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2nd International Conference on 3-D Digital Imaging and Modeling, 3DIM 1999

作者： Hu, Zhencheng Uchimura, Keiichi Department of Computer Science Faculty of Engineering Kumamoto University Kumamoto Japan

ISBN: (纸本)0769500625

Motion detection from a moving observer is a very important technique for 3D dynamical image analysis. Because of continuous background variations, detecting real moving objects has become very difficult and employs an optical flow method to measure the flow vector difference between the background and moving objects. Unfortunately, there is a huge calculation cost for obtaining accurate optical flow vectors. A new motion detecting method based on camera 3D motion analysis is proposed. With the special motion features of an on-board camera and FOE, our method can detect real moving objects simply by matching two adjacent frames. The camera 3D motion can theoretically be determined in our method with only three matching pairs, which makes it fast and more efficient for real-time applications. © 1999 IEEE.

关键词： Cameras

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SPARCS1 from the University of Victoria: Supporting sustainable and integrated outreach activities for educators and young minds

SPARCS1 from the University of Victoria: Supporting sustaina...

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2007 IEEE Meeting the Growing Demand for Engineers and Their Educators 2010-2020 International Summit, MGDETE 2007

作者： Murdoch, Jennifer St. Pierre, Anissa Agah Coady, Yvonne Carruthers, Sarah Gibbs, Celina Lonergan, Steven Srivastava, Gautam Stege, Ulrike Yazir, Onat Department of Computer Science Faculty of Engineering University of Victoria BC Canada

ISBN: (纸本)9781424419166

Although IT industry is flourishing, student enrolment in computer science and related engineering post-secondary degree programs is low. The causes and issues surrounding this trend are diverse, inter-related, and vastly complex;a consensus may never be reached regarding the nature of these issues affected by both global and local factors. Is a consensus regarding underlying causes and best practices required to create and sustain an infrastructure for effective outreach? Perhaps not. In this article, we discuss five key supportive mechanisms that are critical to sustained and integrated outreach initiatives at the grassroots level. We discuss these mechanisms using the example of SPARCS (Solving Problems with Algorithms, Robots, and computers), an initiative at the University of Victoria, British Columbia (BC), Canada. We further consider the tradeoffs associated with a vertical/centralized infrastructure versus a horizontal/distributed infrastructure. © 2007 IEEE.

关键词： engineering education

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Overview of Emerging Biological Computational Framework for Olfactory Studies Utilizing Contextual Technobiomedical engineering 2

Overview of Emerging Biological Computational Framework for ...

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2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Chaudhri, Shiv Nath Faculty of Engineering & Technology Department of Computer Science and Design Wardha India

ISBN: (纸本)9798331528713

Organoid intelligence (OI), the next paradigm of intelligence, draws inspiration from the biological learning of organs. On the other hand, artificial intelligence (AI) draws its inspiration only from the cognitive processes of the brain. While taking ethical and technological limitations into account, biological learning helps to conceptualize, accept, and apply them. Just as AI helped to make supercomputers possible, OI may help create biocomputers. Even though AI has increased the capabilities of technology to unimaginable heights, it still appears immature and is steadily moving toward cognitive computing to push the envelope even farther. In contrast to AI, OI is a new multidisciplinary computer area that attempts to be more approachable. OI has the ability to produce novel biocomputers, such as organoids, that use parts derived from live organisms to perform computational tasks. Organoids, such as human nasal organoids, are microscopic tissue cultures made from stem cells that mimic some of the functions of real organs. Although they have been used for many different purposes, including drug discovery and illness modeling, scientists are only now beginning to explore their potential for biological information processing. © 2024 IEEE.

关键词： Artificial Intelligence (AI) Biological Information Processing Biological Learning Olfactory Organoids Organoid Intelligence (OI)

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Atmospheric Attenuation at mmWave below 57GHz Based on Measurement in Tropical Region 16

Atmospheric Attenuation at mmWave below 57GHz Based on Measu...

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16th IEEE Malaysia International Conference on Communication, MICC 2023

作者： Li, Lu Sali, Aduwati Wali, Sangin Qahtan Universiti Putra Malaysia Faculty of Engineering Department of Computer and Communication Systems Engineering Selangor Serdang43400 Malaysia

ISBN: (纸本)9798350304343

According to ITU-R P.676-12, a modified prediction model of mmWave atmospheric attenuation suitable for tropical areas is proposed in this paper, named AA-mmWave. Combined with Malaysia's air humidity, temperature, and atmospheric pressure measured data in 2020 and 2021 via sensors, the mmWave atmospheric attenuation characteristic curve below 57GHz is simulated and calculated. The results show that the attenuation rate generally increases with frequency, especially from 55GHz to 57GHz, which increases until reaching the highest point of 5.937dB/km. Additionally, the atmospheric attenuation rate of a mmWave is inversely proportional to temperature and pressure. The lowest value of attenuation rate at 32°C achieves 0.3157 dB/km. Finally, there is a proportional correlation between water vapour density and mmWave atmospheric attenuation rate. This finding has essential and indelible reference value for developing mmWave transmission technology in the tropical region. © 2023 IEEE.

关键词： Atmospheric pressure

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MULTILAYER 3-D DISPLAY BY MULTIDIRECTIONAL BEAM SPLITTER

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APPLIED OPTICS 1982年第20期21卷 3659-3663页

作者： TAMURA, S TANAKA, K []The authors are with Osaka University Department of Information Computer Sciences Faculty of Engineering Science Toyonaka Osaka 560 Japan.

This paper describes a method of displaying 3-D images composed of several layers. Each layer image is placed at a different optical path length position from a viewing window and stacked by a multidirectional beam splitter to synthesize a composite 3-D image. Each layer image is overlapped at the corresponding depth. This display presents a real 3-D image and is fitted to show serial sectional images, multilayer wiring diagram, piping diagram, etc.

关键词： Apparent images Beam splitters Integral photography Light intensity Three dimensional imaging Three dimensional television

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Answer set application programming: A case study on Tetris 31

Answer set application programming: A case study on Tetris

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31st International Conference on Logic Programming, ICLP 2015

作者： Schüller, Peter Weinzierl, Antonius Department of Computer Engineering Faculty of Engineering Marmara University Turkey Institute of Information Systems TU Wien Austria

Answer-Set Programming (ASP) is a successful branch of the logic programming paradigm with many applications in modelling and solving of NP-hard problems. Combinatorial problems are the main application domain of ASP and it seems unsuitable for serving as a programming language for interactive applications. However, we conjecture that there is no theoretical obstacle for using ASP to that end. As witnessed by functional programming, it can be useful to use a declarative paradigm for creating applications. In this work we explore possibilities, benefits, and drawbacks, of programming an interactive application in ASP. We find that this is hard mainly for the following reasons: managing change over time, interaction with the user, generating output that is ordered (i.e., not a set), handling persistence of certain data, and ensuring efficiency. ASP and related fields provide powerful techniques for representing actions and change, executing programs with respect to external environments, and processing external events. Even if the full power of these techniques is not required to build an interactive application, combining them is necessary, and putting together these concepts in a practical framework is challenging. We realize such an integration in a framework we call Answer Set Application Programming framework which is based on the HEX language and features syntactic shortcuts to make application programming more intuitive. We describe design decisions and discuss alternative possibilities. Our sample application is a playable version of Tetris which demonstrates that ASP can be used as a general-purpose programming-language.

关键词： Knowledge representation

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SmartCoach: Comprehensive Tutor Recommender and Student Attentiveness Measuring Platform 3

SmartCoach: Comprehensive Tutor Recommender and Student Atte...

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3rd International Conference on Advancements in Computing, ICAC 2021

作者： Samarasekara, H.D.K. Hansaka, H.M.P. Rajapaksha, S.D.D. Tharaka, W.A.D.G. Manathunga, Kalpani Sriyarathna, Disni Charuka Faculty of Computing Department of Computer Science and Software Engineering Sri Lanka

ISBN: (纸本)9781665408622

With the pandemic, coaching or tutoring classes became to halt as the underlying system wasn't facilitating to adapt to emergency teaching mechanisms due to sparse of relevant technologies and tutor unawareness. SmartCoach is an integrated platform that allows students to find suitable tutors based on recommendations and other parameters like proximity, previous track record etc. using sentiment analysis and natural language processing. For tutors, SmartCoach allows publishing learning materials, automatic quiz creation, tracking attendance and, attentiveness during classes using OpenCV library. Moreover tutors get a dashboard featuring critical aspects about their classes and, personal income. This research is aimed to introduce a comprehensive distance learning platform with novel technological approaches that connect both potential students and tutors to a common platform. © 2021 IEEE.

关键词： Sentiment analysis

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Deepfake Detection: Emerging Techniques and Evolving Challenges 12

Deepfake Detection: Emerging Techniques and Evolving Challen...

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12th International Conference on Internet of Everything, Microwave, Embedded, Communication and Networks, IEMECON 2024

作者： Natarajan, Krishnaraj Mathur, Abeer Bhargava, Kshitiz Singh, Manvendra Tejpal, Moulik Department of Database Systems School of Computer Science & Engineering Vellore Institute of Technology Vellore India Department of Software Systems School of Computer Science & Engineering Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350387315

Several newly developed techniques and tools for manipulating images, audio, and videos have been introduced as an outcome of the recent and rapid breakthroughs in AI, machine learning, and deep learning. While most applications for these techniques or tools are in the fields of entertainment and education, some individuals with unlawful intent have also been benefited from them. These individuals use such techniques for various purposes, including the spread of misleading information and unnecessary propaganda, the incitement of political instability, hate and unrest, as well as for purposes of torture and blackmail. These high-quality and convincing manipulated images, audio, or videos are commonly referred to as ‘Deepfakes’. Since then, various solutions to the problems raised by Deepfakes have been proposed in academic studies. This literature review contains relevant publications that offered a variety of approaches to give an updated summary of the research activities in different types of Deepfake attacks, their detection, and countermeasures. It also assesses the effectiveness of the detection capabilities of different techniques with various datasets and algorithms applied in Deepfake detection, while also outlining the various benefits and drawbacks of various methodologies. © 2024 IEEE.

关键词： Deep learning

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Side Tracking in the Alimentary Supply Chain with Network Interface 11

Side Tracking in the Alimentary Supply Chain with Network In...

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11th International Conference on System Modeling and Advancement in Research Trends, SMART 2022

作者： Ali, Arif Madhuri, Sindhu Dev Bhoomi Uttarakhand University Dept of Computer Science and Engineering Uttarakhand Dehradun India Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9781665487320

In order to maintain sustainability and agricultural stability, the global world needs a complicated yet essential food supply system called a global food chain. In recent years, organisations involved in the food industry worldwide have often taken the food supply chain for given, forgetting that even a little disruption in the network might result in severe illness, shortages, or higher pricing. The most fragile individuals in society, such as the poor and small retailers and restaurants, are consistently impacted by this. The food supply chain has become broader and more complicated due to the expansion of the industry throughout the world, which prevents the old transportation model from meeting customer expectation. Food distribution chains face a number of difficulties, including poor traceability and connectivity, the availability of phoney food goods, and ineffective facility inspection. As a result, a system that provides accurate product details and a trustworthy transaction method are required. In this paper, we have outlined a complete approach to utilise Ethereum to improve the supply chain customer-centric. By providing genuine data about the products from the start, blockchain technology in the food business applies in a thoughtful and comprehensive approach to check and certify the food's quality items. This research effort includes discusses issue conceptualization, modelling, and performance monitoring. © 2022 IEEE.

关键词： Smart contract

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Predicting the Prices of the Used Cars using Machine Learning for Resale

Predicting the Prices of the Used Cars using Machine Learnin...

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2023 IEEE International Students' Conference on Electrical, Electronics and computer science, SCEECS 2023

作者： Hemendiran, B. Renjith, P.N. Vit University Department of Computer Science and Engineering with Specialization in Cyber Physical Systems Chennai India Vit University Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350398748

In this paper, we discuss the use of machine learning models that can accurately forecast the price of a used car based on its attributes and features. In this study, we look at applying supervised machine learning models to forecast second-hand car prices in India. The forecasts are based on historical information gathered from daily news articles, magazines and from various standard websites. The predictions were made using a variety of models, including Random Forest Regressor, Extra Tree Regressor, Bagging Regressor, Decision Tree and the XG Boost method. The most accurate predictions are then selected after comparing the predictions of the models applied. The five strategies all delivered performance that was almost equivalent but not equal and the results obtained are comparable. There are many distinct properties that can be measured, and it has taken a lot of effort to forecast the outcome with increased reliability and accuracy. These models are compared based on their prediction accuracy to determine which is more accurate. Our findings demonstrate that the Random Forest model produces the greatest outcomes. © 2023 IEEE.

关键词： Decision trees

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