Showing papers in "International Journal of Electrical and Computer Engineering in 2017"
TL;DR: This paper is a study and proposal paper which discusses the factors and studies that lead towards this patent pending invention, AGRIPI.
Abstract: Agriculture plays a significant role in most countries and there is an enoromous need for this industry to become “Smart”. The Industry is now moving towards agricultural modernization by using modern smart technologies to find solutions for effective utilization of scarce resources there by meeting the ever increasing consumtion needs of global population. With the advent of Internet of Things and Digital transformation of rural areas, these technologies can be leveraged to remotely monitor soil moisture, crop growth and take preventive measures to detect crop damages and threats. Utilize artificial intelligence based analytics to quickly analyze operational data combined with 3rd party information, such as weather services, expert advises etc., to provide new insights and improved decision making there by enabling farmers to perform “Smart Agriculture”. Remote management of agricultural activities and their automation using new technologies is the area of focus for this research activity. A solar powered remote management and automation system for agricultural activities through wireless sensors and Internet of Things comprising, a hardware platform based on Raspberry Pi Micro controller configured to connect with a user device and accessed through the internet network. The data collection unit comprises a set of wireless sensors for sensing agricultural activities and collecting data related to agricultural parameters; the base station unit comprising: a data logger; a server; and a software application for processing, collecting, and sending the data to the user device. The user device ex: mobile, tablet etc. can be connected to an internet network, whereby an application platform (mobile-app) installed in the user device facilitates in displaying a list of wireless sensor collected data using Internet of Things and a set of power buttons. This paper is a study and proposal paper which discusses the factors and studies that lead towards this patent pending invention, AGRIPI.
95 citations
TL;DR: CSA is used to determine the optimal settings of control variables such as generator voltages, transformer tap positions and the amount of reactive compensation required to optimize the certain objective functions.
Abstract: This paper solves an optimal reactive power scheduling problem in the deregulated power system using the evolutionary based Cuckoo Search Algorithm (CSA). Reactive power scheduling is a very important problem in the power system operation, which is a nonlinear and mixed integer programming problem. It optimizes a specific objective function while satisfying all the equality and inequality constraints. In this paper, CSA is used to determine the optimal settings of control variables such as generator voltages, transformer tap positions and the amount of reactive compensation required to optimize the certain objective functions. The CSA algorithm has been developed from the inspiration that the obligate brood parasitism of some Cuckoo species lay their eggs in nests of other host birds which are of other species. The performance of CSA for solving the proposed optimal reactive power scheduling problem is examined on standard Ward Hale 6 bus, IEEE 30 bus, 57 bus, 118 bus and 300 bus test systems. The simulation results show that the proposed approach is more suitable, effective and efficient compared to other optimization techniques presented in the literature.
83 citations
TL;DR: Algorithms such as LMS and RLS proves to be vital in the noise cancellation are reviewed including principle and recent modifications to increase the convergence rate and reduce the computational complexity for future implementation.
Abstract: This paper reviews the past and the recent research on Adaptive Filter algorithms based on adaptive noise cancellation systems. In many applications of noise cancellation, the change in signal characteristics could be quite fast which requires the utilization of adaptive algorithms that converge rapidly. Algorithms such as LMS and RLS proves to be vital in the noise cancellation are reviewed including principle and recent modifications to increase the convergence rate and reduce the computational complexity for future implementation. The purpose of this paper is not only to discuss various noise cancellation LMS algorithms but also to provide the reader with an overview of the research conducted.
79 citations
TL;DR: An IoT Crowd Sensing platform that offers a set of services to citizens by exploiting a network of bicycles as IoT probes by providing real time remote geo-location of users' bikes, anti-theft service, information about traveled route, and air pollution monitoring is presented.
Abstract: In recent years, the Smart City concept is emerging as a way to increase efficiency, reduce costs, and improve the overall quality of citizen life. The rise of Smart City solutions is encouraged by the increasing availability of Internet of Things (IoT) devices and crowd sensing technologies. This paper presents an IoT Crowd Sensing platform that offers a set of services to citizens by exploiting a network of bicycles as IoT probes. Based on a survey conducted to identify the most interesting bike-enabled services, the SmartBike platform provides: real time remote geo-location of users' bikes, anti-theft service, information about traveled route, and air pollution monitoring. The proposed SmartBike platform is composed of three main components: the SmartBike mobile sensors for data collection installed on the bicycle; the end-user devices implementing the user interface for geo-location and anti-theft; and the SmartBike central servers for storing and processing detected data and providing a web interface for data visualization. The suitability of the platform was evaluated through the implementation of an initial prototype. Results demonstrate that the proposed SmartBike platform is able to provide the stated services, and, in addition, that the accuracy of the acquired air quality measurements is compatible with the one provided by the official environmental monitoring system of the city of Turin. The described platform will be adopted within a project promoted by the city of Turin, that aims at helping people making their mobility behavior more sustainable.
43 citations
TL;DR: This article summarizes the current state of the IoT technology in several areas, and also the applications of IoT that cause side effects on the authors' environment for monitoring and evaluation of the impact of human activity on the environment around us.
Abstract: The internet of things (IoT), also called internet of all, is a new paradigm that combines several technologies such as computers, the internet, sensors network, radio frequency identification (RFID), communication technology and embedded systems to form a system that links the real worlds with digital worlds. With an increase in the deployment of smart objects, the internet of things should have a significant impact on human life in the near future. To understand the development of the IoT, this paper reviews the current research of the IoT, key technologies, the main applications of the IoT in various fields, and identifies research challenges. A main contribution of this review article is that it summarizes the current state of the IoT technology in several areas, and also the applications of IoT that cause side effects on our environment for monitoring and evaluation of the impact of human activity on the environment around us, and also provided an overview of some of the main challenges and application of IoT. This article presents not only the problems and challenges of IoT, but also solutions that help overcome some of the problems and challenges.
40 citations
TL;DR: The concepts of cloud computing and fog computing will be explored and their features will be contrasted to understand which is more efficient and better suited for real-time application.
Abstract: In Cloud Computing, all the processing of the data collected by the node is done in the central server. This involves a lot of time as data has to be transferred from the node to central server before the processing of data can be done in the server. Also it is not practical to stream terabytes of data from the node to the cloud and back. To overcome these disadvantages, an extension of cloud computing, known as fog computing, is introduced. In this, the processing of data is done completely in the node if the data does not require higher computing power and is done partially if the data requires high computing power, after which the data is transferred to the central server for the remaining computations. This greatly reduces the time involved in the process and is more efficient as the central server is not overloaded. Fog is quite useful in geographically dispersed areas where connectivity can be irregular. The ideal use case requires intelligence near the edge where ultra-low latency is critical, and is promised by fog computing. The concepts of cloud computing and fog computing will be explored and their features will be contrasted to understand which is more efficient and better suited for real-time application.
38 citations
TL;DR: This work explores the possibilities of recognizing classical dance mudras in various dance forms in India and helps new learners and dance enthusiastic people to learn and understand dance forms and related information on their mobile devices.
Abstract: Digital understanding of Indian classical dance is least studied work, though it has been a part of Indian Culture from around 200BC. This work explores the possibilities of recognizing classical dance mudras in various dance forms in India. The images of hand mudras of various classical dances are collected form the internet and a database is created for this job. Histogram of oriented (HOG) features of hand mudras input the classifier. Support vector machine (SVM) classifies the HOG features into mudras as text messages. The mudra recognition frequency (MRF) is calculated for each mudra using graphical user interface (GUI) developed from the model. Popular feature vectors such as SIFT, SURF, LBP and HAAR are tested against HOG for precision and swiftness. This work helps new learners and dance enthusiastic people to learn and understand dance forms and related information on their mobile devices.
38 citations
TL;DR: It is concluded that the linear precoding technique MMSE achieves the maximum EE more than ZF and MRT because the MMSE is able to make the massive MIMO system less sensitive to SNR at an increased number of antennas.
Abstract: Massive multi-input–multi-output (MIMO) systems are crucial to maximizing energy efficiency (EE) and battery-saving technology. Achieving EE without sacrificing the quality of service (QoS) is increasingly important for mobile devices. We first derive the data rate through zero forcing (ZF) and three linear precodings: maximum ratio transmission (MRT), zero forcing (ZF), and minimum mean square error (MMSE). Performance EE can be achieved when all available antennas are used and when taking account of the consumption circuit power ignored because of high transmit power. The aim of this work is to demonstrate how to obtain maximum EE while minimizing power consumed, which achieves a high data rate by deriving the optimal number of antennas in the downlink massive MIMO system. This system includes not only the transmitted power but also the fundamental operation circuit power at the transmitter signal. Maximized EE depends on the optimal number of antennas and determines the number of active users that should be scheduled in each cell. We conclude that the linear precoding technique MMSE achieves the maximum EE more than ZF and MRT because the MMSE is able to make the massive MIMO system less sensitive to SNR at an increased number of antennas .
32 citations
TL;DR: This paper studied quality of service based task scheduling algorithms and the parameters used for scheduling and compared the results the efficiency of the algorithm is measured and limitations are given.
Abstract: In cloud computing resources are considered as services hence utilization of the resources in an efficient way is done by using task scheduling and load balancing. Quality of service is an important factor to measure the trustiness of the cloud. Using quality of service in task scheduling will address the problems of security in cloud computing. This paper studied quality of service based task scheduling algorithms and the parameters used for scheduling. By comparing the results the efficiency of the algorithm is measured and limitations are given. We can improve the efficiency of the quality of service based task scheduling algorithms by considering these factors arriving time of the task, time taken by the task to execute on the resource and the cost in use for the communication.
30 citations
TL;DR: The conclusion that can be drawn is that the proposed diagnosis system capable of delivering performance in the very good category, with a number of attributes that are not a lot of checks and a relatively low cost.
Abstract: Improved system performance diagnosis of coronary heart disease becomes an important topic in research for several decades. One improvement would be done by features selection, so only the attributes that influence is used in the diagnosis system using data mining algorithms. Unfortunately, the most feature selection is done with the assumption has provided all the necessary attributes, regardless of the stage of obtaining the attribute, and cost required. This research proposes a hybrid model system for diagnosis of coronary heart disease. System diagnosis preceded the feature selection process, using tiered multivariate analysis. The analytical method used is logistic regression. The next stage, the classification by using multi-layer perceptron neural network. Based on test results, system performance proposed value for accuracy 86.3%, sensitivity 84.80%, specificity 88.20%, positive prediction value (PPV) 90.03%, negative prediction value (NPV) 81.80% , accuracy 86,30% and area under the curve (AUC) of 92.1%. The performance of a diagnosis using a combination attributes of risk factors, symptoms and exercise ECG. The conclusion that can be drawn is that the proposed diagnosis system capable of delivering performance in the very good category, with a number of attributes that are not a lot of checks and a relatively low cost .
28 citations
TL;DR: This study aims at developing Virtual Laboratory (V-Lab) for students or college students who are preparing for line follower robot competition with unsettled and changeable tracks.
Abstract: Laboratory serves as an important facility for experiment and research activity. The limitation of time, equipment, and capacity in the experiment and research undertaking impede both students and college students in undertaking research for competition preparation, particularly dealing with line follower robot competition which requires a wide space of the room with various track types. Unsettled competition track influences PID control setting of line follower robot. This study aims at developing Virtual Laboratory (V-Lab) for students or college students who are preparing for line follower robot competition with unsettled and changeable tracks. This study concluded that the trial data score reached 98.5%, the material expert score obtained 89.7%, learning model expert score obtained 97.9%, and the average score of small group learning model and field of 82.4%, which the average score of the entire aspects obtained 90.8%.
TL;DR: A comparative study of some of the prominent tools, techniques, frameworks and models for web application testing is presented and highlights the current research directions ofSome of the web applicationTesting techniques.
Abstract: Testing is an important part of every software development process on which companies devote considerable time and effort The burgeoning web applications and their proliferating economic significance in the society made the area of web application testing an area of acute importance The web applications generally tend to take faster and quicker release cycles making their testing very challenging The main issues in testing are cost efficiency and bug detection efficiency Coverage-based testing is the process of ensuring exercise of specific program elements Coverage measurement helps determine the “thoroughness” of testing achieved An avalanche of tools, techniques, frameworks came into existence to ascertain the quality of web applications A comparative study of some of the prominent tools, techniques and models for web application testing is presented This work highlights the current research directions of some of the web application testing techniques
TL;DR: In this article, the authors investigated the prospects and cost-effectiveness of implementation of standalone PV/wind system in sokoto state Nigeria, and they used the Homer optimization software to determine the optimum sizing of the renewable energy (RE) system.
Abstract: This paper investigates the prospects and cost-effectiveness of implementation of standalone PV/wind system in sokoto state Nigeria. Daily electricity demand, yearly solar radiation and wind speed were applied to determine the optimum sizing of the renewable energy (RE) system. To design optimum RE with proper sizing of system components, meteorological data obtained from the National Aeronautics and Space Administration were applied as input for this study. In Nigeria, sokoto is a region with solar radiation of 6kWh/m 2 /day and wind speed of 5m/s at 10m above height. Using the Homer optimization software, the optimum integrated RE system is 35.21kW PV, 3 x 25kW wind turbines, 12 x 24V lead acid battery and 17.44kW converter. The system has a total capital cost of $249910.24, the replacement cost of $82914.85 and maintenance cost of $53802.80 for 25 years. Though the initial capital cost is high but the long term benefits are enormous, considering the high cost of implementing rural electrification scheme, coupled with ahike in electricity tariff. There is also a payback period of 5 years. The results imply a standalone PV/wind system is feasible in rural communities of sokoto with 100% pollution free energy system.
TL;DR: In this paper, student's performance is evaluated using fuzzy association rule mining that describes prediction of performance of the students at the end of the semester, on the basis of previous database like Attendance, Midsem Marks, Previous semester marks and Previous Academic Records were collected from the student's previous database, to identify those students which needed individual attention to decrease fail ration and taking suitable action for the next semester examination.
Abstract: The major intention of higher education institutions is to supply quality education to its students. One approach to get maximum level of quality in higher education system is by discovering knowledge for prediction regarding the internal assessment and end semester examination. The projected work intends to approach this objective by taking the advantage of fuzzy inference technique to classify student scores data according to the level of their performance. In this paper, student’s performance is evaluated using fuzzy association rule mining that describes Prediction of performance of the students at the end of the semester, on the basis of previous database like Attendance, Midsem Marks, Previous semester marks and Previous Academic Records were collected from the student’s previous database, to identify those students which needed individual attention to decrease fail ration and taking suitable action for the next semester examination.
TL;DR: The discussion of this paper will focus on how simple agent’s structure utilizes flexible and potential outcomes in order to navigate in a productive and unorganized surrounding.
Abstract: This paper set out to supplement new studies with a brief and comprehensible review of the advanced development in the area of the navigation system, starting from a single robot, multi-robot, and swarm robots from a particular perspective by taking insights from these biological systems. The inspiration is taken from nature by observing the human and the social animal that is believed to be very beneficial for this purpose. The intelligent navigation system is developed based on an individual characteristic or a social animal biological structure. The discussion of this paper will focus on how simple agent’s structure utilizes flexible and potential outcomes in order to navigate in a productive and unorganized surrounding. The combination of the navigation system and biologically inspired approach has attracted considerable attention, which makes it an important research area in the intelligent robotic system. Overall, this paper explores the implementation, which is resulted from the simulation performed by the embodiment of robots operating in real environments.
TL;DR: This paper focused on finding out whether or not visual images of tumor ripped lesions ended up being much better by auto fluorescence image resolution as well as narrow-band image resolution graphic evaluation jointly with the latest neuroendoscopy technique.
Abstract: The issue of brain magnetic resonance image exploration together with classification receives a significant awareness in recent years. Indeed, various computer-aided-diagnosis solutions were suggested to support radiologist in decision-making. In this circumstance, adequate image classification is extremely required as it is the most common critical brain tumors which often develop from subdural hematoma cells, which might be common type in adults. In healthcare milieu, brain MRIs are intended for identification of tumor. In this regard, various computerized diagnosis systems were suggested to help medical professionals in clinical decision-making. As per recent problems, Neuroendoscopy is the gold standard intended for discovering brain tumors; nevertheless, typical Neuroendoscopy can certainly overlook ripped growths. Neuroendoscopy is a minimally-invasive surgical procedure in which the neurosurgeon removes the tumor through small holes in the skull or through the mouth or nose. Neuroendoscopy enables neurosurgeons to access areas of the brain that cannot be reached with traditional surgery to remove the tumor without cutting or harming other parts of the skull. We focused on finding out whether or not visual images of tumor ripped lesions ended up being much better by auto fluorescence image resolution as well as narrow-band image resolution graphic evaluation jointly with the latest neuroendoscopy technique. Also, within the last several years, pathology labs began to proceed in the direction of an entirely digital workflow, using the electronic slides currently being the key element of this technique. Besides lots of benefits regarding storage as well as exploring capabilities with the image information, among the benefits of electronic slides is that they can help the application of image analysis approaches which seek to develop quantitative attributes to assist pathologists in their work. However, systems also have some difficulties in execution and handling. Hence, such conventional method needs automation. We developed and employed to look for the targeted importance along with uncovering the best-focused graphic position by way of aliasing search method incorporated with new Neuroendoscopy Adapter Module (NAM) technique.
TL;DR: The results justify the choice of AIS and the use of MOTI in optimal siting of DG sources which improves the distribution system efficiency to a great extent in terms of reduced real and reactive power losses, improved voltage profile and voltage stability.
Abstract: Distributed generation (DG) sources are being installed in distribution networks worldwide due to their numerous advantages over the conventional sources which include operational and economical benefits. Random placement of DG sources in a distribution network will result in adverse effects such as increased power loss, loss of voltage stability and reliability, increase in operational costs, power quality issues etc. This paper presents a methodology to obtain the optimal location for the placement of multiple DG sources in a distribution network from a technical perspective. Optimal location is obtained by evaluating a global multi-objective technical index (MOTI) using a weighted sum method. Clonal selection based artificial immune system (AIS) is used along with optimal power flow (OPF) technique to obtain the solution. The proposed method is executed on a standard IEEE-33 bus radial distribution system. The results justify the choice of AIS and the use of MOTI in optimal siting of DG sources which improves the distribution system efficiency to a great extent in terms of reduced real and reactive power losses, improved voltage profile and voltage stability. Solutions obtained using AIS are compared with Genetic algorithm (GA) and Particle Swarm optimization (PSO) solutions for the same objective function.
TL;DR: In this paper, the authors used the Discrete Wavelet transform (DWT) with details thresholding for efficient noise removal followed by edge detection and threshold segmentation of the denoised images.
Abstract: Magnetic Resonance Imaging is a powerful technique that helps in the diagnosis of various medical conditions. MRI Image pre-processing followed by detection of brain abnormalities, such as brain tumors, are considered in this work. These images are often corrupted by noise from various sources. The Discrete Wavelet Transforms (DWT) with details thresholding is used for efficient noise removal followed by edge detection and threshold segmentation of the denoised images. Segmented image features are then extracted using morphological operations. These features are finally used to train an improved Support Vector Machine classifier that uses a Gausssian radial basis function kernel. The performance of the classifier is evaluated and the results of the classification show that the proposed scheme accurately distinguishes normal brain images from the abnormal ones and benign lesions from malignant tumours. The accuracy of the classification is shown to be 100% which is superior to the results reported in the literature.
TL;DR: In this paper, three factors antecedents of trust directly had a positive impact to customer trust and indirectly had positive impact on customer intention to purchase in e-commerce transactions on social media.
Abstract: This study aims to analyze empirically three factors antecedents of trust they are system quality, information quality, and service quality. Customer trust is used in determining customer intention to purchase of e-commerce in social media (facebook). A number of respondents were 451. The results of this study concluded that three factors antecedents of trust directly had a positive impact to customer trust and indirectly had positive impact on customer intention to purchase in e-commerce transactions on social media.
TL;DR: A hybrid clustered routing approach is proposed for energy optimization in WSN based on K-Means clustering algorithm and LEACH protocol, which outperforms LEach protocol and optimizes the nodes energy and the network lifetime.
Abstract: Energy efficiency is the most critical challenge in wireless sensor network The transmission energy is the most consuming task in sensor nodes, specifically in large distances Clustered routing techniques are efficient approaches used to lower the transmission energy and maximize the network’s lifetime In this paper, a hybrid clustered routing approach is proposed for energy optimization in WSN This approach is based on K-Means clustering algorithm and LEACH protocol The simulation results using MATLAB tool have shown that the proposed hybrid approach outperforms LEACH protocol and optimizes the nodes energy and the network lifetime
TL;DR: This Research was conducted to analyze the identification of eggs by using Matlab prototype tools and the process can be applied for identifying of chicken eggs with the accuracy rate of 100%.
Abstract: This Research was conducted to analyze the identification of eggs. The research processes use two tools, namely thermal imaging camera and smartphone camera. The identification process was done by using Matlab prototype tools. The image has been acquired by means of proficiency level, then analyzed and applied several methods. Image acquisition results of thermal imaging camera are processed using morphological dilation and do the complement in black and white (BW). While the digital image uses the merger method of morphological dilation and opening, and it doesn't need to be complemented. Labeling process is done, and the process of determining centroid and bounding box. The process has been done and it can be applied for identifying of chicken eggs with the accuracy rate of 100%. There are different methods of both images is obtained area (pixels) which is equivalent to the difference is very small as 6 x 10 -3 .
TL;DR: In this article, a multiband and miniature rectangular microstrip antenna is designed and analyzed for Radio Frequency Identification (RFID) reader applications, which is achieved using fractal technique and the physical parameters of the structure as well as its ground plane are optimized using CST Microwave Studio.
Abstract: In this paper, a multiband and miniature rectangular microstrip antenna is designed and analyzed for Radio Frequency Identification (RFID) reader applications. The miniaturization is achieved using fractal technique and the physical parameters of the structure as well as its ground plane are optimized using CST Microwave Studio. The total area of the final structure is 71.6 x 94 mm 2 . The results show that the proposed antenna has good matching input impedance with a stable radiation pattern at 915 MHz, 2.45 GHz, and 5.8 GHz.
TL;DR: Results confirm that total cost of Bayesian classifiers can be further reduced using cost-sensitive learning methods and identify the best classifiers for class imbalanced health datasets through a cost-based comparison of classifier performance.
Abstract: Public health care systems routinely collect health-related data from the population. This data can be analyzed using data mining techniques to find novel, interesting patterns, which could help formulate effective public health policies and interventions. The occurrence of chronic illness is rare in the population and the effect of this class imbalance, on the performance of various classifiers was studied. The objective of this work is to identify the best classifiers for class imbalanced health datasets through a cost-based comparison of classifier performance. The popular, open-source data mining tool WEKA, was used to build a variety of core classifiers as well as classifier ensembles, to evaluate the classifiers’ performance. The unequal misclassification costs were represented in a cost matrix, and cost-benefit analysis was also performed. In another experiment, various sampling methods such as under-sampling, over-sampling, and SMOTE was performed to balance the class distribution in the dataset, and the costs were compared. The Bayesian classifiers performed well with a high recall, low number of false negatives and were not affected by the class imbalance. Results confirm that total cost of Bayesian classifiers can be further reduced using cost-sensitive learning methods. Classifiers built using the random under-sampled dataset showed a dramatic drop in costs and high classification accuracy.
TL;DR: The number of obstacles considered for path planning is reduced by introducing a space in which the obstacles lie, which makes the algorithm suitable to be applied in real-time and will greatly accelerate the development of autonomous cars in the near future.
Abstract: Path planning has been an important aspect in the development of autonomous cars in which path planning is used to find a collision-free path for the car to traverse from a starting point Sp to a target point Tp The main criteria for a good path planning algorithm include the capability of producing the shortest path with a low computation time Low computation time makes the autonomous car able to re-plan a new collision-free path to avoid accident However, the main problem with most path planning methods is their computation time increases as the number of obstacles in the environment increases In this paper, an algorithm based on visibility graph (VG) is proposed In the proposed algorithm, which is called Equilateral Space Oriented Visibility Graph (ESOVG), the number of obstacles considered for path planning is reduced by introducing a space in which the obstacles lie This means the obstacles located outside the space are ignored for path planning From simulation, the proposed algorithm has an improvement rate of up to 90% when compared to VG This makes the algorithm is suitable to be applied in real-time and will greatly accelerate the development of autonomous cars in the near future
TL;DR: A fault-tolerant routing problem has been reduced to the solution of the optimization problem of nonlinear programming and the efficiency of the proposed model and adequacy of the calculation results obtained are confirmed.
Abstract: In this paper, the consistent solution for default gateway protection within fault-tolerant routing in an IP network is presented, and it is based on development of the appropriate flow-based mathematical model. Within the framework of the proposed model, a fault-tolerant routing problem has been reduced to the solution of the optimization problem of nonlinear programming. Fault-tolerance functions are implemented by introducing additional routing variables responsible for the calculation of a backup default gateway and the corresponding path (multipath) in the transport network. Several examples have demonstrated features of the application of the proposed model in solving default gateway protection within fault-tolerant routing for the case of realization of single path and multipath routing. The results have confirmed the efficiency of the proposed model and adequacy of the calculation results obtained.
TL;DR: This study aims to map the method of software quality measurement in any models of quality and showed that though the model of ISO SQuaRE has been widely used since the last five years and experienced the dynamics, the researchers in Indonesia still used ISO9126 until the end of 2016.
Abstract: Software quality is a key for the success in the business of information and technology. Hence, before be marketed, it needs the software quality measurement to fulfill the user requirements. Some methods of the software quality analysis have been tested in a different perspective, and we have presented the software method in the point of view of users and experts. This study aims to map the method of software quality measurement in any models of quality. Using the method of Systematic Mapping Study, we did a searching and filtering of papers using the inclusion and exclusion criteria. 42 relevant papers have been obtained then. The result of the mapping showed that though the model of ISO SQuaRE has been widely used since the last five years and experienced the dynamics, the researchers in Indonesia still used ISO9126 until the end of 2016.The most commonly used method of the software quality measurement Method is the empirical method, and some researchers have done an AHP and Fuzzy approach in measuring the software quality.
TL;DR: In this article, a real time experiment has been conducted to analyze the effect of various factors like irradiance, temperature, and angle of tilt, soiling, shading on the power output of the pv module.
Abstract: Energy is the driving force in all the sectors as it acts like an index of standard of living or prosperity of the people of the country. However heavy dependence on fossil fuels leads to global warming, hence there is a need for the use of clean, sustainable, and eco friendly form of energy. Among the various types of non-conventional energy solar energy is the fundamental as it is abundant, pollution free and universally available.Even though the main input to the PV system is the solar radiation still there are other factors which affects the efficiency of the pv module. In this paper real time experiment has been conducted to analyze the effect of various factors like irradiance, temperature, and angle of tilt, soiling, shading on the power output of the pv module. Temperature is a negative factor which reduces the efficiency of the module and can be reduced by various cooling arrangements. Presence of dust particles and shading obstructs the incident solar radiations entering the panel and the effect is seen in the iv and pv curve .For better performance solar tracking at maximum power point is suggested to improve the power output of the pv module.
TL;DR: A cloud based system for real time targeted advertising based on tweet sentiment analysis is designed and implemented using the big data processing engine Apache Spark, utilizing its streaming library.
Abstract: Big Data constituting from the information shared in the various social network sites have great relevance for research to be applied in diverse fields like marketing, politics, health or disaster management. Social network sites like Facebook and Twitter are now extensively used for conducting business, marketing products and services and collecting opinions and feedbacks regarding the same. Since data gathered from these sites regarding a product/brand are up-to-date and are mostly supplied voluntarily, it tends to be more realistic, massive and reflects the general public opinion. Its analysis on real time can lead to accurate insights and responding to the results sooner is undoubtedly advantageous than responding later. In this paper, a cloud based system for real time targeted advertising based on tweet sentiment analysis is designed and implemented using the big data processing engine Apache Spark, utilizing its streaming library. Application is meant to promote cross selling and provide better customer support.
TL;DR: The general projection model based on collinearity condition is reviewed and used to determine a common projective plane from images and an initial attempt shows a promising result.
Abstract: This paper presents a preliminary result of ongoing research on unmanned aerial vehicle (UAV) for cooperative mapping to support a large-scale urban city mapping, in Malang, Indonesia. A small UAV can carry an embedded camera which can continuously take pictures of landscapes. A convenient way of monitoring landscape changes might be through accessing a sequence of images. However, since the camera’s field of view is always smaller than human eye’s field of view, the need to combine aerial pictures into a single mosaic is eminent. Through mosaics, a more complete view of the scene can be accessed and analyzed. A semi-automated generation of mosaics is investigated using a photogrammetric approach, namely a perspective projection which is based on collinearity condition. This paper reviews the general projection model based on collinearity condition and uses that to determine a common projective plane from images. The overlapped points for each RGB channel are interpolated onto that of orthographic plane to generate mosaics. An initial attempt shows a promising result.
TL;DR: In this article, the authors find that e-Health in Indonesia has been applied since 1985 and the number and variety of technologies and features provided are decreasing and the focus shifted to further analysis of the problems needed to be solved and provision of technologies only relevant to those problems, but they still conducted by certain educational institutions and their uses are not evenly distributed throughout Indonesia.
Abstract: Indonesia is the largest archipelagic country in the world. There are five major islands and thousands of smaller islands, most of which are in the distance. Therefore, its health services are hardly distributed. E-Health is one of the methods expected to deal with the problem of distance in health services. The development and use of technology in health area has given rise to several studies on the applications of e-Health in Indonesia. Based on a number of studies, we find that e-Health in Indonesia has been applied since 1985. The technologies and features used from time to time were growing in some period of time. However, the study also shows that from that point of time the number and variety of technologies and features provided are decreasing and the focus shifted to further analysis of the problems needed to be solved and provision of technologies and features only relevant to those problems. The development of e-Health applications in Indonesia has given promising results in providing health services, but they are still conducted by certain educational institutions and their uses are not evenly distributed throughout Indonesia.