2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)最新文献_第3页

Color and Texture Feature based for Maize Leaf Disease Identification 基于颜色和纹理特征的玉米叶片病害识别

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037498

I. Siradjuddin, Arif Riandika, W. Agustiono

引用次数: 1

Automatic Measurement of Spinous Process Angle on Ultrasound Spinal Column Image 超声脊柱图像棘突角的自动测量

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037464

Gabriela Zurliana Said, T. A. Sardjono, Nada Fitrieyatul Hikmah

引用次数: 0

Correlation-Based Feature Selection on Botnet Activity Detection Using Kendall Correlation 基于肯德尔相关性的僵尸网络活动检测特征选择

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037525

Dandy Pramana Hostiadi, Yohanes Priyo Atmojo, Roy Rudolf Huizen, I. M. D. Susila, Gede A. Pradipta, I. M. Liandana

{"title":"Correlation-Based Feature Selection on Botnet Activity Detection Using Kendall Correlation","authors":"Dandy Pramana Hostiadi, Yohanes Priyo Atmojo, Roy Rudolf Huizen, I. M. D. Susila, Gede A. Pradipta, I. M. Liandana","doi":"10.1109/CENIM56801.2022.10037525","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037525","url":null,"abstract":"Botnets are a dangerous threat to computer networks that uses malicious code to infect computer networks. Thus, the right system security model is needed to detect botnet attack activities accurately. Several previous studies have introduced a botnet detection model using mining-based, but it requires the correct approach to obtain the optimal performance. This paper proposes a botnet detection model by improving feature selection using correlation-based analysis. The aim is to improve accuracy detection by analyzing features with solid correlations that can be used for machine learning classification models. The proposed model consists of 4 main parts: data splitting pre-processing, classification process, and evaluation. The experiment used public datasets, namely CTU-13 datasets containing botnet activity. The experiment shows that the model can detect botnet activity with a detection accuracy of 99.7218%, precision of 99.1691 %, and recall of 96.6533 %. The proposed model can improve the existing botnet detection system model.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116287525","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

C-Band Horn Antenna Fed by Rectangular Microstrip Patch 矩形微带贴片馈电的c波段喇叭天线

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037250

B. Mahatmanto, Dedi Irawadi, A. Pascawati, C. Apriono

引用次数: 0

Frequency Stability Analysis on Optimization of Virtual Inertia Controller Settings Based on Retired Electric Vehicles Battery Using Firefly Algorithm 基于退役电动汽车电池的虚拟惯性控制器设置优化的萤火虫算法频率稳定性分析

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037414

Baity Nuris Syifa, D. A. Asfani, A. Priyadi, H. Setiadi

{"title":"Frequency Stability Analysis on Optimization of Virtual Inertia Controller Settings Based on Retired Electric Vehicles Battery Using Firefly Algorithm","authors":"Baity Nuris Syifa, D. A. Asfani, A. Priyadi, H. Setiadi","doi":"10.1109/CENIM56801.2022.10037414","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037414","url":null,"abstract":"Virtual Inertia Control (VIC) provides simultaneous inertia and damping to grid-connected to enhancing system inertia and damping, keeping the stability of system frequency during Renewable Energy Source (RES) penetration. VIC consist of an Energy Storage System (ESS), inverter, and inertia control technique. This paper uses retired EV battery due to it is potential as a power source for VI, which it can be used as an ancillary service to grid (i.e., frequency regulation), such as to smoothing the output power of RES that caused by it is intermittent characteristic. VIC parameters need to be optimized to get better frequency response. In the current trend, the metaheuristic algorithm is widely used for optimizing VIC parameters. This paper implemented Firefly Algorithm (FA) for optimizing VIC parameters. The results of this paper have been conducted in two secnarios. The simulation result after 10 running simulations with 100 iterations are the standard deviation for FA is 50 percent smaller than PSO for scebario 1 and and 20.8 percent smaller than PSO for scenario 2. Moreover, FA also has a 92 percent faster running time than PSO for scenario 1, and 93 percent faster running time than PSO for scenario 2. From the optimization result, in scenario 1, FA for the VIC parameters optimization is more effective in reducing frequency oscillations and results in 21.5 percent faster settling time but in exchange will make 3 percent greater overshoot and undershoot frequencies than optimizing VIC based on PSO parameters. In scenario 2, due to optimization VIC parameters obtained by FA and PSO have similar results and it makes the frequensy response are also similar.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133372356","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

Multi-Person Key Points Detection for Abnormal Human Behavior Analysis Using The ConvLSTM-AE Method 基于ConvLSTM-AE方法的人异常行为分析的多人关键点检测

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037444

Sofia Ariyani, Eko Mulyanto Yuniarno, Mauridhi Hery Purnomo

引用次数: 0

Mobile Device Facial Beauty Prediction using Convolutional Neural Network as Makeup Reference 基于卷积神经网络的移动设备面部美妆预测

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037321

Muhammad Luthfi, R. F. Rachmadi, I. Purnama, S. M. S. Nugroho

{"title":"Mobile Device Facial Beauty Prediction using Convolutional Neural Network as Makeup Reference","authors":"Muhammad Luthfi, R. F. Rachmadi, I. Purnama, S. M. S. Nugroho","doi":"10.1109/CENIM56801.2022.10037321","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037321","url":null,"abstract":"Beauty or good looks is one aspect of human attraction. Highly attractive people have an 8 to 12 % higher success in negotiations. One of the things that can be used to increase attractiveness is makeup or cosmetics. Makeup can be used alone or through the services of a Makeup Artist (MUA). MUA services are often used during important and once-in-a-lifetime events such as weddings. The difference in beauty before and after using this makeup cannot be measured but only seen and assessed manually. One application of machine learning in this field is Facial Beauty Predictions (FBP). FBP measures the value of a person's facial beauty or good looks. This paper investigated and implemented FBP on mobile devices, which makes it easier to assess anytime and anywhere. We investigated FBP models using five CNN architectures, including EfficientNetB0, VGG-16, ShuffleNet, MobileNet, and Inception. After evaluation, we choose MobileNetV2 CNN architecture as the primary model for mobile application FBP. Experiments on the FBP dataset show that MobileNetV2 achieves Pearson Correlation 0.7893 with only 10.5 MB for model file size. The model implemented for mobile devices works well in 13 different tests.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114511607","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

Auto Thresholding Sputum Color Image Segmentation For Tuberculosis Diagnosis Base On Intuitionistic Fuzzy 基于直觉模糊的痰彩色图像自动阈值分割

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037568

Sari Ayu Wulandari, I. Purnama, M. Purnomo

{"title":"Auto Thresholding Sputum Color Image Segmentation For Tuberculosis Diagnosis Base On Intuitionistic Fuzzy","authors":"Sari Ayu Wulandari, I. Purnama, M. Purnomo","doi":"10.1109/CENIM56801.2022.10037568","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037568","url":null,"abstract":"In this paper, an automatic algorithm for detecting the number of Mycobacterium tuberculosis is presented from the AFB smear image on I and V-shaped colonies, by applying fuzzy Intuitionistic based on the auto-thresholding segmentation method. Acid-fast bacteria, hereinafter referred to as AFB, are a group of bacteria that have unique characteristics, namely that they can prevent acid decolorization during the staining process, so that when sputum preparations are given a blue color, the AFB will retain its red color. One of the main problems in detecting the number of bacteria based on AFB segmentation is due to differences in light intensity and contrast (due to different lighting distributions). This study aims to segment the AFB images data as a whole, without dividing 1 bacterium into several parts. The segmentation process uses the stages of patch preparation, mask preparation and UNet Architecture. In mask preparation process, it is compare 3 color threshold models (grayscale then black and white - Adaptive Histogram then black and white - Fuzzy Intuitionistic- then black and white), all three are then segmented using the UNet method. The novelty of this paper is the creation of an input image mask. In this research, an optimization method is used with a maximal entropy approach. The idea is to find the maximum degree of disorder by calculating the entropy on the modified input image matrix. From the experimental results, it was found that the method that has high accuracy in segmenting AFB on I and V-shaped colonie is the fuzzy intuitionistic method, with an accuracy rate of 94.78%.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128149636","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

Evaluation of Multi-Sensor Gloves Development as an Assistive Interpreter for Indonesian Sign Language 多传感器手套在印尼语手语辅助翻译中的应用评价

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037541

Dwisainstia Aponno, A. Arifin, M. Fatoni, M. Nuh, Takashi Watanabe

引用次数: 0

Wearable FES System For Multi-Joint Movement Restoration With Cycle-To-Cycle Control Method 基于周期-周期控制方法的可穿戴FES多关节运动恢复系统

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037346

Rifqy Nurul Ilmi, A. Arifin, M. Fatoni, M. Nuh

引用次数: 0