UML Modeling of Network Topologies for Distributed Computer System

Nowadays distributed computer systems have become very popular approach due to its availability at low cost and high performance computers, which are connected through a communication network. For connection of the distributed computer systems, network topologies are must for the communication lines. In the present paper a detailed study of network topologies is done for the distributed computer systems. A most popular Unified Modeling Language (UML) is used for designing the different network topologies. A comparative study is done for 2D Mesh, Torus, and Hypercube topologies and performance is evaluated after designing the UML Class, Sequence, and Activity diagrams for these topologies

Proxy Signature Scheme with Effective Revocation Using Bilinear Pairings

We present a proxy signature scheme using bilinear pairings that provides effective proxy revocation. The scheme uses a binding-blinding technique to avoid secure channel requirements in the key issuance stage. With this technique, the signer receives a partial private key from a trusted authority and unblinds it to get his private key, in turn, overcomes the key escrow problem which is a constraint in most of the pairing-based proxy signature schemes. The scheme fulfills the necessary security requirements of proxy signature and resists other possible threats

Fault Detection and Classification in Transmission Line Using Wavelet Transform and ANN

In recent years, there is an increased interest in fault classification algorithms. The reason, behind this interest is the escalating power demand and multiple interconnections of utilities in grid. This paper presents an application of wavelet transforms to detect the faults and further to perform classification by supervised learning paradigm. Different architectures of ANN are tested with the statistical attributes of a wavelet transform of a voltage signal as input features and binary digits as outputs. The proposed supervised learning module is tested on a transmission network. It is observed the Layer Recurrent Neural Network (LRNN) architecture performs satisfactorily when it is compared with the simulation results. The transmission network is simulated on Matlab. The performance indices Mean Square Error (MSE), Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Sum Square Error (SSE) are used to determine the efficacy of the neural network

Fault Detection and Classification in Transmission Line Using Wavelet Transform and ANN

Recent years, there is an increased interest in fault classification algorithms. The reason, behind this interest is the escalating power demand and multiple interconnections of utilities in grid. This paper presents an application of wavelet transforms to detect the faults and further to perform classification by supervised learning paradigm. Different architectures of ANN aretested with the statistical attributes of a wavelet transform of a voltage signal as input features and binary digits as outputs. The proposed supervised learning module is tested on a transmission network. It is observed that ANN architecture performs satisfactorily when it is compared with the simulation results. The transmission network is simulated on Matlab. The performance indices Mean Square Error (MSE), Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Sum Square Error (SSE) are used to determine the efficacy of the neural network

Calm my Headspace: Motivations and Barriers for Adoption and Usage of Meditation Apps during Times of Crisis

Meditation applications for smartphones have been steadily growing in popularity. During the current Coronavirus pandemic, usership of various meditation apps has grown to reach record levels. This study explores the motivations for and barriers to adoption and usage of meditation apps during times of crisis. The study is based on qualitative, semi-structured interviews conducted with seventeen participants. The interviews were audio recorded, transcribed verbatim, and coded using the NVivo software. Inductive thematic analysis identifies five themes: job-related factors, changing lifestyles, psychological conditions and worries, perceived outcomes, and price. All themes except for pricing were found to be motivators for use, while price was deemed a barrier to use. The themes align with the constructs from the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Diffusion of Innovation (DOI) Theory, providing some useful guidance to meditation app providers

Electric Price Forecast using Interbreed Approach of Linear Regression and SVM

Electricity price forecasting is a hypercritical issue due to the involvement of consumers and producers in electricity markets. Price forecasting plays an important role in planning and managing economic operations related with the electrical power (bidding, trading) and other decisions related with load shedding and generation rescheduling. It is also useful for optimization in electrical energy trade. This paper explores an interbreed technique based on Support Vector Machine (SVM) and linear regression to predict the day ahead electricity price using historical data as a raw insert. Different 27 linear regression models are formed to create initial framework for forecasting engine. Comparison of the performance of different forecasting engines is carried out on the basis of error indices namely Mean Square Error (MSE), Sum Square Error (SSE) and other conventional error indices. A detailed explanation of linear regression system based model is presented and simulation results exhibit that the proposed learning method is able to forecast electricity price in an effective manner

Yet Another ‘List’ Of Critical Success ‘Factors’ For Enterprise Systems: Review Of Empirical Evidence And Suggested Research Directions (2)

Critical Success Factors (CSF) remain the most-researched areas within the Enterprise Systems (ES) domain over the years and has resulted in a long ‘list’ of such factors. Consequently, many ‘factors’ are not more than ‘variables’ belonging to the same management area. Therefore, this paper argues for going back to the original definition of CSFs as few key areas and reviews empirical evidence in each CSF area. Thereafter, the paper notes other limitations of the CSF literature and suggests research directions to provide a deeper explanation of the ES phenomena. These include tracing CSFs across time, taking a change-centric view of the ES lifecycle, unpacking interrelationship among CSFs, paying attention to the implementation context, and moving from a list of CSFs to the identification of their underlying mechanisms. We hope that our suggestions will provide a roadmap to ES researchers on conducting focussed research on CSFs