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Cal-IT2 is an international partnership researching physically-coupled distributed embedded systems for large-scale societal applications. The goal is to develop robust and adaptable solutions for infrastructure like transportation and healthcare. Challenges include integrating highly distributed complex systems and legacy systems. Researchers from technology, policy, and industry are collaborating on projects in areas like energy, transportation, and structural health monitoring using sensors and predictive modeling. The community aims to autonomously respond to unexpected events through distributed computing, situational awareness, and adaptive resource management to address issues like hazard response.
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performed by one or several body sensors. The architecture for this system is based on medical sensors which
measure patients’ physical parameters by using wireless sensor networks (WSNs). These sensors transfer data
from patients’ bodies over the wireless network to the cloud environment. The system is aimed to prevent delays
in the arrival of patients’ medical information to the healthcare providers, Therefore, patients will have a high
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eliminating manual data collection, enabling the monitoring of huge numbers of patients. We underline the
necessity of the analysis of data quality on e-Health applications, especially concerning remote monitoring and
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Cyber-physical system (CPS) is a terminology used to describe multiple systems of existing infrastructure and manufacturing system that combines computing technologies (cyber space) into the physical space to integrate human interaction. This paper does a literature review of the work related to CPS in terms of its importance in today’s world. Further, this paper also looks at the importance of CPS and its relationship with internet of things (IoT). CPS is a very broad area and is used in variety of fields and some of these major fields are evaluated. Additionally, the implementation of CPS and IoT is major enabler for smart cities and various examples of such implementation in the context of Dubai and UAE are researched. Finally, security issues related to CPS in general are also reviewed.
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The use of Linux based Operating Systems (OS) in the classroom is increasing, but there is little research to address usability differences between Windows and Linux based OSs. Moreover, studies related to the ability for students to navigate effectively between Ubuntu 14.04 Long Term Support (LTS) and Windows 8 OSs are scant. This research aims to bridge the gap between modern Linux and Windows Oss, as the former represents a viable alternative to eliminate licensing costs for educational institutions. Preliminary findings, based on the analysis of the System Usability Scale results from a sample of 14 students, demonstrated that Ubuntu users did not require technical support to use the system, while the majority found little inconsistency in the system and regarded it as well integrated.
IRJET- Skin Disease Detection using Neural Network
This document presents a proposed system to detect skin diseases using neural networks. The system has two main parts: 1) feature extraction from images using extraction methods, and 2) feeding images to a pre-trained neural network for disease detection. A ResNet neural network trained on a skin disease dataset using TensorFlow is used for detection. The system is intended to help users detect skin diseases from photos and provide disease information and prevention tips.
Top Computer Science & Information Technology Articles of 2019
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
The Human Factor in ICT for For Disaster Warning and Response
ICT systems for disaster warning and response are increasingly sophisticated, but their success depends on how well they meet human needs. While technology plays an important role, the key component is the human user. Successful systems understand the human element as much as the technical aspects to avoid problems from poor usability or lack of fit with real-world requirements. The conference discussed topics like emergency notification systems, risk communication, modeling human behavior in ICT design, and using mobile phones to aid people in disasters.
EuroPACS 2006
The document describes an RIS/PACS system implemented at the Faculty of Medicine, University of Crete that features integrated advanced image processing capabilities. Researchers can develop image processing algorithms in Java or Matlab that are then made available as "image processors" within the system. This allows radiologists and remote researchers to apply the algorithms to exams within the regular workflow. The system has improved collaboration, accelerated image analysis for clinical research, and streamlined the development and testing of new image processing techniques.
Lumen Electronics EEE Career & Employability
The document discusses career opportunities for electrical and electronics engineers. It notes there is a large demand for engineers due to India's plans to significantly increase power generation capacity over the next 10-15 years. Electrical engineers work in diverse fields like power generation, transmission and distribution systems, consumer electronics, telecommunications, and more. The career field is expected to grow with ongoing expansion in communications, consumer electronics, and research and development. Emerging areas of focus include renewable energy, electric vehicles, wireless power transmission, and smart grids.
man_behind_selfhealing_grid
In an interview, Dr. S. Massoud Amin discusses the evolution of the smart grid from his original vision conceived over 20 years ago. He envisioned transforming the electric power system into an "integrated, self-healing and electronically-controlled secure and resilient power system." While progress has been steady, the full vision of an anticipatory, self-healing grid with minimal human intervention has yet to be realized. Technological barriers around integration of renewables and distributed energy remain, as do policy challenges. However, microgrids and a focus on security, resilience and customer value are expected to advance the grid over the next five years.
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The Human Factor in ICT for For Disaster Warning and Response
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The document discusses strategies for improving energy efficiency in embedded, mobile, and multi-core systems through aggressive duty-cycling of platforms. It observes that these systems have large variations in power consumption between active and sleep states. It proposes collaborating between radios and other components to duty-cycle higher power elements using lower power ones. Examples discussed are using Bluetooth to page WiFi and switching between radios. Research projects exploring these approaches through techniques like CoolSpots are also summarized.
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The document discusses embedded computing systems and outlines some key points:
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1) Engineering education is transforming due to the influence of information technology and entrepreneurship.
2) Societal infrastructure is on the threshold of disruptive changes due to technological advances.
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Rajesh K. Gupta discusses how computer science has expanded beyond data to influence many areas of life including ballots, equity, access, health, and education. The document outlines how computer science now integrates with and collaborates across many disciplines at different scales, from molecular to societal levels. It provides examples of recent research initiatives in areas like cybersecurity, learning dynamics, and cyber epidemiology. The conclusion emphasizes the growing importance of computer science education and its role in inspiring students to dig deeper and apply their skills in practical and impactful ways.
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This document discusses transforming institutional infrastructure for research and linking knowledge with action. It discusses three key points:
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2. Making buildings more energy efficient through reducing energy use of IT equipment, HVAC systems, and plug loads using real-time monitoring and control approaches.
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Rajesh Gupta, Chair of Computer Science and Engineering at UC San Diego, introduces CaliT2 which focuses on collaborations and learning in future spaces. The summit identified, articulated, and planned to execute projects at the intersections of computing and fields like culture, environment, health, and energy. These interdisciplinary projects aimed to use computing research to address societal challenges. Gupta welcomed attendees to be part of an exciting time for collaborative, impactful research through CaliT2.
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This document is a resume for Ye Xu, who has 5 years of experience in software engineering, data engineering, and data science. Xu developed efficient solutions for embedded systems and real-time computer resource management, and has experience building data pipelines and using machine learning on large datasets. Current areas of research interest include combining real-time systems with big data in fields like the Internet of Things.
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This document summarizes a presentation on smart troubleshooting of interconnected devices. It discusses how as devices become more connected and complex, troubleshooting failures is challenging. Research aims to gather error logs from different devices, analyze them to match fixes and instructions. This could help with troubleshooting in smart cities and transportation. The proposed approach would reuse a framework to model dependability and security. It is connected to research on symbiotic autonomous systems and addresses areas like big data, machine learning, and cybersecurity.
International Journal of Computer Science, Engineering and Applications (IJCSEA)
International Journal of Computer Science, Engineering and Applications (IJCSEA) is an open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer science, Engineering and Applications. The journal is devoted to the publication of high quality papers on theoretical and practical aspects of computer science, Engineering and Applications.
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This article explores the pivotal role of embedded systems and software in driving technological advancements across various industries. Embedded systems, characterized by their integration into hardware devices and their ability to perform specific tasks with precision, have become ubiquitous in our daily lives. Their applications span across diverse fields such as automotive, healthcare, consumer electronics, and industrial automation. This article delves into the fundamental concepts of embedded systems, highlights their importance, discusses the challenges faced in their development, and explores the latest trends and innovations in embedded software. We are committed to using our findings from this exploration to help others in the embedded systems and software community. We believe that by sharing our knowledge, we can help to accelerate innovation in this field.
EMBEDDED SYSTEMS AND SOFTWARE: ENABLING INNOVATION IN THE DIGITAL AGE
This article explores the pivotal role of embedded systems and software in driving technological
advancements across various industries. Embedded systems, characterized by their integration into
hardware devices and their ability to perform specific tasks with precision, have become ubiquitous in our
daily lives. Their applications span across diverse fields such as automotive, healthcare, consumer
electronics, and industrial automation. This article delves into the fundamental concepts of embedded
systems, highlights their importance, discusses the challenges faced in their development, and explores the
latest trends and innovations in embedded software. We are committed to using our findings from this
exploration to help others in the embedded systems and software community. We believe that by sharing
our knowledge, we can help to accelerate innovation in this field.
International Journal of Computer Science, Engineering and Applications (IJCSEA)
International Journal of Computer Science, Engineering and Applications (IJCSEA) is an open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer science, Engineering and Applications. The journal is devoted to the publication of high quality papers on theoretical and practical aspects of computer science, Engineering and Applications.
All submissions must describe original research, not published or currently under review for another conference or journal.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Information Technology Convergence and services.
International Journal of Computer Science, Engineering and Applications (IJCSEA)
International Journal of Computer Science, Engineering and Applications (IJCSEA) is an open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer science, Engineering and Applications. The journal is devoted to the publication of high quality papers on theoretical and practical aspects of computer science, Engineering and Applications.
All submissions must describe original research, not published or currently under review for another conference or journal.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Information Technology Convergence and services.
EMBEDDED SYSTEMS AND SOFTWARE: ENABLING INNOVATION IN THE DIGITAL AGE
This article explores the pivotal role of embedded systems and software in driving technological
advancements across various industries. Embedded systems, characterized by their integration into
hardware devices and their ability to perform specific tasks with precision, have become ubiquitous in our
daily lives. Their applications span across diverse fields such as automotive, healthcare, consumer
electronics, and industrial automation. This article delves into the fundamental concepts of embedded
systems, highlights their importance, discusses the challenges faced in their development, and explores the
latest trends and innovations in embedded software. We are committed to using our findings from this
exploration to help others in the embedded systems and software community. We believe that by sharing
our knowledge, we can help to accelerate innovation in this field.
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Artificial intelligence in civil engineering seminar report
Artificial intelligence is a branch of computer science, involved in the research,
design, and application of intelligent computer. Traditional methods for modeling
and optimizing complex structure systems require huge amounts of computing
resources, and artificial intelligence based solutions can often provide valuable
alternatives for efficiently solving problems in civil engineering. This seminar
summarizes recently developed methods and theories in the developing direction for
applications of artificial intelligence in civil engineering. The field of artificial
intelligence, or AI, attempts to understand intelligent entities as well as construct
them to make the operation reasonably simple and easy, correct and precise.
Artificial neural networks are typical examples of a modern interdisciplinary
subject. Sophisticated modeling technique that can be used for solving many
complex problems serves as an analytical tool for qualified prognoses of the results.
Using the concept of the artificial neural networks and the results of the performed
numerical analyses make the field of civil engineering more accurate, precise and
efficient especially in the fields of smart materials and many more.
PrabhuCV_2017
Dr. Dattatreya Rachakonda has over 20 years of experience in academia and industry. He has a Ph.D in physics from IISc and has worked at IBM for 7 years managing modeling programs. He is currently a professor teaching undergraduate physics. He has extensive experience in areas such as semiconductor physics, fluid mechanics, and computational modeling.
Zpryme Report on Modeling and Simulation
The document discusses modeling and simulation (M&S) for smart grid infrastructure. It notes that M&S is being used to study the complex interactions between power systems and communication networks in a smart grid context. Several challenges of smart grid simulation are outlined, including combining power system and communication network simulation and different time models used. Solutions discussed include co-simulation, where separate power system and communication network simulators are connected, and integrated simulation, where components are simulated together within one environment. Government agencies and laboratories leading M&S research are also outlined.
Cyber Attack Detection and protection using machine learning algorithm
Cyber attack detection and protection using machine learning algorithms is a rapidly evolving field within cybersecurity. Machine learning techniques offer the ability to analyze large volumes of data in real-time and identify patterns indicative of malicious activity. Here's a general overview of how machine learning can be applied to cyber attack detection and protection:
Data Collection: The first step is to gather relevant data from various sources such as network traffic logs, system logs, firewall logs, and other security devices. This data will serve as the input for the machine learning models.
Feature Engineering: Feature engineering involves selecting and transforming the raw data into a format suitable for machine learning algorithms. This may include extracting features such as IP addresses, timestamps, packet sizes, protocol types, etc., from the raw data.
Model Training: Once the data is prepared, machine learning models can be trained using supervised, unsupervised, or semi-supervised learning techniques.
Supervised Learning: In supervised learning, the model is trained on labeled data, where each data point is associated with a specific class (e.g., normal or malicious). Common supervised learning algorithms for cyber attack detection include Support Vector Machines (SVM), Random Forests, and Neural Networks.
Unsupervised Learning: Unsupervised learning techniques are used when labeled data is scarce or unavailable. These algorithms can detect patterns and anomalies in the data without prior knowledge of specific attack types. Clustering algorithms like K-means or density-based algorithms like DBSCAN are often used in this context.
Artificial intelligence in power systems
A continuous and reliable supply of electricity is necessary for the functioning of today’s modern and advanced society. Since the early to mid1980s, most of the effort in power systems analysis has turned away from the methodology of formal mathematical modelling which came from the areas of operations research, control theory and numerical analysis to the less rigorous and less tedious techniques of artificial intelligence (AI). Power systems keep on increasing on the basis of geographical regions, assets additions, and introduction of new technologies in generation, transmission and distribution of electricity. AI techniques have become popular for solving different problems in power systems like control, planning, scheduling, forecast, etc. These techniques can deal with difficult tasks faced by applications in modern large power systems with even more interconnections installed to meet the increasing load demand. The application of these techniques has been successful in many areas of power system engineering.
Artificial intelligene (1)
This document is a seminar report on artificial intelligence in power system protection. It discusses several artificial intelligence techniques used in power systems, including expert systems, artificial neural networks, genetic algorithms, and fuzzy logic. Expert systems use rules and knowledge bases to solve problems. Artificial neural networks are biologically inspired and can perform tasks like pattern recognition. These techniques help address challenges in reliably detecting and isolating faults in power transmission lines. The document provides examples of how these AI methods can be applied, such as using neural networks to determine transmission line parameters.
Machine learning
Machine learning has many applications in power systems including equipment monitoring, predictive maintenance, load forecasting, anomaly detection, and more. It can help automate tasks, analyze trends in large datasets, and improve systems over time by learning from experience. While machine learning provides benefits like efficiency and automation, it also has disadvantages such as potential errors, challenges in interpreting results and acquiring data, and significant time and resource requirements.
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みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
ここ3000字までしか入らないけどタイトルの方がたくさん文字入ると思います。
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I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
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- 1. Engineering of Physically-Coupled Distributed Systems for Societal Scale Applications International Partnership for Research and Education in Distributed Embedded Systems Cal-IT2, Maryland, IITD, IITB, CMU, Bologna, CAR, Sona Koyo Steering Systems Briefing Material for Cal-IT2
- 9. SHM Problem We are Trying to Solve: Vibration-based SHM
- 10. SHM Testbed at CalIT2: Sensing Strain/Active Probing 6 degrees of freedom (u, w, ) linearly related to applied loads and stiffness matrix.