International Journal of Soft Computing and Engineering

Journal Information
EISSN : 2231-2307
Total articles ≅ 65
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C. Sunitharam, Sayimpu Vinay, Sannapaneni Anand
International Journal of Soft Computing and Engineering, Volume 12, pp 1-4; https://doi.org/10.35940/ijsce.a3544.0312122

Abstract:
The internet was meant to shorten the distance between the people to ground breaking level. It is essential tool for everyday task. But with this, internet service providers are allowed to share and sell their customers web browsing data without their concedence. sometimes, sold data makes security weakened and makes unprecedented way to spammers. With third party trackers, privacy gone under more risk factor, which makes no deterrent for Cyberattacks, terrorism and other phenomena. In today’s hig h tech environment organizations, Government and individual user has to use web browsers and internet for accessing web data. nowadays some Advertisers trying to mislead users. So, we propose a new way of browsing anonymously, untraceable web surfing and s trong firewall using new browser. There will be no bookmarks, Advertisements and no selling of data to marketers.
C. Sunitha Ram, S. Pavan Kumar, M. Shivashankaran
International Journal of Soft Computing and Engineering, Volume 12, pp 5-11; https://doi.org/10.35940/ijsce.a3549.0312122

Abstract:
This study motivates farmers to use an online business stage to shape their income without any middlemen. Online business is one of the quick enterprises on the planet. Numerous organizations were at that point moved to online business and producing immense income inside a brief timeframe. The serious issue is "The farmer who produces nourishment for the country isn't benefitting with the pay". Since there is no such committed stage for farmers to create beneficial pay for their developed items. Existing stages are joined with all classifications (home, kitchen, and electrical apparatuses) of items that could tangle up farmers, and furthermore, the absence of app information is one reason that a farmer will be unable to sell their items on the app. To defeat this, The Bhaaratha Vivasayi app will be useful where a farmer can be ready to sell or buy anything connected with the agribusiness and cultivating classification without middlemen. A basic easy to understand app with numerous rancher merchants and different horticultural items alongside a point-by-point review about the most recent cultivating innovations will definitely shape the cultivating area income. This will help ranchers to get information and save both time and energy. Likewise, new associations and correspondences will be laid out and the item stock will sell effectively with practically no work help. Also, it will help customers to buy organic fresh groceries at a reasonable price directly from farmers. Basically, It is devoted to farmers with all cultivating items like pesticides, seeds, composts, crops, etc. . So, this app will surely play a vital role in uplifting & benefitting framers as well as customers.
International Journal of Soft Computing and Engineering, Volume 11, pp 1-6; https://doi.org/10.35940/ijsce.b3535.0111222

Abstract:
Credit risk as the board in banks basically centers around deciding the probability of a customer's default or credit decay and how expensive it will end up being assuming it happens. It is important to consider major factors and predict beforehand the probability of consumers defaulting given their conditions. Which is where a machine learning model comes in handy and allows the banks and major financial institutions to predict whether the customer, they are giving the loan to, will default or not. This project builds a machine learning model with the best accuracy possible using python. First we load and view the dataset. The dataset has a combination of both mathematical and non-mathematical elements, that it contains values from various reaches, in addition to that it contains a few missing passages. We preprocess the dataset to guarantee the AI model we pick can make great expectations. After the information is looking great, some exploratory information examination is done to assemble our instincts. Finally, we will build a machine learning model that can predict if an individual's application for a credit card will be accepted. Using various tools and techniques we then try to improve the accuracy of the model. This project uses Jupyter notebook for python programming to build the machine learning model. Using Data Analysis and Machine Learning, we attempted to determine the most essential parameters for obtaining credit card acceptance in this project. The machine learning model we built gave an 86 % accuracy for predicting whether the credit card will be approved or not, considering the various factors mentioned in the application of the credit card holder. Even though we achieved an accuracy of 86%, we conducted a grid search to see if we could increase the performance even further. However, using both the machine learning models: random forest and logistic regression, the best we could get from this data was 86 percent.
Shailaj Kumar Shrivastava,
International Journal of Soft Computing and Engineering, Volume 11, pp 7-11; https://doi.org/10.35940/ijsce.b3536.0111222

Abstract:
Digital Technology has changed the education scenario in the educational institutions by enhancing teaching and learning, research and governance. There is great need of adequate infrastructure, better internet connectivity, up to date digital equipment’s, safe platform and digitally competent professionals. In India, higher education institution is evident with the increasing use of ICT, cloud computing, artificial intelligence, robotics and virtual reality in day-to-day practices which enhances competencies and help in aligning with industry-based skills. This article presents the issues related to implementation of digitalization process in higher education institutions.
Edmund Muthigani, Stephen Diang'A, Wanyona Githae
International Journal of Soft Computing and Engineering, Volume 11, pp 8-12; https://doi.org/10.35940/ijsce.a3520.0911121

Abstract:
Background: Adequate descent housing is a universal human rights integral component. Resources’ costs and intensified rural-urban migration increase demand for sustainable housing. Modern knowledge-based-economy uses innovation. Construction industry uses product and process innovation to provide adequate and descent low-cost housing. Kenya adopted innovation practices of slum upgrading that uses cost effective locally available building materials. This study looked at the outcomes; social and economic impacts of innovative construction in housing in the Mathare Valley Slum upgrading project Methods: This post occupancy study used exploratorydescriptive research design. Random sampling was used to sample 384 users of low-cost housing projects in Mathare Valley, Nairobi County. Research instruments included semi-structured questionnaires and interview guides. Pilot study, validity and reliability tests ensured quality of study. Ethical considerations included university approval and consent. Statistical package for social sciences (SPSS) software version 21 was applied to compute the descriptive and inferential statistics. Findings: Slum-upgrading had significant-positive outcome on improved houses and community. Social impacts included communal facilities; assurance of security of tenure; and retained frameworks of establishments. Economic impacts included employment; affordable and durable units (p values <0.05). Upgrading process did not influence rent fees, was corrupt and led to displacement of residents. Conclusion: Slum upgrading process affected positively. Similar projects should consider residents in decision-making.
Kushalatha M R, Prasantha H S, Beena R. Shetty
International Journal of Soft Computing and Engineering, Volume 11, pp 13-22; https://doi.org/10.35940/ijsce.a3522.0911121

Abstract:
Hyperspectral Image (HSI) processing is the new advancement in image / signal processing field. The growth over the years is appreciable. The main reason behind the successful growth of the Hyperspectral imaging field is due to the enormous amount of spectral and spatial information that the imagery contains. The spectral band that the HSI which contains is also more in number. When an image is captured through the HSI cameras, it contains around 200-250 images of the same scene. Nowadays HSI is used extensively in the fields of environmental monitoring, Crop-Field monitoring, Classification, Identification, Remote sensing applications, Surveillance etc. The spectral and spatial information content present in Hyperspectral images are with high resolutions.Hyperspectral imaging has shown significant growth and widely used in most of the remote sensing applications due to its presence of information of a scene over hundreds of contiguous bands In. Hyperspectral Image Classification of materials is the critical application of HSI using Hyperspectral sensors. It collects hundreds of spectrum channels, where each channel consists of a sharp point of Electromagnetic Spectrum. The paper mainly focuses on Deep Learning techniques such as Convolutional Neural Network (CNN), Artificial Neural Network (ANN), and Support Vector machines (SVM), K-Nearest Neighbour (KNN) for the accuracy in classification. Finally in the summary the current state-of-the-art scheme, a critical discussion after reviewing the research work by other professionals and organizing it into review-based paper, also implying about the present status on classification accuracy using neural networks is carried out.
Bhushan Hemant Dhimate, Manjiri Vitthal Khopade, Avadhoot Yogesh Dhere, Supriya Dhanaraj Dhumale
International Journal of Soft Computing and Engineering, Volume 11, pp 40-43; https://doi.org/10.35940/ijsce.a3529.0911121

Abstract:
Text to speech conversion is one of the applications of machine learning. It is widely used in search engines, standalone applications, web applications, chatbots and android applications. But still there is need to upgrade text to speech system so that we can get more interactive and user-friendly application. Traditional text to speech application has monotonous voice as output which does not has emotions in it and seems to be more mechanized. So, there is need to improvise the existing system by embedding the flavour of emotions in it. Existing text to speech cannot be used in story telling applications also it does not provide effective communication. Most of the Text to Speech systems are developed using algorithms such as Support Vector Machine (SVM), Naïve Bayes etc. Emotion Based Text to Speech System will help to improvise the existing Text to Speech system. With the help of machine learning and deep learning algorithm such as Recurrent Neural Network can be used for performing sentiment analysis and semantic analysis on the input text. We are going to use neural network which is more effective and help to maintain a relation between previous word and next word. Emotion based text to speech system will be able to identify four emotions ‘happy’, ‘sad’, ‘angry’ and ‘neutral’. Emotion based text to speech system will be beneficial for educational purpose like listening stories from storytelling applications for young budding children. Emotion based text to speech is going to be serviceable for visually impaired individuals.
International Journal of Soft Computing and Engineering, Volume 11, pp 33-39; https://doi.org/10.35940/ijsce.a3527.0911121

Abstract:
Parkinson's disease is an issue of the central tactile framework that impacts advancement provoking shudders. The tangible cell is hurt in the frontal cortex causing dopamine levels to drop which prompts the condition. Parkinson's is a reformist ailment that causes degeneration of the frontal cortex, provoking both motor and mental issues. While Dysphonia is a voice issue that causes mandatory fits in the larynx muscle, this is one of its indications. While, Bradykinesia, which is ordinarily described as slowness of improvements, is one of the cardinal signs of Parkinson's sickness (PD). Essential clinical rating scales are used usually to measure bradykinesia in routine clinical practice albeit this kind of examination is uneven. It requires clinical investigation, and it can happen starting from the age of 6. Along these lines, this is a starter study that endeavors to recognize connections between Parkinson's contamination factors for basic unmistakable verification of the sickness. There are 1 million cases in India. It is hence reasonable to acknowledge that there is a connection between a patient's ability to talk/make and the development towards Parkinson's as these limits rot as time propels. The mark of the examination was to survey the features of the sound data and the hour of contorting drawing as an extent of bradykinesia. Henceforth to make strong proof that vocalization data and the handwriting test from a patient can assist with dissecting whether they experience the evil impacts of Parkinson's. As needs be, it is at first anticipated that there is an association between the two. We attempt to run distinctive AI classifiers on the data in wants to show up at a high consistency rate that is facilitated with a reasonable runtime. The dataset managed is procured from a new report by the journal, IEEE Transactions on Biomedical Engineering, of various limits of voice repeat. The actual assessment obtained a consistency speed of 95.58% hence we want to show up at a rate close to this or possibly to beat it.
Suyog Gatkal, Vinayak Dhage, Dhanashree Kalekar, Sanket Ghadge
International Journal of Soft Computing and Engineering, Volume 11, pp 44-48; https://doi.org/10.35940/ijsce.a3528.0911121

Abstract:
Nowadays digital data storage and digital communication are widely used in the healthcare sector. Since data in the digital form significantly easier to store, retrieve, manipulate, analyses, and manage. Also, digital data eliminate the threat of data loss considerably. These advantages pushing many hospitals to store their data digitally. But, as the patients reveal their private and important information to the doctor, it is very crucial to maintain the privacy, security, and reliability of the healthcare data. In this process of handling the data securely, several technologies are being used like cloud storage, data warehousing, blockchain, etc. The main aim of this survey is to study the different models and technologies in the healthcare sector and analyses them on different parameters like security, privacy, performance, etc. This study will help the new developing healthcare systems to choose appropriate technology and approach to build a more efficient, robust, secure, and reliable system.
Ravindra Kumar, Navvis Healthcare Technical Account Manager
International Journal of Soft Computing and Engineering, Volume 11, pp 49-50; https://doi.org/10.35940/ijsce.a3521.0911121

Abstract:
The increasing interconnection in the world now presents the customers with customization on delivery of a product, service, and experience. The increasing interconnection is recording a very high rise and there is a challenge on ensuring that the service and the product delivery is stable. However, artificial intelligence has availed a solution to the stabilization and has been a solution to the modern world problems. Artificial intelligence has achieved the development of facial recognition technology without messing up with citizen's rights and firms.
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