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14th IEEE Global Engineering Education Conference, EDUCON 2023

作者： Gottipati, Swapna Shim, Kyong Jin Datta, Subhajit School of Computing and Information Systems Singapore Management University Singapore Heritage Institute of Technology Department of Computer Science and Engineering Kolkata India

The aim of technical education is to design a career-based curriculum that imparts a set of skills to students and enable them to contribute to a nation's economic progress. With their multifarious uses, information systems (IS) lie at the heart of modern economies. IS curricula offer several tracks for students to pursue career paths based on their interests and opportunities. To offer students an opportunity to apply the knowledge they glean from classroom instructions on real-world problems, capstone projects are essential elements in most, if not all, IS programs. As IS programs increasingly offer a wider range of career paths for students, the design and delivery of such capstone projects present a set of unique challenges. In this paper, we examine the set of challenges and share our experience from designing and delivering a career track-based capstone course for the first time at a large university. Feedback from students and faculty supervisors indicates that the course was able to meet its learning objectives to a notable extent and offered important pointers to future improvements in the course design. © 2023 IEEE.

关键词： information systems

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A connectivity index based on adjacent vertices in cubic fuzzy graph with an application

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Journal of Intelligent and Fuzzy Systems 2024年第4期46卷 11025-11040页

作者： Guan, Hao Sadati, Seyed Hossein Talebi, Ali Asghar Shafi, Jana Khan, Aysha Institute of Computing Science and Technology Guangzhou University Guangzhou China School of Computer Science of Information Technology Qiannan Normal University for Nationalities Duyun China Department of Mathematics University of Mazandaran Babolsar Iran Department of Computer Engineering and Information College of Engineering in Wadi Alddawasir Prince Sattam Bin Abdulaziz University Wadi Alddawasir Saudi Arabia Department of Mathematics Prince Sattam Bin Abdulaziz University Al-Kharj Saudi Arabia

A cubic fuzzy graph is a type of fuzzy graph that simultaneously supports two different fuzzy memberships. The study of connectivity in cubic fuzzy graph is an interesting and challenging topic. This research generalized the neighborhood connectivity index in a cubic fuzzy graph with the aim of investigating the connection status of nodes with respect to adjacent vertices. In this survey, the neighborhood connectivity index was introduced in the form of two numerical and distance values. Some characteristics of the neighborhood connectivity index were investigated in cubic fuzzy cycles, saturated cubic fuzzy cycle, complete cubic fuzzy graph and complementary cubic fuzzy graph. The method of constructing a cubic fuzzy graph with arbitrary neighborhood connectivity index was the other point in this research. The results showed that the neighborhood connectivity index depends on the potential of nodes and the number of neighboring nodes. This research was conducted on the Central Bank's data regarding inter-bank relations and its results were compared in terms of neighborhood connectivity index. © 2024-IOS Press. All rights reserved.

关键词： Graph theory

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Comparing Time Series Assist Vector Machines and Recurrent Neural Networks for Hyper Spectral Image Popularity 5th

Comparing Time Series Assist Vector Machines and Recurrent N...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Goswami, Shubhashish Pasha, Afroz Mishra, Awakash Krishnamoorthy, Ramkumar Department of Computer Science & Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India

ISBN: (纸本)9789819780426

This paper examines the overall performance of two system mastering models, Time series help Vector Machines (SVMs) and Recurrent Neural Networks (RNNs), on classification of Hyper Spectral photographs (HSIs). The fashions are in comparison based totally on their recognition accuracy which includes the time requirements to build fashions. The paper additionally evaluates two varieties of preprocessing techniques: minimum Redundancy maximum Relevancy (MRMR) and precept aspect evaluation (PCA). The effects of the experiments highlight that SVMs and RNNs perform considerably distinct for HSI class and that counting on one version simplest may lead to exclusive type performance. Moreover, the experiments show that with increasing complexity, the quantity of time required to assemble the RNNs will increase significantly. The comparisons in the paper allow further exploration in the discipline and help the choice of the high-quality model with the aid of capacity practitioners and developers. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Recurrent neural networks

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Implementing Encryption Algorithms for the Protection of Wireless Networks 5th

Implementing Encryption Algorithms for the Protection of Wir...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Ahmad, Naseem Madhura, K. Agarwal, Trapty Zaidi, Taskeen Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India

ISBN: (纸本)9789819780426

The use of encryption algorithms is more and more turning into a crucial issue of defensive wireless networks. Encryption algorithms may be used to cozy facts that is transferred over a Wi-Fi network while also presenting authentication and integrity protocols for the systems connected to the network. This paper discusses the significance of enforcing encryption algorithms for the safety of a wireless community. It describes the distinct encryption algorithms and protocols which are available, and the criteria for selecting the proper algorithm for exclusive varieties of Wi-Fi networks. It additionally provides unique implementation eventualities based totally on numerous sorts of Wi-Fi community structure in addition to the vast security threats in Wi-Fi networks that may be averted by imposing encryption algorithms. Finally, this paper offers guidelines on selecting and imposing the perfect encryption set of rules for safety of wireless networks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Encryption algorithms

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Fine-Grained Zero-Shot Object Detection via Semantic Decoupling 24

Fine-Grained Zero-Shot Object Detection via Semantic Decoupl...

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8th International Conference on Computer science and Artificial Intelligence, CSAI 2024

作者： Duan, Lijuan Zhang, Zichen Gong, Zhi Beijing Key Laboratory of Trusted Computing Beijing University of Technology Beijing China School of Computer Science Beijing University of Technology Beijing China National Engineering Laboratory for Key Technologies of Information Security Level Protection Beijing China

ISBN: (纸本)9798400718182

Recent deep learning models have advanced object detection capabilities, but their reliance on labeled data limits scalability. Fine-grained zero-shot detection remains challenging due to the need to generalize to unseen classes and distinguish subtle features. To address this, we propose Fine-Grained Zero-Shot Object Detection via Semantic Decoupling (ZSD-SD). Our approach introduces a semantic decoupling module to separate visual features into semantic-related and semantic-unrelated components, facilitating alignment between visual and semantic spaces. A semantic-visual learning module further decouples these features, enhancing visual representations relevant to external semantic knowledge. This semantic-related representation significantly improves zero-shot performance. Experiments on two fine-grained object detection datasets demonstrate that ZSD-SD achieves state-of-the-art results. © 2024 Copyright held by the owner/author(s).

关键词： Zero-shot learning

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Optimal Visualization of Hyper Spectral Time Series Algorithms via Graphical Representations 5th

Optimal Visualization of Hyper Spectral Time Series Algorith...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Agarwal, Trapty Karthikeyan, M.P. Adhikari, Manoj S. Ulla, Mohammed Mujeer Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India Department of Computer Science & Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India

ISBN: (纸本)9789819780426

This technical summary describes how using graphical representations can allow for the best visualization of hyper spectral time series algorithms. Hyper spectral time collection algorithms correctly analyze temporal information from satellite- or plane-borne sensors, for instance, to offer an in-intensity expertise of an environment or system. But, such evaluation can regularly be difficult to realize without graphical aid. This research gives a method for correctly visualizing hyper spectral time series algorithms using graphical representations, consisting of line graphs and tree diagrams. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Visualization

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Hyper Spectral Image Analysis Integrating Fuzzy C-Means Clustering and Feature Selection 5th

Hyper Spectral Image Analysis Integrating Fuzzy C-Means Clus...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Agarwal, Trapty Rengarajan Goyal, Rohit Khan, N. Zafar Ali Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India Department of Computer Science & Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India

ISBN: (纸本)9789819780426

Hyper spectral picture evaluation is an effective tool for analyzing large volumes of excessive-dimensional facts. In this paper, a brand new method to hyper spectral photo analysis is provided that integrates fuzzy C-means clustering and function choice. The proposed approach permits for significant quantification of the exclusive additives within a hyper spectral image and allows for the identification of key spectral functions. Additionally, the fuzzy C-way clustering approach is used to identify awesome clusters within the photograph, supplying a useful method for studying complicated datasets. The characteristic choice technique facilitates to further lessen the data set and to achieve the maximum meaningful capabilities for further evaluation. The overall performance of the proposed technique is evaluated via the use of an actual-international hyper spectral photo, and the effects exhibit the effectiveness of the proposed technique for hyper-spectral photograph analysis. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Image analysis

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An Evaluation of Hashing and Other Applied Cryptography Algorithms 5th

An Evaluation of Hashing and Other Applied Cryptography Algo...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Mishra, Awakash Haripriya Sharma, Apurva Thomas, Jobin S. Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bengaluru India Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India

ISBN: (纸本)9789819780426

In the modern digital world, cryptography is critical in protecting personal statistics. Most of the cryptography algorithms used to ease data, hashing, and other implemented cryptography algorithms are extensively used. Hashing refers to transforming plaintext or every other form of statistics into unreadable ciphertext. This type of encryption is used primarily to store passwords, authentication records, and other touchy records. Other applied cryptography algorithms include symmetric encryption, uneven encryption, and key exchanges. In this paper, an assessment of hashing and different implemented cryptography algorithms is conducted. The evaluation will be conscious of each of those algorithms’ distinctive traits, strengths, weaknesses, and safety concerns. The review also appears in the scenarios wherein one-of-a-kind algorithms can be carried out. It is followed by comparing the one-of-a-kind algorithms about their overall performance, protection, and comfort. Numerous pointers are also discussed regarding the application of these algorithms. Finally, the paper concludes with a standard assessment of the multiple algorithms and their suitability in one-of-a-kind contexts. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Encryption algorithms

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Fog computing Security Challenges and Open Issues: A Short Survey 7

Fog Computing Security Challenges and Open Issues: A Short S...

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7th IET Smart Cities Symposium, SCS 2023

作者： Altamimi, Shahad Al-Haija, Qasem Abu Al-Fayoumi, Mustafa Dept. of Cybersecurity King Hussein School of Computing Sciences Prince Sumaya University for Technology Jordan Dept. of Cybersecurity Faculty of Computer & Information Technology Jordan University of Science and Technology Jordan

ISBN: (纸本)9781839539831

Fog computing (FC) is viewed as an advancement of Cloud computing (CC), with different properties such as location sensitivity, wireless connection, and geographical accessibility to produce new security concerns and issues in cloud security that have not been thoroughly investigated. It also extends CC to forward this message to the network's edge. It defines a decentralized processing model architecture between data-generating hardware and the cloud. FC systems can generate massive amounts of data. Also, it provides CC toward the network's edge. FC technology already poses a threat to data and service privacy and security. Due to its geo-distribution on a grand scale, mobility, and heterogeneity, the current privacy and security mechanisms of CC cannot apply automatically to FC. This paper will discuss and concentrate on the security challenges facing FC and thus will compare surveys focusing on security challenges. © The Institution of Engineering & technology 2023.

关键词： Fog computing

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Optimal Location Based Fuzzy Logic Model for Underwater Communications 5th

Optimal Location Based Fuzzy Logic Model for Underwater Comm...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Agrawal, Jaishree Kalaiarasan, C. Agarwal, Trapty Ojha, Ananta Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India

ISBN: (纸本)9789819780426

The most beneficial location based totally fuzzy good judgment model for Underwater Communications is an advanced and innovative solution for conditions consisting of underwater navigation and verbal exchange, which requires cautious attention of various environmental factors. This version combines 3 special procedures for finding underwater items: the bushy C-method (FCM) technique for clustering, a fuzzy mapping method for locating and tracking gadgets, and a fuzzy common sense method for controlling. The FCM approach is used to create wonderful clusters of objects primarily based on attributes such as salinity, water temperature, and so forth. After which the bushy mapping technique is used to decide the nearest cluster to an object. Sooner or later, the bushy good judgment technique uses input from those clusters to generate top-rated navigation paths for the item being tracked. All 3 elements of this approach paintings together to allow more than one gadgets being tracked on the same time, and it can also make certain the item is constantly headed in the direction of the most fulfilling navigation path. This version gives stepped forward efficiencies in underwater communications and can help provide real-time situational recognition. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Mapping

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