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6th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2022

作者： Salih, Mustafa Muhanad M. Alrubaee, Saif H. Dheyab, Abdullah Abdulateef, Ihsan Amjad Abdulsattar, Nejood Faisal Abbas, Fatima Hashim AL Mansour University College Department of Computer Science and Information System Iraq Al-Farahidi University Department of Communication Technical Engineering Baghdad Iraq Al-Anbar Health Directorate Ministry of Health Iraq Altinbas University Department of Electrical and Computer Engineering Turkey College of Information Technology Imam ja'Afar AI-Sadiq University Department of Computer Technical Engineering Al-Muthanna66002 Iraq Al-Mustaqbal University College Medical Laboratories Techniques Department Hillah51001 Iraq

ISBN: (数字)9781665470131

ISBN: (纸本)9781665470131

One area of study that has gained popularity recently is communication technology. Due to the exponential growth in data transfer rates, optical fibre communication (OFC) is the only viable solution. The OFC technology provides extremely high bandwidth and rates of up to several gigabits per second. Optical fibre can carry a lot of data while being quite lightweight. Unfortunately, attenuation, dispersion, and nonlinearity are all phenomena of optical fibre transmission systems that might increase fibre signals. Rather of relying on dispersive effects, an improved approach lies in the use of optical solitons. Different from non-soliton communication systems, solitons do not grow in size as the distance between nodes increases. This research compares and contrasts the efficiency of solitons and non-solitons in fibres. By comparing the eye diagrams and bit error rates, we may deduce that soli-ton-based fibre systems are the most distortion-free, whereas non-soliton-based fibre systems exhibit some level of background noise. © 2022 IEEE.

关键词： Solitons

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Hybrid CNN LSTM Approach for Sentiment Analysis of Bengali Language Comment on Facebook

Hybrid CNN LSTM Approach for Sentiment Analysis of Bengali L...

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Integrated Circuits and communication systems (ICICACS), IEEE International Conference on

作者： SM Nuruzzaman Nobel S M Masfequier Rahman Swapno Ramachandra A C Hasibul Hossain Shajeeb Md Babul Islam Rezaul Haque Dept of Computer Science and Engineering Bangladesh University of Business and Technology Dhaka Bangladesh Department of Electronics and Communication Engineering Nitte Meenakshi Institute of Technology Bengaluru Dept. of Computer Modeling Electronic and System Engineering UNICAL Rende Italy Dept of CSE East West University Dhaka Bangladesh

This study addresses the challenge of sentiment analysis in Bengali Facebook comments, where users express their opinions on various topics. Existing sentiment analysis techniques have difficulty achieving high accuracy in this situation, which has inspired the creation of a fresh methodology. To improve sentiment analysis of Bengali Facebook comments, we suggest a model that combines a hybrid convolutional neural network (CNN) and a long short-term memory network (LSTM). Our research adds to the expanding area of sentiment analysis, especially for languages with few resources, such as Bengali. The success of the Hybrid CNN LSTM model opens the door for more precise and context-aware sentiment analysis on social media platforms, allowing for a better understanding of user sentiments and boosting user experiences. Our study focused on dividing comments into five groups according to their emotional content: troll, not bully, sexual, religious, and threat. We carefully generated the handmade dataset and ensured the quality and relevance of a dataset of 50,000 Bengali comments before using it to train and test our algorithm. The Hybrid CNN LSTM model outperforms conventional approaches and achieves an outstanding accuracy rate of 92.09%, demonstrating amazing efficiency in sentiment recognition. This dramatic increase in precision indicates that machine learning techniques are successful in sentiment analysis of Bengali Facebook comments.

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Intelligent Energy-Efficient and Fair Resource Scheduling for UAV-Assisted Space-Air-Ground Integrated Networks Under Jamming Attacks

Intelligent Energy-Efficient and Fair Resource Scheduling fo...

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IEEE Conference on Vehicular Technology (VTC)

作者： Shihao Chen Helin Yang Liang Xiao Changyuan Xu Xianzhong Xie Wanting Yang Zehui Xiong Department of Information & Communication Engineering Xiamen University Xiamen China Chongqing Key Laboratory of Computer Network and Communication Technology Chongqing University of Posts and Telecommunications Chongqing China Pillar of Information System Technology & Design Singapore University of Technology and Design Singapore

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

The space-air-ground integrated network (SAGIN) is a crucial technology for sixth-generation (6G) wireless communication networks to achieve seamless coverage and high throughput. In this paper, we propose an unmanned aerial vehicle (UAV)-assisted SAGIN structure, where the UAV is responsible for collecting data from ground users (GUs) and transmitting it to low-earth orbit (LEO) satellites. This paper also formulates a joint energy-efficient and fair resource scheduling optimization problem under jamming attacks and limited energy constraints, where the line-of-sight (LoS) links between the UAV and GUs are susceptible to being jammed. Due to the non-convex problem and dynamic environments, a deep reinforcement learning (DRL)-based twin delayed deep deterministic policy gradient (TD3) is developed to search optimal UAV trajectory to maximize energy efficiency (EE) and fairness against jamming. Simulation results verify that the proposed intelligent resource scheduling algorithm outperforms the baseline algorithms in terms of EE and fairness index in different settings.

关键词： Wireless communication Vehicular and wireless technologies Simulation Autonomous aerial vehicles Space-air-ground integrated networks Energy efficiency Trajectory

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Identification of Key Signaling Pathways and Novel Computational Drug Target for Depression and Coronary Artery Disease

Identification of Key Signaling Pathways and Novel Computati...

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Computing, Applications and systems (COMPAS), IEEE International Conference on

作者： Md. Faruk Hosen Md. Abul Basar Mst. Farjana Yasmin Monir Morshed Muhammad Shahin Uddin Department of Computing and Information System Daffodil International University Dhaka Bangladesh Department of Computer Science and Engineering Uttara University (UU) Dhaka Bangladesh Department of Information and Communication Technology Mawlana Bhashani Science and Technology University Tangail Bangladesh

ISBN: (数字)9798331529765

ISBN: (纸本)9798331529772

Psychological disorders, such as anxiety, bipolar disorder, panic disorder, stress, depression, and schizophrenia, are increasingly prevalent worldwide. Among these conditions, depression is particularly notable as one of the most common and debilitating neuropsychiatric disorders. Individuals with depression may be at a higher risk of developing oronary Artery Disease (CAD). Depression can contribute to poor lifestyle choices, such as unhealthy eating, lack of exercise, and smoking, which are risk factors for CAD. The emotional stress and anxiety associated with depression can strain the heart and exacerbate CAD symptoms. The relationship is not one-sided. CAD itself can be a significant source of emotional distress, leading to symptoms of depression and anxiety in affected individuals. Managing both conditions in tandem can be complicated. Treating CAD may involve medications, lifestyle modifications, and potentially surgical interventions. Meanwhile, depression often requires therapy, counseling, and medication. Coordinating care and addressing both conditions simultaneously is crucial. In our study, we investigated the molecular connections between CAD and Depression using GSE98793 and GSE20681 microarray datasets. After preprocessing, we identified key hub genes, including CCT2, SVIL, REPS2, ASPH, and UBC, in the shared ProteinProtein Interaction network. KEGG pathways linked these DEGs to colorectal and cancer pathways. Our next steps involve exploring microRNAs, TFs, and GO analysis. These findings offer promising leads for potential therapies, uniting CAD and Depression under a common molecular framework, advancing our understanding of these conditions.

关键词： Proteins Drugs Anxiety disorders systems biology Surgery Human factors Schizophrenia Depression Arteries Strain

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Deep Learning Techniques for Advanced Large-Scale Data Processing

Deep Learning Techniques for Advanced Large-Scale Data Proce...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Mp Sunil Jyoti Shekhawat T. Vanaja Vazeer Ali Mohammed Shailesh J. Thaware Vaishali Singh Department of Electronics and Communication Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore Karnataka India Department of Computer Science & Application Vivekananda Global University Jaipur India Department of Information Technology Prince Shri Venkateshwara Padmavathy Engineering College Chennai Department of Computer & Information System Lewis University Illinois USA Department of Computer Engineering Vishwakarma Institute of Technology Pune INDIA Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Deep getting to know techniques have become increasingly more popular due to their potential to improve huge-scale records processing performance. Leveraging specialized hardware which includes GPUs, deep getting to know algorithms can attain mind-blowing pace will increase compared to traditional algorithms. further, deep gaining knowledge of fashions can discover complicated non-linear relationships in big datasets, permitting greater accurate overall performance and less fake predictions. Latest advances in deep mastering have enabled it to be implemented to remedy a plethora of information processing duties, from photo recognition to natural language processing. CNNs, RNNs, and GANs are a number of the maximum famous deep gaining knowledge of fashions used in tackling complex data processing obligations. agencies consisting of Google, fb, and Amazon use these sophisticated frameworks to build predictive models that help improve numerous programs. Deep getting to know strategies offer exquisite ability to take massive-scale information processing to the following stage. corporations are increasingly more becoming privy to the emerging opportunities, and actively investing in deep mastering to liberate the untapped strength of their information.

关键词： Deep learning Accuracy Scalability Information processing Predictive models Data processing Prediction algorithms Hardware Natural language processing Optimization

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Enhanced Signal Processing through Frequency Normalization using Fourier Transform Techniques

Enhanced Signal Processing through Frequency Normalization u...

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Intelligent Technologies (ACOIT), Asian Conference on

作者： Neeraj Bhargava Pramod Singh Rathore Ankur Goswami Apoorva Bhowmick Avanindra Vasuki Vyas School of Engineering & System Sciences MDS University Ajmer India Department of Computer and Communication Engineering Manipal University Jaipur India Department of Computer Applications Govt. Engineering College Bikaner India United Nations Secretariate New Yourk NY USA United Nations Secretariate Baghdad Iraq MDS University Ajmer India

ISBN: (数字)9798350374957

ISBN: (纸本)9798350374964

In the realm of signal processing, achieving accurate frequency normalization is pivotal for the effective analysis and interpretation of signals across various applications. This paper presents a novel approach to frequency normalization utilizing Fourier Transform techniques to enhance signal processing capabilities. By leveraging the mathematical robustness of the Fourier Transform, the proposed method systematically adjusts and normalizes frequency components, thereby improving the clarity and precision of signal analysis. Author addresses common challenges such as signal distortion and noise interference, providing a more reliable framework for applications in communications, biomedical engineering, and audio signal processing. Experimental results demonstrate the efficacy of our method in maintaining signal integrity and enhancing processing performance, particularly in complex and noisy environments. This research offers significant advancements in the field of signal processing, paving the way for more accurate and efficient frequency normalization techniques.

关键词： Fourier transforms Accuracy Noise reduction Noise Reliability engineering Robustness Machine listening Noise measurement Signal analysis Signal integrity

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Quantum Remote State Preparation Based on Quantum Network Coding

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computers, Materials & Continua 2022年第10期73卷 119-132页

作者： Zhen-Zhen Li Zi-Chen Li Yi-Ru Sun Haseeb Ahmad Gang Xu Xiu-Bo Chen School of Information Engineering Beijing Institute of Graphic CommunicationBeijing102600China School of Computer Science and Information Engineering Zhejiang Gongshang UniversityHangzhou310018China Information Security Center State key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China Department of Computer Science National Textile UniversityFaisalabad37610Pakistan School of Information Science and Technology North China University of TechnologyBeijing100144China Advanced Cryptography and System Security Key Laboratory of Sichuan Province China

As an innovative theory and technology,quantum network coding has become the research hotspot in quantum network *** this paper,a quantum remote state preparation scheme based on quantum network coding is *** with the general quantum remote state preparation schemes,our proposed scheme brings an arbitrary unknown quantum state finally prepared remotely through the quantum network,by designing the appropriate encoding and decoding steps for quantum network *** is worth mentioning,from the network model,this scheme is built on the quantum k-pair network which is the expansion of the typical bottleneck network—butterfly ***,it can be treated as an efficient quantum network preparation scheme due to the characteristics of network coding,and it also makes the proposed scheme more applicable to the large-scale quantum *** addition,the fact of an arbitrary unknown quantum state remotely prepared means that the senders do not need to know the desired quantum ***,the security of the proposed scheme is ***,this scheme can always achieve the success probability of 1 and 1-max flow of value ***,the communication efficiency of the proposed scheme is ***,the proposed scheme turns out to be practicable,secure and efficient,which helps to effectively enrich the theory of quantum remote state preparation.

关键词： Quantum remote state preparation quantum network coding quantum k-pair network

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Low Power Consumption of Non-Volatile Memory Device by Tunneling Process engineering

SSRN

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SSRN 2024年

作者： Wang, Fucheng Chu, Mengmeng Chen, Jingwen Pan, Zhong Kim, Yongsang Song, Jang Kun Yi, Junsin Khokhar, Muhammad Quddamah Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of Interdisciplinary Program in Photovoltaic System Engineering Sungkyunkwan University Suwon16419 Korea Republic of College of Information and Communication Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Compared with Si3N4 and Al2O3, SiO2 grown using thermal oxidation process as tunneling layer has the advantages of high bandgap and well interface contact with the surface of silicon wafer, which can be a great solution to the leakage current problem of metal-insulator-semiconductor (MIS) devices. This study investigates the effect of improving the SiO2 tunnel layer on the operating voltage of MIS devices with a SiO2/HfAlOx/Al2O3 structure. The result shows the operating voltage changes as the tunneling layer thickness decreases, with a minimum of only 12 V for a 1.5 nm tunneling layer thickness. In addition, we found that pinholes are generated on the film surface when annealing a 1.5 nm SiO2 tunnel layer at 850 °C N2, in which case the operating voltage of the device is reduced to only 10 V, though it was also accompanied by the deterioration of the retention characteristics. © 2024, The Authors. All rights reserved.

关键词： Silicon wafers

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Size-Dependent Formation of Au-NPs Monolayer Under High Electric Field

Size-Dependent Formation of Au-NPs Monolayer Under High Elec...

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IEEE Conference on Nanotechnology

作者： Firdous Ahmad Deader Yawar Abbas Moh'd Rezeq Ahsanulhaq Qurashi Mahmoud Al-Qutayri Vincent Chan Department of Physics and System on chip lab Khalifa University Abu Dhabi UAE Department of Chemistry Khalifa University Abu Dhabi UAE Department of Computer and Communication Engineering Khalifa University Abu Dhabi UAE Department of Biomedical Engineering and Biotechnology Khalifa University Abu Dhabi UAE

ISBN: (数字)9798350386240

ISBN: (纸本)9798350386257

Nanoparticles (NPs) are considered functional materials due to their fundamental properties of high surface-to-volume ratio, high conductivity, and diversified surface functionalization. We conducted experiments on NPs of different sizes and calculated their UV-Vis absorption and zeta potential when they were suspended as a colloid solution of DI water with some traces of citrate. NPs are stabilized by citrate ions and rendered with a net negative surface potential, which can be confirmed by using a zeta-sizer for zeta potential measurement. Citrate ions acting as ligands form a coating on the surface of NPs and induce electrostatic repulsion due to their overall negative charges, whereas NP's inner cores attract each other due to the van der Waals (vdW) force of attraction. The balance of repulsion and attraction keeps NPs stabilized in the aqueous solution for a prolonged period. Different sizes of NPs were subjected to an electric field to form the monolayer on a silicon substrate. The NPs of smaller sizes form an incomplete monolayer of disintegrated islands, due to their lower core: core attractions, these NPs fail to make a uniform and continuous monolayer. NPs of sizes greater than 40 nm show aggregation when placed in a high electric field environment due to their large core size and hence elevated core: core attraction. These large NPs aggregate irreversibly and form the clumps of NPs called nanoclusters. Interestingly, the optimal size of 20nm NPs leads to the formation of a perfectly hexagonally packed monolayer on the substrate when subjected to an electric field of $\approx 7.2\mathrm{x}10^{4}\mathrm{V}/\mathrm{m}$ ,

关键词： Electric potential Solvents Force Ions Silicon Electric fields Probes

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Lightweight Authentication of Devices in Industrial Control systems

Lightweight Authentication of Devices in Industrial Control ...

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IEEE International Conference on Software engineering and Service Sciences (ICSESS)

作者： Long Wang Siqi Niu Henggao Zhai Jing Fan Lei Wang National Computer System Engineering Research Institute of China Beijing China Department of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Coocaa Network Technology Co. Ltd. Guangdong China

A security authentication protocol based on number theory research unit (NTRU) for industrial control devices is proposed to address the security of data transmission in industrial control systems and the lack of resistance to attacks of security authentication protocols. Most of the original protocols contain complex encryption and decryption operations, which are difficult to run on industrial control devices with simple structures and cannot resist new types of network attacks. In this paper, the protocol takes advantage of the simple operation of NTRU public key encryption system and sets the authorization center to send only the public key of the device in a variant form to achieve the purpose of resisting new attacks such as quantum attacks and internal attacks, and the anti-attack capability is strengthened.

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