Town protection simulation

2020 ◽  
Author(s):  
Agostino G. Bruzzone ◽  
Kirill Sinelshchikov ◽  
Marina Massei ◽  
Massimo Pedemonte
Keyword(s):  
Artificial Intelligence ◽  
Modeling And Simulation ◽  
Innovative Solutions ◽  
Potential Use

This paper proposes an overview on the potential use of AI (Artificial Intelligence) and M&S (Modeling and Simulation) to develop innovative solutions in a new emerging sector defined Legal Analytics. The analysis of previous and existing achievements respect to actual potential advances with special attention to new integrated solutions for Arbitration.

Will Artificial Intelligences will be our judges and arbiters in the future and what role it will be taken by simulators

2020 ◽  
Author(s):  
Agostino G. Bruzzone ◽  
Paolo Gaggero
Keyword(s):  
Artificial Intelligence ◽  
Modeling And Simulation ◽  
Innovative Solutions ◽  
The Future ◽  
Potential Use

This paper proposes an overview on the potential use of AI (Artificial Intelligence) and M&S (Modeling and Simulation) to develop innovative solutions in a new emerging sector defined Legal Analytics. The analysis of previous and existing achievements respect to actual potential advances with special attention to new integrated solutions for Arbitration.

Potential Use of Artificial Intelligence for Regulatory Intelligence: Biopharmaceutical Industry’s Views

2019 ◽  
Vol 53 (6) ◽  
pp. 759-766
Author(s):  
Mark Mayer ◽  
Angelica Canedo ◽  
Tam Dinh ◽  
Madelyn Low ◽  
Ariel Ortiz ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Potential Use

Cost-effectiveness of AI in medicine from a clinical, technical, and economic perspective: A scoping review and a framework of analysis (Preprint)

2021 ◽  
Author(s):  
Jesus Gomez Rossi ◽  
Ben Feldberg ◽  
Joachim Krois ◽  
Falk Schwendicke
Keyword(s):  
Artificial Intelligence ◽  
Cost Effectiveness ◽  
Scientific Literature ◽  
Economic Aspects ◽  
Inclusion Criteria ◽  
Economic Perspective ◽  
Health Policy Analysis ◽  
The Cost ◽  
The Relationship ◽  
Potential Use

BACKGROUND Research and Development (R&D) of Artificial Intelligence (AI) in medicine involve clinical, technical and economic aspects. Better understanding the relationship between these dimensions seems necessary to coordinate efforts of R&D among stakeholders. OBJECTIVE To assess systematically existing literature on the cost-effectiveness of Artificial Intelligence (AI) from a clinical, technical and economic perspective. METHODS A systematic literature review was conducted to study the cost-effectiveness of AI solutions and summarised within a scoping framework of health policy analysis developed to study clinical, technical and economic dimensions. RESULTS Of the 4820 eligible studies, 13 met the inclusion criteria. Internal medicine and emergency medicine were the most studied clinical disciplines. Technical R&D aspects have not been uniformly disclosed in the studies we analysed. Monetisation aspects such as payment models assumed have not been reported in the majority of cases. CONCLUSIONS Existing scientific literature on the cost-effectiveness of AI currently does not allow to draw conclusive recommendations. Further research and improved reporting on technical and economic aspects seem necessary to assess potential use-cases of this technology, as well as to secure reproducibility of results. CLINICALTRIAL Not applicable

Transformation of the Personnel Management System in the Conditions of Digitalization of HR Processes

2021 ◽  
Vol 39 (6) ◽  
Author(s):  
Sergii Kholod ◽  
Valentyna Pavlova ◽  
Anhelina Spitsyna ◽  
Yuliia Maistrenko ◽  
Oksana Anufrieva ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Personnel Management ◽  
Digital Technology ◽  
Management System ◽  
Digital Data ◽  
Ability To Work ◽  
Hr Management ◽  
Innovative Solutions ◽  
Personnel Management System ◽  
The Impact

Human capital is the driving force behind the digital economy. The use of digital technology has a significant impact on the entire life cycle of personnel in an organization, including hiring, onboarding, and firing. The authors examined the essence of the personnel management system, various models for building a personnel management system in an organization, and studied applying a particular model for a specific organization. The authors studied and visually presented the features of objects, subjects and goals of the personnel management system. The authors also examined the impact of digitalization on the personnel management system, what requirements are imposed on personnel's professional competencies, and new and already used trends in HR automation and recruiting that will help to work better and more efficiently. Generalization of theoretical and empirical experience, cognitive technologies based on the use of artificial intelligence and digital data in HR management allowed the authors to highlight innovative solutions and propose an algorithm for transforming the personnel management system in the context of digitalization of HR processes. Besides, the authors proposed criteria and a scale for assessing the effectiveness of the transformation of the personnel management system in the context of the digitalization of HR processes. Thanks to this, as well as the use of such elements in the framework of personnel management as cloud technology, the ability to work remotely, big data, social media and artificial intelligence, companies, can increase their lead over competitors.

Compliance Problems and Digitizing Case Management in England and Wales

2020 ◽  
pp. 153-178
Author(s):  
John Sorabji
Keyword(s):  
Artificial Intelligence ◽  
Case Management ◽  
Civil Procedure ◽  
Civil Justice ◽  
Reform Programme ◽  
Effective Operation ◽  
Compliance Problem ◽  
Civil Justice System ◽  
Civil Courts ◽  
Potential Use

Compliance with case management orders has been a hidden problem undermining the effective operation of the Civil Procedure Rules. The focus of academic critique has, however, been on the adverse consequences to their effective operation of non-compliance with such orders. This chapter considers this unexamined problem of case management: the compliance problem. It first examines the nature of the compliance problem, placing it within the context of the wider and substantially explored problem of non-compliance; the latter having formed a major limb of Zuckerman’s critique of English civil procedure. It then explores how current and potential future reforms to the English civil justice system arising from HMCTS reform programme, the Civil Courts Structure review, digitization and the potential use of artificial intelligence (AI) could overcome this unexplored problem.

scholarly journals Foreword by Guest Editor LTC James H. Schreiner, PhD, PMP, CPEM

2019 ◽  
Vol 7 (1) ◽  
pp. 1
Author(s):  
James Schreiner
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Text Mining ◽  
Decision Analysis ◽  
Modeling And Simulation ◽  
Systems Engineering ◽  
West Point ◽  
United States Military Academy ◽  
United States Military ◽  
Military Academy

This special issue of the Industrial and Systems Engineering Review highlights top papers from the 2019 annual General Donald R. Keith memorial capstone conference held at the United States Military Academy in West Point, NY. Following careful review of 48 academic paper submissions, eight were selected for publication in this journal. Each paper incorporated features of systems or industrial engineering and presented detailed and reflective analysis in the topic. Three general bodies of knowledge in the papers include: systems engineering and decision analysis, modeling and simulation, and artificial intelligence Systems Engineering and Decision Analysis topics included three unique contributions. The work of Flanick et al. examined adaptability in Hyper-Enabled Operator systems and recommended how each technology might address capability gaps for special operations forces. Wilby et al. employed a scalable predictive statistical model for decision support to significant work package prioritization for U.S. Army Corps of Engineers nationally significant inland waterway infrastructure. Contributions by Shi et al. employed value focused thinking and a robust cost model to enable decision quality for PM Cargo CH-47 technologies. Modeling and Simulation works also included three unique contributions. Recognized as ‘best paper’ at the 2019 conference, work by Cooley et al. developed a senior leader engagement model using sparse K-means clustering techniques to greatly improve the planning and execution for AFRICOM leadership. Lovell et al. employed robust military simulation models to evaluate and propose solutions Soldier Search and Target Acquisition protocols. Work by Drake et al. employed vehicle Routing Problem simulation software to enhance United Health Services material handling challenges across NY State thus enabling quality optimization choices. Finally, two unique contributions in artificial intelligence examined key text mining technologies. Shi et al. employed text mining and Latent Dirichlet Allocation modeling to derive insights through trends and clustering narratives on U.S. Army Officer Evaluation Reports and describe success. Similarly, text mining techniques by Senft et al. helped to examine and show similarities in success narratives across genders thus providing valuable insights for promotion boards. Congratulation to the 2019 undergraduate scholars and all authors who provided valuable contributions through thoughtful and steadfast intellectual efforts to their fields of study! LTC James H. Schreiner, PhD, PMP, CPEM Director, Operations Research Center Department of Systems Engineering United States Military Academy Mahan Hall, Bldg 752, Room 305 West Point, NY 10996, USA [email protected]

scholarly journals Approaches Based on Artificial Intelligence and the Internet of Intelligent Things to Prevent the Spread of COVID-19: Scoping Review (Preprint)

2020 ◽  
Author(s):  
Aya Sedky Adly ◽  
Afnan Sedky Adly ◽  
Mahmoud Sedky Adly
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Resource Allocation ◽  
Modeling And Simulation ◽  
Large Scale ◽  
Information Gathering ◽  
The Internet ◽  
Experimental Therapies ◽  
Computer Scientists ◽  
And Control

BACKGROUND Artificial intelligence (AI) and the Internet of Intelligent Things (IIoT) are promising technologies to prevent the concerningly rapid spread of coronavirus disease (COVID-19) and to maximize safety during the pandemic. With the exponential increase in the number of COVID-19 patients, it is highly possible that physicians and health care workers will not be able to treat all cases. Thus, computer scientists can contribute to the fight against COVID-19 by introducing more intelligent solutions to achieve rapid control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes the disease. OBJECTIVE The objectives of this review were to analyze the current literature, discuss the applicability of reported ideas for using AI to prevent and control COVID-19, and build a comprehensive view of how current systems may be useful in particular areas. This may be of great help to many health care administrators, computer scientists, and policy makers worldwide. METHODS We conducted an electronic search of articles in the MEDLINE, Google Scholar, Embase, and Web of Knowledge databases to formulate a comprehensive review that summarizes different categories of the most recently reported AI-based approaches to prevent and control the spread of COVID-19. RESULTS Our search identified the 10 most recent AI approaches that were suggested to provide the best solutions for maximizing safety and preventing the spread of COVID-19. These approaches included detection of suspected cases, large-scale screening, monitoring, interactions with experimental therapies, pneumonia screening, use of the IIoT for data and information gathering and integration, resource allocation, predictions, modeling and simulation, and robotics for medical quarantine. CONCLUSIONS We found few or almost no studies regarding the use of AI to examine COVID-19 interactions with experimental therapies, the use of AI for resource allocation to COVID-19 patients, or the use of AI and the IIoT for COVID-19 data and information gathering/integration. Moreover, the adoption of other approaches, including use of AI for COVID-19 prediction, use of AI for COVID-19 modeling and simulation, and use of AI robotics for medical quarantine, should be further emphasized by researchers because these important approaches lack sufficient numbers of studies. Therefore, we recommend that computer scientists focus on these approaches, which are still not being adequately addressed.

scholarly journals TEKNOLOGI ARTIFICIAL INTELLIGENCE DAN POTENSI PEMANFAATNYA DALAM KONSELING ONLINE DI MASA DEPAN

2019 ◽  
Vol 5 (2) ◽  
pp. 27
Author(s):  
Rudi Haryadi ◽  
Jamaluddin Matarif ◽  
Kabul Budiono
Keyword(s):  
Artificial Intelligence ◽  
Video Conferencing ◽  
Counseling Services ◽  
Online Counseling ◽  
Face To Face ◽  
The Future ◽  
The Times ◽  
Potential Use

Counseling activities that we usually carry out are usually face-to-face processes, as the times develop, counseling activities turn into online counseling where counseling uses technology intermediaries including chat, email, video conferencing, audio, and so on. But in the future with highly developed technology that is rapidly advancing online counseling based on Artificial Intelligence (AI) will be born with a new breakthrough that is more effective and efficient in future online counseling services, for that in this article the author will discuss online counseling, Artificial Intelligence (AI), the potential use of Artificial Intelligence (AI) in online counseling in the future, and differences in artificial intelligence and natural intelligence.

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