Search

Development of novel materials with desirable properties remains at the forefront of modern scientific research. Machine learning (ML), a branch of artificial intelligence, has recently emerged as a powerful technology in optoelectronic devices for the prediction of various properties and rational design of materials. Metal halide perovskites (MHPs) have been at the centre of attraction owing to their outstanding photophysical properties and rapid development in solar cell application. Therefore, the application of ML in the field of MHPs is also getting much attention to optimize the fabrication process and reduce the cost of processing. Here, we comprehensively reviewed different applications of ML in the designing of both MHP absorber layers as well as complete perovskite solar cells (PSCs). At the end, the challenges of ML along with the possible future direction of research are discussed. We believe that this review becomes an indispensable roadmap for optimizing materials composition and predicting design strategies in the field of perovskite technology in the future.

Learning through distance mode very helpful for all of us nowdays. MOOCs plays very important roe in all aspects. Govt of india also launch so many platform for this type of various learning domain. Learning were also early incarnations of varios factors depends of nature of learning in the form of written distance learning. MOOCs are a recent development in online education and have several distinctive features compared to previous distance education models. MOOCs are online courses intended for massive interactive participation and free web access. Materials of many conventional course such as powerpoint presentations, online notes, readings, quizzes, and videos. MOOCs provide very interactive and formation of collaborative learning forums that will be very helpful to build community for students and teachers

Communication platforms are undergoing a transition from physical to digital spaces. The Internet has radically changed the business scenario wherein people have become the “media” for collaborating to share information. Practitioners have started using electronic word of mouth (eWOM) for consumer insight through text analytics, sentiment, hashtag analytics, and other machine learning tools. Due to the growing importance of the topic as a research area, it is vital to map the research domain. This paper uses performance analysis tools (quantitative and qualitative) and science mapping tools (conceptual and intellectual structures) for literature review and the identification of future research directions. The content analysis of emergent topics and themes offers directions for future researchers. Recommender systems, data mining (artificial intelligence and machine learning), semantics, and sentiment analysis are emergent topics. We contribute to the eWOM literature by canvassing state-of-the-art research and proposing future research directions.

In this article, a self-adaptive global mine blast algorithm (GMBA) is proposed for numerical optimization. This algorithm is designed in a novel way, and a new shrapnel equation is proposed for the exploitation phase of mine blast algorithm. A theoretical study is performed, which proves the convergence of any typical shrapnel piece; a new definition for parameters values is defined based on the performed theoretical studies. The promising nature of newly designed exploitation idea is verified with the help of multiple numerical experiments. A state-of-the-art set of benchmark problems are solved with the proposed GMBA, and the optimization results are compared with seven state-of-the-art optimization algorithms. The experimental results are statistically validated by using Wilcoxon signed-rank test, and time complexity of GMBA is also calculated. It has been justified that the proposed GMBA works as a global optimizer for constrained optimization problems. As an application to the newly developed GMBA, an important data clustering problem is solved on six data clusters and the clustering results are compared with the state-of-the-art optimization algorithms. The promising results claim the proposed GMBA as a strong optimizer for data clustering application.

Recent advancement of cyber physical systems open doors to various safety measures, threats, attacks and vulnerabilities are such major key challenges now days. The globally adoption of cyber physical systems basically forms a basis for cyber social attack in order to breakdown secure channel and control actions. Hence loopholes and vulnerabilities in trending cyber physical systems are targeted to make systems unstable and unsafe state. The subjection of CPSs causes new critical issues for research and academics. However expeditious growth of CPS devices a question marks on security, integrity and confidentiality. The paradigm which forms basis for CPS are Smart phones, Defense System, Meteorology, Big data, Smart Technologies and Smart Vehicles. The purpose and analysis behind this paper to find out security issues and challenges of CPSs. Comparison of various cyber physical attacks and analysis on several parameters has been done. Key noted issues are results of cyber attacks, CPS attack traceability and the review on communication security architecture.

Online process monitoring and quality assurance are highly favorable for composite manufacturing processes like automated tape layup (ATL), where the productivity is largely constrained by downtime consisting of quality inspection and error mitigation. The presented work details the use of thermography as an inspection tool for such a process, using thermoplastic based tape material. A new online monitoring system is developed containing Infrared camera integrated on a purpose build ATL test rig. Surface thermal history for the layup course over time is recorded, which is then extracted along the width of the tape. The end result is a single image containing sequence of images, detailing the temperature data over the length of a single tape. Temperature gradient throughout the layup is then used to recognize foreign bodies and defects. Variation in adhesion effects of ply to the tool, ply and ply and ply and foreign bodies can be detected and areas of weak bonding can be recognized.

Water cycle algorithm (WCA) is a population-based metaheuristic algorithm, inspired by the water cycle process and movement of rivers and streams towards sea. The WCA shows good performance in both...

In recent year wireless multimedia sensor network has developed so far that it has attracted various researchers focus toward itself. In wireless multimedia sensor network there are various interconnected devices such as low-cost CMOS cameras, microphone helps to retrieve the multimedia content such as video streams, audio streams and scalar sensor data from the environment so in this paper we have brings out various aspects of wireless sensor network, there protocols for wireless multimedia sensor network , challenges. And their future scope. And we also hope also that it will help new research to clear their ideas among its researchers.

In the modern era, as technologies are getting advance, the work related to them are also getting advance. Today's business is totally dependent on the internet and to run a business we need the help of the internet so that it can grow at bulkier expanse. Everyday humongous amount of data and personal information has been transmitted and retrieved. With the brisk development of internet technology in contemporary years, online business is gradually rampant. Web users are very demanding and they foresee web services to be easily and quickly accessible from other places around the world all the time, whenever they need it. Web users always need quick and rapid responses. With the broadening trend of the internet, it turns out to be an essential part of our life. Website development is a process that takes time and if done by the basic language it takes more time which is not compatible with this fast and developing world of technologies. So to overcome these problems related to web development frameworks are developed. Frameworks are used so that we can create websites conveniently. This paper generalizes the concept of e-commerce website with a framework. What parameters we have to look upon so that we can prepare a website without any Hassel. This research paper also concludes what advantages did Laravel had on other frameworks, and how it is different to work on Framework. Electronic commerce as the name suggests electronic means through digital instruments or through the World Wide Web and commerce suggest the business so it combined means business through the World Wide Web which is on gravitate. LARAVEL is a free open source PHP framework. Frameworks are on go, as there is no need to write whole code.

Cost Estimation of any software is process of evaluating the estimating cost and effort which is must necessary to build any software system or project for increasing the output. The basic input is the cost drivers set and the size of code and the output is the effort which is calculated in terms of Person-Months (PM’s). To estimate cost for software is the main portions of any project type and right estimation of cost for the software will help in completing project in of time and budget. Proper cost estimation of a software project is highly needed to avoid any risk failure. So, there is a strong need to calculate the project’s cost annually and compare it to the other techniques. This paper deals with the analysis and comparison of COCOMO model of Boehm’s and COSYSMO model of Valerdi’s through the help of formulae’s and an online tool present at the CSSE website. For this we have used the COCOMO dataset and it has been observed that COSYSMO model works better than the COCOMO model in every aspect.

Driver's lethargy is one of the main causes of car accidents nowadays. We have discussed fatigue, object detection in hand, head pose estimation and siesta detection. This paper is focused on extracting and analyzing the various factors to alert the driver while driving the car. We have implemented real time face detection by using CNN. We have used light forbearance model as it will be easy to implement in real time situation. Eye tiredness by calculating percentage of eyelid closure over the pupil (PERCLOS), object detection in hand by tensor flow. Object is detected when the driver uses mobile phone and/or holds substance abuse material while driving. Mouth geometric movement detection is implemented by Deep Neural Network. This aims to reduce road accidents and the loss of life. In every 25 second a person dies in road accidents. We have proposed a method to reduce accidents by implementing certain factors. This will alert us whether or not the driver is in the proper condition for driving.

In the present period of wireless network, requirement of MANET is expanding at a quick pace. Explanation behind this expanded consideration is the extensive variety of mixed media applications running in an infrastructure less condition. Due to the framework less condition, constrained power and dynamic topology it turns out to be exceptionally hard to give a safe and secure domain in MANET. In this paper, a basic overview of various sort of attacks and protocols for overcoming of those attacks is presented. This paper additionally gives a short correlation of different protocols accessible for anchored routing in MANET and basic characteristics challenges of MANET are explained.

In microgrid systems, economic load dispatch (ELD) with dynamic approach is preferred over static approach because it not only minimizes the cost but also helps to coordinate between distribution generators (DGs). In this paper, microgrid system consisting of diesel engines (DE), wind turbine (WT), a fuel cell (FC) and a battery, model has been developed and analyzed with considering the effect of reserve, emissions, fluctuations in renewable power and the price variation of the grid. The main objective is to minimize the operation and pollutant treatment cost. Microgrid system analysis is done for two operating modes that is the grid connected and the island mode under four different scheduling schemes. By using the GAMS software with MATLAB interfacing, power and cost analysis of each scheduling scheme is done in detail. In the grid connected mode, priority is given either to the DGs or the main grid to have power exchange between the grid and the microgrid. In islanded mode, battery is used instead of the grid for the economic load dispatch.

This paper presents a novel approximation technique based on metaheuristics and weighted residual function (WRF) for tackling singular boundary value problems (BVPs) arising in engineering and scie...

Mixed Martial Arts is a rapidly growing combat sport that has a highly multi-dimensional nature. Due to a large number of possible strategies available to each fighter, and multitude of skills and techniques involved, the potential for upset in any fight is very high. That is the chance of a highly skilled, veteran athlete being defeated by an athlete with significantly less experience is possible. This problem is further exacerbated by the lack of a well-defined, time series database of fighter profiles prior to every fight. In this paper, we attempt to develop an efficient model based on the machine learning algorithms for the prior prediction of UFC fights. The efficacy of various machine learning models based on Perceptron, Random Forests, Decision Trees classifier, Stochastic Gradient Descent (SGD) classifier, Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) classifiers is tested on a time series set of a fighter’s data before each fight.

We have a great pleasure to presenting a special issue of the 4th International Conference on Harmony Search, Soft Computing and Applications (ICHSA 2018) organised by BML Munjal University, Gurugr...

Object oriented software system selection is an MCDM problem which is analyzed based on the expert's preference on different Parameters. Functionality attribute is one such parameter selected from Software quality model which consists of several other parameters by which quality of any Software can be analyzed. AHP tool is used for subjective weight analysis which is further validated using FTOPSIS technique on Functionality parameter. This analysis helps experts in selection of software systems whose concern is more about the functional operation of system. A MCDM model consists of AHP-FTOPSIS is proposed for ranking of alternatives based on the quantitative and subjective Parameters.

In this article, an artificial neural network (ANN) method is presented to obtain the closed analytic form of the one dimensional Bratu type equations, which are widely applicable in fuel ignition of the combustion theory and heat transfer. Our goal is to provide optimal solution of Bratu type equations with reduced calculus effort using ANN method in comparison to the other existing methods. Various test cases have been simulated using proposed neural network model and the accuracy has been substantiated by considering a large number of simulation data for each model with enough independent runs. Numerical results show that this method has potentiality to become an efficient approach for solving Bratu’s problems with less computing time and memory space.

Harmony Search Algorithm (HSA) is one of the efficient optimization algorithms among various optimization algorithms proposed over the years. In literature, many variants of the Harmony search algorithms are proposed based on the various ideas. In this article the exploration ability of the four HS algorithms are compared. An experimental comparative study of exploration ability of different versions of HS algorithms is done. The article provides a detailed explorative abilities of various HS algorithms. The comparison is based on the theoretical studies performed in [1]. The theoretical conclusions of the exploration analysis are justified with experimental studies. This article concludes with the searching ability of various HS algorithms along with their ranking with most explorative HS algorithm.

In this paper, we present an algorithm based on artificial neural networks (ANNs) and harmony search (HS) for the numerical solution of boundary value problems (BVPs), which evolves in most of the science and engineering applications. An approximate trial solution of the BVPs is constructed in terms of ANN in a way that it satisfies the desired boundary conditions of the differential equation (DE) a utomatically. Approximate satisfaction of the trial solution results in an unsupervised error, which is minimized by training ANN using the harmony search algorithm (HSA). A BVP modeling the flow of a stretching surface is considered here as a test problem to validate the accuracy, convergence and effectiveness of the proposed algorithm. The obtained results are compared with the available exact solution also to test the correctness of the algorithm.

technology has scaled down, the implications of leakage current and power analysis for memory design have increased. To minimize the short channel effect Double-gate FinFET can be used in place of conventional MOSFET circuits due to the self-alignment of the two gates. Design for XOR and XNOR circuits is suggested to improve the speed and power. These circuits act as basic building blocks for many arithmetic circuits. This paper contrasts and evaluates the performance of conventional CMOS and FinFET based XOR-XNOR circuit design. It is based on the study of high speed, low power, and small area in XOR-XNOR digital circuits. The proposed FinFET based XOR and XNOR circuits have been designed using Cadence VIRTUOSO Tool applying voltage supply of 0.2 to 1.2 voltages, with temperature at 27 0 C and all the simulation results have been generated by Cadence SPECTRE simulator at 45nm technology. Simulation results exhibit low power, delay, power, delay product (PDP), and average dynamic power consumption.

We present the mathematical model and an artificial neural network method for calculating the buckling load of a beam column with different end conditions. A trial solution of the beam column equation is written as a sum of two parts, in which first part satisfies the boundary conditions and the second part represents the feed forward neural network containing adjustable parameters, weights and biases. We prepared the Error function by using the beam column equation and its boundary conditions, which is used in the back propagation method with deflection term to update the network parameters. It is found that the artificial neural network method is capable for calculating deflection of a beam column as a part of the training process. To ascertain the soundness, efficiency and accuracy of the proposed method the results are compared to the Euler critical load.

Denial of service attack is one of most interesting attack of network because of this network bandwidth utilization increase. To prevent this attack using various techniques. In our proposed work we give trust or repuatation base technique in which sender and receiver send data using encryption and decryption. Novality of our work we provide by our result.

Mobile ad hoc networks are wireless networks consisting of mobile nodes with no boundary. Nodes are free to move and the network is dynamic. Unique features of these networks serve as benefits as well as drawbacks and give chances to attackers. Intrusion occurs when a malicious node tries to enter the network and misuses the resources. Several attacks and intrusion detection techniques are discussed in this paper.

Software Reliability is an important feature of software quality, like other quality attribute as functionality, usability, performance, serviceability, maintainability, documentation etc. This Software reliability optimization is very important in software development field. Lots of software reliability models have been specified in last few years. This paper reviews the different Evolutionary algorithms for reliability optimization to solve challenging problems in the field of academia and industry. There are many algorithms which have been already used for optimization of software reliability model like Genetic, Ant colony optimization, Bee colony optimization, Bacterial Foraging Optimization; Particle swam optimization, BAT, CAT and hybrid. But still there are so many evolutionary algorithms which are still unused. In this paper we explore the role of some of the well known evolutionary techniques for optimizing software reliability.

Operating system selection problem is to choose the optimum OS based on user preferences on different factors. Functionality is one such attribute selected from software quality model which comprises several other sub factors preferred to analyse the quality of system. Analysis is done using AHP approach for weight calculations and results are validated using Entropy method on Functionality factors of Software quality model ISO 9126. This analysis helps in decision making for users which concerns about how well outcomes of any execution are achieved. A model AHP-Entropy is proposed which can be used to rank alternatives on both subjective and quantitative factors.

Since neural networks have universal approximation capabilities, therefore it is possible to postulate them as solutions for given differential equations that define unsupervised errors. In this paper, we present a wide survey and classification of different Multilayer Perceptron (MLP) and Radial Basis Function (RBF) neural network techniques, which are used for solving differential equations of various kinds. Our main purpose is to provide a synthesis of the published research works in this area and stimulate further research interest and effort in the identified topics. Here, we describe the crux of various research articles published by numerous researchers, mostly within the last 10 years to get a better knowledge about the present scenario.

Harmony Search Algorithm (HSA) has shown to be simple, efficient and strong optimization algorithm. The exploration ability of any optimization algorithm is one of the key points. In this article a new methodology is proposed to measure the exploration ability of the HS algorithm. To understand the searching ability potential exploration range for HS algorithm is designed. Four HS variants are selected and their searching ability is tested based on the choice of improvised harmony. An empirical analysis of the proposed method is tested along with the justification of theoretical findings and experimental results.

In this chapter brief introduction to neural network has been given along with some basic terminologies. We explain the mathematical model of neural network in terms of activation functions. Different architectures of neural network like feed forward, feed backward, radial basis function network, multilayer perceptron neural network and cellular network etc., is described. Backpropagation and other training algorithms have been also discussed in this chapter.

In this chapter we presented different neural network methods for the solution of differential equations mainly Multilayer perceptron neural network, Radial basis function neural network, Multiquadric radial basis function network, Cellular neural network, Finite element neural network and Wavelet neural network. Recent development in all the above given methods has been also presented in this chapter to get better knowledge about the subject.

Here we are presenting a brief history of neural networks, given in Haykin (Neural networks: a comprehensive foundation, 2002) [7], Zurada (Introduction to artificial neural systems, 2001) [8], Nielsen (Neurocomputing, 1990 [9] in terms of the development of architectures and algorithms that are widely used today. The history of neural networks has been divided in four stages: Beginning of neural networks, First golden age, Quiet Years and Renewed enthusiasm which shows the interplay among biological experimentation, modeling and computer simulation, hardware implementation.

In this article, we present an artificial neural network technique to solve some of the two-point nonlinear elliptic boundary value problems arising in science and engineering. A trial solution of the differential equation is written in terms of a feed forward neural network with adjustable parameters weights or biases, and error function is prepared to use in the back-propagation algorithm to update the network parameters with momentum term. Comparison of the results obtained by the present method is done with analytical solution and other existing numerical methods which show the efficiency of Neural network method with high accuracy, fast convergence, and low use of memory for solving nonlinear elliptic boundary value problems. The main advantage of the proposed approach is that once the network is trained, it allows evaluation of the solution at any desired number of points instantaneously with spending negligible computing time.

Inter-vehicle communications have great potential to induce great interest in research and industry. Vehicular ad hoc networks (VANETs) may significantly improve passenger safety and comfort. The deployment of VANETs is a challenging task in weakly interconnected and in highly overloaded networks both. A good back off technique can reduce a large number of collisions in the MAC layer I VANET. This will reduce the collision probability and hence increases the utilization of network resources. A uniform random distribution has been employed to choose the back off value in the Binary Exponential Back off (BEB) technique used in the IEEE 802.11 MAC protocol. This random choosing VANETs leads to unnecessary idle times and reduced throughput. This paper proposes a new back off technique called “Squaring Back off (SB)” in which the differences between the consecutive contention window sizes are reduced to a negligible value. Here, the value of the back off timer is based on the size of the contention window. The size of the contention window is varied in accordance with the result of the previous transmission. A successful transmission reduces the size of the contention window whereas a failure leads to the increase in the contention window size. Simulation results indicate that the proposed technique provides better throughputs and less idle times than the logarithmic and Fibonacci based techniques when used in a mobile ad-hoc environment. Squaring back off based media access control can prove very useful for vehicular ad-hoc networks.

This paper represents the design and analysis of ring oscillator using cadence virtuoso tool in 45 nm technology. Ring oscillator consists of odd number of stages with feedback circuit which forms a closed loop in which each stage output depends on the previous stage. In this paper, nine stage ring oscillator have been designed with a capacitor of 1 fF at each stage and simulated for various parameters such as delay, noise, jitter and power consumption. Power consumption, jitter, noise have been reduced in nine stage ring oscillator. Periodic steady state response of ring oscillator is also observed. Power consumption is reduced by 18.9 %.