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IEEE International Conference on Computing, Communication and Security (ICCCS)

作者： Rik Das Mohammad Arshad P.K. Manjhi Sudeep D. Thepade Post Graduate Programme in Information Technology Xavier Institute of Social Service Ranchi India Faculty of Science (Computer Applications) Vinoba Bhave University Hazaribag India Vinoba Bhave University Hazaribag India Pimpri Chinchwad College of Engineering Pune Maharashtra

ISBN: (数字)9781728191805

ISBN: (纸本)9781728191812

Outbreak of COVID-19 pandemic has imposed a major threat to the existence of human lives. High rate of infection due to the lethal virus has caused major sufferings and premature deaths to many budding possibilities. Nevertheless, quick identification of the disease can lead to faster recovery with medical help. Unfortunately, the ratio of COVID infection to methods of early medical identification of disease is quite feeble. This has motivated researchers in designing computer aided diagnosis (CAD) systems which can identify the disease from easily available chest X-Ray images of patients. However, the success rate of identification of COVID cases is not satisfactory since the proposed systems are emphasizing on identifying pneumonia rather than separating the cause of it as COVID or non COVID. In this paper, the authors have investigated the cause of such misclassification and have identified feature generalization as one of the reasons. A feature fusion based approach is proposed by the authors to encourage generalization of input features to CAD for better identification of COVID 19. The reason for proposing the fusion based feature formation is encompassing diverse X-Ray image information by extracting descriptors with assorted techniques and uniting them with fusion. The classification results with fusion based approach have reported substantial improvements compared to individual techniques. This in turn indicates better generalization of input features with feature fusion.

关键词： Feature extraction COVID-19 Lung X-ray imaging Support vector machines Histograms Convolutional neural networks

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Role of hole transport layers in normal and inverted bulk heterojunction organic solar cells: A light intensity dependent capacitance-voltage analysis

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Materials science in Semiconductor Processing 2025年 198卷

作者： Shailendra Kumar Gupta Durgesh C. Tripathi Amit Kumar Neha Garg Chinmay K. Gupta Vandana Yadav Sandeep Sharma Sanjeev Kumar Ashish Garg Amity School of Physical Sciences Amity University Punjab IT City Sector 82A Mohali 140308 India The Zispel Nano Electronic Center Department of Electrical Engineering Technion-Israel Institute of Technology Haifa 32000 Israel Clarendon Laboratory Department of Physics University of Oxford Oxford OX1 3PU United Kingdom Department of Computer Science and Engineering Manav Rachna International Institute of Research and Studies Faridabad 121004 India Department of Physics National Post Graduate College Barhalganj 273402 Gorakhpur India Physics Department Punjab Engineering College (Deemed to be University) Chandigarh 160012 India Department of Sustainable Energy Engineering Indian Institute of Technology Kanpur Kanpur 208016 India Chandrakanta Kesavan Center for Energy Policy and Climate Solutions Indian Institute of Technology Kanpur Kanpur 208016 India

In organic solar cells (OSC) hole transport layers (HTL) are essential for boosting the power conversion efficiency (PCE); therefore, it is crucial to determine the underlying mechanisms. In the present manuscript, we report a study that examines the effects of two HTL such as PEDOT:PSS and MoO 3 , on the electrical characteristics of P3HT:PC 61 BM (active layer) based bulk heterojunction (BHJ) in normal (ITO/PEDOT:PSS/P3HT:PCBM/Al) and inverted (ITO/ZnO/P3HT:PCBM/MoO 3 /Ag) configurations. Current density-voltage ( J-V ) and illumination intensity dependent capacitance-voltage ( C-V) measurements have been performed and compared for with and without HTL (PEDOT:PSS in normal and MoO 3 in inverted) devices. Results suggest that the extracted photovoltaic parameters (short circuit current density ( J sc ), open circuit voltage ( V oc ) and fill factor ( FF )) of HTL containing devices are superior to without HTL devices in both normal and inverted OSC, due to unfavourable charge carrier accumulation and band bending in HTL free devices. Such charge build-up at active layer/anode interface generates photovoltage contributing as loss factor to PCE and has been investigated in C-V characteristics measured under varied illumination intensities (0/dark, 50 and 100 mWcm −2 ). Parameters such as built-in-voltage (V bi ), effective built-in-voltage (V bi, eff ), accumulated carrier concentration and surface photovoltage (V spv = V bi, eff - V bi ) are extracted as a function of illumination intensity. Our findings reveal that HTL free devices, in both conventional and inverted OSCs structures, marked with low J sc , V oc and FF values generate higher SPV . The SPV calculation method used here has been proven to be crucial in recommending a suitable HTL for OSC device architectures.

关键词： Bulk heterojunction Capacitance-voltage Surface photo-voltage Carrier accumulation

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Combined Drilling and Reaming Operation in Robot and CNC

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IOP Conference Series: Materials science and engineering 2020年第3期912卷

作者： P Giridharan Stalin John Post-Graduate Student Department of Mechanical Engineering SRM Institute of Science and Technology Kattankulathur Tamil Nadu India Associate Professor Department of Mechanical Engineering SRM Institute of Science and Technology Kattankulathur Tamil Nadu India

The drilling and reaming operation are two separate machining processes. In our project drilling and reaming operation are combined by using combined drilling and reaming bit. The industrial robot with agile motion is possible to machine a component. The Industrial robots with high precision and six Degree of freedom are considered as better, for manufacturing processes. This work is to significantly compare the performance of robot drilling over CNC drilling. The manipulator used is ABB - IRB1410 with work volume of 2.6 meters, handling capacity of 5Kg and controlled by IRC5 Controller. Drilling machine utilized is specified with maximum speed of 2800 RPM and power of 600W. The speed of the drilling machine can be varied by using voltage regulator. Speed and feed are the two parameter that are varied and circularity, surface roughness are the parameter checked for. The drilling operation is also done in CNC machine. The parameters such as surface roughness, circularity are checked. Finally, comparisons between robot operation and CNC operation are performed, optimized values are found by using Taguchi method.

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Implementation of Augmented Reality in Pretend Play Therapy for Children with Autism Spectrum Disorder 3

Implementation of Augmented Reality in Pretend Play Therapy ...

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3rd International Conference on Computing and Applied Informatics 2018, ICCAI 2018

作者： Syahputra, M.F. Angkasih, A.P. Purnamawati, S. Andayani, U. Abdullah, D. Sriadhi, S. Iskandar, A. Rosida, T.M. Fitriany, J. Sari, I.N. Utama, M.D. Nanuru, R.F. Department of Information Technology Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Utara Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Pediatric Universitas Malikussaleh Aceh Utara Indonesia Departement of Social Science Education Program Post Graduate Program Universitas Kanjuruhan Malang Malang Indonesia Faculty of Social and Political Science Universitas Kristen Indonesia Maluku Indonesia Universitas Kristen Indonesia Maluku Ambon Indonesia

Autism Spectrum Disorder is a pervasive developmental disorder that will affect children in terms of interpersonal communication, social interaction, and imaginative levels in play. Many therapies to help the motor neuron performance is one of them Pretend Play. Pretend Play is a therapy that invites children in playing to demonstrate something else and tell how to use objects that are considered in the child's imagination. However, in the era of highly developed technology, many fields have used the Augmented Reality method as a visualization of various aspects. With this method researchers will present the therapeutic visualization of the block to 3D transportation tool that is useful for strengthening motor nerves and visual strength of the child. The system can run well during marker detection, marker movement, and 3D object display with the accuracy of precision angle and distance between virtual world with real world reach 100% with angle 0 at distance 31 cm and the maximum distance from the marker is 46 cm and the maximum angle is 30. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Augmented reality

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Developing self-adaptive microservice systems: Challenges and directions

arXiv

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arXiv 2019年

作者： Mendonça, Nabor C. Jamshidi, Pooyan Garlan, David Pahl, Claus Post Graduate Program in Applied Informatics University of Fortaleza FortalezaCE Brazil Computer Science and Engineering Department University of South Carolina ColumbiaSC United States School of Computer Science Carnegie Mellon University PittsburghPA United States Faculty of Computer Science Free University of Bozen-Bolzano Bozen-Bolzano Italy

A self-adaptive system can dynamically monitor and adapt its behavior to preserve or enhance its quality attributes under uncertain operating conditions. This article identifies key challenges for the development of microservice applications as self-adaptive systems, using a cloud-based intelligent video surveillance application as a motivating example. It also suggests potential new directions for addressing most of the identified challenges by leveraging existing microservice practices and technologies. Copyright © 2019, The Authors. All rights reserved.

关键词： Adaptive systems

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Hospital/Home Medical Assistant Robot

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IOP Conference Series: Materials science and engineering 2020年第6期912卷

作者： K S Harikrishnan Daniel Glad Stephen Post Graduate Student SRM Institute of Science & Technology Kattankulathur Chennai Tamilnadu India. Assistant professor Department of Mechanical Engineering SRM Institute of Science & Technology Kattankulathur Chennai Tamilnadu India.

Now a day's health-care facilities increasingly depend on health-care staffs. By aging populace, there is an upsurge in number of old people present in the labor force and even in health-care division. It is significant to take care of aging workforce present in healthcare sector. So, for this process hospitals are providing an opportunity to mobile robots because of rapid technological progress accomplished of working and cooperating with humans and surroundings. This paper presents a design of Hospital/home medical assistant robot that consist of both combination of network system and robotics system for transmitting, receiving and sending information to care taker or doctor. As the robot gets a distress signal which is obtained from the patient, it tries to contact the care taker or doctor. If the robot is unable to contact, it will try to find out the location of doctor or the care taker and then display the condition of the patient so that the doctor can act as early as possible. Doctor or caretaker can access the robot at any time and get the live video feed of the patient at any time.

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Comparative Analysis of Various Machine Learning Algorithms for Detecting Dementia

Comparative Analysis of Various Machine Learning Algorithms ...

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2018 International Conference on Computational Intelligence and Data science, ICCIDS 2018

作者： Bansal, Deepika Chhikara, Rita Khanna, Kavita Gupta, Poonam Department of Computer Science and Engineering NorthCap University Gurugram Haryana India Clinical Psychology Pt. Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences Rohtak India

Nowadays, there has been recent interest in applying machine learning techniques to the neurodegenerative disorders. Dementia is one such emerging global health issue and its early detection can be very helpful. A comparative analysis of four machine learning algorithms i.e., J48, Naïve Bayes, Random Forest and Multilayer Perceptron is presented in this paper. For the attribute reduction, the CFSSubsetEval is used. It has been shown that J48 is performing best among all the algorithms for the detection of Dementia. © 2018 The Author(s).

关键词： Decision trees

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A Lightweight Hybrid Dilated Ghost Model-Based Approach for the Prognosis of Breast Cancer

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Computational intelligence and neuroscience 2022年第1期2022卷 9325452页

作者： Edwin Ramirez-Asis Romel Percy Melgarejo Bolivar Leonid Alemán Gonzales Sushovan Chaudhury Ramgopal Kashyap Walaa F Alsanie G K Viju Universidad Nacional Santiago Antunez de Mayolo Huaraz Peru. Faculty of Statistical Engineering and Computer Science Computer Science Research Institute National University of the Altiplano of Puno P.O. Box 291 Puno Peru. University of Engineering and Management Kolkata India. Amity University Chhattisgarh Chhattisgarh India. Department of Clinical Laboratory Sciences The Faculty of Applied Medical Sciences Taif University Taif Saudi Arabia. Centre of Biomedical Sciences Research (CBSR) Deanship of Scientific Research Taif University Taif Saudi Arabia. Post Graduate Studies University of Garden City Khartoum Sudan.

Most approaches use interactive priors to find tumours and then segment them based on tumour-centric candidates. A fully convolutional network is demonstrated for end-to-end breast tumour segmentation. When confronted with such a variety of options, to enhance tumour detection in digital mammograms, one uses multiscale picture information. . The sampling of convolution layers are carefully chosen without adding parameters to prevent overfitting. The loss function is tuned to the tumor pixel fraction during training. Several studies have shown that the recommended method is effective. Tumour segmentation is automated for a variety of tumour sizes and forms postprocessing. Due to an increase in malignant cases, fundamental IoT malignant detection and family categorisation methodologies have been put to the test. In this paper, a novel malignant detection and family categorisation model based on the improved stochastic channel attention of convolutional neural networks (CNNs) is presented. The lightweight deep learning model complies with tougher execution, training, and energy limits in practice. The improved stochastic channel attention and DenseNet models are employed to identify malignant cells, followed by family classification. On our datasets, the proposed model detects malignant cells with 99.3 percent accuracy and family categorisation with 98.5 percent accuracy. The model can detect and classify malignancy.

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Path Planning of an UAV with the Help of Lidar for Slam Application

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IOP Conference Series: Materials science and engineering 2020年第6期912卷

作者： C Aakash V Manoj Kumar Post-Graduate Student Department of Mechanical Engineering SRM Institute of Science and Technology Kattankulathur Tamil Nadu India. Assistant Professor (Sr. G) Department of Mechanical Engineering SRM Institute of Science and Technology Kattankulathur Tamil Nadu India.

Today's world there will be always a value for path planning. Be it the use of mobile robots such as UAVs, UGVs, USVs, etc., everything functions based on SLAM input. The input parameter can be extracted by any kind of sensors such as Kinect, LiDAR, etc. Here I am using RPLIDAR(LiDAR) as Sensor for UAV path generation. By getting a single Plan reading from lidar I will generate 3D mapping by a gazebo and visualize it by rviz in ROS. Here we use ROS as an interface of robot and sensor.

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A Real Time Approach for Detecting Mobile Malicious WebPages

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Journal of Physics: Conference Series 2019年第1期1228卷

作者： S. Deepika P. Mounika Assistant Professor Dept. Of Computer Science and Engineering Anurag Group Of Institution Hyderabad Post Graduate Student Dept. Computer Science and Engineering Anurag Group of Institutions Hyderabad

Transportable specific web page pages comparison altogether from their work place partners in substance, format and usefulness. Likewise, current processes to apprehend malevolent websites are possibly no longer going to work for such pages. In this paper, we structure and actualize kayo, a machine that acknowledges pernicious and amiable portable webpage. we makes this warranty dependent on static highlights of a website web page going from the amount of iframes to the nearness of found out deceitful Smartphone numbers. Within the first vicinity, we tentatively display the requirement for transportable express structures and in a while recognize a scope of recent static highlights that profoundly relate with flexible malignant WebPages. We then observe to a dataset of extra than 350,000 known favorable and noxious versatile web page pages and showcase 90% precision in characterization. Additionally, we find, describe and document numerous internet site pages missed through Google secure browsing and virus general subsequently, we construct a application augmentation utilizing to defend clients from pernicious flexible web sites steadily. In doing as such, we give the primary static investigation strategy to differentiate malevolent transportable pages.

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