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International Conference on Application of Information and Communication Technologies (AICT)

作者： Kashif Nisar Emilia Rosa Jimson Mohd. Hanafi bin Ahmad Hijazi Ag. Asri Ag. Ibrahim Yong Jin Park Ian Welch School of Engineering and Computer Science Victoria University of Wellington New Zealand Faculty of Computing and Informatics Malaysia Sabah Malaysia

Available bandwidth in network is limited, it is very critical to manage the network bandwidth efficiently. In this research, bandwidth management model based on Software-Defined Networking (SDN) architecture is examined. Through the recommended model, real-time traffic over network was given importance to approach the restricted bandwidth over non real-time traffic. SDN promises the simplification of network management compared to the traditional network. SDN architecture breaks the vertically integrated current network design and it introduces centralized network control through the SDN controller, which is considered as the greatest contribution of SDN in networking area. SDN architecture is adopted in this paper since it promotes centralized control features which enable grid programmability and supports improve network resources administration. Simulation was conducted using the EstiNet network simulator. Two groups of experiments with different situations have been conducted. Each experiment consisted of five simulations with different number of sender and receiver nodes. The first experiment simulated the traffics in a traditional networking; and the second experiment simulated the traffics in a proposed network model. In addition, bulk of the existing bandwidth was reserved to real-time traffic and the remaining quantity was reserved for non-real-time traffic. The real-time throughput results of the two different experiments have been compared to estimate the performance of the proposed SDN research model. The experiment results presented that the recommended model has successfully given urgency to real-time network traffic to approach the limited network bandwidth. As the number of nodes increases, the conventional real-time throughput of setup one and setup two decreases linearly. When nodes reach 10, the real-time ordinary throughput of setup one and setup two are 63SKBps and 473KBps respectively.

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RF Rectifier with High Efficiency over a Wide Input Power Range Using a Voltage Controlled Switch in a ‘Handover’ Fashion

RF Rectifier with High Efficiency over a Wide Input Power Ra...

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Asia-Pacific Conference on Applied Electromagnetics, APACE

作者： Abdulkadir Muhammad Lawan Hieng Tiong Su Yi Lung Then Jiafeng Zhou Faculty of Engineering Computing and Science Swinburne University of Technology Sarawak Kuching Malaysia Department of Electrical Engineering and Electronics University of Liverpool Liverpool UK

ISBN: (数字)9781728121628

ISBN: (纸本)9781728121635

Wireless energy transfer gains from the option of receiving power from multiple sources with different power levels. This paper presents a rectifier that maintains good efficiency over a wide input power range at 2.45 GHz frequency using a MOSFET as the voltage controlled switch (VCS). The VCS performs a `handover' function between a low threshold voltage diode and a high breakdown voltage diode in a seamless manner without interrupting power supply to the load. This topology has only so far produced good results at lower frequencies. An L-matching network is used to achieve impedance matching over the input power range at 2.45 GHz with the help of a blocking capacitor acting as a high pass filter. Simulated results show that the rectifier can maintain its RF to DC conversion efficiency above 50% from 3 to 23.8 dBm. A peak efficiency of 73% at 16.6 dBm is also recorded.

关键词： Rectifiers MOSFET Switches Radio frequency Impedance Wireless communication Resistance

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A generic framework for editing and synthesizing multimodal data with relative emotion strength

A generic framework for editing and synthesizing multimodal ...

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作者： Chan, Jacky C. P. Shum, Hubert P. H. Wang, He Yi, Li Wei, Wei Ho, Edmond S. L. Caritas Institute of Higher Education Tseung Kwan O Hong Kong Faculty of Engineering and Environment Northumbria University Newcastle upon Tyne United Kingdom School of Computing University of Leeds Leeds United Kingdom Yilifilm Shenzhen China School of Computer Science and Engineering Xi'an University of Technology Xi'an China

Emotion is considered to be a core element in performances. In computer animation, both body motions and facial expressions are two popular mediums for a character to express the emotion. However, there has been limited research in studying how to effectively synthesize these two types of character movements using different levels of emotion strength with intuitive control, which is difficult to be modeled effectively. In this work, we explore a common model that can be used to represent the emotion for the applications of body motions and facial expressions synthesis. Unlike previous work that encode emotions into discrete motion style descriptors, we propose a continuous control indicator called emotion strength by controlling which a data-driven approach is presented to synthesize motions with fine control over emotions. Rather than interpolating motion features to synthesize new motion as in existing work, our method explicitly learns a model mapping low-level motion features to the emotion strength. Because the motion synthesis model is learned in the training stage, the computation time required for synthesizing motions at run time is very low. We further demonstrate the generality of our proposed framework by editing 2D face images using relative emotion strength. As a result, our method can be applied to interactive applications such as computer games, image editing tools, and virtual reality applications, as well as offline applications such as animation and movie production. © 2019 John Wiley & Sons, Ltd.

关键词： Computer games

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Prediction of mechanical properties of non-equiatomic high-entropy alloy by atomistic simulation and machine learning

arXiv

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arXiv 2020年

作者： Zhang, Liang Qian, Kun Schuller, Björn W. Lu, Cheng Shibuta, Yasushi Huang, Xiaoxu College of Materials Science and Engineering Chongqing University Chongqing400044 China Department of Materials Engineering University of Tokyo Tokyo113-8656 Japan Educational Physiology Laboratory University of Tokyo Tokyo113-0033 Japan Department of Computing Imperial College London LondonSW72AZ United Kingdom Department of Computer Science University of Augsburg Augsburg86159 Germany Faculty of Engineering and Information Science University of Wollongong WollongongNSW2522 Australia

High-entropy alloys (HEAs) with multiple constituent elements have been extensively studied in the past 20 years due to their promising engineering application. Previous experimental and computational studies of HEAs focused mainly on equiatomic or near equiatomic HEAs. However, there is probably far more treasure in those non-equiatomic HEAs with carefully designed composition. In this study, molecular dynamics (MD) simulation combined with machine learning (ML) methods were used to predict the mechanical properties of non-equiatomic CuFeNiCrCo HEAs. A database was established based on a tensile test of 900 HEA single-crystal samples by MD simulation. We investigated and compared eight ML models for the learning tasks, ranging from shallow models to deep models. It was found that the kernel-based extreme learning machine (KELM) model outperformed others for the prediction of yield stress and Young’s modulus. The accuracy of the KELM model was further verified by the large-sized polycrystal HEA samples. Copyright © 2020, The Authors. All rights reserved.

关键词： High-entropy alloys

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The de Haas-van Alphen Effect in a Silicon Nanosandwich at the Room Temperature. Numerical Simulation of the Oscillations with Integer Filling Factors

The de Haas-van Alphen Effect in a Silicon Nanosandwich at t...

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2019 IEEE International Conference on Electrical engineering and Photonics, EExPolytech 2019

作者： Romanov, Vladimir V. Kozhevnikov, Vadim A. Tracey, Chantal T. Ermakov, Boris S. Peter the Great St.Petersburg Polytechnic University Department of Experimental Physics Saint Petersburg Russia Faculty of Engineering and Computing Kingston Jamaica Peter the Great St.Petersburg Polytechnic University Joint Institute of Science and Technology Saint Petersburg Russia

ISBN: (纸本)9781728144399

We present a study of the high-temperature de Haas-van Alphen effect in a silicon nanostructure with integer filling factors up to ν = 11, inclusively. It is shown that the observed oscillations can be described by the model of the Gaussian broadening of the Landau levels of the twodimensional density of states and an energy-independent basis. The estimation of the magnitude of the carriers effective mass appears to be 10-4 free electron mass. © 2019 IEEE.

关键词： Silicon

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A New 4-D Chaotic System with Self-Excited Two-Wing Attractor, its Dynamical Analysis and Circuit Realization 1

A New 4-D Chaotic System with Self-Excited Two-Wing Attracto...

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1st International Conference on Computer, science, engineering and Technology, ICComSET 2018

作者： Sambas, A. Vaidyanathan, S. Zhang, S. Mujiarto Mamat, M. Subiyanto Sanjaya, W. S. Mada Department of Mechanical Engineering Universitas Muhammadiyah Tasikmalaya Indonesia Research and Development Centre Vel Tech University Avadi Chennai India School of Physics and Opotoelectric Engineering Xiangtan University Hunan China Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Kuala Terengganu Malaysia Department of Marine Science Faculty of Fishery and Marine Science Universitas Padjadjaran Indonesia Department of Physics Universitas Islam Negeri Sunan Gunung Djati Bandung Indonesia

A new four-dimensional chaotic system with only two quadratic nonlinearities is proposed in this paper. It is interesting that the new chaotic system exhibits a two-wing strange attractor. The dynamical properties of the new chaotic system are described in terms of phase portraits, equilibrium points, Lyapunov exponents, Kaplan-Yorke dimension, dissipativity, etc. The new chaotic system has two saddle-foci, unstable equilibrium points. Thus, the new chaotic system exhibits self-excited attractor. Also, a detailed analysis of the new chaotic system dynamics has been carried out with bifurcation diagram and Lyapunov exponents. As an engineering application, an electronic circuit realization of the new chaotic system is designed via MultiSIM to confirm the feasibility of the theoretical 4-D chaotic model. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Chaotic systems

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Corrigendum to “A decision modeling approach for smart e-tourism data management applications based on spherical fuzzy rough environment” [Applied Soft computing 143(2023) 110297]

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Applied Soft computing 2023年 149卷

作者： R.T. Mohammed A.H. Alamoodi O.S. Albahri A.A. Zaidan H.A. AlSattar Uwe Aickelin A.S. Albahri B.B. Zaidan Amelia Ritahani Ismail R.Q. Malik Department of Computing Science Faculty of Science Komar University of Science and Technology (KUST) Sulaymaniyah Iraq Department of Computing and META Technology (FKMT) Universiti Pendidikan Sultan Idris Tanjung Malim 35900 Malaysia Department of Computer Science and Information Technology La Trobe University Melbourne VIC Australia Computer Techniques Engineering Department Mazaya University College Thi-Qar Nassiriya Iraq SP Jain School of Global Management Sydney Australia Department of Business Administration College of Administrative Science The University of Mashreq 10021 Baghdad Iraq School of Computing and Information Systems University of Melbourne 700 Swanston Street Victoria 3010 Australia Iraqi Commission for Computers and Informatics (ICCI) Baghdad Iraq Department of Computer Technology Engineering College of Information Technology Imam Ja'afar Al-Sadiq University Baghdad Iraq Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Douliou Yunlin 64002 Taiwan Kulliyyah of Information and Communication Technology (KICT) International Islamic University Malaysia Kuala Lumpur Malaysia Medical Instrumentation Techniques Engineering Department Al-Mustaqbal University College Babylon Iraq

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PitVis-2023 Challenge: Workflow Recognition in videos of Endoscopic Pituitary Surgery

arXiv

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arXiv 2024年

作者： Das, Adrito Khan, Danyal Z. Psychogyios, Dimitrios Zhang, Yitong Hanrahan, John G. Vasconcelos, Francisco Pang, You Chen, Zhen Wu, Jinlin Zou, Xiaoyang Zheng, Guoyan Qayyum, Abdul Mazher, Moona Razzak, Imran Li, Tianbin Ye, Jin He, Junjun Plotka, Szymon Kaleta, Joanna Yamlahi, Amine Jund, Antoine Godau, Patrick Kondo, Satoshi Kasai, Satoshi Hirasawa, Kousuke Rivoir, Dominik Pérez, Alejandra Rodriguez, Santiago Arbeláez, Pablo Stoyanov, Danail Marcus, Hani J. Bano, Sophia Wellcome EPSRC Centre for Interventional and Surgical Sciences University College London London United Kingdom Department of Neurosurgery National Hospital for Neurology and Neurosurgery London United Kingdom HKISI CAS China Institute of Medical Robotics School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China National Heart and Lung Institute Faculty of Medicine Imperial College London United Kingdom Centre for Medical Image Computing University College London London United Kingdom University of New South Wales Sydney Australia Shanghai AI Lab Shanghai China Informatics Institute University of Amsterdam Amsterdam Netherlands Department of Biomedical Engineering and Physics Amsterdam University Medical Center University of Amsterdam Amsterdam Netherlands Sano Center for Computational Medicine Krakow Poland Heidelberg Division of Intelligent Medical Systems Germany NCT Heidelberg a partnership between DKFZ University Hospital Heidelberg Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Muroran Institute of Technology Hokkaido Japan Niigata University of Health and Welfare Niigata Japan Konica Minolta Inc. Osaka Japan National Center for Tumor Diseases Dresden Germany Centre for Tactile Internet TUD Dresden Germany Universidad de los Andes Bogota Colombia DKFZ UKDD TUD Germany

The field of computer vision applied to videos of minimally invasive surgery is ever-growing. Workflow recognition pertains to the automated recognition of various aspects of a surgery: including which surgical steps are performed;and which surgical instruments are used. This information can later be used to assist clinicians when learning the surgery;during live surgery;and when writing operation notes. The Pituitary Vision (PitVis) 2023 Challenge tasks the community to step and instrument recognition in videos of endoscopic pituitary surgery. This is a unique task when compared to other minimally invasive surgeries due to the smaller working space, which limits and distorts vision;and higher frequency of instrument and step switching, which requires more precise model predictions. Participants were provided with 25-videos, with results presented at the MICCAI-2023 conference as part of the Endoscopic Vision 2023 Challenge in Vancouver, Canada, on 08-Oct-2023. There were 18-submissions from 9-teams across 6-countries, using a variety of deep learning models. A commonality between the top performing models was incorporating spatio-temporal and multi-task methods, with greater than 50% and 10% macro-F1-score improvement over purely spacial single-task models in step and instrument recognition respectively. The PitVis-2023 Challenge therefore demonstrates state-of-the-art computer vision models in minimally invasive surgery are transferable to a new dataset, with surgery specific techniques used to enhance performance, progressing the field further. Benchmark results are provided in the paper, and the dataset is publicly available at: https://***/10.5522/04/26531686. Copyright © 2024, The Authors. All rights reserved.

关键词： Endoscopy

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Combining Deep Neural Network and Fourier Series for Tourist Arrivals Forecasting

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IOP Conference Series: Materials science and engineering 2020年第1期864卷

作者： Ani Shabri Ruhaidah Samsudin Yusliza Yusoff Department of Mathematical Sciences Faculty of Science Faculty of Engineering Universiti Teknologi Malaysia School of Computing Faculty of Engineering Universiti Teknologi Malaysia

Accurate tourist arrivals forecasting is essential for governments and the private sector to formulate policies and allocate funds more effectively. In this paper, the modeling of tourist arrivals time series data was introduced in a hybrid modeling that combines the deep neural network (DNN) with the Fourier series method. The proposed model approach applies the DNN to get the forecasted value and then employs the Fourier series to fit the residual error produced by the DNN. To verify the accurate prediction of the proposed model, different single models such as ARIMA, ANN and DNN, and modified ARIMA and ANN models using Fourier series are investigated. Historical data on monthly tourist arrivals to Langkawi Island with high trend and strong seasonality is used to compare the efficiency of the proposed model. A series of studies demonstrates that the performance of the single model can be further improved by taking into account the residual modification by Fourier series. The result shows that the proposed model is capable of forecasting tourist arrival series with higher reliability than other models used.

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Generation of a Compendium of Transcription Factor Cascades and Identification of Potential Therapeutic Targets using Graph Machine Learning

arXiv

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arXiv 2023年

作者： Sivarajkumar, Sonish Tandale, Pratyush Bhardwaj, Ankit Johnson, Kipp W. Titus, Anoop Glicksberg, Benjamin S. Khader, Shameer Yadav, Kamlesh K. Subramanian, Lakshminarayanan Molecular Robotics Kerala India School of Computing and Information University of Pittsburgh Pennsylvania PA United States Health Informatics & Data Science Georgetown University WashingtonDC United States Department of Computer Science Courant Institute of Mathematical Sciences New York University New YorkNY United States Institute for Next Generation Healthcare Mount Sinai Health System New YorkNY United States Department of Preventive Cardiology DeBakey Heart & Vascular Center Houston Methodist HoustonTX United States Hasso Plattner Institute for Digital Health Icahn School of Medicine at Mount Sinai New YorkNY United States Faculty of Medicine Imperial College London London United Kingdom School of Engineering Medicine Texas A&M University HoustonTX United States Department of Translational Medical Sciences Center for Genomic and Precision Medicine Texas A&M University HoustonTX United States

Transcription factors (TFs) play a vital role in the regulation of gene expression thereby making them critical to many cellular processes. In this study, we used graph machine learning methods to create a compendium of TF cascades using data extracted from the STRING database. A TF cascade is a sequence of TFs that regulate each other, forming a directed path in the TF network. We constructed a knowledge graph of 81,488 unique TF cascades, with the longest cascade consisting of 62 TFs. Our results highlight the complex and intricate nature of TF interactions, where multiple TFs work together to regulate gene expression. We also identified 10 TFs with the highest regulatory influence based on centrality measurements, providing valuable information for researchers interested in studying specific TFs. Furthermore, our pathway enrichment analysis revealed significant enrichment of various pathways and functional categories, including those involved in cancer and other diseases, as well as those involved in development, differentiation, and cell signaling. The enriched pathways identified in this study may have potential as targets for therapeutic intervention in diseases associated with dysregulation of transcription factors. We have released the dataset, knowledge graph, and graphML methods for the TF cascades, and created a website to display the results, which can be accessed by researchers interested in using this dataset. Our study provides a valuable resource for understanding the complex network of interactions between TFs and their regulatory roles in cellular processes. Copyright © 2023, The Authors. All rights reserved.

关键词： Transcription factors

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