Article
Computer Science, Information Systems
Jing Sun, Xingjia Gan, Dunwei Gong, Xiaoke Tang, Hongwei Dai, Zhaoman Zhong
Summary: This paper presents a dynamic multi-objective evolutionary algorithm based on online prediction of self-evolving fuzzy system (SEFS) to quickly and accurately respond to nonlinear environmental changes. The proposed algorithm is compared with seven state-of-the-art dynamic multi-objective evolutionary algorithms on 20 benchmark functions, and shows competitiveness.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Sujit Kumar De
Summary: This study investigates the concept of fuzzy approximate reasoning applied to the classical economic order quantity (EOQ) inventory management problem for cost minimization. By assuming all parameters to be randomized fuzzy sets, expectations of fuzzy membership functions are derived using possibility measures and the model is split into multiple sub models. The proposed approach shows superiority over the existing general fuzzy solution under different scenarios of the objective function.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Thomas Heitz, Ning He, Addi Ait-Mlouk, Daniel Bachrathy, Ni Chen, Guolong Zhao, Liang Li
Summary: Accurate prediction of cutting forces is crucial in milling operations. This study explores the effectiveness of the eXtreme Gradient Boosting algorithm in predicting cutting forces during down-milling of Al2024 and proposes a novel framework to optimize precision, efficiency, and user-friendliness. The results show that the eXtreme Gradient Boosting model outperforms the traditional mechanistic force model and can capture the runout effect.
JOURNAL OF INTELLIGENT MANUFACTURING
(2023)
Article
Computer Science, Information Systems
Sara Sweidan, Nuha Zamzami, Sahar F. Sabbeh
Summary: This article presents a new intelligent system based on fuzzy ontology for predicting the severity of liver fibrosis in patients with chronic viral hepatitis C. The system utilizes semantic rule-based techniques and achieves higher performance compared to the now-standard Mamdani fuzzy inference system. It also supports semantic interoperability between clinical decision support systems and electronic health record ecosystems.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2023)
Article
Operations Research & Management Science
Sujit Kumar De, Gour Chandra Mahata
Summary: Fuzzy reasoning is applied to the EOQ inventory management problem, and the membership function for the fuzzy reasoning is defined using L-fuzzy number and possibility theory on fuzzy numbers. A dual fuzzy mathematical problem is constructed considering the holding cost, set up cost, backordering cost, and demand rate as reasoning based fuzzy number. The proposed method shows superiority over crisp and general fuzzy solutions, as indicated by numerical study, sensitivity analysis, and graphical illustrations.
RAIRO-OPERATIONS RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Pengfei Ding, Xianzhen Huang, Chengying Zhao, Huizhen Liu, Xuewei Zhang
Summary: In modern manufacturing, micro-milling technology is crucial for producing high-precision and complex micro-size parts. Understanding the changing rule of time-varying cutting is significant for comprehending the micro-milling mechanism and improving machining efficiency. Additionally, identifying and updating tool wear in advance can enhance the accuracy and sustainability of micromachining. This study proposes a tool wear prediction framework for micro-milling using a temporal convolution network, bi-directional long short-term memory, and a multi-objective arithmetic optimization algorithm. A new integrated model for real-time micro-milling cutting force monitoring is then developed, considering factors such as tool deformation, tool runout, time-varying cutting coefficient, chip separation state, and tool wear estimation results. The accuracy of the proposed tool wear prediction and cutting force model is verified through micro-milling experiments with Al6061 workpiece material. The developed model provides theoretical guidance for statics and dynamics analysis in micro-milling.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Pu Li, Xin Wang, Hui Liang, Suzhi Zhang, Yazhou Zhang, Yuncheng Jiang, Yong Tang
Summary: This paper presents a new semantic representation and reasoning model for multiple associative predicates based on fuzzy theory to address the issue of ineffective representation of fuzzy semantic information in classical knowledge graphs. Experimental results demonstrate that the proposed method can discover more implicit valid knowledge with fuzzy semantics and is consistent with human judgments.
INFORMATION SCIENCES
(2022)
Article
Multidisciplinary Sciences
Pouya Aghelpour, Vahid Varshavian, Mehraneh Khodamorad Pour, Zahra Hamedi
Summary: Evapotranspiration is a crucial factor affecting agricultural productions, and accurate forecasting of it is vital for water managers and irrigation planners. This study hybridizes the adaptive neuro-fuzzy inference system (ANFIS) model with the differential evolution (DE) optimization algorithm to forecast monthly reference evapotranspiration (ET0). The hybrid ANFIS-DE model shows high capability in ET0 forecasting, with an average improvement of 16% compared to ANFIS alone. Among the time series stochastic models, the seasonal autoregressive integrated moving average (SARIMA) model is found to be the most suitable for monthly ET0 forecasting in all climates due to its simplicity and parsimony. The comparison between different climates reveals that the forecasting accuracies vary significantly, with better performance in extra-arid, arid, and semi-arid climates compared to humid and per-humid areas.
SCIENTIFIC REPORTS
(2022)
Article
Chemistry, Multidisciplinary
Ankit Verma, Gaurav Agarwal, Amit Kumar Gupta, Mangal Sain
Summary: The study introduced a novel approach combining generalized approximate reasoning intelligence control with ant lion optimization algorithm to predict disease type and measure severity range. The method successfully improved the accuracy of disease classification and severity analysis, achieving good predictive results.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Theory & Methods
Long-Hao Yang, Fei-Fei Ye, Jun Liu, Ying-Ming Wang, Haibo Hu
Summary: A new environmental investment prediction model, FRBS-ERSC, is proposed in this study to address challenges in environmental investment prediction. The model provides interpretability and scalability through effective indicator and data selection, and shows satisfactory accuracy compared to some existing models.
FUZZY SETS AND SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Debarati B. Chakraborty, JingTao Yao
Summary: This article proposes a new methodology for unsupervised event prediction from videos, using the motion information in the video to detect events. By using rough sets and fuzzy sets, this method can accurately predict the occurrence of events.
PATTERN ANALYSIS AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Xiaoqian Liu, Yingjun Zhang, Jingping Wang, Hua Huang, Hui Yin
Summary: In this study, a multi-source and multivariate ozone prediction model based on fuzzy cognitive maps (FCMs) and evidential reasoning theory, called ERC-FCM, is proposed. The model addresses the challenges of complex evolution trend of ozone, cross-interference phenomena, and low-quality monitoring data. Experimental results demonstrate the superiority of ERC-FCM in terms of prediction accuracy compared to other classical FCM-based methods.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Fangyi Li, Changjing Shang, Ying Li, Jing Yang, Qiang Shen
Summary: This article provides an overview of the development and current status of Fuzzy Rule Interpolation (FRI) technology, as well as the evolving understanding of rule importance among researchers. The paper discusses FRI methods with both non-weighted rules and weighted rules, offering a comprehensive understanding of this field.
ARTIFICIAL INTELLIGENCE REVIEW
(2021)
Article
Green & Sustainable Science & Technology
Sasa Tesic, Djordje Cica, Stevo Borojevic, Branislav Sredanovic, Milan Zeljkovic, Davorin Kramar, Franci Pusavec
Summary: This study investigates the influence of cutting parameters on the energy consumption of ball-end end milling, and utilizes optimization and prediction techniques to improve the energy efficiency. The total cutting power was measured to calculate the specific energy consumption, and the Taguchi method was used for optimization.
INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING-GREEN TECHNOLOGY
(2022)
Article
Computer Science, Information Systems
Yanwei Zhai, Zheng Lv, Jun Zhao, Wei Wang, Henry Leung
Summary: An online Wang-Mendel fuzzy inference model is proposed in this paper to address the modeling of continuous production process with dynamic and nonlinear characteristics, extracting fuzzy rules from raw data without prior knowledge. Through an adaptive self-evolutionary strategy and sparse fuzzy reasoning approach, continuous learning and extrapolation of knowledge of fuzzy regions can be achieved.
INFORMATION SCIENCES
(2021)
Review
Oncology
Wenping Song, Jinhua Chen, Shuolei Li, Ding Li, Yongna Zhang, Hanqiong Zhou, Weijiang Yu, Baoxia He, Wenzhou Zhang, Liang Li
Summary: The study focuses on summarizing the role of ARHGAP9 gene in tumorigenesis and development as a potential therapeutic target for cancer treatment. The research found that the genetic/epigenetic variations and abnormal expression of ARHGAP9 gene are closely associated with various diseases, particularly cancer. ARHGAP9 can inactivate Rho GTPases and regulate cancer cellular events through signaling pathways. The study also assessed the potential of ARHGAP9 as a predictive biomarker and druggable target for cancer treatment through patent review. Overall, the characterization of ARHGAP9 is crucial for understanding its importance in different stages of cancer progression and therapy.
RECENT PATENTS ON ANTI-CANCER DRUG DISCOVERY
(2022)
Article
Thermodynamics
Zulfikre Esa, Juliana Hj Zaini, Murtuza Mehdi, Asif Iqbal, Malik Muhammad Nauman
Summary: The gravitational water vortex power plant (GWVPP) is a micro-scale hydropower system that converts rotational moving fluid into usable energy. It is capable of generating electricity with ultra-low operating heads and low flow rates, making it suitable for portable energy source applications. This study investigated the formation of vortex and optimized the curve radii parameter for the system basin using computational fluid dynamics (CFD) analysis. The experimental results showed that the narrow dome basin with angled-curved blades profile achieved a maximum efficiency of 31.77%.
INTERNATIONAL JOURNAL OF GREEN ENERGY
(2023)
Article
Chemistry, Multidisciplinary
Asif Iqbal, Quentin Cheok
Summary: A novel computational approach for evaluating a researcher's scholarly output is presented, considering the total number of co-authors and the sequence number of the researcher in the authors list. This method provides a more accurate assessment of a researcher's academic impact.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Manufacturing
Muhammad Jamil, Ning He, Xiang Huang, Wei Zhao, Aqib Mashood Khan, Asif Iqbal
Summary: A newly developed hybrid ethanol-ester oil lubricant-coolant has been proposed for machining titanium alloy, showing superior performance in high-speed machining with reduced cutting temperature, cutting force, surface roughness, and tool wear. Additionally, the biodegradable lubricant-coolant provides efficient cooling and lubrication benefits, preventing microparticles adhesion and reducing frictional heat generation.
JOURNAL OF MANUFACTURING PROCESSES
(2022)
Article
Biochemical Research Methods
Yaowen Gu, Si Zheng, Zidu Xu, Qijin Yin, Liang Li, Jiao Li
Summary: This study proposes a curriculum learning-based training strategy, CurrMG, to improve the efficiency of molecular graph learning. Extensive experiments demonstrate that CurrMG can significantly enhance the performance of molecular graph learning models, particularly in resource-constrained scenarios.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Environmental Sciences
Wenping Song, Lingjie Bian, Mengran Xiong, Yuanyuan Duan, Yi Wang, Xia Zhang, Biao Li, Yulong Dai, Jiawei Lu, Meng Li, Zhiguo Liu, Shigang Liu, Li Zhang, Hongjuan Yao, Rongguang Shao, Guangxi Li, Liang Li
Summary: The study aimed to explore the relationship between variations in metabolic genes and urinary changes in mercapturic acids in humans. The results showed that the difference in mercapturic acids between polluted and clean/purified air was significantly associated with certain single nucleotide polymorphisms in genes. Five SNPs in GSTP1 were found to have the most prominent association with changes in SPMA expression, indicating their potential as biomarkers for susceptibility and prognosis of lung cancer.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH
(2023)
Review
Engineering, Manufacturing
Asim Ahmad Riaz, Ghulam Hussain, Asif Iqbal, Volkan Esat, Mohammed Alkahtani, Aqib Mashood Khan, Naveed Ullah, Maohua Xiao, Shaukat Khan
Summary: Due to worsening environmental conditions and resource depletion, sustainability in manufacturing is becoming increasingly important. Incremental sheet forming (ISF) is a promising process for small production runs, and this study provides a comprehensive review of its sustainability aspects. The review concludes that ISF is more sustainable than conventional forming methods for small production runs.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
(2022)
Article
Engineering, Chemical
Asif Iqbal, Guolong Zhao, Quentin Cheok, Ning He, Malik M. Nauman
Summary: Tool life criterion based on work surface roughness can extend tool life and make the machining process more sustainable.
Article
Oncology
Peter A. Fasching, Duan Liu, Steve Scully, James N. Ingle, Paulo C. Lyra, Brigitte Rack, Alexander Hein, Arif B. Ekici, Andre Reis, Andreas Schneeweiss, Hans Tesch, Tanja N. Fehm, Georg Heinrich, Matthias W. Beckmann, Matthias Ruebner, Hanna Huebner, Diether Lambrechts, Ebony Madden, Jess Shen, Jane Romm, Kim Doheny, Gregory D. Jenkins, Erin E. Carlson, Liang Li, Brooke L. Fridley, Julie M. Cunningham, Wolfgang Janni, Alvaro N. A. Monteiro, Daniel J. Schaid, Lothar Haberle, Richard M. Weinshilboum, Liewei Wang
Summary: This study identified two loci in NLRC5 and TNFSF13B genes that are associated with grade 3/4 neutropenic or leukopenic events (NLE) after chemotherapy. It also revealed that the expression of these genes is influenced by genotypes and chemotherapy, and has an association with disease-free survival in patients.
CLINICAL CANCER RESEARCH
(2022)
Article
Environmental Sciences
Guang-xi Li, Yuan-yuan Duan, Yi Wang, Ling-jie Bian, Meng-ran Xiong, Wen-pin Song, Xia Zhang, Biao Li, Yu-long Dai, Jia-wei Lu, Meng Li, Zhi-guo Liu, Shi-gang Liu, Li Zhang, Hong-juan Yao, Rong-guang Shao, Liang Li
Summary: This study aimed to investigate the potential health effects of coexposure to outdoor air pollution and bioaerosols, particularly in the context of the COVID-19 pandemic. By analyzing urinary metabolites, the researchers identified potential biomarkers for predicting or diagnosing diseases related to airborne particle matter (PM) or bioaerosols. The study revealed dynamic changes in the urinary metabolic profiles of young healthy individuals exposed to clean or polluted air environments.
ENVIRONMENTAL POLLUTION
(2022)
Article
Green & Sustainable Science & Technology
Muhammad Jamil, Ning He, Wei Zhao, Huang Xiang, Munish Kumar Gupta, Asif Iqbal, Aqib Mashood Khan
Summary: This study proposes a new MQL-dry ice blasting lubri-cooling technology as an eco-friendly approach in machining to reduce costs and environmental impact. The experimental findings demonstrate that cutting speed and cooling/lubrication have a substantial effect on machinability and sustainability metrics. The hybrid dry ice blasting technique shows significant reductions in energy consumption, carbon emission, and total cost compared to other lubrication/cooling methods.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Chemistry, Physical
Ray Tahir Mushtaq, Asif Iqbal, Yanen Wang, Quentin Cheok, Saqlain Abbas
Summary: This research aims to optimize the surface roughness of Nylon-6 and Acrylonitrile Butadiene Styrene through analyzing the effects of 3D printing parameters. By using Taguchi analysis and other methods, the surface roughness was successfully optimized. The experimental results showed that the optimized values greatly reduced the surface roughness.
Article
Chemistry, Physical
Muhammad Nihal Naseer, Khurram Kamal, Muhammad Abid, Asif Iqbal, Hamdullah Khan, Ch. Muhammad Zubair, Sagar Kumar, Tahir Abdul Hussain Ratlamwala, Malik Muhammad Nauman
Summary: Energy production from clean and green sources is a major challenge. The integration of fuel cells and biogas offers a promising solution to reduce CO2 emissions. This study contributes by developing a self-sustaining biogas-fuel cell system for cold areas.
INTERNATIONAL JOURNAL OF PHOTOENERGY
(2022)
Article
Chemistry, Physical
Ray Tahir Mushtaq, Asif Iqbal, Yanen Wang, Mudassar Rehman, Mohd Iskandar Petra
Summary: Professionals in industries are developing predictive techniques to assess the characteristics and reactions of engineered materials. This investigation focuses on finding optimal settings for a 3D printer made of acrylonitrile butadiene styrene (ABS) by evaluating different responses such as flexural strength, tensile strength, surface roughness, print time, and energy consumption. Through experimental methods and numerical optimization, the study determines the key factors affecting the desired outcomes and provides valuable insights for manufacturers and practitioners.
Article
Materials Science, Characterization & Testing
Ray Tahir Mushtaq, Asif Iqbal, Yanen Wang, Aqib Mashood Khan, Muhammad S. Abu Bakar
Summary: The potential of Fused Filament Fabrication (FFF) technology to produce complex geometrics has a profound impact on the physical world. This study aims to optimize the mechanical properties, surface roughness, and sustainability of FFF products using PETG polymer. By optimizing the parameters, the desired properties were achieved, and laser polishing further improved the surface roughness and mechanical strength.
