scholarly journals Can an attribution assessment be made for Yellow Rain? Systematic reanalysis in a chemical-and-biological-weapons use investigation

2007 ◽  
Vol 26 (1) ◽  
pp. 24-42 ◽  
Author(s):  
Rebecca Katz ◽  
Burton Singer
Keyword(s):  
Artificial Intelligence ◽  
Southeast Asia ◽  
Information Extraction ◽  
Large Body ◽  
Biological Weapons ◽  
Future Research ◽  
Research Directions ◽  
Chemical And Biological Weapons ◽  
Future Research Directions ◽  
Made In

In intelligence investigations, such as those into reports of chemical- or biological-weapons (CBW) use, evidence may be difficult to assemble and, once assembled, to weigh. We propose a methodology for such investigations and then apply it to a large body of recently declassified evidence to determine the extent to which an attribution can now be made in the Yellow Rain case. Our analysis strongly supports the hypothesis that CBW were used in Southeast Asia and Afghanistan in the late 1970s and early 1980s, although a definitive judgment cannot be made. The proposed methodology, while resource-intensive, allows evidence to be assembled and analyzed in a transparent manner so that assumptions and rationale for decisions can be challenged by external critics. We conclude with a discussion of future research directions, emphasizing the use of evolving information-extraction (IE) technologies, a sub-field of artificial intelligence (AI).

scholarly journals Rational design of photocatalysts for ammonia production from water and nitrogen gas

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Seokwoo Choe ◽  
Sung Min Kim ◽  
Yeji Lee ◽  
Jin Seok ◽  
Jiyong Jung ◽  
...  
Keyword(s):  
Energy Source ◽  
Rational Design ◽  
Future Research ◽  
Ammonia Production ◽  
Significant Progress ◽  
Nitrogen Gas ◽  
Research Directions ◽  
Effective Strategies ◽  
Future Research Directions ◽  
Made In

AbstractPhotocatalytic N2 reduction has emerged as one of the most attractive routes to produce NH3 as a useful commodity for chemicals used in industries and as a carbon-free energy source. Recently, significant progress has been made in understanding, exploring, and designing efficient photocatalyst. In this review, we outline the important mechanistic and experimental procedures for photocatalytic NH3 production. In addition, we review effective strategies on development of photocatalysts. Finally, our analyses on the characteristics and modifications of photocatalysts have been summarized, based on which we discuss the possible future research directions, particularly on preparing more efficient catalysts. Overall, this review provides insights on improving photocatalytic NH3 production and designing solar-driven chemical conversions.

Artificial Intelligence Review

2019 ◽  
pp. 23-39
Author(s):  
Amal Kilani ◽  
Ahmed Ben Hamida ◽  
Habib Hamam
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Fuzzy Logic ◽  
Intelligent System ◽  
Route Planning ◽  
Turing Test ◽  
Future Research ◽  
Interaction Data ◽  
Research Directions ◽  
Future Research Directions

In this chapter, the authors present a profound literature review of artificial intelligence (AI). After defining it, they briefly cover its history and enumerate its principal fields of application. They name, for example, information system, commerce, image processing, human-computer interaction, data compression, robotics, route planning, etc. Moreover, the test that defines an artificially intelligent system, called the Turing test, is also defined and detailed. Afterwards, the authors describe some AI tools such as fuzzy logic, genetic algorithms, and swarm intelligence. Special attention will be given to neural networks and fuzzy logic. The authors also present the future research directions and ethics.

Artificial Intelligence

2019 ◽  
pp. 13-22
Author(s):  
Steven Walczak
Keyword(s):  
Artificial Intelligence ◽  
Problem Solving ◽  
Future Research ◽  
Human Intelligence ◽  
Research Directions ◽  
Intelligent Machines ◽  
History Of ◽  
Future Research Directions ◽  
New Research

Artificial intelligence is the science of creating intelligent machines. Human intelligence is comprised of numerous pieces of knowledge as well as processes for utilizing this knowledge to solve problems. Artificial intelligence seeks to emulate and surpass human intelligence in problem solving. Current research tends to be focused within narrow, well-defined domains, but new research is looking to expand this to create global intelligence. This chapter seeks to define the various fields that comprise artificial intelligence and look at the history of AI and suggest future research directions.

scholarly journals Artificial Intelligence Techniques for Cognitive Sensing in Future IoT: State-of-the-Art, Potentials, and Challenges

2020 ◽  
Vol 9 (2) ◽  
pp. 21 ◽  
Author(s):  
Martins O. Osifeko ◽  
Gerhard P. Hancke ◽  
Adnan M. Abu-Mahfouz
Keyword(s):  
Artificial Intelligence ◽  
Data Collection ◽  
Energy Efficient ◽  
State Of The Art ◽  
Future Internet ◽  
Future Research ◽  
Research Directions ◽  
Efficient Data ◽  
Future Research Directions ◽  
Efficient Data Collection

Smart, secure and energy-efficient data collection (DC) processes are key to the realization of the full potentials of future Internet of Things (FIoT)-based systems. Currently, challenges in this domain have motivated research efforts towards providing cognitive solutions for IoT usage. One such solution, termed cognitive sensing (CS) describes the use of smart sensors to intelligently perceive inputs from the environment. Further, CS has been proposed for use in FIoT in order to facilitate smart, secure and energy-efficient data collection processes. In this article, we provide a survey of different Artificial Intelligence (AI)-based techniques used over the last decade to provide cognitive sensing solutions for different FIoT applications. We present some state-of-the-art approaches, potentials, and challenges of AI techniques for the identified solutions. This survey contributes to a better understanding of AI techniques deployed for cognitive sensing in FIoT as well as future research directions in this regard.

scholarly journals Geographic Question Answering: Challenges, Uniqueness, Classification, and Future Directions

2021 ◽  
Vol 2 ◽  
pp. 1-21
Author(s):  
Gengchen Mai ◽  
Krzysztof Janowicz ◽  
Rui Zhu ◽  
Ling Cai ◽  
Ni Lao
Keyword(s):  
Artificial Intelligence ◽  
Natural Language ◽  
Question Answering ◽  
Future Research ◽  
Open Domain ◽  
Future Directions ◽  
Research Directions ◽  
Classification Framework ◽  
Substantial Progress ◽  
Future Research Directions

Abstract. As an important part of Artificial Intelligence (AI), Question Answering (QA) aims at generating answers to questions phrased in natural language. While there has been substantial progress in open-domain question answering, QA systems are still struggling to answer questions which involve geographic entities or concepts and that require spatial operations. In this paper, we discuss the problem of geographic question answering (GeoQA). We first investigate the reasons why geographic questions are difficult to answer by analyzing challenges of geographic questions. We discuss the uniqueness of geographic questions compared to general QA. Then we review existing work on GeoQA and classify them by the types of questions they can address. Based on this survey, we provide a generic classification framework for geographic questions. Finally, we conclude our work by pointing out unique future research directions for GeoQA.

scholarly journals Artificial Intelligence in the Battle against Coronavirus (COVID-19): A Survey and Future Research Directions

2020 ◽  
Author(s):  
Thanh Thi Nguyen
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Medical Image ◽  
Current Status ◽  
Future Research ◽  
Research Directions ◽  
Daily Lives ◽  
Related Data ◽  
Future Research Directions ◽  
The Internet Of Things

Artificial intelligence (AI) has been applied widely in our daily lives in a variety of ways with numerous successful stories. AI has also contributed to dealing with the coronavirus disease (COVID-19) pandemic, which has been happening around the globe. This paper presents a survey of AI methods being used in various applications in the fight against the COVID-19 outbreak and outlines the crucial roles of AI research in this unprecedented battle. We touch on a number of areas where AI plays as an essential component, from medical image processing, data analytics, text mining and natural language processing, the Internet of Things, to computational biology and medicine. A summary of COVID-19 related data sources that are available for research purposes is also presented. Research directions on exploring the potentials of AI and enhancing its capabilities and power in the battle are thoroughly discussed. We highlight 13 groups of problems related to the COVID-19 pandemic and point out promising AI methods and tools that can be used to solve those problems. It is envisaged that this study will provide AI researchers and the wider community an overview of the current status of AI applications and motivate researchers in harnessing AI potentials in the fight against COVID-19.

scholarly journals COMPUTER VISION FOR COVID-19 CONTROL: A SURVEY

2020 ◽  
Author(s):  
Anwaar Ulhaq ◽  
Asim Khan ◽  
Douglas Pinto Sampaio Gomes ◽  
Manoranjan Paul
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Human Population ◽  
Preliminary Review ◽  
Future Research ◽  
Research Directions ◽  
Survey Paper ◽  
Recent Success ◽  
Future Research Directions ◽  
Research Resources

The COVID-19 pandemic has triggered an urgent need to contribute to the fight against an immense threat to the human population. Computer Vision, as a subfield of Artificial Intelligence, has enjoyed recent success in solvingvarious complex problems in health care and has the potential to contribute to the fight of controlling COVID-19. In response to this call, computer vision researchers are putting their knowledge base at work to devise effective ways to counter COVID-19 challenge and serve the global community. New contributions are being shared with everypassing day. It motivated us to review the recent work, collect information about available research resources and an indication of future research directions. We want to make it available to computer vision researchers to save precious time. This survey paper is intended to provide a preliminary review of the available literature on the computer vision efforts against COVID-19 pandemic.

scholarly journals Big data and artificial intelligence in the maritime industry: a bibliometric review and future research directions

2020 ◽  
Vol 47 (5) ◽  
pp. 577-597 ◽  
Author(s):  
Ziaul Haque Munim ◽  
Mariia Dushenko ◽  
Veronica Jaramillo Jimenez ◽  
Mohammad Hassan Shakil ◽  
Marius Imset
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Future Research ◽  
Maritime Industry ◽  
Research Directions ◽  
Bibliometric Review ◽  
Future Research Directions
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