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The artificial neural network has several training functions that can speed up the training process of the standard backpropagation algorithm. Therefore, the purpose of this research is to evaluate the scaled conjugate gradient algorithm's capability and performance, which develops the training function of standard backpropagation to solve computational problems. The dataset used in this paper uses quantitative data from export data of jewelry and valuable goods by the leading destination country, which is processed from documents customs of the Directorate General of Customs and Excise (PEB and PIB) and quoted from the Indonesian Statistical Publication. A network architecture model will be formed and determined based on this data, including 7-7-1, 7-14-1, and 7-21-1. Based on these three models after training and testing, the results show that the model with the best performance and accuracy is 7-14-1 with a performance value of 0.001118426, the lowest among the three other models and an accuracy of 90.9% (higher than the two models other). So it can be concluded that the SCG algorithm with the 7-14-1 model can be used to solve computational problems, as evidenced by the best performance and accuracy values. [ABSTRACT FROM AUTHOR]

The paper presents the main components of a methodological approach to the creation of an apparatus for analyzing the reliability of fuel and energy supply to consumers in conditions of negative impacts on the energy sector operation. The authors characterize the main factors affecting the scale of the implementation of threats to the reliable functioning of power systems and the energy complex as a whole. The paper describes algorithms for analyzing the impact of negative impacts on the reliability of fuel and energy supply to consumers, algorithms for forming lists of critical objects of energy systems, as well as algorithms for choosing measures to minimize the consequences of negative disturbances in the energy sector. [ABSTRACT FROM AUTHOR]

The software testing process is not only important but also a complex stage SDLC (software development life cycle) process. For estimating the activities of the system in the software testing stage testers implement test scenarios as input for the system under test (SUT). For improving the superiority of the system and also finding faults implementing test-cases shows an energetic role. Our research work target towards implementation of test cases automatically by combinational Unified Modeling Language (UML) diagram so that it can display higher effectiveness in starting phase of the system development procedure of model-based testing. This research uses UML diagrams like Use Case Diagram (UCD), Activity Diagram (AD), and a combination of both generates System Testing Graph (STG). The combination of these two diagrams has been proved as the well-suited diagrams to implement test cases from the earlier combination graphs. Our technique suggested in this research paper is Uniformed Graph Traversing (UGT) Algorithm that is combined with Level Order Traversal (LOT) Algorithm to implement predictable test scenarios. In this research paper, we prove that the UGT algorithm is useful to implement test scenarios, and also these test scenarios are providing precise outcomes; each vertex existing in the test scenarios includes some situation. In this proposed approach we also disclose faults for example decision fault, fault of dependency, interaction fault, and loop fault which results in assessment effort reduction. The implemented test scenarios are directed to one requests controlling tool which can be in contradiction of the requests. It also protects time period and work and also, raises the value of implemented test scenarios, thus enhances the complete routine in a testing phase. [ABSTRACT FROM AUTHOR]

Selection of materials for any part in design process requires meticulous effort especially when suitable materials are available more than one. Trade-offs are required to select the best alternative material from the available suitable materials. Suitable materials are the materials which will satisfy all the required design parameters for that part. Data Envelopment Analysis based Ranking (DEAR), one of the multi criterion decision making algorithm is considered in this paper in selecting the suitable material for making a flexible fixture which is then used for making All Terrain Vehicles (ATV) Control Arms. Best material is to be selected for making the fixture to ensure the minimum distortion so that the exact structure of control arms is obtained which directly affects the performance of ATV especially in maintaining the stability. In this paper, mild steel along with die steel, carbon steels, nylon were considered as suitable candidate for making the fixture. Then, the DEAR algorithm is applied for selecting the suitable material for making the fixture whish was found to be Mild Steel. Further, analysis using ANSYS was performed to validate the results of DEAR Algorithm. [ABSTRACT FROM AUTHOR]

This paper provides a modelling algorithm for renewable energy based distributed generators with the goal of reducing power loss and improving voltage profiles in unbalanced distribution networks. Recently, the utilization of Distributed Generation (DG) technologies in the power system is gaining the utmost importance owing to its potential benefits. The combining of the distribution system with DG put forwards a cost - effective as well as benefits to the clients. In any case the scanty of DGs might not assure the enhancement in terms of system performance. Hence In the distribution system appropriate DG units' placement plays vital role. In this paper, the optimal DG placement problem will be discussed as a constrained nonlinear optimization problem for voltage profile enhancement and power loss minimization. As a novelty the result of Lion Algorithm (LA) compared with the supervised firefly algorithm and Bat algorithm. The voltage profile and power loss reduction in the feeder system with DGs is evaluated for two test cases: case 1(DG supplying real power alone (P), and case 2 (DG supplying reactive power alone (Q). The proposed algorithms are evaluated on the IEEE 33 and IEEE 69 node feeders in a MATLAB environment. Several case studies have been conducted, and the results of the subsequent discussions illustrate the effectiveness of the presented algorithms. [ABSTRACT FROM AUTHOR]

Automated diagnostic systems have become increasingly popular in the healthcare industry in recent years. In recent years, these systems have gained popularity for their diagnostic benefits. The operator-dependent existence of medical imaging systems can be minimized with this method, and the diagnostic process can be made more repeatable. In addition, it aids in the improvement of diagnostic accuracy. This effectively works with features that cannot be obtained by visual analysis or intuitive examinations (such as computational and statistical features). In this paper, we propose a new algorithm called "Optimized Weighted KNNI algorithm" (OWKNNI). In this research paper, we have addressed the topic of migration. This paper discusses the problem of dimensionality reduction and the use of feature selection algorithms, which is one of the most important tasks in feature engineering. The solution is given sorting out the problem is proposed as an algorithm. [ABSTRACT FROM AUTHOR]

In the era of machine intelligence, dynamic gesture recognition is assumed to be a difficult and challenging problem because it involves the human element. Moreover, the gestures formed for a particular problem vary from person to person. Therefore, the accuracy of classification sometimes becomes inappropriate. Also, gesture recognition is affected by lag in detection; however, a negative lag is assumed to be favorable. In this paper, an attempt has been made to control the system volume through hand gesture recognition which may help in the remote operation of a device and differently-abled people. The YOLO algorithm will deep learning approach is used in this paper, which detects hand movement and its direction. Based on the direction of hand movement, the volume can be increased or decreased. [ABSTRACT FROM AUTHOR]

The photovoltaic system is a non-linear system, with variable parameters and subject to external disturbances. It's necessary to use an algorithm so that the PV generator operates at maximum power and therefore high efficiency, for this purpose the DC/DC boost converter is introduced as a control device, The first step in this paper, is for modeling of a photovoltaic model, Then, in the second step, we focus on the implementation of a MPPT command for controlling the duty cycle, we propose the sliding mode control technique (SMC) known for its great robustness in terms of stability and performance, in the final step, the system is designed and simulated using MATLAB/SIMULINK. [ABSTRACT FROM AUTHOR]

Information security plays a crucial role in data protection. All our data is secured and protected by cryptographic algorithms. This paper aims to consider the performance of cryptographic algorithms such as AES (Advanced Encryption Standard), ElGamal, RSA (Rivest Shamir Adelman), and Hybrid Cryptography and further compare them. We have done a comparison on parameters like the CPU execution time, memory space, and encryption-decryption time for different key sizes and file sizes. [ABSTRACT FROM AUTHOR]

People in today's era of smartphones rely on online businesses and door-delivery systems to buy goods and services. Location, as well as the number of storage centers or collecting stations, are critical variables in running a viable door-delivery system. The locations should be able to minimize the average distance from the collecting stations to the destinations. In discrete location theory, this can be treated as a p-median facility location problem (PFLP), which is an NP-hard problem. The PFLP has been solved using a variety of approaches. This paper puts forward a novel algorithm for opening collecting stations for door-delivery systems based on the graph-theoretic concept called "fuzzy median graph". The algorithm prioritizes the shortest possible distance between collecting stations and service points. This algorithm also determines the bare minimum number of collecting stations required to operate the door-delivery system profitably. [ABSTRACT FROM AUTHOR]

In this paper, a proposed Congestion Control Algorithm (CCA) is designed and implemented based on Multipath TCP (MPTCP). Such an algorithm enables the millimeter-wave (mmWave) network to receive more data and exploit network resources better than the other MPTCP Congestion Control Algorithms (MPTCP-CCAs) by dividing the congestion window (CWND) into half, which causes wasting in data transmission. Furthermore, the proposed CCA decreases the CWND by Decreasing Factor (DF), which has a value depending on the period through the packet losses. In this step, CWND can obtain the optimum point quickly and capture the available network resources properly. The proposed algorithm is implemented in Linux Kernel and evaluated in the Mininet emulator. Compared with other algorithms such as MPTCP-LIA, MPTCP-OLIA, and MPTCP-BALIA, the numerical and emulation results demonstrate that the proposed algorithm improves 35.60% and 29.5% regarding CWND and throughput, respectively than the best performance of MPTCP-CCA. [ABSTRACT FROM AUTHOR]

The paper presents a separated staggered phase field methodology for modelling of brittle fracture. The basic relations of the phase field formulation are derived, along with decomposition of the strain energy. In separated scheme, displacement model is computed separately from the phase field model in concurrent fashion. The transfer of variables among models, loading imposition and incrementation are governed by the head routine. A convergence criterion has been suggested, which is based on the norm-2 of the phase field variable. The framework has been implemented into FE software Abaqus and Fortran via user subroutines. The proposed framework has been verified on the standard benchmark problems. The solutions obtained have been compared to the other staggered schemes found in the literature. It has been presented that separated scheme provides correct solutions and requires shorter computational time. [ABSTRACT FROM AUTHOR]

The Long-Term Evolution (LTE) system was presented by the 3rd Generation Partnership Project (3GPP), to assure quality of service (QoS) performance pertaining to non-real-time and real-time services. An effective design with regards to resource allocation scheduling involves core challenges to realise a satisfying service in an LTE system, particularly with the growing demand for network applications especially for real-time video services, which is an ongoing problem. The continuous rise in terms of the number of network's users has resulted in impact on the performance of network, that also creates resource allocation issues when performing downlink scheduling in an LTE network. This research paper puts forward a review of the optimisation pertaining packet scheduling performance through the LTE downlink system, and presenting a new downlink-scheduling algorithm for serving video application through LTE network that accounting for QoS and channel conditions needs. A comparison of the recommended algorithm's performance was made with algorithms are commonly used in scientific research such as Proportional Fair (PF), Modified Largest Weighted Delay First (MLWDF), Exponential PF (EXP/PF), and Exponential Rule (EXPRULE) algorithms, regards to delay, throughput, Packet Loss Ratio (PLR), and fairness for video flow. On the basis of the attained outcomes, the recommended algorithms considerably enhance the efficacy of video streaming as against the familiar LTE algorithms recommended in this research work. [ABSTRACT FROM AUTHOR]

In this paper, variational iteration method (VIM) is applied for solving fractional partial differential equations and the fractional derivative has been used in Caputo and Riemann Liouville sense. Four test problems are discussed to show efficiency and reliability of the method. The approximate solutions obtained by VIM are comparmatheed with solution by other methods. The presented technique is easy to implement and rule out perturbation, linearization, and discretization. [ABSTRACT FROM AUTHOR]

Nowadays, everyone is looking for solutions to send messages in a secure manner. There are two ways to do that-either one delivers the message himself/herself to the receiver or one wraps the message in a way that no delivery partner can access it. In today's fast-paced world, we are all left with the second option of delivering the message through a delivery partner. We can do so through 'Cryptography' which is a technique that ensures secure delivery of our messages. In this paper, we are going to use the 'Stirling Transform' and 'Additive Group' under Modulo 27 to secure and guard a secret message from the ones we do not intend to share the message. In order to make message secure message, various algorithm have been created. [ABSTRACT FROM AUTHOR]

Now a day's test case optimization is necessary as it can improve efficiency and reduce computational cost. In optimization problem only best solution has to select out of all the possible solutions for problem that cannot be solved in polynomial time. So optimization is NP complete problem. Traditional approach was not found competent to solve complex problems thus nature inspired algorithms has been recognized for their competency. Nature inspired algorithm are inspired by natural phenomena. These algorithms are applied to optimize problem and provide acceptable and feasiblesolution in reasonable time. In the present paper an attempt has been made to discuss various nature inspired algorithms for test suite optimization. We have mainly discussed biology inspired algorithm and try to touch social phenomena inspired algorithm. It is concluded that GA is most widely used algorithm but now researchers are moving towards newly added nature inspired techniques and exploring hybrid techniques. [ABSTRACT FROM AUTHOR]

In this investigation, the generalized ( G ′ G 2 ) –expansion method is proposed and applied to the generalized Zakharov-Kuznetsov (ZK) equation with variable coefficient, which exists in many scientific fields like, plasma material science, and optical fiber. Further, our aim in this paper is to achieve the closed form solutions of ZK equation. The newly presented solutions are of hyperbolic, trigonometric, and rational functions. The dynamical representation of the solutions are shown as annihilation of three–dimensional kink waves, and multi-soliton waves. [ABSTRACT FROM AUTHOR]

In this paper, we consider the study of the extreme problem of the fictitious domain method based on the use of the Lagrange functional, with a multiplier defined on the actual boundary and associated with genuine boundary conditions. The theorem of the existence of a generalized solution of the auxiliary FDM problem is proved. The convergence of the solution of the auxiliary FDM problem is shown. For mathematical research, the theory of functional spaces and the technique of obtaining a priori estimates in functional spaces are used. To verify the effectiveness of the developed method, numerical analysis and comparison with other methods of solving the problem were carried out. [ABSTRACT FROM AUTHOR]

In the present paper the algorithm for constructing of the operator D4 [β] is given and the explicit form of the operator is shown. This operator can be used for finding the coefficients of the optimal quadrature and interpolation formulas in the Sobolev space [ABSTRACT FROM AUTHOR]

In the present paper, the initial value problem for the third order delay partial differential equation with involution and Neumann boundary condition is studied. The first order of accuracy difference scheme for the numerical solution of the third order delay partial differential equation with involution and Neumann boundary condition is presented. The illustrative numerical results are provided. [ABSTRACT FROM AUTHOR]

The purpose of this work is to select a set of basic operators for the considered model for calculating estimates, to construct their linear closure, and to prove the existence of a correct algorithm. The paper proposes the selection of a set of basic operators of the considered model for calculating estimates, the construction of their linear closure and a correct algorithm based on the training and control sample. The correctness of the algorithm composed of the previously defined operators and the threshold decision rule is proved. An operator is constructed from the linear closure of the model, such as the calculation of estimates, and the completeness of the linear closure of this model is proved for all problems. [ABSTRACT FROM AUTHOR]

In this paper, we study an algorithmic model for calculating estimates and prove the existence of an optimal algorithm in this model. For problems with disjoint classes, a much simpler in description and much more efficient computational algorithm is constructed. Methods are being developed that make it possible to code operator B more economically, which will reduce the required memory and more efficiently use the constructed correct algorithms for solving applied problems. [ABSTRACT FROM AUTHOR]

In multimedia content, text play major role for transmission and it is crucial to protect text data while transmitting over network. This can be achieved by text encryption algorithm. However, the method relies on many resources that increase the processing unit time, memory, and battery power. There are so many different techniques should be used to protect confidential text from unauthorized access. This paper summarizes on the existing works which used different techniques for text encryption by using deep learning algorithms. Combination of these approaches helps to analyze different algorithms for different text, accelerates the processing time while maintaining accurate preservation and retrieval. [ABSTRACT FROM AUTHOR]

The field of Cryptography serves as a crucial aid in all the circumstances where a secured and a safer communication has to be constructed. The word 'Crypto' means 'hidden' and 'graph' means 'to write'. So far, several cryptographic algorithms have been put forth and implemented, thereby establishing more private communications in English language and in Machine language as well. Since, technology provides the facility to communicate in any desired language, these existing algorithms must be developed and practiced in many languages at a broader extent. But considering the complexity of each language, developing a cryptographic algorithm has not been carried out. Tamil happens to be one of the classical languages. We have developed a cryptographic algorithm to ensure secured communication in Tamil language. But still, manual encryption could become difficult for us to handle in all the situations. In order to overcome this kind of complication, we aim at executing this encryption and decryption algorithm with the help of a programming language. This will reduce the human energy and time consumption which will also be far easier and accurate than the manual performance. Thus, in this paper, we have developed a Python program that will encrypt the message given in Tamil language which shall be the extended version of classical Julius Caesar's method. But because of the larger alphabet structure, the disadvantages occurred while implementing this algorithm in English does not seem to hold for Tamil language. Moreover, we have implemented dual key pattern and uyir mei decomposition technique to strengthen the security. Hence, this would be highly helpful for anyone to communicate with Tamil script itself in a secured manner that too without any hassle. [ABSTRACT FROM AUTHOR]

Sentiment analysis of text data has become very much popular in past few years, because of the interesting challenges it can offer. Among these challenges, sarcasm is unique. We can address sarcasm as the 'Achilles heel ' of sentiment analysis. Detection of sarcasm from the given data is same time complicated and interesting. It is interesting because, if researchers can find the optimized solutions for finding sarcastic words in the data, it will enhance the sentiment analysis of that data. Even humans also have difficulties in understanding the actual interpretation of a sentence, if it is presented indirectly. This means, a person stated something, but he meant contradictory to the word meaning of the statement. This makes sarcasm detection an interesting topic for researchers. In this paper, we evaluated the performance of several machine learning models like Support vector machine, Naïve Bayes, Decision tree etc., and different ensemble models like Random Forest, XGBoost and AdaBoost etc., with the collaboration of various feature extraction methods such as Term Frequency-Inverse Document Frequency etc. The main evaluation metrics we used to evaluate the performance are accuracy, precision, f-score and recall. Based on the results, we concluded that the models such as XGBoost, LightGBM and Bagging classifiers provide better results in detecting sarcasm with respect to other machine learning models. [ABSTRACT FROM AUTHOR]

In this paper, a new method is presented to calculate the complement of each Sum of Products. The corresponding mathematical procedure is based on the novel linking technique of orthogonalizing difference-building- and is integrated in Quaternary-Vector-List arithmetic. This algorithm has clear advantages in terms of computation time and memory usage in con-trast to the conventional method. Thus, the computation time is on average about 80 times faster and the number of terms in the determined complement function is on average about 180 times fewer. [ABSTRACT FROM AUTHOR]

Maintaining the integrity of pipelines over long distances is an ongoing challenge for oil and gas companies. Among many factors, corrosion is one of the major causes of pipeline failure. Therefore, timely and accurate detection of corrosion is crucial. Along with the growing use of In-Pipe Inspection Robot (IPIR) technologies, a camera-based visual inspection has become a reliable technique for pipe defects detection. However, the conventional manual surveying process by the operators shows a lack of efficiency in this task. This paper studies the application of YOLO, an image-processing algorithm based on Convolutional Neural Network (CNN), for automating corrosion inspection. The results demonstrate that the proposed method is capable of performing detection with an accuracy rate of 64% under AP75 threshold. The system developed can be a promising tool in providing real-time autonomous defect detection to enhance IPIR devices. [ABSTRACT FROM AUTHOR]

The community#x2019;s views and inputs have always been the main and most beneficial source for varied range of enterprises. With more widespread community media, it provides a spectacular study and assessment of many fields in which companies used to have faith in peculiar, exhausting and inaccurate ways. This form of analysis is subclass of #x2019;sentence analysis#x2019; area. Sentiment analysis is a broad term that refers to the process of effectively classifying user-generated content into specific polarities. To perform sentiment identification and analysis, a variety of tools and techniques are available, includes supervised techniques for machine-learning that classify the target group after training in data. Hybrid instruments are a blend of machine learning and lexicon-based algorithms, which classify according to annotated dictionary. We employed the SVM with Weka for analyzing sentiments in this paper. Two pre-categorized datasets of tweets are utilized. The performance of SVM is analyzed with the help of analytical metrics. [ABSTRACT FROM AUTHOR]

This paper presents an algorithm for determining the frequency response of vibration transducers using broadband random vibration (BRV). The parameters of excitation signal are determined based on the required signal-to- noise (SNR) value in the whole working frequency range and the required RMS acceleration value. The excitation signal is represented as a linear piecewise function defined on three frequency intervals. The proposed algorithm enabled increasing the spectral power density in the low-frequency section of the working range of the electrodynamic shaker working in the BRV mode and providing the required SNR value. Compared to the verification methods using sine sweep technique at fixed frequencies of the 1/3 octave band, the proposed method can reduce the verification time by a factor of 3...4. It was also possible to reduce the error of determining frequency response caused by the use of BRV to 0.5% relative to the sine sweep procedure. [ABSTRACT FROM AUTHOR]

The paper proposes an algorithm for balancing a platform on aerodynamic suspension based on measurements of the angular velocity sensor. Results of the algorithm experimental development are presented. The developed algorithm makes it possible to improve adequacy of results of the nanosatellite angular motion control system testing. The balancing algorithm error is comparable with errors of the known algorithms that are using more expensive measurement instruments. [ABSTRACT FROM AUTHOR]

One of the most important stages of the service mission is the service satellite rendezvous with a serviced spacecraft. The task is complicated by the fact that the serviced satellite is generally non-cooperative and could be in a state of uncontrolled motion. The paper proposes a hierarchical structure of a service satellite control system and presents results in the Matlab/Simulink environment of simulating the service satellite control algorithms at the stage of rendezvous with the non-cooperative spacecraft. [ABSTRACT FROM AUTHOR]

The use of computer vision for landing operations on the mars and martian rover navigation is very important for scientific space missions. In this paper we implement an iterative visual navigation algorithm based on Gauss-Newton method for estimating position based on the image captured by only one camera. We find the pose that minimize the squared error of the predicted location of the image features to the measured location. For computing the error of pose estimation, synthetic images were generated. Considered a two-dimensional object (square) containing a set of distinct points (at least four points). The algorithm error is calculated for many relative distances between the camera and the object and three noise levels. Several images of the body are generated and taken from different elevation and azimuth angles, the position of the camera in relation to the body is estimated by applying the algorithm, then compared with the real position, to calculate the error. [ABSTRACT FROM AUTHOR]

In the paper the results of laboratory study of algorithms for angular motion determination are presented. Algo-rithms are based on extended Kalman filter using measurements of sun sensors, magnetometer and angular velocity sen-sor. The influence of vital parameters on algorithm performance is studied experimentally using laboratory facility with aerodynamic suspension. Modifications of angular motion determination algorithms are proposed and tested. [ABSTRACT FROM AUTHOR]

Recent research had shown that conventional AR-IoT applications only specialize in the localized area for industrial monitoring. One of the biggest challenges in the application of AR technology in the industry is the absence of the tools and skills to do so. Therefore, this paper introduces a programming algorithm for the development of an off-site AR-monitoring for a material handling process. A case study was conducted on a simple process using a conveyor system to sort out coloured cubes into respective buckets using TSC3200 colour sensor and ESP32 microprocessor. The CAD design of the conveyor was re-designed and imported into Unity to create the virtual 3D visualization of the machine. The simulation is made in sync with the movements of the real machine, through the communication between smart sensors and microcontroller, ESP32 using Uduino concept. The connection is cloud-based with the use of MQTT to communicate between different devices. From the fusion of these concept, a programming algorithm was created. The AR-Simulasi Apps allows user to access the virtual version of the process in real-time remotely, in Augmented Reality environment. The AR 3D visualization was superimposed in real world using AR marker. Therefore, the relationships among accuracy, augmented simulation error and object interaction were investigated. The results of the numerical simulation indicate that the AR-IoT 3D simulation would be a great potential for the current AR-IoT monitoring applications used by industries. In which it shall enhances user interaction for better viewing and perception between human and machine for off-site monitoring. [ABSTRACT FROM AUTHOR]

Solving the problem of constructing the trajectory of a UAV in a complex urban area is a difficult task. The possibility of automated formation of the trajectory of movement, without the operator's participation, allows to reduce errors and simplify the task of monitoring in conditions of a single movement. The paper considers the methodology and algorithm for constructing the trajectory of the UAV movement in the conditions of urban development. The criterion for constructing the motion curve is the possibility of a UAV flying between objects, equidistance from their boundaries, and the possibility of constructing a closed trajectory. The article contains a block diagram of the algorithm, its description, and examples of constructing a trajectory based on simulation. The algorithm obtained in the article made it possible to perform automated construction of the UAV motion curve in a complex environment along an equidistant trajectory. The proposed approach made it possible to build the route 35% faster than the primary algorithm. The proposed computational operations are based on simple calculations and can be obtained onboard the UAV. [ABSTRACT FROM AUTHOR]

Analysis of the data obtained from the UAV is hampered by the low performance of the calculation unit on board the device. Most often, the procedure is carried out on a remote unit, data transmission to which is carried out via a wireless communication channel. The need for such a solution is due to the requirements for the operations performed, including both the analysis and formation of the control actions of the UAV and the decision-making on changes in the current flight tasks. The paper proposes an algorithm for the automated selection of areas with great detail. The algorithm allows you to reduce the amount of analyzed data. Reducing the size of the analyzed blocks allows you to introduce parallelization of processes, reduce the requirements for computing resources, select processing parameters and increase the speed of data analysis. The proposed algorithm is based on data analysis in local windows, with an automated selection of coefficients. The test dataset shows examples of masks of detailed objects that have different sizes. The proposed algorithm detects detailed elements in images with a complex object structure from 80% to 10% from the size image. For a small object size, the block was deleted. For large sizes, the algorithm searches elements inside the object by gouging out a part of it. The proposed algorithm allowed for an increase in the speed of analysis by 24% compared to the previously developed approach and made it possible to analyze data in the infrared range. [ABSTRACT FROM AUTHOR]

The paper reviewed the state-of-the-art MCP-I and ESSO-M systems, discussed the interconnection of the MCP-I and ESSO-M systems and included the converter interfaces with the ESSO. Algorithms for determining the location and order of wagons have been developed for the development of hardware and software. The proposed algorithm is the basis for the development of a mathematical model for calculating the time spent by a wagon on non–road routes. The developed algorithm is based on a combination of the technology of optical recognition of railway tank numbers and the technology of axle counting using inductive wheel pair sensors and can be used at any length and configuration. At the hardware level, the system is integrated with the control system for the freedom/employment of sections of the ESSO-M railway track, at the software level — with any upper–level systems. It has been established that the hardware and software system operates in real time for the purpose of producing objective data on the presence and condition of the wagon fleet at stations at any given time. [ABSTRACT FROM AUTHOR]

The paper addresses the problem of reducing the error in determining the decisive function of the coordinate of a train approaching a crossing under conditions of instability of parameters of the primary information sensor. Rail lines of the section approaching the crossing are used as a sensitive element of the primary train position sensor. The decisive coordinate determination function (system model) is obtained by the solution of the system of conditional equations, and the model is used as Kolmogorov — Gabor polynomial. The arguments (informative features) of the decisive function are complex amplitudes of voltages and currents at the inlet of the four-pole rail line of the approach section. The algorithm of correction of the decisive function in conditions of irregularity of sensor parameters is shown by the principles of self tuning and adaptation of the polynomial of the decisive function to changed parameters. The purpose of the self-adaptive function is to minimize the error of determining the coordinates of the train in the vicinity of the crossing. The feasibility of the approach is graphically illustrated by the results of the self-recussion of the decisive function by the recurrence algorithm. [ABSTRACT FROM AUTHOR]

Computer graphics is the Visual Presentation of diagram, photographs that we draw on a surface with the help of Computer. We can transform the data or information in visual form and can represent that on any display device. Numerous drawing algorithms have been used in computer graphics for rasterizing the screen. This paper deals with a new way to reduce the error in the accessible Midpoint Circle Drawing Algorithm. In this approach, we have measured two dissimilar values of h as (1 and 0.1) in the first quadrant of a circle. For h=1, every one of the outcomes of Midpoint Circle Drawing Algorithm have been confirmed and for different values of h it is seen that as the value of h diminishes, the quantity of cycle increments yet the errors between the points created and the first circle points diminishes and the other way around. Finally by doing symmetry a whole circle is been drawn. [ABSTRACT FROM AUTHOR]

Nature Inspired Computing Algorithms are the best solutions for solving complex problems around us. The objective of our paper use Ant Colony Optimization (ACO) to optimize the shortest route between various departments located in university campus. The Internet of Things (IoT) technologies by navigation of mobile application to find shortest path located by online graphical form in a SR University campus. A graph is generated by MATLAB and the simulation results showing information of shortest route of source to destination & neighbour information. The working procedure of ACO is edge(departments) between vertices(paths) then maintain the pheromone level at that edge should be higher. As per pheromone level is high on that path, other ants also follow this path, or otherwise omitted the edge. The paper focus on Internet of Things (IoT) based ACO Optimized intelligent system for mobile phone application that students and visitors found nearest location within shortest time selective locations within SR University campus. For that save time and flexibility to find short route in a reasonable amount of time while using NIC based algorithm. [ABSTRACT FROM AUTHOR]

The growing reality today is the application of Internet of Things (IoT) in day-to-day. Though there are lot of complexities around this environment such as security, energy consumption and heterogeneity, this giant network of connecting devices with internet is sky rocketing. The mounting increase in the sharing of information made this connected network of devices is mandatory in everyday life. This powerful IoT platform suffers a lot by the security breaches as more people uses it. Authentication of IoT users using One Time Password (OTP) is one kind of resolution to solve many security issues. The OTP has added an additional coating to the traditional username-password authentication system. So, this research proposes a hybrid One-time Password generation algorithm, AroSheb_Jo, for IoT data and presents a security analysis of that algorithm. Additionally, this paper presents a comparison of its lightweight characteristics and resistance against security attacks. Experimental and performance analysis of that algorithm is also elaborated in this paper. [ABSTRACT FROM AUTHOR]

The paper explores how the daily lives of people with vision impairments are changed by artificial intelligence. They suffer a great deal in circumstances they are not aware of. When they go alone in town, people are worried about their safety. The overall aim of the system is to provide low-cost navigation assistance to blind people that give a sense of artificial vision by informing people of the artificial intelligence environment of objects. An ultrasound sensor is used to detect the distance between objects to the blind person to guide voice and vibration, which can be heard and felt by the blind person. The software can help identify objects in the world by using the voice command, conduct text analysis and recognize the document's text on paper. It can be an important way for blind people to communicate and encourage blind people to live independently. [ABSTRACT FROM AUTHOR]

The goal to promote human limits is for Artificial Intelligence (AI). It takes a posture on public administrations, represents the increasing availability of regaining clinical data and the rapid creation of intelligent strategies. The need to stress the need to use AI in the fight against the COVID-19 crisis. The paper outlines the main role played by Ai technologies in this unprecedented war and introduces a survey of AI methods used for multiple purposes in the fight against the outbreak of COVID-19. This paper also explains how the body temperature and coughing of the incoming person are assessed and whether the incoming person has not a protective facial mask. Should either of the above tests disqualify the participant, an alarming device invokes the local officials; the entrant may otherwise enter the premises after his/her hand has been sanitized. [ABSTRACT FROM AUTHOR]

The new results presented in this paper are based on the long-term research conducted recently over several years. Creation and development of multi-disciplinary knowledge resources and implementation of practical computational and numerical algorithms and solutions require flexible and long-term approaches to structures. The goal of this research is to create a flexible fundament of structures for arbitrary long-term knowledge and references, which allow an efficient deployment for knowledge creation, development, and mining. The knowledge-centric structural solution is consequently based on complements of knowledge and a coherent system of conceptual knowledge integrated in the fundamental methodology of superordinate knowledge. The results allow to sustainably master structures and algorithms for long-term computational and numerical scenarios. The solution is targeting knowledge resources and scenarios and has been developed and used for many practical implementations over a time span of more than three decades. The paper presents an overview of new, previously unpublished results on architecture complements, object development architecture, resulting knowledge resources' structures, and the new archaeological Rhodos case results. [ABSTRACT FROM AUTHOR]

Typically, refactoring are expressed in high-level, general purpose programming languages, which are impractical to verify because they are too complex to have tractable formal semantics definitions. Refactoring can be defined in various formats at various abstraction levels, the sorting algorithm is the most important and powerful in most or all programs language and database, the mighty importance of the sorting towards data mining that needs ordered the datasets elements to be fast particularly in preprocessing data. Methods : The challenges side incur of this paper summed up development the sort algorithm many times, using different refactoring ways as sequentially method sometimes with list comprehension moreover recursive listing, further with parallel computing, Implementation and execute different methods for the sorting algorithm code on several different computers with different in CPU to achieve the best rate of pure results for implementation under the Erlang code. Proposed solution : The purpose of this paper is to conduct a comparison between methods by evaluate the runtime execution prepared code that writing under Erlang functional programming, the research effort comparative analysis between the approaches adopted many member of the sort algorithm and proposed a new technique that works ordered the list by minimum elements with recursive the list comprehensive. Result: then this paper will a prove the Quick Sort technique is the fastest compared with the others. [ABSTRACT FROM AUTHOR]

AI-based predictive data mining algorithms play an important role in the prediction-role of the two-faceted roles of data mining (classification as the other role). Having a rigid predictive algorithm is tantamount to a successful and near-human predictive decision in knowledge discovery among databases being implemented among government, commercial and educational sectors. In this paper, three (3) of the most commonly used AI-based predictive data mining algorithms, namely: instance-based (nearest neighbor), statistical (naive Bayes), and Bayesian networks were evaluated using academic admission data in order to assess which predictive algorithm is best suited for predicting an ideal collegiate course for a student based on the student's high school grades and historical admission records. This study sought also to find out which among the four predictive algorithms can be used in terms of volume of historical data and number of data attributes. [ABSTRACT FROM AUTHOR]

With industry development, suburbanization, and population growth, the load demand is constantly increasing year by year. Excessive load demand has greatly strained the distribution network (DN), resulting in increased power losses due to the high-power flow. Therefore, it becomes very important to minimize power losses at the DN to maximize the efficiency of the distribution companies. Network reconfiguration is one of the effective methods used by distribution companies to minimize losses in the DN. This paper proposes Mayfly Algorithm (MA) to solve network reconfiguration problems and minimize the DN's power loss. MA is inspired by the social behavior of the mayflies, especially their mating process. IEEE-33 bus DN has been used to demonstrate the effectiveness of the proposed method. The obtained simulation results compared with other methods in the literature and comparison showed that the proposed MA provides better quality solutions than other methods. [ABSTRACT FROM AUTHOR]

Optimizing modes of the modern power system on active power is a complex problem of nonlinear mathematical programming. Despite the existence of many methods and algorithms for solving this problem, the issues of their improvement in the direction of correctly taking into account the factors that affect the regime remains an important problem. One of such factors is functional inequality constraints. The paper presents a new algorithm for optimising the modes of power system, taking into account losses in networks and functional constraints in the form of inequalities on power flows of controlled power transmission lines (PTL). A characteristic feature of the algorithm is taking into account the losses in branches by transferring them to the nodes of the electrical network. The algorithm's efficiency is investigated by the example of optimization of the mode of a complex electric power system with four thermal power plants participating in the optimization, ten PTL, in two of which the active power flows are controlled. In this case, the power flows in the controlled lines are determined by linearized formulas using the power distribution coefficients of the nodes. The economic effect on the total fuel consumption due to the use of the proposed algorithm is 0.45%. [ABSTRACT FROM AUTHOR]

Routing in Wireless-Sensor-Network is an indispensable research area where continuous improvements are needed as the junctions are resource constrained. The junctions in the WSN when optimized with routing showing, it leads to increase of lifetime of WSN besides other showing benefits. Many nature-inspired routing enhancement algorithms came into existence as found in the literature. In this paper we proposed an Enhanced Flower –Pollination-Optimization (E-FPO) that has features such as computing junction localization and find shortest path for routing more efficiently. There are mechanisms in the algorithm that results in energy efficiency. It monitors sensed data of junctions and data density to make well informed decisions. A grouping approach with filter convention is used to leverage showing. The grouping of data and filtering besides finding best possible pat makes the algorithm better than its predecessors like LEACH. A simulation study is made to have empirical observations. The results show that the proposed E-FPOA showed better showing in terms of many metrics including lifetime of WSN. In fact, E-FPOA outperforms LEACH with 35% better lifetime showing. [ABSTRACT FROM AUTHOR]

This paper studies one of the important structural methods in the classification of texture images, which is scale-invariant feature transform (SIFT), where the Brodatz database was used as sample images to test the proposed algorithm. The k-mean classifier and the frequency density function are used to classify the images based on classifying the obtained feature pointsﻭ where an analysis of the proposed classification algorithm is presented. The results confirmed the possibility of the proposed algorithm in classifying histological images. [ABSTRACT FROM AUTHOR]