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2020 IEEE International Conference on Computing, Power and Communication Technologies, GUCON 2020

作者： Yadav, Savita Chakraborty, Pinaki Netaji Subhas University of Technology Department of Computer Science and Engineering New Delhi110078 India

ISBN: (数字)9781728150703

ISBN: (纸本)9781728150703

Personal computers and smartphones are now used by people belonging to different age groups and professions, and for different purposes. Human-computer interaction is a sub-discipline of computer science that studies how users interact with these devices and use the knowledge to design efficient user interfaces. In this tutorial article, we discuss the fundamentals of human-computer interaction and its relevance. We discuss the characteristic features of window-based user interface and explain why it is more popular than other types of user interfaces. We conduct an experiment to determine the ease of use of various widgets used in window-based user interfaces. Results of ANOVA show that the time taken by users to use different types of widgets vary significantly (mathrm{P} © 2020 IEEE.

关键词： User interfaces

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A robust approach to detect video-based attacks to enhance security

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International Journal of Innovative Computing and Applications 2019年第3-4期10卷 175-184页

作者： Arora, Shefali Bhatia, M.P.S. Department of Computer Engineering Netaji Subhas Institute of Technology Delhi India

Face authentication has become widespread on smart devices and in various applications these days. Real time detection of human faces in video surveillance systems is challenging due to variations in expression and background conditions. Thus, precise detection of spoofed faces is important to make such security systems robust against potential attacks. Several deep learning-based techniques involving the use of convolutional neural networks have proven to be excellent in detection of spoofed faces. In this paper, we have proposed the combined use of spatial and temporal information from facial images using CNN and long short-term memory networks. We have tested the approach on Idiap Replay Attack benchmark and compared the results with the application of pre-trained models like InceptionV3, VGGNet and ResNet models to detect replay attacks during video surveillance. Our approach proves to be robust and more efficient for detection of security breaches in real time situations. © 2019 Inderscience Enterprises Ltd.

关键词： Security systems

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An Energy Efficient Artificial Neural Network based Clustering Protocol for Wireless Sensor Network

An Energy Efficient Artificial Neural Network based Clusteri...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Rajanish Kumar Kaushal Sourabh Tiwari Laxmi Piyush Charan K Ramesh Chandra Rachit Manchanda Department of Electrical Engineering Chandigarh University Mohali Punjab India Department of CSE Chandigarh University Mohali Punjab India Department of ECE Netaji Subhas Institute of Technology Bihta Patna Bihar India Department of ECE Manav Rachna University Faridabad Haryana India Department of ECE Vishnu Institute of Technology Kovvada Andhra Pradesh India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

Wireless sensor nodes are equipped with compact batteries that supply the necessary energy for a several operational tasks in a wireless sensor network (WSNs). During the execution of these tasks, significant power is depleted from the sensor nodes (SNs). Nonetheless, given the restricted battery capacity of these SNs, they eventually become depleted, leading to the failure of individual nodes and compromising the integrity of the entire network. An essential aspect of addressing the challenge of energy depletion is the choice of the most suitable cluster head (CH). In this research paper, we proposed a model that employs an Artificial Neural Network (ANN) to designate a single node within each cluster as the $\mathbf{C H}$. This approach has resulted in the development of an energy-efficient clustering protocol, referred to as the Energy-Efficient Artificial Neural Network-Based Clustering Protocol (EEANNCP), tailored specifically for WSNs. Through extensive simulations, we have demonstrated that our proposed approach substantially enhances energy conservation and extends the network’s lifespan.

关键词： Wireless communication Wireless sensor networks Protocols Clustering algorithms Artificial neural networks Energy efficiency Stability analysis Batteries Sensors Internet of Things

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Photon orbits and phase transitions in Kiselev-AdS black holes from gravity

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The European Physical Journal C 2024年第8期84卷 1-13页

作者： Sood, Ashima Kumar, Arun Singh, J. K. Ghosh, Sushant G. Centre for Theoretical Physics Jamia Millia Islamia New Delhi India Department of Mathematics Netaji Subhas University of Technology New Delhi India Institute for Theoretical Physics and Cosmology Zhejiang University of Technology Hangzhou China Astrophysics and Cosmology Research Unit School of Mathematics Statistics and Computer Science University of KwaZulu-Natal Durban South Africa

The acceleration observed in cosmological expansion is often attributed to negative pressure, potentially arising from quintessence. We explore the relationship between the photon orbit radius and the phase transition of spherical AdS black holes in f(R, T) gravity influenced by quintessence dark energy, specifically Kiselev-AdS black holes in f(R, T) gravity. We are treating the negative cosmological constant $$\Lambda $$ as the system’s pressure to examine the impact of the state parameter $$\omega $$ and the f(R, T) gravity parameter $$\gamma $$ . Interestingly, Kiselev-AdS black holes within the f(R, T) gravity framework exhibit a van der Waals-like phase transition. In contrast, these black holes display a Hawking–Page-like phase transition in general relativity. We demonstrate that below the critical point, the black hole undergoes a first-order vdW-like phase transition, with $$r_{ps}$$ and $$u_{ps}$$ serving as order parameters exhibiting a critical exponent of 1/2, similar to ordinary thermal systems. It suggests that $$r_{ps}$$ and $$u_{ps}$$ can serve as order parameters in characterizing black hole phase transitions, hinting at a potentially universal gravitational relationship near critical points within black hole thermodynamic systems. Investigating the correlation between photon sphere radius and thermodynamic phase transitions provides a valuable means of distinguishing between different gravity theory models, ultimately shedding light on the nature of dark energy. Finally, as $$\gamma $$ tends towards zero, our results precisely align with those of Kiselev-AdS black holes.

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Memristor Based Oscillator

Memristor Based Oscillator

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2019 International Conference on Computing, Power and Communication Technologies, GUCON 2019

作者： Anand, Ankit Aggarwal, Bhawna Singh, Kunwar Netaji Subhas Institute of Technology Department of Electronics and Communication Engineering New Delhi India

ISBN: (纸本)9789353510985

In this paper memristor based RC phase shift oscillator and Colpitts oscillator have been proposed. In the proposed oscillators resistors and inductors present in the conventional circuits have been replaced by memristors. Memristor characteristics like nano scale dimension, low power consumption and electronic programmability help in achieving high performance oscillators. LTspice has been used to simulate the conventional and proposed circuits. These simulaton results show that RC phase shift and Colpitts oscillators can be tuned in the frequency range of 3 to5 kHz and 52 to 58 kHz respectively, if controlling voltage is changed from 0.3 to 1.8 V. © 2019 Galgotias University.

关键词： Memristors

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Image Analysis for E-Healthcare Systems using Multi-Biometric Recognition Model

Image Analysis for E-Healthcare Systems using Multi-Biometri...

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

作者： Naman Bansal Pranav Arora Deepak Kumar Sharma Koyel Datta Gupta Chandana Kuntala Department of Instrumentation and Control Engineering Netaji Subhas Institute of Technology University of Delhi New Delhi India Department of Information Technology Indira Gandhi Delhi Technical University for Women New Delhi India Department of Computer Science and Engineering Maharaja Surajmal Institute of Technology New Delhi India Department of Information Technology Indira Gandhi Delhi Technical University for Women New Delhi India

With the dawn of e-Healthcare systems, Medical Record Management has become an important research problem. The storage and organization of medical records have made relatively little progress in a world of constantly emerging new technologies and continuous innovation. Many hospitals keep the records on paper, which raises many challenges, including but not limited to a significant amount of time for searching and retrieving a specific record, high maintenance costs, lack of backup, and limited security. Although the inclusion of technology has made this task far more efficient and secure, there is still much that can be done to improve it. This paper proposes a double index-based approach for mapping medical records directly to a patient’s biometrics which would take advantage of the uniqueness of biometrics to identify a patient. The proposed multi-biometric model achieves an accuracy of 97% and an F 1 score of 0.9814.

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Photon orbits and phase transition for Letelier AdS black holes immersed in perfect fluid dark matter

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Chinese Physics C 2024年第6期48卷 247-259页

作者： Ashima Sood Md Sabir Ali J.K.Singh Sushant G.Ghosh Department of Mathematics Netaji Subhas University of TechnologyNew Delhi-110078India Centre for Theoretical Physics Jamia Millia IslamiaNew Delhi 110025India Department of Physics Mahishadal Raj CollegePurba MedinipurWest Bengal721628India Institute of Theoretical Physics&Research Center of Gravitation Lanzhou UniversityLanzhou 730000China Key Laboratory of Quantum Theory and Applications of MoE Lanzhou UniversityLanzhou 730000China Lanzhou Center for Theoretical Physics&Key Laboratory of Theoretical Physics of Gansu Province Lanzhou UniversityLanzhou 730000China Astrophysics and Cosmology Research Unit School of MathematicsStatistics and Computer ScienceUniversity of KwaZulu-NatalPrivate Bag X54001Durban 4000South Africa

We obtain an exact solution for spherically symmetric Letelier AdS black holes immersed in perfect fluid dark matter(PFDM).Considering the cosmological constant as the positive pressure of the system and volume as its conjugate variable,we analyze the thermodynamics of our black holes in the extended phase *** to the background clouds of strings parameter(a)and the parameter endowed with PFDM(β),we analyze the Hawking temperature,entropy,and specific ***,we investigate the relationship between the photon sphere radius and phase transition for the Letelier AdS black holes immersed in *** the analysis,with a particular condition,non-monotonic behaviors are found between the photon sphere radius,impact parameter,PFDM parameter,temperature,and *** can regard the changes in both the photon sphere radius and impact parameter before and after phase transition as the order parameter;their critical exponents near the critical point are equal to the same value,1/2,similar to that in ordinary thermal *** indicates that a universal relation of gravity may exist near the critical point for a black hole thermodynamic system.

关键词： AdS black holes perfect fluid dark matter Letelier spacetime photon orbit extended phase space thermodynamics correlation of photon orbit and thermodynamics

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Comparison of LSCP and Cluster Coverage Model for Emergency Train’s Assets Management:Use Case;North Eastern Railway

Comparison of LSCP and Cluster Coverage Model for Emergency ...

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Maintenance and Intelligent Asset Management (ICMIAM), International Conference on

作者： Kshitij Mishra Swastika Mishra Abhyuday Computer Engineering International Institute of Information Technology Hyderabad India Mechanical Engineering Netaji Subhas University of Technology New Delhi Indian Railways Service of Mechanical Engineers Indian Institute of Technology Kharagpur India

Deployment of Accident Relief Medical Vans (ARMV) used for accident relief and rescue operations is generally done heuristically. ARMV is an ambulance-train equipped with various tools like jacks, heavy cutting tools, generators, operation theatre, artificial breathing equipment etc. to ease the rescue process. Taking North Eastern Railway (NER) as a case study, Location Set Covering Problem (LSCP) model will be used to find the minimum number of ARMVs required for the given network and their locations so that all demand points can be ‘covered’ within a maximum of one hour @ 100 kmph for each of the nearest facility. This paper proposes a new mathematical model based on the Cluster Coverage Model (CCM) to provide a better coverage of ARMV’s demands. We have used Girvan-Newman (GN) algorithm, a weight-based graph for clustering of NER network where nodes are taken as depots with ARMV parking facilities & crew availability and distance between these nodes is taken as edge weight of the graph. Finally, we present a comparison of results between the proposed cluster coverage models with LSCP and suggest relocations of the existing ARMVs and show that our proposed model is economical and provides a better coverage of ARMVs demands.

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SPEAR: Design and Implementation of an Advanced Virtual Assistant

SPEAR: Design and Implementation of an Advanced Virtual Assi...

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Sustainable Expert Systems (ICSES), International Conference on

作者： Garima Jain Amita Shukla Nitesh Kumar Bairwa Anamika Chaudhary Ashish Patel Ankush Jain Department of Computer Science and Buisness Systems Noida Institute of Engineering and Technology Greater Noida India Department of Artificial Intelligence Noida Institute of Engineering and Technology Greater Noida India Department of Data Science Noida Institute of Engineering and Technology Greater Noida India Department of Artificial Intelligence and Machine Learning Dronacharya Group of Institutions Greater Noida India Department of Computer Science and Enginnering Netaji Subhash University of Technology Delhi India

ISBN: (数字)9798331540364

ISBN: (纸本)9798331540371

This research presents the development and evaluation of SPEAR, an advanced voice-activated personal desktop assistant designed to address challenges in existing virtual assistant technology, such as limited language support, low recognition accuracy, and inadequate task automation. Despite recent advancements in Natural Language Processing (NLP) and machine learning, implementation in current systems remains subpar. SPEAR achieves an 88% overall command execution success rate, with a speech recognition accuracy of 92% and an average response time of 1.8 seconds, demonstrating efficiency in real-time interactions. Developed using Python and machine learning libraries, SPEAR supports 15 voice commands across multiple platforms, excelling in note creation (95% success), web searching (94%), and information retrieval (92%). Its natural language understanding score of 0.86 and context retention rate of 75% highlight its conversational capabilities. While the assistant performs well in messaging functionality (85% success) and currently supports three languages, expanding its multilingual capabilities is essential for broader user engagement. Metrics indicate a satisfaction score of 8.2/10 and an average of 12 daily interactions per user, showcasing its practical utility. Additionally, the system's text-to-speech quality (8.5/10) and error recovery rate (82 %) affirm its robustness. These findings contribute valuable insights for future research, focusing on enhancing multilingual support, broadening task categories, and improving context retention, ultimately positioning SPEAR to rival established industry leaders by offering a comprehensive suite of services.

关键词： Accuracy Personal voice assistants Machine learning Information retrieval Natural language processing Real-time systems Robustness Text to speech Time factors Web search

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Dependence of Number of Inputs and Weights during Training of FFANN 17

Dependence of Number of Inputs and Weights during Training o...

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17th IEEE India Council International Conference, INDICON 2020

作者： Veenu, Veenu Singh Bhatia, Mohinder Pal Netaji Subhas University of Technology Department of Computer Science and Engineering Dwarka New Delhi78 India

ISBN: (纸本)9781728169163

When the analysis of processing time series is done, learning becomes complex consumes more time, hence various training algorithms are required that are accurate robust. This paper compares performance in minimizing the error using twelve different variants of back propagation algorithms. The analysis is performed on different data sets from UCI machine learning repository and approximation functions. The weights are initialized by using random, Nguyen-Widrow and proposed weight initialization methods. After analysis it is found that our proposed methods give better results shown graphically also in this paper. © 2020 IEEE.

关键词： Time series analysis

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