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Deep Learning Cerebral Splitting: Adaptation for Spine Elimination

Deep Learning Cerebral Splitting: Adaptation for Spine Elimi...

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communication, Computing and Energy Efficient Technologies (I3CEET), International Conference on

作者： M. Balasubramani B. J. Job Karuna Sagar K. C. Rajheshwari E. Saranya B. Aishwarya P. Murugeswari Assistant Professor Department of Computer Science and Engineering V.S.B. Engineering College Professor Department of Computer Science and Engineering Joginpally B.R Engineering College Hyderabad India Department of Computer Science and Engineering Sona College of Technology Assistant Professor Department of Computer Science and Engineering Sri Eshwar College of Engineering Coimbatore Assistant Professor Department of Computer Science and Engineering(Cyber Security) Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Department of Electronics and Communication Engineering Theni Kammavar Sangam College of Technology

ISBN: (数字)9798331541583

ISBN: (纸本)9798331541590

The posterior fossa volume and the total intracranial volume are important factors to consider when doing a brain volumetric analysis using structural electromagnetic resonance imaging. The thorough segmentation of the whole cortex offers a method for non-invasively evaluating different brain regions. In addition, the extraction of skulls in a way that maintains anonymity is increasingly being used as a means of disseminating large amounts of data obtained from brain images. Therefore, generalizing machine learning brain regions for intracranial measurements after skull removal is an interesting task. However, data collecting is difficult due to the small number of handwritten and whole-brain atlases marked with his TICV/PFV. In this study, we use U-Net tiles to estimate intracranial volume and perform whole-brain segmentation with and without cranial characteristics simultaneously. In the absence of individually recorded total cortical volume, a transfer learning approach has been shown to estimate extra her TICV and PFV labeling during whole-brain delineation on T1-weighted MRI. More specifically, U-Net tiles are pre-trained using a big Brain COLOR atlas generated using multi-atlas segmentation, and do not include his PFV labels. The pre-trained model is improved to learn more His TICV and PFV labels using the limited Brain COLOR atlas. We also elaborate on his method for processing MR images of the brain in the absence of a skull. The results show that our method produces reasonable segmentation and size estimation results in terms of average contact distance, cubic similarity index, and total volumetric similarity for both brains within and outside the skull. is showing off. This technology is currently available as open source to the general public.

关键词： Deep learning Image segmentation Image color analysis Magnetic resonance imaging Transfer learning Pipelines Estimation Skull Resonance Telecommunication computing

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An Analysis of Random Non-deterministic Signals Using Recursive Methods and Stochastic Control System

An Analysis of Random Non-deterministic Signals Using Recurs...

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International Conference on Advances in Data science and Computing Technologies, ASDC 2022

作者： Singha, Tanmoy Misra, Lisha Dutta, Joydeep Dhar, Rudra Sankar Biswas, Arindam Department of Electronics and Communication Engineering National Institute of Technology Mizoram Mizoram Aizawl796012 India Asansol Institute of Engineering & Management-Polytechnic Asansol713339 India Department of Computer Science and Engineering Siliguri Institute of Technology Sukna West Bengal Darjeeling734009 India School of Mines and Metallurgy Kazi Nazrul University West Bengal Asansol713340 India

ISBN: (纸本)9789819936557

In order to simplify the analysis of processes as well as the design of controllers, discrete domain analysis is a powerful tool since it reduces characteristic roots from infinite to finite numbers. Our work focuses on the process of introducing discretization to the domain conversion, as well as considering a recursive method for analyzing random non-deterministic data. With the proper discretization of tuned stable systems, nonlinear modeling of a system can be designed. Several simulations are used in this paper to demonstrate the application of non-deterministic, stochastic control theory. A method for controlling random non-deterministic signals based on sampled data has also been developed, and the time complexity has been analyzed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Stochastic control systems

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Image Denoising Using Various Image Enhancement Techniques 5th

Image Denoising Using Various Image Enhancement Techniques

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5th International Conference on Intelligent Computing and Applications, ICICA 2019

作者： Premnath, S.P. Arokia Renjith, J. Department of Electronics and Communication Engineering Sri Krishna College of Engineering and Technology Coimbatore India Department of Computer Science and Engineering Jeppiaar Engineering College Chennai India

ISBN: (纸本)9789811555657

The main aim of the image enhancement technique is to process any image given as input and to obtain the resultant outcome more accurately than the existing image. The level of accuracy of an image can be restored in different forms using image enhancement techniques. The choices of choosing different image enhancement techniques may vary depending upon the quality of the picture, task, and atmospheric conditions. The different algorithms used for enhancement and the concepts are discussed in this paper. The frequency and spatial domain of the image can be enhanced by using these processes. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Image enhancement

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ACoCo: An Adaptive Congestion Control Approach for Enhancing CoAP Performance in IoT Network

ACoCo: An Adaptive Congestion Control Approach for Enhancing...

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Applied Artificial Intelligence and Computing (ICAAIC), International Conference on

作者： J. Jayaudhaya S. Supriya Vijay Anand Kandaswamy Samuthira Pandi V S. Kamatchi C Pushpa Priya Department of Electronics and Communication Engineering R. M. D. Engineering College Tamil Nadu India Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Tamil Nadu India Department of Electronics and Instrumentation Engineering R.M.K Engineering College Tamil Nadu India Department of Electronics and Communication Engineering SRM Institute of Science and Technology Ramapuram Tamil Nadu India Department of Electronics and Communication Engineering Saveetha School of Engineering SIMATS Chennai Tamil Nadu India Department of Electronics and Communication Engineering Dhanalakshmi College of Engineering Tamil Nadu India

The Industrial Internet of Things (IIoT) requires the real-time transmission of critical data to ensure functionality and prevent hazardous situations. However, current data transmission scheduling methods in 6TiSCH networks do not efficiently handle heterogeneous traffic based on its criticality and performance requirements, potentially leading to violations of timing limits. To address this issue, this paper proposes ACoCo, an Adaptive Congestion Control approach for CoAP that uses reinforcement learning techniques to dynamically adapt congestion control parameters based on real-time network conditions, node behaviors, and traffic patterns. Simulation results demonstrate ACoCo's effectiveness in reducing end-to-end transaction delay and improving transaction delivery ratio under congested network conditions, providing valuable insights for IoT network optimization and design. ACoCo operates effectively within the 6TiSCH network architecture, taking into account the scheduling function and communication requirements of the network.

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Secure Smart Healthcare Surveillance Framework Using Fuzzy C-Means Clustering with Effective Ant Colony Optimization in Internet of Things

Secure Smart Healthcare Surveillance Framework Using Fuzzy C...

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2022 IEEE International Conference on Knowledge engineering and communication Systems, ICKES 2022

作者： Karuppaiah, Jayakumar Aarthi, C. Girirajan Jananai, M. Parameshachari, D.B. Biomedical Engineering Kalaigar Karunanidhi Institute of Technology Coimbatore India Sengunthar Engineering College Thiruchengode India Sr University Department of ECE Warangal India Kpr Instiute of Engineering and Technology Computer Science and Engineering Coimbatore India Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9781665456371

The emergence of IoT device networks is not limited to a specific industry, application, or environment;instead, they are assisting in the development of the country in a number of sectors, including industries, cities, agriculture, and defense. But IoT device networks have some restrictions, including those related to bandwidth, energy resources, and other resources, as well as restrictions based on the environment. The fast growth of the Internet of Things (IoT) has brought to light significant privacy protection problems. This has a tremendous impact on the large-scale IoT applications. In this study, a ground-breaking IOT computing platform for secure and knowledgeable healthcare monitoring services is introduced. Within an IoT architecture, fully homomorphism encryption (FHE), which protects data privacy, is handled and kept. For the proposed IoT framework, a distributed method for clustering-based approaches is created with the scalability to gather and independently analyse massive amounts of hetrogeneous data in distributed IoT devices before it is transferred to the cloud. In this study, the Cluster Heads (CHs) were chosen from the available IoT devices using a brand-new Efficient Ant Colony Optimization (EACO) technique. For healthcare surveillance, fuzzy C-Means clustering (FCMC) is employed. FCM allows us to recognise regular (typical) bio signal patterns. © 2022 IEEE.

关键词： Internet of things

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Fortifying Database Security: Integrating Advanced Honeypot Technology for Resilient SQL Injection Defense

Fortifying Database Security: Integrating Advanced Honeypot ...

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communication, computer sciences and engineering (IC3SE), International Conference on

作者： Kumaran U Thammisetty Swetha G. S. N. Santhosh Reddy Harini Ala Senthil Murugan Nagarajan B. Umah Department of Computer Science & Engineering Amrita School of Computing Bengaluru India Department of Computer Science & Engineering (Data Science) Madanapalle Institute of Technology & Science Madanapalle Andhra Pradesh India Department of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru Karnataka India Department of Mathematics Faculty of Science Technology and Medicine University of Luxembourg Luxembourg Department of Computer Science & Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru Karnataka India

ISBN: (数字)9798350366846

ISBN: (纸本)9798350366853

The dynamic nature of cyber threats necessitates the development of novel approaches to strengthen database system security. The novel method for fortifying defenses against SQL injection attacks—a pervasive and ongoing danger in the field of cybersecurity—is presented in this study. The suggested methodology creates a strong and adaptable defense mechanism by seamlessly integrating cutting-edge honeypot technology with current SQL injection mitigation techniques. Our approach, which we have named HoneySQLGuard, uses carefully con- structed honeypot tables inside the database system. These tables serve as sly bait, drawing potential attackers’ attention away from genuine data and toward themselves. By utilizing the most recent developments in technology, Honey SQL Guard surpasses the limitations of conventional signature-based detection techniques and is able to adjust to changing attack strategies via anomaly and machine learning. The honeypot tables are cleverly incorporated within the database architecture, making them invisible to an outside observer when compared to real tables. The technology immediately recognizes and isolates unusual behavior suggestive of SQL injection attempts by closely monitoring and analyzing query patterns. Furthermore, HoneySQLGuard has real-time reporting and alerting functions that guarantee an early reaction to any possible intrusions. Extensive testing is conducted to validate the effectiveness of the proposed solution, which shows it can dramatically lower the success rate of SQL injection attacks while keeping false-positive rates low. This study advances the subject by providing a thorough and flexible method for fortifying databases against SQL injection attacks, in line with the industry's increasing demand for robust cybersecurity defenses.

关键词： Protocols Prevention and mitigation Machine learning SQL injection Observers Database systems Real-time systems

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Towards Mutation Testing of Embedded Software: A Framework and Case Study

Towards Mutation Testing of Embedded Software: A Framework a...

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IEEE International Conference on Software Reliability engineering Workshops (ISSRE Wksp)

作者： Wei Jiang Sijin Dong Jiaming Zhang Jin Tang Zichao Zhang Chang-ai Sun Xiaoyi Zhang Information Science Academy China Electronics Technology Group Corporation Beijing China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China

ISBN: (数字)9798350367041

ISBN: (纸本)9798350367058

Embedded software commonly executes safety-critical tasks and thus is expected to be highly reliable, which calls for stronger quality assurance techniques. As a fault-based testing technique, mutation testing is widely recognized to have stronger fault detection capability than those coverage or function-based testing techniques. However, some unique features of embedded software, such as limited hardware resources, real-time requirements, and differences between development and execution environments, pose challenging issues for the application of mutation testing. In this study, we explore the application of mutation testing to embedded software. As a result, we propose a mutation testing framework for embedded software, and evaluate the simulation capability of mutation operators for real-life faults in embedded software. A case study was conducted on a realistic open-source embedded software to evaluate the effectiveness and efficiency of the proposed technique. The experimental results demonstrate that mutation testing is able to detect various faults of embedded software, thus delivering a promising supplement for embedded software testing.

关键词： Quality assurance Fault detection Conferences Prototypes Real-time systems Hardware Software reliability Optimization Embedded software Testing

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IoT based Patients Monitoring System in Healthcare Service 1

IoT based Patients Monitoring System in Healthcare Service

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1st IEEE International Conference on Automation, Computing and Renewable Systems, ICACRS 2022

作者： Hanumanthakari, Sudheer Kumar Pullela, S.V.V.S.R. Bhukya, Shankar Nayak Vijayalakshmi, K. Rehan Ahmad, S. Kumar, Narendra Department of Electronics and Communication Engineering Faculty of Science and Technology IFHE Telangana Hyderabad501203 India Department of Computer Science and Engineering Aditya College of Engineering Andhra Pradesh Surampalem533437 India CMR Technical Campus Telangana Hyderabad501401 India Department of Computer Science and Engineering Sri Sai Ram Institute of Technology Tamil Nadu Chennai600044 India Department of Zoology Hiralal Mazumdar Memorial College for Women West Bengal Kolkata700035 India Department of Electronics and Communication Engineering RNS Institute of Technology Karnataka Bengaluru560098 India

ISBN: (纸本)9781665460842

The medical field requires constant updating and the usage of advanced technology. This is due to the fact that different kinds of diseases as increased as the population of world has increased. S cientists and doctors try to come up with different types of preliminary tests and other diagnostic technologies to detect the presence of a disease in its early stages. Though the preliminary test for different health issues is different it all consists of the measurement of basic vital parameters like temperature and the d pressure etc. To ease this process this study aims the development a circuit which is capable of constantly monitoring the vitals of a patient and displaying the result to an attendant. The principal flow of the circuit is initiated by the sensors that are instantly fastened to the patient. The sensors continuously gather and transmit the patient's vital indicators to the node MCU model. The AWS cloud then receives data from the model. The platform compares the collected data to the specified value. If no anomalies are found, the cloud simply records the data before stopping. However, if there are any anomalies, the cloud orders the node MCU model to activate the emergency output gadgets, such as the buzzer and the LED, to immediately alert the attendant or the nurses. A website is also created, and it is utilised to display the patient's information as well as vital records. Along with the patient's vital signs, it also shows an emergency condition when one of the patients has certain irregularities in one or more of the parameters. The physicians and other staff can keep an eye on all the patients at once without having to frequently visit a specific room thanks to this display of emergency information. This system is anticipated to be enhanced in the future with additional capabilities including automated parameter control without human intervention. In other words, the temperature is regulated when the ambient humidity or the body's temperature is

关键词： Internet of things

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Design and development of information management system using QR code based technique

Design and development of information management system usin...

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Intelligent and Innovative Technologies in Computing, Electrical and electronics (IITCEE), International Conference

作者： Sangeeta Prasad Madhumitha P Rakshita Adhyapak Aditi N Pai Veena Gadad Sindhu Rajendran Department of Computer Science and Engineering R. V College of Engineering Bangalore India Department of Electronics and Communication Engineering R. V College of Engineering Bangalore India

Today's university students, staff and visitors expect an intelligent, digitally connected campus that improves security, supports integrated learning experiences and simplifies student services. It is very common for a visitor to get lost in the large universities searching for a particular department or information. To prevent this, the paper discusses a QR code based solution to help visitors of the campus to provide campus information at one point. Although QR code is used for product tracking, item identification, time tracking and document management, its usefulness can be explored in information management too. This paper discusses the digitization of the university campus by using simple technological tools. Every university has a website that contains detailed information such as faculty information, placement statistics, student information and a complete virtual tour of the entire college campus. This site is linked to QR Codes that will be displayed in front of each department in the campus. People can use a QR code scanner and obtain the information quickly instead of surfing the university website. The main objective is to provide appropriate information efficiently at one place obviating the need to type in the URL of the website.

关键词： Uniform resource locators Industries QR codes Information management Security Task analysis Automotive engineering

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Cloud-Based Smart Sensing System for Real-Time Health Management of Dementia Patients 2

Cloud-Based Smart Sensing System for Real-Time Health Manage...

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2nd International Conference on Smart Technologies for Smart Nation, SmartTechCon 2023

作者： Latha, R. Arul, U. Dhanalakshmi, S. Ramya, R. Mishra, Nilamadhab Department of Computer Science and Engineering K.Ramakrishnan College of Engineering Tamil Nadu Trichy India Department of Artificial Intelligence and Machine Learning Saveetha School of Engineering Saveetha Institute of Medical And Technical Sciences Saveetha Nagar Thandalam Tamil Nadu Chennai India Department of Electronics and Communication Engineering Sri Muthukumaran Institute of Technology Tamil Nadu Chennai India Department of Mathematics S.A Engineering College Tamil Nadu Chennai India School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh India

ISBN: (纸本)9798350305418

The paper describes an innovative technique of monitoring updates on the health of people with dementia by integrating smart sensing technologies with a cloud-based platform. Because dementia is a degenerative neuropsychiatric disease that develops with time, constant patient monitoring is essential for ensuring the health and safety of those living with the condition. The proposed system uses smart sensing devices, including wearable and ambient sensors, to monitor dementia patients' health in real-time. Data like heart rates, movements used, and ambient conditions are collected and sent to a server in the cloud for analysis. The camera can monitor and analyze visual data, capture crucial information, and help evaluate the patient's well-being. Multiple patients can be monitored effectively in real time because of the cloud-based system's scalability, accessibility, and storage capacities. For healthcare providers to recognize irregular movements, identify possible risks to health, and implement preventative measures, doctors utilize the moment data analytics devices to gather valuable insights from the acquired data. In addition, the cloud-based solution improves collaborative care and enhances patient support by allowing for continuous communication and information sent among caregivers, doctors, nurses, and family members. Predefined thresholds or anomalous occurrences may trigger alerts and messages, allowing for quick action in reaction to emergencies. Modern technology and data analytics increase the health and happiness of people with dementia. © 2023 IEEE.

关键词： Cloud platform Dementia patients Healthcare Real-time monitoring Sensors

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