Search
1981 articles for “A* algorithm” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
-
Parallel Computing to Perform Isogeometric Topology Optimisation of Continuum Structures Using Aqua Search Evolutionary Algorithm
Abstract: AbstractThe efficiency and effectiveness of using the computational power to solve engineering problems is the real challenge. The knowledge of Computer Science and Information Technology should enable us to address these challenges in the field of computational mechanics and solvea few structural engineering problems. The main focus in this paper is to be able to apply parallel computing to perform engineering optimization of NP(non-deterministic polynomial-time hardness)-hard problems using fewer computational …
Published in Recent Trends in Parallel Computing · Vol. 4, Issue 2, 2017 · pp. 21–31 Read article
-
Fast All Sum Algorithm Over 2D-Mesh Network
Abstract: Total sum (aka summation, all sums) is an important mathematical tool which is used extensively in various computational and statistical techniques. Fastest summation plays a vital role in overall calculation of specific technique which reduces cost and time. Thus in this paper we propose an improved parallel summation algorithm on 2D-Mesh network with N (=n2) processing elements which will perform summation of N (= n2) summands (or addends) in + …
Published in Recent Trends in Parallel Computing · Vol. 5, Issue 3, 2018 · pp. 37–43 Read article
-
Parallel Algorithms for Mean, Variance, and Standard Deviation over a 2D-Mesh Network
Abstract: Abstract: Due to advanced technology and usage of internet at worldwide scale, there has always been a challenge to handle and manage the huge amount of data in an efficient way. There are so many statistical and non-statistical methods applied to data to find result and conclusions that can later be used to solve many other complex problems in an easy and fast way, which also reduces the cost. In …
Published in Recent Trends in Parallel Computing · Vol. 6, Issue 3, 2019 · pp. 17–22 Read article
-
Analysis of Machine Learning Algorithms for the Detection of Mental Health Problems in Employees
Abstract: Mental health-related issues are more critical issues in the workplace. Mental health has been a major and challenging issue, especially for working professionals. A bad work environment can cause a variety of physical and physiological problems as well as decreased productivity. People are reluctant to ask for help from mental health specialists, according to studies. The fundamental reason for this is the stigma attached to mental illness. Working professionals therefore …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 3, 2022 · pp. 12–24 Read article
-
Stock Price Movement Prediction using Machine Learning Algorithms and Time Series Models: A Review
Abstract: The stock market is a very important place for investment in a country. It also serves as the index of the growth for an economy. To determine the behavior of the stock market trends has been the focal point of researchers for very long. The nonlinear structure of the stock market makes it challenging to predict how the stock price will change. But it has been demonstrated that stock market …
Published in Journal of Operating Systems Development & Trends · Vol. 9, Issue 2, 2022 · pp. 7–13 Read article
-
Dynamic Analysis of a Switched Boost Converter Singular System using Mehtod-Rachid Algorithm
Abstract: Electronics technology is a very dynamically evolving technology as compared to any other domains. The advent of these changes is forcing us to relook at the conventional physics, and mathematical models related to switching systems in particular or singular systems in general. Mostly we always drive system characteristics assuming a singular system to be linear. Singular systems are those the dynamics of which are governed by a mixture of algebraic …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 1, Issue 3, 2014 · pp. 1–4 Read article
-
Genetic Algorithm Based Tree Formation in Wireless Sensor Networks
Abstract: A typical task in wireless sensor networks is to collect data through nodes of sensor network towards sink. wireless sensor network has various data gathering techniques based on tree, data gathering based on chain and data gathering based on hierarchy etc. This paper shows a tree formation technique used in the data gathering. The data is collected from different sensors forward and towards the sink node for this purpose. The …
Published in Journal Of Network security · Vol. 3, Issue 3, 2015 · pp. 22–32 Read article
-
GENETIC ALGORITHM BASED DESIGN OF A SIMPLY SUPPORTED REINFORCED CONCRETE BEAM
Abstract: This paper demonstrates an application of the genetic algorithms to the design of a simply supported reinforced concrete beam. Cost optimisation of reinforced concrete beam is carried out to get the most economical concrete section and the reinforcements at user specified intervals. Genetic algorithm is used to find out the depth, the number and diameter of bars and the diameter and spacing of stirrups. A program is created based on …
Published in Journal of Structural Engineering and Management · Vol. 2, Issue 3, 2015 · pp. 55–59 Read article
-
Advancements in AI-Driven Diagnostics for Dental Health: A Comprehensive Review
Abstract: Dental diseases, also known as oral diseases or dental conditions, encompass a range of health problems affecting the teeth, gums, mouth, and associated structures. These conditions can lead to pain, discomfort, and severe complications if left untreated. Early detection and accurate diagnosis are crucial for effective treatment and prevention of further complications. This comprehensive literature review aims to identify common dental problems such as Tooth Decay (Cavities), Gingivitis, Periodontitis, and …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 1–7 Read article
-
Crop Disease Prediction by Machine Learning
Abstract: The classification of Crop can be classified into several methods. The data set of crop leaf illnesses, notably Bacterial Leaf Blight disease (BLB), a crop leaf disease with significant outbreaks throughout Thailand, and Brown Spot Crop disease (BSR), is classified employing image classification in this study. Additionally, image processing technology is used for identifying different types of crop leaf disease. These algorithms include the Random Forest, Decision Tree, Gradient Boost, …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 21–25 Read article
-
Performance Analysis of Fusion Classifier of Face Recognition System based on ANN and GA
Abstract: Though a lot of significant work has been done for recognizing and improving the performance in facial pattern, most techniques have been developed based on a single classifier. But most often, the performance of the classifier is not satisfactory in some case. It has been proposed that the performance of face recognition will beimproved by fusing two or more classifiers. We can combine the information/data in different level i.e., feature …
Published in Current Trends in Information Technology · Vol. 4, Issue 1, 2014 · pp. 4–13 Read article
-
Twisting, Super Twisting and Adaptive Algorithm Sliding Mode Controller for Second Order Time Delay Systems
Abstract: The sliding mode control approach is widely considered as one of the most effective methods for designing a reliable controller for a complicated higher-order dynamic plant operating under uncertainty. The primary advantages of sliding mode is its low sensitivity to changes in plant parameters and the ability to entirely eliminate disruptions. Sliding mode control has been widely applied as a robust control design methodology that is completely insensitive to uncertainties, …
Published in Current Trends in Signal Processing · Vol. 11, Issue 4, 2021 · pp. 10–27 Read article
-
An Approach for Travel Pattern Analysis Using HDBSCAN and Apriori Algorithms
Abstract: Most mega-city regions around the world are suffering from an ongoing increase in the number of commuting trips. Understanding commuting patterns is crucial for both public and authority planners. The understanding of travel patterns helps passengers to know about the places and the time where they could get vacant transport and also helps authority planners in laying out a new transport service. The traditional way of understanding travel patterns includes …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 2, 2023 · pp. 1–9 Read article
-
A Simplistic Review of the Soundex Algorithm: The Magic of Phonetics
Abstract: As a human, we always make mistakes while pronouncing words, names, and terms that sound alike. As a result of which those spellings are difficult to identify. To simplify this problem, we have discussed an algorithm called Soundex algorithm which provides a solution to pronunciation problems by giving a similar code with 1-letter and 3-digit code as a syntactical solution to all terms that sound alike. In this study, we …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 1, 2024 · pp. 1–8 Read article
-
Enhancing Cancer Diagnosis: AI/ML Algorithms and Nanotechnology-Based Biosensors for Colorectal Cancer Screening
Abstract: Colorectal cancer (CRC) is one of the most common and deadly cancers worldwide, and enhancing patient outcomes requires early identification. This study explores the potential of nanotechnology- enhanced biosensors and artificial intelligence/machine learning (AI/ML) algorithms to revolutionize colorectal cancer screening and diagnosis. Nanotechnology offers unique opportunities for the development of highly sensitive and specific biosensors capable of detecting cancer biomarkers at an early stage. By incorporating nanomaterials with exceptional optical, …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 26, Issue 1, 2024 · pp. 16–28 Read article
-
Multiple Disease Prediction Using Machine Learning Algorithms
Abstract: The incorporation of machine learning algorithms into healthcare has transformed disease prediction and diagnosis. This research introduces a method for predicting various diseases using machine learning techniques. A comprehensive dataset, consisting of patient records, medical histories, and key disease-related features, was utilized to build predictive models. Data preprocessing methods, including feature selection and normalization, were implemented to clean and prepare the dataset. Several machine learning algorithms, such as Decision Trees, …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 3, 2024 · pp. 34–38 Read article
-
Encoding-Decoding Algorithm Using the Catalan Transform of Weighted Tribonacci Sequence
Abstract: In order to improve information security, this paper presents a unique algorithm for encoding and decoding messages utilizing the Catalan Transform of a Weighted Tribonacci Sequence. Utilizing the Catalan and Tribonacci sequences, the methodology combines the concepts of number theory and combinatorics to create an effective encryption and decryption process. First, an array is created by mapping each character in the plaintext message to its corresponding ASCII value. The ASCII-weighted …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 3, 2024 · pp. 12–16 Read article
-
A Hybrid Algorithm for Processor Scheduling Using Game Theory Variants
Abstract: This study proposes a novel hybrid algorithm for processor scheduling in modern operating systems, integrating the strengths of traditional scheduling methods with game theory variants. Traditional schedulers often struggle to adapt to dynamic workload changes, leading to suboptimal performance. Our hybrid approach addresses this by treating processes as "players" in a game, where the "payoff" is CPU time. A base scheduler (e.g., Weighted Fair Queuing, Earliest Deadline First) provides a …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 48–56 Read article
-
IoT Sensors to Monitor Pipeline Pressure and Flow Rate Combined with ML-Algorithms to Detect Leakages
Abstract: In the field of fluid mechanics, pipelines are the lifeblood of industries, transporting everything from natural gas and oil to water and chemicals. Maintaining their integrity is paramount for safety, economic efficiency, and environmental protection. Traditional leak detection methods explained in fluid mechanics can be slow, expensive, and sometimes fail to identify small leaks early enough to prevent significant damage. However, the convergence of Internet of Things (IoT) and Machine …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 40–48 Read article
-
Adaptive E-Learning Algorithms and Heutagogy: A Systematic Analysis
Abstract: The proliferation of artificial intelligence (AI) and machine learning (ML) technologies has transformed the digital education landscape by enabling adaptive e-learning systems capable of personalizing content and optimizing learning paths. This study provides a systematic analysis of adaptive e-learning algorithms within the framework of heutagogy, an educational paradigm that emphasizes learner autonomy, self-direction, and capability development. The convergence of adaptive technologies with heutagogical principles offers new avenues for creating more …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 33–38 Read article