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9th International Conference on Wireless and Telematics, ICWT 2023

作者： Ahdan, Syaiful Zaki Hamidi, Eki Ahmad Riskiono, Sampurna Dadi Negara, Ridha Muldina Mayasari, Ratna Ramadona, Suci Nurhayati, Ade Sucipto, Adi Jupriyadi Nurkahfi, Galih Nugraha Farahiyah, Dzata Naseer, Muchammad Universitas Teknokrat Indonesia Faculty of Engineering & Computer Science Lampung35132 Indonesia Uin Sunan Gunung Djati Bandung Electrical Engineering Department Bandung40614 Indonesia School of Electrical Engineering Telkom University Bandung40257 Indonesia Elearical Engineering Study Program Politeknik Caltex Riau Riau28265 Indonesia Institut Teknologi Telkom Jakarta Faculty of Engineering Jakarta11710 Indonesia Bandung40135 Indonesia Universitas Islam Indonesia Yogyakarta Faculty of Industrial Technology Yogyakarta55584 Indonesia Sekolah Tinggi Teknologi Bandung Informatics Department Bandung40235 Indonesia

ISBN: (纸本)9798350305029

Many different industries are currently making substantial use of the Internet of Things (IoT). IoT is the process through which electronic devices communicate with their surrounding virtual environment by continuously exchanging data via sensors. Due to increased IoT security concerns, digital forensic investigators now possess greater knowledge and abilities to investigate IoT devices. IoT-DigFor are required in terms of cybercrime due to the rapid growth in the number of electronic devices and the collection and consumption of enormous amounts of data. IoT systems with billions of devices have produced a significant amount of evidence, which presents a significant challenge to digital investigators and practitioners who must connect with IoT devices to conduct fast and thorough investigations into cybercrimes. This article presents detailed information about forensics in the IoT environment. The IoT forensic paradigm and the challenges that design-based security requirements and IoT system security offer for IoT-DigFor are covered in great detail at the beginning of the article. © 2023 IEEE.

关键词： Internet of things

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Effect of physical and biological pretreatment on sugarcane bagasse waste-based biogas production

Effect of physical and biological pretreatment on sugarcane ...

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3rd International Conference on Chemical engineering and Applied Sciences, ICChEAS 2022

作者： Sumardiono, Siswo Matin, Hashfi Hawali Abdul Sulistianingtias, Ihdina Nugroho, Tri Yulianto Budiyono, Budiyono Department of Chemical Engineering Faculty of Engineering Universitas Diponegoro Semarang50239 Indonesia Study Program of Environmental Science Faculty of Mathematic and Natural Science Universitas Sebelas Maret Surakarta57126 Indonesia Vocational School Universitas Diponegoro Semarang50239 Indonesia

Sugarcane bagasse is a biomass with very potential, especially in agricultural countries. In this research, a study related to pretreatment and the ratio of C/N to biogas production from sugarcane bagasse was conducted. The study was carried out on a laboratory scale with physical pretreatment by grinding with a size of 6 mesh, then biological pretreatment with the microbial consortium 5 % g/V, and variations in the C/N ratio at 25 and 30. Cow rumen fluid was used in this study as a source of anaerobic bacteria and technical urea is used to adjust the C/N ratio. The solid total is set at 7 %. Based on research that has been carried out for 60 days, it was found that physical pretreatment by grinding with a size of 6 mesh can increase biogas production. Biogas production increased both at C/N ratio conditions of 25 and 30. Furthermore, biological pretreatment with the microbial consortium 5 % g/V was proven to increase biogas production at both C/N ratios of 25 and 30. Further studies on the C/N ratio, it was found that the C/N ratio of 25 was better than the C/N ratio of 30. This is evident in several variables, including raw and fine substrate conditions, as well as on variables with or without a microbial consortium, with the amount of biogas productivity at a C/N 25 ratio of 53-90.5 % higher than the C/N 30 ratio. © 2023 Elsevier Ltd. All rights reserved.

关键词： Grinding (machining)

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Impact of High-k Materials and Tube Numbers on CNFET Gate's Performances 5

Impact of High-k Materials and Tube Numbers on CNFET Gate's ...

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5th International Conference on Smart Systems and Inventive Technology, ICSSIT 2023

作者： Yalung, Christofer Tantraviwat, Doldet Uatrongjit, Sermsak Yamwong, Wittawat Doctor of Philosophy Program in Nanoscience and Nanotechnology International Program/Interdisciplinary Center of Excellence in Materials Science and Technology Faculty of Science Chiang Mai University Chiang Mai Thailand Chiang Mai University Faculty of Engineering Department of Electrical Engineering Chiang Mai Thailand Chachoengsao Thailand

ISBN: (纸本)9781665474672

Carbon nanotube field effect transistor (CNFET) performance is primarily influenced by a variety of characteristics, such as nanotube diameter, operating voltage, pitch, the number of tubes, dielectric constant, and contact materials. In this study, the dielectric constant and the number of carbon nanotubes (CNTs) were emphasized to analyze the propagation delay and average power dissipation of basic logic gates. Zirconium dioxide (ZrO2), hafnium oxide (HfO2), and silicon dioxide (SiO2) were used as dielectric materials. In this experiment, the Stanford CNFET model was utilized, and variable factors such as the number of CNTs and the dielectric constant (Kox) accumulated on the nanotube gate's surface were diversified. The correlation coefficients of the delay, the average power, and the CNT numbers were also presented. Furthermore, the multi-objective genetic algorithm and the Rmethod were utilized to find the optimal Kox and the number of CNTs for minimizing the average dissipation power and the propagation delay of some logic gates designed with CNFET. For all the gates considered, the optimal number of CNTs is 4 while the dielectric constant is within the ranges of 19 to 24. © 2023 IEEE.

关键词： Carbon nanotubes

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Evaluation electrical System of Mini Plant Waste Energy on Institut Teknologi PLN

Evaluation Electrical System of Mini Plant Waste Energy on I...

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Converging Technology in electrical and Information engineering (ICCTEIE), International Conference on

作者： Pawenary Dwi Listiawati Hendri Electrical Engineering Study Program Faculty of Electricity and Renewable Energy Insitut Teknologi PLN Jakarta Indonesia

Waste is a problem in almost every region, especially related to how the processing of waste can be converted into other forms as a form of energy that can be utilized, one of which is waste processing by pyrolysis is one of the technologies to convert waste into useful energy or fuel. At this time waste processing requires waste processing machines ranging from organic and un-organic waste shredding machines, briquette processing machines, pellets, using star-delta 3-phase motors, generally still conventional/manually. Current research, the author began to develop a waste and flue gas particle handling machine, a non-incinerator pyrolysis machine with the wet method, a high efficiency cyclone system which originally used a machine manually/ conventionally, replaced with a Delta series Star - Delta series with interlock and interface) automatically. Garbage processing The machine in addition to aiming to reduce waste waste, the machine must be made automatically and friendly to the operator who runs it.

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Fixed-parameter algorithms for cardinality-constrained graph partitioning problems on sparse graphs

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Discrete Applied Mathematics 2025年 373卷 343-354页

作者： Yamada, Suguru Hanaka, Tesshu Graduate Program of Mathematics for Innovation Kyushu University 744 Motooka Nishi-ku Fukuoka Fukuoka819-0395 Japan Faculty of Information Science and Electrical Engineering Kyushu University 744 Motooka Nishi-ku Fukuoka Fukuoka819-0395 Japan

For an undirected and edge-weighted graph G=(V,E) and a vertex subset S⊆V, we define a function φG(S)≔(1−α)⋅w(S)+α⋅w(S,V∖S), where α∈[0,1] is a real number, w(S) is the sum of the weights of edges having two endpoints in S, and w(S,V∖S) is the sum of the weights of edges having one endpoint in S and the other in V∖S. Then, given an undirected and edge-weighted graph G=(V,E) and a positive integer k, MAX (MIN)α-FIXED CARDINALITY GRAPH PARTITIONING (MAX (MIN)α-FCGP) is the problem to find a vertex subset S⊆V of size k that maximizes (minimizes) φG(S). In this paper, we first show that MAXα-FCGP with α∈[1/3,1] and MINα-FCGP with α∈[0,1/3] can be solved in time 2o(kd+k)(e+ed)knO(1) where k is the solution size, d is the degeneracy of an input graph, and e is Napier's constant. Then we consider MAX (MIN) CONNECTEDα-FCGP, which additionally requires the connectivity of a solution. We show that if MAX (MIN)α-FCGP is W[1]-hard parameterized by k, so is MAX (MIN) CONNECTEDα-FCGP. Then, we give a 2O(klog2k)nO(1)-time randomized algorithm on apex-minor-free graphs. Moreover, for MAX CONNECTEDα-FCGP with α∈[1/3,1] and MIN CONNECTEDα-FCGP with α∈[0,1/3], we propose a (1+d)k2o(kd)+O(k)nO(1)-time algorithm. Finally, we show that they admit FPT-ASs parameterized by k when edge weights are constant. © 2025 Elsevier B.V.

关键词： Graph algorithms

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Building a Simple COVID-19 Knowledge Graph in Bahasa Indonesia: A Preliminary study 3

Building a Simple COVID-19 Knowledge Graph in Bahasa Indones...

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3rd IEEE International Biomedical Instrumentation and Technology Conference, IBITeC 2023

作者： Muharram, Arief Purnama Taufikulhakim, Farhan Hilmi Purwarianti, Ayu Universitas Indonesia Faculty of Medicine Jakarta Indonesia Institut Teknologi Bandung School of Electrical Engineering and Informatics Master Program of Informatics Bandung Indonesia

ISBN: (纸本)9798350302424

COVID-19 is an acute respiratory disease that has become a pandemic worldwide. Many studies have been conducted to enhance our understanding of COVID-19. However, the abundance of information obtained from these studies has resulted in information overload. In this study, we purposed a simple COVID-19 Knowledge Graph in Bahasa Indonesia as a way to reconstruct knowledge to combat this information overload. We used Bahasa Indonesia in our study to explore its potential for constructing a Knowledge Graph (KG). The construction of our KG involved manual curation of medical literatures and annotation of entities and relationships by the domain experts. The KG was implemented using Neo4J version 5. We successfully demonstrated our COVID-19 KG, which consists of 240 nodes and 276 relationships with 15 and 14 node and relationship labels, respectively. Accessing the information within the KG is made effortless through the use of Cypher queries in Neo4J. Further research is still needed to develop the KG into a larger and better one. However, our COVID-19 KG can serve as a basis for further development. © 2023 IEEE.

关键词： COVID-19

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Deep Semantic and Attentive Network for Unsupervised Video Summarization

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ACM Transactions on Multimedia Computing, Communications and Applications 2022年第2期18卷 1-21页

作者： Zhong, Sheng-Hua Lin, Jingxu Lu, Jianglin Fares, Ahmed Ren, Tongwei College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Department of Electrical Engineering Computer Systems Engineering Program Faculty of Engineering at Shoubra Benha University Cairo Egypt State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China

With the rapid growth of video data, video summarization is a promising approach to shorten a lengthy video into a compact version. Although supervised summarization approaches have achieved state-of-the-art performance, they require frame-level annotated labels. Such an annotation process is time-consuming and tedious. In this article, we propose a novel deep summarization framework named Deep Semantic and Attentive Network for Video Summarization (DSAVS) that can select the most semantically representative summary by minimizing the distance between video representation and text representation without any frame-level labels. Another challenge associated with video summarization tasks mainly originates from the difficulty of considering temporal information over a long time. Long Short-Term Memory (LSTM) performs well for temporal dependencies modeling but does not work well with long video clips. Therefore, we introduce a self-attention mechanism into our summarization framework to capture the long-range temporal dependencies among the frames. Extensive experiments on two popular benchmark datasets, i.e., SumMe and TVSum, show that our proposed framework outperforms other state-of-the-art unsupervised approaches and even most supervised methods. © 2022 Association for Computing Machinery.

关键词： Semantics

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Deep Convolutional Neural Networks for Accurate Solar Module Classification in Thermal Images

Deep Convolutional Neural Networks for Accurate Solar Module...

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International electrical engineering Congress (iEECON)

作者： Chutinun Phungket Prasit Nangthin The Graduate Program Faculty of Engineering Faculty of Engineering Pathumwan Institute of Technology Bangkok Thailand Department of Electrical Engineering Faculty of Engineering Pathumwan Institute of Technology Bangkok Thailand

ISBN: (数字)9798350383591

ISBN: (纸本)9798350383607

The rapid and continuous technological advancements in computer and internet technologies, combined with data management techniques, find applications in various domains. For example, they aid in predictive maintenance systems, evaluate the performance of solar modules, and differentiate efficiently performing solar modules from less efficient ones using thermal imagery. The accuracy of solar module classification significantly impacts the subsequent assessment. In this study, we employ advanced techniques, particularly deep learning through Convolutional Neural Networks (CNN), to classify thermal images of solar modules. The practical aspects of applying CNN to the dataset of thermal images are explored, including transfer learning from pretrained CNN architectures and custom CNN architecture training. Experiments are conducted with three prominent types of solar module conditions: normal, cracked, and dusty. The results reveal that the most effective approach involves learning and fine-tuning pre-trained architectures on detailed studies, achieving a classification accuracy of up to 94.5 % .

关键词： Training Photovoltaic cells Transfer learning Neural networks Computer architecture Thermal conductivity Thermal analysis

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The Impact Perceived Desirability, Propensity to Act, and Perceived Feasibility towards Technoprenurial Commitment Based on A Entreprenurial Event Theory 6

The Impact Perceived Desirability, Propensity to Act, and Pe...

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6th International Conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Rumangkit, Stefanus Irianto, Aloysius Bagas Pradipta Hadi, Antonius Satria Management Department BINUS Business School Bina Nusantara University Jakarta Indonesia Information System Department Faculty of Engineering Atma Jaya University Yogyakarta Indonesia Study Program of Entrepreneurship Faculty of Economy University of Widya Mataram Yogyakarta Indonesia

ISBN: (纸本)9798331539603

Technopreneurship represent a form of entrepreneurship that emphasizes entrepreneurial skills and technology. Studies on technopreneurship have been conducted, but research investigating antecedents of technopreneurship based on the entrepreneurial event model (EEM), is still limited. Most research on technopreneurship is dominated by the use of the theory of planned behavior (TPB). Therefore, this study aims to investigate the driving factors in EEM, namely perceived desirability, propensity to act, and perceived feasibility to technopreneurship intention. In addition, another purpose of this study is to explore technopreneurship intention towards technopreneurship commitment. To achieve this goal, the study used quantitative research design, primary data sources, and data collection methods using questionnaires. The sample in this study amounted to 240, with the sampling method using purposive sampling. Reliability, validity, and hypothesis testing using Smart-PLS software version 3. The results showed that perceived desirability affects technoprenurial intention, propensity to act affects technoprenurial intention, perceived feasibility affects technoprenurial intention, and technoprenurial intention affects technopreneurial commitment. © 2024 IEEE.

关键词： Entrepreneurship Intention Entreprenurial Event Model Technopreneurship

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Security Door Lock Using Multi-Sensor System Based on RFID, Fingerprint, and Keypad

Security Door Lock Using Multi-Sensor System Based on RFID, ...

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Green Energy, Computing and Sustainable Technology (GECOST), International Conference on

作者： Joni Welman Simatupang Ramses Wanto Tambunan Electrical Engineering Study Program Faculty of Engineering President University Cikarang Indonesia

ISBN: (纸本)9781665486644

Thefts problem in household needs to be anticipated with home security system. One of simple methods is using automatic solenoid door lock system, so that it is difficult to be duplicated and will reduce the chance of theft action when the house is empty. Therefore, a home security system prototype that can be accessed by utilizing biometric fingerprint, Radio Frequency Identification (RFID), and keypad sensors was designed and tested. Arduino Uno works to turn on the door lock solenoid, so door access will be given when authentication is successful. Experimental results show that fingerprint sensor works well by being able to read fingerprints perfectly and the average time required to scan a fingerprint was 3.7 seconds. Meanwhile, Radio Frequency Identification (RFID) sensor detects Electronic-Kartu Tanda Penduduk (E-KTP) and the average time required for Radio Frequency Identification (RFID) to scan the card is about 2.4 seconds. Keypad functions to store password to unlock the door which produces the average time of 3.7 seconds after 10 trials. Average time to open with multi-sensor is 9.8 seconds. However, its drawback is no notification or SMS which directly be accessed by a cellphone or website with Wi-Fi or Telegram applications allow homeowners to monitor their doors from afar as to minimize the number of house thefts.

关键词： Prototypes Thumb Passwords Fingerprint recognition Sensor systems Sensors Security

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