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2022 International Mobile and Embedded Technology Conference, MECON 2022

作者： Akila, D. Elangovan, V.R. Batth, Ranbir Singh Balaganesh, D. Padmavathi, R. Vels Institute of Science Echnology and Advanced Studies Department of Information Technology Chennai117 India Agurchand Manmull Jain College Department of Computer Application Chennai114 India Lovely Professional University School of Computer Science and Engineering Punjab India Lincoln University College Department of Computer Science and Multimedia Malaysia

ISBN: (纸本)9781665420204

In the years hate, aspects of reusability software are very strange and cannot be avoided by building new software arms. Service-oriented architecture (SOA) is a model for organising and leveraging distributed capabilities that may be controlled by several domains. This is a type of software design in which application components use network communication protocols to provide services to other components. In software components, the reusable handling project team is generally very familiar with the use of the source code database, so they can find the code they need and easily enter it into the application. Developers can also apply code to the repository for analysis, approval and inclusion. Developers can also monitor which applications using the UX version received. This is allowed because the library section is permitted. The software development process includes development time, development costs and human power requirements and so on. To reduce these things, programmers can apply technology called Reusability software components. The process of implementing or modifying software systems using existing software components is known as software component use. which can reduce human power, costs, and time. In this paper applying a new framework for SOA architecture in this architecture ensures the reuse of user services, easy maintenance to software, independent platforms, reliability, and scalability. In this framework for reuse and reduce the time and cost of software components to develop enhanced projects in an efficient way. © 2022 IEEE.

关键词： computer software reusability

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A Novel Two-way cross-tab Machine Learning Approach for predicting Life Insurance using Bivariate Exploratory Analysis

A Novel Two-way cross-tab Machine Learning Approach for pred...

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International Conference on computer Communication and Informatics (ICCCI)

作者： N. Deepa N Udayakumar T Devi. Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Department of Computer Science and Engineering Vels Institute of Science Technology & Advanced Studies (VISTAS)

Life Insurance prediction is the main objective of the research: to evaluate a person’s life insurance using a machine learning model. In day-to-day life human life becomes hectic and the life span of everyone gets reduced due to pandemic situations, unavoidable accidents and historical impacts, etc. Even though the security and saving beneficiaries are there in life insurance, risk factors are also associated with it. Machine learning techniques propose a risk reduction avoidance and prediction of financial scams to save customer’s lives when individual customers claim their own experience in risk factors by sharing their own credentials. The analysis is made by logistic regression based on the probability of categorical data such as identity proof, Aadhar proof, PAN number, and so on as attribute value. Using the novel Two-way cross-tab method the relationships based on attribute value matrix value are generated to find the customer who has no mutual identifier to take the life insurance cash and summarize the prediction using the bivariate exploratory flow of graph. By seeing the difference in the relationship, the threats and risk full factors can be reduced in accuracy compared to existing machine learning models.

关键词： Training Pandemics Insurance Machine learning Predictive models Security Risk management

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An ultra wide-band, high-sensitivity Q-band receiver for single-dish telescopes, eQ: Rest-frequency determination of CCS (J_N = 4₃–3₂) and SO (J_N = 1₀–0₁) and high-redshift CO (J = 1–0) detection

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Publications of the Astronomical Society of Japan 2024年第4期76卷 563-578页

作者： Nakamura, Fumitaka Chiong, Chau-Ching Taniguchi, Kotomi Chien, Chen Ho, Chin-Ting Hwang, Yuh-Jing Yeh, You-Ting Shimoikura, Tomomi Yamasaki, Yasumasa Liu, Sheng-Yuan Hirano, Naomi Lai, Shih-Ping Nishimura, Atsushi Kawabe, Ryohei Dobashi, Kazuhito Fujii, Yasunori Yonekura, Yoshinori Ogawa, Hideo Nguyen Luong, Quang National Astronomical Observatory of Japan The Graduate University for Advanced Studies (SOKENDAI) Department of Astronomy The University of Tokyo Institute of Astronomy and Astrophysics Academia Sinica National Taiwan University Institute of Astronomy National Tsing Hua University Faculty of Social Information Studies Otsuma Women’s University Department of Physics Graduate School of Science Osaka Metropolitan University Nobeyama Radio Observatory National Astronomical Observatory of Japan (NAOJ) National Institutes of Natural Sciences (NINS) Department of Astronomy and Earth Sciences Tokyo Gakugei University Center for Astronomy Ibaraki University Department of Computer Science Mathematics and Environmental Science American University of Paris

We report on the development and commissioning of a new Q-band receiver for the Nobeyama 45 m telescope, covering 30–50 GHz with a receiver noise temperature of about 15 K. We name it eQ (extended Q-band) receiver. The system noise temperatures for observations are measured to be ∼30 K at 33 GHz and ∼75 K at 45 GHz. The half-power beam-width (HPBW) is around 38^'' at 43 GHz. To enhance the observation capability, we tested the smoothed bandpass calibration technique and demonstrated that the observation time can be significantly reduced compared to the standard position switch technique. The wide-bandwidth capability of this receiver provides precise determination of rest frequencies for molecular transitions with an accuracy of a few kHz through simultaneous observations of multiple transitions. Particularly, we determined the rest frequency of SO (J_N = 1₀–0₁) to be 30.001542 GHz, along with the rest frequency of CCS (J_N = 4₃–3₂) being 45.379033 GHz, adopting CCS (J_N = 3₂–2₁) at 33.751370 GHz as a reference line. The SO profile shows a double peak shape at the Cyanopolyyne Peak (CP) position of the Taurus Molecular Cloud-1 (TMC-1). The SO peaks coincide well with the CCS sub-components located near the outer parts of the TMC-1 filament. We interpret that the gravitational infall of TMC-1 generates shocks which enhance the SO abundance. The TMC-1 map shows that carbon-chain molecules are more abundant in the southern part of the filament, whereas SO is more abundant in the northern part. The eQ’s excellent sensitivity allowed us to detect faint CO (J = 1–0) spectra from the high-redshift object at a redshift of 2.442. Our receiver is expected to open new avenues for high-sensitivity molecular line observations in the Q-band. © The Author(s) 2024. Published by Oxford University Press on behalf of the Astronomical Society of Japan.

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Deep Learning Enhancing Performance Using Support Vector Machine HTM Cortical Learning Algorithm 2

Deep Learning Enhancing Performance Using Support Vector Mac...

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2nd International Conference on Physics and Applied sciences, ICPAS 2021

作者： Akila, D. Pal, Souvik Jayakarthik, R. Chattopadhyay, Sitikantha Obaid, Ahmed J. Department of Information Technology Vels Institute of Science Technology and Advanced Studies Chennai India Department of Computer Science and Engineering Global Institute of Management and Technology Kolkata India Department of Computer Science Vels Institute of Science Technology and Advanced Studies Chennai India Department of Computer Science and Engineering Brainware University Barasat India Faculty of Computer Science and Mathematics University of Kufa Iraq

Deep Learning is a function of AI that duplicates the mechanisms of human thought in the processing of information and selection processes. The aim of this study is to apply a technology known as SVMHTMC to improve deep learning. The HTM Cortical Learning Approach and the Support Vector Machine have been combined in this suggested algorithm. The deep learning technique is based on the assumption that the mean absolute percentage error is reduced. Aside from the overlapping duty cycle, the high proportion of which shows the speed of the classifier's processing function. The findings demonstrate that by halving the value, the suggested set of criteria minimizes the absolute proportion of mistakes. In addition, raise the percentage of overlapping duty cycles by 17%. © Published under licence by IOP Publishing Ltd.

关键词： Support vector machines

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Quantum speedups of optimizing approximately convex functions with applications to logarithmic regret stochastic convex bandits 22

Quantum speedups of optimizing approximately convex function...

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Proceedings of the 36th International Conference on Neural Information Processing Systems

作者： Tongyang Li Ruizhe Zhang Advanced Institute of Information Technology Center on Frontiers of Computing Studies and School of Computer Science Peking University Department of Computer Science The University of Texas at Austin

ISBN: (纸本)9781713871088

We initiate the study of quantum algorithms for optimizing approximately convex functions. Given a convex set K ⊆ ℝn and a function F : ℝn → ℝ such that there exists a convex function f : K → ℤ satisfying supx∈K |F(x) - f(x)| ≤ ε/n, our quantum algorithm finds an x* ∈ K such that F(x*) - minx∈K F(x) ≤ ε using Õ(n3) quantum evaluation queries to F. This achieves a polynomial quantum speedup compared to the best-known classical algorithms. As an application, we give a quantum algorithm for zeroth-order stochastic convex bandits with Õ(n5 log2 T) regret, an exponential speedup in T compared to the classical (√T) lower bound. Technically, we achieve quantum speedup in n by exploiting a quantum framework of simulated annealing and adopting a quantum version of the hit-and-run walk. Our speedup in T for zeroth-order stochastic convex bandits is due to a quadratic quantum speedup in multiplicative error of mean estimation.

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Vulnerability Analysis and Exploitation Attacks on Smart Wearable Devices

Vulnerability Analysis and Exploitation Attacks on Smart Wea...

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Advancement in Computation & computer Technologies (InCACCT), International Conference on

作者： Shujahat Ali Khan Hasan Raza Bajwa Jawahar Sundaram Pritika Bharanidharan Shanmugam Energy and Resources Institute Faculty of Science and Technology Charles Darwin University Darwin Australia Department of Computer Science and Applications Christ Academy Institute for Advanced Studies Bengluru India

ISBN: (数字)9798350371314

ISBN: (纸本)9798350371321

Wearable devices are becoming more popular these days due to its unique features and its effectiveness. The evolution of Internet of Things (IoT) that combined health care devices and sensors has entirely changed the scenario in the healthcare infrastructure. This innovation will confidently improve the existing healthcare facilities and practices due to the continuous observing of patient’s health even in the remote places. Regardless of their effectiveness, IoT devices are insecure and are vulnerable to security threats that should need to be overcome. The main issue is to protect from outside entities or attacks that may obstruct the advancement and put the individual’s information at risk. This study focuses on outlining the vulnerabilities focusing on smartwatches in the healthcare IoT domain. Furthermore, it has been observed that a limited Bluetooth Low Energy (BLE) based smartwatches has a very weak or no security defense system making these devices vulnerable to various security threats such as Brute-force attacks, Man-in-The-Middle (MiTM) attacks, Denial of Service (DoS) attacks, and Phishing. Experimental testing has been performed to test the vulnerabilities in smartwatch devices to verify the data integrity concerns. By using Bluetooth sniffing tools, the security of the smart wearable devices has been tested to identify its weaknesses and to target the BLE devices. Attempts have been made to tamper its parameters by gaining access to the devices through Bluetooth connection. The overall result reveals that these devices are vulnerable to different exploits. This study provides the foundation to assess possible vulnerabilities in smart wearable devices. Furthermore, it highlights the loopholes existed in these devices which can be exploited.

关键词： Performance evaluation Technological innovation Phishing Medical services Sensors Security Internet of Things

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Optimization of the ART Tomographic Reconstruction Algorithm - Monte Carlo Simulation 2

Optimization of the ART Tomographic Reconstruction Algorithm...

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2nd International Conference on Applied Artificial Intelligence and computing, ICAAIC 2023

作者： Raviraja, S. Seethalakshmi, K. Kushwaha, Sumit Vishnu Priya, P.M. Kumar, Kallakunta Ravi Dhyani, Bijesh Prabhu, V. Royal Research Foundation® Department of Computer Studies West Bengal Kolkata700050 India Department of Computer Science and Engineering Vel Tech RangarajanDr.Sagunthala R&d Institute of Science and Technology Tamil Nadu Chennai India University Institute of Computing Chandigarh University Department of Computer Applications Punjab 140413 India Kristu Jayanti College Department of Computer Science Karnataka Bengaluru560077 India Koneru Lakshmaiah Education Foundation Department of Electronics and Communication Engineering Andhra Pradesh Vaddeswaram522302 India Graphic Era Deemed to Be University Department of Management Studies Uttarakhand Dehradun248002 India Sri Sai Ram Engineering College Department of Mechanical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9781665456302

This research study discusses about the algebraic reconstruction technique (ART) for performing 3D object reconstruction and two other variants: the use of positivity constraints for reconstructed values and the extra use of transversal projections. This study has used Monte Carlo techniques for 3D objects to mimic illusions and projections using Poisson noise. For a variety of practical signal-to-noise ratios, the modulation parameter was optimized. In contrast to the reuse of transverse projection lines, this study has determined the usage of positivity restriction in the ART technique. If computing time is considered as a significant factor, these enhancements can be compromised in terms of processing speed. © 2023 IEEE.

关键词： Signal to noise ratio

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Scalable parallel photonic processing unit for various neural network accelerations

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Photonics Research 2024年第11期12卷 2691-2702页

作者： SHIYIN DU JUN ZHANG HAO OUYANG ZILONG TAO QIUQUAN YAN HAO HAO JUNHU ZHOU JIE YOU YUHUA TANG TIAN JIANG State Key Laboratory of High-Performance Computing College of ComputerNational University of Defense TechnologyChangsha 410073China National Innovation Institute of Defense Technology Academy of Military Sciences PLA ChinaBeijing 100071China College of Advanced Interdisciplinary Studies National University of Defense TechnologyChangsha 410073China Institute for Quantum Science and Technology College of ScienceNational University of Defense TechnologyChangsha 410073China

In recent years,integrated optical processing units(IOPUs)have demonstrated advantages in energy efficiency and computational speed for neural network inference ***,limited by optical integration technology,the practicality and versatility of IOPU face serious *** this work,a scalable parallel photonic processing unit(SPPU)for various neural network accelerations based on high-speed phase modulation is proposed and implemented on a silicon-on-insulator platform,which supports parallel processing and can switch between multiple computational paradigms simply and without latency to infer different neural network structures,enabling to maximize the utility of on-chip *** SPPU adopts a scalable and process-friendly architecture design,with a preeminent photonic-core energy efficiency of 0.83 TOPS/W,two to ten times higher than existing integrated *** the proof-of-concept experiment,a convolutional neural network(CNN),a residual CNN,and a recurrent neural network(RNN)are all implemented on our photonic processor to handle multiple tasks of handwritten digit classification,signal modulation format recognition,and review emotion *** SPPU achieves multi-task parallel processing capability,serving as a promising and attractive research route to maximize the utility of on-chip components under the constraints of integrated technology,which helps to make IOPU more practical and universal.

关键词： network acceleration attractive

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Unlocking the Potential of Competition-Based Learning: A Case Study of Kaggle in Big Data Analytics Education 10

Unlocking the Potential of Competition-Based Learning: A Cas...

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10th International Conference on Smart computing and Communication, ICSCC 2024

作者： Fan, Pengfei Purwanto, Erick Li, Na Wang, Jia Tay, Ting Ting Wang, Ling Wang, Qiufeng School of Advanced Technology Xi'an Jiaotong-Liverpool University Department of Intelligent Science Suzhou China School of Electronic Engineering and Computer Science School of Physical and Chemical Sciences Queen Mary University of London London United Kingdom School of Advanced Technology Xi'an Jiaotong-Liverpool University Department of Computing Suzhou China Xi'an Jiaotong-Liverpool University Department of Educational Studies Academy of Future Education Suzhou China Xi'an Jiaotong-Liverpool University Educational Development Unit Academy of Future Education Suzhou215123 China

ISBN: (纸本)9798350363104

This study investigates the effectiveness of Competition-Based Learning (CBL) using Kaggle in teaching Big Data Analytics. Through a quasi-mixed research design, integrating qualitative and quantitative methods, data was collected from students who completed the Big Data Analytics module. Results indicate high satisfaction levels among participants, with the majority expressing willingness to recommend CBL using Kaggle to future students. Moreover, the CBL approach significantly enhanced student engagement and improved their understanding of Big Data Analytics concepts and techniques. The matic analysis revealed positive aspects such as real-time scoring and leaderboards, but also highlighted challenges including the lack of structured learning and guidance. Solutions proposed by students include additional support mechanisms, a balance between competition and learning, and diverse competition themes. Overall, this study underscores the potential of CBL using Kaggle to transform Big Data Analytics education, while also emphasizing the need for tailored support and refinement of course design. © 2024 IEEE.

关键词： Contrastive Learning

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Identification of Diabetic Retinopathy by Transfer Learning Based Retinal Images 9

Identification of Diabetic Retinopathy by Transfer Learning ...

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9th International Conference on Communication and Electronics Systems, ICCES 2024

作者： Sagili, Sreenivas Reddy Goswami, Chandrashekhar Bharathi, V.C. Ananthi, S. Rani, K. Sathya, R. Rochester Institute Of Technology Department of computer science Lomb Memorial Drive RochesterNY14623 United States Mit School of Computing Mit Art Design and Technology University Department of Computer Science & Engineering Maharashtra Pune India School of Computer Science and Engineering VIT-AP University Andhra Pradesh Amaravati India Advanced Research Centre for Future Networks and Digital Twin Sri Eshwar College of Engineering Tamil Nadu Coimbatore India M. Kumarasamy College of Engineering Department of Information Technology Tamilnadu Karur India Kongunadu College of Engineering and Technology Department of It Tamil Nadu Trichy India

ISBN: (纸本)9798350377972

The human eye is frequently considered to deliver a space into a person's strength because it is only with diabetic retinopathy (DR), a devastating eye illness caused by diabetes mellitus, that one may understand the subject's unprotected surface without invasive operations. There are certain disorders, notably vascular illness, that authority telltale indicators in the eye retina. Microaneurysms (MAs) are primary indicators of diabetic retinopathy (DR), making their detection crucial for an effective screening program that adheres to clinical procedures. Retinal examinations can reveal pathological deviations caused by limited ocular diseases such as arteriosclerosis, diabetes, cardiovascular disease hypertension and stroke. The proposed work introduces image processing algorithms, such as shady object identification, to predict the disorder or improve the contribution frame, thereby improving the perceptibility of vessels in color fundus frames. Following this enhancement, an automated classification algorithm, specifically a Convolutional Neural Network (CNN), is executed. The CNN architecture is designed to efficiently extract features from retinal frames, capturing complex patterns connected with diabetic retinopathy. The trained CNN is then assessed on a separate test condition, with its performance system of measurement-accuracy, specificity, recall, and Fl measure-being reported. © 2024 IEEE.

关键词： Convolutional neural networks

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