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    Study Results from Abu Dhabi School of Management in the Area of Artificial Inte lligence Published (Managerial insights for AI/ML implementation: a playbook for successful organizational integration)

    87-87页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on artificial intelligenc e is the subject of a new report. According to news reporting originating from t he Abu Dhabi School of Management by NewsRx correspondents, research stated, "In the contemporary business environment, the assimilation of artificial intellige nce (AI) and machine learning (ML) is pivotal for fostering innovation and ensur ing long-term growth." Our news reporters obtained a quote from the research from Abu Dhabi School of M anagement: "This paper examines the strategic aspects of AI/ML adoption, emphasi zing that its success rests not just on technology but also on strategic alignme nt, collaboration, and robust leadership. Highlighting the indispensable role of senior leaders, the paper offers a managerial framework for AI/ML integration, ensuring its alignment with organizational goals. Using real-world examples, the paper presents how AI/ML can be strategically embedded to enhance customer inte ractions, streamline operations, and unveil new revenue streams."
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    Studies in the Area of Machine Learning Reported from Ningbo University of Techn ology (Application of machine learning in ultrasonic diagnostics for prismatic l ithium-ion battery degradation evaluation)

    88-88页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on artificial intelligen ce have been presented. According to news reporting from Zhejiang, People's Repu blic of China, by NewsRx journalists, research stated, "Lithium-ion batteries ar e essential for electrochemical energy storage, yet they undergo progressive agi ng during operational lifespan." The news editors obtained a quote from the research from Ningbo University of Te chnology: "Consequently, precise estimation of their state of health (SOH) is cr ucial for effective and safe operation of energy storage systems. This paper inv estigates the viability of ultrasound-based methods for assessing the SOH of pri smatic lithium-ion batteries. In the experimental framework, a designated prisma tic lithium-ion battery was subjected to numerous charging and discharging cycle s using a battery cycling system. Subsequently, ultrasonic detection experiments were conducted to record the waveforms of the transmitted and received signals. These signals were then processed through wavelet transforms to extract signal amplitude and time-of-flight data. To analyse these data, we applied four algori thms: linear regression, support vector machines, Gaussian process regression, a nd neural networks."
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    Study Data from North Carolina State University (NC State) Provide New Insights into Androids (Exploring the Impact of Humanrobot Interaction On Workers' Menta l Stress In Collaborative Assembly Tasks)

    89-89页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Robotics-An droids have been published. According to news reporting originating in Raleigh, North Carolina, by NewsRx journalists, research stated, "Advances in robotics ha ve contributed to the prevalence of human-robot collaboration (HRC). However, wo rking and interacting with collaborative robots in close proximity can be psycho logically stressful." Financial support for this research came from National Science Foundation (NSF). The news reporters obtained a quote from the research from North Carolina State University (NC State), "Therefore, understanding the impacts of human-robot inte raction (HRI) on mental stress is crucial for enhancing workplace wellbeing. To this end, this study investigated how the HRI factors-presence, complexity, an d modality-affect the psychological stress of workers. We employed both the NA SA-Task Load Index for subjective assessment and physiological metrics including galvanic skin responses, electromyography, and heart rate for objective evaluat ion. An experimental setup was implemented in which human operators worked toget her with a collaborative robot on Lego assembly tasks, using different interacti on paradigms including pressing buttons, showing hand gestures, and giving verba l commands. The results revealed that the introduction of interactions during HR C helped reduce mental stress and that complex interactions resulted in higher m ental stress than simple interactions. Meanwhile, using hand gestures led to sig nificantly higher mental stress than pressing buttons and verbal commands."
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    New Machine Learning Findings from Southern University of Science and Technology (SUSTech) Described (A Machine Learning Based-method To Generate Random Circle- packed Porous Media With the Desired Porosity and Permeability)

    90-90页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Machine Learning are pre sented in a new report. According to news reporting originating in Shenzhen, Peo ple's Republic of China, by NewsRx journalists, research stated, "The generation of digital porous media facilitates the fabrication of artificial porous media and the analysis of their properties. The past random digital porous medium gene ration methods are unable to generate a porous medium with a specified permeabil ity." Financial supporters for this research include Department of Science and Technol ogy of Guangdong Province, China, National Natural Science Foundation of China ( NSFC), Shenzhen Peacock Plan, China, Center for Computational Science and Engine ering of Southern University of Science and Technology, China.
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    University of Burgos Researcher Discusses Research in Machine Learning (Monitori ng Educational Intervention Programs for Children and Young People with Disabili ties through a Web Application)

    91-92页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on artificial intelligence is now available. According to news reporting from Burgos, Spain, by NewsRx jou rnalists, research stated, "Early care professionals have to use instruments for assessing functional skills in children susceptible to early intervention that apply records and produce developmental profiles and personalized intervention p roposals." Funders for this research include European Commission. Our news correspondents obtained a quote from the research from University of Bu rgos: "The aims of the study were (1) to analyze the development of functional s kills in users with an age range of 48-252 months attending school in a therapeu tic intervention center for people with motor impairments; and (2) to analyze th e development of functional skills in users with different impairments and ages ranging from 7 to 162 months participating in an early outpatient care program. Study 1 applied a sample of 50 users aged between 48 and 252 months all with mot or disabilities and Study 2 included a sample of 71 users aged between 7 and 162 months with different disabilities. Factorial and descriptive-correlational des igns were applied in both studies. The Student's t-test for dependent samples, s upervised machine learning techniques (linear regression analysis and logarithmi c regression analysis), unsupervised machine learning techniques (k-means), ANOV A, and cross-tabulations were used as contrast tests. In Study 1, no significant changes were found in the development of users' functional skills, except for a decrease in maladaptive behaviors. Likewise, the chronological age variable did not seem to be a determining factor in the results."
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    Studies Conducted at Leiden University on Artificial Intelligence Recently Repor ted (Licensing High-risk Artificial Intelligence: Toward Ex Ante Justification f or a Disruptive Technology)

    92-92页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Artificial Intelligenc e is the subject of a report. According to news reporting originating from Leide n, Netherlands, by NewsRx correspondents, research stated, "The regulation of ar tificial intelligence (AI) has heavily relied on ex post, reactive tools. This a pproach has proven inadequate, as numerous foreseeable problems arising out of c ommercial development and applications of AI have harmed vulnerable persons and communities, with few (and sometimes no) opportunities for recourse." Our news editors obtained a quote from the research from Leiden University, "Wor se problems are highly likely in the future. By requiring quality control measur es before AI is deployed, an ex ante approach would often mitigate and sometimes entirely prevent injuries that AI causes or contributes to. Licensing is an imp ortant tool of ex ante regulation, and should be applied in many high-risk domai ns of AI. Indeed, policymakers and even some leading AI developers and vendors a re calling for licensure in the area. To substantiate licensing proposals, this article specifies optimal terms of licensure for AI necessary to justify its use . Given both documented and potential harms arising out of high-risk AI systems, licensing agencies should require firms to demonstrate that their AI meets clea r requirements for security, non-discrimination, accuracy, appropriateness, and correctability before being deployed. Under this ex ante model of regulation, AI developers would bear the burden of proof to demonstrate that their technology is not discriminatory, not manipulative, not unfair, not inaccurate, and not ill egitimate in its lawful bases and purposes."
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    Findings in the Area of Machine Learning Reported from National Institute of Tec hnology Delhi (Enhancing the Performance of Photonic Sensor Using Machine-learni ng Approach)

    93-93页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Ma chine Learning. According to news reporting from Delhi, India, by NewsRx journal ists, research stated, "This article reports on the implementation of adequate m achine-learning (ML) models on different datasets vis-a-vis fiber-optic plasmoni c sensor devices. The variation of the sensor & rsquo;s figure of merit (FOM) with light wavelength (1) and metal layer thickness (d(m)) is consid ered as a starting point and accordingly, the appropriate ML model is chosen." Financial support for this research came from Science Engineering Research Board (SERB), India. The news correspondents obtained a quote from the research from the National Ins titute of Technology Delhi, "The FOM datasets were found to be consistent with t he Gaussian process regressor (GPR) model. The application of GPR with finer res olution (0.001 nm) of 1 on the datasets led to enhanced magnitudes of the sensor & rsquo;s FOM. The dataset (459 points) having nine different val ues of d(m) led to a predicted FOM of 6526.23 at lambda = 1099.343 nm. Furthermo re, the dataset (714 points) having 13 different values of d(m) led to a predict ed FOM value of 6356.98 at lambda =1099.345 nm. These are promising results as f ar as the application of the sensor in biosensing is concerned. Furthermore, the chosen model is found to be highly consistent with the data in terms of trend m atching, and the values of other evaluation parameters [e.g., R-2 and mean absolute error (MAE)] are found to be in consid erably desirable ranges. This study clearly reveals that the selection of an app ropriate ML model and its implementation on various datasets can lead to more ef ficient finalization of the sensor design with enhanced sensing performance."
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    Bilecik Seyh Edebali University Reports Findings in Artificial Intelligence (Exp lainable artificial intelligence in the design of selective carbonic anhydrase I -II inhibitors via molecular fingerprinting)

    94-94页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Artificial Intelligenc e is the subject of a report. According to news reporting originating from Bilec ik, Turkey, by NewsRx correspondents, research stated, "Inhibiting the enzymes c arbonic anhydrase I (CA I) and carbonic anhydrase II (CA II) presents a potentia l avenue for addressing nervous system ailments such as glaucoma and Alzheimer's disease. Our study explored harnessing explainable artificial intelligence (XAI ) to unveil the molecular traits inherent in CA I and CA II inhibitors." Our news editors obtained a quote from the research from Bilecik Seyh Edebali Un iversity, "The Pub- Chem molecular fingerprints of these inhibitors, sourced from the ChEMBL database, were subjected to detailed XAI analysis. The study encompas sed training 10 regression models using IC values, and their efficacy was gauged using metrics including R , RMSE, and time taken. The Decision Tree Regressor a lgorithm emerged as the optimal performer (R:0.93, RMSE: 0.43, time-taken: 0.07) . Furthermore, the PFI method unveiled key molecular features for CA I inhibitor s, notably PubChemFP432 (C( O)N) and Pub- ChemFP6978 (C( O)O). The SHAP analysis h ighlighted the significance of attributes like PubChemFP539 (C( O)NCC), PubChemF P601 (C( O)OCC), and PubChemFP432 (C( O)N) in CA I inhibitiotable n. Likewise, f eatures for CA II inhibitors encompassed PubChemFP528(C( O)OCCN), PubChemFP791 ( C( O)OCCC), PubChemFP696 (C( O)OCCCC), PubChemFP335 (C( O)NCCN), PubChemFP580 (C ( O)NCCCN), and PubChemFP180 (C( O)NCCC), identified through SHAP analysis. The sulfonamide group (S), aromatic ring (A), and hydrogen bonding group (H) exert a substantial impact on CA I and CA II enzyme activities and IC values through th e XAI approach."
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    Researchers from Universitas Padjadjaran Report on Findings in Algorithms (Lands cape dynamics and its related factors in the Citarum River Basin: a comparison o f three algorithms with multivariate analysis)

    95-95页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Research findings on algorithms are discussed in a new report. According to news reporting out of the Universitas Padjadjaran by NewsRx editors, research stated, "AbstractLandscape change is intricately linked to natural resource utilization. Landscape dynamics are closely tied to land us e and land cover (LULC), serving as a representation of ecosystems and human act ivities." Our news editors obtained a quote from the research from Universitas Padjadjaran : "In the Citarum River Basin, Indonesia, a comprehensive approach is necessary to comprehend landscape dynamics as a manifestation of human interaction with th e environment. This research aims to analyze landscape dynamics and its factors that can significantly drive changes. We focused on the Cirasea Watershed, which serves as an upper region of the Citarum River Basin. Data was acquired from La ndsat-series imageries from 1993 to 2023, and LULC analyses were conducted using classification and regression trees (CART), random forest (RF), and support vec tor machine (SVM). We analyzed seven independent variables, including slope (X1) , elevation (X2), main river (X3), population (X4), central business district (X 5), distance from the past settlements (X6), and accessibility (X7) using multiv ariate analysis. This research found that RF stands out as the optimal choice fo r LULC analysis over CART and SVM because it had the highest overall accuracy an d overall kappa (0.91-0.92, 0.88-0.89). Notably, there was a substantial 273.43% increase in built-up areas, coupled with significant declines in plantations and horticultures. LULC changes was more pronounced in the lower areas near Bandung City."
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    New Machine Learning Study Findings Have Been Reported by Investigators at Natio nal University of Defense Technology (A Survey of Machine Learning for Network-o n-chips)

    96-96页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in Machine Learning. According to news reporting originating from Hunan, People's Republic of China, by NewsRx correspondents, research stated, "The popularity of Machine Learning (ML) has extended to numerous disciplines, including the domain of Net work-onchips (NoCs), leading to a consequential impact. Recent works have explo red ML models' appli-cability for NoCs design, optimization, and performance eva luation." Funders for this research include National Key Research and Development Program of China, National Natural Science Foundation of China (NSFC), Excellent Youth F oundation of Hunan Province. Our news editors obtained a quote from the research from the National University of Defense Technology, "ML-based NoCs design has demonstrated superior performa nce to heuristic methods employed by human experts in NoCs design. This has faci litated a tight collaboration between ML and NoCs research, offering novel persp ectives and optimization strategies to advance NoCs design. In this paper, we pr esent a comprehensive survey into implementing ML techniques for NoCs. Initially , we provide an overview of ML-based research for NoCs in two aspects: (i) the a doption of ML for performance modeling and prediction and (ii) ML-based for NoCs design, including individual components (such as routing algorithm, arbitration , traffic control, etc.). Subsequently, we summarize the challenges and difficul ties in designing NoCs for applying ML techniques and discuss the preliminary so lutions to these issues. Finally, we prospect the perspective on future research directions for expanding the application of ML techniques to diverse scenarios of NoCs, exploring the adoption of ML techniques for NoCs design automation."
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