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Feature selection is an important technique in building prediction systems. In various searches, the judgment of the relevancy of a feature is often calculated using all the instances of the considered sample. However, when the dataset size grows, some of the instances are not useful for weighting the features. In this paper, we rank features according to a fitness function that relies on the relevancy using all instances and on the relevancy using a maximum number of significant instances (which really contribute to the feature positive relevancy with the target variable). The relevancy is based on preordonnances theory where the instances are expressed in pairs. The proposed algorithm can be mainly divided into three steps, namely, (a) eliminating all features that are in disagree with the target feature, (b) Finding the best subset of instances, to each feature, that maximize the relevancy and which the cardinal tends to the cardinal of instances in the original dataset, and (c) Ranking features. The second step is defined by dividing the dataset (instances of each feature) into several consistent regions by fuzzy clustering. Then, performing GA-based instances selection independently within each cluster. Finally, aggregating of the partial results by the ensemble voting. Experimental results verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Uncertainties, parameters variations and external disturbances may affect highly the task of lane-keeping, lane-changing and path-tacking autonomous vehicles. This paper presents a novel variable gains second-order sliding mode algorithm for en-hanced path tracking performance of autonomous vehicles subject to uncertainties and disturbances. The used algorithm is a modified super-twisting with both nonlinear and linear correction terms. Hence, the proposed method doesn't suffer from the chattering phenomenon, ensures high order precision and guarantees both the robustness against perturbations and the convergence in finite-time during the reaching phase. To evaluate the efficiency of the developed approach, a double lane-changing scenario is considered in simulation for an uncertain autonomous vehicle and the results are compared with the first-order sliding mode. [ABSTRACT FROM AUTHOR]

The concept of web of things (WoT) is to connect anything in the physical world and then display them in the World Wide Web, that is the major objective, but that mean information storage or transfer that led to thinking how can protected this information from attacks, this can happen by protected information by encryption it. Cryptography and chaos inextricably linked because of many features. In this paper uses a novel model for the encryption of information via WoT, we suggest HIGHT and Simon as a block cipher algorithm using for lightweight encryption by make a new hybrid between them. Also use chaotic system to take key from it; moreover, we use other operations to arrive the best result. [ABSTRACT FROM AUTHOR]

Path planning algorithms is the most significant area in the robotics field. Path Planning (PP) can be defined as the process of determining the most appropriate navigation path before a mobile robot moves. The goal of optimization of PP is to find a path that is close to or optimal path. Multi-objective optimization (MOO) is concerned with finding the best solution values that satisfy multiple objectives, such as shortness, smoothness, and safety. MOO present the challenge of making decisions while balancing these contradictory issues through compromise (tradeoff). As a result, there is no single solution appropriate for all purposes in MOO, but rather a range of solutions. This paper the problem of PP is investigated with path length, security and smoothness objectives for autonomous mobile robots in dynamic environment with moving target. The proposed approach based on Bat algorithm (BA). The proposed solution is tested in a number of simulations with varying scenarios. The simulation results show that multi objective can be achieved efficiently in a dynamic environment which proves its effectiveness. [ABSTRACT FROM AUTHOR]

During pandemic circumstance world, the size of data is exploded like rocket speed. At the same time, there is a need to process it and investigate the enormous volumes of information. The company and research tool is Hadoop and is most broadly utilized in information serious applications. The Hadoop default processing nature is homogeneous. The limit of enormous measure of data in Hadoop is finished utilizing Hadoop Distributed File System. The performance is degraded when it applied to heterogeneous environment. Hadoop mainly uses 2 components viz HDFS used for storage purpose and MapReduce used for programming. In this paper we introduce Optimal Data Placement Algorithm (ODPA). [ABSTRACT FROM AUTHOR]

The real world has been changed into a virtual one as a result of the pandemic scenario. Cloud computing plays a major role for storing and computing the data using remote computing infrastructure for solving the day to day activities. The LB Techniques are used in the cloud computing process. LB techniques distributing the system's load among its various nodes in order to maximise resource efficiency and job response time. The major issues in load balancing are Geographical Distributed system, Single point of failure (SPoF), live Migration of instance, Heterogeneous device, Storage device Management, Scale-out/scale-in and Complexity of Algorithm. Load balancing ensures that each node in the network shortens reaction times, reduces expenses, and boosts performance. This paper address the various cloud computing balancing algorithm survey. [ABSTRACT FROM AUTHOR]

Today's modern world is being driven towards automation and as well gathering any type of information from every nook and corner of the world which is possible through one of the technology named Internet of Things(IoT). IoT is not just a single technology but it is a combination of various technologies like embedded systems, wireless sensor networks, cloud computing etc. Basic IoT network consists of various layers; one among them is the device layer which is the base layer responsible for gathering the data from physical world through the sensors. Various sensors can be deployed into an area depending upon the type of application it is used for. Various homogenous sensors can be made into clusters due to which it would be beneficiary in terms of bandwidth and power consumption, number of internet connections required, fault tolerance, longevity of devices etc. This paper presents a comparison between various algorithms used to cluster the sensors at device level. [ABSTRACT FROM AUTHOR]

By using thoracic electrical bioimpedance (TEB) analysis stroke volume calculated for sudden cardiac arrests. In this paper proposed robust normalized diffusion least power algorithm (RNDLPA) is proposed to get high resolution components. In clinical scenarios, TEB components are contaminated with various artifact components, which interrupts the identification of several features in stroke intensity. The number of multiplications is also one of the key elements for monitoring in health care applications. Hence by proposed RNDLPA algorithm it reduces computational complexity, stability is improved and also steady state error rate is reduced. To eliminate noise components various adaptive cancelers are presented and they are compared with proposed algorithm. Further to show performance improvement signal to noise ratio (SNR) improvement is taken into consideration it gets better values 14.3594 dB and 12.3551 dB for respiratory noise and muscle noise respectively when compared to existed techniques. [ABSTRACT FROM AUTHOR]

Xilinx System Generator (XSG) integrates with MATLAB Simulink to build a complex system through Xilinx and Simulink blocks. This paper presents a hardware implementation of various image processing techniques to modify and extract the pixel information from various input images in run time. Complex coding strategies are eradicated with integrated system. The intricacy in structural design is reduced to a huge extent using Xilinx System generator. The reconfigurable attribute of Field Programmable Gate Array (FPGA) bags the massive advantages in image processing like co simulating with selective pixel and verified on FPGA. Image processing algorithms explored in methodical manner by performing diverse operations like edge detection, and color enhancement, complement, contrast stretching etc. The proposed image processing techniques (IPT) intended for various applications. Dissimilar image processing techniques are processed by FPGA and displayed on Video Graphics Array (VGA). Image processing system is designed in XSG, hardware description language (HDL) like VHDL & Verilog code is generated by processing system by system generator token. Design is implemented on Artix-7 and targeted on Basys3 reconfigurable hardware (XC7A35T-1-CPG236C). [ABSTRACT FROM AUTHOR]

We live in times where technology is advancing at an unprecedent rate. From online communication, shopping, data sharing, cashless payments to transmitting sensitive information through internet, everything is being done online. These online methods of data transfer are always vulnerable to online phishing and frauds. Therefore, it becomes very imperative to devise ways for safe and secure transmission of data. To keep up this, new and secure cryptographic schemes are the need of the modern age. In this paper, the author presents a new improvised encryption technique which makes modifications in the traditional approach of the Caesar cipher by combining it with extended Hill cipher. Additionally, it makes use of the Linear congruential method to generate the randomized secret key. [ABSTRACT FROM AUTHOR]

The paper considers the main methods of testing a software product at the development stage. The methods are compared with typical architectures of software products. The optimization problem of the testing process is solved on the basis of the algorithm development that presents the process under consideration at a more detailed level. The optimization of the algorithm is presented on business processes by BPMN 2.0 notation. [ABSTRACT FROM AUTHOR]

The article presents the software implementation of the bioinspired ant colony algorithm, which is used to form the composition of the multiversion software modules. It is shown that the reliability of programs and performance indicators of multiversion software significantly depend on the results of the design stage, at which a decision is made on the formation of the structure of the program complex and the choice of the composition of multiversion software modules. The solution of these problems is supported by the developed software application. The application is focused on the user, who sets all the parameters of the multiversions. Within the framework of the bioinspired approach, the paper presents the main functions implemented in a software package using ant colony algorithms. [ABSTRACT FROM AUTHOR]

Active Contour Model is the most original algorithm among the class of Contour Finding methods. Its capability is tested against wound parameter detection given image data. The performance is less satisfying, in general, few perimeters are found correctly, but the rest are far from ideal. However, through some tuning by adding an extra pre-processing step, the result can be improved. Image Interpolation is used to achieve this improvement. This paper reports how significant the improvement is. [ABSTRACT FROM AUTHOR]

One of the measurements for evaluating time series forecasting performances is the mean square error (MSE). This paper proposes an algorithm to find the smallest MSE. To capture the four components of the time series data (namely, seasonal variation, trend variation, cyclical variation, and random variation), the exponential smoothing method was used. This method uses three factors for smoothing where the data are the smoothing factor, 0 < α < 1, the trend smoothing factor, 0 < γ < 1, and the seasonal change smoothing factor, 0 < β < 1. First, all possible combination values of smoothing factors will be generated to one decimal digit. After that, the smallest MSE of those combinations will be determined by using an algorithm and observing their convergence pattern. [ABSTRACT FROM AUTHOR]

In this paper, we propose a modified mean-variance portfolio selection procedure using the proximal gradient method. This novel selection procedure has the advantage of encouraging sparsity in the entire portfolio usingl0−norm while requiring only O(n) storage. The proximal gradient method (PSG) introduces a multiple damping gradient (MDG) method to reduce the computation time, with Lipschitz constant serving as the step size, and iterative thresholding (IHT) as the proximal method to induce the sparsity of the portfolio. To find the optimal portfolio, an efficient algorithm is developed. The performance of the proposed selection procedure is illustrated by its application to real-life data set. It is shown that the proposed portfolio performs consistently better in comparison with other methods. [ABSTRACT FROM AUTHOR]

The emerging growth of edge devices and the expansion of IoT systems produced the demand to enhance their security algorithms to run on diverse applications and appliances. Lightweight cipher algorithms are mainly designed for IoT-constrained devices. Thus, due to the new services and applications of IoT that require extensive networks and devices, the need for efficient lightweight cipher algorithm implementations is a critical issue. In this paper, an enhanced cipher LED-128 algorithm based on Galois Fields (GF) operations is presented. The mathematical model of the LED algorithm simply requires a slight execution time for encryption-decryption processing. The Enhanced LED algorithm is applied with 64 bits of block plaintext and 128 bits of the key size which turn out 64 bits block size of ciphertext. The proposed algorithm is presented to advance the randomness of cipher text by enhancing the key schedule based on GF operations. The developed key schedule is enhanced to generate a robust key for the proposed algorithm. The NIST statistical tests have been examined and experimented for the proposed enhanced algorithm by utilizing diverse keys with distinct cipher text, which passed the randomness for each test. The proposed algorithm demonstrated a high confusion and diffusion based on the correlation coefficient analysis. The executed time for the encryption and decryption processes of the proposed enhanced LED algorithm is concentrated at minimum compared to the original LED-128 cipher algorithm. Hence, the proposed enhanced algorithm can be implemented for diverse IoT systems and can reach the trade-off between cost and performance as an efficient lightweight algorithm. The results of the enhanced algorithm are benchmarked with the current LED 64/128 algorithms and presented significant improvements in the performance compared to original design of the LED cipher algorithm. [ABSTRACT FROM AUTHOR]

This paper aims to apply two variants of the hybrid optimization algorithm, namely Chaotic Honey Badger Algorithm (CHBA) and Group Teaching Optimization Algorithm (GTOA) to solve the Uncapacitated Facility Location Problem (UFLP). We enhance using chaotic maps on the HBA to strengthen the search process and hybridization with GTOA leads to a fast exploration process in finding the best solution. There are two variants of hybrid CHBA and GTOA applied. In the first variant, GTOA is applied to determine the initial population of CHBA, then for the second variant, CHBA is used to determine the initial population of GTOA. The performance of these two hybrid variants is used to solve the Uncapacitated Facility Location Problem (UFLP). There were three types of data for UFLP such as small data, medium data, and large data. Furthermore, by comparing the best results it was concluded that hybrid variant GTOA-CHBA has better solution than CHBA-GTOA. The results of the hybrid were compared with other algorithms such as Cuckoo Search (CS), Flower Pollination Algorithm (FPA), and Teaching Learning Based Optimization (TLBO). It was concluded that the average of hybrid GTOA-CHBA better than each algorithm. In terms of best and PRDmin, the hybrid GTOA-CHBA on several data has good results from the other algorithms. [ABSTRACT FROM AUTHOR]

Three contributions are presented in this paper. Designing two cascade controllers to control the position of two brushless DC motors (BLDC) working together at the same time is the first contribution. The second is using a sliding mode speed synchronization controller to connect these motors and fine-tune the precise synchronization of their movement on the axes. In the third contribution, the best parameter values for the two cascade controllers and the synchronization controller are extracted using the salp swarm algorithm (SSA) and the objective function Integral Time Absolute Error (ITAE) to produce the most accurate results. the results were compared by using this algorithm with manual tuning. The results of the simulation revealed that the tuning that was done by the salp swarm algorithm (SSA) was superior to the manual tuning in terms of performance and overshoot as well as any deviation in tracking the path to reach the intended position. note that the drop in velocity (0.11 rad/sec) at a time of 15 seconds because of the load causes deviations (0.343 rad for BLDC 1 and 0.3496 rad for BLDC 2) For manual tuning. while the drop in velocity is very small (0.0037 rad/sec) at the same time causes deviations very small (0.003 rad for BLDC 1 and 0.0052 rad for BLDC 2) for second tuning. [ABSTRACT FROM AUTHOR]

Currently, the quality management of production processes is not only an integral part of the enterprise management system, but also largely determines the ability to meet the needs of consumers with minimal production costs. In this regard, the paper considers one of the modern methods of quality management, based on the probabilistic assessment of the qualitative completion of the stages of the process under study. This approach takes into account the sequential dependence of the production stages, as well as the joint impact of measures aimed at effective process management. At the same time, the costs of the activities carried out must be minimized. The subject of this paper is a mathematical problem of operational management of multi-stage production processes with consistently interrelated stages based on a probabilistic approach to quality assessment. An algorithm for solving the problem and its software implementation in the form of an application is presented. The software product is acceptable for practical use and allows you to optimally choose the measures of influence on consistently interrelated stages of the process. [ABSTRACT FROM AUTHOR]

This paper presents the developed algorithms for a tool environment for the design of complex information systems based on automata models using the algebra of high-dimensional vectors. The paper raises the problem of the little knowledge of methods of coding complex systems in the format of automata based on the algebra of hyperdimensional vectors. Methods of formalized description of systems in the form of hyperdimensional vectors and description of algorithms for transformation of formalized description using the algebra of hyperdimensional vectors are introduced. The features, advantages and disadvantages of modeling automata models using hyperdimensional vectors are listed. [ABSTRACT FROM AUTHOR]

The paper presents quasy-steady thermodynamics model of ice formation on the aircraft surface of a streamlined body. Numerical methods for solving thermodynamics equations are proposed. Test cases for moist gas flow around the NACA 0012 airfoil and the GLC-305 wing are given. The results are compared with the experimental data to validate the adequacy and the accuracy of models and algorithms. Conclusions about application of algorithm for forecasting the ice accretion on the aircraft elements using proposed approach are given. [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]

The methodology of functional modeling provides visual and understandable means of describing the domain for a wide range of specialists. The paper proposes a formal language for describing a functional model based on graph theory. Within this language, each functional diagram is represented as a graph with marked edges. The nodes of this graph define the function blocks, the edges correspond to the arrows of the diagram. We develop rules for diagram bounds description with special nodes, the arrows positions using the system of roles, branching arrows as a set of special nodes and multiple edges. The hierarchy which links individual diagrams into a single model, is defined by the relation of decomposition on graphs. We form rules that connect the arrows of the parent and child functional diagrams in correctly constructed functional models. To verify these rules, a functional model verification algorithm has been developed. This algorithm is implemented by means of logic programming using the PROLOG language. The structure of the fact base for describing the relations of decomposition, nodes, and edges of graphs is proposed. A set of predicates is provided to verify the correctness of the functional model description. [ABSTRACT FROM AUTHOR]

Software defect estimation is an approach aiming to make an estimation of which algorithms can predict defects present in the software. This will help in improving the software quality which indeed can satisfy customers. The process is done during the development life cycle so at an early phase which reduces a lot of time and saves cost. Our model is going to be efficient because it can improve the performances and also give better results by estimation results. The main aim of this paper is to evaluate the capability of machine learning algorithms and find the best category while comparing seven machine learning algorithms within the context of NASA datasets obtained from the public PROMISE repository. The best algorithm is the one with highest accuracy rates. [ABSTRACT FROM AUTHOR]

The development of modern mobile robots is often connected with advanced reliability, especially in undetermined conditions. One widespread reason for robotic mission failures is robot tip-over. In this paper, a method to avoid tip-over is proposed based on the existing tip-over detection methods in application to a mobile robot with two arms. The method has been validated in Matlab/CoppeliaSim co-simulation environment. [ABSTRACT FROM AUTHOR]

The paper considers the algorithm for solving axisymmetric contact problems of thermoelasticity, taking into account the processes of creep. To take into account the contact interaction of bodies, the mortar method was used, the modified symmetric successive upper relaxation method (MSSOR) was used to solve the obtained system of linear equations. For the numerical solution of the problem modeling the creep process, time discretization based on the implicit Euler method was applied, the Newton method was used to linearize the resulting system of equations. An algorithm with automatic step selection based on obtaining an estimate of local error of the method is proposed. The results of the application of the proposed a lgorithm to the demo problem, which simulate thermomechanical processes in the section of the fuel element, which includes from 1 to 10 fuel pellets are presented. [ABSTRACT FROM AUTHOR]

Optimization problems are interest and common problems that are often encountered in life. Optimization can be applied to solve various problems, for example development, government, business, social, economic and something related to the limitation of resource capacity. The most frequently encountered, optimization is often used to find the best solution, that is maximizing profits or minimizing production costs. One of the optimization problems that often occurs is the knapsack problem. There are several types of knapsack problems, one of which is Modified Bounded Knapsack with Multiple Constraints (MBKMC) problem. In popular mathematical studies, metaheuristic algorithms are very often used to solve optimization problems. In this paper the authors did not only use one algorithm, but implemented two metaheuristic algorithms which were combined into one, namely the Gravitational Search Algorithm (GSA) and the Cat Swarm Optimization (CSO) algorithm. The combined algorithm uses the entire GSA algorithm mechanism which is added with the CSO algorithm seeking mode to become the GSA&sCSO algorithm. The author uses the GSA&sCSO algorithm to solve the MBKMC problem of uncertain coefficient. Based on the results of this research, the GSA&sCSO algorithm produces a better solution (higher profit) than the GSA algorithm and the CSO algorithm and earn a better advantage in accordance with the knapsack capacity. In addition, the uncertain coefficient greatly affects the solution obtained, i.e if there is a change of the coefficient, then the solution also changes. [ABSTRACT FROM AUTHOR]

The Network Design Problem (NDP) is the optimum network expansion planning problem that the branching ought to be involved within the network for obtaining the lowest merit index. This paper aims to apply the branch and bound algorithm to obtain the optimal solution in extend railway (Basrah-faw) project. Numerical experiments show that our algorithm is superior to previous algorithms in terms of both computation time and solution quality. The finding shows that representing the project through a network would facilitate the work of the executing company in calculating the shortest possible time as well as we obtain two paths with lower merit index which gives the flexibility and applicability of our algorithm for the decision maker. [ABSTRACT FROM AUTHOR]

Cloud computing is among the technologies that have become popular in recent times, due to the increasing demand for their use by individuals, companies and organizations. It offers its resources as an online service upon demand by its users. In order to enhance the trust between the cloud and its users, attention must be paid to addressing the issues that the cloud suffers from, the most outstanding of those are problems relating to the safety and privacy of users' data on the cloud. Encryption is considered one of the successful and efficient ways to raise the security of data kept on the cloud by converting it into data that is incomprehensible to unauthorized persons. In our research paper, we will present a method that provides security and privacy for data stored on the cloud, and this method consists of a combination of two lightweight algorithms (mCrypton and salsa20) to form a new lightweight hybrid algorithm based on the mCrypton algorithm, where stages were added to it and other modifications. Additionally, chaos has been added to generate encryption keys. [ABSTRACT FROM AUTHOR]

Traffic congestion is one of the major problems facing drivers all over the world, especially in the urban road network, where lost time and fuel consumption are a major concern. Traffic Signal Control (TSC) can be self-regulating and adaptive to changes in traffic conditions using Vehicle Dedicated Network (VANET) technology and intelligent control algorithm as VANET technology provides comprehensive information on vehicles approaching intersections. Scheduling algorithm for traffic lights in VANET scenario shows low performance with large coverage area. This is, most probably, because an intersection is considered to be isolated under a small coverage area. As the area increases, especially in large cities, such a consideration is not suitable. Hence, a scheduling algorithm for traffic lights in a VANET scenario is investigated and developed in this paper under different coverage areas. The main objects here are to alleviate the problem of traffic congestion and shorten vehicle wait times at an intersection in Ramadi city as a case study. Instead of using a scheduling algorithm with a fixed maximum green time, an adaptive time is proposed according to coverage area. The orders of vehicles that have arrived or will arrive at the intersection make maximum green time adaptive. The developed algorithm is simulated for different coverage areas and interesting results are shown in detail. The results showed the superiority of the developed scheduling algorithm over the traditional system used in the intersection, and this algorithm is suitable for non-isolated intersections because even outgoing vehicles from an intersection can be taken into consideration. [ABSTRACT FROM AUTHOR]

Numerous researchers have applied nature-inspired population-based metaheuristics for solving optimization problems including data clustering. However, the issues of premature convergence and slow convergence rate can still occur when these promising search methods are applied to complex and large data-clustering problems, including the evaporation-rate based water cycle algorithm, WCAER. In this paper, a recently proposed hybrid version of WCAER in conjunction with a local search method named Hookes and Jeeves method was further tested to perform data clustering for large dataset. The proposed hybrid algorithm is experimented on the gas turbine emission data that contains 36733 instances of 11 sensor measures aggregated over one hour, from a gas turbine in Turkey, available from the UCI machine-learning repository. The simulation results confirm the superiority of the hybrid method as an efficient and reliable algorithm to solve gas turbine clustering problem, in comparison to the original evaporation-rate based water cycle algorithm, in terms of solution quality as well as computational performance formulated from two applied objective functions namely the Euclidean distance and the Davies-Bouldin index. Thus, the outcome of the study generally provides some performance evaluation of WCAER for large dataset when applied in cluster analysis, a valuable data analysis and data mining technique. It is hoped that other metaheuristics could be applied to the 5 years span large dataset for performance comparison with other further considerations such as using various suitable objective functions and cluster validity indices. [ABSTRACT FROM AUTHOR]

With increasing number of applications of Unmanned Aerial Vehicles (UAVs) in civilian sectors, enthusiasts are finding ways to build their own UAV which can be used for jobs that are too dull, dirty or dangerous for humans. Design of UAVs may vary according to their respective mission and payload requirements. The algorithm asks for the specific requirements of the user such as payload weight & volumetric dimensions, maximum speed at which UAV is supposed to fly etc. The process includes aerodynamic analysis of numerous airfoils and selecting the optimum one, calculating wing-span required with the selected airfoil cross section to attain required lift, reducing drag, maintaining stability of aircraft etc. This process is iterative and can take lot of time. Here arose a need to make this process automatic with the help of computer by developing an algorithm which can save lot of time for the people who have to work from scratch in order to make an UAV. In this research paper an effort is made to establish a computer-based algorithm for design and development of a flying wing UAV using MATLAB. [ABSTRACT FROM AUTHOR]

Many research paid much attention to attain robot automation for implementation in several industrial applications. In order to improve the robot guidance, the methods of robot path planning are modified. This paper proposed the hybridization of the artificial potential field and firefly algorithm for path planning of the robot in the dynamic environment. The artificial potential field is applied to analyze the environment and provide the guiding force. The firefly algorithm is applied to select the best next movement of the robot within a specific distance. The essential function of the firefly algorithm is to select randomly potential field forces and determine the best next point. The firefly algorithm depends on the iterative update of the total potential for the environment that contains the dynamic obstacles. The collision check function is used to avoid select the point from the distance of dynamic obstacle influence. The proposed method is applied to find the robot path in the tested environment consists of moving obstacles only. The demonstrated results of applied the hybridization method represent the efficiency of the proposed method performance in finding the robot path in the dynamic environment with minimum cost and avoiding all the dynamic obstacles. And the hybridization method guarantee finds the shortest path in the case of various environments' complexity with free-collision with dynamic obstacles. [ABSTRACT FROM AUTHOR]

In this paper we build a constructive algorithm that returns a rectifiable curve that connects two points in a weakly convex set in a Hilbert space. We have proven that this algorithm converges and obtained an estimate on the curve's length and compare the length of the curve obtained to known results. [ABSTRACT FROM AUTHOR]

OCR post-processing is an important step to improve OCR text accuracy. It includes two main tasks, error detection and error correction. Hill climbing algorithm is a heuristic search method used for solving optimization problems. In this paper, we present a novel OCR error correction approach using an adapted version of the Hill climbing algorithm. Correction candidates of OCR errors are explored by random character edits and evolved with the Hill climbing. The character edit patterns are obtained from the training data. The proposed model is evaluated on the benchmark dataset in the OCR post-correction competition of the International Conference on Document Analysis and Recognition 2017. It is shown that our model outperforms various baseline approaches in the competition. In addition, the randomness of the proposed algorithm is analyzed to verify its stability under parameter configurations. [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]

In this paper we present formulations of flow laws and evolutive laws in non-smooth plasticity. This formulations are suitable for non-smooth problems in plasticity theory. The tools of convex analysis is adopted in order to properly treat non-differentiable functions. Within this framework generalized forms of flow laws and complimentarity conditions are expressed. The treatment is particularly useful for variational formulations and for the development of computational algorithms in non-smooth plasticity problems. [ABSTRACT FROM AUTHOR]

For the past few years, the Third Generation Partnership Project (3GPP) has introduced the Long-Term Evolution (LTE) as a critical answer to supporting the users' demand for a faster data connection. Nevertheless, another problem arises as the users move from one location to another; they will face a service interruption. As a result, switching from one base station to another base station is required. This process is known as handover. The LTE handover can be done using two algorithms: the A3RSRP and A2A4RSRQ. Both algorithms are associated with two Handover Control Parameters (HCPs). Earlier, many studies have been conducted to evaluate the handover algorithms' impact on the LTE network of Handover Control Parameters (HCPs). However, the studies solely focused on the Quality of Service (QoS), thus neglecting the Quality of Experience (QoE). Therefore, this paper presents an empirical analysis of the impact of the Handover Control Parameters based on user trajectories in terms of the QoS (Throughput and delay) and QoE (time to complete file download). The study found that the A2A4RSRQ algorithm performed better than the A3RSRP algorithm once the mobile user moved in a range of Angle-1 and Angle-2 directions. On the other side, different Handover Control Parameters should be assigned based on user trajectories to obtain good handover performances. [ABSTRACT FROM AUTHOR]

Slime mould Algorithm (SMA) is modern meta–heuristic algorithm that is depended on the mechanism of swarming of slimes. SMA considers one of the good algorithms in the field of intelligence optimization. In this paper we proposed a new binary Slime mould Algorithm to depend on transformation function which converts the continuous space to discrete space. The purpose of create this algorithm is to use in the feature selections. The new algorithm used with different dataset and compared with different algorithm. The results of numerical experimental showed that the proposed algorithm have a good performance compared with other algorithm. [ABSTRACT FROM AUTHOR]

In modern systems of automated architectural and construction design, the method of creating three-dimensional models of objects under development is widely used. This method allows to visualize the object, determine various geometric object parameters, calculate its strength characteristics, solve issues related to production technology, etc. In most up-to-date graphics systems, standard solid-state objects, such as a parallelepiped, a cylinder, a ball, etc., are used as input data when creating three-dimensional models. At the same time, when creating complex models consisting of standard bodies, it is nec-essary to determine the type of object, its position and geometric parameters. The paper considers algorithms for recognizing some standard solids and determining their basic geometric parameters. The algorithms are implemented using ObjectARX technology for the AutoCAD system. The algorithms developed in the article can be applied in the problems of designing various objects, using technologies for creating three-dimensional models. [ABSTRACT FROM AUTHOR]

AES as a block cipher considers as one of the most important security applications that provides confidentiality through encryption. However, AES cryptosystem is under analyzing by cryptanalysts using the computing technologies that have rapidly progressed. Therefore, the possibility of breaking AES algorithm might be accelerated in anytime. Consequently, this paper improves the AES security against a possible future attack. It proposes a model that has the ability to encrypt data with block size 256-bit and a key size of 256-bits. In addition, it also uses S-box of the serpent algorithm to be replaced the original S-box of the AES cryptosystem. The implementation of the proposed idea shows that the time requirements is acceptable even if the shifting algorithm is applied in two directions on row and column. Moreover, the randomness of the modified algorithm remains high. [ABSTRACT FROM AUTHOR]

In the last decade, a scientific workflow has become the dominant trend to enable specialists to accelerate scientific developments in various areas. The scientific workflow requires high computing, therefore, cloud computing is exploited, as it provides the computing required for scientific workflow with a good cost. The frequent use of scientific workflows by researchers in cloud computing stimulates the need to find mechanisms to manage scientific workflow, providing resources, and scheduling in a way that achieves fairness for all users and meets the required Quality of Service (QoS). In a cloud computing environment, scheduling scientific workflows is an NP-hard problem. A lot of work has been done to resolve the decision problem of scheduling workflows, provision of resources, or both. In this survey, many papers related to scientific workflow algorithms of provisioning and scheduling in a cloud computing system are reviewed. We investigate and classify numerous related articles in the field. The objectives of each study, the application domains, and tools that were used are highlighted. [ABSTRACT FROM AUTHOR]

The Advanced Encryption Standard (AES) algorithm is a symmetric encryption algorithm which is much faster, secure and consumes less power when compared to the previous cryptographic algorithms like DES and RSA. It can be implemented in software as well as hardware. The paper compares the advantages and disadvantages of various implementation of AES algorithm and proposes the design of standard cells and macro cells for Application-Specific Integrated Circuit (ASIC) of AES. A total of 212 standard cells and 20405 instances were designed and implemented using cadence virtuoso. The cells were fully custom designed using 45 nm technology with minimum channel length of 50 nm. The total number of cells in proposed implementation was lesser than other ASIC implementations. There was a significant percentage of decrease in area, power and timing constraints when compared to GPDK045_SC. [ABSTRACT FROM AUTHOR]

This manuscript introduces a valid strategy to prove the optimization problem is the NP_Hardness problem. First of all, K-cluster is one of the most important NP-hardness problems of combinatorial optimization problems. Secondly, a problem is hard if it cannot be solved by a feasible (polynomial time) algorithm; i.e. the hard problem cannot be solved in particular. Furthermore, the strategy of this paper is to use a technique to show the problem is NP-Hard. Finally, the problem is NP-Hard if every problem from NP can be reduced to that which is means reductions proven. [ABSTRACT FROM AUTHOR]

Chaos-based cryptographic algorithm has proposed to build reliable image encryption techniques in recent years. This paper. Presents a partial encryption method for grey images focused on α (the critical region) that determined by the contribution of a of significance bit plane's level. The method using Henon Chaos Map and DNA coding in image encryption. Using henon map gives the algorithm wide range of randomness distribution bits, the DNA provides high capacity in transmitting information and enhance computational speed. The efficacy of the proposal algorithm security was tested using histogram analysis, correlation test, entropy test, NPCR, UACI. [ABSTRACT FROM AUTHOR]

The job sequencing technique is used to determine the best order in which jobs should be processed on different machines. In this paper, we propose a novel method for determining the best job sequence. Optimal sequence computed using the proposed algorithm, minimizes the total elapsed and idle time. Numerical illustration is also provided. [ABSTRACT FROM AUTHOR]

In a present world, some of the incident has occurred on without the any prior information. In this case our entire human society (survival, health etc.) and industrial peoples are affected in many parameters. For particularly transportation is most important need of day to day life. So, in this paper we consider the above situation and to analyze the optimization range value of neutrosophic transportation problem. In this article intends to develop the algorithm of transportation problem on neutrosophic environment. An example is included. [ABSTRACT FROM AUTHOR]

In this paper a different solutions approach for the replacement problem has discussed under fuzzy environment. This different approach is used to find the optimal age of the machine, which we have used to find the best machine by comparing the two different machines. We have developed new algorithm and a theorem also proved based on it. [ABSTRACT FROM AUTHOR]

In machining operation, there is frequent tool wearing and breakage. Many a times, the root cause for early failure of tool is inappropriate cutting forces. In milling operation, cutting force is an intrinsic phenomenon which plays important role in machine tool conditioning. Prediction of the cutting force by traditional modelling methods becomes time consuming and costly. Artificial Neural Network (ANN) gives an easier way of predicting force model in case of machining operations and it is best technique to be used when the process is non-linear and as the milling operation is non-linear and time dependent. This technique gives good result in lesser time. In this paper three feed forward backpropagation algorithms are compared on the basis of six different criterion to decide the best suited algorithm for predicting the cutting force in face milling. [ABSTRACT FROM AUTHOR]

Several picture encryption techniques have been developed in recent years. This work proposes a supported and advanced encryption technology and encryption, 2D encryption picture encryption method on paper. The sha-256 method removes picture components first, then generates a replacement key that matches the user's key before inserting the original image. For every grey image size, we enable rows and columns in the same order by the same members created by the Logistic map. We determine the beginning values and parameters of complicated maps using the sha-256 hash of a clear image, making an important change in all encryptions without modifying the standard keys. Finally, the method is used to recover the encrypted picture. The system can accomplish good encryption results and security standards, according to test findings and security analyses. Data transmission over the Internet and personal networks has risen day by day as multimedia technology has advanced. As a result, today's main focus is safeguarding data from unauthorised access and encrypting multimedia elements as they are stored on web servers and sent over networks. As a result, data encryption for multimedia is necessary. The multimedia encryption approach, on the other hand, is difficult to apply since it requires more time and memory. [ABSTRACT FROM AUTHOR]