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Optimization of enhanced weathering networks with alternative transportation modes

Carbon Resources Conversion 2022年第2期5卷 167-176页

作者： Raymond R.Tan Beatriz A.Belmonte Michael Francis D.Benjamin Viknesh Andiappan Kathleen B.Aviso Department of Chemical Engineering De La Salle University2401 Taft Avenue0922 ManilaPhilippines Research Center for the Natural and Applied Sciences/Department of Chemical Engineering University of Santo TomasEspana Blvd.1015 ManilaPhilippines School of Engineering and Physical Sciences Heriot-Watt University Malaysia62200PutrajayaWilayah Persekutuan PutrajayaMalaysia Faculty of Engineering Computing and ScienceSwinburne University of TechnologyJalan Simpang Tiga93350KuchingSarawakMalaysia

Enhanced weathering of alkaline rocks and minerals is a negative emissions technology (NET) that is potentiallyscalable to deliver gigaton-level carbon dioxide removal (CDR) for climate change mitigation. This techniquerelies on the acceleration of naturally occurring weathering reactions with water and carbon dioxide by reducingthese substances into a fine powder with high specific surface area. The ex situ enhanced weathering processchain consists of the acquisition of suitable natural or synthetic materials, grinding to a fine particle size,transportation, and application on suitable sites. Future enhanced weathering systems can be envisioned assupply chain-like networks which have to be optimized to deliver maximum CDR given physical *** is a notable research gap in the literature on decision support for such systems. To address this gap, amixed integer linear programming (MILP) model is developed in this work to optimize enhanced weatheringnetworks for CDR. The model also incorporates the availability of multiple transportation options and constraintson network topology. Two test cases are used to demonstrate the model capability to determine optimal andnear-optimal networks. The top ten solutions in these two scenarios yield total CDR levels of 3.4316–3.4363 Mtand 15.27017–15.27960 Mt.

关键词： Process integration Optimization Mathematical programming Carbon drawdown Carbon management network Decarbonization

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Dengue Dashboard for Forecasting the Future Trend of Dengue Cases in Pahang

Dengue Dashboard for Forecasting the Future Trend of Dengue ...

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Software Engineering & Computer Systems and International Conference on Computational science and Information Management (ICSECS-ICOCSIM), International Conference on

作者： Muhammad Khairul Syafiq Mustafa Junaida Sulaiman Faculty of Computing College of Computing and Applied Sciences Universiti Malaysia Pahang Pekan Pahang Malaysia Faculty of Computing College of Computing and Applied Sciences Centre For Data Science & Artificial Intelligence Soft Computing & Intelligent Systems (SPINT) Universiti Malaysia Pahang Pekan Pahang Malaysia

ISBN: (数字)9781665414074

ISBN: (纸本)9781665414081

The study is concerned about the rising number of dengue cases in Pahang. As a preventive solution, an analytical dashboard is proposed to forecast the trend of dengue cases in Pahang for the next two years using Auto Regressive Integrated Moving Average (ARIMA) model. Due to its efficiency to solve linear problems, ARIMA model is a popular model used by the researchers and economists to forecast a time-series data. The dashboard contains various information of dengue cases for instances the total number of dengue cases in Pahang, total number of dengue cases by district, a map that shows the green zone and the red zone which indicates the risk of the dengue infection in that area and a graph that displays the forecasted trend of dengue cases in Pahang from 2021 to 2023 using the best- fitted ARIMA model. The dashboard and the forecasted data trend of dengue is generated to assist JKN Pahang to plan a preventive measure regarding the rising number of dengue cases in thefuture.

关键词： Temperature Rain Scientific computing Meteorological factors Weather forecasting Predictive models Market research

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Dynamic Analysis and Circuit Design of a New 3D Highly Chaotic System and its Application to Pseudo Random Number Generator (PRNG) and Image Encryption

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SN Computer science 2024年第4期5卷 420页

作者： Sambas, Aceng Benkouider, Khaled Kaçar, Sezgin Ceylan, Nurdoğan Vaidyanathan, Sundarapandian Sulaiman, Ibrahim Mohammed Mohamed, Mohamad Afendee Ayob, Ahmad Faisal Mohamad Muni, Sishu Shankar Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Campus Besut Terengganu Kuala 22200 Malaysia Department of Mechanical Engineering Universitas Muhamadiyah Tasikmalaya Tamansari Gobras Tasikmalaya 46196 Indonesia Department of Electronics Faculty of Technology Badji-Mokhtar University B.P. 12 Sidi Ammar Annaba 23000 Algeria Department of Electrical and Electronics Engineering Sakarya University of Applied Sciences Serdivan Sakarya 54050 Turkey Department of Mechanical Engineering Adıyaman University Merkez Adıyaman 02040 Turkey Centre for Control Systems Vel Tech University Tamil Nadu Chennai 600062 India School of Quantitative Science University Utara Malaysia Sintok Kedah Bukit Kayu Hitam 06010 Malaysia Faculty of Education and Arts Sohar University Sohar 311 Oman Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Gong Badak Terengganu Kuala Terengganu 21300 Malaysia Department of Physical Sciences Department of Physical Sciences Indian Institute of Science Education and Research Mohanpur Kolkata 741246 India

In this paper, a new 3D dynamical system with four quadratic nonlinear terms is presented. It is shown that the proposed chaotic system has two saddle-foci, unstable, equilibrium points. Thus, the proposed chaotic system exhibits self-excited chaotic attractors. Dynamical analysis methods such as Lyapunov exponents spectrum, bifurcation diagrams, and phase portraits are used to explore the complex dynamical behaviors of the proposed chaotic system and analyze its basic qualitative properties. It is shown that the maximal Lyapunov exponent (MLE) of the new chaotic system is 7.196, which is a high value. The proposed highly chaotic system exhibits high complexity and it will be very useful for applications in cryptography, encryption and secure communications. The physical feasibility of the proposed system is verified by implementing its electronic circuit schematic using Multisim software. Additionally, a PRNG has been developed using the derived state variables and analyze with NIST-800–22 test. Lastly, we developed a PRNG-based image encryption and employ it for an encryption. The experimental outcomes obtained prove that the 3D chaotic system-based encryption application presented in this section has a very good performance. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Chaos Image encryption Pseudo random number generator

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UX Definitions: The Missing Components and the Need for the Context and Time of Use 13

UX Definitions: The Missing Components and the Need for the ...

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13th International Conference on computing Communication and Networking Technologies, ICCCNT 2022

作者： Mkpojiogu, Emmanuel O.C. Okeke-Uzodike, Obianuju E. Emmanuel, Emelda I. Eze, Chika Universiti Utara Malaysia School of Computing Sintok06010 UUM Malaysia Veritas University Department of Software Engineering Abuja Nigeria Durban University of Technology Faculty of Management Sciences Department of Applied Management KwaZulu-Natal Pietermaritzburg South Africa Ibrahim Badamasi Babangida University Faculty of Management and Social Science Department of Sociology Niger State Lapai Nigeria Veritas University Abuja Faculty of Education Department of Educational Foundations Guidance and Counselling Unit Abuja Nigeria

ISBN: (数字)9781665452625

ISBN: (纸本)9781665452625

There are several definitions for user experience (UX). However, this study unveiled that there are missing components in those definitions. An analysis of user experience definitions shows that the definitions had the elements of time of use and context of use absent in them. These missing components limit and obscure the understanding of user experience. Nevertheless, the inclusion of these components improves the specificity, robustness, uniqueness, and meaningfulness of UX and will provide illumination for the conceptualization, design, evaluation, and modeling of UX. As UX is understood the way it is defined, an all-encompassing definition that comprises the components of time and context of use will therefore be worthwhile. This study reviewed extant related literature and unraveled these gaps and suggested their inclusion in user experience definitions. © 2022 IEEE.

关键词： User experience

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Spin-energy entanglement of a time-focused neutron

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Physical Review applied 2024年第3期22卷 L031005页

作者： J.C. Leiner S.J. Kuhn S. McKay J.K. Jochum F. Li A.A.M. Irfan F. Funama D. Mettus L. Beddrich C. Franz J. Shen S.R. Parnell R.M. Dalgliesh M. Loyd N. Geerits G. Ortiz C. Pfleiderer R. Pynn Neutron Technologies Division Physik-Department Department of Physics Center for Exploration of Energy and Matter Institute for Quantum Computing Jülich Centre for Neutron Science JCNS Laboratory for Neutron Scattering and Imaging Faculty of Applied Sciences Chilton Oxfordshire OX11 0QX United Kingdom Atominstitut Quantum Science and Engineering Center Princeton New Jersey 08540 USA Center for Quantum Engineering (ZQE) Neutron Sciences Directorate

Intraparticle entanglement of individual particles such as neutrons could enable another class of scattering probes that are sensitive to entanglement in quantum systems and materials. In this work, we present experimental results demonstrating quantum contextuality as a result of entanglement between the spin and energy modes (i.e., degrees of freedom) of single neutrons in a beam using a pair of resonant radio-frequency neutron spin flippers in the modulated intensity with zero effort configuration. We verified the mode entanglement by measuring a Clauser-Horne-Shimony-Holt contextuality witness S defined in the spin and energy subsystems, observing a clear breach of the classical bound of |S|≤2, obtaining S=2.40±0.02. These entangled beams could enable alternative approaches for directly probing dynamics and entanglement in quantum materials whose low-energy excitation scales match those of the incident entangled neutron.

关键词： Entanglement detection Quantum correlations in quantum information Quantum metrology Quantum superposition Quantum fluids & solids Neutron scattering Neutron spin echo spectroscopy Time-of-flight neutron spectroscopy

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CrypToth: Cryptic Pocket Detection through Mixed-Solvent Molecular Dynamics Simulations-Based Topological Data Analysis

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Journal of Chemical Information and Modeling 2025年第11期65卷 5567-5575页

作者： Koseki, Jun Motono, Chie Yanagisawa, Keisuke Kudo, Genki Yoshino, Ryunosuke Hirokawa, Takatsugu Imai, Kenichiro Cellular and Molecular Biotechnology Research Institute National Institute of Advanced Industrial Science and Technology (AIST) Tokyo 135-0064 Japan Integrated Research Center for Self-Care Technology (irc-sct) National Institute of Advanced Industrial Science and Technology (AIST) Tokyo 135-0064 Japan Computational Bio Big-Data Open Innovation Laboratory (CBBD-OIL) National Institute of Advanced Industrial Science and Technology (AIST) Waseda University Shinjuku-ku Tokyo 169-8555 Japan Department of Computer Science School of Computing Institute of Science Tokyo Tokyo 152-8550 Japan Middle Molecule IT-based Drug Discovery Laboratory (MIDL) Institute of Science Tokyo Tokyo 152-8550 Japan Physics Department Graduate School of Pure and Applied Sciences University of Tsukuba Ibaraki 305-8571 Japan Division of Biomedical Science Faculty of Medicine University of Tsukuba Ibaraki 305-8575 Japan Transborder Medical Research Center University of Tsukuba Ibaraki 305-8577 Japan Global Research and Development Center for Business By Quantum-AI Technology (G-QuAT) National Institute of Advanced Industrial Science and Technology (AIST) Ibaraki 305-8560 Japan

Some functional proteins undergo conformational changes to expose hidden binding sites when a binding molecule approaches their surface. Such binding sites are called cryptic sites and are important targets for drug discovery. However, it is still difficult to correctly predict cryptic sites. Therefore, we introduce an advanced method, CrypToth, for the precise identification of cryptic sites utilizing the topological data analysis such as persistent homology method. This method integrates topological data analysis and mixed-solvent molecular dynamics (MSMD) simulations. To identify hotspots corresponding to cryptic sites, we conducted MSMD simulations using six probes with different chemical properties: dimethyl ether, benzene, phenol, methyl imidazole, acetonitrile, and ethylene glycol. Subsequently, we applied our topological data analysis method to rank hotspots based on the possibility of harboring cryptic sites. Evaluation of CrypToth using nine target proteins containing well-defined cryptic sites revealed its superior performance compared with recent machine-learning methods. As a result, in seven of nine cases, hotspots associated with cryptic sites were ranked the highest. CrypToth can explore hotspots on the protein surface favorable to ligand binding using MSMD simulations with six different probes and then identify hotspots corresponding to cryptic sites by assessing the protein’s conformational variability using the topological data analysis. This synergistic approach facilitates the prediction of cryptic sites with a high accuracy. © 2025 The Authors. Published by American Chemical Society.

关键词： Binding sites

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Dual Fuel-Based Multi-Energy System for Australian Renewable Energy Zones at Country Scale

SSRN

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SSRN 2025年

作者： Tariq, Abdul Haseeb Amin, Uzma Shafie-Khan, Miadreza Dehghanian, Payman Senjyu, Tomonobu National University of Sciences and Technology Pakistan School of Electrical Engineering Computing and Mathematical Sciences Curtin University Australia Research and Innovation Division Nowocert Dublin Ireland School of Engineering and Applied Science The George Washington University United States Faculty of Engineering University of the Ryukyus Japan University of Vaasa Finland

The multi-energy system (MES) is an attractive option for producing multi-energy for remote areas. This paper aims to optimize dual-fuel green hydrogen and blended natural gas (BNG) facilitated heterogeneous off-/on-grid MES integrated with renewable sources for different Renewable Energy Zones (REZs) of Australia at the country scale. The main objective is to develop a novel MES for green hydrogen production and BNG for remote housing applications, like combi boilers and gas stoves. The proposed study generates green hydrogen via a proton exchange membrane (PEM) electrolyzer and blends it with natural gas (NG). The blending process involves 20% hydrogen and 80% NG in the overall volume. The optimal sizing of the components, economic-energy-environmental, and performance analyses are performed to examine a feasible solution for each REZ. The results indicate that the North Queensland REZs have the lowest levelized cost of energy (LCE) of 1.28 A$/kWh and 0.1003 A$/kWh, and the net present cost (NPC) of A$0.311 million and A$0.219 million for off-grid and on-grid configurations. The off-grid system has 99.99% and the on-grid system has 95.27% fewer carbon emissions than the NG-fuelled combustion energy system. Therefore, the proposed on-grid dual-fuel-based MES is both more reliably feasible and economically beneficial. © 2025, The Authors. All rights reserved.

关键词： Clean energy

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Classification of Breast Thermal Images into Healthy/Cancer Group Using Pre-Trained Deep Learning Schemes

Classification of Breast Thermal Images into Healthy/Cancer ...

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2022 International Conference on Machine Learning and Data Engineering, ICMLDE 2022

作者： Kadry, Seifedine Crespo, Rubén González Herrera-Viedma, Enrique Krishnamoorthy, Sujatha Rajinikanth, Venkatesan Faculty of Applied Computing and Technology Noroff University College Kristiansand94612 Norway Computer Science Department School of Engineering and Technology Universidad Internacional de la Rioja Andalusia26006 Spain Research Institute in Data Science and Computational Intelligence University of Granada Granada Spain Zhejiang Bioinformatics International Science and Technology Cooperation Center Wenzhou-Kean University Zhejiang Province China Wenzhou Municipal Key Lab of Applied Biomedical and Biopharmaceutical Informatics Wenzhou-Kean University Zhejiang Province China Department of Computer Science and Engineering Saveetha School of Engineering SIMATS Tamil Nadu Chennai602105 India

In the women's community, Breast Cancer (BC) is a severe disease. The World Health Organization reported in 2020 that 2.26 million deaths occur due to BC. BC is curable if detected early. Since thermal imaging is non-invasive and supports disease detection, it is commonly used in clinics. Compared to other methods, it keeps BC early and accurate. The proposed work aims to evaluate the performance of the Pretrained Deep-Learning Methods (PDLM) in detecting BC using the thermal images collected from the benchmark dataset. It includes the following stages: primary image processing, deep feature mining, handcrafted feature mining, feature optimization using Firefly-Algorithm (FA), classification and validation. Visual Lab thermal images were used in the study. The investigational outcome of this study authenticates that the VGG16, along with the DT, provides better detection accuracy (95.5%) compared to other classifiers used in this study. To justify the significance of the implemented technique, the proposed work not only improved accuracy, but also improved precision, sensitivity, specificity, and F1-Scores. © 2023 The Authors. Published by Elsevier B.V.

关键词： Classification (of information)

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Hybrid Layered Encoding Cascade Optimization Model in Two-Stage Amplifier Circuit Design

Hybrid Layered Encoding Cascade Optimization Model in Two-St...

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IEEE Symposium on Industrial Electronics & Applications (ISIEA)

作者： Nazuha Fadzal Ahmad Nazmi Fadzal Nurul Huda Kamarulzaman Suziana Omar Norhayati Ahmad School of Electrical Engineering College of Engineering Universiti Teknologi MARA (Terengganu) Dungun Terengganu Malaysia College of Computing Informatics and Mathematics Universiti Teknologi MARA (Terengganu) Kuala Terengganu Terengganu Malaysia Faculty of Applied Science Universiti Teknologi MARA (Terengganu) Bukit Besi Terengganu Malaysia

ISBN: (数字)9798350386868

ISBN: (纸本)9798350386875

The integration of hybrid computational intelligence techniques into the Layered Encoding Cascade Optimization (LECO) model is driven by a balanced approach, combining exploration through Genetic Algorithm (GA) for broader solutions and focused local search employing Particle Swarm Optimization (PSO). In this model, a distinct external layer introduces a layer encoding structure with multi- resolution capabilities. This structure enables GA functions for integral value individuals, while conducting PSO functions for real-valued individuals as potential solutions. To estimate the efficacy of the GA-PSO LECO model, a specific study involving the design of a two-stage amplifier circuit is carried out. Results indicate that the GA-PSO LECO model surpasses existing APLAC built-in optimization methods, achieving a minimum on S (1,1) and S (2,2) at the same time, simultaneously maximizing dB [S (2,1)] to 16.469 dB from the two-stage amplifier circuit.

关键词： Computational modeling Optimization models Search problems Encoding Circuit synthesis Integrated circuit modeling Particle swarm optimization

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Fake Twitter Followers Detection using Machine Learning Approach

Fake Twitter Followers Detection using Machine Learning Appr...

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Business Analytics for Technology and Security (ICBATS), International Conference on

作者： Muhammad Zeshan Shabbir Iftikhar Naseer Shamim Akhter Muhammad Abubakar Ghassan F. Issa Muhammad Hassaan Mehmood Faculty of Information and Technology Comsats University Islamabad Pakistan Faculty of Computer Science & Information Technology The Superior University Lahore Pakistan School of Library & Information Sciences Minhaj University Lahore Pakistan Fast School of Computing National University of Computer and Emerging Sciences Lahore Pakistan School of Information Technology Skyline University College University City Sharjah Sharjah UAE School of Computer Science NCBA&E Lahore Pakistan Applied Science Research Center Applied Science Private Universit Amman Jordan

Fake user accounts on social media are a serious threat. Artificial intelligence can play an important role in getting rid of fake user accounts. Twitter has a problem with fake accounts that are run by automated bots. These bots are used for bad things like spamming, sabotaging trends, and getting more followers. In this research, publicly available information about Twitter users, such as their activity patterns, profile information, and tweets, to figure out how real each one is. Twitter’s API and other ways of getting information will be used to get user data. The proposed model consists of a machine learning technique, and it detects whether the user accounts are real or fake. Various algorithms such as logistic regression, long short-term memory, K-mean, and random forest are applied to evaluate the proposed model. The experimental results show that the random forest algorithm has obtained the highest accuracy 0.7557, a precision of 0.7277, and F1 of 0.7943 among all other algorithms.

关键词： Machine learning algorithms Social networking (online) Unsolicited e-mail Blogs Forestry Chatbots Market research

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