VOLUME 9, ISSUE 11, NOVEMBER 2020

Abstract: The present work shows the development of a prototype that aims to offer an alternative tool through the implementation of a musical instrument, such is the case of a mat-type electronic keyboard, with the purpose that children with ASD, after interacting with the instrument to way of playing, they can receive motor, sensory, cognitive and emotional stimulation based on the fact that it has been shown that auditory stimulation is an excellent aid in treatments against stress and anxiety, among other different problems of the general population around the world. Keywords: Autism Spectrum Disorder (ASD), Electronic keyboard, Auditory stimulation, Music therapy. Keywords: Autism Spectrum Disorder (ASD), Electronic keyboard, Auditory stimulation, Music therapy.

Abstract: The purpose of this research work is to describe the modeling of the performance of 2D material such as (WSe₂, MoSe₂, etc.,) nanowire FETs and to study their performance as parameter of the transistor’s structure variation like diameter, gate dielectric thickness, and gate dielectric constant. Simulations of ballistic transport in the calculation of the current-voltage (I-V) characteristics for nanoscale single gate FETs. FET channel lengths are getting smaller and high-mobility channel materials are being used, near-ballistic models of FET device physics operation is being realized. Keywords: Nanowire, FET, Semiconductor, Temperature.

Abstract: Advances in technology have a swift impact on any area of life, whether medical or other. Through its analysis of data, artificial intelligence has shown promising results for health care. Over 100 countries have been affected by COVID-19 in no time. People worldwide are vulnerable in the future to its impacts. A control system for the detection of corona virus is imperative. The detection of disease using different AI methods may be one solution to manage the current catastrophe. This article classified textual clinical reports by using classical and ensemble machine algorithms into four classes. The study has used the concept of Natural language processing in which reports are classified using machine learning. In this work we have performed the classification using Naïve Bayes, Support Vector Machine, Logistic regression and Decision tree and we have observed decision tree has outperformed other state of algorithms with an accuracy of 97.8%. Before implementing the classification, feature engineering has also applied. Keywords: Coronavirus, Naïve Bayes, Artificial Intelligence, Natural Language Processing, Precision.

Abstract: This study introduces the idea of Big Data. First of all, a definition and the highlights of Big Data are given. Furthermore, the distinctive strides for Big Data handling and the principle issues experienced in Big Data administration are depicted. Next, a general outline of architecture for taking care of it is described. At that point, the issue of consolidating Big Data architecture in an officially existing data framework is talked about. At last this review handles semantics (reasoning, coreference determination, element connecting, data extraction, solidification, philosophy arrangement) in the Big Data context.

Keywords: Big Data, Hadoop, Ontology alignment, Extraction of Information.

Abstract: Internet of Things (IOT) is the primary services in smart automated systems. Markov chain prediction model to assist positioning called Novel Localization Method (LNM).The Neighbor Relative Received Signal Strength (NRSS) used  to build the fingerprint database and adopts a Markov chain prediction model to assist positioning  as Novel Localization Method (LNM).The history data of the pedestrian’s locations are analyzed to positioning for various devices. Performance evaluation conducted in realistic environment demonstrates localization performance compared with existing schemes, when the problems of device heterogeneity and WiFi signals fluctuation exist future.

Keywords: Mobile Internet of Things (IOT), Novel Localization Method (LNM), Location Base Services (LBS), Current Neighbor Difference (CND), Received Signal Strength (RSS).

Abstract: Recognition of handwritten digits has been an important area in recent years because of its uses in many fields. Arabic pattern digits, weak work is performed because Arabic digits (Indian) are more complicated than English patterns. This study focuses on the recognition component of the recognition of handwritten Arabic digits (Indian) that faces many obstacles, including the infinite variety of human handwriting and the broad public databases. The study presented a deep learning approach that can effectively be applied to the recognition of handwritten Arabic digits. Convolutional Neural Network (CNN) trained and tested MADBase database (Arabic handwritten digits images) with 60000 training and 10000 test images.. A contrast is made between the results, and it is seen at the end that the use of CNN has resulted in substantial improvements across various classification algorithms for machine learning, As a test accuracy with better results than other approaches using the same database, the test accuracy was improved to 99.25%.

Keywords: Recognition, handwritten, classification, Convolutional Neural Network.

Abstract: In today’s world, social media is used by every individual for expressing their feelings, opinion, experiences and emotions. People feel free to discuss and share their experiences on social media. We are intended to take people posts, likes, and comments from these social media and apply web content mining to the data collected for finding the person’s behavior. Earlier there was a system which does web content mining on twitter data. But in our project we are going to take collective data from social media like Face book, Twitter, Google and so on.

Keywords: Java Netbeans IDE, MySQL, Xamp Server , Bayesian Equation.

Abstract: In the process of determining the best lecturer by students, there are several criteria, including in terms of explaining the material, teaching methods, which make it easier for students to follow their courses. To assist in the selection process for someone to become the best lecturer for students, a decision support system is needed using Fuzzy Multiple Addictive Decision Making (FMADM). This study uses the SAW (Simple Addictive Weighted) method based on predetermined criteria. The SAW method can determine the selection of the best lecturer based on predetermined criteria for students, as well as looking for the weight value of each attribute to get the best lecturer.

Keywords: Fuzzy Multiple Addictive Decision Making, SAW Method, Decision Support System, criteria for the best lecturers

Abstract: Color image features are very important victor of values. Which is used as an image identifier or primary key which can be used easily in a color image retrieval system, the features victor can be used also as an image signature to compute image classifier in a color image recognition system.  In this paper research we will introduce a texture method to create color image features. This method will have based on using crossing number to detect some objects in the image, the detected objects where isolated, ending, connected and crossing points. The idea of the proposed method is to find the count of each objects, these counts will form the image features. The proposed method will be implemented and the experimental results will be analyzed to prove the efficiency, accuracy, and stability of the proposed method.

Keywords: Features, crossing number, isolated point, ending point, connected point, crossing point.

Abstract: Wise Tutoring Systems (ITS) are intuitive learning conditions dependent on guidance helped by P.C.s. The insight of these frameworks is, to a great extent, ascribed to their capacity to adjust to a particular understudy during the educating cycle. As a rule, the variation cycle depicts by three stages: (I) getting the data about the understudy, (ii) preparing the data to introduce and refresh an understudy model, also, (iii) utilizing the understudy model to give the transformation. In this paper, we considered viewpoints related to understudy displaying (S.M.) in Intelligent Tutoring Systems. First, we make a subjective examination of two procedures: Bayesian Networks (B.N.) and Case-based Reasoning (CBR) for S.M. We apply the two strategies to a contextual analysis concerning the advancement of an ITS for e-learning in the clinical space. At last, we talk about the outcomes acquired. Index Terms: Bayesian Networks, Case-based Reasoning, Intelligent Tutoring Systems, Student Model.

Abstract: In the last decade, the clinical reasoning in physical therapy has been to develop smart and automated systems for physiotherapists to make clinical decisions rapidly and efficiently in response to the complex upcoming needs of health and rehabilitation units. The major problem addressed in this review paper is about antalgic and ataxic gait population. The common problem faced by both subjects is improper body weight balance during walking. This imbalance causes them an additional pain in their shoulders and joints, which may lead to serious suffocation. So designing an automated smart walker with balance management system, fall management system and light assistance system can prevent their unnecessary pain and correct their gait pattern too.  Along with this walker therapy, Dynamic EMG will be acquired from the subject and transmitted to the concern physiotherapist. Based on the therapy environment, Bluetooth setup is used to transmit the EMG data from patient to the therapist for continuous and periodic assessment of muscle re-education.

Keywords: Physiotherapy, antalgic gait, ataxic gait, walker and EMG

Abstract: The most neglected topic in health protection facilities is the management of the wastes generated by them. Health hazard wastes are the wastes that are produced from health protection facilities, laboratories, and research centers, animal test laboratories, mortuary and autopsy centers, blood banks, nursing homes for the elderly, etc. As per the World Health Organization (WHO), it is been stated that nearly 85% of wastes generated in health protection sectors are non-hazardous and the rest 15 % is hazardous. Until now we are following manual sorting and handling of Bio-Medical Wastes (BMW). The purpose of the review is to: (i) evaluate the generation of biomedical wastes; (ii) analyze methodologies used in biomedical waste management (iii) explain advantages of replacing humans with robotic arms in health care waste management system (iv) Identify the applications of artificial intelligence in healthcare sectors (v) explain the application of image processing methodologies in waste segregation and disposal. The results from various authors give us a detailed explanation of how image processing techniques, neural networks, and robotics can be applied in healthcare waste management system. These above-mentioned technologies enable us to gain knowledge about how to prevent disease transmission in healthcare workers as a result of BMW.

Keywords: BMW, robotics, image processing, object recognition, manpower, autonomous waste disposal.

Abstract: Internet of Things (IoT) is a new trending phase of technology. IoT refers to communication and connectivity between things such as technological devices, actuators, sensors, and people or processes with unique identifiers. The importance of IoT is to improve the daily living standards of an average user. IoT is made for the people and used by the people for many reasons such as improved health, business innovations, and personal health trackers. Examples of IoT applications and services today include Smart thermostats like NEST, connected cars like Car2Go, activity trackers like BASIS, smart outlets like Belkin, Parking sensors like street line and so much more services being developed. The main goal of this study is to identify the challenges users face in understanding IoT and monitoring it as it undergoes change through self-adaptation. In this paper, an observational study is conducted. Within the study, two data collection methods were used; observational of the users and post observation questionnaires. The observational study was done by video recording users while using the IoT application. This was to obtain information about the IoT.

Keywords: User requirements, Internet of Things, Observational study, Software engineering

Abstract: Artificial Intelligence (AI) and Internet of Things (IoT) are nowadays phenomenon technology, and it is used in modern agriculture. In agriculture, wireless sensors are used to collect data on soil, water, soil moisture and other environmental aspects to monitor and monitor soil health and to achieve greater benefits from the perspective of farmers and the environment. In these days, the use of artificial intelligence is everywhere from our daily life to space technology, automobile industry to medical facilities. As a passage of time, the use of AI technology and different sensors also used in Agriculture, this is called smart farming or Precision Agriculture. In this study, review of different machine learning (ML) techniques and IoT are discussed which were used in agriculture.

Keywords: IoT, Machine Learning, Precision Agriculture, Smart Farming.

Abstract: : This paper potray you about how we can enhance our farming techniques through latest technology and get 100% out of it. And this paper will show you how can monitor and secure our farming. India is a nation which is having more population and it is imperative to take care of the food adequately to all the individuals. The primary concern which is expected to satisfy this prerequisite is exceptional "farming" with enough water and minerals in the dirt keeping up this is bit risky. So incorporating the agribusiness field with Technology will make sound. Programmed soil highlights and condition bringing and choice taking should be possible by utilizing sensors and actuators, developing the seed and getting the yield isn't the solitary thing, we can give security to cultivate land just as to the product (obtained yield). And in this paper I am going to show some of the ways to work on problem.

Keywords: IOT, Internet Of Things, Security System, Smart Farming.

Abstract: This paper focuses on related study of reconfiguration system in VANET. It considers various attacks during data transfer from sender to receiver. Various authors provides their advance technology related to vehicular networks and suggests some improvement points.  It provides improvement in mobility-based routing to improve performance in VANET. Various routing protocol related to VANET is studied by various researchers work. Due to this, it focuses on improved mobility-based routing that helps to prevent attacks in system. All simulations will be presented in MATLAB tool.  

Keywords: VANET, Reconfiguration system, Packet Delivery Ratio, Energy Management etc

Abstract: To study the instructions which are being governed by a procedure, when the first machines are to follow a learning pattern and then to try for various rules and knowledge within which it is found that how the machine is to perform, that is called as Machine Learning. In this paper the various abilities and working implementations of machine learning as a tool is studied and analyzed with the help of case study in linear regression and logistic regression using python language. This also shows the coherence and application of machine learning algorithms by the prediction of various events that are considered in this study.

Keywords: M LAlgorithms, sampling, train and test, Python language.

Abstract: Wireless sensor network is a network of tiny and small sensors. Due to limited size, it has limited energy supply and called a energy constraint network. It is required to design network in such a way so that it can pertain long time. To enhance network lifetime routing play a crucial role in it. Hierarchical routing is best to conserve more energy for data transmission. LEACH is the first hierarchical routing protocol for wireless sensor networks. However, it lacks in various scenarios of real deployment of the networks. In this paper, a Partition based Multi-Chain Clustering (PMCC) protocol for wireless sensor networks has been proposed to extend network lifetime. The objective of this work is to prolong the network lifetime by logically dividing the sensing field into a number of zones, which a multi-chain structure in the cluster is used for data forwarding and minimum spanning tree algorithm is adopted for communication among cluster heads. The simulation results shows that the use of proposed protocol offers significant improvement over existing protocols in extending network lifetime.

Keywords: Wireless sensor network, multi-chain, residual energy, network lifetime, load balancing.