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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]

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]

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]

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]

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 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 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 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 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]

In this paper we will discuss the theoretical analysis for Bickley's method and numerical procedure for getting the approximate solution. If (sm, ck) denote the class of spline functions consisting of piecewise polynomial of degree m, joined at "knots" with at-least k continuous derivatives (k < m) then spline functions in (Sm, cm-1) are used as approximating function for two point boundary value problem in the second order differential equations. The result shows that the presented cubic spline function which interpolates the lacunary data was efficient and effective for solving such problems. [ABSTRACT FROM AUTHOR]

Ontology helps in specifying the domain knowledge of texts. The process of extracting subject and object and their relationships in domain texts is called ontology extraction. Most of the existing techniques for ontology extraction only managed to identify and extract the relation of a subject (term) and an object (term) in a single sentence. However, not all sentences in domain texts will have a complete subject and object or known as pair of concepts in a single sentence. Some sentences may only have a subject without a clear object being defined in a sentence or vice versa. Therefore, there is an issue to extract the concepts as the subject or object is not clear in texts. Currently, one solution that can be applied to encounter this problem is by extracting it manually with the help of domain experts, but it is a costly and time-consuming method. Hence, this paper presents a Rough Set Model to solve the problem in ontology extraction, especially related to the missing concept and the selection of the most possible relationship for concepts in incomplete sentences. The proposed algorithm consists of three main steps; the first step is the identification of all possible concepts, the second step is the selection of the most possible concept, and the last step is the identification of the relevant relationship of concepts by using the accuracy of the approximation. This model shows significant accuracy improvement in ontology extraction based on the Rough Set Model been used. The model will be evaluated with benchmark data and the dataset will be based on medical domain texts. [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]

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 describes methods for workload distribution problem solving using local groups of devices (LDG) and based on the ontological analysis procedure. The method of selecting a candidate nodes survey strategy as one of the stages of constraint formation in workload distribution problem solving in the fog-computing environment based on ontological analysis, taking into account the localization of nodes in the fog layer and the topology of the computer network, is described. A new technique of workload distribution in the fog-computing environment, based on the combined use of the method of constraint formation based on ontological analysis, the technique for choosing a strategy for candidate nodes survey and the LDG method, is proposed. Computational experiments which demonstrate an increase in the effectiveness of the ontological analysis procedure depending on the depth of the fog layer have been carried out in this paper. [ABSTRACT FROM AUTHOR]

This work is devoted to the problem of ensuring the safety of vessel traffic at marine areas. Navigation safety in conditions of heavy traffic can be ensured only if the vessels comply with a certain traffic pattern. The paper highlights the problem of planning a system of routes (traffic patterns) of vessels. This schema depends on the geography of the water area and the characteristics of traffic. The necessity to ensure the maximum safety of vessel traffic and practical considerations determine the choice of a specific variant for a traffic scheme. Modeling the vessels motion along a set of possible trajectories and evaluating the metric describing the degree of movement danger is the basis of the method for solving the problem. The frequency of dangerous approaches of vessels is proposed as a metric for assessing the danger of traffic, and the possibility of using other metrics is noted. The work demonstrates that the model representation of the problem based on a weighted graph does not allow its solution without the involvement of specialized computing resources. An alternative approach is motion construction of schemes in an expert way from typical structural elements (primitives). Simulation modeling of a problem becomes possible on available general-purpose computing and software platforms if it is isolated within a separate primitive. The paper con-siders four such primitives and estimates the average time between dangerous approaches of vessels for each of them. An example of using the obtained modeling results for planning safe ship traffic patterns is given. [ABSTRACT FROM AUTHOR]

This paper is an improvement from the previous paper which discussed the traffic situation on the Cinunuk-Cileunyi Line (Jalur Cibiru Cileunyi, JCC), also known as Cinunuk street, which located in east of Bandung District, WestJava, Indonesia. This paper discuss about adding features to the simulation model, namely the situation of obstacles for all of T-junction points along the JCC. Through simulation, we analysed the various causes of traffic congestion at JCC. Sometraffic engineering alternatives can be perform to minimize congestion, such as opening and closing the flow of traffic intersections. However, based on the volume increment of vehicles, various traffic engineering that applied at JCC are actually not significantly solve the problem. As the government planned years ago, one of the best alternatives is to builda clear ring circumference (Jalur Lingkar Cileunyi, JLC), as an additional road to solve the traffic congestion to solve or at least to reduce the congestion problem at JCC. [ABSTRACT FROM AUTHOR]

The paper presents the results of numerical experiments to determine the drag coefficient and study the flow patterns around small aircraft using the SolidWorks flow simulation CAE system. A feature of the problem being solved was the specificity of the calculation of small bodies when compared with the results of a ballistic experiment on a ballistic track. The structure of this experiment is presented in the paper. The use of launchers of various capacities made it possible to cover a wide range of subsonic velocities, highlighting three characteristic values of the flight velocity of a small-sized spherical aircraft. For these velocities, the values of the drag coefficient were determined. The conditions of the ballistic experiment were used as input data when organizing a numerical experiment in SolidWorks flow simulation. Moreover, the used parameters of the computational domain and the resulting flow patterns around a spherical body are presented. In addition, the values of the drag coefficient of this body are calculated. Comparison of the results of the ballistic and numerical experiments showed the high accuracy of modeling the considered processes in SolidWorks flow simulation. Additional verification with known data obtained for a similar problem in another software package confirms the effectiveness of the numerical experiment. [ABSTRACT FROM AUTHOR]

KM clustering is the most popular technique that finds each cluster's hidden intrinsic pattern in a given real-life application dataset. But it has some limitations, like its run time complexity is very high for high dimensional data sets, and this clustering is very sensitive to its initial centroids. This traditional approach requires the number of clusters, k, in advance for KM, which will not give good quality of clusters, and at the time, this algorithm converges to local optimal solution. So, for solving the problem of local optimal solutions, this paper presented some of the updated NI meta-heuristic algorithms, which has been hybridized with the KM clustering. This hybridized algorithm converges to global optimal solutions rather than local optima in a large search space. Further, we discussed some python API packages from scikit-learn.org for hybrid KM clustering that gives good quality of clusters, and at last, we describe some comparative analyses of KM clustering with integrated KM (KM+NIC). Most of the integrated KM show better accuracy results compared to traditional KM clustering. [ABSTRACT FROM AUTHOR]

WordPress is the world's most popular content management system. In recent years, websites using WordPress have been a popular target for hackers due to the platform's popularity. To solve these problems, users turn to security plugins to help them deal with security threats. However, there is no in-depth security analysis of the WordPress plugin system. In this regard, the paper aims to analyze the work of the main security plugins, including code analysis, testing with different types of threats, checking the data that they collect, and evaluating their strengths and weaknesses. The working principles and implementations of modern security plugins have been described and the criteria for selecting the studied plugins have been defined. The results have been summarized and the approaches used by the different plugins have been compared. [ABSTRACT FROM AUTHOR]

This paper describes the detection of unusual event that occurs in ATM machine. ATM is a simple source for people to get their money in a faster way. Also, there are many thefts and crime happening in ATM. The COVID-19 outbreak is the toughest challenge we have faced. The main precautions to avoid the transmission of virus are to wear a mask and maintaining the social distance between us. Here we introduce a system to solve such problems by using a computer vision to keep track of activity and detect violations (Not Wearing Mask) and alerts a mail with violation photo attached to concerned authority. In addition to this object detection and weapon detection is also appended. [ABSTRACT FROM AUTHOR]

The constant accumulation of Waste Electric and Electronic Equipment (WEEE) at an accelerating pace pose a threat to the environment and people. On the other hand, the WEEE and specifically their component Waste Printed Circuit Boards (WPCBs) are rich in Precious Metals (PMs) and Base Metals (BMs), more than ten times their content in natural ores. Such an opportunity has already attracted the minerals processing industry (e.g., metallurgical companies) to the WEEE recycling problem solving. However, analogically to virgin mining, the presently more or less worthless parts of WPCBs also pose a health threat since they contain toxic pollutants. The key to efficient metal recovery from WPCBs is selective processes for fragmentation and separation which are accurate for both metals and non-metals. Fragmentation is a prerequisite for accurate separation. The closed-circuit grinding (size reduction) method is preferred in the case of WPCB processing, and a prospective technology for carrying it out is High Intensity Impact Milling (HIIM). In this paper, the HIIM (disintegrator) technology is compared with commonly known technologies for selective WPCB size reduction. The HIIM demonstrated possibility to adjust the size reduction process to different materials and replication of the initial results obtained under laboratory conditions. [ABSTRACT FROM AUTHOR]

Applications of deep learning to solve complex problems related to computer vision and human level control system has been successfully implemented in real life. On the other hand, deep leaning based systems can also cause harm to the privacy and security of the personnel or a system. One of the threats that is powered by deep learning and AI is deep fake technique which is used to create fake images, video and audios that are not identified by human visual or audio system. This makes it difficult for human to distinguish between the original data and the deep fake data. This paper aims at discussing the techniques or algorithm require to create deepfake and to detect the deepfake in audiodata. [ABSTRACT FROM AUTHOR]

This paper deals with Fuzzy Integer Linear Programming problems (FILPP) in which all the constraints and variables are PFN. In this research, a technique created on the combined construction of m-LPPs for solving FILP Problems is presented. Also, an attempt is made to compare the present result with previous methods proposed by different authors. This study helps out to choose the better procedure for solving FILP Problems. [ABSTRACT FROM AUTHOR]

This paper introduces the hybrid of Potential Method (PM) and Graph Theory and Matrix Approach (GTMA) to surmount the issues in the existing hybrid of Analytic Hierarchy Process (AHP) and Graph Theory and Matrix Approach (GTMA) concerning the complexity of the calculation of the weight of the attributes when involving many attributes, no visualization of the relationship between attributes and complex calculation of ranking order of attributes for missing information. Subsequently, the implementation of the proposed method is utilized in the fuel selection problem in solving two issues namely complexity in pairwise comparison and missing information. Besides, the proposed method could surmount the complexity in pairwise comparison and deal well with missing information in providing the ranking order of alternatives. Finally, the results obtained indicate that the method could be utilized for ranking purposes in Multi-Criteria Decision Making (MCDM) problem. [ABSTRACT FROM AUTHOR]

Among major meshes in computational fluid dynamics are those of uniform, piecewise-uniform, graded, and hybrid over which the solutions of discretized governing equations are found. Bad solutions as spurious oscillations, over-or under-predictions, and excessive computation time might be the results of unwitting application of the meshes. Accentuating comparative effectiveness of two meshes, namely uniform mesh and Shishkin-graded mesh with mesh expansion factor, this paper takes the solution of a singularly perturbed convection-diffusion problem into account. The problem is solved by assigning three combinations of mesh expansion factor and transition variable to Shishkin-graded mesh, while the mesh number is kept constant. Based on the values of singularly perturbed parameter, four test cases were considered. Shishkin-graded mesh is proven relatively more robust, particularly due the solution on the mesh being free from spurious oscillation. Moreover, the accuracy level of the solution of up to one order of magnitude higher is obtained. The mesh expansion factor therefore contributes to a stable and highly accurate solution corresponding to all interested perturbation parameter values. [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]