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Journal articles on the topic 'Cognitive development optimization algorithm'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Ahmet, Demir, and Kose Utku. "BRAIN Journal - Solving Optimization Problems via Vortex Optimization Algorithm and Cognitive Development Optimization Algorithm." BRAIN - Broad Research in Artificial Intelligence and Neuroscience 7, no. 4 (2016): 23–42. https://doi.org/10.5281/zenodo.1045013.

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ABSTRACT In the fields which require finding the most appropriate value, optimization became a vital approach to employ effective solutions. With the use of optimization techniques, many different fields in the modern life have found solutions to their real-world based problems. In this context, classical optimization techniques have had an important popularity. But after a while, more advanced optimization problems required the use of more effective techniques. At this point, Computer Science took an important role on providing software related techniques to improve the associated literature.

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Bowling, Alan, and Fillia Makedon. "Cognitive Optimization in Assistive Living System Development." Applied Bionics and Biomechanics 9, no. 1 (2012): 1–14. http://dx.doi.org/10.1155/2012/427838.

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This paper presents an exploration of the characteristics and structure of a cognitive architecture for control of assisted living systems. The aspects of cognition considered are self-organization, communication, and inherited knowledge. A cognitive solution for a related problem, function optimization, is developed because of the complexity and size of the assistive living problem. Support for this approach stems from the artificial intelligence field where optimization is considered to be a critical aspect of cognition, and from the similarity between the performance metrics for the two pro

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Utku, Kose, and Arslan Ahmet. "BRAIN Journal - Realizing an Optimization Approach Inspired from Piaget's Theory on Cognitive Development." BRAIN - Broad Research in Artificial Intelligence and Neuroscience 6, no. 1-2 (2015): 14–21. https://doi.org/10.5281/zenodo.1044171.

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ABSTRACT The objective of this paper is to introduce an artificial intelligence based optimization approach, which is inspired from Piaget’s theory on cognitive development. The approach has been designed according to essential processes that an individual may experience while learning something new or improving his / her knowledge. These processes are associated with the Piaget’s ideas on an individual’s cognitive development. The approach expressed in this paper is a simple algorithm employing swarm intelligence oriented tasks in order to overcome single-objective optimization problems. For

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Ameen, Azad A., Tarik A. Rashid, and Shavan Askar. "CDDO–HS: Child Drawing Development Optimization–Harmony Search Algorithm." Applied Sciences 13, no. 9 (2023): 5795. http://dx.doi.org/10.3390/app13095795.

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Child drawing development optimization (CDDO) is a recent example of a metaheuristic algorithm. The motive for inventing this method is children’s learning behavior and cognitive development, with the golden ratio being employed to optimize the aesthetic value of their artwork. Unfortunately, CDDO suffers from low performance in the exploration phase, and the local best solution stagnates. Harmony search (HS) is a highly competitive algorithm relative to other prevalent metaheuristic algorithms, as its exploration phase performance on unimodal benchmark functions is outstanding. Thus, to avoid

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Petukhova, Alina Vladimirovna, Anna Vladimirovna Kovalenko, and Anna Vyacheslavovna Ovsyannikova. "Algorithm for Optimization of Inverse Problem Modeling in Fuzzy Cognitive Maps." Mathematics 10, no. 19 (2022): 3452. http://dx.doi.org/10.3390/math10193452.

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Managerial decision-making is a complex process that has several problems. The more heterogeneous the system, the more immeasurable, non-numerical information it contains. To understand the cognitive processes involved, it is important to describe in detail their components, define the dependencies between components, and apply relevant algorithms for scenario modelling. Fuzzy cognitive maps (FCMs) is the popular approach for modeling a system’s behavior over time and defining its main properties. This work develops a new algorithm for scenario analysis in complex systems represented by FCMs t

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Saranya, A., and Anandan R. "Cognitive Human Gait Analysis for Neuro-Physically Challenged Patients by Bat Optimization Algorithm." International Journal of Reliable and Quality E-Healthcare 11, no. 1 (2022): 1–11. http://dx.doi.org/10.4018/ijrqeh.313915.

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Autism spectrum disorder and cerebral palsy are called developmental disorders that affect the brain development, communication, and behaviour of a child or an adult. Individuals with Cerebral palsy can also display symptoms of autism. Both conditions have varying degrees of severity, which can make it difficult to form a clear diagnosis. This research paper proposes the model-free green environment for the prediction of the above-mentioned disorders by doing gait analysis only with the camera. The new intelligent algorithm CAGLearner (cognitive analysis for gait) works on the standards of gra

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Gao, Kanke, Onur Ozdemir, Dimitris A. Pados, Stella N. Batalama, Tommaso Melodia, and Andrew L. Drozd. "Cognitive Code-Division Channelization with Admission Control." Journal of Computer Networks and Communications 2012 (2012): 1–9. http://dx.doi.org/10.1155/2012/510942.

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We consider the problem of joint resource allocation and admission control in a secondary code-division network coexisting with a narrowband primary system. Our objective is to find the maximum number of admitted secondary links and then find the optimal transmitting powers and code sequences of those secondary links such that the total energy consumption of the secondary network is minimized subject to the conditions that primary interference temperature constraints, secondary signal-to-interference-plus-noise ratio (SINR) constraints and secondary peak power constraints are all satisfied. Th

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Wang, Qian, Zhaoqi Fang, and Xinchun Ye. "Research on the Construction of Labor Education Curriculum Model Based on Multi-Objective Optimization Algorithm under Fuzzy Cognitive Orientation." Journal of Combinatorial Mathematics and Combinatorial Computing 127a (April 15, 2025): 1897–915. https://doi.org/10.61091/jcmcc127a-110.

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Optimization problems usually involve multiple objectives, while fuzzy cognitive maps can effectively show the causal relationship between concepts, and the combination of the two can greatly advance the development of the education field. In this paper, we design a fuzzy cognition-based knowledge map for labor education courses and a multi-objective optimization model for labor education courses to optimize learners’ learning paths and recommend personalized exercises from multiple stages. Through teaching experiments and regression analysis, the teaching effect of the multi-objective optimiz

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Deka, Rashmi, Soma Chakraborty, and Sekhar Roy. "Optimization of spectrum sensing in cognitive radio using genetic algorithm." Facta universitatis - series: Electronics and Energetics 25, no. 3 (2012): 235–43. http://dx.doi.org/10.2298/fuee1203235d.

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Spectrum availability is becoming scarce due to the rise of number of users and rapid development in wireless environment. Cognitive radio (CR) is an intelligent radio system which uses its in-built technology to use the vacant spectrum holes for the use of another service provider. In this paper, genetic algorithm (GA) is used for the best possible space allocation to cognitive radio in the spectrum available. For spectrum reuse, two criteria have to be fulfilled - 1) probability of detection has to be maximized, and 2) probability of false alarm should be minimized. It is found that with the

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Utku, Kose, Emre Guraksin Gur, and Deperlioglu Omer. "BRAIN Journal - Cognitive Development Optimization Algorithm Based Support Vector Machines for Determining Diabetes." BRAIN - Broad Research in Artificial Intelligence and Neuroscience 7, no. 1 (2016): 80–90. https://doi.org/10.5281/zenodo.1044230.

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ABSTRACT The definition, diagnosis and classification of Diabetes Mellitus and its complications are very important. First of all, the World Health Organization (WHO) and other societies, as well as scientists have done lots of studies regarding this subject. One of the most important research interests of this subject is the computer supported decision systems for diagnosing diabetes. In such systems, Artificial Intelligence techniques are often used for several disease diagnostics to streamline the diagnostic process in daily routine and avoid misdiagnosis. In this study, a diabetes diagnosi

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Kamble, Vijaykumar S., Prabodh Khampariya, and Amol A. Kalage. "A Survey on the Development of Real-Time Overcurrent Relay Coordination Using an Optimization Algorithm." NeuroQuantology 20, no. 5 (2022): 74–85. http://dx.doi.org/10.14704/nq.2022.20.5.nq22150.

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The current work is a survey on the development of real-time overcurrent relay coordination utilizing an optimization approach. Overcurrent relays are a safeguard commonly used in transmission and distribution networks owing to their low cost. Depending on the operating conditions and the location of the faults, load or fault currents in a mesh system may loop in or out of the protective zone of the overcurrent relay. As a result, directional overcurrent relays are employed to determine whether the fault is inside or outside the protective zone. The goal of overcurrent relay coordination is to

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Tang, Jiali. "Optimization of English Learning Platform Based on a Collaborative Filtering Algorithm." Complexity 2021 (April 29, 2021): 1–14. http://dx.doi.org/10.1155/2021/6624012.

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This paper provides a detailed description of the recommendation system and collaborative filtering algorithm to optimize the English learning platform through the collaborative filtering algorithm and analyses the algorithmic principles and specific techniques of collaborative filtering. After introducing the recommendation system and collaborative filtering algorithm, this paper elaborates on the theoretical basis and technical principles of the recommendation algorithm based on cognitive ability and difficulty and provides an in-depth analysis of the design and implementation of the recomme

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Zhang, Yu, Wei He, and Jianchuan Zhao. "Cooperative Sensing and Allocation Algorithm of Cognitive Radio Spectrum Based on Artificial Intelligence." Journal of Physics: Conference Series 2066, no. 1 (2021): 012059. http://dx.doi.org/10.1088/1742-6596/2066/1/012059.

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Abstract In recent years, with the rapid development of artificial intelligence technology, people’s demand for wireless spectrum resources is increasing, which poses a huge challenge to the originally tight and limited wireless spectrum resources. On the other hand, the traditional fixed spectrum cooperative sensing and allocation algorithms result in extremely low spectrum utilization for a considerable part of the licensed spectrum. The purpose of this paper is to study the cooperative sensing and allocation algorithm of cognitive RS (radio spectrum) based on artificial intelligence. This d

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Altalbe, Ali A., Aamir Shahzad, and Muhammad Nasir Khan. "Design, Development, and Experimental Verification of a Trajectory Algorithm of a Telepresence Robot." Applied Sciences 13, no. 7 (2023): 4537. http://dx.doi.org/10.3390/app13074537.

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Background: Over the last few decades, telepresence robots (TRs) have drawn significant attention in academic and healthcare systems due to their enormous benefits, including safety improvement, remote access and economics, reduced traffic congestion, and greater mobility. COVID-19 and advancements in the military play a vital role in developing TRs. Since then, research on the advancement of robots has been attracting much attention. Methods: In critical areas, the placement and movement of humans are not safe, and researchers have started looking at the development of robots. Robot developme

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Vasantha, Gokula, Jonathan Corney, and Chandra Kant Upadhyay. "Cognitive Factors Affecting the Manufacturing Optimization Skills of Rural Indian BPO Workers." Knowledge 3, no. 4 (2023): 626–41. http://dx.doi.org/10.3390/knowledge3040039.

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Crowdsourcing offers on-demand access to large numbers of human workers to implement new forms of human–computer collaborative functionalities that can be seamlessly integrated into advanced software and algorithms. However, crowdsourcing tasks are primarily undertaken by urban rather than rural workers. To enable the development of skilled rural employment, this research aims to assess rural crowdsourcing workers’ spatial reasoning and creative abilities and their abilities to solve irregular strip packing problems associated with the manufacture of sheet materials. The study conducted experi

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Gao, Chuanzhe, Shidang Li, Mingsheng Wei, Siyi Duan, and Jinsong Xu. "A Fair Energy Allocation Algorithm for IRS-Assisted Cognitive MISO Wireless-Powered Networks." Information 15, no. 1 (2024): 49. http://dx.doi.org/10.3390/info15010049.

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With the rapid development of wireless communication networks and Internet of Things technology (IoT), higher requirements have been put forward for spectrum resource utilization and system performance. In order to further improve the utilization of spectrum resources and system performance, this paper proposes an intelligent reflecting surface (IRS)-assisted fair energy allocation algorithm for cognitive multiple-input single-output (MISO) wireless-powered networks. The goal of this paper is to maximize the minimum energy receiving power in the energy receiver, which is constrained by the sig

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Saini, Dilip Kumar Jang Bahadur, Anupama Mishra, Dhirendra Siddharth, et al. "Development of Enhanced Chimp Optimization Algorithm (OFCOA) in Cognitive Radio Networks for Energy Management and Resource Allocation." International Journal of Software Science and Computational Intelligence 15, no. 1 (2024): 1–20. http://dx.doi.org/10.4018/ijssci.335898.

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Transmit time and power optimisation increase secondary network energy efficiency (EE). The optimum resource allocation strategy in cognitive radio networks is the enhanced chimp optimisation algorithm (OFCOA) since the EE maximising problem is a nonlinear fractional programming problem. To control resources and energy, this research offers an energy-efficient CRN opposition function-based chimpanzee optimisation algorithm (OFCOA) solution. Combining the opposition function (OF) with the chimpanzee optimisation technique is recommended. OF in COAs improves decision-making. Spectrum measurement

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Keshishyan, E. S., G. A. Alyamovskaya, E. S. Sakharova, et al. "Algorithm of diagnostics of cognitive functions development violation in children born extremally premature." Rossiyskiy Vestnik Perinatologii i Pediatrii (Russian Bulletin of Perinatology and Pediatrics) 64, no. 6 (2020): 39–44. http://dx.doi.org/10.21508/1027-4065-2019-64-6-39-44.

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A qualitative improvement in the management of pregnancy and delivery, optimization of General care and provision of intensive care for children born prematurely, particularly with low and extremely low body weight, significantly reduced the risk of damage to the nervous system of perinatal hypoxic-ischemic genesis. At the same time, there is a significant number of children born at low gestational age, with a significant violation of intellectual, cognitive development and behavior change. One of the assumptions about cause of improper maturation of the brain is the role of unbalanced chromos

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Baklanov, Oleksii, Volodymyr Bezkorovainyi, and Liudmyla Kolesnyk. "Studying cognitive services for websites search engine optimization." Bulletin of Kharkov National Automobile and Highway University, no. 97 (September 5, 2022): 7. http://dx.doi.org/10.30977/bul.2219-5548.2022.97.0.7.

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The subject of research in the article is machine learning models for classifying web-pages by quality and compliance with SEO rules. The goal of the article is improving the efficiency of search engines by establishing and using factors that have the greatest impact on the degree of SEO optimization of web pages. The article solves the following tasks: study of the effectiveness of using machine learning methods to build a classification model that automatically classifies web pages according to the degree of adaptation to SEO optimization recommendations; assessment of the influence of relev

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Sadhana D. Poshattiwar, Sandip B. Shrote ,. "Dynamic Spectrum Sensing For 5G Cognitive Radio Networks Using Optimization Technique." Journal of Electrical Systems 20, no. 3s (2024): 1221–31. http://dx.doi.org/10.52783/jes.1433.

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With increasing development of 5G technology, the rapid growth of various technologies and the growth of various wireless devices, demand for wireless spectrum becomes more urgent. Wireless communication technologies have been advancing rapidly, leading to the emergence of 5G communication systems .Spectrum sensing is the key model utilized to access the spectrum dynamically in CRN. Various researchers are done in spectrum sensing scenario and different methods are designed to perform the task of spectrum resource sharing. Most of the methods design a decision statistics for identifying the si

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Sharma, Divya, and Shikha Lohchab. "Search based Software Modularization Using Evolution Algorithm." NeuroQuantology 20, no. 5 (2022): 822–31. http://dx.doi.org/10.14704/nq.2022.20.5.nq22240.

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To comprehend a Software system, Software modularization strategies are used. The goal of modularization is to break down a software system into meaningful and intelligible sub-systems from its source-code (modules). Because software classification modularization is an NP-hard task, evolutionary methods produce better modularization quality rather than avaricious algorithms. All available transformative techniques for software modularization only take into account structural aspects reliant on programming language syntax. Because most computer languages lack a mechanism for extracting structur

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Peng, Jun, Yudeng Qiao, Dedong Tang, Lan Ge, Qinfeng Xia, and Tingting Chen. "The Least Squares SVM for the Prediction of Production in the Field of Oil and Gas." International Journal of Cognitive Informatics and Natural Intelligence 12, no. 1 (2018): 60–74. http://dx.doi.org/10.4018/ijcini.2018010105.

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With the development of cognitive information technology and continuous application, human society has also accelerated the development. Cognitive information is widely used in the field of oil and gas, where production forecasts are of great importance to firms and companies. In this article, the support vector machine and the least squares support vector machine (LS-SVM) and particle swarm optimization algorithm research, combined to accurately predict and make error estimates. In this article, the model is applied to verify the actual output data of certain enterprises in previous years. Th

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Anantharajan, Shenbagarajan, Shenbagalakshmi Gunasekaran, and havasi Subramanian. "Brain Tumor Segmentation based on Red-Bellied Woodpecker Mating Optimization Algorithm." NeuroQuantology 20, no. 5 (2022): 785–90. http://dx.doi.org/10.14704/nq.2022.20.5.nq22235.

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Earlier, many researchers proposed various segmentation algorithms to segment tumor from MRI Brain image. The method of a nature-inspired meta heuristic-based woodpecker characteristics approach is used to segment the tumored area of this proposed study. In this automated MRI brain tumor segmentation, the MRI brain image gets enhanced for improving the performance of the segmentation accompanied by the skull elimination phase to eliminate the morphological operations of all non-brain tissues. In the end, the RBWMOA (Red-Bellied Woodpecker Mating Optimization Algorithm) is suggested for the seg

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Hipparge, Praveen, and Shivkumar S. Jawaligi. "CHAOTIC EQUILIBRIUM OPTIMIZATION ALGORITHM BASED COOPERATIVE SPECTRUM SENSING AND ENERGY EFFICIENT COGNITIVE RADIO NETWORKS." ICTACT Journal on Communication Technology 14, no. 4 (2023): 3057–62. http://dx.doi.org/10.21917/ijct.2023.0455.

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The need for wireless communication in the present and the future is for green communication. The cognitive radio network must meet the requirements for green communication in order to be the next-generation communication network. So improving energy efficiency is a must for the development of cognitive radio networks. However, sensor performance must be reduced in order to improve energy efficiency. In order to consider the two key indicators of sensing performance and energy efficiency, this research suggests a Chaotic Equilibrium Optimization (CEO) method that may effectively boost energy e

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Ma, Xiaozheng, Yao Wang, and Long Zhang. "Multipath Stability Routing in Cognitive UAV Swarm for Emergency Communications: A Hypergraph Matching Approach." Wireless Communications and Mobile Computing 2022 (August 1, 2022): 1–11. http://dx.doi.org/10.1155/2022/6783041.

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With the rapid development of unmanned aerial vehicles (UAVs), it has been considered as an effective solution for emergency communications. In order to solve the contradiction between the rapid growth of user equipments and the shortage of spectrum resources as well as the problem that a single UAV cannot meet the multimission requirements, we integrate the cognitive radio spectrum access and UAVs to form a cognitive UAV swarm. Since most of the base stations cannot work properly in disaster scenarios, cognitive UAV swarm transmits the collected information through multihop routing in the for

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Hu, Zhiyong. "Study of the Effectiveness of 5G Mobile Internet Technology to Promote the Reform of English Teaching in the Universities and Colleges." Computational Intelligence and Neuroscience 2022 (July 13, 2022): 1–8. http://dx.doi.org/10.1155/2022/3053694.

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The development of educational information processes and information technology has made it possible to build a remote learning environment for English education. The application of fifth-generation communication (5G) has carried out revolutions in education for both teachers and students. In this study, an optimization approach is presented for English teaching mode to overcome the limits of current college English teaching settings and broaden the span of 5G technology. The proposed optimization technique varies from traditional college English teaching methods in that it integrates 5G, whic

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Ferens, Ken, Darcy Cook, and Witold Kinsner. "Chaotic Walk in Simulated Annealing Search Space for Task Allocation in a Multiprocessing System." International Journal of Cognitive Informatics and Natural Intelligence 7, no. 3 (2013): 58–79. http://dx.doi.org/10.4018/ijcini.2013070104.

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This paper proposes the application of chaos in large search space problems, and suggests that this represents the next evolutionary step in the development of adaptive and intelligent systems towards cognitive machines and systems. Three different versions of chaotic simulated annealing (XSA) were applied to combinatorial optimization problems in multiprocessor task allocation. Chaotic walks in the solution space were taken to search for the global optimum or “good enough” task-to-processor allocation solutions. Chaotic variables were generated to set the number of perturbations made in each

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Zhao, Hongwei, Tokan Caleb Abashe, and Ziqi Zhang. "APPLICATION OF EMOTION COMPUTING BASED ON EMOTION REGULATION COMBINED WITH EDGE COMPUTING IN EMERGENCY MANAGEMENT PLATFORM." International Journal of Neuropsychopharmacology 25, Supplement_1 (2022): A87—A88. http://dx.doi.org/10.1093/ijnp/pyac032.118.

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Abstract Background With the development of mobile Internet and intelligent Internet of things, more and more new generation information technologies are applied in the field of emergency management. At present, the traditional cloud computing architecture can no longer meet the dynamic and real-time computing needs in these scenarios. As a new computing architecture, edge computing and affective computing achieve the sinking of computing power through computing unloading. The development of affective computing depends on the research of human intelligence and emotion in cognitive psychology,

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Wang, Yan. "Applications and Ethical Challenges of AI and Virtual Reality (VR/AR) Technologies in Preschool Education." Lecture Notes in Education Psychology and Public Media 98, no. 1 (2025): 1–8. https://doi.org/10.54254/2753-7048/2025.24642.

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With the rapid development of artificial intelligence and virtual reality technologies, AI educational robots and VR immersive games are gradually revolutionizing the model of early childhood education. This study focuses on the personalized social training achieved by AI educational robots through natural language processing and emotion recognition technologies, as well as the simulation of real social scenarios by immersive virtual environments constructed with VR technology, and deeply explores its dual promoting effect on the cognitive and social ability development of young children. To a

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Ni, Hao. "Modeling and Optimization Analysis of Ancient Building Construction Rule Components Based on Deep Learning." Security and Communication Networks 2022 (September 21, 2022): 1–13. http://dx.doi.org/10.1155/2022/1119059.

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Chinese culture is broad and profound, and successive dynasties have left many cultural treasures. Ancient architecture is a significant treasure, and it is also the core content of the inheritance of Chinese culture. Every Chinese ancient building has its own characteristics, and the creative components of each ancient building are an important part of ancient buildings. As a new learning mode of current scientific inquiry, the deep learning model includes high-level and high-stage cognitive processing ability and innovative thinking ability. Under the background of the above modeling and opt

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Samigulina, G. A., and T. I. Samigulin. "Development of a cognitive mnemonic scheme for an optical Smart-technology of remote learning of the Experions PKS distributed control system on the basis of Artificial Immune Systems." Computer Optics 45, no. 2 (2021): 286–95. http://dx.doi.org/10.18287/2412-6179-co-736.

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The article discusses current issues related to the development of an information optical Smart technology for distance learning of Honeywell's distributed Experion PKS control system for the oil and gas industry. About 70 % of industrial accidents are caused by the human factor through the fault of operators. The work of operators consists in monitoring and managing high-tech proc-esses through mnemonic scheme circuits and is characterized by increased tension in the visual apparatus, as well as general fatigue and loss of concentration. The innovative personalized tech-nology of distance lea

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Elhoseny, Mohamed, Zahraa Tarek, and Ibrahim M. EL-Hasnony. "Advanced Cognitive Algorithm for Biomedical Data Processing: COVID-19 Pattern Recognition as a Case Study." Journal of Healthcare Engineering 2022 (March 22, 2022): 1–11. http://dx.doi.org/10.1155/2022/1773259.

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Automated disease prediction has now become a key concern in medical research due to exponential population growth. The automated disease identification framework aids physicians in diagnosing disease, which delivers accurate disease prediction that provides rapid outcomes and decreases the mortality rate. The spread of Coronavirus disease 2019 (COVID-19) has a significant effect on public health and the everyday lives of individuals currently residing in more than 100 nations. Despite effective attempts to reach an appropriate trend to forecast COVID-19, the origin and mutation of the virus i

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Raveendra Reddy Enumula. "Development of Improved Weighed Quantum Lion Optimization with Smooth Support Vector Machine for Alzheimer’s Disease." Journal of Electrical Systems 20, no. 2 (2024): 2328–42. http://dx.doi.org/10.52783/jes.1999.

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Accurate diagnosis of Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) was identified on an early stage is essential in the healthcare industry to stop degeneration. The Smooth Support Vector Machine (SSVM) model, Principal Component Analysis (PCA), feature extraction, and Magnetic Resonance Imaging (MRI) image prepossessing are the components for the diagnosis of AD is proposed in this research at early stage. To assist in the classifier's training, we proposed a novel Improved Weighed Quantum Lion Optimization (IWQLO). The SSVM parameters are specifically proposed to be optimized

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Jiao, Jie, Guangsheng Feng, and Gang Yuan. "Research on the Human–Robot Collaborative Disassembly Line Balancing of Spent Lithium Batteries with a Human Factor Load." Batteries 10, no. 6 (2024): 196. http://dx.doi.org/10.3390/batteries10060196.

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The disassembly of spent lithium batteries is a prerequisite for efficient product recycling, the first link in remanufacturing, and its operational form has gradually changed from traditional manual disassembly to robot-assisted human–robot cooperative disassembly. Robots exhibit robust load-bearing capacity and perform stable repetitive tasks, while humans possess subjective experiences and tacit knowledge. It makes the disassembly activity more adaptable and ergonomic. However, existing human–robot collaborative disassembly studies have neglected to account for time-varying human conditions

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Xiao, Haitao, Limeng Dong, and Wenjie Wang. "Intelligent Reflecting Surface-Assisted Secure Multi-Input Single-Output Cognitive Radio Transmission." Sensors 20, no. 12 (2020): 3480. http://dx.doi.org/10.3390/s20123480.

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Intelligent reflecting surface (IRS) is a very promising technology for the development of beyond 5G or 6G wireless communications due to its low complexity, intelligence, and green energy-efficient properties. In this paper, we combined IRS with physical layer security (PLS) to solve the security issue of cognitive radio (CR) networks. Specifically, an IRS-assisted multi-input single-output (MISO) CR wiretap channel was studied. To maximize the secrecy rate of secondary users subject to a total power constraint (TPC) for the transmitter and interference power constraint (IPC) for a single ant

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Ji, Meng, Yanmeng Liu, and Tianyong Hao. "Predicting Health Material Accessibility: Development of Machine Learning Algorithms." JMIR Medical Informatics 9, no. 9 (2021): e29175. http://dx.doi.org/10.2196/29175.

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Background Current health information understandability research uses medical readability formulas to assess the cognitive difficulty of health education resources. This is based on an implicit assumption that medical domain knowledge represented by uncommon words or jargon form the sole barriers to health information access among the public. Our study challenged this by showing that, for readers from non-English speaking backgrounds with higher education attainment, semantic features of English health texts that underpin the knowledge structure of English health texts, rather than medical jar

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Aldabbagh, Ghada, Daniyal M. Alghazzawi, Syed Hamid Hasan, Mohammed Alhaddad, Areej Malibari, and Li Cheng. "Optimal Learning Behavior Prediction System Based on Cognitive Style Using Adaptive Optimization-Based Neural Network." Complexity 2020 (November 5, 2020): 1–13. http://dx.doi.org/10.1155/2020/6097167.

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Widespread development of system software, the process of learning, and the excellence in profession of teaching are the formidable challenges faced by the learning behavior prediction system. The learning styles of teachers have different kinds of content designs to enhance their learning. In this learning environment, teachers can work together with the students, but the learning materials are designed by the teachers. The cognitive style deals with mental activities such as learning, remembering, thinking, and the usage of language. Therefore, being motivated by the problems mentioned above

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Abdikeev, Niyaz Mustjakimovich, and Anton Alekseevich Losev. "MANAGEMENT OF VALUE-ADDED REPRODUCTION CHAINS IN PRODUCTION SYSTEMS BASED ON A COGNITIVE APPROACH." Computational nanotechnology 6, no. 4 (2019): 18–23. http://dx.doi.org/10.33693/2313-223x-2019-6-4-18-23.

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The Concept of competitive value chains in production systems, as an institutional structure operating on network principles, was the impetus for the development of a system of models of inter-industry digital platform for the management and optimization of cooperation of high-tech network production systems. The paper describes the process of working with the cognitive model of decision support in the management of value chains in production systems, the algorithm for constructing a conflict resolution diagram, the ways of integrating it into business processes in interaction with other model

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Renukadevi, P., and Dr A. Rajiv Kannan. "Improved Linear Factor based Grasshopper Optimization Algorithm with Ensemble Learning for Covid-19 Forecasting." NeuroQuantology 19, no. 8 (2021): 169–81. http://dx.doi.org/10.14704/nq.2021.19.8.nq21129.

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Recently the COVID’19 is extensively increasing around the world with many challenges for researchers. Rigorous respiratory disease corona virus 2 show aggression to many parts of COVID’19 affected patients, together with brain and lungs. The changeableness of Corona virus with likely to infect Central Nervous System emphasize the necessity for technological development to identify, handle, and take care of brain damages in COVID’19 patients. An exact short-term predicting the quantity of newly infected and cured cases is vital for resource optimization to stop or reduce the growth of infectio

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Массель, Алексей Геннадьевич, Тимур Габилович Мамедов, and Наталья Ивановна Пяткова. "COMPUTATIONAL EXPERIMENT TECHNOLOGY IN RESEARCH OF POWER INDUSTRIES WHEN IMPLEMENTING THREATS TO ENERGY SECURITY." Информационные и математические технологии в науке и управлении, no. 3(23) (November 8, 2021): 62–73. http://dx.doi.org/10.38028/esi.2021.23.3.006.

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В работе представлен алгоритм проведения вычислительного эксперимента на примере реализации одной из угроз энергетической безопасности «Недостаток инвестиций в отрасли энергетики» с использованием когнитивных и экономико-математических моделей. Рассмотрены особенности включения инвестиционной составляющей в модель оптимизации вариантов развития ТЭК с учетом энергетической безопасности. Представлена когнитивная модель для анализа угрозы «Недостаток инвестиций в отрасли энергетики». Дается описание ПК ИНТЭК-А, обеспечивающего возможность интеграции когнитивных и математических моделей. The paper

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Iwazaki, Shogo, Yu Inatsu, and Ichiro Takeuchi. "Bayesian Quadrature Optimization for Probability Threshold Robustness Measure." Neural Computation 33, no. 12 (2021): 3413–66. http://dx.doi.org/10.1162/neco_a_01442.

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Abstract In many product development problems, the performance of the product is governed by two types of parameters: design parameters and environmental parameters. While the former is fully controllable, the latter varies depending on the environment in which the product is used. The challenge of such a problem is to find the design parameter that maximizes the probability that the performance of the product will meet the desired requisite level given the variation of the environmental parameter. In this letter, we formulate this practical problem as active learning (AL) problems and propose

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Cui, Xiaoye, Yijie Li, Lishengsa Yue, Haoyu Chen, and Ziyou Zhou. "Investigating Blind Spot Design Effects on Drivers’ Cognitive Load with Lane Changing: A Comparative Experiment with Multiple Types of Intelligent Vehicles." Applied Sciences 14, no. 17 (2024): 7570. http://dx.doi.org/10.3390/app14177570.

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Lane changing is a frequent traffic accident scenario. To improve the driving safety in lane changing scenarios, the blind spot display of lane changing is increased through human–machine interaction (HMI) interfaces in intelligent vehicles to improve the driver’s rate of risk perception with regard to the driving environment. However, blind spot information will increase the cognitive load of drivers and lead to driving distraction. To quantify the coupling relationship between blind spot display and drivers’ cognitive load, we proposed a method to quantify the cognitive load of the driver’s

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Sengupta, Saptarshi, Sanchita Basak, and Richard Peters. "Particle Swarm Optimization: A Survey of Historical and Recent Developments with Hybridization Perspectives." Machine Learning and Knowledge Extraction 1, no. 1 (2018): 157–91. http://dx.doi.org/10.3390/make1010010.

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Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has gained prominence in the last two decades due to its ease of application in unsupervised, complex multidimensional problems that cannot be solved using traditional deterministic algorithms. The canonical particle swarm optimizer is based on the flocking behavior and social co-operation of birds and fish schools and draws heavily from the evolutionary behavior of these organisms. This paper serves to provide a thorough survey of the PSO algorithm with special emphasis on the development, deployment, and i

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Leite, Walter L., I.-Chan Huang, and George A. Marcoulides. "Item Selection for the Development of Short Forms of Scales Using an Ant Colony Optimization Algorithm." Multivariate Behavioral Research 43, no. 3 (2008): 411–31. http://dx.doi.org/10.1080/00273170802285743.

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Al Duhayyim, Mesfer, Heba G. Mohamed, Jaber S. Alzahrani, et al. "Modeling of Fuzzy Cognitive Maps with a Metaheuristics-Based Rainfall Prediction System." Sustainability 15, no. 1 (2022): 25. http://dx.doi.org/10.3390/su15010025.

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Rainfall prediction remains a hot research topic in smart city environments. Precise rainfall prediction in smart cities becomes essential for planning security measures before construction and transportation activities, flight operations, water reservoir systems, and agricultural tasks. Precise rainfall forecasting now becomes more complex than before because of extreme climatic changes. Machine learning (ML) approaches can forecast rainfall by deriving hidden patterns from historic meteorological datasets. Selecting a suitable classification method for forecasting has become a tough job. Thi

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Obayya, Marwa, Adeeb Alhebri, Mashael Maashi, et al. "Henry Gas Solubility Optimization Algorithm based Feature Extraction in Dermoscopic Images Analysis of Skin Cancer." Cancers 15, no. 7 (2023): 2146. http://dx.doi.org/10.3390/cancers15072146.

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Artificial Intelligence (AI) techniques have changed the general perceptions about medical diagnostics, especially after the introduction and development of Convolutional Neural Networks (CNN) and advanced Deep Learning (DL) and Machine Learning (ML) approaches. In general, dermatologists visually inspect the images and assess the morphological variables such as borders, colors, and shapes to diagnose the disease. In this background, AI techniques make use of algorithms and computer systems to mimic the cognitive functions of the human brain and assist clinicians and researchers. In recent yea

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Liu, Yuqi, Jiaqing Chen, and Molan Wang. "BO–FTT: A Deep Learning Model Based on Parameter Tuning for Early Disease Prediction from a Case of Anemia in CKD." Electronics 14, no. 12 (2025): 2471. https://doi.org/10.3390/electronics14122471.

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Renal anemia (RA) is a common complication of chronic kidney disease (CKD). Patients with prolonged RA may present with nonspecific systemic manifestations, including cold intolerance, fatigue, drowsiness, anorexia, muscle weakness, reduced physical activity, impaired memory and cognitive function, and difficulty concentrating. Although previous studies have identified risk factors for anemia development in CKD, challenges remain in early diagnosis and therapeutic intervention. Therefore, we analyzed a dataset of CKD patients with RA from the MIMIC database and used machine learning models to

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Yao, Cenglin, Yongzhou Li, Mohd Dilshad Ansari, Mohammed Ahmed Talab, and Amit Verma. "Optimization of industrial process parameter control using improved genetic algorithm for industrial robot." Paladyn, Journal of Behavioral Robotics 13, no. 1 (2022): 67–75. http://dx.doi.org/10.1515/pjbr-2022-0006.

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Abstract A number of suggestions are made based on the improved evolutionary algorithm and using the polishing parameter optimization of an industrial robot as an example to optimize the industrial process parameter control. By fitting a cubic B-spline curve, the trajectory curve of each joint is determined. The kinematic constraint is replaced with the control point constraint of a B-spline curve, and the time optimal time node is solved using an enhanced evolutionary algorithm. This foundation allows for the creation of the nonlinear trajectory curve that satisfies the time optimization. The

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Hu, Zechun, and Zhengfeng Huang. "Biomechanical research on the construction and optimization of youth basketball training system based on the integration of sports and education." Molecular & Cellular Biomechanics 22, no. 2 (2025): 797. https://doi.org/10.62617/mcb797.

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The development and improvement of a youth basketball training program founded on the fusion of education and sports is investigated in this study. Athlete performance and academic advancement must be balanced in light of the growing need for comprehensive youth development. Biomechanical factors play a significant role in both sports performance and injury prevention, making it essential to integrate them into the training program design. To increase the effectiveness and design of training programs, the suggested model makes use of the Tabu Search Optimized Intelligent Random Forest (TSO-IRF

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Senthamarai, C., and N. Malmurugan. "Efficient Spectral Allocation for Cognitive Full Duplex Relay Network Systems Based Soft Computing Technique." Current Signal Transduction Therapy 15, no. 1 (2020): 46–55. http://dx.doi.org/10.2174/1574362413666180831105203.

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Background: Due to the huge development of wireless devices and mobile data traffic had gained attention towards identifying accurate solutions for more proficient utilization of the wireless spectrum. An essential issue confronting the future in wireless systems is to identify the appropriate spectrum bands to satisfy the request of future administrations. While the greater part of the radio spectrum is allocated to various services, applications and users show that spectrum usage is quite low. Materials and Methods: The spectrum sensing is performed at the start of each time slot before the

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