Although, Integer Factorization is one of the hard problems to break RSA, many factoring techniques are still developed. Fermat’s Factorization Algorithm (FFA) which has very high performance when prime factors are close to each other is a type of integer factorization algorithms. In fact, there are two ways to implement FFA. The first is called FFA-1, it is a process to find the integer from square root computing. Because this operation takes high computation cost, it consumes high computation time to find the result. The other method is called FFA-2 which is the different technique to find prime factors. Although the computation loops are quite large, there is no square root computing included into the computation. In this paper, the new efficient factorization algorithm is introduced. Euler’s theorem is chosen to apply with FFA to find the addition result between two prime factors. The advantage of the proposed method is that almost of square root operations are left out from the computation while loops are not increased, they are equal to the first method. Therefore, if the proposed method is compared with the FFA-1, it implies that the computation time is decreased, because there is no the square root operation and the loops are same. On the other hand, the loops of the proposed method are less than the second method. Therefore, time is also reduced. Furthermore, the proposed method can be also selected to apply with many methods which are modified from FFA to decrease more cost.
IRJET- Design of Photovoltaic System using Fuzzy Logic ControllerIRJET Journal
This document describes a study that assesses the use of a fuzzy logic controller in a standalone photovoltaic (PV) system. The PV system was designed and simulated in MATLAB/Simulink. A fuzzy logic controller was used for maximum power point tracking (MPPT) to dynamically adjust the duty cycle of a boost converter connected to the PV panels. The performance of the fuzzy logic controller was evaluated under constant and varying weather conditions in terms of output power efficiency, dynamic response, and output ripples. Results showed the controller was able to efficiently track the maximum power point with output power reaching 98.66% of the target under constant conditions.
Comparative study of fuzzy logic and ann for short term load forecastingeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
AN OPTIMAL FUZZY LOGIC SYSTEM FOR A NONLINEAR DYNAMIC SYSTEM USING A FUZZY BA...IJCNCJournal
The impetus for this paper is the development of Fuzzy Basis Function “FBF” that assigns in an optimal fashion, a function approximation for a nonlinear dynamic system. A fuzzy basis function is applied to find the best location of the characteristic points by specifying the set of fuzzy rules. The advantage of this technique is that, it may produce a simple and well-performing system because it selects the most significant fuzzy basis functions to minimize an objective function in the output error for the fuzzy rules. The fuzzy basis function is a linguistic fuzzy IF_THEN rule. It provides a combination of the numerical information and the linguistic information in the form input-output pairs and in the form of fuzzy rules. The proposed control scheme is applied to a magnetic ball suspension system.
This document proposes an approach for automatic programming using deep learning. It describes a hybrid method using generative recurrent neural networks trained on source code to generate predictions, which are then used to build abstract syntax trees (ASTs) representing potential code structures. The ASTs are combined and mutated using techniques from genetic programming and random forests. Experimental results found the method was able to generate functions like computing the square root using an iterative method, demonstrating it can generalize logical algorithms from short descriptions. The document outlines the scope of the problem and approach, and describes using a GitHub scraper to collect a dataset of relevant Python source code files to train and evaluate the models.
This document provides an introduction to data structures and algorithms. It defines data as quantities, characters, or symbols operated on by a computer. Data structures are described as organized ways to store and access data efficiently. Common data structures include arrays, linked lists, trees, stacks, and queues. Algorithms are sets of instructions to solve problems, taking input and producing output. Good algorithms are correct, unambiguous, and efficient. Examples demonstrate data structures like arrays and graphs, as well as a simple maximum-finding algorithm. The conclusion emphasizes the importance of data structures.
IRJET - Comparative Study of Flight Delay Prediction using Back Propagati...IRJET Journal
This document describes a study that compares using backpropagation and radial basis function neural networks to predict flight delays. The study uses historical flight data to train models to predict delays. Both algorithms are described and their methodology is outlined. The data will be preprocessed, split for training and testing models, and then the models will be evaluated and compared to determine the most accurate for predicting flight delays.
IRJET- Design of Photovoltaic System using Fuzzy Logic ControllerIRJET Journal
This document describes a study that assesses the use of a fuzzy logic controller in a standalone photovoltaic (PV) system. The PV system was designed and simulated in MATLAB/Simulink. A fuzzy logic controller was used for maximum power point tracking (MPPT) to dynamically adjust the duty cycle of a boost converter connected to the PV panels. The performance of the fuzzy logic controller was evaluated under constant and varying weather conditions in terms of output power efficiency, dynamic response, and output ripples. Results showed the controller was able to efficiently track the maximum power point with output power reaching 98.66% of the target under constant conditions.
Comparative study of fuzzy logic and ann for short term load forecastingeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
AN OPTIMAL FUZZY LOGIC SYSTEM FOR A NONLINEAR DYNAMIC SYSTEM USING A FUZZY BA...IJCNCJournal
The impetus for this paper is the development of Fuzzy Basis Function “FBF” that assigns in an optimal fashion, a function approximation for a nonlinear dynamic system. A fuzzy basis function is applied to find the best location of the characteristic points by specifying the set of fuzzy rules. The advantage of this technique is that, it may produce a simple and well-performing system because it selects the most significant fuzzy basis functions to minimize an objective function in the output error for the fuzzy rules. The fuzzy basis function is a linguistic fuzzy IF_THEN rule. It provides a combination of the numerical information and the linguistic information in the form input-output pairs and in the form of fuzzy rules. The proposed control scheme is applied to a magnetic ball suspension system.
This document proposes an approach for automatic programming using deep learning. It describes a hybrid method using generative recurrent neural networks trained on source code to generate predictions, which are then used to build abstract syntax trees (ASTs) representing potential code structures. The ASTs are combined and mutated using techniques from genetic programming and random forests. Experimental results found the method was able to generate functions like computing the square root using an iterative method, demonstrating it can generalize logical algorithms from short descriptions. The document outlines the scope of the problem and approach, and describes using a GitHub scraper to collect a dataset of relevant Python source code files to train and evaluate the models.
This document provides an introduction to data structures and algorithms. It defines data as quantities, characters, or symbols operated on by a computer. Data structures are described as organized ways to store and access data efficiently. Common data structures include arrays, linked lists, trees, stacks, and queues. Algorithms are sets of instructions to solve problems, taking input and producing output. Good algorithms are correct, unambiguous, and efficient. Examples demonstrate data structures like arrays and graphs, as well as a simple maximum-finding algorithm. The conclusion emphasizes the importance of data structures.
IRJET - Comparative Study of Flight Delay Prediction using Back Propagati...IRJET Journal
This document describes a study that compares using backpropagation and radial basis function neural networks to predict flight delays. The study uses historical flight data to train models to predict delays. Both algorithms are described and their methodology is outlined. The data will be preprocessed, split for training and testing models, and then the models will be evaluated and compared to determine the most accurate for predicting flight delays.
The document describes a study that uses a hybrid neuro-fuzzy (HNF) approach for automatic generation control (AGC) of a two-area interconnected power system. The HNF controller is designed using an adaptive neuro-fuzzy inference system to control frequency and tie-line power deviations. Simulation results show the HNF controller provides improved dynamic response and faster control compared to a conventional PI controller. The HNF approach can handle non-linearities in power systems while providing faster control than other conventional controllers.
This document presents a VHDL implementation of a complex number multiplier using the ancient Vedic mathematics technique known as Urdhva Tiryakbhyam sutra. The implementation is tested on a Spartan 3 FPGA kit. Simulation results show the resource utilization and delay for 4-bit, 8-bit, and 16-bit complex multipliers designed using this Vedic multiplication method. The results indicate that the Urdhva Tiryakbhyam sutra can efficiently implement complex number multiplication with relatively low resource usage and delay, making it suitable for digital signal processing applications requiring extensive complex number operations.
A HYBRID CLUSTERING ALGORITHM FOR DATA MININGcscpconf
The document proposes a hybrid clustering algorithm that combines K-means and K-harmonic mean algorithms. It performs clustering by alternating between using harmonic mean and arithmetic mean to recalculate cluster centers after each iteration. Experimental results on five datasets show the hybrid algorithm produces clusters with lower mean values, indicating tighter grouping, compared to traditional K-means and K-harmonic mean algorithms. The hybrid approach overcomes issues with initialization sensitivity and helps improve computation time and clustering accuracy.
This should give you an idea about how to operate the software. And use it to solve Ordinary Differential Equations. I will be using foggler's book for the examples that have code given with it.
The document presents an optimization algorithm called System Rank Ordering Heuristic (System RO-H) for queries with conjunction of predicates. System RO-H extends the traditional System R optimization algorithm by:
1. Using a heuristic called h-metric to order predicates for joining relations.
2. The h-metric orders predicates in ascending order based on either the predicate's rank or a ratio of selectivity and cost per tuple, whichever is lower.
3. By ordering predicates based on h-metric, System RO-H finds optimal plans in both left-deep and bushy join trees in polynomial time relative to the number of predicates.
The document discusses different sorting algorithms like selection sort and bubble sort. It provides examples of how selection sort and bubble sort work on sample arrays. It also provides C++ code to implement selection sort and bubble sort to sort 5 random numbers entered by the user in ascending order. Selection sort works by selecting the smallest element from the unsorted part and swapping it with the element in the first index of unsorted array. Bubble sort works by repeatedly comparing adjacent elements and swapping them if they are in wrong order.
i-Eclat: performance enhancement of Eclat via incremental approach in frequen...TELKOMNIKA JOURNAL
One example of the state-of-the-art vertical rule mining technique is called equivalence class transformation (Eclat) algorithm. Neither horizontal nor vertical data format, both are still suffering from the huge memory consumption. In response to the promising results of mining in a higher volume of data from a vertical format, and taking consideration of dynamic transaction of data in a database, the research proposes a performance enhancement of Eclat algorithm that relies on incremental approach called an Incremental-Eclat (i-Eclat) algorithm. Motivated from the fast intersection in Eclat, this algorithm of performance enhancement adopts via my structured query language (MySQL) database management system (DBMS) as its platform. It serves as the association rule mining database engine in testing benchmark frequent itemset mining (FIMI) datasets from online repository. The MySQL DBMS is chosen in order to reduce the preprocessing stages of datasets. The experimental results indicate that the proposed algorithm outperforms the traditional Eclat with 17% both in chess and T10I4D100K, 69% in mushroom, 5% and 8% in pumsb_star and retail datasets. Thus, among five (5) dense and sparse datasets, the average performance of i-Eclat is concluded to be 23% better than Eclat.
This document discusses search algorithms, including linear search and binary search. It covers:
1) Linear search sequentially scans an array to find a match, working for both sorted and unsorted arrays.
2) Binary search uses recursion to search a sorted array, eliminating half the search space each iteration, making it faster than linear search.
3) Implementation examples of linear and binary search in Java are provided, along with analysis of the time efficiency of each method.
Available transfer capability computations in the indian southern e.h.v power...eSAT Journals
Abstract This paper presents three methods for computing the available transfer capability (ATC). One method is the conventional method known as continuation repeated power flow (CRPF) and other two are the intelligent techniques known as radial basis function neural network (RBFNN), basic adaptive neuro fuzzy inference system (ANFIS). In these two intelligent techniques, the basic ANFIS works with a multiple input single output (MISO) and it is modified as multiple input multiple output (MIMO) ANFIS using the proposed MIMO ANFIS. The main intension of this proposed method is to utilise the significant features of ANFIS with respect to the multiple outputs, as the basic ANFIS has been proved as the best intelligent techniques in the modelling of any application, but it has a disadvantage of single output and this drawback will be overcome using the proposed MIMO ANFIS. In this paper, the latest Indian southern region extra high voltage (SREHV) 72-bus system considered as test system to obtain the ATC computations using three methods. The ATC computations at desired buses are obtained with and without contingencies and compared the conventional ATC computations with the intelligent techniques. The obtained results are scrupulously verified with different test patterns and observed that the accuracy of proposed method is proved as the best as compared to the other methods for computing ATC. In this way, this paper shows a better way to compute ATC for the different open power market system Keywords— Available Transfer Capability, Total Transfer Capability, Open Power Markets, Repeated Power Flow, Radial Basis Function Neural Networks, Adaptive Neuro Fuzzy Inference System etc.
Simulation design of trajectory planning robot manipulatorjournalBEEI
Robots can be mathematically modeled with computer programs where the results can be displayed visually, so it can be used to determine the input, gain, attenuate and error parameters of the control system. In addition to the robot motion control system, to achieve the target points should need a research to get the best trajectory, so the movement of robots can be more efficient. One method that can be used to get the best path is the SOM (Self Organizing Maps) neural network. This research proposes the usage of SOM in combination with PID and Fuzzy-PD control for finding an optimal path between source and destination. SOM Neural network process is able to guide the robot manipulator through the target points. The results presented emphasize that a satisfactory trajectory tracking precision and stability could be achieved using SOM Neural networking combination with PID and Fuzzy-PD controller.The obtained average error to reach the target point when using Fuzzy-PD=2.225% and when using PID=1.965%.
In this playlist
https://youtube.com/playlist?list=PLT...
I'll illustrate algorithms and data structures course, and implement the data structures using java programming language.
the playlist language is arabic.
The Topics:
--------------------
1- Arrays
2- Linear and Binary search
3- Linked List
4- Recursion
5- Algorithm analysis
6- Stack
7- Queue
8- Binary search tree
9- Selection sort
10- Insertion sort
11- Bubble sort
12- merge sort
13- Quick sort
14- Graphs
15- Hash table
16- Binary Heaps
Reference : Object-Oriented Data Structures Using Java - Third Edition by NELL DALE, DANEIEL T.JOYCE and CHIP WEIMS
Slides is owned by College of Computing & Information Technology
King Abdulaziz University, So thanks alot for these great materials
Linear search examines each element of a list sequentially, one by one, and checks if it is the target value. It has a time complexity of O(n) as it requires searching through each element in the worst case. While simple to implement, linear search is inefficient for large lists as other algorithms like binary search require fewer comparisons.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This document provides an overview of data structures and algorithms. It introduces common linear data structures like stacks, queues, and linked lists. It discusses the need for abstract data types and different data types. It also covers implementing stacks as a linked list and common stack operations. Key applications of stacks include function call stacks which use a LIFO structure to remember the order of function calls and returns.
Improving the initial values of VFactor suitable for balanced modulus IJECEIAES
The aim of this study is to estimate the new initial values of VFactor. In general, this algorithm is one of the members in a group of special proposed integer factorization algorithm. It has very high performance whenever the result of the difference between two prime factors of the modulus is a little, it is also called as balanced modulus. In fact, if this situation is occurred, RSA which is a type of public key cryptosystem will be broken easily. In addition, the main process of VFactor is to increase and decrease two odd integers in order to compute the multiplication until the targets are found. However, the initial values are far from the targets especially that the large value of the difference between two prime factors that is not suitable for VFactor. Therefore, the new initial values which are closer to the targets than the traditional values are proposed to decrease loops of the computation. In experimental results, it is shown that the loops can be decreased about 26% for the example of 256 bits-length of modulus that is from the small result of the difference between prime factors.
IRJET- A Study on Algorithms for FFT ComputationsIRJET Journal
This document analyzes and compares several algorithms for computing the Fast Fourier Transform (FFT), including Radix-2, Radix-4, and Split Radix algorithms. It examines each algorithm in terms of the amount of computations required, computation speed, and memory requirements. The Radix-4 algorithm requires the fewest floating point additions and multiplications, while the Split Radix algorithm has the fastest computation speed, especially for larger data sizes. However, all three algorithms have similar memory requirements. In general, the choice of best algorithm depends on the specific constraints of the application, such as available memory or need for computational speed.
The document describes a study that uses a hybrid neuro-fuzzy (HNF) approach for automatic generation control (AGC) of a two-area interconnected power system. The HNF controller is designed using an adaptive neuro-fuzzy inference system to control frequency and tie-line power deviations. Simulation results show the HNF controller provides improved dynamic response and faster control compared to a conventional PI controller. The HNF approach can handle non-linearities in power systems while providing faster control than other conventional controllers.
This document presents a VHDL implementation of a complex number multiplier using the ancient Vedic mathematics technique known as Urdhva Tiryakbhyam sutra. The implementation is tested on a Spartan 3 FPGA kit. Simulation results show the resource utilization and delay for 4-bit, 8-bit, and 16-bit complex multipliers designed using this Vedic multiplication method. The results indicate that the Urdhva Tiryakbhyam sutra can efficiently implement complex number multiplication with relatively low resource usage and delay, making it suitable for digital signal processing applications requiring extensive complex number operations.
A HYBRID CLUSTERING ALGORITHM FOR DATA MININGcscpconf
The document proposes a hybrid clustering algorithm that combines K-means and K-harmonic mean algorithms. It performs clustering by alternating between using harmonic mean and arithmetic mean to recalculate cluster centers after each iteration. Experimental results on five datasets show the hybrid algorithm produces clusters with lower mean values, indicating tighter grouping, compared to traditional K-means and K-harmonic mean algorithms. The hybrid approach overcomes issues with initialization sensitivity and helps improve computation time and clustering accuracy.
This should give you an idea about how to operate the software. And use it to solve Ordinary Differential Equations. I will be using foggler's book for the examples that have code given with it.
The document presents an optimization algorithm called System Rank Ordering Heuristic (System RO-H) for queries with conjunction of predicates. System RO-H extends the traditional System R optimization algorithm by:
1. Using a heuristic called h-metric to order predicates for joining relations.
2. The h-metric orders predicates in ascending order based on either the predicate's rank or a ratio of selectivity and cost per tuple, whichever is lower.
3. By ordering predicates based on h-metric, System RO-H finds optimal plans in both left-deep and bushy join trees in polynomial time relative to the number of predicates.
The document discusses different sorting algorithms like selection sort and bubble sort. It provides examples of how selection sort and bubble sort work on sample arrays. It also provides C++ code to implement selection sort and bubble sort to sort 5 random numbers entered by the user in ascending order. Selection sort works by selecting the smallest element from the unsorted part and swapping it with the element in the first index of unsorted array. Bubble sort works by repeatedly comparing adjacent elements and swapping them if they are in wrong order.
i-Eclat: performance enhancement of Eclat via incremental approach in frequen...TELKOMNIKA JOURNAL
One example of the state-of-the-art vertical rule mining technique is called equivalence class transformation (Eclat) algorithm. Neither horizontal nor vertical data format, both are still suffering from the huge memory consumption. In response to the promising results of mining in a higher volume of data from a vertical format, and taking consideration of dynamic transaction of data in a database, the research proposes a performance enhancement of Eclat algorithm that relies on incremental approach called an Incremental-Eclat (i-Eclat) algorithm. Motivated from the fast intersection in Eclat, this algorithm of performance enhancement adopts via my structured query language (MySQL) database management system (DBMS) as its platform. It serves as the association rule mining database engine in testing benchmark frequent itemset mining (FIMI) datasets from online repository. The MySQL DBMS is chosen in order to reduce the preprocessing stages of datasets. The experimental results indicate that the proposed algorithm outperforms the traditional Eclat with 17% both in chess and T10I4D100K, 69% in mushroom, 5% and 8% in pumsb_star and retail datasets. Thus, among five (5) dense and sparse datasets, the average performance of i-Eclat is concluded to be 23% better than Eclat.
This document discusses search algorithms, including linear search and binary search. It covers:
1) Linear search sequentially scans an array to find a match, working for both sorted and unsorted arrays.
2) Binary search uses recursion to search a sorted array, eliminating half the search space each iteration, making it faster than linear search.
3) Implementation examples of linear and binary search in Java are provided, along with analysis of the time efficiency of each method.
Available transfer capability computations in the indian southern e.h.v power...eSAT Journals
Abstract This paper presents three methods for computing the available transfer capability (ATC). One method is the conventional method known as continuation repeated power flow (CRPF) and other two are the intelligent techniques known as radial basis function neural network (RBFNN), basic adaptive neuro fuzzy inference system (ANFIS). In these two intelligent techniques, the basic ANFIS works with a multiple input single output (MISO) and it is modified as multiple input multiple output (MIMO) ANFIS using the proposed MIMO ANFIS. The main intension of this proposed method is to utilise the significant features of ANFIS with respect to the multiple outputs, as the basic ANFIS has been proved as the best intelligent techniques in the modelling of any application, but it has a disadvantage of single output and this drawback will be overcome using the proposed MIMO ANFIS. In this paper, the latest Indian southern region extra high voltage (SREHV) 72-bus system considered as test system to obtain the ATC computations using three methods. The ATC computations at desired buses are obtained with and without contingencies and compared the conventional ATC computations with the intelligent techniques. The obtained results are scrupulously verified with different test patterns and observed that the accuracy of proposed method is proved as the best as compared to the other methods for computing ATC. In this way, this paper shows a better way to compute ATC for the different open power market system Keywords— Available Transfer Capability, Total Transfer Capability, Open Power Markets, Repeated Power Flow, Radial Basis Function Neural Networks, Adaptive Neuro Fuzzy Inference System etc.
Simulation design of trajectory planning robot manipulatorjournalBEEI
Robots can be mathematically modeled with computer programs where the results can be displayed visually, so it can be used to determine the input, gain, attenuate and error parameters of the control system. In addition to the robot motion control system, to achieve the target points should need a research to get the best trajectory, so the movement of robots can be more efficient. One method that can be used to get the best path is the SOM (Self Organizing Maps) neural network. This research proposes the usage of SOM in combination with PID and Fuzzy-PD control for finding an optimal path between source and destination. SOM Neural network process is able to guide the robot manipulator through the target points. The results presented emphasize that a satisfactory trajectory tracking precision and stability could be achieved using SOM Neural networking combination with PID and Fuzzy-PD controller.The obtained average error to reach the target point when using Fuzzy-PD=2.225% and when using PID=1.965%.
In this playlist
https://youtube.com/playlist?list=PLT...
I'll illustrate algorithms and data structures course, and implement the data structures using java programming language.
the playlist language is arabic.
The Topics:
--------------------
1- Arrays
2- Linear and Binary search
3- Linked List
4- Recursion
5- Algorithm analysis
6- Stack
7- Queue
8- Binary search tree
9- Selection sort
10- Insertion sort
11- Bubble sort
12- merge sort
13- Quick sort
14- Graphs
15- Hash table
16- Binary Heaps
Reference : Object-Oriented Data Structures Using Java - Third Edition by NELL DALE, DANEIEL T.JOYCE and CHIP WEIMS
Slides is owned by College of Computing & Information Technology
King Abdulaziz University, So thanks alot for these great materials
Linear search examines each element of a list sequentially, one by one, and checks if it is the target value. It has a time complexity of O(n) as it requires searching through each element in the worst case. While simple to implement, linear search is inefficient for large lists as other algorithms like binary search require fewer comparisons.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This document provides an overview of data structures and algorithms. It introduces common linear data structures like stacks, queues, and linked lists. It discusses the need for abstract data types and different data types. It also covers implementing stacks as a linked list and common stack operations. Key applications of stacks include function call stacks which use a LIFO structure to remember the order of function calls and returns.
Improving the initial values of VFactor suitable for balanced modulus IJECEIAES
The aim of this study is to estimate the new initial values of VFactor. In general, this algorithm is one of the members in a group of special proposed integer factorization algorithm. It has very high performance whenever the result of the difference between two prime factors of the modulus is a little, it is also called as balanced modulus. In fact, if this situation is occurred, RSA which is a type of public key cryptosystem will be broken easily. In addition, the main process of VFactor is to increase and decrease two odd integers in order to compute the multiplication until the targets are found. However, the initial values are far from the targets especially that the large value of the difference between two prime factors that is not suitable for VFactor. Therefore, the new initial values which are closer to the targets than the traditional values are proposed to decrease loops of the computation. In experimental results, it is shown that the loops can be decreased about 26% for the example of 256 bits-length of modulus that is from the small result of the difference between prime factors.
IRJET- A Study on Algorithms for FFT ComputationsIRJET Journal
This document analyzes and compares several algorithms for computing the Fast Fourier Transform (FFT), including Radix-2, Radix-4, and Split Radix algorithms. It examines each algorithm in terms of the amount of computations required, computation speed, and memory requirements. The Radix-4 algorithm requires the fewest floating point additions and multiplications, while the Split Radix algorithm has the fastest computation speed, especially for larger data sizes. However, all three algorithms have similar memory requirements. In general, the choice of best algorithm depends on the specific constraints of the application, such as available memory or need for computational speed.
IRJET - Design and Implementation of FFT using Compressor with XOR Gate TopologyIRJET Journal
This document describes a design for implementing a Fast Fourier Transform (FFT) using an adder compressor with a new XOR gate topology. The goals are to increase power efficiency, reduce logic utilization (LUTs), and decrease time complexity/delay compared to other FFT implementations. An adder compressor is proposed that uses XOR gates to compress 4 input bits into 2 output bits (sum and carry), allowing parallel addition without carry propagation. Simulation results on a Xilinx FPGA show the compressor-based FFT uses fewer LUTs, consumes less power, and has a shorter delay compared to an FFT using a Booth multiplier.
AMAZON STOCK PRICE PREDICTION BY USING SMLTIRJET Journal
This document discusses predicting stock prices of Amazon (AMZN) stock using machine learning algorithms. It evaluates KNN, SVR, elastic net, and linear regression algorithms and finds that linear regression has the highest accuracy based on precision, recall, and F1 score metrics. The document provides details on each algorithm and compares their performance on this stock price prediction task. Linear regression builds a linear model to predict the dependent variable (stock price) based on independent variables and is shown to outperform the other supervised learning algorithms for this specific prediction problem.
Implementation Of Grigoryan FFT For Its Performance Case Study Over Cooley-Tu...ijma
This document discusses the implementation and performance comparison of two fast Fourier transform (FFT) algorithms - the Cooley-Tukey FFT and the Grigoryan FFT - on three Xilinx FPGAs. The Grigoryan FFT uses a decomposition based on paired transforms, while the Cooley-Tukey FFT uses a radix-2 decomposition. Both algorithms were implemented on Virtex-II Pro, Virtex-5, and Virtex-4 FPGAs. The results showed that the Grigoryan FFT operated at higher sampling rates and was faster than the Cooley-Tukey FFT. Additionally, the Virtex-5 FPGA provided the highest speed for implementing the Grigoryan FFT compared
This document proposes a new approach to improve the Apriori algorithm for mining association rules from transactional databases. The approach uses a Boolean modeling of the association rules mined to represent them in a cellular automaton. The key steps are:
1) Applying the Apriori-Cell algorithm to a transactional database to extract frequent itemsets and generate association rules.
2) Representing the association rules using a Boolean model within a cellular automaton framework consisting of two layers - one for items and one for transactions.
3) Managing and simulating inference on the represented association rules using the cellular automaton's inference engine to optimize representation and processing of the rules.
An example is provided to illustrate
This document presents a new technique for designing an area efficient FFT/IFFT processor for WPAN applications using a Radix-25 algorithm and Wallace tree multiplier. The proposed design reduces the size of the twiddle factor memory and number of complex multiplications compared to previous designs. Simulation results show the proposed design occupies less area (14% of total logic elements) and has lower hardware complexity than prior approaches.
A study of the Behavior of Floating-Point Errorsijpla
The dangers of programs performing floating-point computations are well known. This is due to numerical reliability issues resulting from rounding errors arising during the computations. In general, these round-off errors are neglected because they are small. However, they can be accumulated and propagated and lead to faulty execution and failures. Typically, in critical embedded systems scenario, these faults may cause dramatic damages (eg. failures of Ariane 5 launch and Patriot Rocket mission). The ufp (unit in the first place) and ulp (unit in the last place) functions are used to estimate maximum value of round-off errors. In this paper, the idea consists in studying the behavior of round-off errors, checking their numerical stability using a set of constraints and ensuring that the computation results of round-off errors do not become larger when solving constraints about the ufp and ulp values.
PERFORMANCE ANALYSIS OF PARALLEL POLLARD’S RHO FACTORING ALGORITHM ijcsit
Integer factorization is one of the vital algorithms discussed as a part of analysis of any black-box cipher
suites where the cipher algorithm is based on number theory. The origin of the problem is from Discrete
Logarithmic Problem which appears under the analysis of the cryptographic algorithms as seen by a
cryptanalyst. The integer factorization algorithm poses a potential in computational science too, obtaining
the factors of a very large number is challenging with a limited computing infrastructure. This paper
analyses the Pollard’s Rho heuristic with a varying input size to evaluate the performance under a multicore environment and also to estimate the threshold for each computing infrastructure.
A high performance hardware FFT have various application in instrumentation and communication systems. It
describes new parallel FFT architecture which come together the split-radix algorithm with a constant geometry
interconnect structure. The split-radix algorithm knows to have lower multiplicative difficulty than both radix-2 as well as
radix-4 algorithm. The split-radix algorithm maps onto a constant geometry interconnect structure in which the wiring in
each FFT stage is the same, resulting in low multiplexing overhead. We are exploiting the lower arithmetic obscurity of
split-radix to lower dynamic energy, by gating the multipliers during trivial multiplication. The proposed FFT accomplishes
less power than a parallel radix-4 design when calculate at few point, the real-valued transform
Bounded ant colony algorithm for task Allocation on a network of homogeneous ...ijcsit
This document summarizes a research paper that proposes a bounded ant colony algorithm (BTS-ACO) for task scheduling on a network of homogeneous processors using a primary site. The algorithm uses an initial bound on each processor's load to control task allocation. It investigates scheduling tasks from a sorted list (SLoT) versus a random list (RLoT). Simulation results show that BTS-ACO with a sorted task list achieves better performance than a random list in terms of scheduling time, makespan, and load balancing.
SWARM INTELLIGENCE SCHEDULING OF SOFT REAL-TIME TASKS IN HETEROGENEOUS MULTIP...ecij
The document presents a hybrid swarm intelligence algorithm called VNABCSA for scheduling soft real-time tasks in heterogeneous multiprocessor systems. VNABCSA combines artificial bee colony and simulated annealing algorithms. It aims to minimize total tardiness, number of processors used, completion time, total waiting time of tasks and processors. The algorithm represents solutions as an ordering of tasks and assignment to processors. It uses artificial bee colony for global search and simulated annealing for local search to improve convergence. Simulation results show it performs better than existing scheduling algorithms.
This document presents an implementation of the Fast Fourier Transform (FFT) algorithm. It begins with an introduction to FFTs, explaining that they can compute the Discrete Fourier Transform (DFT) much more efficiently than direct evaluation, reducing the computation time from O(N^2) to O(N log N). It then describes the basic butterfly structures used in FFTs and shows how to implement 16-point FFT blocks. The document includes MATLAB code for an 8-point DFT and FFT, as well as VHDL code for a 16-point FFT processor. It provides details on decimation-in-time and decimation-in-frequency algorithms and how they recursively break down the DFT into smaller transforms
This document summarizes a research article that proposes a hybrid scheduling algorithm for real-time operating systems that combines Earliest Deadline First (EDF) and Ant Colony Optimization (ACO) algorithms. The hybrid algorithm aims to overcome the limitations of EDF, which cannot handle overloaded systems well, and ACO, which has longer execution times than EDF. The document provides background on real-time operating systems and describes EDF and ACO scheduling algorithms. It then proposes the hybrid algorithm that automatically switches between EDF and ACO to leverage the advantages of both. The goal is to enhance system performance, reduce failures, and decrease missed deadlines under different load conditions.
This document introduces multi-rate integration algorithms as a promising approach for efficiently simulating large object-oriented models. Multi-rate algorithms allow different components of a model to be integrated with different time steps, using smaller steps for fast subsystems and larger steps for slow subsystems. This is more efficient than single-rate algorithms that use a single small time step for the entire model. The document presents a self-adjusting multi-rate integration scheme and applies it to a test case model of a heating system with centralized heating and multiple user units. Results show the multi-rate approach reduces the number of derivative evaluations and computational time compared to a single-rate approach, especially as the system size increases.
IRJET- Low Complexity Pipelined FFT Design for High Throughput and Low Densit...IRJET Journal
This document describes a low complexity pipelined FFT design for high throughput applications. It proposes a feedforward FFT architecture based on rotator allocation to reduce the number and complexity of rotators. The key aspects are:
1) It uses a divide-and-conquer approach to split the FFT computation into stages, with butterflies operating on data whose indexes differ in the stage bit position.
2) It allocates the index bits into serial and parallel dimensions to optimize the distribution of rotations across stages. This aims to minimize the number of rotators and keep rotations in the same serial allocation set.
3) The proposed approach is shown to reduce the number and complexity of rotators in the FFT architecture compared
Resourceful fast dht algorithm for vlsi implementation by split radix algorithmeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Solving practical economic load dispatch problem using crow search algorithm IJECEIAES
The document presents a crow search algorithm to solve the practical economic load dispatch problem considering valve-point loading effects and multiple fuel options. This problem is non-convex, non-smooth, and non-linear. The crow search algorithm is inspired by the intelligent social behavior of crows. It models the crows following each other to find food storage locations. The algorithm updates crow positions based on whether another crow detects it or not. Simulation results show the crow search algorithm finds high-quality solutions and performs effectively compared to other algorithms for solving the non-convex economic load dispatch problem.
Contention - Aware Scheduling (a different approach)Dimos Raptis
This presentation covers the topic of scheduling in operating systems and more specifically the field of contention-aware scheduling that seems to be really promising. It presents the outcome of a recent project, where a different approach resulted in the implementation of a contention-aware scheduler (called LCN) attempting to compete with the most modern schedulers and the current scheduler of Linux
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Neural network optimizer of proportional-integral-differential controller par...IJECEIAES
Wide application of proportional-integral-differential (PID)-regulator in industry requires constant improvement of methods of its parameters adjustment. The paper deals with the issues of optimization of PID-regulator parameters with the use of neural network technology methods. A methodology for choosing the architecture (structure) of neural network optimizer is proposed, which consists in determining the number of layers, the number of neurons in each layer, as well as the form and type of activation function. Algorithms of neural network training based on the application of the method of minimizing the mismatch between the regulated value and the target value are developed. The method of back propagation of gradients is proposed to select the optimal training rate of neurons of the neural network. The neural network optimizer, which is a superstructure of the linear PID controller, allows increasing the regulation accuracy from 0.23 to 0.09, thus reducing the power consumption from 65% to 53%. The results of the conducted experiments allow us to conclude that the created neural superstructure may well become a prototype of an automatic voltage regulator (AVR)-type industrial controller for tuning the parameters of the PID controller.
An improved modulation technique suitable for a three level flying capacitor ...IJECEIAES
This research paper introduces an innovative modulation technique for controlling a 3-level flying capacitor multilevel inverter (FCMLI), aiming to streamline the modulation process in contrast to conventional methods. The proposed
simplified modulation technique paves the way for more straightforward and
efficient control of multilevel inverters, enabling their widespread adoption and
integration into modern power electronic systems. Through the amalgamation of
sinusoidal pulse width modulation (SPWM) with a high-frequency square wave
pulse, this controlling technique attains energy equilibrium across the coupling
capacitor. The modulation scheme incorporates a simplified switching pattern
and a decreased count of voltage references, thereby simplifying the control
algorithm.
A review on features and methods of potential fishing zoneIJECEIAES
This review focuses on the importance of identifying potential fishing zones in seawater for sustainable fishing practices. It explores features like sea surface temperature (SST) and sea surface height (SSH), along with classification methods such as classifiers. The features like SST, SSH, and different classifiers used to classify the data, have been figured out in this review study. This study underscores the importance of examining potential fishing zones using advanced analytical techniques. It thoroughly explores the methodologies employed by researchers, covering both past and current approaches. The examination centers on data characteristics and the application of classification algorithms for classification of potential fishing zones. Furthermore, the prediction of potential fishing zones relies significantly on the effectiveness of classification algorithms. Previous research has assessed the performance of models like support vector machines, naïve Bayes, and artificial neural networks (ANN). In the previous result, the results of support vector machine (SVM) were 97.6% more accurate than naive Bayes's 94.2% to classify test data for fisheries classification. By considering the recent works in this area, several recommendations for future works are presented to further improve the performance of the potential fishing zone models, which is important to the fisheries community.
Electrical signal interference minimization using appropriate core material f...IJECEIAES
As demand for smaller, quicker, and more powerful devices rises, Moore's law is strictly followed. The industry has worked hard to make little devices that boost productivity. The goal is to optimize device density. Scientists are reducing connection delays to improve circuit performance. This helped them understand three-dimensional integrated circuit (3D IC) concepts, which stack active devices and create vertical connections to diminish latency and lower interconnects. Electrical involvement is a big worry with 3D integrates circuits. Researchers have developed and tested through silicon via (TSV) and substrates to decrease electrical wave involvement. This study illustrates a novel noise coupling reduction method using several electrical involvement models. A 22% drop in electrical involvement from wave-carrying to victim TSVs introduces this new paradigm and improves system performance even at higher THz frequencies.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
2. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 10, No. 2, April 2020 : 1469 - 1476
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two large prime numbers. Nevertheless, it becomes very difficult to factor the modulus. Furthermore,
RSA has been improved continuously to avoid attacking from intruders [3].
In fact, if attackers can recover two large prime factors of the modulus, then RSA is broken.
Although, Integer Factorization is one of the hard problems to break RSA, many integer factorization
algorithms, such as [4-10] are still developing to find the weakness of RSA which is not still disclosed.
In general, the efficiency of each algorithm is based on characteristic of prime factors. For example, if one of
two prime factors is very small, Trial Division Algorithm (TDA) [11, 12] is the best algorithm for this
situation. However, TDA becomes inefficient algorithm whenever both of prime factors are very large.
The other example is that if all prime factors of p–1 or q–1 are very small, where p and q are represented as
two large prime factors of the modulus, Pollard’s p-1 [13] should be chosen to recover both of them.
Fermat’s Factorization Algorithm (FFA) [14, 15] discovered by Pierre De Fermat in 1600 is one of integer
factorization algorithms. FFA can factor modulus very fast when the difference between two large prime
factors is small. In addition, the other form of modulus which is equal to the difference between two perfect
square numbers is considered instead of the form of the production between two prime numbers.
In fact, many improvement of FFA algorithms [16-21] were presented to reduce loops. In 2017, Specific
Fermat's Factorization Algorithm Considered from X (SFFA-X) [22] was proposed to reduce the time
complexity. The last m digits of modulus are considered to leave many unexpected values out from
the computation. Furthermore, SFFA-X can be increased performance by changing the value of m which
must be larger. However, assuming only traditional FFA is considered, there are two techniques to implement
FFA. Both of them have the different advantage and disadvantage. The advantage of the first technique
which is called FFA-1 is small loops when it is compared with the other technique which is called FFA-2.
However, every loops have to compute square root operation which is not included to FFA-2.
The aim of this paper is to propose the new integer factorization algorithm. Euler’s theorem is applied with
FFA to get the new idea behind the proposed method. In fact, the proposed method is from the combination
of the advantage from both of FFA-1 and FFA-2.
2. RELATED WORKS
2.1. Fermet’s factorization algorithm: FFA
FFA is the one of the methods to find two large prime factors. It suits to solve modulus which both
of prime factors are close to each other. Assume p, q are odd prime numbers and n is the modulus that n=p*q.
By using Fermat’s technique, n must be rewritten in the other form as following:
n=x2
–y2
(1)
where, x=
p + q
2
and y=
p - q
2
FFA is distinguished as two methods which have different advantage and disadvantage as following:
2.2. FFA-1
Assigning, the initial value of x is n
, from (1), y is calculated from the following equation:
y= 2
-x n (2)
Generally, if y is an integer, then p=x+y and q=x–y are two prime factors of n. On the other hand, x must be
increased by 1 to find the new value of y whenever it is not the integer. In fact, the process must be repeated
until the integer of y is found. Assigning l1 is the number of loops for FFA-1, then
l1=
p + q
2
- n
(3)
Nowadays, many improvements of FFA-1 were proposed to reduce l1 such as [16-18]. However,
the disadvantage of FFA-1 and it’s improving algorithms are about computing square root of integer.
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The new integer factorization algorithm based on Fermat’s Factorization … (Kritsanapong Somsuk)
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2.3. FFA-2
FFA-2 is different from FFA-1, because there is no square root computing in the main process.
From (1), the equation can be rewritten as following:
4n=u2
–v2
(4)
where, u=p+q and v=p–q. Assuming the initial value of u and v are 2 n
and 0, respectively, then r is
computed by following equation:
r=u2
–v2
–4n (5)
From (5), if r is equal to 0, p and q are recovered from p=
u + v
2
and q=
u + v
2
. On the othe hand,
if r is not equal to 0, the process is divided as two cases:
- Case 1: r>0, v will be increased by 2 in order to reduce r until r which is equal to 0 is found.
- Case 2: r<0, u will be increased by 2 in order to enlarge r until r which is equal to 0 is found.
Assigning l2 is represented as the number of loops computation for FFA-2, l2 can be computed from,
l2=lu+lv (6)
where, lu is loops of u and lv is loops of v,
Considering lu: the initial and target of u are 2 n
and p+q. Moreover, it is always increased by 2
then it implied that lu is equal to l1. Considering lv: the target result of v is p-q and the increment is 2, then
lv=
p - q
2
(7)
As FFA-1, there are many algorithms improved from FFA-2 such as Estimated Prime Factor (EPF) for
estimating the new initial values [15] and Specific Fermat's Factorization Algorithm Considered from
X (SFFA-X) [22] to leave unrelated integers from the computation. Although, integer square root is not
computed, time to find prime factors is still high because of large loops. Table 1 is shown advantage and
disadvantage between FFA-1 and FFA-2.
Table 1. Advantage and disadvantage between FFA-1 and FFA-2
Factorization Algorithm Square root Computing Loops
FFA-1 Every Time Small (Compared with FFA-2)
FFA-2 None Large
2.4. Euler’s theorem
Euler’s Theorem [23] is the theorem modified from Fermat’s little Theorem. Assigning a
and
gcd(a, n)=1, (n)=(p–1)*(q–1)=n–(p+q)+1 and a is relative prime to (n), then
(n)
a 1
mod n (8)
In fact, this theorem is one of the main cores for implementing the proposed method mentioned in
the next section.
3. THE PROPOSED METHOD
In this paper, the new algorithm based on FFA is proposed. The main core is to replace square root
computing with modular multiplication. In dept, modular multiplication takes low cost in comparison to
square root operation. Moreover, the loops are same as FFA-1. In addition, the method is from
the combination between euler’s theorem and FFA. In fact, (8) is rewritten as following:
an–(p +q) +1 1 mod n (9)
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Algorithm: The Proposed Method
Input: n
Output: p, q
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
u←2 n
Select c, where gcd(c, n)=1
a←c-1
mod n
s←c2
mod n
t←an–u+1
mod n
IF t=1 then
x←
u
2
y← 2
-x n
Else
y←0.1
End IF
While y is not an integer do
t←t*s
IF t>n then
t←t mod n
End IF
u←u+2
IF t=1 then
x←
u
2
y← 2
-x n
End IF
End While
p←x+y
q←x–y
Because lu=
p + q
2
- n
(x is increased by 1) or p+q-2 n
(u is increased by 2), therefore,
if u increased by 2 is considered, then p+q=lu+2 n
.
Assigning b, c
, b=
n 2 n 1
a
mod n and c=a-1
mod n then,
b*clu
=(
n 2 n 1
a
)*(a-1
)lu
mod n
=
n 2 n 1-lu
a
mod n
=
n (2 n lu) 1
a
=an–(p +q)+1
mod n
In fact, the process begins with b=
n 2 n 1
a
mod n and b is recomputed by using modular
multiplication with c2
mod n whenever the result which is equal to 1 is not found as follow:
b=b*c2
mod n (10)
From (10), the result is certainly equal to 1 whenever the process is repeated lu times.
Assigning x= u
l
2
, then y can be recovered by using (2). However, it is possible that there are some
integers, assigned as li where i=0, 1, 2, ∙∙∙, u-1 and li<lu, that
n (2 n li) 1
a
mod n is equal to 1. Nevertheless,
y is not certainly an integer. Therefore, the process must be repeated until the b=1 and integer of y is found.
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In fact, square root operation will be processed only when b is equal to 1. Because, lu is represented as loops
of the proposed method and the increasing step is 2, it implies that loops between the method and FFA-1 are
same. In addition, c2
mod n should be calculated as the constant at first, because it is often operated in (10).
Furthermore, it should be assigned as small integer to decrease the cost. Therefore, c will be assigned before
finding a: a=c-1
mod n.
Example 1: Factoring n=340213 by using the proposed method
Sol. Each step from the algorithm is at following:
Step 1-2: u=1168, c=2
Step 3: a=2-1
mod 340213=170107
Step 4: s=22
mod 340213=4
Step 5: t=170107339046
mod 340213=186054
Step 6-11: Because t 1, y=0.1
Step 12–19 (Loops)
Loop 1:
Step 13-16: t=186054*4=744216
Because t>340213 then 744216 mod 340213=63790
Step 17: u=1168+2=1170
Loop 2:
Step 13: t=63790*4 mod 340213=255160
Step 17: u=1170+2=1172
Loop 3:
Step 13-16: t=255160*4=1020640
Because t>340213 then 1020640 mod 340213=1
Step 17: u=1172+2=1174
Step 18–21: Because t=1, then
Step 19-20: x=
1174
2
=587 and y= 2
587 340213 =66
Because t=1 and y is an integer (end of loop), then
Step 23-24: p=587+66=653, q=587-66=521
Therefore, there are only three loops to implement n=340213 by using the proposed method.
Considering FFA-1: l1=
653 + 521
2
-584=3
Considering FFA-2: lv=
653 - 521
2
=66, and l2=3+66=69
Therefore, it implies that loops of FFA-2 are larger than the proposed method. However,
FFA-1 takes time complexity higher than the proposed method, because modular multiplication takes low
time complexity in comparison to square root operation [24]. Because n=340213 is too small, all mentioned
algorithms can solve the problem very quick. The information in Table 2 is shown the main process and
loops of FFA-1, FFA-2 and the proposed method to factor n = 340213. Assuming n=788582867650121563
which is from the production between p=1066200463 and q=739619701 (p and q have the same bits’ length),
Table 3 is shown the comparison during three algorithms to find p and q of n=788582867650121563.
Table 2. The comparison during three algorithms to solve problem with n = 340213
Factorization Algorithm Loops Main Process
FFA-1 3 Square root
FFA-2 69 Multiplication
The Proposed Method 3 Multiplication
Table 3. The comparison during three algorithms to solve problem with n=788582867650121563
Factorization Algorithm Loops Time (Second)
FFA-1 902910079 19.04
FFA-2 1066200460 25.75
The Proposed Method 902910079 2.82
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From Table 3, although the loops between FFA-1 and the proposed method are same, the proposed
method takes time lower than FFA-1. In addition, FFA-2 consumes the highest computation cost.
In the example, the method is faster than FFA-1 and FFA-2 about 75% and 89%, respectively.
Next, assuming n=1047329636821139813 which is from the production between p=1971074143 and
q=531349691 (p and q have the different bits’ length). Table 4 is shown the comparison during three
algorithms to find p and q of n=1047329636821139813.
Table 4. The comparison during three algorithms to solve problem with n=1047329636821139813
Factorization Algorithm Loops Time (Second)
FFA-1 227820673 290.02
FFA-2 947682899 142.53
The Proposed Method 227820673 41.17
In Table 4, the proposed method still takes the lowest computation time. However, FFA-2 becomes
faster than FFA-1. The reason is that, although loops of FFA-2 are the highest, FFA-1 is slower than FFA-2,
because square root computing becomes inefficient operation when loops are large (bits length between p and
q are different). In the example, the method is faster than FFA-1 and FFA-2 about 75% and 72%.
4. COMPLEXITY ANALYSIS
4.1. The proposed method Vs. FFA-1
The multiplication of the main process from the proposed method is different from square root
operation. The value of s which is the multiplication of t is selected at first. Then, the cost for the production
between t and s is equal to the s-1 times of the addition between t and itself. For example, the compared
process of proposed method in the example 1 is t+t+t+t = 4t. For each iteration, it implies that the complexity
of the main process for the proposed method is close to the addition operation that is (m) when m is
represented as binary based on t. Therefore, it is less than square root cost which is (M(m)), for Newton’s
method.
4.2. The proposed method Vs. FFA-2
In fact, the multiplication with the small multiple value is the main process for FFA-2. Therefore,
the cost complexity for each iteration is equal to the proposed method. However, loops of FFA-2 are very
larger than the proposed method. Therefore, the proposed method’s cost is less than the compared algorithm.
5. APPLIED PROPOSED METHOD WITH IMPROVED ALGORITHMS
In addition, the proposed method can be applied with most of algorithms that modified from both of
FFA-1 and FFA-2. However, two algorithms are selected as the examples to combine with the proposed
method. First, EPF [15] improved from FFA-2 is the method to estimate the new initial values (u and v) for
unbalanced modulus. In fact, the new initial value of u is also applied with the proposed method.
Example 2: Factoring n=1783647329 (p=84449 and q=21121)
Sol. Assign ui is the new initial value, the loop's equation is changed as: i
p + q - u
2
Because, n
=42234, then from (3) the loops are 10551. However, ui is computed as 97430, then the new
loops can be re-estimated as 4070 that is less than traditional proposed method.
Second method is Multi Forms of Modulus for Fermat Factorization Algorithm (Mn-FFA) [25].
The key of this method is to find the pattern of x which is distinguished as 16 cases from the considering
forms of n mod 4, n mod 6 and n mod 20 together. In fact, this method can be applied the proposed method
by converting pattern of x as pattern of u.
Example 3: Factoring n=571187 (p=941 and q=607)
Sol. Because, 571187 mod 4=3, 571187 mod 6=5 and 571187 mod 20=7, then from Table 2 in [15], u must
be divided by 12 and the last digit is 2 or 8.
Because 2 n
=1512 that is divided by 12 and the last digit is 2, ui is equal to 1512.
Assigning c=2, then a=285594 and t=an–u+1
mod n=411191
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Usually u=u+2=1514 must be computed for the proposed method. However, for applying Mn-FFA
with the proposed method, u can be computed as follow: u=u+36=1548, because it is the minimum value
which is larger than 1512 and still in the condition. Therefore, the multiple value is not c2
but it is c36
as
following: c36
mod n=539953 and t=t*c36
mod n=1, then x=774 and y=167. Because y is an integer, then p
and q can be recovered. In fact, there are only 2 loops for the implementation which are less than loops of
tradition proposed method which are equal to 18.
6. CONCLUSION
In this paper, the new factorization algorithm from the applied method between Fermat’s
factorization algorithm and euler’s theorem is proposed. The key is that the almost square root operations are
left from the computation while the loops are not increased. In fact, multiplication operation with small
multiple value is the main process of the proposed method. Then, it implies that the complexity for each
iteration is only (m), where m is binary based of computed number. Moreover, the proposed method can
be also chosen to apply with the other algorithms modified from FFA to decrease more costs. In addition,
this paper shows the proposed method which is applied with EPF and Mn-FFA.
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BIOGRAPHY OF AUTHOR
Kritsanapong Somsuk is an assistant professor of the department of Computer and Communication
Engineering in Faculty of Technology, Udon Thani Rajabhat University, Udon Thani, Thailand.
He received his M.Eng. (Computer Engineering) from department of Computer Engineering in
Faculty of Engineering, Khonkaen University, M.Sc. (Computer Science) from department of
Computer Science in Faculty of Science, Khonkaen University and his Ph.D. (Computer
Engineering) from department of Computer Engineering in Faculty of Engineering, Khonkaen
University. His research interests include computer security, cryptography and integer factorization
algorithms.