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Du Zhang

University of Science and Technology of China

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Yingxu Wang

Yunnan University

Witold Kinsner

University of Manitoba

Jun Peng

Central South University

Éric Grégoire

Université d'Artois

Meiliu Lu

California State University, Sacramento

Bensheng Qiu

University of Science and Technology of China

Xiaoxiao Wang

University of Science and Technology of China

George Baciu

Hong Kong Polytechnic University

Yanming Wang

University of Science and Technology of China

Benedictor Alexander Nguchu

University of Science and Technology of China

Cooperative Institutions

University of Science and Technology of China

Fudan University

Chinese Academy of Sciences

Macau University of Science and Technology

California State University, Sacramento

Tsinghua University

Hefei National Center for Physical Sciences at Nanoscale

Peking University

Huashan Hospital

Shenzhen University

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James Joshi Elisa Bertino Bhavani Thuraisingham Ling Liu Lotfi Zadeh

10.1109/iri.2014.7051720

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All‐Optical Phosphorene Phase Modulator with Enhanced Stability Under Ambient Conditions

Laser & Photonics Review (2018)

Yunzheng Wang Feng Zhang Xian Tang Xing Chen Yunxiang Chen

Abstract All‐optical modulators, wherein signal light can be manipulated by another controlling light, have recently emerged as a promising perspective in all‐optical communications, interconnects and signal processing. Herein, by taking advantage of the strong light‐matter interaction and thickness‐dependent direct energy bandgap in few‐layer phosphorene, an all‐fiber all‐optical modulator based on a Mach–Zehnder interferometer comprising few‐layer fluorinated phosphorene‐deposited microfiber has been devised and further demonstrated with phase modulation ability. The phase shift of the signal light, capable of being converted into intensity modulation, could be readily controlled by the photothermal effect in phosphorene. A maximal phase shift of 8π is obtained at a control light of 290 mW, corresponding to a conversion efficiency of 0.029 π mW −1 . The optical information carried by the control light is successfully copied towards the signal light with a modulation depth of 17 dB and a rise time constant of 2.5 ms. Stability under ambient conditions is enhanced significantly thanks to atomistic fluorination in phosphorene that can overcome drawbacks of easy oxidation of intrinsic phosphorene and maintain performance for a long term. This prototypical phosphorene‐based all‐optical phase modulator will have a great potential to be applied in all‐optical information processing and be integrated into optical fiber systems.

Phosphorene

Modulation (music)

SIGNAL (programming language)

10.1002/lpor.201800016

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Perspectives on the Field of Cognitive Informatics and its Future Development

IGI Global eBooks (2012)

Yingxu Wang Bernard Widrow Bo Zhang Witold Kinsner Kenji Sugawara

The contemporary wonder of sciences and engineering has recently refocused on the beginning point of: how the brain processes internal and external information autonomously and cognitively rather than imperatively like conventional computers. Cognitive Informatics (CI) is a transdisciplinary enquiry of computer science, information sciences, cognitive science, and intelligence science that investigates the internal information processing mechanisms and processes of the brain and natural intelligence, as well as their engineering applications in cognitive computing. This paper reports a set of eight position statements presented in the plenary panel of IEEE ICCI’10 on Cognitive Informatics and Its Future Development contributed from invited panelists who are part of the world’s renowned researchers and scholars in the field of cognitive informatics and cognitive computing.

Cognitive Computing

Wonder

10.4018/978-1-4666-2476-4.ch002

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Abstract Intelligence

IGI Global eBooks (2020)

Yingxu Wang Lotfi A. Zadeh Bernard Widrow Newton Howard Françoise Beaufays

Basic studies in denotational mathematics and mathematical engineering have led to the theory of abstract intelligence (aI), which is a set of mathematical models of natural and computational intelligence in cognitive informatics (CI) and cognitive computing (CC). Abstract intelligence triggers the recent breakthroughs in cognitive systems such as cognitive computers, cognitive robots, cognitive neural networks, and cognitive learning. This paper reports a set of position statements presented in the plenary panel (Part II) of IEEE ICCI*CC'16 on Cognitive Informatics and Cognitive Computing at Stanford University. The summary is contributed by invited panelists who are part of the world's renowned scholars in the transdisciplinary field of CI and CC.

Cognitive Computing

Cognitive robotics

10.4018/978-1-7998-2460-2.ch005

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On Admissible Consensuses

HAL (Le Centre pour la Communication Scientifique Directe) (2018)

Éric Grégoire Yacine Izza Du Zhang

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GAPS: A Genetic Programming System

International Journal of Artificial Intelligence Tools (2003)

Du Zhang Michael D. Kramer

One of the major approaches in the field of evolutionary computation is genetic programming. Genetic programming tackles the issue of how to automatically create a computer program for a given problem from some initial problem statement. The goal is accomplished by genetically breeding a population of computer programs in terms of genetic operations. In this paper, we describe a genetic programming system called GAPS. GAPS has the following features: (1) It implements the standard generational algorithm for genetic programming with some refinement on controlling introns growth during evolution process and improved termination criteria. (2) It includes an extensible language tailored to the needs of genetic programming. And (3) It is a complete, standalone system that allows for genetic programming tasks to be carried out without requiring other tools such as compilers. Results with GAPS have been satisfactory.

Genetic representation

10.1142/s0218213003001198

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Cognitive function and cerebellar morphometric changes relate to abnormal intra-cerebellar and cerebro-cerebellum functional connectivity in old adults

Experimental Gerontology (2020)

Jean de Dieu Uwisengeyimana Benedictor Alexander Nguchu Yanming Wang Du Zhang Yanpeng Liu

Cerebro

Cerebellar diseases

10.1016/j.exger.2020.111060

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Citations (19)

Cognitive Informatics

IGI Global eBooks (2011)

Du Zhang Witold Kinsner Jeffrey J. P. Tsai Yingxu Wang Phillip C.‐Y. Sheu

The 2005 IEEE International Conference on Cognitive Informatics (ICCI'05) was held during August 8th to 10th 2005 on the campus of University of California, Irvine. This was the fourth conference of ICCI [Kinsner et al. 05]. The previous conferences were held at Calgary, Canada (ICCI'02) [Wang et al. 02], London, UK (ICCI'03) [Patel et al. 03], and Victoria, Canada (ICCI'04) [Chan et al. 04], respectively. ICCI'05 was organized by General Co-Chairs of Jeffrey Tsai (University of Illinois) and Yingxu Wang (University of Calgary), Program Co-Chairs of Du Zhang (California State University) and Witold Kinsner (University of Manitoba), and Organization Co- Chairs of Philip Sheu (University of California), Taehyung Wang (California State University, Northridge), and Shangping Ren (Illinois Institute of Technology). Request access from your librarian to read this chapter's full text.

10.4018/9781605661704.ch022

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Taming Inconsistency in Value-based Software Development.

Software Engineering and Knowledge Engineering (2009)

Value (mathematics)

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Perpetual Learning through Overcoming Inconsistencies

This paper provides a panoramic view on perpetual learning through overcoming inconsistencies. The approach elevates learning stimuli to the first class status and considers inconsistencies as a special type of learning stimuli. As telltales, inconsistencies indicate that an agent is operating at its knowledge boundaries, necessitating subsequent learning episodes. Learning amounts to finding ways to circumvent inconsistencies. We describe a framework called inconsistency induced learning, or i ² Learning, and discuss several specific learning algorithms for it. The perpetual nature is embodied in the fact that i ² Learning accommodates the open-ended sequence of learning episodes.

Sequence (biology)

10.1109/ictai.2013.132

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