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DeepCNN:Spectro-temporal feature representation for speech emotion recognition

CAAI Transactions on Intelligence technology 2023年第2期8卷 401-417页

作者： Nasir Saleem Jiechao Gao Rizwana Irfan Ahmad Almadhor Hafiz Tayyab Rauf Yudong Zhang Seifedine Kadry Department of Electrical Engineering Faculty of Engineering and TechnologyGomal UniversityD.I.KhanPakistan Department of Computer Science University of VirginiaCharlottesvilleVirginiaUSA Department of Information Technology College of Computing and Information Technology at KhulaisUniversity of JeddahJeddahSaudi Arabia Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySkaka AljoufSaudi Arabia Centre for Smart Systems AI and CybersecurityStaffordshire UniversityStoke‐on‐TrentUK School of Computing and Mathematical Sciences University of LeicesterLeicesterUK Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) Ajman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon

Speech emotion recognition(SER)is an important research problem in human-computer interaction *** representation and extraction of features are significant challenges in SER *** the promising results of recent studies,they generally do not leverage progressive fusion techniques for effective feature representation and increasing receptive *** mitigate this problem,this article proposes DeepCNN,which is a fusion of spectral and temporal features of emotional speech by parallelising convolutional neural networks(CNNs)and a convolution layer-based *** parallel CNNs are applied to extract the spectral features(2D-CNN)and temporal features(1D-CNN)representations.A 2D-convolution layer-based transformer module extracts spectro-temporal features and concatenates them with features from parallel *** learnt low-level concatenated features are then applied to a deep framework of convolutional blocks,which retrieves high-level feature representation and subsequently categorises the emotional states using an attention gated recurrent unit and classification *** fusion technique results in a deeper hierarchical feature representation at a lower computational cost while simultaneously expanding the filter depth and reducing the feature *** Berlin Database of Emotional Speech(EMO-BD)and Interactive Emotional Dyadic Motion Capture(IEMOCAP)datasets are used in experiments to recognise distinct speech *** efficient spectral and temporal feature representation,the proposed SER model achieves 94.2%accuracy for different emotions on the EMO-BD and 81.1%accuracy on the IEMOCAP dataset *** proposed SER system,DeepCNN,outperforms the baseline SER systems in terms of emotion recognition accuracy on the EMO-BD and IEMOCAP datasets.

关键词： decision making deep learning

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OLBR: Optimization of Location-Based Routing Protocols in Vehicular Ad Hoc Networks

OLBR: Optimization of Location-Based Routing Protocols in Ve...

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Recent Innovation in Smart and Sustainable technology (ICRISST), International Conference on

作者： Thangam S M Vivek Srikar Reddy Karthik Ullas N Abdul Khadar Jilani K Venkatesh J Jesy Janet Kumari A Saleem Raja Dept. of Computer Science and Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India IT Department College of Computing and Information Sciences University of Technology and Applied Sciences-Shinas Sultanate of Oman

ISBN: (数字)9798350309140

ISBN: (纸本)9798350309157

The proposed work employs ns-3, SUMO, and NetAnim to create geographical routing in vehicular ad hoc networks (VANETs). The research attempts to assess the performance of three well-known protocols AODV, DSDV, and OLSR in VANET settings. Utilizing SUMO’s realistic mobility models and NS3’s simulation capabilities, the project simulates node communication, protocol behaviour, and vehicle movement. The main purpose is to know how well various routing techniques work in dynamic vehicular situations.

关键词： Technological innovation Roads Vehicular ad hoc networks Packet loss Routing Routing protocols Delays Vehicle dynamics AODV Optimization

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cVIL: Class-Centric Visual Interactive Labeling

arXiv

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arXiv 2024年

作者： Matt, Matthias Zeppelzauer, Matthias Waldner, Manuela TU Wien Institute of Visual Computing & Human-Centered Technology Austria St. Pölten University of Applied Sciences Austria

(Image Presented) We present cVIL, a class-centric approach to visual interactive labeling, which facilitates human annotation of large and complex image data sets. cVIL uses different property measures to support instance labeling for labeling difficult instances and batch labeling to quickly label easy instances. Simulated experiments reveal that cVIL with batch labeling can outperform traditional labeling approaches based on active learning. In a user study, cVIL led to better accuracy and higher user preference compared to a traditional instance-based visual interactive labeling approach based on 2D scatterplots. © 2024, CC BY.

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Hill Matrix and Radix-64 Bit Algorithm to Preserve Data Confidentiality

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Computers, Materials & Continua 2023年第5期75卷 3065-3089页

作者： Ali Arshad Muhammad Nadeem Saman Riaz Syeda Wajiha Zahra Ashit Kumar Dutta Zaid Alzaid Rana Alabdan Badr Almutairi Sultan Almotairi Department of Computer Science National University of TechnologyIslamabadPakistan Department of Computing Abasyn UniversityIslamabadPakistan Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia Department of Computer Science Faculty of Computer and Information SystemsIslamic university of MadinahMedinah42351Saudi Arabia Department of Information Systems Faculty of Computer and Information Sciences CollegeMajmaah University11952Saudi Arabia Department of Information Technology College of Computer Sciences and Information Technology CollegeMajmaah UniversityAl-Majmaah 11952Saudi Arabia Department of Natural and Applied Sciences Faculty of Community CollegeMajmaah UniversityMajmaah11952Saudi Arabia

There are many cloud data security techniques and algorithms available that can be used to detect attacks on cloud data,but these techniques and algorithms cannot be used to protect data from an *** cryptography is the best way to transmit data in a secure and reliable *** researchers have developed various mechanisms to transfer data securely,which can convert data from readable to unreadable,but these algorithms are not sufficient to provide complete data *** algorithm has some data security *** some effective data protection techniques are used,the attacker will not be able to decipher the encrypted data,and even if the attacker tries to tamper with the data,the attacker will not have access to the original *** this paper,various data security techniques are developed,which can be used to protect the data from attackers ***,a customized American Standard Code for Information Interchange(ASCII)table is *** value of each Index is defined in a customized ASCII *** an attacker tries to decrypt the data,the attacker always tries to apply the predefined ASCII table on the Ciphertext,which in a way,can be helpful for the attacker to decrypt the *** that,a radix 64-bit encryption mechanism is used,with the help of which the number of cipher data is doubled from the original *** the number of cipher values is double the original data,the attacker tries to decrypt each *** of getting the original data,the attacker gets such data that has no relation to the original *** that,a Hill Matrix algorithm is created,with the help of which a key is generated that is used in the exact plain text for which it is created,and this Key cannot be used in any other plain *** boundaries of each Hill text work up to that *** techniques used in this paper are compared with those used in various papers and discussed that how far the current algorithm is better than all other algorit

关键词： Cryptography symmetric cipher text encryption matrix cipher encoding decoding hill matrix 64-bit encryption

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Automatic classification of histology images into normal/cancer class with pre-trained CNN 8

Automatic classification of histology images into normal/can...

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8th International Virtual Conference on Biosignals, Images, and Instrumentation, ICBSII 2022

作者： Achuthan, Geetha Kadry, Seifedine Suresh Manic, K. Meqdad, Maytham N. Department of Electrical and Communication Engineering National University of Science and Technology Oman Faculty of Applied Computing and Technology Noroff University College Kristiansand94612 Norway Al-Mustaqbal University College Babil Hillah Iraq

Deep-Learning-Scheme (DLS) based medical data assessment has been widely employed in recent years due to its improved accuracy. Our goal is to study the performance of the pre-trained DLS on RGB-scale breast-histology images. The implemented idea holds these phases;(i) Data collection, pre-processing and resizing, (ii) Training the DLS with chosen test-pictures, (iii) Testing and validating the performance of the DLS with 5-fold cross-validation. This investigation considered the breast-histology pictures for the study and binary classification is employed to achieve Normal/Cancer class grouping of images. The proposed work compared the classification performance of AlexNet, VGG16 and *** experimental outcome of this study authenticates that the AlexNet with the Random-Forest (RF) classifier helps to get a higher classification accuracy (>87%) compared to VGG16 and VGG19. © Published under licence by IOP Publishing Ltd.

关键词： Histology

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Effect of vertical rotation and salt on the stability of a couple stress fluid layer

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Chinese Journal of Physics 2025年 96卷 245-257页

作者： Choudhary, Shalu Devi, Reeta Mahajan, Amit Sunil Chandel, Vishal Sharma, Manoj Sarita Yadav, Dhananjay Department of Mathematics Uttaranchal University Uttarakhand Dehradun India Department of Mathematics Govt. Post Degree College Nagrota Bagwan H.P. Kangra India Department of Applied Sciences National Institute of Technology Delhi India Department of Mathematics and Scientific Computing NIT Hamirpur India Department of Mathematics and Physical Sciences University of Nizwa Oman

The study investigates the stability characteristics of the effect of rotation and salt on convection in a couple stress fluid subject to different conducting boundary conditions. The stability analysis, conducted through linear stability theory and energy theory, confirms that the critical conditions for the onset of instability remain identical for both approaches. The results indicate that couple stresses significantly hinder fluid flow, reducing heat transfer through convection. Furthermore, increased rotation and salt concentration exhibit stabilizing effects, delaying the onset of convection. Among the boundary conditions examined, the free-free (FF) system exhibits an earlier onset of convection, while the rigid-rigid (RR) system demonstrates enhanced stability at lower Taylor numbers. However, beyond a certain threshold of the Taylor number, the FF system becomes more stable than the RR system. These findings underscore the crucial role of boundary conditions and physical parameters in modulating convection in a rotating couple stress fluid layer. © 2025 The Physical Society of the Republic of China (Taiwan)

关键词： Couple-stress fluid Rotation Solute Stability analysis

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Availability and Demand of Jobs from the Perception of Automated Recruitment in Oman

Availability and Demand of Jobs from the Perception of Autom...

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International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)

作者： Mohamed Abdul Karim Sadiq Nasser Mohammed Al-Fannah Thirumurugan Shanmugam Firdous Kausar College of Computing and Information Science University of Technology and Applied Sciences (UTAS) Oman Ministry of Transport Communications and Information Technology Muscat Oman UTAS College of Computing and Information Science Suhar Oman College of Computing and Information Science University of Technology and Applied Sciences Suhar Oman Department of Mathematics and Computer Science Fisk University Nashville Tennessee USA

Natural Language Processing has been applied for automation of the recruitment process globally with the increase in volumes of profiles and jobs. This paper discusses certain challenges in the use of cutting-edge technologies for documents in the Arabic language. We analyze the availability and demand of jobs in Oman with reference to that in UAE. As a result, hurdles can be minimized in the job-resume matching process between the employers and prospective candidates.

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Exploring the Aging Dynamics of Lithium-Ion Batteries for Enhanced Lifespan Understanding 7

Exploring the Aging Dynamics of Lithium-Ion Batteries for En...

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7th International Symposium on Hydrogen Energy and Energy Technologies, HEET 2024

作者： Madani, Seyed Saeed Allard, François Shabeer, Yasmin Fowler, Michael Panchal, Satyam Ziebert, Carlos Mekhilef, Saad Dou, Shi Xue See, Khay Wang, Zolu Department of Chemical Engineering University of Waterloo WaterlooON Canada VarennesQCJ3X 1P7 Canada Institute of Applied Materials-Applied Materials Physics Karlsruhe Institute of Technology Germany School of Science Computing and Engineering Technologies Swinburne University of Technology Australia AIIM University of Wollongong WollongongNSW2500 Australia Institute of Energy Materials Science University of Shanghai for Science and Technology Shanghai China Centre for Efficiency and Performance Engineering University of Huddersfield HuddersfieldHD1 3DH United Kingdom

This review examines the aging mechanisms and performance decline of lithium-ion batteries under various conditions, focusing on temperature effects, charge/discharge efficiency, and operational limits. It covers high-temperature aging and its impact on the solid electrolyte interphase (SEI) layer, as well as thermal runaway risks. Low-temperature aging is also discussed, emphasizing reversible capacity loss, increased resistance, and lithium plating. The review addresses degradation from overcharge/overdischarge scenarios and explores coulombic efficiency (CE) degradation and its link to capacity loss. By synthesizing current research, it provides insights into optimizing battery management and enhancing performance. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Lithium-ion batteries

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Polynomial Reduction Methods and their Impact on QAOA Circuits

arXiv

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arXiv 2024年

作者： Schmidbauer, Lukas Wintersperger, Karen Lobe, Elisabeth Mauerer, Wolfgang Technical University of Applied Sciences Regensburg Regensburg Germany Siemens AG Technology Munich Germany Institute of Software Technology Department High-Performance Computing Braunschweig Germany Technical University of Applied Sciences Regensburg Siemens AG Technology Regensburg Munich Germany

Abstraction layers are of paramount importance in software architecture, as they shield the higher-level formulation of payload computations from lower-level details. Since quantum computing (QC) introduces many such details that are often unaccustomed to computer scientists, an obvious desideratum is to devise appropriate abstraction layers for QC. For discrete optimisation, one such abstraction is to cast problems in quadratic unconstrained binary optimisation (QUBO) form, which is amenable to a variety of quantum approaches. However, different mathematically equivalent forms can lead to different behaviour on quantum hardware, ranging from ease of mapping onto qubits to performance scalability. In this work, we show how using higher-order problem formulations (that provide better expressivity in modelling optimisation tasks than plain QUBO formulations) and their automatic transformation into QUBO form can be used to leverage such differences to prioritise between different desired non-functional properties for quantum optimisation. Based on a practically relevant use-case and a graph-theoretic analysis, we evaluate how different transformation approaches influence widely used quantum performance metrics (circuit depth, gates count, gate distribution, qubit scaling), and also consider the classical computational efforts required to perform the transformations, as they influence possibilities for achieving future quantum advantage. Furthermore, we establish more general properties and invariants of the transformation methods. Our quantitative study shows that the approach allows us to satisfy different trade-offs, and suggests various possibilities for the future construction of general-purpose abstractions and automatic generation of useful quantum circuits from high-level problem descriptions. © 2024, CC BY.

关键词： Timing circuits

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Fabric4show: real-time vision system for fabric defect detection and post-processing

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Visual Intelligence 2024年第1期2卷 1-13页

作者： Lin, Huaizhou Cai, Dan Xu, Zengmin Wu, Jinsong Sun, Lixian Jia, Haibin School of Materials Science and Engineering Guangxi Key Laboratory of Information Guilin University of Electronic Technology Guilin China School of Mathematics and Computing Science Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation Guilin University of Electronic Technology Center for Applied Mathematics of Guangxi (GUET) Guilin China Anview.ai Guilin China School of Artificial Intelligence Guilin University of Electronic Technology Guilin China Department of Electrical Engineering University of Chile Santiago Chile

The exploration of computer vision applications for fabric defect detection has immense potential value. However, current relevant research in this area has primarily focused on detection models that aim for high detection accuracy and algorithmic efficiency, while neglecting the practical industrial production requirements. Therefore, we propose a fabric defect detection and post-processing system that integrates an optimized region with convolutional neural network (CNN) features (i.e., Faster R-CNN) for defect detection, defect localization and detection model evaluation. In addition, the proposed intelligent system incorporates novel approaches, such as a rearranged fabric dataset, anomaly detection, recommended clipping region division, and a replenishment device. This study illustrates an example of artificial intelligence (AI)-driven automated technology in fabric manufacturing. The accuracy and detection speed of different detection models under identical hardware conditions are evaluated and compared with related work. Experimental results demonstrate that the proposed approach achieves comparable performance to other models, while significantly reducing computational resource requirements. The potential efficiency of using two-stage networks on hardware systems for fabric defect detection tasks is highlighted, which is likely to have relevant implications for the textile industry. © The Author(s) 2024.

关键词： Automation Computer vision Defect detection Fabric manufacturing Faster R-CNN

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