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

Development of Mechanism to Create Dialysate Liquid in Hemodialysis Machine 血液透析机产生透析液机理的研究进展

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037330

Gusfatul Mukhairiq, T. A. Sardjono, M. Fatoni

引用次数: 0

Analyzing The Effect of Network Traffic Segmentation on The Accuracy of Botnet Activity Detection 网络流量分割对僵尸网络活动检测准确性的影响分析

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037365

Muhammad Aidiel Rachman Putra, Umi Laili Yuhana, T. Ahmad, Dandy Pramana Hostiadi

{"title":"Analyzing The Effect of Network Traffic Segmentation on The Accuracy of Botnet Activity Detection","authors":"Muhammad Aidiel Rachman Putra, Umi Laili Yuhana, T. Ahmad, Dandy Pramana Hostiadi","doi":"10.1109/CENIM56801.2022.10037365","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037365","url":null,"abstract":"Botnet is known as a dangerous threat in computer networks. Malicious activities from bots include phishing, sending spam messages, click misrepresentation, spreading malicious programming and activities of Distributed Denial of Service (DDoS) attacks. Thus, it needs to be handled appropriately. Some research proposed a botnet detection model using segmentation analysis on network traffic data. However, it has not shown the optimal segmentation time and analyzed the effect of the segmentation process on increasing detection accuracy. This paper proposes a Botnet activity detection model using machine learning classification by involving the segmentation process. The proposed classification model contributes to the segmentation analysis process to obtain the optimal traffic segment and segment time. The purpose of the proposed model is to analyze the segmentation process to increase the accuracy of Botnet activity detection. The results of testing on two different datasets show that the classification model using segmentation can increase the detection accuracy of Botnet activity. Two classification algorithms that can produce the best detection accuracy are Random Forest of 99.95% and Decision Tree algorithm of 99.92%. This accuracy value is higher than previous research by testing using the same classification algorithm and dataset.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"106 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":"124783482","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

Hematocrit Measurement to Determine Blood Viscosity Value and Blood Volume Changes During Hemodialysis 测定血液透析过程中血液粘度值和血容量变化的红细胞压积

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037266

Grace Lamria Pakpahan, Rachmad Setiawan, Nada Fitrieyatul Hikmah

{"title":"Hematocrit Measurement to Determine Blood Viscosity Value and Blood Volume Changes During Hemodialysis","authors":"Grace Lamria Pakpahan, Rachmad Setiawan, Nada Fitrieyatul Hikmah","doi":"10.1109/CENIM56801.2022.10037266","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037266","url":null,"abstract":"Management of excess fluid is a critical element during hemodialysis. Monitoring blood volume and measuring blood viscosity are two common techniques used to assess fluid overload. Optical methods allow for the precise quantification of hematocrit levels. In this research, a PPG sensor was employed to assess hematologic parameters. The ratio of the AC to DC portions of the LED signal is used to calculate hemoglobin concentration. The pulsatile and non-pulsatile characteristics of blood are represented by the AC and DC components, respectively. After the LED signal from the sensor has been processed, the straight-line approximation can be used to get the AC and DC components. There is a 94.63% degree of precision and an 89.17% rate of accuracy when measuring hemoglobin concentration. The concentration of hematocrit can be measured to within a precision of 94.63 percentage points and an accuracy of 88.82 percent. This study has the potential to be included into hemodialysis machines in the future, allowing these devices to detect changes in blood viscosity and blood volume in hemodialysis patients.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"1 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":"130311971","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

Frequency Stability Analysis On Optimization Of Virtual Inertia Control (VIC) Capacitor Energy Storage (CES) Controller Settings Using Particle Swarm Optimization 基于粒子群算法的虚拟惯性控制(VIC)电容储能(CES)控制器设置优化频率稳定性分析

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037313

Alief Nur Aisyi Maulidhia, D. A. Asfani, A. Priyadi, H. Setiadi

{"title":"Frequency Stability Analysis On Optimization Of Virtual Inertia Control (VIC) Capacitor Energy Storage (CES) Controller Settings Using Particle Swarm Optimization","authors":"Alief Nur Aisyi Maulidhia, D. A. Asfani, A. Priyadi, H. Setiadi","doi":"10.1109/CENIM56801.2022.10037313","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037313","url":null,"abstract":"Rapid industrial development requires more energy to support all industrial processes. Using conventional energy is not environmentally friendly as it can destroy the environment. The conversion from using conventional energy to using renewable energy sources is increasingly being used around the world. However, the presence of renewable energy poses new challenges to the world of power systems. To generate renewable energy sources, components such as inverters must be connected to the power grid. Inverters are zero-inertia devices because they have no rotating bodies that generate inertia. In a system, frequency stability is highly dependent on the inertia and damping of the system itself. To overcome this problem, we study the impact of integrating renewable energy into the power system using a virtual inertial controller (VIC) based on energy storage systems. One of the energy storage systems used is Capacitor Energy Storage (CES). Optimizing the output power that can be generated by the capacitor energy store requires optimizing the values of the individual parameters. One of the methods available is the Particle Swarm Optimization (PSO) method. The focus of this study is to study the effect of installing a VIC in his CES optimized with a particle swarm optimization algorithm on system frequency oscillations induced by static loads.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"418 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":"124255226","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

Design of Teleconsultation System with Artificial Intelligence Based Chatbot Using Docker Platform 基于Docker平台的人工智能聊天机器人远程会诊系统设计

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037290

Norma Hermawan, Atar Babgei, Salsanabilah

{"title":"Design of Teleconsultation System with Artificial Intelligence Based Chatbot Using Docker Platform","authors":"Norma Hermawan, Atar Babgei, Salsanabilah","doi":"10.1109/CENIM56801.2022.10037290","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037290","url":null,"abstract":"The implementation of the National Health Insurance Program (JKN) caused an increase in the number of visits to the first-level health facilities, while there are still clinics that lack medical personnel. Teleconsultation is defined as the possibility of contact between patients and doctors through a telemonitoring platform. Chatbot is a program that automatically provides services by talking to users through many types of communication media. A study shows a positive result in the use of support-chatbot for breast cancer patients, and that doctor agrees that chatbot can help in carrying out some simple tasks in healthcare scenario. Microservice is a system architecture that allows improvement of stability and security. We proposed a chatbot with three main functions: as a teleconsultation platform where doctors can arrange consultation questions that can either be reused for some patients with similar conditions or a specific set of questions for a particular patient; an artificial intelligence based disease diagnosis function made with the decision tree model using data that was collected from the results of literature studies; and disease information search function where the data was obtained from the results of web scraping. Each function was made in their respective services, allowing the usage of different technology according to their specific needs while providing easier maintenance, testing, and deployment. The chatbot's ability to lead the conversation flow was tested using predetermined test cases and direct user testing, the predetermined test cases shows positive results with the chatbot being able to correctly answer all the input as expected, while the user testing shows some areas of the system that could be improved further, including the addition of more commonly used disease term in the disease information database and more training for the chatbot.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"43 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":"123652840","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

A New Annotation System for Dynamic Web Pages Driven by NLP 基于自然语言处理的动态网页标注系统

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037528

Mohammad Smadi, Mohammad Hawash, Omar Daqqa, Amjad Hawash, Ahmed Awad

{"title":"A New Annotation System for Dynamic Web Pages Driven by NLP","authors":"Mohammad Smadi, Mohammad Hawash, Omar Daqqa, Amjad Hawash, Ahmed Awad","doi":"10.1109/CENIM56801.2022.10037528","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037528","url":null,"abstract":"Web annotation has become an essential technique to express people's thoughts and feelings by attaching annotations to web content. Annotators with the same interests can exchange their ideas and experiences by conducting universal online collaborations. The idea of submitting annotations depends on attaching vocal or textual notes with the contents of websites. However, annotating dynamic data is a problem that encourages researchers to work on proper solutions. Losing annotations because of the change in website annotated contents will definitely lead to losing the intended collaboration between annotators. This work is related to annotating dynamic websites by computing the textual similarity between erased (or relocated) annotated text and the remained text in dynamic websites by exploiting NLP (Natural Language Processing) algorithms. The attached annotation with dynamic content will be attached to the most related text on the website. By this, annotators will not lose their annotations and replies and hence their collaboration will remain. The experimental tests conducted in this work reflect promising results.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"145 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":"114763272","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

Convolution Neural Network (CNN) Architectures Analysis for Photovoltaic (PV) Module Defect Images Classification 用于光伏组件缺陷图像分类的卷积神经网络(CNN)架构分析

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037564

Nurul Atikah Mazlan, K. Othman, S. Shahbudin, Murizah Kassim

{"title":"Convolution Neural Network (CNN) Architectures Analysis for Photovoltaic (PV) Module Defect Images Classification","authors":"Nurul Atikah Mazlan, K. Othman, S. Shahbudin, Murizah Kassim","doi":"10.1109/CENIM56801.2022.10037564","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037564","url":null,"abstract":"Photovoltaic (PV) module is the medium to convert solar energy to electrical energy. The existence of defects in the PV module will affect the system's efficiency to generate electricity. In this work, Convolutional Neural Network (CNN) architecture is proposed in PV module defect image classification due to its capability to extract patterns and consist of several unique layers to classify images accurately. Thus, the objective of this paper is to analyze PV defect image classification using CNN architectures namely Residual Neural Network (ResNet) and Visual Geometry Group (VGG), and to identify which architectures give the best performance. In this paper, two types of ResNet architectures which are ResNet-18 and ResNet-50, and two types of VGG architectures which are VGG-16 and VGG-19 were applied. For validation and verification purposes, other performance metrics such as F1-score, sensitivity, specificity, and precision are evaluated. The result shows that VGG-19 is outperformed in terms of accuracy with a value of 92.58%, sensitivity (73.14%), and specificity (95.10%) compared to ResNet-18, ResNet-50, and VGG-16 architecture.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"57 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":"126308444","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

Deep Learning Approach for Loneliness Identification from Speech using DNN-LSTM 基于DNN-LSTM的语音孤独感识别深度学习方法

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037300

Ririn Tri Rahayu, E. M. Yuniarno, Derry Pramono Adi, Andreas Agung Kristanto

{"title":"Deep Learning Approach for Loneliness Identification from Speech using DNN-LSTM","authors":"Ririn Tri Rahayu, E. M. Yuniarno, Derry Pramono Adi, Andreas Agung Kristanto","doi":"10.1109/CENIM56801.2022.10037300","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037300","url":null,"abstract":"Perceived loneliness and social isolation have been on the rise over the past decade, especially in countries with rapidly ageing populations and, most notably, as a result of the stress of dealing with the COVID-19 outbreak over the past two years. By using a natural language processing (NLP) approach to quantify sentiment and variables that signal loneliness in transcribed spoken text of older persons, this paper investigates the use of deep learning technology in the evaluation of interviews on loneliness. We conducted loneliness state detection using Deep Neural Network (DNN) and Long Short-Term Memory (LSTM). Participants who were lonely and those who weren't were compared (using both qualitative and quantitative measures). Individuals who were lonelier (as determined by qualitative measures) took longer to respond to questions about their loneliness and expressed more grief in their answers. When asked about loneliness, more women than men admitted it during the qualitative interview. When responding, men were more likely to utilize expressions of dread and happiness. When trained on textual data, DNN models were 100% accurate at predicting qualitative loneliness and LSTM models were 75.42% accurate at predicting loneliness on textual data.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"34 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":"130730406","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

A Novel Ranked Emission-Factor Retrieval for Emission Calculation 一种用于排放计算的新型排序排放因子检索方法

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037450

Sathees Paskaran, A. Gamage, S. Chandrasiri

{"title":"A Novel Ranked Emission-Factor Retrieval for Emission Calculation","authors":"Sathees Paskaran, A. Gamage, S. Chandrasiri","doi":"10.1109/CENIM56801.2022.10037450","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037450","url":null,"abstract":"Emission Factors (EF) selection is a vital task during Carbon Management Systems (CMS) emission calculation. Due to Carbon footprint reduction regulations, there is a demand increase for CMS with better usability and scalability. However, most CMS assumes users know emission technologies well. To circumvent these problems, authors have proposed an approach to building an EF ranking system with a combined scoring approach. It has considered each EF as a document unit and emission activity information provided by the user as the search query. This system uses a linear combination of the Vector Space Model (VSM) and Natural Language Processing (NLP) Word Embedding techniques to rank EF documents for exact and non-exact search queries. This approach's user satisfaction measured with Mean Average Precision (MAP) for “glove-wiki-gigaword-300” at 0.41 linear combination parameter was nearly 30% better than the VSM model and 127% more than the word embedding. In addition, the paper discusses performance metrics such as speed, future EFs scalability, and system resource utilization concerning the solution's overall scalability. This approach can provide better usability and scalable for EF selection tasks compared to single-ranking approaches (VSM or Word Embedding).","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"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":"132954325","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

Venous Chamber Pressure Control and Air Bubbles Detection in Hemodialysis Delivery System Based on Fuzzy Logic 基于模糊逻辑的血液透析输送系统静脉腔压力控制与气泡检测

2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM) Pub Date : 2022-11-22 DOI: 10.1109/CENIM56801.2022.10037412

M. Fatoni, Firdausi Nuzula Alghozali, Rachmad Setiawan

{"title":"Venous Chamber Pressure Control and Air Bubbles Detection in Hemodialysis Delivery System Based on Fuzzy Logic","authors":"M. Fatoni, Firdausi Nuzula Alghozali, Rachmad Setiawan","doi":"10.1109/CENIM56801.2022.10037412","DOIUrl":"https://doi.org/10.1109/CENIM56801.2022.10037412","url":null,"abstract":"Air bubbles can enter the exctracorporeal hemodialysis circuit because of air trapped inside the tubing or because of a faulty pump connection. If a considerably dangerous amount of air bubble were to enter the veins, the patient will most likely to experience venous air embolism (VAE). To avoid the possibility of VAE, an air bubble detection along with an automatic clamping system is needed right before the blood is returned to the patients vein. A sudden change of venous chamber pressure during hemodalysis may cause hemolysis. This change of pressure can be caused by a kink in the venous chamber tubing, clotting in the patient's venous access, or a change in blood pump speed. A pressure sensor is required to monitor the pressure inside the hemodialysis venous chamber before the blood enters the vein. This study propose a device to monitor venous chamber pressure and detect air bubbles in the hemodialysis delivery system based on fuzzy logic. The pressure error and derivative error to the ideal pressure measured by the sensor will be the input of a DC motor speed control system to drive the peristaltic pump based on fuzzy logic controller (FLC). Output value of the designed FLC is Pulse Width Modulation (PWM) signal using a pressure sensor as the feedback. Air bubble detection is done by utilizing an air bubble sensor. Based on the DC motor test, saturation of rotation speed (RPM) occurs when given duty cycle of 84,3% and above. This was used as a consideration during the development of the fuzzy logic parameters, which results in the duty cycle given is between 65%-70%. The system needs 72,42 seconds to return to the set point when given disruption in the form of sudden increased pressure. It also needs 28,755 seconds to return to the set point when given disruption in the form of sudden pressure loss. Air bubble detection using the air bubble sensor has a result of 100% detection rate","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"432 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":"125760294","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