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TERNARY ZERO CORRELATION ZONE SEQUENCE SETS WITH PERFECT PERIODIC CORRELATIONS

Telecommunications and Radio engineering (English translation of Elektrosvyaz and Radiotekhnika) 2025年第6期84卷 29-46页

作者： Premalatha, B. Bhatt, T.D. Srikanth, G. CMR College of Engineering & Technology Medchal Hyderabad501401 India CMR Technical Campus Medchal Hyderabad501401 India

A radar sensor network comprises multiple pulse compression radar systems, each transmitting a unique coded waveform from a set of orthogonal waveforms. This approach enhances target echoes, leading to improved performance in target detection, measurement, and recognition. By integrating data from multiple radar sources, the system achieves more accurate and reliable results through the fusion of information from various targets. This paper presents a new approach of constructing the sets of orthogonal ternary zero correlation zone (ZCZ) sequences using Paley’s matrix (type-I). The sequences derived from Paley’s matrix, along with the Hadamard matrix, are used to construct an orthogonal set of sequences, which exhibit perfect periodic auto and cross-correlation properties within the ZCZ. These sequences can be a better choice than pulse compression codes in high resolution radars when multiple radars are employing continuous wave (CW) signals. Multiple-input multiple-output (MIMO) radar, which is a special case of radar sensor network, is used to enhance the direction-finding accuracy, and can also use a set of orthogonal waveforms to increase the spectral efficiency effectively with the available spectrum. Proposed sequences can also be applied to non-coherent pulse compression (NCPC) radars and in many other areas of wireless communications. © 2025 by Begell House, Inc.

关键词： Hadamard matrices

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Design of UWB Antenna with Band Rejection Characteristics Using EBG Structures

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Journal of The Institution of Engineers (India): Series B 2025年第1期106卷 103-111页

作者： Bantupalli, Premalatha Gimmadi, Srikanth Shaik, Abdul Subhani Dept of ECE CMR College of Engineering & Technology Kandlakoya Hyderabad India Dept of ECE CMR Technical Campus Kandlakoya Hyderabad India

In today's fast-evolving communication landscape, the demand for Ultra-wideband (UWB) antennas with band-notching capabilities has surged due to advancements in the field. This study showcases significant progress in UWB antenna technology, offering antennas that are characterized by their reduced weight, compact dimensions, and cost-effectiveness. This paper introduces an Ultra-wideband notch antenna consists of a simple EBG structure and a strategically designed slot to effectively mitigate interference from 5G sub-6and satellite uplink *** proposed design of the antenna combines an inverted π slot, with an Electromagnetic Band Gap (EBG) unit cell to minimize interference from both upper and lower frequency bands. The antenna is made with RT/duroid 5880 material having dimensions 50 × 42 × 1.57 mm3. The frequency range that the antenna can operate in is 2 to 12 GHz. with a notch band (3.3–3.7 GHz) designed to address interference from sub 6 5G signals, as well as an upper notch band (5.9 to 6.9 GHz) intended to reduce interference from satellite uplink communications. EM simulation software CST is used to examine the antenna's performance. This study presents the results obtained. © The Institution of Engineers (India) 2024.

关键词： Cost effectiveness

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An Efficient Mechanism for Automatically Limiting Data Leakage in Multi-cloud Storage Services 15th

An Efficient Mechanism for Automatically Limiting Data Leaka...

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15th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Chintalapudi, S. Rao Kumar, G. Pavan Revathi, B. Prasanthi, Bommireddy Parameswar, Maddela Babu, Ch. Raja Kishore CMR Technical Campus Telangana Hyderabad India CMR Engineering College Telangana Hyderabad India CMR College of Engineering and Technology Hyderabad India

ISBN: (纸本)9783031889912

Recently, a lot of innovative systems have been developed for data storage across various clouds. Since a single point of assault will release all the information, users are provided with some degree for data leakage control when data is distributed among several cloud storage providers (CSPs). Even when using numerous clouds, yet, uncontrolled dispersal of data chunks can result in excessive evidence disclosure. Here we investigate a significant information leakage issue brought on by random data distribution across multiple cloud storage providers. Next, we introduce Data Sim, a multi-cloud data loss conscious storage system. Data Sim seeks to minimize the consumer’s information leakage across various clouds by storing grammatically identical information on the identical cloud. We create a tool to calculate the information leakage depending on these signatures and an approximation algorithm for effectively developing similarity-preserving identities for information chunks depending on Min Hash and Bloom filter. We introduce a clustering-based efficient storage plan formation approach for spreading data chunks over various clouds by low information leakage. Moreover, the characteristics comprise Storage capacity offered by the cloud and Alert Notification while surpassing the permitted storage limit of the cloud. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Sensitive data

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School Sustainable Education Personal Learning Assistant Using Artificial Neural Network 12th

School Sustainable Education Personal Learning Assistant Usi...

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12th International Conference on Frontiers of Intelligent Computing: Theory and Applications, FICTA 2024

作者： Rasheeduddin, Sayyad Sravani Kumar, V. Praveen Kumar, T. Ramesh, L.V. Sivaiah, Borra Bhanu, Sasi CMR Engineering College Telangana Hyderabad India CMR Engineering College Telangana Hyderabad India Department of MBA CMR Technical Campus Telangana Hyderabad India Department of IT CMR Technical Campus Telangana Hyderabad India Department of CSE CMR College of Engineering and Technology Telangana Hyderabad India CMR College of Engineering and Technology Telangana Hyderabad India

ISBN: (纸本)9789819601462

Computer-based systems for knowledge and computation are emerging as important sources of competitive advantage for various industry sectors. Global educational systems and learning procedures are therefore about to undergo a significant digital revolution. In the context of computer education in primary and secondary schools, this research aims to investigate the idea of an intelligent tutoring system (ITS) based on artificial neural networks (ANNs). A learning assistant is one of the elements of an ITS that can help students ask for help whenever they need it, from anywhere. The pilot chatbot prototype is created as part of this study to act as learning aid for Scratch subjects (Scratch is the graphical tool employed to teach schoolchildren fundamentals of programming). Students asked questions to the chatbot using an open-source ANN library and Slack, and the chatbot responded with the desired explanation. The chatbot’s ANN extraction and information retrieval ability was assessed through a two-phase testing procedure. The testing results demonstrated the reasonable accuracy of the ontology model for this kind of learning assistant and indicated that it may be developed further as cloud solutions in the future. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Ability testing

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An Analytical Investigation on Images and Application of Different Methodologies Presenting Significant Challenges in Attaining Reliable Categorization 15th

An Analytical Investigation on Images and Application of Di...

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15th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Laxmaiah, Bagam Bhukya, Shankar Nayak Narasimha, V. Rao, K. Venkateswara Mrunalini, G. Balakrishna, Balineni CMR Technical Campus Telangana Hyderabad India CMR College of Engineering and Technology Telangana Hyderabad India CMR Engineering College Telangana Hyderabad India

ISBN: (纸本)9783031889912

The accelerated progression of computer applications, transitioning from basic data processing to the realm of machine learning, can be attributed to the increased accessibility and abundance of extensive data sets obtained from various sensors and the internet. This study provides evidence that robots have the capacity to acquire self-awareness and evolve through appropriate teaching. The effectiveness of human categorization of photos is contingent upon the utilization of image analysis techniques and the implementation of diverse approaches, which provide inherent challenges. Due to the intricate nature of the task at hand, it has become imperative to implement automation techniques in order to achieve a significant level of precision. The proposed study aims to provide a comparative analysis on the efficacy and accuracy of a number of machine learning algorithms in the context of image categorization. The logistic regression approach, Naive Bayes classifier approach, Support Vector approach, and Random Forest algorithms for classifiers were employed to evaluate the UC Merced dataset. The experimentation began by preprocessing and training of the dataset, which was then followed by the testing phase. At this juncture, the inquiry shifts its focus towards determining the optimal selection algorithm by analyzing the computed accuracies of the evaluated methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Random forests

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Assesment on Homomorphic Algorithm in the Analysis of Multi Blocks File Security and Privacy Access Policy Using Cloud Computing 15th

Assesment on Homomorphic Algorithm in the Analysis of Multi ...

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15th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Reddy, P. Sandhya Lavanya, M. S. S. Lakshmi Saidulu, Golla Sanagala, Siva Skandha Narasimharao, Jonnadula Kumar, Y. Lakshman CMR Engineering College Telangana Hyderabad India CMR College of Engineering and Technology Telangana Hyderabad India CMR Technical Campus Telangana Hyderabad India

ISBN: (纸本)9783031889912

Cloud computing clients as well as suppliers commonly utilize evidence metrics for the purpose of assessment. Determine the selection of services offered across various geographic regions. Cloud computing effectively tackles the fundamental challenges pertaining to privacy, reliability, and access control. The attainment of control holds significant importance inside a cloud computing environment, as it underscores the provision of client access to diverse capabilities offered by the cloud. Numerous widely adopted file encryption methods, such as AES and Blowfish, are currently employed as auxiliary components in cloud encryption devices. We proposed the implementation of a unique trust fund-based availability control mechanism in order to safeguard the cloud ecosystem against potential threats posed by malevolent customers. Before gaining access to cloud resources, this version of the system validates the client’s authorization by considering the customer’s trust and reputation. Additionally, the data is segregated into many blocks for enhanced security. This study offers a comprehensive analysis of the suggested cryptographic method that is based on cloud computing. Additionally, it explores the components that should be prioritized in the hierarchy of fog-cloud architecture to alleviate computational burdens at the network edge, hence meeting the latency demands of the application. The contrast and evaluation illustrate the advantageous and secure nature of the suggested technique. The effectiveness and security of the system remain uncompromised, even with the inclusion of a cipher text evolutionary mechanism to manage crucial updates and delegation revocation. The suggested methodology for dividing various obstacles and implementing an Access Policy can be used to different accessible authorization methods that require modifying the key or revoking the permission. The system exhibits a high level of security and also demonstrates pragmatism in its functionality

关键词： Authorization

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An Advanced Forensic Image Processing Technique for CCTV Footage Augmentation of Corrupted Images 15th

An Advanced Forensic Image Processing Technique for CCTV Foo...

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15th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Murali, Kanthi Bhaskar, Nuthanakanti Saranya, B. Sree Suhasini, T.S. Kirubakaran, S. Gayathri CMR Technical Campus Telangana Hyderabad India CMR Engineering College Telangana Hyderabad India CMR College of Engineering and Technology Telangana Hyderabad India

ISBN: (纸本)9783031889912

Deep learning-based image identification technologies have advanced dramatically subsequently. Investigating crimes has shown to benefit greatly from the use of forensic analysis. By examining tangible evidence, forensic analysis offers proof and fundamental details about the alleged crime. This study focuses on an exciting method for improving CCTV footage’s visual quality to help with criminal case investigations. CCTV is used to gather face data comprising seven distinguishable aspects from a person during the pre-processing stage of face recognition. Deep learning is used for identifying facial features in the gathered dataset after it has been annotated and classified. When at least four features are identified, the image data is interpreted as human, and 81 feature vectors are used to compare the face in detail against user data that has been saved. Machine learning techniques and pure image processing methods are used to address this issue of image enhancement. After analyzing the two aforementioned methods, this study came to the further conclusion that the machine learning strategy yields a more effective outcome. This method can be used for both basic picture filtration and sophisticated forensic image processing. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Image enhancement

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Analysis of Digital Image Processing for the Identification and Detection of Skin Lesion Melanoma Assessment 15th

Analysis of Digital Image Processing for the Identification ...

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15th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Prashanth, Badam Deepak Kumar, B.P. Singh, Sunil Kumar Saimanasa, Mannem Kumar, Anil Upender, T. CMR Technical Campus Telangana Hyderabad India CMR Engineering College Telangana Hyderabad India CMR College of Engineering and Technology Telangana Hyderabad India

ISBN: (纸本)9783031810794

A skin lesion is a strange development of a body component that is located on the skin. Lesion identification at the earliest stages is essential. This is where the melanoma illness is detected. The occurrence of melanoma has increased dramatically in the modern period. Melanoma has the potential to be fatal. It might be utilized to obtain quantitative data regarding a body part lesion in the medical field. Investigating the digital photos of the epidermal lesion on the affected body part is a straightforward method. The extraction of features is a crucial component in this study work that might be utilized to appropriately examine and assess the image. Various photos underwent pre-processing, and characteristics were taken out of them. An additional crucial step in identifying an injury on the body part is image pre-processing. In the initial phases of melanoma diagnosis, we have suggested use the SVM approach to identify the disease. The methodology utilizes the capabilities of the Support Vector Machine Algorithm (SVM) and image processing techniques. The Support Vector Machine algorithm is in employment for the objective of categorization. As the input to the classification algorithm, the characteristics are provided. The support vector classification is the classifier that needs to be applied. Python is the method employed, and the confusion matrix is employed to generate the findings for improved precision. The paper compares several precision functions and provides an overview of the technique used. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Photointerpretation

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Relevant Product Recommendation for Social Network Using Supervised Learning Algorithm Classifier 15th

Relevant Product Recommendation for Social Network Using Sup...

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15th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Gangaram, Goda Ranjith Reddy, K. Sree Saranya, B. Ravi, C.N. Gurumoorthi, E. Kirubakaran, S. CMR Technical Campus Telangana Hyderabad India CMR Engineering College Telangana Hyderabad India CMR College of Engineering and Technology Telangana Hyderabad India

ISBN: (纸本)9783031810824

Conventional techniques have produced less accurate and lower-quality search results. In order to improve prediction quality, this topic is addressed and a suggested strategy utilizing the supervised learning method is given. A unique paradigm for relevant product suggestions in social networks is presented in this study. This strategy's main objective is to let computers learn on their own, without human help, and then adjust operations as needed. In order to reduce noise, social inputs for suggested method are the first preprocessed. After that, feature extraction is done using an information-based Fisher discriminant approach. The features are then selected from the obtained ones employing the process. Subsequently, product is proposed by employing the supervised learning method to anticipate these clusters. Lastly, exception outputs were assessed, performance measurement looked at, and comparison with traditional approaches were done to confirm the efficacy of the suggested system. The recommended strategy gets a 90.15% positive score out of 3000 evaluations. The analysis shows that the recommended approach is more successful in producing better outcomes for relevant product recommendations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Supervised learning

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Enhancing the Protocol for Prolonged Node Longevity in WSNs via Low Energy Adaptive Hierarchy 15th

Enhancing the Protocol for Prolonged Node Longevity in WSNs ...

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15th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Revathi, B. Prasanthi, Bommireddy Sruthi, Pinamala Bhaskar, T. Bhaskar, Nuthanakanti Sudhamalla, Mallesh CMR Engineering College Telangana Hyderabad India CMR College of Engineering and Technology Telangana Hyderabad India CMR Technical Campus Telangana Hyderabad India

ISBN: (纸本)9783031810855

Wireless Sensor Networks (WSN) consist of a diverse array of cost-effective and energy-efficient network sensors employed for environmental sensing, data collection, data processing, and transmission of data that has been processed to a central base station (BS). Furthermore, the disparate distribution of cluster heads in this particular network category is accompanied by issues of insufficient power with a limited lifetime. The adoption of the This issue is efficiently addressed by the LEACH (Low Energy Adaptive Clustering Hierarchy) protocol, which ensures a fair distribution of resources cluster leaders throughout the network, ultimately leading to a decrease in energy consumption. The findings obtained during the simulations demonstrate that the enhanced technique effectively reduces power consumption and enhances the longevity throughout the network. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Sorting

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