2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE)最新文献_第2页

Optimized Dense Convolutional Neural Networks for Micro-expression Recognition 微表情识别的优化密集卷积神经网络

2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE) Pub Date : 2022-05-21 DOI: 10.1109/iscaie54458.2022.9794470

Koo Sie Min, Mohd Asyraf Zulkifley, N. A. Mohamed Kamari

{"title":"Optimized Dense Convolutional Neural Networks for Micro-expression Recognition","authors":"Koo Sie Min, Mohd Asyraf Zulkifley, N. A. Mohamed Kamari","doi":"10.1109/iscaie54458.2022.9794470","DOIUrl":"https://doi.org/10.1109/iscaie54458.2022.9794470","url":null,"abstract":"Micro-expressions are facial expressions that can reflect genuine human emotions. Alas, manual recognition of micro-expression is a time-consuming and arduous task due to its low-intensity reactions and brief occurrence. Convolutional layer, which is a well-known component in a deep learning architecture, are often used to learn the micro-level expression features so that the right micro-expression can be recognized. However, there is bound to be some feature loss when the feature maps are down-sampled towards the end of the network. If the loss occurs in the early layers, the network capability to learn the optimal features will be affected, which in turn degrades the model performance. In this paper, pooling layers are placed at the later layers, rather than the early layers to ensure optimal feature learning. In addition, a new set of hyperparameters are fine-tuned to deal with the learning problems caused by the modified pooling layers. For further improvement, the residual skip connections are also fed to forward layers, which are then combined using concatenate operator. The models require an input set of micro-expression onset-apex optical flow features to learn and recognize the correct emotion class; namely positive, negative, and surprise emotions. The overall recognition accuracy of micro-expression recognition has improved by around 4.83% compared to the base model. Hence, the proposed network improvements and modifications have managed to better recognize the correct micro-expression.","PeriodicalId":395670,"journal":{"name":"2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129718327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Empirical Mode Decomposition Method Based on Cardinal Spline and its Application on Electroencephalogram Decomposition 基于基数样条的经验模态分解方法及其在脑电图分解中的应用

2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE) Pub Date : 2022-05-21 DOI: 10.1109/iscaie54458.2022.9794540

Raymond Ho, K. Hung

{"title":"Empirical Mode Decomposition Method Based on Cardinal Spline and its Application on Electroencephalogram Decomposition","authors":"Raymond Ho, K. Hung","doi":"10.1109/iscaie54458.2022.9794540","DOIUrl":"https://doi.org/10.1109/iscaie54458.2022.9794540","url":null,"abstract":"This paper presents an improved empirical mode decomposition method called cardinal-spline empirical mode decomposition (CS-EMD). Unlike the classical empirical mode decomposition (EMD), the proposed method uses cardinal splines instead of cubic splines for signal envelope estimation. The decomposition performance of the CS-EMD method on synthetic signals is compared to the classical EMD method using performance evaluation indices. The orthogonal indices OIavg and OImax for an intermittent signal using CS-EMD are 0.0024 and 0.0105, respectively, compared to those of the classical EMD of 0.4438 and 1.9537 (closer to 0 is desirable). The energy conservation index (ECI) for the intermittent signal using CS-EMD is 0.9198 compared to 13.4496 using the classical EMD (closer to 1 is desirable). For a synthetic signal with components of close frequencies, the performance evaluation indices are OIavg=0.0019, OImax=0.0095, and ECI=0.8800 for CS-EMD and OIavg=0.0719, OImax=1.7821, and ECI=9.6610 for the classical EMD. Both EMD methods were also applied to an electroencephalogram (EEG), and the amount of mixed modes were observed and compared. The results show that the signal decomposition properties using CS-EMD are more desirable than those of the classical EMD, providing an improved EMD method for biosignal processing applications.","PeriodicalId":395670,"journal":{"name":"2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127214540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Performance Evaluation of Flowtable Eviction Mechanisms for Software Defined Networks considering Traffic Flows variabilities 考虑交通流变化的软件定义网络表驱逐机制的性能评价

2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE) Pub Date : 2022-05-21 DOI: 10.1109/iscaie54458.2022.9794547

Babangida Isyaku, Kamalrulnizam Bin Abu Bakar, Fuad A. Ghaleb, Sapiah Sulaiman

{"title":"Performance Evaluation of Flowtable Eviction Mechanisms for Software Defined Networks considering Traffic Flows variabilities","authors":"Babangida Isyaku, Kamalrulnizam Bin Abu Bakar, Fuad A. Ghaleb, Sapiah Sulaiman","doi":"10.1109/iscaie54458.2022.9794547","DOIUrl":"https://doi.org/10.1109/iscaie54458.2022.9794547","url":null,"abstract":"Software Defined Networks (SDN) is a new paradigm that emerged to improve network management through separation of control from the data plane using a standardized protocol. OpenFlow is the most popular standard to achieve the benefit of SDN. For every arrived flow, a corresponding flow entry is installed in the switch flowtable to guide the data transmission process. The proliferation of the Internet of Things (IoT) devices increases the number of flows generation unfortunately switch flowtable is constraint with limited space. Consequently, it led to flowtable overflow. Several studies leverage the First in First Out, Random replacement policy to removed old flow entries when the flowtable is overflowed. Although some performance gains were reported. However. Flows exhibit variabilities in terms of duration, inter-arrival-time, and the number of packets differs. Usually, some flows contain a large number of packets others have few packets. Applying these replacement policies may not always meet the demand of these types of flows. As such, this study experiments eviction mechanism to evaluate the performance of the two schemes and observe their eviction behavior with respect to flow features. On average FIFO preserved flows with a large number of packets by 4.95% while Random preserved by 36.11%. In conclusion, Random showed better performance compared to FIFO with respect to an increasing flow generation and change in flowtable size.","PeriodicalId":395670,"journal":{"name":"2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"274 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122915236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Implementation of Real Time Approach for Early Warning Gas Leakage Detection 煤气泄漏预警实时检测方法的实现

2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE) Pub Date : 2022-05-21 DOI: 10.1109/iscaie54458.2022.9794548

Anisa Qistina Binti Nor Azuwan, Tuan Norjihan Binti Tuan Yaakub, Anees Bt Abdul Aziz

引用次数: 1

PHYSICAL ACTIVITY TECHNIQUE MONITORING (PATMo) BASED POSE ESTIMATION USING CNN 基于身体活动技术监测(PATMo)的姿势估计

2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE) Pub Date : 2022-05-21 DOI: 10.1109/iscaie54458.2022.9794545

Wan Umar Farid Wan Khairilanwar, M. Yusoff

{"title":"PHYSICAL ACTIVITY TECHNIQUE MONITORING (PATMo) BASED POSE ESTIMATION USING CNN","authors":"Wan Umar Farid Wan Khairilanwar, M. Yusoff","doi":"10.1109/iscaie54458.2022.9794545","DOIUrl":"https://doi.org/10.1109/iscaie54458.2022.9794545","url":null,"abstract":"Exercising is a physical activity to increase the quality of life. However, exercising may come with various injuries ranging from minor to an injury that can cause fatality. Exercising requires gathering information to perform a specific physical activity with extreme caution and safety. Immediate feedback on human pose on performing a physical activity is a prime of importance to avoid harm to the human body. This study emphasizes pose estimation using a Convolution Neural Network model to identify a person’s key points. A prototype called Physical Activity Technique Monitoring (PATMo) embedded with Mobilenet-YOLOv3 and Simple Pose Tesnet18 v1b models is developed. PATMo focuses on a single movement and angle for receiving feedback for the physical activity. PATMo utilizes two optimizers and several batch sizes for parameter tuning. The batch size 32 with Adaptive Moment Estimation optimizer has the highest accuracy of 82.66% to Stochastic Gradient Descent, but the computational time took about 12 hours. More evaluations are expected with more powerful computer and Convolution Neural Network models variants. It is a starting point for further investigation to improve the feedback time during physical.","PeriodicalId":395670,"journal":{"name":"2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127828266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Simulation Performance Comparison of A*, GLS, RRT and PRM Path Planning Algorithms A*、GLS、RRT和PRM路径规划算法的仿真性能比较

2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE) Pub Date : 2022-05-21 DOI: 10.1109/iscaie54458.2022.9794473

A. Muhammad, N. R. Hasma Abdullah, Mohammed A. H. Ali, I. H. Shanono, R. Samad

引用次数: 0

Tiebreaker Vogel’s Approximation Method, a Systematic Approach to improve the Initial Basic Feasible Solution of Transportation Problems 一种改进交通问题初始基本可行解的系统方法——破铁Vogel近似法

2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE) Pub Date : 2022-05-21 DOI: 10.1109/iscaie54458.2022.9794502

Spencer Madamedon, E. Correa, P. Lisboa

引用次数: 0

Towards Personalized and Simplified Expository Texts: Pre-trained Classification and Neural Networks Co-Modeling 迈向个性化和简化说明文:预训练分类和神经网络协同建模

2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE) Pub Date : 2022-05-21 DOI: 10.1109/iscaie54458.2022.9794534

Safura Adeela Sukiman, Nor Azura Husin

{"title":"Towards Personalized and Simplified Expository Texts: Pre-trained Classification and Neural Networks Co-Modeling","authors":"Safura Adeela Sukiman, Nor Azura Husin","doi":"10.1109/iscaie54458.2022.9794534","DOIUrl":"https://doi.org/10.1109/iscaie54458.2022.9794534","url":null,"abstract":"The goal of automatic text simplification is to reorganize complex text structures into simpler, more comprehendible texts while retaining their original meaning. The automatic text simplification model, coupled with the personalization element, makes it an indispensable tool for assisting students with learning disabilities who struggle to comprehend expository texts found in school textbooks. In recent years, neural networks have been widely embraced in simplified text generation, with most earlier researchers focusing on the Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), and Transformer models. In general, however, the majority of their efforts resulted in simple, generic texts, and a lack of cognitive-based personalization elements was found in their models. In this paper, we present the concept of generating personalized and simplified expository texts by joining both pre-trained classification and neural networks models. The pre-trained classification aims to predict complex text structures and phrases that give challenges for students with learning disabilities to comprehend, while the neural networks model is then used to generate simplified expository texts based on the predicted text complexity. The advantage of these joint models is the ability to generate simplified expository texts adapted to the cognitive level of students with learning disabilities. This opens up opportunities for continuously personalized learning, makes them less struggling, and increases their motivation to stay competitive with their peers.","PeriodicalId":395670,"journal":{"name":"2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115994423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of an Automated and Electronic Transport System 发展自动化及电子运输系统

2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE) Pub Date : 2022-05-21 DOI: 10.1109/iscaie54458.2022.9794513

Bennyvic Joyce J. Esguerra, Ma. Ivy Aragon, Christian Cavita, Anthony James Pamil, David Robles, Roderick C. Tud, Marvin S. Verdadero

{"title":"Development of an Automated and Electronic Transport System","authors":"Bennyvic Joyce J. Esguerra, Ma. Ivy Aragon, Christian Cavita, Anthony James Pamil, David Robles, Roderick C. Tud, Marvin S. Verdadero","doi":"10.1109/iscaie54458.2022.9794513","DOIUrl":"https://doi.org/10.1109/iscaie54458.2022.9794513","url":null,"abstract":"The Automated and Electronic Transport System for the Blind is a project developed with the use of new advancements in microcontroller and sensor technology applied in electronic-controlled vehicles. This study uses a Product Development Design wherein the researchers focused on developing an Automated and Electronic Transport System for the Blind which included designing the sub-systems responsible for the operation of the transport system and its physical appearance, determining the appropriate components and suitable materials for the transport system and evaluating its performance in terms of its functionality, and safety. It has an automated navigation system responsible for controlling the movement of the transport system from one station to another. The researchers incorporated object detection and automatic speed regulation for the safety of the passenger. The transport system was integrated with a manual operation controlled by a yoke for direction and speed, a pedal for the braking system, and switches for other peripherals. The transport system can operate at a maximum speed of ten kilometers per hour during its automated operation which matches the maximum speed of existing electric wheelchairs in the market. The prototype can carry a maximum weight capacity of one hundred kilograms (100 kg). The researchers gathered data in evaluating its performance in terms of its functionality and safety. It can be used by visually-impaired persons in schools, industrial plants, parks, other persons with disability.","PeriodicalId":395670,"journal":{"name":"2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127921325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bitcoin Price Prediction- an Analysis of Various Regression Methods 比特币价格预测——各种回归方法分析

2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE) Pub Date : 2022-05-21 DOI: 10.1109/iscaie54458.2022.9794532

Komal Soni, Sugandha Singh

引用次数: 0