Browse Items (11858 total)
Sort by:
-
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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). -
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. -
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. -
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). -
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. -
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. -
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. -
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. -
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. -
Machine learning approach for automatic solar panel direction by using nae bayes algorithm
The upsurge in fuel prices are pointing out the fact that, the deficiency of conventional form of natural resources and building dams can never fulfill the demand of the growing population and it is exponentially increasing the electricity demand. Electricity is a day-to-day component, which is utilized for lighting, running appliances, machines. Moreover a large number of people are now switching to electric cars. Henceforth, it is equally important to achieve self-sustainability in energy needs and also it is necessary to have an infinite energy source. Sustainable power is the solitary solution to resolve this issue. On the other hand, the Indian government is promoting solar technology a lot in the year 2021 by providing subsidies to a maximum limit of 65% for the installation of home solar projects and this encourages people to switch to electric vehicles to reduce the pollution. This article presents a machine learning based dual-axis solar tracker to enhance the energy harnessing efficiency. Furthermore, the proposed method utilizes Nae Bayes algorithm to develop a better solution for producing higher energy from the solar panel. The Nae Bayes algorithm is a type of machine learning algorithm, which has been used to predict the reliable direction. This proposed method generates higher electricity, when compared with the traditional method. The experimental results aim to fix the north east direction of solar panel that produces 17.4 watts per hour, wherein the proposed method produces 24.8 watts. It is indicated that, more than 25% additional power generation is obtained by using Nae Bayes algorithm method. 2021 IEEE. -
Removal of Artifacts from Electroenchaphalography Signal using Multiwavelet Transform
The signal from the brain can be recorded using Electroenchaphalography (EEG). The proposed work summarizes a unique method which is used for the removal of mixed artifacts presented in the electroencephalography signal during the acquisition process. Artifacts comprises of various bio-potential unit such as electrooculogram, electrocardiogram, and electromyogram. These artifacts are referred as a noise sources which is responsible for the complexity of the EEG signal. The artifacts obtained from the EEG signal leads towards improper diagnosis of pathological conditions. The EEG signal which is obtained from the brain is the multi-dimensional signal with the various statistical properties. Time consumption of the EEG signal is not reproducible due to the biological properties of the signal. The information of the EEG signal consists of the data of the neuron levels which is collected for every millisecond with the temporal resolution scale. In account of special cases, EEG signal contains noise and artifacts where information is collected using the extraction of signals. To obtain the information of the artifacts the proposed technique is used to maintain higher accuracy in the extraction process. The proposed technique consists of multiwavelet transform to remove the artifacts from the input EEG signal. In the proposed multiwavelet transform, the signal which consists of noisy features can be decomposed using GHM and thresholding technique. This experimental analysis shows the removal of artifacts from the EEG signals. The pathological conditions are removed which leads to the increase in the accuracy of the system. Also, this research findings shows that the proposed multiwavelet transform based approach outperforms significantly with respect to conventional approaches. The reconstructed EEG signal has the lesser reliability range which is measured in-terms of signal to noise ratio and power spectral density. Published under licence by IOP Publishing Ltd. -
Novel hybrid metamaterial to improve the performance of a beamforming antenna
This paper investigates the design and implementation of a novel hybrid metamaterial unit cell to improve a beamforming Wi-Fi antenna's performance. The proposed metamaterial unit cell is created on an FR-4 substrate (?? = 4.4) and a thickness of 1.6 mm. The metallization height of the unit cell is maintained at 0.035 mm. The designed metamaterial unit cell is simulated using HFSS Ver. 18.2 to verify the double negative behaviour. The unit cell consists of five Split Ring Resonators (SRR's) at the bottom and a hexagonal ring of six triangles. Initially, a conventional inset fed microstrip patch antenna is designed then an array of the proposed unit cell is created and used as a superstrate to study the performance. A Three Element Antenna Array (TEAA) is designed to operate at 2.4 GHz Wi-Fi band, and the superstrate created out of the proposed unit cell is used to study its effect. Metamaterial superstrate improved the conventional Single Element Antenna (SEA) gain by approximately 2 dB. Superstrate with TEAA exhibited an improved gain of 1 dB over TEAA. Published under licence by IOP Publishing Ltd. -
Comparison of HOG and fisherfaces based face recognition system using MATLAB
Face recognition and validation is not an easy task due to barriers in between like variation in pose, facial expressions and illumination. There are many algorithms available to build a face recognition system. One such popular method of approach is the Histogram of Oriented Gradients (HOG). It is a simple but effective algorithm. Even though it gives satisfactory results, it sometimes mismatches query image with irrelevant images, especially in poor lighting conditions. This paper presents a more accurate technique called Fisherfaces. It is a more reliable method for face recognition and validation. Fisherface algorithm is utilized primarily for reducing the dimensionality of the feature space. Fisherface method for image recognition involves a series of steps. Firstly, the face space dimension is reduced using Principal Component Analysis (PCA) method, then the Linear Discriminant Analysis (LDA) method is used for feature extraction. Fisherface method produced good results even under complex situations like varying illumination conditions and images with different poses and expressions which is a major drawback of HOG. Fisherface algorithm can reach a maximum accuracy of 96.87%. Error Correcting Output Code (ECOC) is the classifier used for both HOG and Fisherfaces. 2021 IEEE.