Journal of Autonomous Intelligence最新文献

{"title":"Exploring the relationship between computational frameworks and neuroscience studies for sensorimotor learning and control","authors":"Ahmed Mahmood Khudhur","doi":"10.32629/jai.v7i3.1245","DOIUrl":"https://doi.org/10.32629/jai.v7i3.1245","url":null,"abstract":"The relationship between computational frameworks and neuroscience studies is crucial for understanding sensorimotor learning and control. Various tools and frameworks, such as Bayesian decision theory, neural dynamics framework, and state space framework, have been used to explore this relationship. Bayesian decision theory provides a mathematical framework for studying sensorimotor control and learning. It suggests that the central nervous system constructs estimate of sensorimotor transformations through internal models and represents uncertainty to respond optimally to environmental stimuli. The neural dynamics framework analyzes patterns of neural activity to understand the computational mechanisms underlying sensorimotor control and learning. The state space framework assesses the structure of learning in the state space and helps understand how the brain transforms sensory input into motor output. Computational frameworks have provided valuable insights into sensorimotor learning and control. They have been used to study the organization of motor memories based on contextual rules and the role of structural learning in the sensorimotor system. These frameworks have also been employed to investigate the neural dynamics under sensorimotor control and learning tasks, as well as the effect of explicit strategies on sensorimotor learning. The interplay between computational frameworks and neuroscience studies has enhanced our understanding of sensorimotor learning and control. Bayesian decision theory, neural dynamics framework, and state space framework have provided valuable tools for studying the computational mechanisms underlying these processes. They have helped uncover the role of contextual information, structural learning, and neural dynamics in sensorimotor control and learning. Further research should continue exploring the relationship between computational frameworks and neuroscience studies in sensorimotor learning and control. This interdisciplinary approach can lead to a better understanding of how motor skills are learned, retained, and improved through targeted interventions. Additionally, the application of computational frameworks in clinical settings may help develop more effective rehabilitation strategies for individuals with motor impairments.","PeriodicalId":307060,"journal":{"name":"Journal of Autonomous Intelligence","volume":"11 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139158876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Iris presentation attack detection: Research trends, challenges, and future directions","authors":"Noura S. Al-Rajeh, Amal A. Al-Shargabi","doi":"10.32629/jai.v7i2.1012","DOIUrl":"https://doi.org/10.32629/jai.v7i2.1012","url":null,"abstract":"Currently, interest in biometrics has increased, and personal identity verification is ubiquitous. Iris recognition techniques have recently attracted considerable attention from researchers and are considered one of the most popular topics as they are used for verification purposes. Because of the increasing use of iris recognition, many potential risks have emerged as a natural result of the increased deployment of these technologies. One of the most serious risks is the so-called presentation attack (PA). A PA is the presentation of a sample to an iris sensor to trick the biometric system into making an incorrect decision. Iris presentation attacks are used to spoof or disguise a person’s identity. Many studies have focused on iris presentation attack detection techniques, which are a subset biometric recognition. However, some gaps remain unsolved, and new challenges are rapidly emerging. Despite significant advances in the literature, the problems in iris presentation attack detection have not been adequately addressed and remain open questions. This paper provides a comprehensive overview of iris presentation attack detection from various aspects (e.g., detection techniques, attack types, datasets, and performance measurements). It also attempts to explore the main challenges that may affect presentation attack detection models in terms of important aspects. The challenges that remain to be unresolved are summarised to facilitate problem solving. This review concludes with some directions for future research to help researchers focus on important aspects of the field and try to improve what previous researchers have started. Furthermore, it is likely that this review will be used as a reference for scientists/researchers in the existing science of iris presentation attack detection.","PeriodicalId":307060,"journal":{"name":"Journal of Autonomous Intelligence","volume":"19 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139158356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The 5G revolution: Tackling challenges in smart cities and intelligent transportation systems","authors":"Sunil Kumar Vohra, V. Suresh Kumar, Ramkumar Krishnamoorthy, Poornima Mahesh, Bhadrappa Haralayya, Nupur Soni, Shashi Kant Gupta","doi":"10.32629/jai.v7i2.1342","DOIUrl":"https://doi.org/10.32629/jai.v7i2.1342","url":null,"abstract":"The use of cutting-edge technology and data systems to increase the effectiveness, safety, and environmental responsibility of transport networks is known as intelligent transportation systems (ITS). In order to improve many elements of transportation, ITS incorporates a wide range of technologies, including sensors, communication networks, data analytics, and robots. By addressing the shortcomings of the current 4G network, the next mobile technology, 5G, challenges the electronic communication environment as it stands. By allowing a large number of concurrent connections and networks ubiquitous, even in high mobility scenarios or densely inhabited places, such Smart trains and smart cities (SC) are made possible by cutting-edge technology a new approach of becoming fully integrated. According to this strategy; 5G will enable the true Internet of Things (IoT) and its related automobiles on the World Wide Web (WWW). This conversation attempts to thoroughly explain how 5G wireless networks will impact urban smart transport networks, including semi-autonomous or self-driving cars, and automotive communication over the coming years, as well as any technical, economical, and regulatory issues.","PeriodicalId":307060,"journal":{"name":"Journal of Autonomous Intelligence","volume":"5 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138944170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence governance in smart cities: A European regulatory perspective","authors":"Brian Fabregue","doi":"10.32629/jai.v7i2.672","DOIUrl":"https://doi.org/10.32629/jai.v7i2.672","url":null,"abstract":"The integration of AI in our daily lives is rapidly increasing, offering numerous benefits to society. In a Smart City context, said integration is almost implicit: Smart Cities allow for a stream of data upon which AI is not only used but developed and trained. There are however concerns about the unpredictability and uncontrollability of AI, prompting calls for transparency and explainability of its underlying machine-learning algorithms. To ensure useful and understandable explanations of inherent biases, policymakers should focus on the concrete risks and biases of algorithms in relation to specific legal contexts. This article examines the legal implications of AI, including potential regulatory frameworks, the impact on privacy and intellectual property laws, and ethical issues. It also explores governance drivers and policy processes of AI regulation and governance in the European Union. Then, after focusing on the newest Artificial Intelligence Act—viewed both under a fundamental right and a smart city AI integration perspective, it is argued that a three principle-based approach to AI deployment in smart cities is needed to balance inefficiencies derived from the inherent complexity of AI, namely: fairness, privacy and transparency.","PeriodicalId":307060,"journal":{"name":"Journal of Autonomous Intelligence","volume":"58 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138946373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic scoping review of the analysis of COVID-19 disease using chest X-ray images with deep learning models","authors":"Kirti Saini, Reeta Devi","doi":"10.32629/jai.v7i2.928","DOIUrl":"https://doi.org/10.32629/jai.v7i2.928","url":null,"abstract":"The significance of chest X-ray data in screening patients for COVID-19 has been recognised by medical experts. Deep learning (DL) technologies, particularly artificial intelligence (AI) algorithms, have emerged as efficient classifiers for diagnosing disease through the inspection of chest X-rays. Medical professionals may use deep learning skills to effectively allocate resources and prioritise patients, ensuring that people in critical need of medical attention receive it on time. In reviewed papers, chest X-ray images datasets are used in order to investigate if trained convolutional neural networks (CNNs) can be utilized to accurately classify COVID-19 cases. The study is made more fascinating by the availability of many kinds of new DL models designed specifically for this specific purpose. As the findings illustrate the efficacy of fine-tuned pretrained CNNs for COVID-19 identification using chest X-ray data, the usage of AI-based approaches for COVID-19 identification using chest X-ray data should see substantial growth, giving a more quick and cost-effective approach. The combination of CNN technology and the diagnostic capacity of chest X-ray imaging offers a lot of promise in the fight against COVID-19. Ultimately, the goal is to reduce the strain on healthcare resources and improve patient outcomes by providing medical practitioners with dependable technologies, such as those based on the artificial intelligence (AI), that can aid in real-time monitoring, rapid diagnosis, and patient triage. These advancements enable more effective use of healthcare resources, which benefits patients.","PeriodicalId":307060,"journal":{"name":"Journal of Autonomous Intelligence","volume":"22 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138947425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hardhat-wearing detection based on YOLOv5 in Internet-of-Things","authors":"Wanbo Luo, Rajeswari Raju, K. K. Mohd Shariff, Ahmad Ihsan Yassin","doi":"10.32629/jai.v7i2.1255","DOIUrl":"https://doi.org/10.32629/jai.v7i2.1255","url":null,"abstract":"Worker safety is paramount in many industries. An essential component of industrial safety protocols involves the proper use of hardhats. However, due to lax safety awareness, many workers neglect to wear hardhats correctly, leading to frequent on-site accidents in China. Traditional detection methods, such as manual inspection and video surveillance, are inefficient and costly. Real-time monitoring of hardhat use is vital to boost compliance with hardhat usage and decrease accident rates. Recently, the advancement of the Internet of Things (IoT) and edge computing has provided an opportunity to improve these methods. In this study, two detection models based on You Only Look Once (YOLO) v5, hardhat-YOLOv5s and hardhat-YOLOv5n, were designed, validated, and implemented, tailored for hardhat detection. First, a public hardhat dataset was enriched to bolster the detection model’s robustness. Then, hardhat detection models were trained using the YOLOv5s and YOLOv5n, each catering to edge computing terminals with varying performance capacities. Finally, the models were validated using image and video data. The experimental results indicated that both models provided high detection precision and satisfied practical application needs. On the augmented public dataset, the hardhat-YOLOv5s and hardhat-YOLOv5n models have a Mean Average Precision (mAP) of 87.9% and 85.5%, respectively, for all six classes. Compared with the hardhat-YOLOv5s model, Parameters and Giga Floating-point Operations (GFLOPs) of the hardhat-YOLOv5n model decrease by 74.8% and 73.4%, respectively, and Frame per Second (FPS) increases by 30.5% on the validation dataset, which is more suitable for low-cost edge computing terminals with less computational power.","PeriodicalId":307060,"journal":{"name":"Journal of Autonomous Intelligence","volume":"52 38","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138946250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An efficient framework for secure data transmission using blockchain in IoT environment","authors":"Shyama Barna Bhattacharjee, Shivam Gangwar, Manish Kumar, Kirti Saini, Rashmi Saini, Shivani Chauhan, Krishna Pandey, Richard Essah, Nitin Goyal","doi":"10.32629/jai.v7i2.1073","DOIUrl":"https://doi.org/10.32629/jai.v7i2.1073","url":null,"abstract":"The secure and efficient sharing of data has been recognised as a significant concern in Internet of Things (IoT)-enabled smart systems, including smart cities, smart agriculture, and smart health applications. Smart systems utilise a substantial quantity of IoT devices, which in turn generate a significant volume of data. Internet of Things (IoT) devices typically possess constrained storage and processing capacities, making the implementation of security measures on such devices a difficult task. This paper presents a framework for secure data transmission using blockchain (SDTUB) for blockchain-based IoT systems, with a focus on enhancing data security. The use of clustered authorization aims to enhance the interoperability of IoT authorization. The central blockchain is employed for permission purposes concerning cluster management nodes, whereas the regional blockchain suffices for authorization of regular nodes. The proposed mechanism is implemented using MATLAB, and the performance is analysed using performance metrics such as energy consumption and objective value. In the proposed mechanism, the energy consumption is low compared to the AuBWSN technique.","PeriodicalId":307060,"journal":{"name":"Journal of Autonomous Intelligence","volume":"9 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138948320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficiency analysis of path-finding algorithms in a 2D grid environment","authors":"Ch Nirmal Prabhath, M. Kavitha, Kanak Kalita","doi":"10.32629/jai.v7i2.1284","DOIUrl":"https://doi.org/10.32629/jai.v7i2.1284","url":null,"abstract":"This paper offers a focused overview of pathfinding algorithms, particularly emphasizing Greedy Best First Search (G-BFS) and Rapidly-Exploring Random Trees (RRT). Their performance is evaluated within a 2D grid setting tailored for Unmanned Aerial Vehicles (UAVs). Divided into two main sections, the study first expounds on the theoretical underpinnings of these algorithms, followed by empirical validation. A series of systematic experiments, involving varied 2D grid dimensions and traversal patterns, facilitates a comparative analysis between G-BFS and RRT. Importantly, the real-world implementation of these algorithms in UAV navigation underscores their practicality, illuminating their respective execution times and resource utilization. While G-BFS thrives in straightforward scenarios, RRT, especially RRT*, displays superior capability in navigating more intricate and expansive terrains, albeit with marginally extended execution durations attributed to its explorative nature.","PeriodicalId":307060,"journal":{"name":"Journal of Autonomous Intelligence","volume":"42 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138949665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Verification of the effectiveness of digital therapeutics principle textbooks for elementary and secondary school teachers","authors":"Eunsun Choi, Namje Park","doi":"10.32629/jai.v7i2.994","DOIUrl":"https://doi.org/10.32629/jai.v7i2.994","url":null,"abstract":"As the digital transformation of medical systems accelerates, digital therapeutics based on digital technology is attracting attention. Research on digital therapeutics has just begun, and the digital therapeutic market is growing internationally. For students to prepare for an intelligent information society, teachers must be prepared to lead and teach the principles of promising convergence technologies in the future. In this paper, we developed textbooks that can teach the principle of digital therapeutics (DTx) to elementary and secondary school teachers. Textbooks for elementary school teachers were designed with the principle of DTx for attention-deficit/hyperactivity disorder (ADHD), and textbooks for middle school teachers were developed with DTx corresponding to digital dramas as the central theme. The textbooks were developed based on the analyze learners, state objectives, select methods, media, and materials, utilize media and materials, require learner participation, evaluate and revise (ASSURE) model and included teaching and learning plans, worksheets, and reading materials for immediate use in the school field. In addition, textbooks can be used in non-face-to-face classes by using customized online teaching tools. In order to confirm the effectiveness of the developed textbooks, we applied the textbooks to 33 Korean teachers. As a result, teachers’ teaching and learning competency and information teaching efficacy were improved in preparation for the intelligent information society of elementary and secondary school teachers. It was a statistically significant result.","PeriodicalId":307060,"journal":{"name":"Journal of Autonomous Intelligence","volume":"117 40","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138953978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"One shot alpha numeric weight based clustering algorithm with user threshold","authors":"Durga Venkata Prasad Maradana, Srikanth Thota","doi":"10.32629/jai.v7i2.984","DOIUrl":"https://doi.org/10.32629/jai.v7i2.984","url":null,"abstract":"Information Retrieval from Files and data bases like data sources is a major issue now days. After Information Retrieval clustering is also a one of the important things. In the market so many clustering algorithms were available. But choosing of the clustering algorithm depends on the user requirements. This paper addresses the study of agglomerative approach for different constraints or metrics or user preferences like Number of levels in the clustering process, number of clusters that should be generated at each level and range of the attributes at each level for doing the clustering for the given data set. In brief overview we discuss the agglomerative approach for clustering algorithm with their user preferences.","PeriodicalId":307060,"journal":{"name":"Journal of Autonomous Intelligence","volume":" 800","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138960408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}