Displaying publications 1 - 20 of 353 in total

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  1. Fulltext Future stem cell analysis: progress and challenges towards state-of-the art approaches in automated cells analysis
    Mohamad Zamani NS, Wan Zaki WMD, Abd Hamid Z, Baseri Huddin A
    PeerJ, 2022;10:e14513.
    PMID: 36573241 DOI: 10.7717/peerj.14513
    BACKGROUND AND AIMS: A microscopic image has been used in cell analysis for cell type identification and classification, cell counting and cell size measurement. Most previous research works are tedious, including detailed understanding and time-consuming. The scientists and researchers are seeking modern and automatic cell analysis approaches in line with the current in-demand technology.

    OBJECTIVES: This article provides a brief overview of a general cell and specific stem cell analysis approaches from the history of cell discovery up to the state-of-the-art approaches.

    METHODOLOGY: A content description of the literature study has been surveyed from specific manuscript databases using three review methods: manuscript identification, screening, and inclusion. This review methodology is based on Prism guidelines in searching for originality and novelty in studies concerning cell analysis.

    RESULTS: By analysing generic cell and specific stem cell analysis approaches, current technology offers tremendous potential in assisting medical experts in performing cell analysis using a method that is less laborious, cost-effective, and reduces error rates.

    CONCLUSION: This review uncovers potential research gaps concerning generic cell and specific stem cell analysis. Thus, it could be a reference for developing automated cells analysis approaches using current technology such as artificial intelligence and deep learning.

    Matched MeSH terms: Artificial Intelligence*
  2. Fulltext Consistency and Accuracy of Artificial Intelligence for Providing Nutritional Information
    Hoang YN, Chen YL, Ho DKN, Chiu WC, Cheah KJ, Mayasari NR, et al.
    JAMA Netw Open, 2023 Dec 01;6(12):e2350367.
    PMID: 38150258 DOI: 10.1001/jamanetworkopen.2023.50367
    Matched MeSH terms: Artificial Intelligence*
  3. Fulltext Computational intelligence and metaheuristic algorithms with applications
    Yang XS, Chien SF, Ting TO
    ScientificWorldJournal, 2014;2014:425853.
    PMID: 25610904 DOI: 10.1155/2014/425853
    Matched MeSH terms: Artificial Intelligence*
  4. Fulltext Examining the psychometric properties of the Schutte’s Self Report Emotional Intelligences Scale (SREIS)
    Nurul-Azza A
    Jurnal Psikologi Malaysia, 2018;32:19-29.
    Emotional intelligence is usually used in order to measure an individual’s effectiveness. One of the instruments that is used to measure emotional intelligence is Schutte’s Self-Report Emotional Intelligence Survey (SREIS). The main objective of this study is to evaluate the psychometric properties of SREIS. A set of SREIS was distributed to 152 undergraduate psychology students from a public university in Malaysia. Other than SREIS, Life Satisfaction Scale (LSS) by Krapu (2006) was also used in this study. In evaluating reliability, Cronbach’s alpha was used, and criterion and construct validity methods were used to test its validity. Results obtained showed that Schutte’s SREIS was valid to be used in Malaysia and using principle component analysis, six components were extracted with 49% variance. The SREIS also showed good criterion validity from the significant correlations with the Life Satisfaction Scale. In addition to that, the results of reliability were satisfactory with Cronbach’s alpha ranging from 0.55 to 0.85 for all the dimensions.
    Matched MeSH terms: Emotional Intelligence
  5. Fulltext The contribution of particle swarm optimization to three-dimensional slope stability analysis
    Kalatehjari R, Rashid AS, Ali N, Hajihassani M
    ScientificWorldJournal, 2014;2014:973093.
    PMID: 24991652 DOI: 10.1155/2014/973093
    Over the last few years, particle swarm optimization (PSO) has been extensively applied in various geotechnical engineering including slope stability analysis. However, this contribution was limited to two-dimensional (2D) slope stability analysis. This paper applied PSO in three-dimensional (3D) slope stability problem to determine the critical slip surface (CSS) of soil slopes. A detailed description of adopted PSO was presented to provide a good basis for more contribution of this technique to the field of 3D slope stability problems. A general rotating ellipsoid shape was introduced as the specific particle for 3D slope stability analysis. A detailed sensitivity analysis was designed and performed to find the optimum values of parameters of PSO. Example problems were used to evaluate the applicability of PSO in determining the CSS of 3D slopes. The first example presented a comparison between the results of PSO and PLAXI-3D finite element software and the second example compared the ability of PSO to determine the CSS of 3D slopes with other optimization methods from the literature. The results demonstrated the efficiency and effectiveness of PSO in determining the CSS of 3D soil slopes.
    Matched MeSH terms: Artificial Intelligence*
  6. What does ChatGPT advise about predatory publishing?
    Tsigaris P, Kendall G, Teixeira da Silva JA
    J Prof Nurs, 2023;49:188-189.
    PMID: 38042556 DOI: 10.1016/j.profnurs.2023.08.002
    The debate surrounding "predatory publishing" continues to be unable to find entirely effective solutions to dealing with this problem, despite fervent efforts by many academics and policy makers around the world. Given this situation, we were interested in appreciating whether ChatGPT would be able to offer insight and solutions, to complement current human-based efforts.
    Matched MeSH terms: Artificial Intelligence*
  7. Fulltext Explainable AI in Scene Understanding for Autonomous Vehicles in Unstructured Traffic Environments on Indian Roads Using the Inception U-Net Model with Grad-CAM Visualization
    Kolekar S, Gite S, Pradhan B, Alamri A
    Sensors (Basel), 2022 Dec 10;22(24).
    PMID: 36560047 DOI: 10.3390/s22249677
    The intelligent transportation system, especially autonomous vehicles, has seen a lot of interest among researchers owing to the tremendous work in modern artificial intelligence (AI) techniques, especially deep neural learning. As a result of increased road accidents over the last few decades, significant industries are moving to design and develop autonomous vehicles. Understanding the surrounding environment is essential for understanding the behavior of nearby vehicles to enable the safe navigation of autonomous vehicles in crowded traffic environments. Several datasets are available for autonomous vehicles focusing only on structured driving environments. To develop an intelligent vehicle that drives in real-world traffic environments, which are unstructured by nature, there should be an availability of a dataset for an autonomous vehicle that focuses on unstructured traffic environments. Indian Driving Lite dataset (IDD-Lite), focused on an unstructured driving environment, was released as an online competition in NCPPRIPG 2019. This study proposed an explainable inception-based U-Net model with Grad-CAM visualization for semantic segmentation that combines an inception-based module as an encoder for automatic extraction of features and passes to a decoder for the reconstruction of the segmentation feature map. The black-box nature of deep neural networks failed to build trust within consumers. Grad-CAM is used to interpret the deep-learning-based inception U-Net model to increase consumer trust. The proposed inception U-net with Grad-CAM model achieves 0.622 intersection over union (IoU) on the Indian Driving Dataset (IDD-Lite), outperforming the state-of-the-art (SOTA) deep neural-network-based segmentation models.
    Matched MeSH terms: Artificial Intelligence*; Intelligence
  8. Fulltext A Vision-Based Machine Learning Method for Barrier Access Control Using Vehicle License Plate Authentication
    Islam KT, Raj RG, Shamsul Islam SM, Wijewickrema S, Hossain MS, Razmovski T, et al.
    Sensors (Basel), 2020 Jun 24;20(12).
    PMID: 32599883 DOI: 10.3390/s20123578
    Automatic vehicle license plate recognition is an essential part of intelligent vehicle access control and monitoring systems. With the increasing number of vehicles, it is important that an effective real-time system for automated license plate recognition is developed. Computer vision techniques are typically used for this task. However, it remains a challenging problem, as both high accuracy and low processing time are required in such a system. Here, we propose a method for license plate recognition that seeks to find a balance between these two requirements. The proposed method consists of two stages: detection and recognition. In the detection stage, the image is processed so that a region of interest is identified. In the recognition stage, features are extracted from the region of interest using the histogram of oriented gradients method. These features are then used to train an artificial neural network to identify characters in the license plate. Experimental results show that the proposed method achieves a high level of accuracy as well as low processing time when compared to existing methods, indicating that it is suitable for real-time applications.
    Matched MeSH terms: Intelligence
  9. Modified Cramer’s rule and its application to solve linear systems in WZ factorization
    Olayiwola Babarinsa, Hailiza Kamarulhaili
    MATEMATIKA, 2019;35(1):25-38.
    MyJurnal
    The proposed modified methods of Cramer's rule consider the column vector as well as the coefficient matrix concurrently in the linear system. The modified methods can be applied since Cramer's rule is typically known for solving the linear systems in $WZ$ factorization to yield Z-matrix. Then, we presented our results to show that there is no tangible difference in performance time between Cramer's rule and the modified methods in the factorization from improved versions of MATLAB. Additionally, the Frobenius norm of the modified methods in the factorization is better than using Cramer's rule irrespective of the version of MATLAB used.
    Matched MeSH terms: Artificial Intelligence
  10. Fulltext Adaptive particle swarm optimisation for solving non-convex economic dispatch problems
    Nurhafizah Jamain, Ismail Musirin, Mohd Helmi Mansor, Muhammad Murtadha Othman, Siti Aliyah Mohd Salleh
    Pertanika Journal of Science & Technology, 2017;25(103):275-286.
    MyJurnal
    This paper presents adaptive particle swarm optimization for solving non-convex economic dispatch problems. In this study, a new technique was developed known as adaptive particle swarm optimization (APSO), to alleviate the problems experienced in the traditional particle swarm optimisation (PSO). The traditional PSO was reported that this technique always stuck at local minima. In APSO, economic dispatch problem are considered with valve point effects. The search efficiency was improved when a new parameter was inserted into the velocity term. This has achieved local minima. In order to show the effectiveness of the proposed technique, this study examined two case studies, with and without contingency.
    Matched MeSH terms: Artificial Intelligence
  11. Fulltext A Novel Markov Model-Based Traffic Density Estimation Technique for Intelligent Transportation System
    Beenish H, Javid T, Fahad M, Siddiqui AA, Ahmed G, Syed HJ
    Sensors (Basel), 2023 Jan 09;23(2).
    PMID: 36679565 DOI: 10.3390/s23020768
    An intelligent transportation system (ITS) aims to improve traffic efficiency by integrating innovative sensing, control, and communications technologies. The industrial Internet of things (IIoT) and Industrial Revolution 4.0 recently merged to design the industrial Internet of things-intelligent transportation system (IIoT-ITS). IIoT sensing technologies play a significant role in acquiring raw data. The application continuously performs the complex task of managing traffic flows effectively based on several parameters, including the number of vehicles in the system, their location, and time. Traffic density estimation (TDE) is another important derived parameter desirable to keep track of the dynamic state of traffic volume. The expanding number of vehicles based on wireless connectivity provides new potential to predict traffic density more accurately and in real time as previously used methodologies. We explore the topic of assessing traffic density by using only a few simple metrics, such as the number of surrounding vehicles and disseminating beacons to roadside units and vice versa. This research paper investigates TDE techniques and presents a novel Markov model-based TDE technique for ITS. Finally, an OMNET++-based approach with an implementation of a significant modification of a traffic model combined with mathematical modeling of the Markov model is presented. It is intended for the study of real-world traffic traces, the identification of model parameters, and the development of simulated traffic.
    Matched MeSH terms: Intelligence
  12. Fulltext Genetic justification of COVID-19 patient outcomes using DERGA, a novel data ensemble refinement greedy algorithm
    Asteris PG, Gandomi AH, Armaghani DJ, Tsoukalas MZ, Gavriilaki E, Gerber G, et al.
    J Cell Mol Med, 2024 Feb;28(4):e18105.
    PMID: 38339761 DOI: 10.1111/jcmm.18105
    Complement inhibition has shown promise in various disorders, including COVID-19. A prediction tool including complement genetic variants is vital. This study aims to identify crucial complement-related variants and determine an optimal pattern for accurate disease outcome prediction. Genetic data from 204 COVID-19 patients hospitalized between April 2020 and April 2021 at three referral centres were analysed using an artificial intelligence-based algorithm to predict disease outcome (ICU vs. non-ICU admission). A recently introduced alpha-index identified the 30 most predictive genetic variants. DERGA algorithm, which employs multiple classification algorithms, determined the optimal pattern of these key variants, resulting in 97% accuracy for predicting disease outcome. Individual variations ranged from 40 to 161 variants per patient, with 977 total variants detected. This study demonstrates the utility of alpha-index in ranking a substantial number of genetic variants. This approach enables the implementation of well-established classification algorithms that effectively determine the relevance of genetic variants in predicting outcomes with high accuracy.
    Matched MeSH terms: Artificial Intelligence
  13. Fulltext Heuristics for multiobjective optimization of two-sided assembly line systems
    Jawahar N, Ponnambalam SG, Sivakumar K, Thangadurai V
    ScientificWorldJournal, 2014;2014:458959.
    PMID: 24790568 DOI: 10.1155/2014/458959
    Products such as cars, trucks, and heavy machinery are assembled by two-sided assembly line. Assembly line balancing has significant impacts on the performance and productivity of flow line manufacturing systems and is an active research area for several decades. This paper addresses the line balancing problem of a two-sided assembly line in which the tasks are to be assigned at L side or R side or any one side (addressed as E). Two objectives, minimum number of workstations and minimum unbalance time among workstations, have been considered for balancing the assembly line. There are two approaches to solve multiobjective optimization problem: first approach combines all the objectives into a single composite function or moves all but one objective to the constraint set; second approach determines the Pareto optimal solution set. This paper proposes two heuristics to evolve optimal Pareto front for the TALBP under consideration: Enumerative Heuristic Algorithm (EHA) to handle problems of small and medium size and Simulated Annealing Algorithm (SAA) for large-sized problems. The proposed approaches are illustrated with example problems and their performances are compared with a set of test problems.
    Matched MeSH terms: Artificial Intelligence*
  14. Commentary on Bailey C, Murphy R & Porock D (2011) Professional tears: developing emotional intelligence around death and dying in emergency work. Journal of Clinical Nursing 20, 3364-3372
    Hassan H, Das S
    J Clin Nurs, 2012 May;21(9-10):1492-3.
    PMID: 22494424 DOI: 10.1111/j.1365-2702.2011.04060.x
    Matched MeSH terms: Intelligence*
  15. A Synthesis of Spiritual Intelligence Themes from Islamic and Western Philosophical Perspectives
    Hanefar SB, Sa'ari CZ, Siraj S
    J Relig Health, 2016 Dec;55(6):2069-85.
    PMID: 27048294 DOI: 10.1007/s10943-016-0226-7
    Spiritual intelligence is an emerging term that is widely discussed and accepted as one of the main components that addresses and solves many life problems. Nonetheless there is no specific study being done to synthesize the spiritual intelligence themes from Western and Islamic philosophical perspectives. This research aimed to identify common spiritual intelligence themes from these two perspectives and elucidated its contents by the view of two well-known Islamic scholars; al-Ghazali and Hasan Langgulung. Seven spiritual intelligence themes were identified through thematic analysis; meaning/purpose of life, consciousness, transcendence, spiritual resources, self-determination, reflection-soul purification and spiritual coping with obstacles. These findings will be the groundwork for centered theory of spiritual intelligence themes that synthesize the Islamic and Western philosophical perspectives. It is hoped that this study will contribute significantly to the development of valid and reliable spiritual intelligence themes beyond the social and cultural boundaries.
    Matched MeSH terms: Intelligence*
  16. Fulltext Emotional Intelligence and Depressive Symptoms as Predictors of Happiness Among Adolescents
    Abdollahi A, Abu Talib M, Motalebi SA
    Iran J Psychiatry Behav Sci, 2015 Dec;9(4):e2268.
    PMID: 26834804 DOI: 10.17795/ijpbs-2268
    BACKGROUND: Given that happiness is an important construct to enable adolescents to cope better with difficulties and stress of life, it is necessary to advance our knowledge about the possible etiology of happiness in adolescents.
    OBJECTIVES:The present study sought to investigate the relationships of emotional intelligence, depressive symptoms, and happiness in a sample of male students in Tehran, Iran.
    MATERIALS AND METHODS: This cross-sectional study was conducted on a sample of high school students in Tehran in 2012. The participants comprised of 188 male students (aged 16 to 19 years old) selected by multi-stage cluster sampling method. For gathering the data, the students filled out assessing emotions scale, Beck depression inventory-II, and Oxford happiness inventory. Data analysis was carried out using descriptive and analytical statistics in statistical package for social sciences (SPSS) software.
    RESULTS: The findings showed that a significant positive association existed between high ability of emotional intelligence and happiness (P < 0.01). Conversely, the low ability of emotional intelligence was associated with unhappiness (P < 0.01), there was a positive association between non-depression symptoms and happiness (P < 0.05), and severe depressive symptoms were positively associated with unhappiness (P < 0.01). High ability of emotional intelligence (P < 0.01) and non-depression symptoms (P < 0.05) were the strongest predictors of happiness.
    CONCLUSIONS: These findings reinforced the importance of emotional intelligence as a facilitating factor for happiness in adolescences. In addition, the findings suggested that depression symptoms may be harmful for happiness in adolescents.

    KEYWORDS:
    Depression; Emotional Intelligence; Iranian Students; Wellbeing
    Matched MeSH terms: Emotional Intelligence*
  17. Fulltext Application of artificial neural network for automatic contingency analysis in power security assessment
    Ismail Musirin, Titik Khawa Abdul Rahman
    Scientific Research Journal, 2006;3(1):11-25.
    MyJurnal
    Several incidents that occurred around the world involving power failure
    caused by unscheduled line outages were identified as one of the main
    contributors to power failure and cascading blackout in electric power
    environment. With the advancement of computer technologies, artificial
    intelligence (AI) has been widely accepted as one method that can be applied
    to predict the occurrence of unscheduled disturbance. This paper presents
    the development of automatic contingency analysis and ranking algorithm
    for the application in the Artificial Neural Network (ANN). The ANN is
    developed in order to predict the post-outage severity index from a set of preoutage
    data set. Data were generated using the newly developed automatic
    contingency analysis and ranking (ACAR) algorithm. Tests were conducted
    on the 24-bus IEEE Reliability Test Systems. Results showed that the developed
    technique is feasible to be implemented practically and an agreement was
    achieved in the results obtained from the tests. The developed ACAR can be
    utilised for further testing and implementation in other IEEE RTS test systems
    particularly in the system, which required fast computation time. On the other
    hand, the developed ANN can be used for predicting the post-outage severity
    index and hence system stability can be evaluated.
    Matched MeSH terms: Artificial Intelligence; Intelligence
  18. Fulltext Can Building "Artificially Intelligent Cities" Safeguard Humanity from Natural Disasters, Pandemics, and Other Catastrophes? An Urban Scholar's Perspective
    Yigitcanlar T, Butler L, Windle E, Desouza KC, Mehmood R, Corchado JM
    Sensors (Basel), 2020 May 25;20(10).
    PMID: 32466175 DOI: 10.3390/s20102988
    In recent years, artificial intelligence (AI) has started to manifest itself at an unprecedented pace. With highly sophisticated capabilities, AI has the potential to dramatically change our cities and societies. Despite its growing importance, the urban and social implications of AI are still an understudied area. In order to contribute to the ongoing efforts to address this research gap, this paper introduces the notion of an artificially intelligent city as the potential successor of the popular smart city brand-where the smartness of a city has come to be strongly associated with the use of viable technological solutions, including AI. The study explores whether building artificially intelligent cities can safeguard humanity from natural disasters, pandemics, and other catastrophes. All of the statements in this viewpoint are based on a thorough review of the current status of AI literature, research, developments, trends, and applications. This paper generates insights and identifies prospective research questions by charting the evolution of AI and the potential impacts of the systematic adoption of AI in cities and societies. The generated insights inform urban policymakers, managers, and planners on how to ensure the correct uptake of AI in our cities, and the identified critical questions offer scholars directions for prospective research and development.
    Matched MeSH terms: Artificial Intelligence*
  19. Fulltext Modern Trends and Applications of Intelligent Methods in Biomedical Signal and Image Processing
    Kubicek J, Penhaker M, Krejcar O, Selamat A
    Sensors (Basel), 2021 Jan 27;21(3).
    PMID: 33513910 DOI: 10.3390/s21030847
    There are various modern systems for the measurement and consequent acquisition of valuable patient's records in the form of medical signals and images, which are supposed to be processed to provide significant information about the state of biological tissues [...].
    Matched MeSH terms: Artificial Intelligence*
  20. Artificial intelligence in drug development: present status and future prospects
    Mak KK, Pichika MR
    Drug Discov Today, 2019 03;24(3):773-780.
    PMID: 30472429 DOI: 10.1016/j.drudis.2018.11.014
    Artificial intelligence (AI) uses personified knowledge and learns from the solutions it produces to address not only specific but also complex problems. Remarkable improvements in computational power coupled with advancements in AI technology could be utilised to revolutionise the drug development process. At present, the pharmaceutical industry is facing challenges in sustaining their drug development programmes because of increased R&D costs and reduced efficiency. In this review, we discuss the major causes of attrition rates in new drug approvals, the possible ways that AI can improve the efficiency of the drug development process and collaboration of pharmaceutical industry giants with AI-powered drug discovery firms.
    Matched MeSH terms: Artificial Intelligence*
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