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Improved UNet Deep Learning Model for Automatic Detection of Lung Cancer Nodules

Computational Intelligence and Neuroscience 2023年第1期2023卷

作者： Vinay Kumar Baraa Riyadh Altahan Tariq Rasheed Prabhdeep Singh Devpriya Soni Hashem O. Alsaab Fardin Ahmadi Department of Computer Science Dyal Singh Evening College (University of Delhi) Delhi 110003 India Department of Medical Instrumentation Techniques Engineering Al-Mustaqbal University College Hilla Babylon Iraquomus.edu.iq Department of English College of Science and Humanities Al-Kharj Prince Sattam Bin Abdulaziz University Al-Kharj 11942 Saudi Arabiapsau.edu.sa Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun 248002 Uttarakhand Indiageu.ac.in Associate professor Department of Computer Science & Engineering and Information Technology Jaypee Institute of Information Technology Noida Indiajiit.ac.in Department of Pharmaceutics and Pharmaceutical Technology Taif University P.O. Box 11099 Taif 21944 Saudi Arabiatu.edu.sa Addiction and Neuroscience Research Unit Taif University Taif 21944 Saudi Arabiatu.edu.sa Computer Science Faculty University Rana University Kabul Afghanistan

Uncontrolled cell growth in the two spongy lung organs in the chest is the most prevalent kind of cancer. When cells from the lungs spread to other tissues and organs, this is referred to as metastasis. This work uses image processing, deep learning, and metaheuristics to identify cancer in its early stages. At this point, a new convolutional neural network is constructed. The predator technique has the potential to increase network architecture and accuracy. Deep learning identified lung cancer spinal metastases in as energy consumption increased CT readings for lung cancer bone metastases decreased. Qualified physicians, on the other hand, discovered 71.14 and 74.60 percent of targets with energies of 140 and 60 keV, respectively, whereas the proposed model gives 76.51 and 81.58 percent, respectively. Expert physicians’ detection rate was 74.60 percent lower than deep learning’s detection rate of 81.58 percent. The proposed method has the highest accuracy, sensitivity, and specificity (93.4, 98.4, and 97.1 percent, respectively), as well as the lowest error rate (1.6 percent). Finally, in lung segmentation, the proposed model outperforms the CNN model. High-intensity energy-spectral CT images are more difficult to segment than low-intensity energy-spectral CT images.

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Efficiënt load balancing by optimized flexi max-min algorithm

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Journal of Physics: Conference Series 2021年第1期1716卷

作者： P Praveen Kumar V Kanchana Devi Student Master of Computer Applications Vellore Institute of Technology Chennai Campus Tamilnadu India Associate Professor School of Computing Science and Engineering Vellore Institute of Technology Chennai Campus Tamilnadu India

Load Balancing is required to distribute tasks across Virtual Machines on one hand and on the other hand in a cloud Environment. Here, a new task scheduling algorithm: 'Optimized Flexi Max-Min Scheduling Algorithm' is proposed. The algorithm maintains a data structure which is modeled after a Binary Search Tree (BST) for estimations, enhanced searching, task allocation, and migration of tasks. Cloud-Sim is used to model and simulate the cloud computing environment in order to obtain simulated data. The result of this experiment shows that the proposed algorithm outperforms the traditional Max-Min task scheduling algorithms.

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Compressing Biosignal for Diagnosing Chronic Diseases

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Journal of Physics: Conference Series 2021年第1期1998卷

作者： P. Ithayarani A. Jainul Fathima Associate Professor Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation (KLEF) Deemed to be University Green Fields Vaddeswaram Guntur District A.P. India Assistant Professor Department of Information Technology Francis Xavier Engineering College Tirunelveli TN. India

Electrocardiogram, electromyogram, electroencephalogram are the foremost required vital signs for diagnosing chronic diseases like sleep disorder, mood disorder, epilepsy etc., which demands long-term monitoring. A sensor based wearable system which is enabled with internet technology, supports the continuous recordings of these vital signs without troubling the patient's daily activities. And the wearable hub is responsible for collecting the readings of bio signals from multiple micro-sensor nodes deployed around the body which creates the short range of communication and forward to the observer. These continuous monitoring increases the signal transmission cost and declines the battery life of wearables. So, the observed multiple bio signals can be compressed jointly than individually before sending, at an edge level. This paper proposes transfer learning based multimodal convolutional denoising autoencoder to perform multimodal compression and to reconstruct the data from its latent representation. Transfer learning helps the system to reuse the learned weights which may reconstruct the data with better quality score than by randomly initialized weights. The proposed work achieves compression ratio of 128 and it is proved that multimodal compression is better than unimodal compression in case of consuming multiple sensors. And the experimental result proves that the computation cost is low in multimodal compression than in unimodal compression.

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Automatic Turning ON/OFF Bike Indicator Using Offline GPS Navigation System

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IOP Conference Series: Materials science and engineering 2021年第1期1055卷

作者： S Usha M Karthik R Lalitha M. Jothibasu T Krishnamoorthy Associate Professor Department of Electrical and Electronics Engineering Kongu Engineering College Perundurai-638 060 Erode Professor Department of Computer Science and Engineering Rajalakshmi Institute of Technology Chennai Assistant Professor (Senior Grade) Department of Electronics and Communication Engineering PSG Institute of Technology and Applied Research Coimbatore UG Scholar Department of EEE Kongu Engineering College Perundurai-638060 Erode

In the present modern world, most of the people are using the roadways for transportation purposes. The utilization of roadways increases by one side, on the other side the road accidents are also escalating. The current assessment shows that the reasons for the road accidents are not obeying the traffic rules, inappropriate usage of indicators while turning right or left while driving the vehicles and so on. In peak hours and in traffic times people are speeding up with their vehicle and forgot to use their indicator. This leads to an accident while sudden turning and braking without a proper indication. In order to overcome these types of difficulties, an automatic turning on/off bike indicators using offline GPS navigation system is proposed. The proposed system works in an offline mode and does not need any internet connectivity. By turning on the supply to the board, it will generate the hotspot and it will be connected with Wi-Fi in Mobile Phone. Then the destination is fixed in the mobile application. When turning is available in the way to destination before 100 meters of that turning, indicator will be automatically turned on and after that indicator will be automatically turned off. Thus the proposed work would help the people during the rush hours and also during the emergency situations to avoid accidents.

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Multi Path Routing Technique Based RRP for P2P Network

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IOP Conference Series: Materials science and engineering 2020年第1期994卷

作者： Mary Subaja Christo R. M. Bommi K. Mariyappan Associate Professor Department of Information Science and Engineering Faculty of Engineering Technology Jain University Bangalore India Associate Professor Mechatronics Engineering Department Chennai Institute of Technology Kundratur India Assistant Professor Department of Computer Science and Engineering Jain University Bangalore India

All articles must contain an abstract. Peer to Peer (P2P) network is useful for developing applications and downloading files from the internet. In the existing P2P networks, communication is initiated and supported by peers. Security issues constitute the main challenge in the design of reliable communication techniques for P2P networks. In the past, Rumor Riding Protocol was used in distributed systems for performing coordination and communication. However, the existing Rumor Riding Protocol is used flooding technique to forward the response to the initiator it may leads high network traffic to avid this I have Enhanced Multi path forwarding technique to Rumor Riding Protocol and also enhancement with security features to make them suitable for downloading applications in P2P networks. In this method, it enhances the Rumor Riding Protocol with security features by including a Cryptographic Puzzle, a Challenge Question scheme using trust modeling and an intelligent beta reputation model for secured communication in P2P networks. For this purpose, five new techniques are proposed in this research work, all of which aim at enhancing the security of communication using Rumor Riding Protocol in the P2P networks.

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Performance evaluation of Energy Efficient algorithm using Spatial Trusted and Energy Aware Trusted Distance routing in WSN

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IOP Conference Series: Materials science and engineering 2020年第1期993卷

作者： M. Rajasekaran A. Ayyasamy R. Jebakumar Research Scholar Department of Computer Science and Engineering Annamalai University Chidambaram Tamilnadu India Assistant Professor Department of Computer Science and Engineering Annamalai University Chidambaram Tamilnadu India Associate Professor Department of Computer Science and Engineering SRMIST Kattankulathur Tamilnadu India

Energy efficient routing is the most important design criterion for WSN (Wireless Sensor Network) as the nodes are either powered by batteries, or by other external power sources. In a Sensor network, the nodes communicate with each other in a multi-hop fashion. The availability of each node is equally important to the proper functioning of the network. The power failure of nodes greatly affects the overall performance of the network. The Quality of Service (QoS) has been measured using the parameters of data quality, energy utilization and position of the sensor nodes. In this paper Energy efficient routing algorithm called Location and Energy Aware Trusted distance source routing (LEATDSR), Energy-aware Spatial Trusted Routing algorithm (ESTR) and Intelligent Weighted Fuzzy Cluster based Secure Routing Algorithm (IWFCSRA) were analyzed in term of energy efficiency performance. This paper implements LEATDSR, ESTR and IWFCSRA by using NS2 simulator. Energy Consumption and Security Analysis are used to evaluate LEATDSR, ESTR and IWFCSRA routing protocols performance analysis in WSN.

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Smart Gas Monitoring System for Home and Industries

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IOP Conference Series: Materials science and engineering 2020年第2期981卷

作者： Modepalli Kavitha Dr. S. Hrushikesava Raju Saiyed Faiayaz Waris Dr. Ashok Koulagaji Assistant Professor Department of computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram AP India Associate Professor Department of computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram AP India

Nowadays, gas industries or gas cylinders in a home will experience gas leakages because of human negligence or other external conditions and lack of patience. Due to disaster to be raised by such cases, the demolition happened is unpredictable. To predict the disaster in advance, then alternatives could be taken to avoid such cases. In this paper, an IoT device is designed that will detect gas leakages and the status of the gas to be known whenever cut off is specified by the user. The proposed IoT methodology for knowing the status of the gas summary is demonstrated using the specific use cases. The proposed IoT to be installed through a manual approach or virtual approach is depending on the consumer interest. There were many instances experiencing the many people to become victims of this and also the environment to be also spoiled and it takes more time to purify the infected environment or to bring the affected environment to a normal level. It is demanded nowadays to predict future disasters using G-IoT. In G-IoT, the components whenever meet less than the cut off values, will notify the report to the main center and authorized user. The V-IoT is also used to monitor outer environments like gas pipeline and its conditions. If the resources are supplied at the time of installation of setup and detected whenever a specific component becomes shortage, the automatic approach takes place and will start filling that specific component with required according to manual recording.

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Diabetic Foot Ulcer Treatment Device Using Peltier and Embedded Electronics

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Journal of Physics: Conference Series 2020年第1期1712卷

作者： I. D. Soubache T. Thirumurugan B. Annapurna Raushan Kumar Singh Associate Professor Department of BME Rajiv Gandhi College of Engineering and Technology Puducherry India Professor Department of Electronics and Communication Engineering Puducherry India Associate Professor Department of Computer Science and Engineering Aditya College of Engineering AP India Technical Director Spectrum Solutions Puducherry India

People's degrading lifestyle reflects their health graphs and occurrence of different disease in their bodies. With different food habits and exercise patterns the endurance capacity of the body changes. Foot ulcer is a disease quite common today among Indians around. The foot ulcer creates a threat to the movement for human beings. It is a deep infected sore or damage in the foot sole commonly caused by nerve/skin damage. Several infections in the foot may also result in leg amputations. Foot ulcer is very common among diabetic patients. India is the country with the highest number of diabetics worldwide. Over 3 million people are infected with diabetes which is a big number to worry about. The CPR (Crude Prevalence Rate) for cities is around 9% of the population whereas in village areas the occurrence is around 3 percent [1]. Though the foot ulcer prevalence of diabetic patients in India is 3% which looks small but it is a big number. Our proposal is an embedded system innovation to develop a foot ulcer treatment system. It deals with the combined approach to embedded electronics and biomedical engineering to overcome the situation. We create a footrest equipped with Peltier, vibrator, and UV rays to overcome the issue. It is the first of its kind foot ulcer treatment equipment that can solve the issue. We also used the android technology to provide the vocal user interface to help the user. Clear instructions are displayed and spoken upon usage to the patients. The result obtained on the patients are highly acceptable and recommended for both urban and rural populations. The Atmega 328 P PU microcontroller is interfaced with the HC-05 Bluetooth and Vibrators through Relays to perform the task. The microcontroller acts as the overall think-tank to control and coordinate the overall system.

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Segmentation of cervix using minimum spanning superpixel tree detector

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IOP Conference Series: Materials science and engineering 2020年第1期983卷

作者： TS Sheela Shiney S Albert Jerome Jemila Rose Assistant Professor Department of Computer Science and Engineering St. Xavier's Catholic College of Engineering Chunkankadai Tamil Nadu India Associate Professor Department of Biomedical Engineering Noorul Islam Centre for Higher Education Kumaracoil Tamil Nadu India Associate Professor Department of Computer Science and Engineering St. Xavier's Catholic College of Engineering Chunkankadai Tamil Nadu India

Cervical cancer occurs in cervix region of women which is life threatening and is a key research in the field of medical diagnosis. Cervical cancer can be prevented if precancerous changes is diagnosed earlier and cured properly. But finding cancer at the earlier stage is a tedious process. Cervical cancer screening is crucial since utmost of the screening procedures are invasive in nature. The objective is to automatically extract the area where in the cervical cancer starts to occur. In order to diagnose cervical cancer and distinguish the malignant and benign tissues, a cytology image obtained by cervicographic or colposcopy device is used. A robust segmentation algorithm is proposed that uses superpixel for the image segmentation method. This method is regularized by the combination of structural properties such as color, texture, and spatial data present in the superpixel graph.

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Identification of high grade and low grade tumors in MR Brain Image using Modified Monkey Search Algorithm

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IOP Conference Series: Materials science and engineering 2020年第1期993卷

作者： Saravanan Alagarsamy T. Abitha S. Ajitha S. Sangeetha Vishnuvarthanan Govindaraj Assistant Professor Department of Computer Science and Engineering Kalasalingam Academy of Research and Education India Under Graduate Scholar Department of Computer Science and Engineering Kalasalingam Academy of Research and Education India Associate Professor Department of Biomedical Engineering Kalasalingam Academy of Research and Education India

Detection of tumors present in the Magnetic Resonance brain image is a challenging task in the research field of medical imaging processing. The tumors with distinguished boundaries are difficult to find in the MR brain images, while performing the manual segmentation process. There is a necessity of an automated segmentation technique for performing better segmentation in terms of tumors with distinguished boundaries. The automated modified monkey search technique is used to find the optimized cluster position, and a random search operation is performed is locate all the pixels present in the image and then finally the location of the tumor region is exactly segmented/predicted by using the suggested monkey search algorithm. The suggested technique will support the radiologist for finding the tumors with distinguishing boundaries and accuracy of prediction of tumors is also improved lot with this approach. Based on the early prediction of tumors, diagnosing procedures will save the lives of many human beings.

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