International Journal of Soft Computing and Engineering

Journal Information
EISSN : 2231-2307
Total articles ≅ 61

Latest articles in this journal

Bhushan Hemant Dhimate, Manjiri Vitthal Khopade, Avadhoot Yogesh Dhere, Supriya Dhanaraj Dhumale
International Journal of Soft Computing and Engineering, Volume 11, pp 40-43;

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;

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;

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.
Edmund Muthigani, Stephen Diang'A, Wanyona Githae
International Journal of Soft Computing and Engineering, Volume 11, pp 8-12;

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;

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.
International Journal of Soft Computing and Engineering, Volume 11, pp 51-56;

Cloud computing the technology which have the capability of modifying the method computing strongly, and storage resources will be accessed shortly. User Identification is an entity to detect the user who using the system or website. In information technology the protection of information consistently become a major issue to handle. The data might place in various locations in the world since it become particularly serious. The two main factors regarding cloud technology are information protection and security. The cloud operators can easily reach the sensitive information that affects the data security and protection measures. Therefore, this research protocol mainly focuses on secure data storage that always been a significant feature of quality of service. To guarantee the ‘rightness of users’ information in cloud storage system a Protection Aware User Identity and Data Storage (PAUIDS) algorithm is proposed that separates the document and independently stores the user information in the cloud storage servers. The proposed algorithm reduces the encryption and decryption time in a cloud storage system and providing secure and efficient data storage in cloud environments.
Nek Dil Khan, , Muhammad Taimoor Khan, Duaa, Adil Zaman
International Journal of Soft Computing and Engineering, Volume 11, pp 1-7;

Recently a rapid increase has been seen in the technology and health care became an unavoidable sector because an enormous amount of data is collected day to day. The Big data analytics has many uses and it is associated to big data. It gives an important judgment in the area of health care. This paper aims to present a review of big data in health care that how big data can aid the healthcare. In this paper multiple research paper has been reviewed and the limitations and research gaps of these papers has been discussed accordingly.
Ravindra Kumar, Navvis Healthcare Technical Account Manager
International Journal of Soft Computing and Engineering, Volume 11, pp 49-50;

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.
Sharanappa P. H., Mahabaleshwar S. Kakkasageri
International Journal of Soft Computing and Engineering, Volume 11, pp 23-31;

The use of wireless sensor technology in various Internet of Things (IoT) applications is growing rapidly. With the exponential increase of smart devices and their applications, collecting and analyzing data is gradually becoming one of the most difficult tasks. As sensor nodes are powered by batteries, energy efficiency is essential. To that intention, before passing the final data to the central station, a sensor node should reduce redundancies in the received data from neighbor nodes. There will be some redundancy in the data because different sensor nodes typically notice the same phenomenon. Data aggregation is one of the most important approaches for eliminating data redundancy and improving energy efficiency, as well as extending the life time of wireless sensor networks. Furthermore, the effective data aggregation technique might help to reduce network traffic. In this paper we have proposed cluster based data aggregation using intelligent agents. The performance of the proposed scheme is compared with Centralized Data Aggregation (CDA) mechanism in IoT.
Mohit Singh, Shobha G
International Journal of Soft Computing and Engineering, Volume 10, pp 21-26;

With the rise of mobile devices and their usage, a lot of development has been made in terms of the development of applications for mobile devices. Traditionally, app development was restricted to the particular operating system, and a separate codebase was required for applications to be developed for multiple operating systems. A new paradigm of development took place in recent years which was of Hybrid app development, leading to the development of multiple frameworks which allowed for a single codebase to be used for multiple operating systems. This paper explores the features and analysis of different hybrid app development frameworks available in the market. A comprehensive analysis has been made to compare the different frameworks which are cross-platform and support web, Android, and iOS platforms. The analysis shows that all the frameworks have their merits and usage of anyone framework over others can vary from case-to-case basis. The detailed analysis of the features will bring a general conclusion over the choice of framework.
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