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Applied Imagery Pattern Recognition Workshop (AIPR)

作者： Yu Li Rana Das Cuong Duong Teng-Teeh Lim Timothy Haithcoat Ilker Ersoy Chi-Ren Shyu Department of Electrical Engineering and Computer Science University of Missouri Columbia MO US Biological Engineering University of Missouri Columbia MO US Plant Science and Technology Extension University of Missouri Columbia MO US Institute for Data Science and Informatics University of Missouri Columbia US Institute for Data Science and Informatics University of Missouri Columbia MO US Electrical Eng. and Computer Science Dept. Institute for Data Science and Informatics University of Missouri Columbia MO US

Poultry productions have shifted towards larger farms and often cluster in certain regions. However, many of the smaller farms with a considerable amount of production are not considered concentrated animal feeding operation under regulation in many regions, and therefore are not required to obtain a permit. As a result, information of these operations is not being recorded and monitored, contributing to an increased risk for biosecurity issues. The development in computer vision and availability of high-resolution remote sensing imagery allows the possibility for automatic localization and operation estimation of the unregistered farms, filling in the missing information needed for biosecurity risk management. The farm information extracted from images can be incorporated with other available geospatial data, such as road networks, watersheds, etc., to build a comprehensive knowledge base for actionable plans. In the current study, we present a framework for automated localization, analysis, and visualization of poultry farms from remote sensing images. A robust machine learning method was developed to computationally link the visual features from remote sensing imagery to Missouri Department of Natural Resources Concentrated Animal Feeding Operation data, to identify the animal farm type, location, and potential capacity in the region. The developed process can be performed automatically on images of different timestamps to analyze temporal and spatial development of poultry production facilities of a region. This research contributes to the effective management and regulation of poultry and potentially other animal farms, providing insights into farm characteristics and capacities while facilitating informed decision-making.

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Effect of Interest Variation and Prefix Length on Pending Interest Table (PIT) Performance in Named Data Networking (NDN)

Effect of Interest Variation and Prefix Length on Pending In...

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International Conference on Wireless and Telematics (ICWT)

作者： Helmi Ahmad Khaderani Ishlah Muhammadi Lutfi Razan Muhammad Adi Sucipto Luthfi Restu Kusumastuti Ade Nurhayati Syaiful Ahdan Nana Rachmana Syambas Dept. of Telecommunication Engineering Bandung Institute of Technology Bandung Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia Faculty of Engineering & Computer Science Universitas Teknokrat Indonesia Lampung Indonesia Faculty of Engineering Telkom University Jakarta Barat Indonesia

Pending interest table (PIT) is one of the data structures on each named data network router. The speed of delivery of interest as well as the interest served at PIT are several important parameters for measuring PIT performance. This research was conducted to analyze the performance of PIT by measuring the round trip time (RTT) of sending data and sending interests from consumers to producers on the Palapa Ring Sumatra topology. Testing is carried out using miniNDN by varying the length of the prefix and the number of interests sent. From the simulation and results of the analysis that has been carried out, it is known that the correlation between the length of the prefix and RTT is directly proportional. The longer the prefix of an interest packet, the higher the RTT value. Apart from the simulation results, the number of interest packets sent is the same as those received at each node.

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Video Streaming QoS Analysis with TIPHON Standard NDNts

Video Streaming QoS Analysis with TIPHON Standard NDNts

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International Conference on Wireless and Telematics (ICWT)

作者： I Made Aditya Putra J.D Lisdatul Alifa Muhammad Hilmi Fawwaz Nissha Kinaya Mauren Sibayak Ratna Mayasari Hasan Nur Arifin Syaiful Ahdan Ridha Muldina Negara Nana Rachmana Syambas Dept. of Telecommunication Engineering Bandung Institute of Technology Bandung Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia School of Electrical Engineering Telkom University Bandung Indonesia Faculty of Engineering & Computer Science Universitas Teknokrat Indonesia Lampung Indonesia

Named data networks are a new concept in network architecture that can process data transmission by name. This concept can be utilized in the case of video streaming. TIPHON is a standard used to support streaming multimedia activities. According to TIPHON, three factors-delay, packet loss, and throughput-can influence how a stream behaves. This study's goal is to evaluate the quality of service (QoS) of video streaming services using an NDN network that adheres to the TIPHON NDN standard. Several things can affect throughput, such as bottlenecks on the computer or network device used.

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Queuing Theory Approach for NDN Mobile Producer's Rate of Transmission Using Network Coding

Queuing Theory Approach for NDN Mobile Producer's Rate of Tr...

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2021 International Congress of Advanced Technology and engineering, ICOTEN 2021

作者： Ahmed, Muhammed Zaharadeen Hashim, Aisha Hassan Abdallah Khalifa, Othman Omran Alsaqour, Raed Ali Saeed, Rashid Abdelhaleem Alkali, Abdulkadir Hamidu International Islamic University Malaysia Dept. of Electric and Computer Engineering Kuala Lumpur Malaysia Saudi Electronic University College of Computing and Informatics Riyadh Branch Saudi Arabia Taif26571 Saudi Arabia University of Maiduguri Deparmtent of Computer Engineering Maiduguri Nigeria

ISBN: (纸本)9781665412247

Nowadays, Internet has become a crucial part of everyday life in areas of academic research, healthcare, military, commercial industries, transportation, and entertainment. The Internetwork was not invented for its present-day state of operation. Numerous limitations are currently emerging in terms of Internet performance, mobility, scalability, dependability, security, and service quality. In this paper we consider real time network application for voice and video, both having variable bitrate sources. A mobile producer is solely responsible to direct the traffic to a specified destination, either in one network or different. For voice traffic, a constant bitrate (CBR) is generated in real time during a talkspurt. During this generation interval, a small amount of traffic is transmitted in a period of silent pause. For video traffic, the bitrate is changed because video coding form is altering due to time interval. Also, the visible image in the proposed video application varies due to network coding application. In the results, performance analysis is measured due to amount of time spend in each cell residence and signalling cost between mobile producer and rendezvous node as a definite destination. We conducted simulation coding in ndnSIM 2.1 and performance analysis using Python. Simulation output present better results compared with other benchmarked research. © 2021 IEEE.

关键词： Python

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Intra-Datacenter Load Balancing in a Federated Cloud with Throttled Algorithm

Intra-Datacenter Load Balancing in a Federated Cloud with Th...

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2024 International Conference on Science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Akinola, Damola Gideon Adetiba, Emmanuel Abayomi, Abdultaofeek Nnaji, Uche Thakur, Surendra Moyo, Sibusiso Covenant University Covenant Applied Informatics and Communications African Center of Excellence Department of Electrical and Information Engineering Ota Nigeria Durban University of Technology HRA Institute for Systems Science Durban South Africa Mangosuthu University of Technology Department of Information and Communication Technology Durban South Africa Covenant University Dept. of Computer and Information Science Covenant Applied Informatics and Communications African Center of Excellence Ota Nigeria Durban University of Technology KZN E-Skills CoLab Durban South Africa Stellenbosch University School for Data Science and Computational Thinking Department of Mathematical Sciences Stellenbosch7602 South Africa

ISBN: (纸本)9798350358155

The emergence of cloud computing technology has motivated a very high number of users in different organizations to access its services in running and delivering their various operations and services. However, this surge of cloud users has led to the problem of uneven load sharing among the cloud computing infrastructures. As a result, federated cloud infrastructure was initiated to provide more cloud computing resources to accommodate more cloud users' requests and also to provide equal requests mapping with the available cloud resources. Nevertheless, the issue of unequal allocation of requests within the datacenter(s) that makes up the federated cloud environment still persists. This research work presents an intra-datacenter load balancing algorithm in a federated cloud environment named;the intra-balancer adapted throttled algorithm to evenly distribute requests in each datacenter that formulate the federated cloud infrastructures. The simulation of the intra-balancer was carried out in CloudAnalyst, the results of the implementation showed that the intra-balancer outperformed the Round-Robin and ESCE with 98.93ms and 2.26ms for the response and processing time respectively. The results assert that the intra-balancer algorithm provides a better load balancing solution in a federated cloud environment. © 2024 IEEE.

关键词： Cloud platforms

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On recognizing occluded faces in the wild

arXiv

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arXiv 2021年

作者： Erakın, Mustafa Ekrem Demir, Ugur Ekenel, Hazım Kemal Faculty of Computer and Informatics Dept. of Computer Engineering Maslak Istanbul34469 Turkey

Facial appearance variations due to occlusion has been one of the main challenges for face recognition systems. To facilitate further research in this area, it is necessary and important to have occluded face datasets collected from real-world, as synthetically generated occluded faces cannot represent the nature of the problem. In this paper, we present the Real World Occluded Faces (ROF) dataset, that contains faces with both upper face occlusion, due to sunglasses, and lower face occlusion, due to masks. We propose two evaluation protocols for this dataset. Benchmark experiments on the dataset have shown that no matter how powerful the deep face representation models are, their performance degrades significantly when they are tested on real-world occluded faces. It is observed that the performance drop is far less when the models are tested on synthetically generated occluded faces. The ROF dataset and the associated evaluation protocols are publicly available at the following link https://***/ekremerakin/RealWorldOccludedFaces. © 2021, CC BY-NC-ND.

关键词： Face recognition

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Lane Departure Warning based on Road Marking Detection using Mask Region-based Convolutional Neural Networks

Lane Departure Warning based on Road Marking Detection using...

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International Conference on Electrical engineering, computer and Information Technology (ICEECIT)

作者： Ilham Ramadani Arianto Eko Mulyanto Yuniarno Reza Fuad Rachmadi Dept. of Electrical Engineering Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Computer Engineering Dept. of Electrical Engineering Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (纸本)9781665464277

Lane departure warning system (LDW) is a system where when the condition of the car being driven on the road and maneuvering out of the lane without the driver realizing it, there is a visual or audible warning that will allow the driver to correct the maneuver. In implementing this system, tracking is needed on road lane line markings. One way to detect road markings is to use a camera that is placed on the windshield in the middle of the car with various methods. In previous research, the method used was using image filters, namely Hough Transform and Canny Edge. This method is quite effective on straight road conditions and sunny conditions without any obstacles. The weakness is when the road conditions start to turn quite sharply and also in low light conditions. In this study, the proposed method for tracking road markings is Mask Regional-based Convolutional Neural Networks (Mask R-CNN). This method is the latest development of the existing image segmentation method. The tracking process is with input from the video camera and then pre-processing is carried out to reduce distortion and calibrate the incoming frame. After that, the detection process uses a Mask R-CNN and the output will be line fitting to get the middle point and the right and left lines. After that the last process is Lane Departure Warning where the midpoint when approaching the line will give a warning to the driver.

关键词： Visualization Roads Transforms Cameras Surface texture Convolutional neural networks Automobiles

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A Model for Intelligible Interaction Between Agents That Predict and Explain

arXiv

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arXiv 2023年

作者： Baskar, A. Srinivasan, Ashwin Bain, Michael Coiera, Enrico Dept. of Computer Science Information Systems BITS Pilani Goa Campus India Dept. of Computer Science Information Systems and APPCAIR BITS Pilani Goa Campus India School of Computer Science Engineering University of New South Wales Australia Centre for Health Informatics Macquarie University Sydney Australia

Machine Learning (ML) has emerged as a powerful form of data modelling with widespread applicability beyond its roots in the design of autonomous agents. However, relatively little attention has been paid to the interaction between people and ML systems. In this paper we view interaction between humans and ML systems within the broader context of communication between agents capable of prediction and explanation. We formalise the interaction model by taking agents to be automata with some special characteristics and define a protocol for communication between such agents. We define One- and Two-Way Intelligibility as properties that emerge at run-time by execution of the protocol. The formalisation allows us to identify conditions under which run-time sequences are bounded, and identify conditions under which the protocol can correctly implement an axiomatic specification of intelligible interaction between a human and an ML system. We also demonstrate using the formal model to: (a) identify instances of One- and Two-Way Intelligibility in literature reports on humans interacting with ML systems providing logic-based explanations, as is done in Inductive Logic Programming (ILP);and (b) map interactions between humans and machines in an elaborate natural-language based dialogue-model to One- or Two-Way Intelligible interactions in the formal model. © 2023, CC BY.

关键词： Inductive logic programming (ILP)

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Smart Odontogram: Dental Diagnosis of Patients Using Deep Learning 23

Smart Odontogram: Dental Diagnosis of Patients Using Deep Le...

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23rd International Electronics Symposium, IES 2021

作者： Fadhillah, Excel Daris Bramastagiri, Pravasta Caraka Sigit, Riyanto Sukaridhoto, Sritrusta Brahmanta, Arya Dewantara, Bima Sena Bayu Politeknik Elektronika Negeri Surabaya Dept. of Informatics and Computer Engineering Surabaya Indonesia Politeknik Elektronika Negeri Surabaya Department of Electronic Engineering Surabaya Indonesia Universitas HangTuah Surabaya Department of Orthodontic Surabaya Indonesia

ISBN: (纸本)9781665443463

Odontogram is a medical record for dental patient. It records the condition of patient's tooth and helps dentist to diagnose patient's tooth and to provide further treatment. Though, many dentists do not fill odontogram completely because either they are too busy to treat other patient, or they run out of odontogram form. Therefore, this research aims to build a platform that could help dentists to create, store, and analyze dental medical record called Smart Odontogram. The platform consists of cloud computing and edge computing. The cloud computing act as a server to store and analyze medical record using big data technology and deep learning, while the edge computing diagnoses the patient's tooth using intraoral camera with the help of artificial intelligence. The AI used in this platform is using deep learning method with YOLO algorithm. The test result shows that the model accuracy for diagnosing dental disease is 85.7% and tooth classification is 99.3%. The delay result for storing medical record on the cloud has average latency 5734.2ms, retrieve patient's medical record is 91.2ms, and analytic simulation time when uploading and analyze tooth image simultaneously is 1008.8ms. © 2021 IEEE.

关键词： Edge computing

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A Study of the Ecological Dynamics of Batumi, on the Black Sea Coast, Analyzing Environmental Factors and Their Impact

A Study of the Ecological Dynamics of Batumi, on the Black S...

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International Black Sea Conference on Communications and Networking (BlackSeaCom)

作者： Lily Petriashvili Irine Khomeriki Mzia Kiknadze Tamar Lominadze Nona Otkhozoria Dept. of Program Engineering Georgian Technical University Tbilisi Georgia Dept. of Interdisciplinary Informatics Georgian Technical University Tbilisi Georgia Dept. of Computer Engineering Georgian Technical University Tbilisi Georgia Dept. of Information Systems Georgian Technical University Tbilisi Georgia Dept. of Microprocessor and Measurement Systems Georgian Technical University Tbilisi Georgia

ISBN: (数字)9798350351859

ISBN: (纸本)9798350351866

This paper studies the complex ecological dynamics of Batumi on the Black Sea coast, through adetailed analysis of environmental factors and their impact. We use Business Intelligence (BI) methods to explore the complex interactions between natural and human impacts on the local ecosystems. By using data-focused approaches, including statistical analysis and predictive modeling, we aim to distinguish patterns and trends in ecological dynamics. This study aspires to make clear the complex relationships between environmental factors such as climate change, pollution levels, habitat degradation, and biodiversity loss, and their impacts on the coastal ecosystem of Batumi. Through this study, we aim to provide valuable information on sustainable management practices and conservation measures to protect the ecological integrity of this important coastal region.

关键词： Sea coast Pollution Statistical analysis Ecosystems Habitats Sea measurements Predictive models

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