex, which generally prompted research in the field of various model-based methodologies. Of particular interest to this study is the Quality by Design initiative in the agro-industrial complex. Motivated by their need, this paper reports some of the contributions to analysing the existence and availability of the experimental plan. The analysis of the feasibility and adaptation of the nested sampling algorithm for the probabilistic characteristics of the design space is considered. There is described an initial adaptation of the nested sampling algorithm, common for large Bayesian calculations, for the probabilistic characterization of spatial design, which is a key work for practitioners in the agro-industrial complex. The choice-based approach has been found to be effective with the optimization approach, allowing practitioners to take advantage of the choice-based approach with other methods. A step-by-step technology is given for complex and one-time implementations of the original nested sample for spatial design, which further reduces the computational load, thereby allowing solutions of more complex problems. Design-centring methodology is shown as an alternative coding method for methodological choice, providing the practitioner with a convenient format for communicating with process operators. A particular attention is paid to several pronounced problems that arise in the special design of experiments when there are various levels of model uncertainty, which are often encountered in the early stages of model development. The paper presents the results of the study obtained by developing optimal experimental queries in the presence of restrictions. [ABSTRACT FROM AUTHOR]

It is a challenge to make robots move from one place to another on the shortest path and avoid obstacles at the same time, especially when there are some special conditions occur on the path. Reinforcement learning (RL) is widely used in training mobile robots to plan the shortest path, whereas people are facing sparse reward problem when using it. Hindsight experience replay (HER) is one of the great solutions to the sparse reward problem. It improves RL by making use of failed experience that may be ignored in RL. However, when applying HER, it's hard to avoid survivorship bias. Another method, unbiased sampling for hindsight experience replay (USHER) was proposed to solve this problem. By altering the loss function used to train the goal-conditioned Q-value network, USHER improves the original HER. It successfully realizes that solving the sparse reward problem while alleviating the survivorship bias. This paper is going to introduce the method of USHER and an experiment that evaluates its effectiveness. [ABSTRACT FROM AUTHOR]

A simple limit analysis modeling for masonry arches with innovative strengthening is proposed in this paper, where the arch ring is discretized by rigid blocks according to the real bond pattern and the reinforcement effect is modeled through updating the failure surface of the contact joints. Considering all the extra force resultants provided by the reinforcement layer, we have first derived the constraints for the new yield condition and flow rule, defining the failure surface after applying the strengthening, and the new limit analysis formulation with consideration of reinforcement effect is then given. Such modeling is also very convenient to incorporate with sequential linear programming to solve non-associated problems. Applying the proposed theory, collapse analysis of an FRP-reinforced arch in 2D is presented and the results predicted from associated and non-associated formulations are compared. The results show that when analyzing the arch with reinforcement, the associated limit analysis may overestimate the ultimate load, as well as produce an incorrect collapse mechanism. Therefore, it is necessary to employ the non-associated flow rule for an accurate prediction of the collapse performance of reinforced arches. [ABSTRACT FROM AUTHOR]

This paper examines the findings from research into an approach to solving optimization problems, in which the depen-dencies on diverse groups of parameters are of a different nature. A scheme has been proposed for choosing the problem parameters, which have a local effect on the objective function. It allows solving essentially multidimensional problems using the nested op-timization scheme. In this case, different optimization algorithms are used at differing nesting levels. The proposed approach has demonstrated its efficiency in solving several series of test problems. [ABSTRACT FROM AUTHOR]

In our research, we are focusing on the development of iterative algorithms for solving contact problems emerging in the analysis of steel structures bolt connections. Despite the project is focusing mainly on the development of efficient numerical algorithms, several supplementary problems have to be solved. In our research, we decided to utilize widely-used popular commercial software Ansys to provide the data for our algorithms implemented in Matlab as well as for the comparison of results. This paper presents experiences with our newly developed data interface. [ABSTRACT FROM AUTHOR]

In Handwritten Character Recognition (HCR), interest in feature extraction has been on the increase with the abundance of algorithms derived to increase the accuracy of classification. In this paper, a metaheuristic approach for feature extraction technique in HCR based on Crow Search Algorithm (CSA) was proposed. Freeman Chain Code (FCC) was used as data representation. The main problem in representing a character using FCC is that the results of the extractions depend on the starting points that affected the route length of chain code. To solve this problem, the metaheuristic approach via CSA was proposed to find the shortest route length and minimum computational time for HCR. The performance measurements of the proposed CS-FCC extraction algorithm are the route lengths and computation times. The experiments on the algorithms are performed based on the chain code representation derived from established previous works of Center of Excellence for Document Analysis and Recognition (CEDAR) dataset which consists of 126 upper-case letter characters. Based on the result, the proposed CS-FCC obtained 1880.28 in term of route length and only needs 1.10 second to solve the whole character images. [ABSTRACT FROM AUTHOR]

In engineering applications for determining natural frequencies during vibrations and critical forces in stability problems, an important place is occupied by the numerical implementation of spectral problems. In this paper, we propose a numerical approach to solving the differential problem in spectral problems for non-self-adjoint operators. As an example, the problem of determining critical compressive forces and torques in rods is considered. [ABSTRACT FROM AUTHOR]

Padang is one of the metropolitan cities in Indonesia and the capital city of West Sumatra Province. As a metro city, traffic jams are one of the city's problems, especially at adjacent intersections. Isolated traffic management applied in the city has yet to successfully solve the problem. This paper aims to evaluate the performance of some intersections if traffic signal coordination is applied. In this simulation study, PTV Vissim software was used. The study's findings indicated that traffic signal coordination would improve the traffic performance of the intersection. [ABSTRACT FROM AUTHOR]

Mathematical representation is one of the fundamental abilities used in mathematics to build the connection between abstract ideas and logical thinking to understand and solve mathematics problems. The level of student representation ability will affect the way students convey the idea of solving mathematics problems. This shows how important this ability is in mathematics. But in fact, the ability of mathematical representation is felt to be less comprehensively mastered. This is indicated by the large number of students having difficulty conveying their ideas in solving mathematics problems. This paper describes students' abilities in mathematical representation to solve math problems. The indicators for mathematical representation ability in this research are classified as verbal representation (written text), visual representation (picture, diagram, graph, or table), and symbolise representation (mathematical statement, numerical/algebra symbol, mathematical notation). The subject of this research was 8-grade students of one of the junior secondary schools at Bukittinggi. The results showed that 22 out of 34 students have difficulty in conveying their ideas to solve math problems, while the rest feel quite good about it. [ABSTRACT FROM AUTHOR]

The country's socioeconomic growth places the livestock sector in a special position. It also contributes significantly to the rural economy by boosting family incomes and creating gainful employment for rural residents, notably for women, landless workers, small and marginal farmers, and farmers in rural areas. 3035 million rural residents engage in livestock raising, with an average household holding of 2-3 cattle, buffalo, and 5-6 sheep or goats, which contributes to 30–40% of their income from livestock but handling livestock is a dangerous activity. Many livestock handlers cannot watch them all day long, by that time animal related accidents are happening. To stop that from happening, livestock handlers should communicate with cattle. As a solution, this paper presents a design that may aid in solving these problems. [ABSTRACT FROM AUTHOR]

In this paper, we have proposed a new algorithm to find optimal solutions to fuzzy transportation problems. Here, defuzzified the trapezoidal fuzzy numbers by implementing the ranking methodology. This article gives methodology that brings down the optimal solution. The numerical example illustrates the validity of our proposed method. [ABSTRACT FROM AUTHOR]

The paper considers the process of filtration of water and oil phases, taking into account the deformation of the medium. A suitable mathematical model of the process is proposed. Using the proposed model, the influence of medium deformation on hydrodynamic parameters was analyzed. The problem was solved numerically by the large particle method. Based on the obtained results, the influence of environmental deformation on reservoir pressure, porosity, permeability, oil saturation and oil production was studied. [ABSTRACT FROM AUTHOR]

Transfer skill is the ability to use knowledge from previous learning to solve new problems. The purpose of this article is to explore proportion problems for 7th graders, which are classified as isomorphism, and how they can be used to facilitate transfer skills development. The use of isomorphism problems requires thinking analogously between pairs of problems. This analogical thinking skill encourages students to retrieve the knowledge that has been previously achieved because isomorphism problems contain similarities both in context and numeric. By writing down the solution results by analogy, students also develop their representational skills. Transfer skills are built from these two thinking skills: analogy and representational thinking skills. Examples of how the strategy of constructing isomorphism in proportional learning are discussed in this paper. [ABSTRACT FROM AUTHOR]

This paper aims to develop a student worksheet with a discovery learning-STEM model on dynamic electric material to build on students' problem-solving skills in YAPPI Wonosari Vocational High school. The method used is R&D with a 4-D model that includes defining, designing, developing, and disseminating. The instruments used include validation sheets and tests—data in a physics worksheet to improve students' problem-solving skills. This study's data collection methods contain expert validation, observation, pre-test, and post-test—the data analysis using the sign test. The results showed that 1) the development of student worksheets with discovery learning-STEM on dynamic electric material was feasible in terms of the validation results. This can be seen from the results of validation that show the feasibility of physics worksheets for improving problem-solving skills is in the excellent category, and 2) the effectiveness of using physics worksheet with discovery learning-STEM based on data obtained from the pre-test and post-test results can improve problem-solving skills as a problem in the implementation class. Thus, student worksheet developed with discovery learning STEM is compatible with improving problem-solving skills. [ABSTRACT FROM AUTHOR]

The paper examines optimization problems for underground structures based on algorithmic methods, develops mathematical models, and specifies algorithms for solving them. Solving these problems allowed us to achieve significant savings in materials and costs compared to existing projects. The possibility of designing vault structures with minimal consumption of materials is being explored. The results of calculations for the optimization of underground structures are presented. [ABSTRACT FROM AUTHOR]

This work is devoted to the development of a method for optimal load distribution between units of thermal stations using geometric programming. Load distribution problems for thermal power plants, including turbines, boilers, units and other components, are complex and relevant in the context of energy systems. The paper discusses optimization features for condensing turbine units, blocks and boilers. The use of geometric programming makes it possible to simplify the conditions for the most favorable distribution, providing effective methods for solving the problem. The developed method not only provides optimal load distribution, but also takes into account various technical characteristics and limitations of plant components. The results of the study represent a significant contribution to the field of optimization of energy systems, and the proposed method can be effectively used in practical problems of controlling thermal power plants to improve their efficiency and reliability. [ABSTRACT FROM AUTHOR]

This study looked at the effectiveness of blended learning in a South Korean university's nursing department during the length of a semester, from September to December 2019, before the pandemic lockdown. Evaluations of blended learning efficacy are closely tied to both nursing educators and learners. The goal of this paper is to look at ongoing English-medium education at a nursing department at a Korean university that uses a blended learning model. The current study examines the learning experiences of 41 Korean Freshmen and Sophomores, assessing their development and acceptance of blended learning, as well as the efficacy of this pedagogical tool in improving nursing undergraduates' learning outcomes. Our primary approaches are interviews and surveys. We believe that the blended learning technique may equip Korean students with more effective learning opportunities in terms of critical thinking and problem solving. As a result, blended learning may be essential for future nursing education applications. [ABSTRACT FROM AUTHOR]

Interventional study design has been adopted widely in design process and research, bringing new insights into design thinking, and innovating new ways of solving design problems through pragmatic and participative approach. However, there is still a lack of studies conducted in intervening design process at earliest stage with systematic approach due to contextual complexity and levels of competencies among designers. In this paper, we develop criteria preference tool for designing project briefs, as a result of analysing 21 designer's preferences in the specific designated task using pre- and post-study. The criteria preference tool provides us vocabularies that help to explain the challenges and priorities, what are influences the formulation of the brief's design direction and what informs the selection and development of the methods. [ABSTRACT FROM AUTHOR]

The Optimization of cost in any product is plays the important role. The Gradient descent method is used to solve the problem of local minimization. This is an Optimizing algorithm that also used for minimize the cost function in various machine learning. Basically we discussed the types of Gradient descent algorithm like Batch gradient descant, Stochastic gradient descant and Mini batch descant. This paper will be discussed on the different parts of Gradient descant and stochastic gradient descant algorithm. This paper is the comparative study of both algorithms. [ABSTRACT FROM AUTHOR]

This article discusses promising directions for the organization of project-research activities at school when solving problems with practical content and analyzes the possibilities of origametry, which gives great potential for the formation of research skills and abilities of students. Origametry as one of the practical areas of geometry holds unexpected prospects for shaping research competencies of students. It offers the opportunity to use simple improvised media, such as a sheet of paper, to prove a rather large variety of geometric statements. In the course of the experiment the importance of this approach in the study of geometry was established, which fosters a positive personal attitude towards the discipline in question. The article discusses sample mini-projects, which include a selection of methods for solving problems in constructive geometry and make it possible to implement project-research activities of pupils in a practical way at school. [ABSTRACT FROM AUTHOR]

This article proposes a solution to the problem of optimization based on the relation function given in the form of a triangle in an uncertain environment. In this case, the practical problem will be solved by minimizing the number and time of letters received by organizations. A statistical method has been proposed for a new approach to solving the problem of poor security. In this case, the process of adjusting the parameters by means of obscure functions was proposed. This paper also calculates the integral value of the weighted average h-level based on the triangular correlation function. And we use a statistical interpretation of the electronic document exchange system based on the theory of obscure sets. Here the triangular relation function is used. [ABSTRACT FROM AUTHOR]

Various studies for solving problems in electrical power have been published. Many of these studies are related to the development of technology to solve the problem of electrical power alone or to solve the problem of electrical power and consider the environmental impact, often referred to as green technology. This paper discusses government policy support in encouraging technology development to have an economic impact and specific constraints in technological development in electrical power concerning the economic impact compared to the technology in communication and information. [ABSTRACT FROM AUTHOR]

In the recent times, deep learning has gained significant importance in various domains. Computer Vision is one the domains in which deep learning has seen vast development and is still gaining a lot of attention. CNNs are deep architectures that are specifically applied for image classification and object detection in computer vision. Image classification has also been successfully applied in the field of agriculture. Using deep learning, various agricultural problems have been addressed and solved. Keeping in view the enormous uses of deep learning in agricultural domain, this paper gives a brief review of the various works proposed by the researchers working in the field of deep learning and agriculture. This paper will put some light on the various agricultural problems, the deep learning models that have been employed to solve the problem, any pre-processing techniques that have been applied on the images to prepare the dataset for the specific model and the results that have been achieved by the model in solving the problem they focus on. It will also provide any research gap found in the specific work. This work will be useful for future researchers to gain an overview of the work done so far and the deep learning techniques used in agriculture. [ABSTRACT FROM AUTHOR]

As we can see today, the new technology provides many facilities and fast communication, such as the Internet. We must think about how this information transfers from the source to the destination. Due to the fact that a device called a router does managing the transfer operation, this device explores the path from the source to the destination at a low cost. Furthermore, in this paper, we present one of the most popular algorithms used in routing, is the Distance Vector (DV) algorithm, which is the basis of the well-known Routing Information Protocol (RIP). Therefore, we will explain how this protocol works and what is the problem when implementing it in the weird network and shows how can this protocol manage this problem and solve it. Besides, show where this protocol is used. As a result, the discussion part will explain the purpose of using this protocol and make a comparison with other routing protocols to see the efficiency of this protocol. Thus, during this paper, we will find the accuracy of this algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we will find expansion formulas for 5 hypergeometric functions of two variables from Horn's list, which includes 34 functions, and for 11 of them, expansion formulas were previously known according to works of Burchnall and Chaundy. To solve the problem, we introduce operators that generalize the well-known Burchnall-Chaundy's operators, study the properties of these new operators, and apply them to finding expansion formulas. At the end of the paper, to give an example, we will show the application of the expansion formula for one of the five functions to determine the order of the singularity at the origin of the fundamental solution used in solving boundary value problem for the multidimensional Helmholtz's equation with one singular coefficient. [ABSTRACT FROM AUTHOR]

In this paper, two new hybrid algorithms are proposed to solve global optimization problems. The first algorithm combines the sooty tern optimization algorithm with the arithmetic optimization algorithm, and the second algorithm combines the sooty tern optimization algorithm with the conjugate gradient method. The sooty tern optimization algorithm is a metaheuristic algorithm proposed by Dhiman and Kaur in 2019 Sooty migration and attack behaviors seabirds in nature were the primary inspiration for this algorithm. In this paper, this algorithm was hybridized using the arithmetic optimization algori thm and the conjugate gradient method, and the two algorithms were measured by applying them to 10 functions, and the results of the hybrid algorithms were very good compared to the original algorithm. [ABSTRACT FROM AUTHOR]

In the case of a multi-criteria problem, it involves deciding over an alternative that is characterised by several criteria. It can also solve the problem of prioritising the criteria that are difficult to measure, which is typically determined in a normative fashion that needs expert views. One of the popular techniques capable of dealing with expert opinions data is multi-criteria decision-making (MCDM). This study aims to demonstrate the application of one of the MCDM methods, the best worst method (BWM). In this paper, the BWM is used to prioritise the criteria of Zakat Kedah recipients. The BMW analysis was conducted with input data from a total of 51 Lembaga Zakat Negeri Kedah (LZNK) personnel and Amil. The criteria are ranked according to their average weight calculated from the BMW analysis. From the results, of 17 criteria, marriage status is ranked as the most critical criteria in identifying the Zakat Kedah recipient, followed by health level, food, number of households and protection criteria. The results from this paper may help the management of LZNK plans its Zakat distribution strategically by using a combination of data-based decision making and expert judgment in distributing the Zakat to the most eligible Zakat Kedah candidates. [ABSTRACT FROM AUTHOR]

With the spread of the Internet and a large number of network users, the problem of congestion on the network has arisen. This paper presents a strategy to reduce network congestion using clustering algorithms, K-means, and shortest path algorithms. The paper aims to solve the problems of congestion control, access to quality of service, reduce time wasted when sending and receiving network users, take advantage of network devices, and provide quality of service without data loss. The results of the proposed system simulation showed its effectiveness and accuracy through the simulation of the system. [ABSTRACT FROM AUTHOR]

One of the profound things that human being has ventured is to demystify the natural process that is happening in nature. Nature inspires technology to solve real-time problems. There are various nature-inspired techniques based on insects that are used in population-based or ecology-based nature-inspired algorithms. In this paper, the nature-inspired Bat Algorithm, which is based on the echolocation behavior of bats, is discussed in detail. The Bat Algorithm has various hybrids which are used in numerous applications; all these hybrids are reviewed and discussed in this paper. Systematic analysis is conducted using Scopus and WoS databases to analyze the research trend for these hybrid algorithms, study its variants and application domains, and predict the future for these nature-inspired algorithms. Numerous experiments based upon year-wise analysis, correlation of related terms, article growth, etc. are conducted and described in this paper. [ABSTRACT FROM AUTHOR]

The paper solves the problem of generating informative patterns, which is the most important stage of logical data analysis. A greedy heuristic algorithm for pattern search is proposed, with the help of which a chain of patterns of different coverage and homogeneity is generated. Such a chain of patterns is an approximation of the Pareto optimal set of patterns, maximum in coverage of observations of the target class and minimum in coverage of observations of other classes. Computational experiments show that the choice of the pattern variant with the best informativeness (according to the used criterion of informativeness) avoids both the effect of retraining due to excessive selectivity of patterns and insufficient homogeneity of the pattern due to its excessive generalization. [ABSTRACT FROM AUTHOR]

The paper considers the issues of determining the distance from an object to an arbitrary plane. Point N is defined as an object from which the distance is determined, triangle ABC is considered as a plane. The position of the vertices of a triangle in space is determined by the Cartesian coordinates of the points of its vertices. Three methods for solving the problem were applied: the mathematical method, the graphical method, the method of modeling the results. The mathematical method made it possible to use the analytically composed general equation of the plane α(ΔАВС), setting the values of the coordinates of its three points A, B and C. The vector form of the equation of the plane was used. A transformation is performed to obtain the general equation of the plane in a Cartesian rectangular coordinate system, and then, a transformation is carried out to the normal equation of the plane. The segment NE to the plane α is found. In addition, the problem is solved by the graphical method of descriptive geometry. From the point N a straight-line l is passed to the plane α, the determinant of which is the triangle ABC, at an angle equal to 90°. Then, the value of the resulting distance NE was determined by graphical methods. The accuracy of the graphical solution method was verified by solving analytical equations. 3D modeling made it possible to solve the same problem. To increase the visibility, visualization tools of the computer-aided design system were used. [ABSTRACT FROM AUTHOR]

The paper considers the issues of determining points corresponding to the line of intersection of two surfaces. Sets of descriptive geometry, computer graphics tools and building 3-D models of intersecting surfaces by means of the method of spheres and auxiliary cutting planes have been used by the authors. Both surfaces of revolution (a cone, a truncated cone, a sphere) and polyhedra (a prism in various combined combinations) were considered as surfaces in solving the problem. The problem is solved on a complex drawing. Then the line of intersection of these surfaces in space was obtained. A 3D model of the line of intersection was created. The next step in the implementation of this task was the transfer of visualization of the computer-aided design system to a flat drawing. The use of 3D modeling made it possible to bring the mathematical problem closer to the practical activities of the developer and designer. Visualization tools made it possible to actively interpret and use the final result in designing in various areas of engineering. [ABSTRACT FROM AUTHOR]

The Hybrid Flow Shop Scheduling (HFS) topic has received wide attention regarding problem modeling and solution techniques. The HFS problem has been extensively researched due to its importance and complexity. This paper presents an optimization scheme for a case study on minimizing makespan and energy consumption in a hybrid flow shop scheduling problem. The HFS consists of a few productions line with several parallel machines in one or more stages. The significant difficulty is assigning work to specific devices at different locations. A case study was implemented with twenty-seven jobs in four stages comprising bending machines, lathe machines, milling machines, and wire cut machines. The (EE-HFS) optimization has been carried out using Multi Objectives Dragonfly Algorithm (MODA). The optimization result was compared with well-established algorithms, the Pareto Envelope-based Selection Algorithm II (PESA2), Multi Objectives Evolutionary Algorithm Based on Decomposition (MOEA/D), and new algorithms, Multi Objectives Grasshopper Optimization Algorithm (MOGOA) and Multi-Objective Ant Lion Optimizer (MOALO). Five metrics were employed for comparison purposes, Error Ratio (ER), Spacing (SP), Maximum Spread (MS), computational speed (CS), and Generational Distance (GD). The MODA outperformed other algorithms based on the convergence metric and was on par with different algorithms for spacing and maximum spread metrics optimization results. In conclusion, these results are significant for Hybrid flow shop scheduling regarding the energy utilization model and MODA's excellent potential to be implemented further in other combinatorial scheduling problems. This case study considerably benefits the company by revising its time and minimizing its daily energy use. [ABSTRACT FROM AUTHOR]

The paper considers the issues of creating a system of second-order differential equations for controlling a dynamic object described by a system with an elastic property, alignments which are further transformed into two polynomial controls in matrix form. To solve the problem of synthesizing a control system in a control system, two matrix polynomials are introduced into the control system with unknown parameters that were the transfer function of the controller, the order of which is equal to two, which gives the system astatic properties. To solve this problem, matrix polynomial control is converted to matrix linear control with real coefficients. The results of simulation modeling show that the synthesized system meets the requirements of the object, the proposed device allows you to ensure the stability of the system, gives the properties of astaticism, and the duration of the transition process is determined by the location of the poles of the system and the desired quality indicators. [ABSTRACT FROM AUTHOR]

In this paper, the influence of intermediate parameters of roving compactors in the drafting tool of ring spinning machines on quality parameters of Siro yarn production is studied. To solve the optimization problem, the optimization problem was solved using the obtained regression relations. Based on the experiments, it was determined that the highest specific tensile strength of the yarn can be achieved when the distance between the holes of the compactors is L=10 mm. [ABSTRACT FROM AUTHOR]

In this paper, we study the problem for a quasilinear parabolic equation with free boundary. To solve the problem, a priori estimates of the Hölder norms are established. On the basic of a priori estimates, the existence and uniqueness of the solution is proved. [ABSTRACT FROM AUTHOR]