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SSRN 2023年

作者： Ranny, Ranny Lestari, Dessi Puji Mengko, Tati Latifah Erawati Rajab School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia School of Electrical Engineering and Informatics U-CoE AI-VL Institut Teknologi Bandung Bandung Indonesia Department of Biomedical Engineering School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

Background: Sound processing frameworks have many kinds of approaches. The approaches are distinguished based on data and purpose of the sound processing research area. One of the research purposes are localization and detection of sound events. The research also uses non-overlapping data and overlapping data to test the sound processing algorithms. The previous research has a good accuracy with non-overlapping sound, but the accuracy decreased when it uses the overlapping data sound. Whereas the overlapping data sound appeared in a real condition. So, this research is developing a framework that can handle the non-overlapping and overlapping data. Objective: This research focused on overlapping sound processing. The using of overlapping sound in sound recognition system decreases the recognition accuracy. This research tries to improve the sound recognition system without eliminating the using of overlapping sound. Methods: This research uses a different approach than any other common research. This research used the non-overlapping data and separated sound data as the data train for sound event localization and detection (SELD). The separation of overlapping sound generates the separated sound and is used for detection the overlapping data sound. This new framework is called Separation ***: This Separation SELDnet framework gives 81% localization accuracy and 70% detection accuracy when the SELDnet only gives a lower accuracy for the overlapping ***: The Separation SELDnet gives a good opportunity to increase the sound recognition with using non overlapping and overlapping sound. This new method can be more adaptive with real condition. © 2023, The Authors. All rights reserved.

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Optical Intra- and Inter-Rack Switching Architecture for Scalable, Low-Latency Data Center Networks

Optical Intra- and Inter-Rack Switching Architecture for Sca...

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IEEE Symposium on computers and Communications (ISCC)

作者： Georgios Drainakis Peristera Baziana Adonis Bogris School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Department of Informatics and Telecommunications University of Thessaly Lamia Greece Department of Informatics and Computer Engineering University of West Attica Egaleo Greece

In this paper we propose a DC network (DCN) architecture that interconnects servers in the intra-rack and inter-rack domain, utilizing optical switching at each domain. The proposed interconnection techniques are studied as an intermediate step before migrating the entire DCN to all-optical schemes. Unlike other studies, we study the server-to-server communication across the whole DCN. For the performance evaluation we produce numerical results for throughput and end-to-end delay for three traffic classes co-existing in DCN s. The numerical analysis reveals that bandwidth utilization reaches 90% and 100% in the intra- and inter- domain respectively. Meanwhile, the maximum end-to-end delay for the highest priority packets under congested load is lower than 0.56 and 0.41 µs for the two examined intra-rack capacity scenarios of 400 and 600 Gbps respectively. A comparative study shows that our solution can effectively interconnect up to 10000 servers with lower environmental footprint and end-to-end delay than other DCN s.

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Abridged Neat Key Instance: an Integrity Property for Digital Multimedia Asset of Non-fungible Token

Abridged Neat Key Instance: an Integrity Property for Digita...

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International Conference on informatics and Computing (ICIC)

作者： Fardani Annisa Damastuti Moch Fachri Nugrahardi Ramadhani Didit Prasetyo Aliridho Barakbah Mochamad Hariadi Electrical Engineering Department Institut Teknologi Sepuluh Nopember Surabaya Indonesia Informatics and Computer Engineering Dept Politeknik Elektronika Negeri Surabaya Surabaya Indonesia Computer Engineering Department Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798331517601

ISBN: (纸本)9798331517618

The non-fungible token (NFT) is a record used to ensure the privilege and ownership of a certain digital asset with a distinctive digital identifier in a blockchain. In digital-multimedia assets i.e. images, videos, audio, etc. NFTs generally retain references to the properties of the asset. Due to the nature of blockchain technology, NFT is oftentimes associated with its immutability. NFTs that represent digital multimedia assets may utilize blockchain-based file servers, but oftentimes time the associated file is stored off-chain. This makes the assets themselves vulnerable to link rot and causes the NFT owner to lose access to their assets since the off-chain storageis not immutable like the NFT. To preserve the integrity of the NFT’s associated digital assets, we introduce Abridged Neat Key Instance (ANKI). ANKI is a property embedded inside NFT that contains the seed number of the digital multimedia asset to be procedurally generated. We are taking advantage of Procedural Content Generation (PCG) technology to reproduce the digital multimedia asset presented by the information available inside the NFT itself. By leveraging Procedural Content Generation(PCG) technology, our approach can regenerate the exact digital asset directly from the information encoded within the *** our experiments, we successfully recreated music files using the ANKI seed and a PCG engine, verifying their accuracy by comparing the MD5 and SHA-512 checksums of the generated files with those of the original NFT assets. All 50 generated musicfiles produced identical checksums to their original counterparts,confirming the integrity of our method.

关键词： Procedural generation Accuracy Streaming media File servers Nonfungible tokens Reliability informatics Engines Phonocardiography Videos

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Multi-objective optimization of electric automated bus trajectories based on the ε-constraint method

Multi-objective optimization of electric automated bus traje...

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Mediterranean Conference on Control and Automation (MED)

作者： C. Pasquale S. Sacone S. Siri A. Ferrara Department of Informatics Bioengineering Robotics and Systems Engineering University of Genova Italy Department of Electrical Computer and Biomedical Engineering University of Pavia Italy

This paper deals with electric automated buses that have to follow a given route in inter-urban roads including stops, with a given timetable. Some stops are provided with a charging infrastructure allowing to charge the batteries while others are not. In order to control these buses, it is necessary to account for the traffic conditions along the road and to minimize two objectives, respectively related to the minimization of the deviations from the timetable and the minimization of the energy lack, at the end of the bus route, with respect to a desired final energy level. To address this problem and to investigate the conflicting nature of these objectives, two multi-objective methods based on the $\varepsilon$-constraint approach are applied in this paper, allowing to find different sets of efficient solutions for the problem. The results obtained in a real case study show that the two objective are in conflict, and compromise solutions can be found using the methods proposed in this paper.

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An Explainable Artificial Intelligence model in the assessment of Brain MRI Lesions in Multiple Sclerosis using Amplitude Modulation – Frequency Modulation multi-scale feature sets

An Explainable Artificial Intelligence model in the assessme...

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International Conference on Digital Signal Processing (DSP)

作者： Andria Nicolaou Antonis Kakas Constantinos S. Pattichis Marios S. Pattichis Kevin Fotso Christos P. Loizou Marios Pantzaris Department of Computer Science University of Cyprus Nicosia Cyprus Department of Electrical Engineering and Computer Engineering University of New Mexico USA Department of Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus Cyprus Institute of Neurology and Genetics Nicosia Cyprus

The objective of this study was to implement an explainable artificial intelligence (AI) model with embedded rules to assess Multiple Sclerosis (MS) disease evolution based on brain Magnetic Resonance Imaging (MRI) multi-scale lesion evaluation. Amplitude Modulation-Frequency Modulation (AM-FM) features were extracted from manually segmented brain MS lesions obtained using MRI and were labeled with the Expanded Disability Status Scale (EDSS). Machine learning models were used to classify the MS subjects with a benign course of the disease and subjects with advanced accumulating disability. Rules were extracted from the selected model with high accuracy and then were modified to perform argumentation-based reasoning. It is demonstrated that the proposed explainable AI modeling can distinguish MS subjects and give meaningful information to track the progression of the disease. Future research will examine more subjects and add new feature sets and models.

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Support Vector Machine Method for Predicting Children's Emotions 9

Support Vector Machine Method for Predicting Children's Emot...

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9th International Conference on electrical engineering, computer Science and informatics, EECSI 2022

作者： Gehara Zhafirah, Fildzah Aure Rokhana, Rika Sigit, Riyanto Bayu Dewantara, Bima Sena Politenik Elektronika Negeri Surabaya Department of Electrical Engineering Surabaya Indonesia Politenik Elektronika Negeri Surabaya Department of Informatics and Computer Engineering Surabaya Indonesia

ISBN: (数字)9786239213565

ISBN: (纸本)9781665470438

Emotion is an intense feeling that is directed at someone or something that can trigger to take an action or expression from inside or outside themself. In everyday life, it is important to be able to understand and predict the emotional state of a person. One of the emotions of a person can be known through facial expressions, but sometimes a person can manipulate it by controlling his facial expressions. Therefore, we need a system that can predict children's emotions based on changes in their body condition. In this study, two sensors were used, namely the GSR sensor and the heart rate sensor. The data obtained from each sensor is processed using a microcomputer or raspberry pi. Furthermore, the sensor output will be processed first using the Support Vector Machine (SVM) method by comparing 2 pieces of data, namely normalized data and unnormalized data based on linear, polynomial, RBF, and sigmoid kernels, so that a model will be obtained and will be used as a reference to predict 3 types of emotions namely happy, sad, and angry. From this research, the best model is obtained when using linear and sigmoid kernels with normalized data types. This is proven when using normalized data with linear and sigmoid kernels, there are only 18 incorrect data with an accuracy rate of 86.67%. This research is expected to help parents and teachers to predict emotions, especially in children. © 2022 Institute of Advanced engineering and Science (IAES).

关键词： Children Emotion Prediction Galvanic Skin Response (GSR) Heart Rate Support Vector Machine (SVM)

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Home Healthcare Technologies and Services: HeartRate Fetus Monitoring System Using an MCU ESP8266 Node

Home Healthcare Technologies and Services: HeartRate Fetus M...

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2022 Panhellenic Conference on Electronics and Telecommunications, PACET 2022

作者： Skrivanos, Anastasios G. Chronopoulos, Spyridon K. Kosma, Evangelia I. Kouretas, Ioannis Peppas, Kostas P. University of Peloponnese Department of Informatics and Telecommunications Tripolis Greece Ioannina Greece University of Ioannina Department of Speech Language Therapy Ioannina Greece University of Patras Department of Electrical and Computer Engineering Patras Greece

ISBN: (数字)9798350399585

ISBN: (纸本)9798350399585

In this paper, a preliminary implementation of a system monitoring the fetus's heart rate (FHR) has been designed and implemented as a mobile wearable measuring system with remote sensing specifically developed on Node MCU ESP8266 (ESP). In particular, the proposed system uses sensors for heart rate, humidity, temperature, and a transceiver module. The transceiver module is capable of efficient data transmission to a remote server station using an IEEE 802.11 b/g/n protocol - based on the wireless network. A major benefit is that the patient's data is monitored at distance using an IoT device. Hence, it complies with the health safety distance measures required due to various situations, including that of the COVID-19 pandemic. The proposed implementation has been proven to be efficient in terms of hardware simplicity and cost-effectiveness and is accompanied by preliminary accurate measurements of the FHR. © 2022 IEEE.

关键词： COVID-19

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Decentralized Control of Intercity Electric Automated Buses via Time-Varying Objective Prioritization

Decentralized Control of Intercity Electric Automated Buses ...

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IEEE Conference on Decision and Control

This paper considers electric automated buses traveling in inter-urban roads and following a given route including stops, that must be reached according to a given timetable. Some of these stops are provided with a charging infrastructure allowing to charge the bus batteries. The paper proposes a decentralized control scheme for determining the optimal speed profiles, the dwell and charging times of the buses, by taking into account the traffic conditions along the road through a suitable traffic flow prediction model. Two objectives are considered contemporarily: the minimization of the deviations from the timetable and the minimization of the energy lack at the end of the bus route. To attain both these conflicting objectives, a lexicographic approach is adopted to design the controller which considers that, depending on the system state, the priority of the two objectives can change. Accordingly, the proposed control scheme changes the objective prioritization in real time and switches between two different lexicographic-based optimal control solutions. Some tests are discussed in the paper to show the effectiveness of the proposed control scheme.

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Automatic Determination of Seeded Region Growing Parameters in Watershed Regions to Segmentation of Tuna 7

Automatic Determination of Seeded Region Growing Parameters ...

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7th International Conference on informatics and Computing, ICIC 2022

作者： Saputra, Wanvy Arifha Arifin, Agus Zainal Wiranda, Nuruddin Yohanes, Edi Abidin, Zainal Suriansyah, Bambang Politeknik Negeri Banjarmasin Department of Electrical Engineering Banjarmasin Indonesia Institut Teknologi Sepuluh Nopember Surabaya Department of Informatics Surabaya Indonesia Lambung Mangkurat University Department of Computer Education Banjarmasin Indonesia

ISBN: (纸本)9798350345711

Seeded region growing has two main parameters, namely seed initialization and threshold determination. Parameter values can be done manually or automatically. Automatic parameter assessment is suitable to be applied on a real time basis, but the parameter assessment must be precise. This is due to the greater risk of segmentation errors than manual. This research aims to propose automatic determination of seeded region growing in the watershed region for image segmentation of tuna. The tuna image was processed into the hue, saturation, and intensity (HSI) color space. The hue color space was then taken up in the formation of the watershed region. After that, the density of a region was calculated, then the density was sorted and the highest density was taken. The region that had the highest density was taken based on the highest gray level intensity, then the threshold was obtained from the difference between the average number of regions used and the average intensity of the region left. The results of tuna image segmentation were successfully carried out by proving the average values of relative foreground area error (RAE), missclassification error (ME), and modified Hausdroff distance (MHD) respectively for category 1 data of 6.77%, 1.78% and 0.18%, while for category 2 data of 3.44%, 1.30% and 0.66%. © 2022 IEEE.

关键词： Watersheds

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Evaluation and Integration of Advanced AI Chatbots for Biological Pathway Curation

Evaluation and Integration of Advanced AI Chatbots for Biolo...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Muhammad Azam Fei He Krpns Santosh Dong Xu Mihail Popescu Department of Electrical Engineering and Computer Science University of Missouri Columbia Missouri USA Department of Health Management and Informatics University of Missouri Columbia Missouri USA

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

The rapid expansion of biological literature presents significant challenges in manually curating pathway knowledge from images for biological and medical research. Recent advancements in AI, particularly multimodal AI chatbots like GPT-4V, Claude, and Gemini, offer promising capabilities for image understanding and extraction of biological interactions. This study evaluates the effectiveness of these AI chatbots in curating gene interactions from 50 curated tumor signaling pathway images. Our results highlight the superior performance of GPT-4V, achieving a precision of 0.778, a recall of 0.664, an F1-score of 0.716 in non-directional analysis, and a precision of 0.566, a recall of 0.471, an F1-score of 0.512 in directional analysis. Claude followed with a precision of 0.735, recall of 0.594, and F1-score of 0.6571 in non-directional analysis, and a precision of 0.500, recall of 0.400, and F1-score of 0.445 in directional analysis. Gemini recorded the lowest performance metrics across both analyses. We further developed a model fusion integrating Claude-3 chatbots and our pathway curation pipeline, achieving notable improvements.

关键词： Analytical models Accuracy Biological system modeling Predictive models Chatbots Real-time systems Reliability Artificial intelligence Bioinformatics Tumors

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