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检索条件"任意字段=2022 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2022"

共 960 条记录，以下是51-60 订阅

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Predicting Habitual Activities for Reducing Perceived Latency

Predicting Habitual Activities for Reducing Perceived Latenc...

引用

2022 ieee asia-pacific conference on computer science and data engineering, csde 2022

作者： Deng, YuFeng Manoharan, Sathiamoorthy Ye, Xinfeng School of Computer Science University of Auckland Auckland New Zealand

ISBN: (纸本)9781665453059

Human activities are usually habitual, following some patterns. The patterns make these activities predictable. A number of our activities these days are online, and these activities require us to access resources from online sources, incurring data transfer latencies. Being able to predict the patterns in online activities allows automatic prefetching of these resources so that the perceived latency of accesses can be vastly reduced. While there is a lot of prior research to predict short-term activities, research relating to predicting long-term habitual activities is sparse. This paper attempts to address the general area of how long-term habitual activities can be predicted. It proposes a model using long short-term memory (LSTM) capable of learning long-term habitual activities and predicting future activities based on this model. Our experimental evaluation shows that the prediction accuracy is promising. © 2022 ieee.

关键词： data transfer

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Choosing Suitable Object Detection Method to Examine Pigment Powders of Similar Shape

Choosing Suitable Object Detection Method to Examine Pigment...

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2022 ieee asia-pacific conference on computer science and data engineering, csde 2022

作者： Wakabayashi, Naoya Shimakawa, Hiromitsu Graduate School of Ritsumeikan Uni. Information Science and Engineering Shiga Kusatsu Japan

ISBN: (纸本)9781665453059

In recent years, a variety of paints have been developed in response to the diversification of color design. Due to the powder manufacturing process, different sizes of powders may randomly attach to each powder. Since the objects attached to larger ones affect the quality of the product, they are specifically referred to as asteroid powder. Asteroid powders are similar in shape have many problems and it difficult to detect. This paper investigates whether an object detection method can automatically detect asteroid powders. It also tries to choose a suitable detection method. The paper compared two typical object detection methods YOLO and SSD. As a result, it has turned out YOLO works far better than SSD. © 2022 ieee.

关键词： Object detection

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Driver Fatigue Detection Using OpenCV and Dlib Library

Driver Fatigue Detection Using OpenCV and Dlib Library

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2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Shen, Kuang Ramli, Rusyaizila Chuah, Joong Huang Chai, Grace Mei Ting School of Electronics and Computer Science University of Southampton Southampton United Kingdom University of Southampton Malaysia Carbon Neutrality Research Group Johor Iskandar Puteri79100 Malaysia University of Malaya Faculty of Engineering Department of Electrical Engineering Kuala Lumpur50603 Malaysia University of Southampton Malaysia Smart Manufacturing System Reasearch Group Johor Iskandar Puteri79100 Malaysia

ISBN: (纸本)9798350341072

Driver fatigue and distraction are major contributors to fatal road accidents worldwide. To enhance vehicle safety, this article proposes a fatigue detection system using EAR and MAR algorithms to identify signs of fatigue, such as eye closure and yawning. When prolonged eye closure or yawning is detected, the system issues an alert to the driver. It leverages OpenCV and Dlib libraries for implementation. Additionally, the system detects driver distraction by monitoring head swivels, counting left and right movements. It's worth noting that Dlib may yield facial landmark deviations for non-frontal faces. To mitigate this, the study selected 69 videos from the YawDD database, focusing on near-frontal face views, achieving a 91.3% accuracy rate. © 2023 ieee.

关键词： Vehicle safety

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Cluster Analysis Using Explainable AI for Confused Learners

Cluster Analysis Using Explainable AI for Confused Learners

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Samani, Chaitali Musial, Katarzyna School of Computer Science University of Technology Sydney Sydney Australia School of Computer Science University of Technology Sydney Complex Adaptive Systems Lab Sydney Australia

ISBN: (纸本)9798350341072

The process of learning is multifaceted and intricate, with confusion playing a pivotal role in engagement and motivation. Confusion arises from a disequilibrium that a learner may have due to some knowledge misconceptions when performing cognitive tasks. While some form of confusion can lead to better achievements in such tasks, prolonged confusion causes frustration and disengagement. So, to maintain a balance between less confused to highly confused states is highly crucial. In this study we propose explainable clustering technique for confused learners. In this study we first dig deeper into the set of confused learners and form clusters using K-Means clustering. K-Means clustering provides the clusters like a black-box technique is since the purpose of this clustering was to better understand the confused learners, we extended the clustering with tree-based approach that explains why a particular learner was placed in a particular cluster. This explainability provides an opportunity to design better intervention strategies to control confusion in learners © 2023 ieee.

关键词： K-means clustering

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Automated Chemical Mixing Plant

Automated Chemical Mixing Plant

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2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Nadarajah, Srikanthan Muralitharan, Rasendram Jayasinghe, Upul Ragel, Rohan G Sasitharagurukkal, Muthusamyiyer Inuvaisubramaniam, Nilani Rockwell Collins United States Faculty of Engineering University of Peradeniya Department of Computer Engineering Sri Lanka Office of the Deputy Chief Secretary Engineering Service Northern Province Sri Lanka

ISBN: (纸本)9798350341072

The chemical mixing plant could be automated using supervisory control and data acquisition (SCADA) technique. The SCADA system contains a central control unit, a remote terminal unit, and a communication medium. The chemical mixing plant operator may use the central control unit to automate the operations of the chemical mixing plant. The field devices of the chemical mixing plant are connected with the remote terminal unit. Ethernet, Profinet, or WAN network could be used to establish the communication medium between the central control unit and the remote terminal unit. The central control unit acts as the server and the remote terminal unit act as the client. The simple server-client communication system is used to exchange the messages between the central control unit and remote terminal unit. The communication medium uses Genesys protocol to exchange the messages between the central control unit and the remote terminal unit. © 2023 ieee.

关键词： SCADA systems

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Analysis Support by Estimating Speaker's State in Sensor-Based Active Listening

Analysis Support by Estimating Speaker's State in Sensor-Bas...

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2022 ieee asia-pacific conference on computer science and data engineering, csde 2022

作者： Yoshida, Shinjiro Shimakawa, Hiromitsu Harada, Fumiko Graduate School of Information Science and Engineering Ritsumeikan University Shiga Japan College of Information Science and Engineering Ritsumeikan University Shiga Japan Research Organization of Science and Technology Ritsumeikan University Shiga Japan

ISBN: (纸本)9781665453059

This study examines whether the speaker's state during active listening can be estimated using sensors. Few studies work on active listening, where the elderly get refreshed through their talking. This study extracts important features from the data obtained from the accelerometer and tension sensors measuring the speaker's body movement during active listening utilizing tips to promote talking. To verify the effectiveness of the proposed method, an experiment is conducted. New findings on listening were obtained. The delay of the body movements is clarified for each kind of tips. The transition of the speaker's state was found to be characterized by the speaker's body movement which appears after the transition. The data obtained from the tension sensor turns out to be the most important explanatory variable. © 2022 ieee.

关键词： Machine learning

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Food Affection Determination Through Biosignal Based Affective Computing

Food Affection Determination Through Biosignal Based Affecti...

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2022 ieee asia-pacific conference on computer science and data engineering, csde 2022

作者： Islam, Tanvir Joyita, Anika Rahman Ananna, Aisha Rahmot Khandoker, Rafi Ahsan, Fatema Alam, Md. Golam Rabiul University of Hawai'i at Mānoa Information and Computer Sciences HonoluluHI United States Brac University Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9781665453059

When people seek food, their emotions shift, and not all foods are appealing in all moods. It is incredibly tough to learn people's eating habits and provide advice depending on their emotions at the time. The goal of this study is to create a system that will categorize emotional information from meals based on a person's present emotion. This study proposes a technique for evaluating a person's emotion using an electroencephalogram (EEG) output. To that purpose, we organized trials for EEG data collecting as well as questionnaires. On the raw data, a prominent feature extraction approach known as Discrete Wavelet Transform (DWT) was utilized, and Gradient Boosting Classifier and AdaBoost Classifier were used for affectivity classification. We obtained a notable Accuracy Score and AUC Score from these classifiers in this study. © 2022 ieee.

关键词： Discrete wavelet transforms

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Is Cybersecurity Winning: A CrossSectional Study in Fiji

Is Cybersecurity Winning: A CrossSectional Study in Fiji

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2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Reddy, Pritika Goundar, Munil Shiva Khan, Shaireen Shabnam Sharma, Bibhya Fiji National University Department of Computing Science and Information Systems Suva Fiji Health Information and Intelligence Unit Aspen Medical Lautoka Fiji School of Information Technology Engineering Mathematics and Physics The University of the South Pacific Suva Fiji

ISBN: (纸本)9798350341072

The advent of the Internet, as well as the increasing use of various web applications, social media platforms, and the Internet of Things, are posing online threats to people. Moreover, with the growing dependence on Industry 4.0 operations, cybersecurity awareness and practices have become more important to organizations and countries than ever before. The current study intends to evaluate cybersecurity practices and awareness at a local education service provider in Fiji. A quantitative methodology comprising an online survey was administered to collect responses from its students who are employees from 22 different organizations in Fiji. The results of the study showed that the employees in Fiji have an average awareness of cyber hygiene. The highly positive correlation value between employee response to cybersecurity practices and awareness indicates that some organizations follow good cyber hygiene. The results from this study indicate that organizations in Fiji need to be more vigilant to defend themselves from the raising cyber threats and vulnerabilities. © 2023 ieee.

关键词： Cybersecurity

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Framework for Pre-processing, Feature-extraction, and Specialisation of Nominal data

Framework for Pre-processing, Feature-extraction, and Specia...

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2022 ieee asia-pacific conference on computer science and data engineering, csde 2022

作者： Aryal, Krishna Jha, Meena School of Engineering and Technology Central Queensland University Sydney Australia

ISBN: (纸本)9781665453059

There have always been many challenges to understand and use nominal data as effectively as numerical data. The judgment-based scaling of nominal data is not as efficient as a formula-based transformation of numerical data where mean, mode, median, and standard deviation are calculated. In this paper, we propose a novel framework to process nominal data by transforming nominal attributes into equivalent statistically significant values for any given data domain. The transformation process has three stages. The three stages consist of addition of domain knowledge, preservation of collected attributes/features, and evaluation of numerical values by identifying co-relations and similarities of the features. These three stages in the framework will help improve the nominal data processing and will address issues related to knowledge transformation such as adding existing knowledge to the data domain, data loss such as rejecting less relevant attributes, and feature transformation such as transforming the values while processing nominal data. © 2022 ieee.

关键词： Extraction

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Generating Robust Convolutional Networks by Injecting Partial Noise in the Training data

Generating Robust Convolutional Networks by Injecting Partia...

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2022 ieee asia-pacific conference on computer science and data engineering, csde 2022

作者： Pilzak, Artem Thivierge, Jean-Philippe School of Psychogy University of Ottawa Ottawa Canada

ISBN: (纸本)9781665453059

Convolutional Neural Networks (CNN) have emerged as a highly efficient deep learning algorithm for processing, classifying, and analyzing images. Currently, there is a high demand for networks that are robust to noise in the training and testing data. However, the presence of noise in images has been an ongoing problem when it comes to deploying CNN for real-world applications. In this paper, we propose a solution to this problem by incorporating noisy and noise-free images in the training set of a CNN network. Using the Modified National Institute of Standards and Technology database (MNIST), we demonstrate that marked improvements to classification accuracy only require a small proportion of noisy images in the training set. This result generalized across test sets with different amounts of noise and types of noise. In sum, our novel training method increases the generalization of a CNN model when processing noisy data. © 2022 ieee.

关键词： computer vision

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