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2nd International Conference on Emerging Trends in information technology and engineering, ic-ETITE 2024

作者： Supriya, K. Anitha, A. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350328202

The advancements in technology help in analyzing and predicting the disease of human life using automation. Out of various technologies, Machine Learning (ML) and Deep learning (DL) provide some promising results to help humankind. Automated technologies help improve the prediction process of the healthcare system, especially in carcinoma detection based on past information. Thus, the proposed model made a survival analysis of the patients who are affected by bladder cancer (BC) based on their past health records. The tumor in the urinary bladder indicates that cancer among patients, when not treated can be spread to the other parts of the human body and cause death. However, the health records provide some linear combinations of the data to analyze the survival rate on treatments such as Placebo and Thiotepa. Thus, the proposed work utilized DeepMLPSurv and CoxPH survival model to make an analysis on the tumour recurrence and predicts the survival rate among the bladder cancer patients. © 2024 IEEE.

关键词： Diseases

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Game-Hypothetical Methodology for Continuous Undertaking Planning in Distributed computing Conditions

Game-Hypothetical Methodology for Continuous Undertaking Pla...

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2024 International Conference on Computer Communication, Networks and information science, CCNIS 2024

作者： Gautam, Puneet Harrisburg University of Science and Technology Information Systems Engineering HarrisburgPA United States

ISBN: (纸本)9798331507046

Cloud computing, with its fundamental virtualization technique, offers a flexible and powerful platform for deploying various applications. Real-time task scheduling in cloud environments, however, presents significant challenges due to timing constraints and the need for efficient resource allocation. This paper proposes a game-theoretic method for real-time task scheduling, leveraging both cooperative and non- cooperative game models. A systematic framework is developed, considering tasks as players and virtual machines as strategies. Through extensive experimental analysis, the effectiveness of the proposed approach is demonstrated, showing superior perfor- mance in terms of completion time and waiting time compared to traditional scheduling methods. Additionally, future research directions are outlined, including the integration of additional evaluation metrics to enhance scheduling efficiency in cloud computing systems further. © 2024 IEEE.

关键词： Cloud platforms

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Multi-View Graph Embedding Learning for Image Co-Segmentation and Co-Localization

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IEEE Transactions on Circuits and systems for Video technology 2024年第6期34卷 4942-4956页

作者： Huang, Aiping Li, Lijian Zhang, Le Niu, Yuzhen Zhao, Tiesong Lin, Chia-Wen Fuzhou University Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information College of Physics and Information Engineering Fuzhou350108 China Fuzhou University Fujian Key Laboratory of Network Computing and Intelligent Information Processing College of Computer and Data Science Fuzhou350108 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Fuzhou University Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information College of Physics and Information Engineering The Fujian Science and Technology Innovation Laboratory for Optoelectronic Information Fuzhou350108 China Institute of Communications Engineering National Tsing Hua University Department of Electrical Engineering Hsinchu30013 Taiwan

Image co-segmentation and co-localization exploit inter-image information to identify and extract foreground objects with a batch mode. However, they remain challenging when confronted with large object variations or complex backgrounds. This paper proposes a multi-view graph embedding (MV-Gem) learning scheme which integrates diversity, robustness and discernibility of object features to alleviate this phenomenon. To encourage the diversity, the deep co-information containing both low-layer general representations and high-layer semantic information is generated to form a multi-view feature pool for comprehensive co-object description. To enhance the robustness, a multi-view adaptive weighted learning is formulated to fuse the deep co-information for feature complementation. To ensure the discernibility, the graph embedding and sparse constraint are embedded into the fusion formulation for feature selection. The former aims to inherit important structures from multiple views, and the latter further selects important features to restrain irrelevant backgrounds. With these techniques, MV-Gem gradually recovers all co-objects through optimization iterations. Extensive experimental results on real-world datasets demonstrate that MV-Gem is capable of locating and delineating co-objects in an image group. © 1991-2012 IEEE.

关键词： Semantics

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Firepower distribution method of anti-ship missile based on coupled path planning

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Journal of systems engineering and Electronics 2022年第4期33卷 1010-1024页

作者： LIU Gang AN Zhibiao LAO Songyang LI Wu School of Information Science and Engineering Hunan Institute of Science and TechnologyYueyang 414006China College of Systems Engineering National University of Defense TechnologyChangsha 410000China

Anti-ship missile coordinated attack mission planning is a complex multi-objective optimization problem with multiple combinations of platforms, strong decision-making constraints,and tightly coupled links. To avoid the coupling disorder between path planning and firepower distribution and improve the efficiency of coordinated attack mission planning, a firepower distribution model under the conditions of path planning is established from the perspective of decoupling optimization and the algorithm is implemented. First, we establish reference coordinate system of firepower distribution to clarify the reference direction of firepower distribution and divide the area of firepower distribution;then, we construct an index table of membership of firepower distribution to obtain alternative firepower distribution plans;finally, the fitness function of firepower distribution is established based on damage income, missile loss,ratio of efficiency and cost of firepower distribution, and the mean square deviation of the number of missiles used, and the alternatives are sorted to obtain the optimal firepower distribution plan. According to two simulation experiments, the method in this paper can effectively solve the many-to-many firepower distribution problem of coupled path planning. Under the premise of ensuring that no path crossing occurs, the optimal global solution can be obtained, and the operability and timeliness are good.

关键词： anti-ship missile path planning firepower distribution cooperation weapon-target assignment(WTA) coupled

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A Hybrid Approach to Validate and Retrieve Fingerprint Image for Authenticating Database Sensitive information Access and to Verify Some of Topological Multi-Granular Rough Sets Properties on Authenticated Database Fields 2

A Hybrid Approach to Validate and Retrieve Fingerprint Image...

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2nd International Conference on Emerging Trends in information technology and engineering, ic-ETITE 2024

作者： Raghavan, R. John Singh, K. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350328202

Content based image retrieval has already begun to turn into an intriguing and exceptionally needed field to meet with the client prerequisite. Fingerprint approvals likewise have become a fascinating field to principally uphold the confirmation framework. Notwithstanding foundations regulating guaranteed about information straightforwardly, affiliations are also obliging them to examine the fingerprint endorsement. Despite establishments overseeing ensured about data, directly associations are similarly obliging them to research the fingerprint check. Organizations and foundations both are typically utilizing the idea of fingerprint for the participation and presence reason. Nevertheless, establishments presently managing secured information as like institutes and additionally going along with them to investigate the fingerprint authentication. More than this usual action there are some particular applications where the authentication would be considerable to help the application than using a traditional pattern of password. We proposed a fingerprint authentication system for the scientific based industry database access system. We removed the noise if any found in the input fingerprint using anisotropic Gauss filtering. The noise free fingerprint image is not further passed to the binarization phase as the need of binarization and some form of the drawback of binarization is replaced with a thinning algorithm. The thinned fingerprint image is followed by the matching process and once it is matched, then only the sensitive and highly confidential information are allowed to access from the database. The testing is done using OpenCV and FVC 2004 dataset to assess the projected retrieval method. Further the matched fingerprints are used to prove some of the internal structure properties of multi-granular rough sets (MGRS) on authenticated database fields. The accuracy obtained in this hybrid approach is found to be more satisfactory and hence the security towards acce

关键词： Database systems

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Enhanced Traffic Management in IoT-Integrated Internet of Vehicles (IoV) with Optimized Routing and Deep Learning Algorithm 5th

Enhanced Traffic Management in IoT-Integrated Internet of Ve...

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5th International Conference on Advances in Distributed Computing and Machine Learning, ICADCML 2024

作者： Sahoo, Arundhati Tripathy, Asis Kumar School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9789819735228

The integration of the Internet of Things (IoT) into vehicular networks has paved the way for the exciting development of the Internet of Vehicles (IoV) within Intelligent Transportation systems (ITS). These breakthroughs bring about enhancements in urban transportation services, including improved quality and interaction, reduced costs, more efficient resource utilization, and enhanced traffic management capabilities. The incorporation of IoV into transportation has the potential to address various traffic-related challenges in smart cities. Nevertheless, optimizing routing and monitoring network traffic presents significant challenges, primarily due to limited node-to-node communication capabilities. To tackle these problems, this study proposes the BiLSTM-GreedyNet, which combines the Improved Greedy Perimeter Stateless Routing Algorithm with the Bi-LSTM neural network technology in a 5G network environment. The system delivers impressive results, as evidenced by simulations in MATLAB, boasting a remarkable 98.22% accuracy rate, a low 34.2 MJ energy consumption, and a high Packet Delivery Ratio (PDR) of 91%, all tested with a network of 100 nodes. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Internet of things

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Face Recognition Based Attendance Management System Using Deep Learning Method 2

Face Recognition Based Attendance Management System Using De...

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2nd International Conference on Emerging Trends in information technology and engineering, ic-ETITE 2024

作者： Angulakshmi, M. Susithra, V. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (数字)9798350328202

ISBN: (纸本)9798350328202

Deep learning and transfer learning are extremely important in the internet sector and the health care industry. Face recognition technology is essential in practically every industry in our digital age. Several improvements have been made to automatic facial recognition (AFR) technology in an ever-changing world. Managing the daily student attendance system is made simple with Smart attendance with Real-Time Face Recognition. In the proposed method, Images of the students in class are used to construct a dataset. Both Face detection and recognition are performed using the Multitask Convolution Neural Network algorithm. The data will be uploaded after the face is recognition. The proposed method compared with Haar Cascade Convolution Neural Network Classification method and other few methods. The proposed method produced better resultcompared to other methods © 2024 IEEE.

关键词： Students

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Efficient 3D Hilbert Curve Encoding and Decoding Algorithms

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Chinese Journal of Electronics 2022年第2期31卷 277-284页

作者： JIA Lianyin LIANG Binbin LI Mengjuan LIU Yong CHEN Yinong DING Jiaman Faculty of Information Engineering and Automation Kunming University of Science and Technology Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and Technology Library Yunnan Normal University School of Information Science and Engineering Guangxi University for Nationalities School of Computing Informatics and Decision Systems Arizona State University

Hilbert curve describes a one-to-one mapping between multidimensional space and 1 D *** traditional 3D Hilbert encoding and decoding algorithms work on order-wise manner and are not aware of the difference between different input data and spend equivalent computing costs on them, thus resulting in a low efficiency. To solve this problem, in this paper we design efficient 3D state views for fast encoding and decoding. Based on the state views designed, a new encoding algorithm(JFK-3HE) and a new decoding algorithm(JFK-3HD) are proposed. JFK-3HE and JFK-3HD can avoid executing iteratively encoding or decoding each order by skipping the first 0 s in input data, thus decreasing the complexity and improving the efficiency. Experimental results show that JFK-3HE and JFK-3HD outperform the state-of-the-arts algorithms for both uniform and skew-distributed data.

关键词： order-wise manner multidimensional space encoding state-of-the-arts algorithms encoding algorithm parallel algorithms JFK-3HE statistical distributions decoding solid modelling design efficient 3D JFK-3HD traditional 3D Hilbert encoding equivalent computing costs different input data decoding algorithm Hilbert curve state views iterative methods

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Enhancing User Authentication with a Secure Human-Computable Password Scheme 2

Enhancing User Authentication with a Secure Human-Computable...

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2nd International Conference on Emerging Trends in information technology and engineering, ic-ETITE 2024

作者： Ayeswarya, S. John Singh, K. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350328202

Authentication in the digital world has become a challenging and difficult task. The username-password combination is no longer reliable and the tools that support authentication mechanism are all breakable. In addition to authentication, to avoid bots, CAPTCHA is used which increases the complexity of the system. Thus the research is going towards making use of human brain which is so unique and powerful in the authentication process. This will also eliminate the need for CAPTCHA since human is computing the password. To make it feasible, the function that is computed by the human should be simple enough. The existing method trusts the computer to store the public images and if there is a key logger installed in the system, the adversary will be able to get the password. This again tends to be a fixed password. Instead, if it is based on a challenge from the server, the password will be dynamic and secure. In this paper a human computable password protocol is suggested. The experimental results prove that the proposed technique is efficient and is less prone to attacks. © 2024 IEEE.

关键词： Authentication

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Two-dimension high efficiency beam steering based on liquid crystal polarization gratings

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Optics Express 2025年第10期33卷 21425-21440页

作者： Li, Zifan Yu, Bijun Gong, Junhao Liu, Yutong Fan, Lina Gao, Xin Yin, Jiahang Ding, Tongshan Zhang, Dawei Wang, Jun Hong, Ruijin Mao, Hongmin Lu, Huanjun Cao, Zhaoliang Key Laboratory of Intelligent Optoelectronic Devices and Chips of Jiangsu Higher Education Institutions School of Physical Science and Technology Suzhou University of Science and Technology Suzhou215009 China Advanced Technology Research Institute of Taihu Photon Center School of Physical Science and Technology Suzhou University of Science and Technology Suzhou215009 China School of Optoelectronic Information and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China School of Electronics and Information Engineering Suzhou University of Science and Technology Jiangsu Suzhou215009 China

Cascaded liquid crystal polarization grating (LCPG) structure is commonly used to realize two-dimension large angle optical beam steering. In this architecture, different LCPGs have different incident angles. As a liquid crystal half-wave plate (LC HWP) is placed in front of the LCPG to control steering direction, the different incident angles will affect the phase modulation of LC HWP and then, decrease the steering efficiency. In this paper, the steering efficiency of cascaded LCPGs under tilt incidence is considered and a compensation method is proposed to increase the steering efficiency. A simple analysis model is established to calculate the steering efficiency of cascaded LCPG structure for tilt incidence with arbitrary direction. Further, the effect of tilt incidence on the phase modulation of LC HWP is compensated and a simple formula is given to compute the compensation voltage. A validation experiment is performed to verify the proposed method. All the simulated and experimental results indicate that the steering efficiency of cascaded LCPGs can be improved for two-dimension beam scanning. This work is helpful for high efficiency beam steering based on cascaded LCPGs. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Bragg gratings

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