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Research & application of IFN in cypher science

Ye Qiusun

Strategic Study of Chinese Academy of Engineering 2008, Volume 10, Issue 5,   Pages 51-57

Abstract:

To overcome 3 shortcomings of the traditional PNCT (pure numerals ciphering technology) of that, properties of the divulging a secret, the allotted time and the dead secrets. This paper gives a novel ciphering technique based on specific properties of intelligent VCN (variable carrying numbers). All allowed cipher numbers are FCN (fixed carrying numbers), in the traditional PNCT, and their changing rules of FCN are both very simple, mechanism and too difficult to be remembered, so that they make the mentioned shortcomings of being sure secrecy in the course of nature. The VCN are extension of the FCN, which are also a new concept of numbers in a broad sense, but their complex,intelligence and flexibility in changing rules are just to overcome the 3 shortcomings of PNCT in FCN.

Keywords: variable carrying numbers (VCN)     cypher science (CS)     fixed carrying numbers (FCN)     artificial intelligence(AI)     AI-Fuzzy VCN (IFN)    

Supervision System of AI-based Software as a Medical Device

Zhang Jiannan,Li Yingying,Zhou Jiahui,Zhu Yelin,Li Lanjuan

Strategic Study of Chinese Academy of Engineering 2022, Volume 24, Issue 1,   Pages 198-204 doi: 10.15302/J-SSCAE-2022.01.021

Abstract: Artificial intelligencebased software as a medical device (AI-Based SaMD) is an important product inthe health field enabled by artificial intelligence (AI).As AI develops further, its unique black box algorithm and independent learning ability have posed majorThis article summarizes the current status of supervision systems and supporting resources of AI-BasedIn addition, we explore the problems and challenges of AI-Based SaMD in China.

Keywords: software as a medical device (SaMD),artificial intelligence (AI),supervision science    

Bayesian Optimization for Field-Scale Geological Carbon Storage

Xueying Lu, Kirk E. Jordan, Mary F. Wheeler, Edward O. Pyzer-Knapp, Matthew Benatan

Engineering 2022, Volume 18, Issue 11,   Pages 96-104 doi: 10.1016/j.eng.2022.06.011

Abstract:

We present a framework that couples a high-fidelity compositional reservoir simulator with Bayesian optimization (BO) for injection well scheduling optimization in geological carbon sequestration. This work represents one of the first at tempts to apply BO and high-fidelity physics models to geological carbon storage. The implicit parallel accurate reservoir simulator (IPARS) is utilized to accurately capture the underlying physical processes during CO2 sequestration. IPARS provides a framework for several flow and mechanics models and thus supports both stand-alone and coupled simulations. In this work, we use the compositional flow module to simulate the geological carbon storage process. The compositional flow model, which includes a hysteretic three-phase relative permeability model, accounts for three major CO2 trapping mechanisms: structural trapping, residual gas trapping, and solubility trapping. Furthermore, IPARS is coupled to the International Business Machines (IBM) Corporation Bayesian Optimization Accelerator (BOA) for parallel optimizations of CO2 injection  strategies during field-scale CO2 sequestration. BO builds a probabilistic surrogate for the objective function using a Bayesian machine learning algorithm—the Gaussian process regression, and then uses an acquisition function that leverages the uncertainty in the surrogate to decide where to sample. The IBM BOA addresses the three weaknesses of standard BO that limits its scalability in that IBM BOA supports parallel (batch) executions, scales better for high-dimensional problems, and is more robust to initializations. We demonstrate these merits by applying the algorithm in the optimization of the CO2 injection schedule in the Cranfield site in Mississippi, USA, using field data. The optimized injection schedule achieves 16% more gas storage volume and 56% less water/surfactant usage compared with the baseline. The performance of BO is compared with that of a genetic algorithm (GA) and a covariance matrix adaptation (CMA)-evolution strategy (ES). The results demonstrate the superior performance of BO, in that it achieves a competitive objective function value with over 60% fewer forward model evaluations. 

Keywords: Compositional flow     Bayesian optimization     Geological carbon storage     CCUS     Machine learning     AI forscience    

Industrial Application of Artificial Intelligence in China: Current Status and Challenges

Xu Wenwei, Xiao Lizhi, Liu He

Strategic Study of Chinese Academy of Engineering doi: 10.15302/J-SSCAE-2022.07.010

Abstract: style="text-align: justify;">Deep learning has enhanced the versatility of artificial intelligence (AIIn the last decade, the AI industry has been spawned and developing rapidly.pertaining to industrial application of AI and propose corresponding suggestions.technologies that focus on full-stack AI, AI basic platform and tool system, and AI root technology,thus to improve the independence of China’s AI core technologies.

Keywords: artificial intelligence (AI)     enterprise scenarios     intelligent solutions     application     full-stack AI     AI root technology    

Ensemble unit and AI techniques for prediction of rock strain

Frontiers of Structural and Civil Engineering   Pages 858-870 doi: 10.1007/s11709-022-0831-3

Abstract: Many researchers employ AI technology in order to solve these difficulties.AI algorithms such as gradient boosting machine (GBM), support vector regression (SVR), random forest

Keywords: prediction     strain     ensemble unit     rank analysis     error matrix    

Intelligent high-speed cutting database system development

XIANG Kejun, LIU Zhanqiang, AI Xing

Frontiers of Mechanical Engineering 2008, Volume 3, Issue 2,   Pages 180-188 doi: 10.1007/s11465-008-0038-x

Abstract: In this paper, the components of a high-speed cutting system are analyzed firstly. The component variables of the high-speed cutting system are classified into four types: uncontrolled variables, process variables, control variables, and output variables. The relationships and interactions of these variables are discussed. Then, by analyzing and comparing intelligent reasoning methods frequently used, the hybrid reasoning is employed to build the high-speed cutting database system. Then, the data structures of high-speed cutting case base and databases are determined. Finally, the component parts and working process of the high-speed cutting database system on the basis of hybrid reasoning are presented.

Keywords: control     hybrid reasoning     process     component     uncontrolled    

Ni-Co bimetallic catalyst for CH

Xiaohong LI, Jun AI, Wenying LI, Dongxiong LI

Frontiers of Chemical Science and Engineering 2010, Volume 4, Issue 4,   Pages 476-480 doi: 10.1007/s11705-010-0512-y

Abstract: A co-precipitation method was employed to prepare Ni/Al O -ZrO , Co/Al O -ZrO and Ni-Co/Al O -ZrO catalysts. Their properties were characterized by N adsorption (BET), thermogravimetric analysis TGA , temperature-programmed reduction (TPR), temperature-programmed desorption (CO -TPD), and temperature-programmed surface reaction (CH -TPSR and CO -TPSR). Ni-Co/Al O -ZrO bimetallic catalyst has good performance in the reduction of active components Ni, Co and CO adsorption. Compared with mono-metallic catalyst, bimetallic catalyst could provide more active sites and CO adsorption sites (C+ CO = 2CO) for the methane-reforming reaction, and a more appropriate force formed between active components and composite support (SMSI) for the catalytic reaction. According to the CH -CO -TPSR, there were 80.9% and 81.5% higher CH and CO conversion over Ni-Co/Al O -ZrO catalyst, and its better resistance to carbon deposition, less than 0.5% of coke after 4 h reaction, was found by TGA. The high activity and excellent anti-coking of the Ni-Co/Al O -ZrO catalyst were closely related to the synergy between Ni and Co active metal, the strong metal-support interaction and the use of composite support.

Keywords: Ni-Co bimetallic catalyst     composite support     CH4 reforming with CO2    

Toward human-in-the-loop AI: Enhancing deep reinforcement learning via real-time human guidance for autonomous

Jingda Wu,Zhiyu Huang,Zhongxu Hu,Chen Lv,

Engineering doi: 10.1016/j.eng.2022.05.017

Abstract: complex scenarios, it is crucial to introduce humans into the training loop of artificial intelligence (AI

Keywords: Human-in-the-loop AI     Deep reinforcement learning     Human guidance     Autonomous driving    

Application of AI techniques in monitoring and operation of power systems

David Wenzhong GAO, Qiang WANG, Fang ZHANG, Xiaojing YANG, Zhigang HUANG, Shiqian MA, Qiao LI, Xiaoyan GONG, Fei-Yue WANG

Frontiers in Energy 2019, Volume 13, Issue 1,   Pages 71-85 doi: 10.1007/s11708-018-0589-4

Abstract: In recent years, the artificial intelligence (AI) technology is becoming more and more popular in manyHowever, the application of AI techniques in power systems is still in its infancy.Therefore, in this paper, the application potentials of AI technologies in power systems will be discussedFor the power system operation, the problems, the demands, and the possible applications of AI techniquesnetwork (NN) for power flow analysis is provided as a simple example to demonstrate the viability of AI

Keywords: power system operation and monitoring     artificial intelligence (AI)     deep learning     power flow analysis    

Ethical Principles and Governance Technology Development of AI in China Review

Wenjun Wu, Tiejun Huang, Ke Gong

Engineering 2020, Volume 6, Issue 3,   Pages 302-309 doi: 10.1016/j.eng.2019.12.015

Abstract: Ethics and governance are vital to the healthy and sustainable development of artificial intelligence (AIWith the long-term goal of keeping AI beneficial to human society, governments, research organizations, and companies in China have published ethical guidelines and principles for AI, and have launched projectsto develop AI governance technologies.It also describes the major research challenges in AI governance research and discusses future research

Keywords: AI ethical principles     AI governance technology     Machine learning     Privacy     Safety     Fairness    

One-step synthesis of

Kuiyi YOU, Fangfang ZHAO, Xueyan LONG, Pingle LIU, Qiuhong AI, Hean LUO

Frontiers of Chemical Science and Engineering 2012, Volume 6, Issue 4,   Pages 389-394 doi: 10.1007/s11705-012-1218-0

Abstract: A simple and efficient approach for the synthesis of -caprolactam via the liquid phase nitrosation of cyclohexane and nitrosyl sulfuric acid in the presence of concentrated sulfuric acid has been developed. A series of novel AlVPO composites were prepared by an impregnation method and the composites were then employed to catalyze the nitrosation reaction of cyclohexane and nitrosyl sulfuric acid. Compared to the reaction using fuming sulfuric acid, the selectivity for the desired product was significantly improved using this one-step catalytic process. This method affords a shortcut to prepare -caprolactam and its analogs from cyclohexane.

Keywords: cyclohexane     ?-caprolactam     AlVPO composite catalysts     one-step synthesis     concentrated sulfuric acid    

Crowd intelligence in AI 2.0 era Review

Wei LI,Wen-jun WU,Huai-min WANG,Xue-qi CHENG,Hua-jun CHEN,Zhi-hua ZHOU,Rong DING

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 1,   Pages 15-43 doi: 10.1631/FITEE.1601859

Abstract: has profoundly changed the information environment for the development of artificial intelligence (AI), bringing a new wave of AI research and promoting it into the new era of AI 2.0.As one of the most prominent characteristics of research in AI 2.0 era, crowd intelligence has attracted

Keywords: Crowd intelligence     Artificial intelligence 2.0     Crowdsourcing     Human computation    

Roles of acid-producing bacteria in anaerobic digestion of waste activated sludge

Sijia Ai, Hongyu Liu, Mengjie Wu, Guangming Zeng, Chunping Yang

Frontiers of Environmental Science & Engineering 2018, Volume 12, Issue 6, doi: 10.1007/s11783-018-1050-y

Abstract:

Three acid-producing strains were isolated and identified.

The isolated bacteria accelerated the anaerobic digestion processes.

Bacillus coagulans improved TCOD removal, VS removal and biogas production.

The optimal inoculum concentration of Bacillus coagulans AFB-1 was 30%.

Keywords: Anaerobic digestion     Waste activated sludge     Acid-producing bacteria     Bacillus coagulans    

Novel quantum-inspired firefly algorithm for optimal power quality monitor placement

Ling Ai WONG,Hussain SHAREEF,Azah MOHAMED,Ahmad Asrul IBRAHIM

Frontiers in Energy 2014, Volume 8, Issue 2,   Pages 254-260 doi: 10.1007/s11708-014-0302-1

Abstract: The application of a quantum-inspired firefly algorithm was introduced to obtain optimal power quality monitor placement in a power system. The conventional binary firefly algorithm was modified by using quantum principles to attain a faster convergence rate that can improve system performance and to avoid premature convergence. In the optimization process, a multi-objective function was used with the system observability constraint, which is determined via the topological monitor reach area concept. The multi-objective function comprises three functions: number of required monitors, monitor overlapping index, and sag severity index. The effectiveness of the proposed method was verified by applying the algorithm to an IEEE 118-bus transmission system and by comparing the algorithm with others of its kind.

Keywords: quantum-inspired binary firefly algorithm     topological monitor reach area     power quality    

Spray-coated SnO

Yaqin Wang, Lin Yang, Chunxiang Dall’Agnese, Gang Chen, Ai-Jun Li, Xiao-Feng Wang

Frontiers of Chemical Science and Engineering 2021, Volume 15, Issue 1,   Pages 180-186 doi: 10.1007/s11705-020-1917-x

Abstract: SnO has been proven to be an effective electron transport layer (ETL) material for perovskite solar cells (PSCs) owing to its excellent electrical and optical properties. Here, we introduce a viable spray coating method for the preparation of SnO films. Then, we employ a SnO film prepared using the spray coating method as an ETL for PSCs. The PSC based on the spray-coated SnO ETL achieves a power conversion efficiency of 17.78%, which is comparable to that of PSCs based on conventional spin-coated SnO films. The large-area SnO films prepared by spray coating exhibit good repeatability for device performance. This study shows that SnO films prepared by spray coating can be applied as ETLs for stable and high-efficiency PSCs. Because the proposed method involves low material consumption, it enables the low-cost and large-scale production of PSCs.

Keywords: spray coating     SnO2 film     ETL     PSCs    

Title Author Date Type Operation

Research & application of IFN in cypher science

Ye Qiusun

Journal Article

Supervision System of AI-based Software as a Medical Device

Zhang Jiannan,Li Yingying,Zhou Jiahui,Zhu Yelin,Li Lanjuan

Journal Article

Bayesian Optimization for Field-Scale Geological Carbon Storage

Xueying Lu, Kirk E. Jordan, Mary F. Wheeler, Edward O. Pyzer-Knapp, Matthew Benatan

Journal Article

Industrial Application of Artificial Intelligence in China: Current Status and Challenges

Xu Wenwei, Xiao Lizhi, Liu He

Journal Article

Ensemble unit and AI techniques for prediction of rock strain

Journal Article

Intelligent high-speed cutting database system development

XIANG Kejun, LIU Zhanqiang, AI Xing

Journal Article

Ni-Co bimetallic catalyst for CH

Xiaohong LI, Jun AI, Wenying LI, Dongxiong LI

Journal Article

Toward human-in-the-loop AI: Enhancing deep reinforcement learning via real-time human guidance for autonomous

Jingda Wu,Zhiyu Huang,Zhongxu Hu,Chen Lv,

Journal Article

Application of AI techniques in monitoring and operation of power systems

David Wenzhong GAO, Qiang WANG, Fang ZHANG, Xiaojing YANG, Zhigang HUANG, Shiqian MA, Qiao LI, Xiaoyan GONG, Fei-Yue WANG

Journal Article

Ethical Principles and Governance Technology Development of AI in China

Wenjun Wu, Tiejun Huang, Ke Gong

Journal Article

One-step synthesis of

Kuiyi YOU, Fangfang ZHAO, Xueyan LONG, Pingle LIU, Qiuhong AI, Hean LUO

Journal Article

Crowd intelligence in AI 2.0 era

Wei LI,Wen-jun WU,Huai-min WANG,Xue-qi CHENG,Hua-jun CHEN,Zhi-hua ZHOU,Rong DING

Journal Article

Roles of acid-producing bacteria in anaerobic digestion of waste activated sludge

Sijia Ai, Hongyu Liu, Mengjie Wu, Guangming Zeng, Chunping Yang

Journal Article

Novel quantum-inspired firefly algorithm for optimal power quality monitor placement

Ling Ai WONG,Hussain SHAREEF,Azah MOHAMED,Ahmad Asrul IBRAHIM

Journal Article

Spray-coated SnO

Yaqin Wang, Lin Yang, Chunxiang Dall’Agnese, Gang Chen, Ai-Jun Li, Xiao-Feng Wang

Journal Article