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The world of communication & computing platform in research perspective: Opportunities and challenges
Computing paradigms are introduced for solving complex problems by analyzing, designing and implementing by complex systems. Computing can be defined as the effective use of computer or computer technology to solve tasks that are goal oriented. Computing is used in development of producing scientific studies, building intelligent systems, channeling different media for communication. Over the last few years, internet became so popular which lead to the increase in computer processing capacity, data storage and communication with one another. Computing has evolved from one technology to another in its field and formed a robust framework over the years. In this paper a survey on different computing paradigms like evergreen computing is cloud computing, to deal with basic scheduling is grid computing, for multi task handing is parallel computing, to handle smart phone data's that is mobile computing, cluster computing, and distributed computing is carried out. These technologies improved the way computing functions and made it easier to the computer world. The applications and research issues of the most of the computing paradigms are discussed in this article. The recent research issues in computing platform are scheduling and security. The scheduling is dealing with data processing from one computing platform to other computing device. Security is one of the important research issues. 2021 IEEE. -
A Review on DC-DC Converters with Photovoltaic System in DC Micro Grid
Photovoltaic system is the low-cost source of electrical power in high solar energy regions. The benefits of PV system are like nonpolluting and minimum maintenance. Solar energy changes as per irradiance and temperature and also one factor which reduces the power output is the partial shading in the cells. Hence f o r th, various algo rith ms a r e p u t fo rth to obta in t h e maximum power f r o m t h e PV arrangement and dc-dc converters intend to regulate the supply. The concept of micro grid is emerging as an excellent solution for inter connecting renewable energy sources and loads. DC micro grid is a necessity in today's world. There is wide increase in usage of DC systems in commercial, residential and industrial systems. DC micro grids are dominant in reliability, control and efficiency. Direct current architectures will be used in demand in the future electrical distribution systems. This paper reviews on all above concepts to be used in DC micro grid for future DC applications. Published under licence by IOP Publishing Ltd. -
Assesment of bone mineral density in X-ray images using image processing
X-ray application in medical fields has given rise to various research challenges related to bone, due to its wide usage in finding out the disease related to human anatomy. It has lot of research challenges to solve using available wide application of medical imaging techniques and inspired by this, a novel X-ray images based survey was conducted to understand the role of Xray images in medical field. Bone mass density identification is the standard procedure to monitor the risk of fracture in bone using DEXA. Lot of research has been carried out to calculate BMD using X-ray images and it provided prominent results. Since Xray is economically affordable and very economical compared to DEXA, we have decided to work on X-ray images. This paper explains us about various current advancements and disadvantages with respect to X-ray image in medical sector and various techniques related to BMD calculation. X-ray images characteristics and its fundamentals in the medical field for identifying bone related diseases are also discussed. 2021 Bharati Vidyapeeth, New Delhi. Copy Right in Bulk will be transferred to IEEE by Bharati Vidyapeeth. -
Perceptive VM Allocation in Cloud Data Centers for Effective Resource Management
Virtual Machine allocation in cloud computing centers has become an important research area. Efficient VM allocation can reduce power consumption and average response time which can benefit both the end users as well as the cloud vendors. This work presents a perceptive priority aware VM allocation policy named P-PAVA algorithm, which takes into account the priority of an application along with its compute, memory and bandwidth requirement. The algorithm performs allocation of the applications based on the priority it gets using a machine learning based prediction model. Furthermore, to reduce the overhead of the allocation algorithm, parallelization is employed before assigning various workloads. To achieve this, the algorithm employs the First fit technique as a baseline for the requests allocation with a criteria as low priority. When compared to the state of the art algorithm for VM allocation for priority aware applications, P-PAVA performs better on several criteria such as average response time, execution time and power consumption. 2021 IEEE. -
Machine learning based Unique Perfume Flavour Creation Using Quantitative Structure-Activity Relationship (QSAR)
Artificial intelligence played a vital role in brings revolutionary changes in the field of perfumery. It is much evident with events including the success of Philyra, exhibitions showcasing the ideas of this concept. Machine learning made it user friendly and more comfortable for the users by means of suggestive interaction. Machine learning also benefited the perfumers in helping them to choose the best combinations and likely successful outcomes. With growing concern about a healthy lifestyle, the thoughts about having an artificial intelligence to predict the user friendliness could be a huge success. This definitely would require a huge database comprising a large detail about diseases and the causes and combinational results of the various chemicals used in perfumery. This system may not be a completely successful one but would be reliable to a better extent. It would gain a positive response from various governmental health departments and would be encouraged by the consumers. Also, another possible development would be Artificial intelligence that is able to predict how long a perfume can last. This would let the consumer choose the one that suits the need. Through this idea we could now get a clear idea about the progress that we have made till this day. Further we can also be driven into vague ideas about how the future of Artificial intelligence would likely grow into. Machine learning and deep learning is a major pillar of artificial intelligence with larger application. Coming to our domain of discussion, artificial intelligence changed the way that things were in the past centuries about fragrance. This article proposed Quantitative structure-activity relationship (QSAR) method is used to predict the best perfume flavour. The proposed system also reduces mean absolute error (MAE). The proposed QSAR is also reducing the chemical composition and increase the perfume quality. 2021 IEEE. -
Harnessing nanotechnology applications and solutions for environmental and climate protection-an overview
Nanotechnology is an emerging technology that has drawn considerable interest from environmentalists. Numerous nano techniques identify Nanotechnology applications as having the potential for imperative advantages and innovation. This work offers a wide-overview of the main beliefs that strengthen s nanotechnology. We focus on the potential applications of nanotechnology for environmental protection and management by thoroughly reviewing past literature. To our understanding, this is an academic, peer-reviewed work to deliver a systematic review of nano-activities in the areas of environmental and climate protection. Our study has been systematically arranged into two different groups (1) Potential applications of nanotechnology in r environmental protection and (2) The best part of Nanotechnology that combats Climate Change. For each of these cases, our contribution is twofold: First, in identifying the technical ways by which nanotechnology can solve environmental risks, and secondly, in briefly presenting its potential advantages. The paper ends with deliberation of challenges and operational barriers that technology needs to overcome to prove its commercial viability and for being adopted for commercial use. 2021 Author(s). -
Assessment of composite materials on encrypted secret message in image steganography using RSA algorithm
The use of the internet in this modern era is increased many fold. The communications between different peers take place in digital form. While sharing the messages between different recipients, the confidentiality of the messages is very important. For creating the high level of security while sharing the secret messages, the cryptographic algorithms are introduced along with steganography. Image Steganography is a methodology used to hide the messages inside of the cover image. Initially, the secret information is encrypted by using the RSA Algorithm. Then the encrypted secret information is hidden in the Least Significant Bit (LSB) of the different components of the color image in such a way that the original quality of the image to be minimized. The recipient of the message is able to retrieve the encrypted secret message from the LSB bit of stego_image and then the cipher text is converted into original plain text by using the RSA algorithm. The proposed algorithm verified and analysed its performance against the different combinations of key pairs. 2021 Elsevier Ltd. All rights reserved. -
A Translator for Indian Sign Boards to English using Tesseract and SEQ2SEQ Model
Language translator for Indian language to English have been developed and it have proven to a challenging domain due to large combination of character in Indic scripts such as Tamil, Kannada and Hindi. In this paper we propose a system which captures Indian printed character and translates it into English, we have discussed the various method and machine learning model that was used to build this system with an accuracy of 87%. 2021 IEEE. -
Unlocking the potentials of using nanotechnology to stabilize agriculture and food production
In the face of alarmingly increasing climate change, agricultural sector is exposed to innumerable and unprecedented challenges globally. This has led to food insecurity worldwide and in order to achieve the required food security at the global level, various methods and techniques have been put forth by researchers from around the world for boosting crop production and ensuring sustainability. Advanced nano-engineering is found to be of great import in improving production in agriculture and increasing input efficiency and minimization of losses. The fertilizers and pesticides, used for increasing and protecting the crop production respectively, can gain not only specific but also wider surface area with the help of nanomaterials, which serve as exclusive agrochemical carriers and assure facilitation of nutrients to target areas with the help of delivery monitoring techniques. Nanobiosensors, an example of the wide ranging nanotools, scaffold the growth of high-tech agricultural farms and also stand proof for the practical and proposed applications of the nanotools in terms of agricultural inputs control and their management precision. Nanosensors the off-spring of the culmination of biology and nanotechnology has an increased potential level in sensing and identifying both the advantageous and adverse conditions of the environment. The other applications of nano-technology include nanofertiliers with release-control techniques for healthy growth and rich yield and productivity of crops, nano-based target delivery approach, also referred to as gene transfer technique, for improved quality of crops, nanopesticides for effective protection of crops and other nanomaterials for promotion of stress tolerance among plants and enhancement of quality of soil [4]. In our review paper, we intend sum up the recent research and studies on the nanotechnology's innovative uses in agriculture to cope up with the ever-increasing necessity for food and sustenance of environment. 2021 Author(s). -
Artificial Intelligence in Data-Driven Analytics for the Personalized Healthcare
Among the various developments in progress over the last decade, we have seen the generous growth of information investigation to take care of, plan, and use a lot of information beneficially. Be that as it may, because the analysis of evidence will only operate for authentic information and have findings as predefined by individuals, explicit principle-based calculations have been developed to broaden the investigation of information, 'Which is usually referred to as 'AI'. AI didn't expect PCs to be personalized unambiguously, which is a definite bit of leeway. In order to break down information and construct complicated equations to foresee models, which was called prescient analysis, AI was then joined with information inquiry. A set of laws characterized by persons, known as prescient equations, drive the prescient inquiry, and are used to break down genuine knowledge in order to predict potential outcomes. 2021 IEEE. -
An Intelligent Business Automation with Conversational Web Based Build Operate Transfer (BOT)
The field of AI chatbots with voice help capabilities has seen significant advancements recently because to the usage of NLP (Natural Language Processing), NLG (Natural Language Generation), and (DNN) Deep Neural Networks. Using the expanding skills of chatbots, which are assisted by AI and ML technologies, a variety of business challenges may be handled. Profitability is one of the most crucial features of a business. This is only achievable if top-level management is aware of the company's costs, revenues, and human resource performance. In this case, an AI-powered chatbot with voice help may be utilised to evaluate corporate data and provide a report. The Bot knows the meaning of words and responds to them thanks to the wordnet in the corpus. Corpus is basically a dictionary for ChatBot. Top management may ask the Bot anything, and the Bot will quickly undertake exploratory data analysis and create a report. The Bot first understands the data using feature selection and then performs exploratory data analysis. After the EDA technique, Bot activates the voice recognition mode to understand the question and give answers. The Bot can use a male or female voice (depending on the developer). Then BOT provides a data table and visualisations for better understanding. 2020 Copyright for this paper by its authors. -
Effect of Heat Treatment on Fatigue Characteristics of En8 Steel
Fatigue failure is an important factor in most of the engineering applications, especially in steel materials, and among the steel materials, it is an important phenomena in medium carbon steels like EN8, which is very commonly used in components like shaft, gears etc., since it is prone to fatigue failure. Hence, without changing the composition, an attempt is made to enhance the fatigue strength by different heat treatment techniques. In this study, the investigation is carried out on heat treatment of EN8 steel material. Various kinds of heat treatment techniques like quench and temper, normalizing and annealing are performed on EN8 steel. After exposure to the heat treatment, the EN 8 steel material specimens are machined as per the ASTM standards and are subjected to RR MOORE test and SN-curves are plotted from the obtained results; the obtained results from the fatigue tests are further analyzed with the help of ANSYS software. Fatigue life and Factor of Safety (FOS) comparisons for EN 8 steel material is made with the structural steel material and it is found from the comparisons, that the heat treatment process enhances the fatigue strength and endurance limit. Published under licence by IOP Publishing Ltd. -
Corroboration of skin diseases: Melanoma, vitiligo vascular tumor using transfer learning
The precise identification of skin disease is an exigent process even for more experienced doctors and dermatologists because there is a small variation between surrounding skin and lesions, a visual affinity between different skin diseases. Transfer learning is the approach which stores acquired knowledge while solving one problem and apply that knowledge to similar problems. It is a type of machine learning task where a model proposed for a task can be used again. Transfer learning is used in various areas like image processing and gaming simulation. Image processing is an evolving field in the diagnosis of various kinds of skin diseases. Here transfer learning is used to identify three skin diseases such as melanoma, vitiligo, and vascular tumors. The inception V3 model was used as a base model. Networks were pre-trained and then fine-tuned. Considerable growth of training accuracy and testing accuracy were achieved. 2021 IEEE. -
Experimental Investigation of Air Circulation Using Duct System in a Non-AC Bus Coach
Public transport is the life line in many of the developing and under developed countries for the safe conveyance, i.e. also consider as economical. The major limitation in public transport (non-AC busses) Air Condition, is the lack of proper air circulation leading to suffocation and vomiting. The present research work emphasis on design and analysis of air flow duct system (non AC Busses) to increase the level of comfortance of the passengers, tools like solidworks software 2016 is used for 3D drawing, Hypermesh software 13.0 is for the discretization and ANSYS Fluent software 16.0 for the Computational Fluid Dynamic (CFD) analysis, from the experimental the airflow is found to be 10 m/s, and from the numerical analysis the airflow is found to be 9.8 m/s, by comparing the experimental and numerical results a negligible deviation of 2% is observed and it is within the limit. Published under licence by IOP Publishing Ltd. -
ML based sign language recognition system
This paper reviews different steps in an automated sign language recognition (SLR) system. Developing a system that can read and interpret a sign must be trained using a large dataset and the best algorithm. As a basic SLR system, an isolated recognition model is developed. The model is based on vision-based isolated hand gesture detection and recognition. Assessment of ML-based SLR model was conducted with the help of 4 candidates under a controlled environment. The model made use of a convex hull for feature extraction and KNN for classification. The model yielded 65% accuracy. 2021 IEEE. -
Envisioning the potential of Natural Language Processing (NLP) in Health Care Management
Natural Language Processing (NLP) continues to play a strategic role in disease detection, intensive care, drug discovery and control of mushrooming infections during the current pandemic. It energizes chat programs to reduce outbreaks during the initial stages of coronavirus infection. NLP technologies have reached new heights in terms of utility, and are at the heart of the success of a multilingual conversation system, and Deep learning language models. It supports more languages around the world. NLP powered AI such as Health map and Copweb platforms track patient requests and perform incident detections. This study looks at the role of NLP and its technologies, challenges, and future possibilities using AI and machine learning for crisis mitigation and easier electronic health records (EHRs) maintenance in the health care industry. This research work explores the strategic approach and potential of NLP which maximizes the value of the EHR and healthcare data, making data a critical and trusted component in improving health outcomes 2021 IEEE. -
Analysis of benchmark image pre-processing techniques for coronary angiogram images
Coronary Artery supplies oxygenated blood and nutrients to the heart muscles. It can be narrow by the plaque deposited on the artery wall. Cardiologists and radiologists diagnose the disease through visual inspection based on x-ray images. It is a challenging part for them to identify the plaque in the artery in the given imagery. By using image processing and pattern recognition techniques, a narrowed artery can be identified. In this paper, pre-processing methods of image processing are discussed with respect to coronary angiogram image(s). In general the angiogram images are affected by device generated noise / artifacts; pre-processing techniques help to reduce the noise in the image and to enhance the quality of the image so that the region of interest is sensed. The main objective of the medical image analysis is to localize the region of interest by removing the noise. It is essential to find the structure of the artery in the angiogram image, for that preprocessing is useful. 2021 IEEE. -
A Comparative Analysis of Biodiesel Properties Derived from Meat Stall Wastes through Optimized Parameters
Biodiesel is considered as alternative green fuels that can be used in Internal Combustion engines as a replacement fuel for conventional diesel. Biodiesel is extracted from vegetable and animal sources which are rich in triglycerides. In this work, an attempt has been made to obtain and characterize the biodiesel from animal wastes such as chicken skin and pig tallow which are available in abundance and at an economical cost within the authors' geographical location. Initially, the feedstock is decontaminated and subjected to conventional heating to convert it into fatty oil. Heating is carried out at different temperatures and for varying time to find out the optimal combination of time and temperature, which would result in maximum fat yield. The fatty oil is then subjected to the trans-esterification process with methyl alcohol in the presence of a catalyst to extract crude biodiesel. A de-canter funnel is used to separate the glycerine and biodiesel from the crude extract. The extracted biodiesel is mixed in different volume percentages with conventional diesel, and various thermochemical properties were evaluated as per ASTM standards. The test result indicated that the properties of the biodiesel blends were well within the limits as prescribed by ASTM standards. Published under licence by IOP Publishing Ltd. -
Rating of Online Courses: A Machine Learning Based Prediction Model
Online courses market has provided an economical and easy access to knowledge. When it comes to make a decision related to purchase of online course, little is known about what attributes can be depended upon to guess the quality of an online course. Ratings for online courses act as a reliable signal for assessing the quality of a course. The study discusses the prediction of ratings for online courses using Artificial Neural Network based on Particle Swarm Optimization (ANN-PSO). The experimental results suggests that ANN-PSO model has the capacity to predict the ratings for online courses on the basis of its attributes with accuracy. 2021 IEEE. -
Power Line Communication Parameters in Smart Grid for Different Power Transmission Lines
In an electrical power system smart grid is a network that renewable energy sources along with smart devices. Communication capabilities of the conventional grid can be improved by the inclusion of superior sensing and computing abilities. Device control, remote management, information collection, intelligent power management is achievable by using communication networks. Wired communication technology is used because of its advantages like reliable connection, free from interference, and faster speed. In this paper, the data communication parameters have been analyzed using Power Line Communication (PLC) with various lengths of transmission lines. An orthogonal Frequency Modulation scheme is used to obtain the minimum BER.MATLAB Programming has been carried out and the results have been compared with the standards and found to be satisfactory. 2021 IEEE.