USER PERCEPTION OF DSPACE IN PDPU LIBRARY: A CASE

This paper examines the extent use of DSpace open source software and its adoption and users perceptions among PDPU libraries as an intuitional repository. Two separate questionnaires were used to gather data. 118 users are selected from stratified random sampling technique from total population of 400; questionnaires were shared to 118 users. The findings revealed that 94 responses were obtained. It is a clear sign coming out from this study is that DSpace software is becoming adoptable option to managing digital collections and building digital repository in Pandit Deendayal Petroleum University Libraries, Gandhinagar, and Gujarat. The current research is a descriptive study to evaluate DSpace digital repository open source system among PDPU Library users (Students, faculties, and staff). Through the experimental study analysis the similarities and differences between cases, identifying areas that have direct implementations for DSpace for Digital Repository to be collected from multiple sources, printed and electronic questionnaires. Web based tools for evaluation and analysis have been accepted for the study. This study it is observed that digital repositories (DR) are become formative in PDPU. Now the things have changed and DSpace has become mature and popular than another open source software for managing Institutional repository, in terms of features, DSpace is rich according to users’ perceptions, availability of community supports, and active participation of DSpace development leads make a very strong software

Enhanced Differential Crossover and Quantum Particle Swarm Optimization for IoT Applications

An optimized design with real-time and multiple realistic constraints in complex engineering systems is a crucial challenge for designers. In the non-uniform Internet of Things (IoT) node deployments, the approximation accuracy is directly affected by the parameters like node density and coverage. We propose a novel enhanced differential crossover quantum particle swarm optimization algorithm for solving nonlinear numerical problems. The algorithm is based on hybrid optimization using quantum PSO. Differential evolution operator is used to circumvent group moves in small ranges and falling into the local optima and improves global searchability. The cross operator is employed to promote information interchange among individuals in a group, and exceptional genes can be continued moderately, accompanying the evolutionary process's continuance and adding proactive and reactive features. The proposed algorithm's performance is verified as well as compared with the other algorithms through 30 classic benchmark functions in IEEE CEC2017, with a basic PSO algorithm and improved versions. The results show the smaller values of fitness function and computational efficiency for the benchmark functions of IEEE CEC2019. The proposed algorithm outperforms the existing optimization algorithms and different PSO versions, and has a high precision and faster convergence speed. The average location error is substantially reduced for the smart parking IoT application

A Novel Enhanced Quantum PSO for Optimal Network Configuration in Heterogeneous Industrial IoT

A novel enhanced quantum particle swarm optimization algorithm for IIoT deployments is proposed. It provides enhanced connectivity, reduced energy consumption, and optimized delay. We consider heterogeneous scenarios of network topologies for optimal path configuration by exploring and exploiting the hunts. It uses multiple inputs from heterogeneous IIoT into quantum and bio-inspired optimization techniques. The differential evolution operator and crossover operations are used for information interchange among the nodes to avoid trapping into local minima. The different topology scenarios are simulated to study the impact of $p$ -degrees of connectivity concerning objective functions’ evaluation and compared with existing techniques. The results demonstrate that our algorithm consumes a minimum of 30.3% lesser energy. Furthermore, it offers improved searching precision and convergence swiftness in the possible search space for $p$ -disjoint paths and reduces the delay by a minimum of 26.7%. Our algorithm also improves the throughput by a minimum of 29.87% since the quantum swarm inclines to generate additional diverse paths from multiple source nodes to the gateway

USER PERCEPTION OF DSPACE IN PDPU LIBRARY: A CASE

This paper examines the extent use of DSpace open source software and its adoption and users perceptions among PDPU libraries as an intuitional repository. Two separate questionnaires were used to gather data. 118 users are selected from stratified random sampling technique from total population of 400; questionnaires were shared to 118 users. The findings revealed that 94 responses were obtained. It is a clear sign coming out from this study is that DSpace software is becoming adoptable option to managing digital collections and building digital repository in Pandit Deendayal Petroleum University Libraries, Gandhinagar, and Gujarat. The current research is a descriptive study to evaluate DSpace digital repository open source system among PDPU Library users (Students, faculties, and staff). Through the experimental study analysis the similarities and differences between cases, identifying areas that have direct implementations for DSpace for Digital Repository to be collected from multiple sources, printed and electronic questionnaires. Web based tools for evaluation and analysis have been accepted for the study. This study it is observed that digital repositories (DR) are become formative in PDPU. Now the things have changed and DSpace has become mature and popular than another open source software for managing Institutional repository, in terms of features, DSpace is rich according to users’ perceptions, availability of community supports, and active participation of DSpace development leads make a very strong software

NASH BARGAINING BASED BANDWIDTH ALLOCATION IN COGNITIVE RADIO FOR DELAY CRITICAL APPLICATIONS

In order to effectively regulate the existing resources, dynamic spectrum access in cognitive radio needs to adopt the effective resource allocation strategies. Multimedia applications require large bandwidth and have to meet the delay constraints while maintaining the data quality. Game theory is emerging as an effective analytical tool for the analysis of available resources and its allocation. This paper addresses resource allocation schemes employing bargaining game model for Multi-carrier CDMA based Cognitive Radio. Resource allocation scheme is designed for transmission of video over cognitive radio networks and aim to perform bandwidth allocation for different cognitive users. Utility function based on bargaining model is proposed. Primary user utility function includes the pricing factor and an upbeat factor that can be adjusted by observing the delay constraints of the video. Allocated bandwidth to the secondary user can be adjusted by changing the upbeat factor. Throughput in the proposed scheme is increased by 2% as compared to other reported pricing based resource allocation schemes. The edge PSNR of reconstructed video obtained as 32.6dB resulting to optimum decoding of the video at the receiver. The study also shows upbeat factor can be used to enhanced capacity of the network

Multi-Armed Bandit Algorithm Policy for LoRa Network Performance Enhancement

Low-power wide-area networks (LPWANs) constitute a variety of modern-day Internet of Things (IoT) applications. Long range (LoRa) is a promising LPWAN technology with its long-range and low-power benefits. Performance enhancement of LoRa networks is one of the crucial challenges to meet application requirements, and it primarily depends on the optimal selection of transmission parameters. Reinforcement learning-based multi-armed bandit (MAB) is a prominent approach for optimizing the LoRa parameters and network performance. In this work, we propose a new discounted upper confidence bound (DUCB) MAB to maximize energy efficiency and improve the overall performance of the LoRa network. We designed novel discount and exploration bonus functions to maximize the policy rewards to increase the number of successful transmissions. The results show that the proposed discount and exploration functions give better mean rewards irrespective of the number of trials, which has significant importance for LoRa networks. The designed policy outperforms other policies reported in the literature and has a lesser time complexity, a comparable mean rewards, and improves the mean rewards by a minimum of 8%

EW WEIGHT DEPENDENT ROUTING AND WAVELENGTH ASSIGNMENT STRATEGY FOR ALL OPTICAL NETWORKS IN ABSENCE OF WAVELENGTH CONVERTERS

In wavelength division multiplexed all optical networks; lightpath establishes a connection between sending and receiving nodes bypassing the electronic processing at intermediate nodes. One of the prime objectives of Routing and Wavelength Assignment (RWA) problem is to maximize the number of connections efficiently by choosing the best routes. Although there are several algorithms available, improving the blocking performance in optical networks and finding optimal solutions for RWA problem has still remained a challenging issue. Wavelength conversion can be helpful in restricting the problem of wavelength continuity constraint but it increases complexity in the network. In this paper, we propose new weight dependent routing and wavelength assignment strategy for all optical networks without use of wavelength converters. Proposed weight function reduces blocking probability significantly, improving the network performance at various load conditions. Further, due to absence of wavelength converters, the cost and complexity of network reduces. Results show that the proposed strategy performs better than earlier reported methods