VOLUME 9, ISSUE 9, SEPTEMBER 2020

Abstract: To develop security critical web applications, specifying security requirements is important, since 75% to 80% of all attacks happen at the web application layer. I adopted security requirements engineering methods to identify security requirements at the early stages of software development life cycle to minimize vulnerabilities at the later phases. In this paper, I present the evaluation of Model Oriented Security Requirements Engineering (MOSRE) framework and Security Requirements Engineering Framework (SREF) by implementing the identified security requirements of a web application through each framework while developing respective web application. I also developed a web application without using any of the security requirements engineering method in order to prove the importance of security requirements engineering phase in software development life cycle. This study led the requirements engineers to use MOSRE framework to elicit security requirements efficiently and trace security requirements from requirements engineering phase to later phases of software development life cycle for developing secure web applications. Keywords: Requirements engineering, security mechanism, security requirements, security requirements engineering, web applications and vulnerabilities.

Abstract: An overview of Educational Data mining is discussed in this paper. It introduces the concepts and importance of Data Mining, which has led to evolve educational data mining and its applications. It also illustrates nature of data used in Educational Data Mining, nature of Patterns for Educational Data Mining based on the kinds of knowledge to be mined, the kinds of technologies used, and popular tools used in various kinds of applications that are targeted. Finally, major challenges in the field of educational data mining are also highlighted. While taking a general overview of educational data Mining, a brief focus on technologies used in educational data mining are also covered.

Keywords: Educational Data Mining (EDM), Statistics, Data Mining, Prediction, Technologies in EDM, Challenges in EDM, Applications.  

Abstract: With the growth in mobile phone use, there has been inevitable increase and proliferation of mobile phone Base Transceiver Stations (BTS), accompanied by public concern for possible health impacts associated with exposure to Electromagnetic Waves (EMW) emanating from BTS. This survey was carried out to determine the awareness of inhabitants about the health problems associated with GSM Base Transceiver Stations (BTS) due to the exposure of people to EMW. The study area covers selected BTS in Buwaya, Gonin Gora and Maraba Rido in Chikun local government area; and Kakuri in Kaduna south local government area. These sample areas were selected due to the high population density. A sample size of 400 was selected randomly based on the literacy level of the respondents. Data was collected from respondents through structured questionnaire. The data collected was analysed using tables of frequency and percentages, and bar charts. A test of statistic was conducted with Chi Square test. The results showed that about 78.5% have no knowledge of electromagnetic radiation and its consequences on human health; and the Chi Square test based on the respondent’s duration of living near BTS showed that EMR affects human health. However, no medical tests were carried out to confirm the claims by respondents and the result of the study was based on what the respondents reported.

Keywords: Base Transceiver Station or Base Transmitter Station (BTS), Electromagnetic Radiation (EMR), Electromagnetic Wave (EMW), Global System of Mobile Telecommunication (GSM), Antenna, Radio Signals.

Abstract: Six Sigma is a method that provides organizations tools to improve the capability of their business processes. This increase in performance and decrease in process variation helps lead to defect reduction and improvement in profits, employee morale, and quality of products or services. In the era of cut-throat competition, especially in automobile sector, success of an organization resides in its ability to respond quickly to the needs of its customers. These customer needs must be attended with minimum manufacturing costs, minimum lead time to launch the product in market, and delivering better performance than the existing competitors in the market. Six Sigma is a powerful methodology which ultimately helps in cost reduction. Because of defect prevention and improved product and processes, it leads to increase in profitability and market share. This is accomplished through the use of two Six Sigma sub-methodologies. By adopting Design For Six Sigma methodology in the design stage itself leads to launch of a product with maximum quality performance, with tighter tolerances, and with reduced or no defects. This paper considers cost of poor quality as the loss imparted to society from the time the product is shipped, and deals with the applications and benefits of Six Sigma methodology and its positive impact on cost of poor quality. A case study is presented, which enabled application of six sigma methodology in wider range of manufacturing activities. This paper is of value to the researcher in the field of quality management, as well as professionals in the manufacturing industry, wherever the quality improvement is an issue. Quality costs or Cost of Quality is a means to quantify the total cost of quality related efforts and deficiencies. Six Sigma is a strategic initiative to boost profitability, increase market share and improve customer satisfaction through statistical tools that can lead to breakthrough quantum gains in quality. A case study is carried out in automobile casting industry, where Six Sigma tools i.e. Taguchi approach for the defect reduction is applied, which analyses various significant process parameters of the casting process at a foundry, based at north India. This study aims to develop a novel approach to create Six Sigma projects and identify the critical parameters of these projects. The optimized parameters obtained using Taguchi method will then be tested in an industrial case study and a trade-off will be made to finalize the recommended process parameters used in manufacture automobile parts.

Keywords: Define Measure, Analyse, Improve and Control (DMAIC), Quality costs or Cost of Quality, Taguchi approach, Six Sigma, automobile parts, minimum manufacturing costs, minimum lead time and increased market share.

Abstract: The native concept of 3D human localization, from monocular color images is an ill posed problem. Considering the limitations of neural networks, we compare various loss functions that are based on a variety of distributions. Monoloco is a 3D pedestrian localization architecture which uses a lightweight feed forward neural network and predicts the distance of pedestrians, from the camera and the uncertainty associated with its prediction based on Laplacian loss. We trained two individual models on Kitti dataset with updated unnormalization methods, changed dataset sizes and Losses which are Cauchy and Generalized Extreme Value (Gev) losses. These newly trained models using Monoloco were observed to perform better. We evaluated these trained models on Kitti dataset and found improvised results than existing Monoloco. 

Keywords: Deep Learning, Kitti, Nuscenes, MonoLoco, Loss Function,Neural Networks.

Abstract: Machine learning algorithms come under different categories like supervised, unsupervised and Reinforcement learning. In each case many algorithms are there that serves specific purposes like Regression, Classification, Clustering, and Dimensionality Reduction and so on. Regression type algorithms are mainly used for prediction, Classification is used for dividing or categorizing, Clustering is for grouping similar items. In Reinforcement learning it analyses and optimizes the behaviour of an agent based on the environment. We have to choose the correct algorithms available based on the output required. Because for a single problem we may have different solutions but the thing is we have to choose the one with high accuracy and it should fit for any updating in the datasets.

Keywords: Machine Learning, Classification, Kernel, Hyper Planes and Confusion Matrix

Abstract: The emergence ofehealth systemshas shown that there is potential for the improvement of quality of healthcare servicedelivery. Health facilities use Health Information Systems (HIS)to make their workflow more efficient as compared to the traditional manual operations.Ehealth systems encompasses all HIS tools and applicationsthat are meant to improve user’s experiences with the service.HIS tools are meant to enhance/improve collaboration amongst healthcare practitioners, facilities administration, commodities management, patient record keeping and hence quick evidence baseddecision-making. This paper investigated user’s perspectives of ehealth in terms of service delivery. It provides the quantitative and qualitative methodology, which comprised of a random sample of key stakeholdersand the use of questionnaire and interviews. The study found that there is a positive user perception on the potential benefits of ehealth systems based on user experiences and expectations. Keywords:Ehealth,Health Information Systems, Healthcare Quality, Patient Centered.

Abstract: The institution of higher education close due to reduce and control the rapidly spread of Covid-19 toprevent from infection of novel corona virus among young population. Government of India and UGC has initiated   intensive measures to control, prevent and protect to all higher education students, teaching staffs and other non-teaching staffs from Covid-10. The Covid-19 outbreak brought not only the risk of death from the viral infection but also unbearable psychological pressure to students in higher education across the India.The outbreak of Covid-19 has affected educational systems worldwide, leading to the near-total closures of schools, universities and colleges. University and College students are facing a variety of challenges in the wake of the COVID-19 outbreak.  

Keywords: Higher Education, Students, Examination, Covid-19, Online, Syllabus.

Abstract: Image Enhancement techniques are widely used to improve the quality of the images.  This technique is used to smooth the images or detecting the edges of the images. Image processing is to manipulate the images by using algorithms. In this paper the cotton leaf disease such as Bacterial Blight, Anthracnose, Leafhopper damage symptom images are capture. The captured images are processed with images sharpening techniques such as Unsharp Masking, Gaussian Sharpening and images enhancing techniques such as Color Histogram Equalization are used to improve the quality of images. The image dataset are measured with PSNR and MSE values. The results of the three technique are compared with MATLAB Image processing ToolBox, the Unsharp Masking technique results with better PSNR and MSE measurement.

Keywords: Cotton leaf, Bacterial Blight, Anthracnose, Leafhopper, PSNR, MSE, Enhancement Techniques.

Abstract: In this paper, the Aerial Platform (AP) Wireless Sensor Network (WSN) is modelled and demonstrated for surveillance applications such as traffic monitoring and management. The system geometrical model and coverage parameters of AP such as coverage diameter, beamwidth of beam patter, and coverage area per AP are investigated where the AP network design equations are deduced for several WSN scenarios which include the coverage of rural areas linked by highways and urban cities as well. Also, the sensor data rate and density in the coverage area are related to the AP coverage parameters and a set of design curves are developed which determines the coverage diameter required per AP at a specific sensor data rate and uplink capacity for the whole AP covered area. The sensors are assumed of two kinds which are low-speed sensors for monitoring slowly varying physical quantities and high-speed sensors such as those used in video monitoring. Keywords: Aerial platforms, wireless sensor network, traffic monitoring, surveillance systems.

Abstract: This project is based on safety measures of vehicles.It is inspired by the daily observations while driving at night related to the headlight conditions of the rear vehicle which causes dazzling in the eyes of the driver in the front vehicle.With increase in number of vehicles comes increase in number of road accidents, though the automobile sector have achieved a huge margin on reducing the number of accidents by advancing the safety systems in the vehicles still one major cause of accidents ( also the most common cause. ) is the blinding vision of the driver while night driving due to the headlight of the approaching vehicle or the vehicle behind. Human eyes are very sensitive to the light, if eyes suddenly comes in contact with the light after darkness, cornea present in eyes gets contract i.e. vision gets blank and require some time to recover the vision. Due to which while night drives the upper mode of other vehicle blinds the vision of the driver which in many cases leads to some deadly accidents, to overcome the issue a Headlight Automation System has been introduced which will surely contribute in making night drive safe. The circuit, working and need of the system is briefly discussed in this paper.

Keywords: Microcontroller,Ultrasonic Sensor(HC-S04),Led,Headlight,etc.

Abstract: Cyber securityis concerned with protecting information, hardware, and software on the internet from unauthorized use, intrusions, sabotage, and natural disasters. The numerous ways in which computer systems and data can be compromised has made cyber security a growing field. Data needing cyber security could be online banking information, medical or financial information, and private photographs. However, cybersecurity is not always easy to implement as there are threats to cyber security itself. Cyber security threat is any malicious act that seeks to damage or steal data and disrupt digital life in general. This paper analyses and identifies the various threats on the internet and proposes possible solutions to enable internet users keep on guard.  

Keywords: Threats, CyberSecurity, Internet, Digital Life.

Abstract: Crop disease detection system focuses on providing the information about the crop disease prediction, pesticide recommendation and the amount of pesticide or chemicals to be used for an unhealthy crop. The user, who is the Farmer clicks a picture of the unhealthy crop and uploads it to the server by using the android application installed in mobile or by using webpage. After uploading the image the farmer clicks the Predict button which is displayed over screen. Then uploaded image is processed and accordingly the features of that image are extracted from it. Based on these features, classification of image is done using Convolutional neural network and the classes having maximum probability is selected for further process. Then the result consisting of the disease name is retrieved and shown to the user. This result is then uploaded into the message table in the server and retrieved in mobile application or on the webpage where corresponding information such as pesticide name, amount of pesticide to be used and organic pesticides which are stored. Now the Farmer will be able to retrieve the complete information in a presentable, readable format on the screen of the Application. Keywords:Pesticide, classification, Extraction, Convolutional neural Networks

Abstract: Now days the usage of Internet and online marketing has become very popular. Millions of products and services are available in online marketing that generate huge amount of information. Social media sites can have a major influence in expanding the span of this kind of story. Fake news is a news created to intentionally misguide or mislead readers. Fake news is spread mainly for gaining political or financial incentives. There has been a large surge of fake news in recent times due to the immense use of social media and online news media. It has become much easier to spread fake news then how it used to be earlier. This kind of fake news when spread may have a severe effect. Hence it is extremely essential that certain measures should be taken in order to reduce or distinguish between real and fake news. This paper presents a survey on fake news detection based on various supervised, unsupervised and semi supervised data mining and machine learning techniques. Keywords:Machine Learning, Fake News, supervised, unsupervised and semi supervised

Abstract: This work proposes the characterization of improved region growing level set segmentation using Magnetic Resonance Imaging for brain & heart images. For this, it uses an optimization approach to equalize the contrast of MR image. To enable the use of voxel gray values for interpretation of disease, it provides a new method, energy minimization with a spline model, to correct the severe intensity in homogeneity that arises from the surface coil array. A level set segmentation method is used that provides proper segmentation of tissues in MR image. The important parameter is entropy which is minimized by changing the knots.All simulations are done in MATLAB.

Keywords: MR images, Region Growing Segmentation, Image Processing, Spline Method etc