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

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Control of Temperature in Biodiesel Water Removal System 生物柴油脱水系统的温度控制
2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037451
Hafizh Ghazidin, Kristianto Adi Widiatmoko, F. M. Kuswa, Romelan, Maharani Dewi Solikhah
{"title":"Control of Temperature in Biodiesel Water Removal System","authors":"Hafizh Ghazidin, Kristianto Adi Widiatmoko, F. M. Kuswa, Romelan, Maharani Dewi Solikhah","doi":"10.1109/CENIM56801.2022.10037451","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037451","url":null,"abstract":"Currently, biodiesel has been implemented as substitution of petroleum diesel fuel in order to reduce carbon emission and counter global warming. However the quality of biodiesel is one of the issues that need to be addressed, especially water content that may increase due to its hygroscopic nature. Biodiesel water removal process using the vacuum drying method can reduce water content. In this process, heating control becomes an important thing to able to maintain the quality of biodiesel. The control strategy using the integral, proportional integral, and proportional integral derivatives method is not suitable to be applied to the biodiesel heating system because there is an overshoot which results in a decrease in the quality of biodiesel. The derivative proportional control method does not cause overshoot and reaches the set point value faster than the proportional control method.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"13 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":"129413898","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
Classifying Composition of Software Development Team Using Machine Learning Techniques 利用机器学习技术对软件开发团队的组成进行分类
2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037407
Umi Laili Yuhana, Umi Sa’adah, Chandra Kirana Jatu Indraswari, S. Rochimah, M. Rasyid
{"title":"Classifying Composition of Software Development Team Using Machine Learning Techniques","authors":"Umi Laili Yuhana, Umi Sa’adah, Chandra Kirana Jatu Indraswari, S. Rochimah, M. Rasyid","doi":"10.1109/CENIM56801.2022.10037407","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037407","url":null,"abstract":"Software development projects still reportedly have high failure rates. The ineffective composition of the software team has been recognized as the main aspect of the failure of the software project. In this study, a classification model of the composition of an effective software development team was developed. The model developed consists of three predictor variables: personality, role, and gender. Outcome variables to determine team effectiveness are seen in the quality of the team. To measure the quality of the team, two metrics were used: team development level assessment and team dysfunction assessment. The techniques used for classification are logistic regression and decision trees. The experimental results show that the best method is produced by a decision tree with the highest accuracy value of 70%. Therefore, the results conclude that the use of the decision tree method can determine an effective team as software development team.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"59 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":"128485768","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
Identification of Conflicts in User Story Requirements Using The Clustering Algorithm 用聚类算法识别用户故事需求中的冲突
2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037416
Sarwosri, Umi Laili Yuhana, S. Rochimah
{"title":"Identification of Conflicts in User Story Requirements Using The Clustering Algorithm","authors":"Sarwosri, Umi Laili Yuhana, S. Rochimah","doi":"10.1109/CENIM56801.2022.10037416","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037416","url":null,"abstract":"In a software development life cycle, a critical phase that must be an important concern is the phase of exploring user requirement. In Agile Software Development, user requirements are written in a user story. User stories are written in Natural Language Processing with the format “As I, I want to, So that. There can be conflicts between user story. Grouping user stories will make it easier and faster for software developers to evaluate potentially conflicting or conflicting user stories. The steps are taken starting from preprocessing for syntax checking. These attributes are well formed, atomic, minimal, and unique. The clustering algorithm chosen Single Linkage, and K means. From 31 sentences of user stories passed syntax 115. User stories pass this syntax are then clustered. The results of the evaluation of these two algorithms using the best silhouette values were obtained for single linkage 6 clusters, and k means 6 clusters.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"2 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":"129822443","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
Classification Anterior and Posterior of Knee Osteoarthritis X-Ray Images Grade KL-2 Using Deep Learning with Random Brightness Augmentation 基于随机亮度增强的深度学习对KL-2级膝关节骨性关节炎x线图像前后的分类
2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037483
Supatman, E. M. Yuniarno, M. Purnomo
{"title":"Classification Anterior and Posterior of Knee Osteoarthritis X-Ray Images Grade KL-2 Using Deep Learning with Random Brightness Augmentation","authors":"Supatman, E. M. Yuniarno, M. Purnomo","doi":"10.1109/CENIM56801.2022.10037483","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037483","url":null,"abstract":"Osteoarthritis of the knee (KOA) is a narrowing of the joint space area (JSA) due to lack of fluid in the knee joint, resulting in pain when moving and when it is severe, the femur and tibia meet. Medical personnel and existing computer-based methods have been able to detect patients with X-rays but have not been able to detect where visually the posterior AJ is still wide while the anterior AJ is actually narrow, so that the patient still feels joint pain. A new approach is proposed for the classification of X-Ray Grade Kellgren-Lawrence (KL)-2 Osteoarthritis Initiative image datasets using Deep Learning Neural Networks (DCNN) by setting the Random Brightness Augmentation hyperparameter. The experimental results obtained X-Ray Grade KL-2 narrowing image classification “Anterior View KOA” and “Posterior View KOA” with training accuracy of 83.33% and validation accuracy of 54.69% at Random Brightness with a value of 30.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"5 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":"127247233","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
A Detection System for Center of Pressure Change and Lower Extremity Kinematics During Pregnancy for Welfare Design Recommendation of Pregnant Women 孕期压力中心变化及下肢运动检测系统对孕妇福利设计的建议
2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037565
Aminy Widinal Hartiningrum, A. Arifin
{"title":"A Detection System for Center of Pressure Change and Lower Extremity Kinematics During Pregnancy for Welfare Design Recommendation of Pregnant Women","authors":"Aminy Widinal Hartiningrum, A. Arifin","doi":"10.1109/CENIM56801.2022.10037565","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037565","url":null,"abstract":"Since human feet bears body weight, they play a crucial role in daily life activities. The increase in joint load as a result of an increase in body mass during pregnancy will certainly affect the postural balance and walking balance of pregnant women. Therefore, a system with pressure sensor and accelerometer-gyroscope combined sensor computed by the STM32F10C8T6 microcontroller displayed data on a Personal Computer (PC) via Bluetooth communication. The results showed that the imitate gait of pregnant women compared to a normal gait had center of pressure (COP) position tending to the medial-anterior direction with a more diffuse COP deviation, decreased flexion and increased extension of the knee joint, and decreased plantarflexion and dorsiflexion of ankle joint. Recommendations from this study showed that pregnant women were more comfortable when using slippers footwear designs and the need for supporting cushions on the lower extremities when sitting/sleeping positions.","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":"128843236","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
Electronic Nose using Convolutional Neural Network to Determine Adulterated Honeys 利用卷积神经网络的电子鼻检测掺假蜂蜜
2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037552
Misbah, M. Rivai, Fredy Kurniawan, D. Purwanto, Sheva Aulia, Tasripan
{"title":"Electronic Nose using Convolutional Neural Network to Determine Adulterated Honeys","authors":"Misbah, M. Rivai, Fredy Kurniawan, D. Purwanto, Sheva Aulia, Tasripan","doi":"10.1109/CENIM56801.2022.10037552","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037552","url":null,"abstract":"Honey is a sweet and thick food substance that has high economic value which is often found in its adulteration. Impure honey frequently causes harm to people. Therefore, it requires a system that can assist in resolving the issue of adulterated honey. One method to deal with this issue is to use an electronic nose system. The system consists of gas sensors, a data acquisition circuit, and a pattern recognition algorithm. In this study, an electronic nose system comprised of an array of semiconductor gas sensors was built. Arduino microcontroller is used for data acquisition circuit. The pattern recognition algorithm uses the convolutional neural network (CNN) method. The experimental results show that this system recognizes honey with levels of 50%, 75%, 100%, and sugar with an accuracy rate of 100%.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"5 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":"130121980","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
Detection of Dead Victims at Volcanic Disaster Location based on Drone and LoRa 基于无人机和LoRa的火山灾害定位遇难者识别
2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037372
M. Z. S. Hadi, Achmad Abie Dafa, P. Kristalina
{"title":"Detection of Dead Victims at Volcanic Disaster Location based on Drone and LoRa","authors":"M. Z. S. Hadi, Achmad Abie Dafa, P. Kristalina","doi":"10.1109/CENIM56801.2022.10037372","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037372","url":null,"abstract":"When a natural disaster occurs, the process of evacuating victims after a disaster must be carried out immediately to reduce the risk due to the late evacuation process. In this evacuation process, the Search and Rescue (SAR) team played a big role in addition to focusing on the safety of victims and also paying attention to their own safety. Meanwhile, due to the large area of the disaster the search took quite a long time. In this paper, research was carried out to facilitate the evacuation process at the location of volcanic disasters by using drones carrying electronic devices to find the whereabouts of victims on the surface. This process of detecting and classifying is based on the Convolutional Neural Network (CNN) method with the MobileNetV2 model. We train the data set of disaster victims using batch sizes 16 and 32 with epochs of 40, 80 and 100. The resulting model has the greatest accuracy of 0.81 and f1-score of 0.86.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"75 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":"132656796","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
A Study to Improve Image Steganography Using Linear Feedback Shift Register 利用线性反馈移位寄存器改进图像隐写的研究
2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037395
Majd Shunnar, Amaal Othman, Ahmed Awad
{"title":"A Study to Improve Image Steganography Using Linear Feedback Shift Register","authors":"Majd Shunnar, Amaal Othman, Ahmed Awad","doi":"10.1109/CENIM56801.2022.10037395","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037395","url":null,"abstract":"Concealing data during communicating is often a security requirement. Image steganography is one way to do that by hiding data in the cover image. Least Significant Bit (LSB) insertion is one of the spatial domain methods, wherein, a message is concealed in the least significant bits of the pixels composing an image. However, such technique is vulnerable to various attacks. Furthermore, low-cost hardware is essential to employ steganography in lightweight security applications. This paper, thus, proposes a way to improve LSB based image Steganography by integrating a Linear-Feedback Shift Register (LFSR), as a low cost hardware, in the hiding process in such a way that the message is hidden in a pseudorandom fashion. Thereafter, the efficiency of the improved algorithm is analyzed and compared to the original algorithm. Experimental results demonstrate the effectiveness of our proposed LSB based image Steganography which successfully hides the message with a linear computational complexity.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"94 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":"134311993","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
Autonomous Surface Vehicle in Search and Rescue Process of Marine Casualty using Computer Vision Based Victims Detection 基于计算机视觉的自主水面车辆在海上伤亡搜救过程中的受害者检测
2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037319
Achmad Zidan Akbar, C. Fatichah, Rudy Dikairono
{"title":"Autonomous Surface Vehicle in Search and Rescue Process of Marine Casualty using Computer Vision Based Victims Detection","authors":"Achmad Zidan Akbar, C. Fatichah, Rudy Dikairono","doi":"10.1109/CENIM56801.2022.10037319","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037319","url":null,"abstract":"An Autonomous Surface Vehicle (ASV) is proposed to help the search process of maritime accident victims. A catamaran-type hull is implemented on the ASV for its stability. The ASV fix-mounted the electric propulsion system T200 Thruster on the stern of the ASV. Robot Operating System (ROS) is implemented on the ASV main software architecture. The ASV uses sensors such as a Global Positioning System (GPS), compass, Inertial Measurement Unit (IMU), and gyroscope to detect the state of the ASV. The ASV also uses ultrasonic sensors for obstacle avoidance. To interface with the actuators, a microcontroller STM32F4 is used. You Only Look Once (YOLO)v4 as Convolutional Neural Network (CNN) Architecture was used for the victim detection that was running on Nvidia RTX 2060 Mobile. The navigation system of the ASV performs well despite the noise from the sensor. The ASV is also capable of avoiding obstacles when moving at low speed. Dataset annotation was done manually from the images taken in Danau 8 Institut Teknologi Sepuluh Nopember (ITS). YOLOv4 gives an accuracy of 0.840203. Optimizing the YOLOv4 model from the darknet model to TensorRT increases the inference speed from 27 FPS to 85 FPS.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"88 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":"115625787","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
OOV Handling Using Partial Lemma-Based Language Model in LF-MMI Based ASR for Bahasa Indonesia 基于部分引理的语言模型在基于LF-MMI的印尼语语音识别中的OOV处理
2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037479
Agung Santosa, Asril Jarin, E. M. Yuniarno, Hammam Riza, M. Purnomo
{"title":"OOV Handling Using Partial Lemma-Based Language Model in LF-MMI Based ASR for Bahasa Indonesia","authors":"Agung Santosa, Asril Jarin, E. M. Yuniarno, Hammam Riza, M. Purnomo","doi":"10.1109/CENIM56801.2022.10037479","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037479","url":null,"abstract":"One of the common problems in ASR is the out-of-vocabulary word in an utterance that can degrade the performance of the system. Bahasa Indonesia, as an agglutinative language, uses affixation to generate words from a set of affixes and root words. We propose the use of a partial lemma-based language model (LM) and lexicon that can handle words created from affixation. The partial lemma-based LM and lexicon are created from the original ones using morphology analyzer output as a reference. The experiment shows that using the LM in ASR with LF-MMI cost function gives a better WER when the heuristic to insert inter-word short pause is modified to also consider the affixes.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"17 6 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":"123689818","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
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