Proceeding of the Electrical Engineering Computer Science and Informatics
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    649 research outputs found

    Ball and Beam Control using Adaptive PID based on Q-Learning

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    The ball and beam system is one of the most used systems for benchmarking the controller response because it has nonlinear and unstable characteristics. Furthermore, in line with the increasing of computation power availability and artificial intelligence research intensity, especially the reinforcement learning field, nowadays plenty of researchers are working on a learning control approach for controlling systems. Due to that, in this paper, the adaptive PID controller based on Q-Learning (Q-PID) was used to control the ball position on the ball and beam system. From the simulation result, Q-PID outperforms the conventional PID and heuristic PID controller technique with the swifter settling time and lower overshoot percentage

    Implementation of Secure Work From Home System Based on Blockchain using NS3 Simulation

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    Work from Home (WFH) is an activity carrying out official duties, completing outputs, coordination, meetings, and other tasks from the residence of employees. Implement WFH many users use the zoom application has vulnerabilities. The network architecture used refers to the simple experiment network. In Secure WFH there are 3 offices connected through a router. Each client in each office is connected to the router via a Virtual Private Network (VPN) on a peer-to-peer (P2P). That architecture has 18 nodes that will be simulated. Secure WFH simulation with blockchain combines secure WFH with a bitcoin code simulator from Arthur Gervais's. Implementation of blockchain on secure WFH can increase security but the resulting speed decreases. The decrease in speed when implementing secure WFH is due to the generate block process and the verification process

    Optimal Sizing of Micro Hydropower to Improve Hybrid Renewable Power System

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    This paper presents an analysis of optimal micro hydropower (MH) capacity of hybrid systems to improve renewable energy based power systems. The electricity system was designed by considering river water flow data and solar radiation data at the research location, Andalas University. Optimal results obtained for the configuration of the Grid, MH, and PV with a head height of 30 m and a flow rate of 800 L/s with the lowest COE value of $ 0.065. As an optimal sizing system has been able to increase the composition of renewable energy generation in the Unand electrical network. The renewable energy fraction has increased from 26.4% to 36.5%. Therefore, determining the optimal capacity will increase the use of renewable energy generation. Conversely, an increase in electricity supply from renewable energy plants will reduce electricity consumption from the PLN grid. The latest excess power generation at a low load can be sold to the PLN gri

    Data Reduction Approach Based on Fog Computing in IoT Environment

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    This paper investigates a data processing model for a real experimental environment in which data is collected from several IoT devices on an edge server where a clustering-based data reduction model is implemented. Then, only representative data is transmitted to a cloud-hosted service instead of raw data. In our model, the subtractive clustering algorithm is employed for the first time for streamed IoT data with high efficiency. Developed services show the real impact of data reduction technique at the fog node on enhancing overall system performance. High accuracy and reduction rate have been obtained through visualizing data before and after reduction

    Design of Regenerative Damper for Energy Harvester in Playground Seesaw

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    Increasing demand for electricity, coupled with a greater understanding of the environmental impact of conventional power generation, has led to growing research interest on alternative energy sources. Energy harvesters based on playground equipment, such as the seesaw, has been proposed as an alternative method to generate electrical power. In this study, a new harvesting mechanism based on the electromagnetic regenerative damper is proposed as an alternative method to harness energy from a playground seesaw. The proposed design is intended for higher power output and efficiency, smaller dimensions, and ease of installation on a seesaw. Lab tests have been carried out to characterize the proposed design experimentally. The energy harvesting (stroke velocity-to-voltage) coefficient for the proposed seesaw-based energy harvester is obtained as 73.18 V/(ms -1 ). The regenerative damper is capable of producing up to 110 mW of power at 9.34% efficiency

    Features Extraction on IoT Intrusion Detection System Using Principal Components Analysis (PCA)

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    There are several ways to increase detection accuracy result on the intrusion detection systems (IDS), one way is feature extraction. The existing original features are filtered and then converted into features with lower dimension. This paper uses the Principal Components Analysis (PCA) for features extraction on intrusion detection system with the aim to improve the accuracy and precision of the detection. The impact of features extraction to attack detection was examined. Experiments on a network traffic dataset created from an Internet of Thing (IoT) testbed network topology were conducted and the results show that the accuracy of the detection reaches 100 percent

    Quality in Use of Digital Wallet based on ISO/IEC 25022

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    The growth of financial technology (fintech) has led to an increase in cashless transactions. One of the technology that is developing and widely used is digital wallets. Because of the frequent use of digital wallet services, an assessment to measure quality in use needs to be done. Quality in use relates to user interaction with software when the product is used. The assessment standard used to measure quality in use is ISO/IEC 25022. The criteria assessed are effectiveness, efficiency, satisfaction, and freedom from risk. To strengthen the results obtained, a correlation between the existing criteria and the quality in use of digital wallets is sought. From these results, it will be known which criteria have the highest correlation to the quality in use of digital wallets. This study does not focus on assessing the quality in use of each digital wallet, but on digital wallets globally (in this study the digital wallets used are OVO, Gopay, and Dana) because after the results of the questionnaire, almost all respondents use more than one digital wallet, even besides the mentioned digital wallets. The conclusion obtained in this study is that digital wallet product users are satisfied with the use of digital wallets although there are still some risks that may arise

    The Effect of Using Histogram Equalization and Discrete Cosine Transform on Facial Keypoint Detection

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    This study aims to figure out the effect of using Histogram Equalization and Discrete Cosine Transform (DCT) in detecting facial keypoints, which can be applied for 3D facial reconstruction in face recognition. Four combinations of methods comprising of Histogram Equalization, removing low-frequency coefficients using Discrete Cosine Transform (DCT) and using five feature detectors, namely: SURF, Minimum Eigenvalue, Harris-Stephens, FAST, and BRISK were used for test. Data that were used for test were obtained from Head Pose Image and ORL Databases. The result from the test were evaluated using F-score. The highest F-score for Head Pose Image Dataset is 0.140 and achieved through the combination of DCT & Histogram Equalization with feature detector SURF. The highest F-score for ORL Database is 0.33 and achieved through the combination of DCT & Histogram Equalization with feature detector BRISK

    SCADA Solution by Installing DTM6000 and Trunking Tier Three

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    The aim of this study is to provide the new solution for the SCADA system by using the DTM6000 with Tier three and the multipoint node topology for the application offshore mining industry. The application of the proposed design can provide the data as wind speed, machine temperature, sonar, vessel position. Applying the SCADA Software, NMS (network management system), and DWS (Dispatch Work Station), data can be monitored through the control Center. The SCADA system with radiofrequency can cover a wide coverage area (ie up to 60 km). The trunking base station, carry out the data, and able to transmit voice communication with good quality. The technical design and the installation as well as the trial for validation of the proposed system in the remote area offshore of the mining industry is provided. It is might be stated that the system enables the development and addition of more other SCADA equipment in the futur

    Combination of Genetic Algorithm and Brill Tagger Algorithm for Part of Speech Tagging Bahasa Madura

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    Part of speech (POS) is commonly known as word types in a sentence such as verbs, adjectives, nouns, and so on. Part of Speech (POS) Tagging is a process of marking the word class or part of speech in every word in a sentence. Part of Speech Tagging has an important role to be used as a basis for research in Natural Language Processing. That is why research on Part of Speech Tagging for Bahasa Madura as an effort to preserve and develop the use of regional languages. In this research, POS Tagging is done using the Brill Tagger Algorithm which is combined with the Genetic Algorithm. Brill Tagger is a POS Tagging Algorithm that has the best level of accuracy when implemented in other languages. Genetic Algorithms used in the contextual learner process with consideration in previous studies can increase the speed of the training process so that it is more efficient. The results of this study are then compared with the results of the previous study so that we can find out suitable algorithms used for the development of text processing in Bahasa Madura. From a series of experiments, the average accuracy obtained by using Brill Tagger is 86.4% with the highest accuracy of 86.7%, while using GA Brill Tagger shows an average accuracy of 86.5% with the highest accuracy of 86.6%. Testing by observing OOV (Out of Vocabulary) achieves an average accuracy of 67.7% for Brill Taggers and 64.6% for GA Brill Taggers. Testing by considering multiple POS with Brill Tagger produces an average accuracy of 73.3% while testing using GA Brill Tagger produces an average accuracy of 90.9%. This shows that the accuracy with GA Brill Tagger is better than Brill Tagger, especially if considering multiple POS. This is because GA Brill Tagger can generate rules for handling the existence of multiple POS more than pure Brill Tagger.Part of speech (POS) is commonly known as word types in a sentence such as verbs, adjectives, nouns, and so on. Part of Speech (POS) Tagging is a process of marking the word class or part of speech in every word in a sentence. Part of Speech Tagging has an important role to be used as a basis for research in Natural Language Processing. That is why research on Part of Speech Tagging for Bahasa Madura as an effort to preserve and develop the use of regional languages. In this research, POS Tagging is done using the Brill Tagger Algorithm which is combined with the Genetic Algorithm. Brill Tagger is a POS Tagging Algorithm that has the best level of accuracy when implemented in other languages. Genetic Algorithms used in the contextual learner process with consideration in previous studies can increase the speed of the training process so that it is more efficient. The results of this study are then compared with the results of the previous study so that we can find out suitable algorithms used for the development of text processing in Bahasa Madura. From a series of experiments, the average accuracy obtained by using Brill Tagger is 86.4% with the highest accuracy of 86.7%, while using GA Brill Tagger shows an average accuracy of 86.5% with the highest accuracy of 86.6%. Testing by observing OOV (Out of Vocabulary) achieves an average accuracy of 67.7% for Brill Taggers and 64.6% for GA Brill Taggers. Testing by considering multiple POS with Brill Tagger produces an average accuracy of 73.3% while testing using GA Brill Tagger produces an average accuracy of 90.9%. This shows that the accuracy with GA Brill Tagger is better than Brill Tagger, especially if considering multiple POS. This is because GA Brill Tagger can generate rules for handling the existence of multiple POS more than pure Brill Tagge

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    Proceeding of the Electrical Engineering Computer Science and Informatics
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