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检索条件"机构=Dept. of Control and Computer Engineering"

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3D modelling and virtual reality for museum heritage presentation: Contextualisation of sculpture from the tang era 10

3D modelling and virtual reality for museum heritage present...

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10th International Workshop 3D-ARCH "3D Virtual Reconstruction and Visualization of Complex Architectures"

作者： Spallone, R. Lamberti, F. Vigo, L. Ronco, F. Calandra, D. Ferraro, M. Dept. of Architecture and Design Politecnico di Torino Italy Dept. of Control and Computer Engineering Politecnico di Torino Italy Curator of Asian Arts Montreal Museum of Fine Arts MontrealQC Canada

The present research concerns the contextualisation and presentation of eleven small statues from the Tang era dated from the XI and XII centuries CE today housed at the Asian Art Museum in Turin (MAO). A multidisciplinary group with expertise in Asian art, digital representation, and information processing systems, with the support of VR@POLITO and MOD Lab Arch of the Politecnico di Torino is involved in the work. The goal is to present together several Tang-era pottery models not belonging to the same funerary outfit within the spaces of a coeval, philologically compatible hypogeal tomb. With a pronounced storytelling intent, the reconstructive 3D model represents a virtual exhibition project summarizing Tang art's architectural, pictorial, and sculptural features. The pipeline was developed through photogrammetric acquisition with Structure from Motion (SfM) technology and 3D modeling of the artworks, reconstructive modeling and texturing of a Tang tomb as the ideal space of the statues, and communication through a virtual reality (VR) experience augmented with a set of information. © Author(s) 2024.

关键词： 3D modeling

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From Product Sheet to Text and Video: A NLG Pipeline to Transform Structured Data into Comprehensive Descriptions 32

From Product Sheet to Text and Video: A NLG Pipeline to Tran...

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32nd Italian Symposium on Advanced Database Systems, SEBD 2024

作者： Avignone, Andrea Fiori, Alessandro Chiusano, Silvia Rizzo, Giuseppe Dept. of Control and Computer Engineering Politecnico di Torino Corso Duca degli Abruzzi 24 Torino10129 Italy LINKS Foundation Torino Italy

The recent improvement of powerful Large Language Models is the key to automatically produce satisfactory written and spoken language, in contrast to the constraints of conventional template-based solutions. However, the most advanced models can be costly and complex to integrate into practical applications, especially in business contexts where the output quality significantly matters. This study presents a tailored pipeline for data-to-text and text-to-speech generation, primarily harnessing the availability of open source pre-trained language models and leveraging established Natural Language Processing tasks. As a use case, we worked on the automatic generation of both textual and video product descriptions from the structured information about the product features. The pipeline involves all the required steps, providing the final trained and customized model. The obtained descriptions showed the capability of replicating the overall semantic, lexical and linguistic style of the corresponding human counterpart, despite being based on a cost-effective model. © 2024 Copyright for this paper by its authors.

关键词： Semantics

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A Novel DB CASE Tool for Relational Databases 31

A Novel DB CASE Tool for Relational Databases

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31st Symposium of Advanced Database Systems, SEBD 2023

作者： Avignone, Andrea Chiusano, Silvia Fiori, Alessandro Garza, Paolo Marchetta, Emanuele Dept. of Control and Computer Engineering Politecnico di Torino Corso Duca degli Abruzzi 24 Torino10129 Italy

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control of Deterministic Chaotic Modes in Power Systems

Control of Deterministic Chaotic Modes in Power Systems

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2023 IEEE International Conference on Smart Information Systems and Technologies, SIST 2023

作者： Beisenbi, Mamyrbek Satpayeva, Ainur Mussabayeva, Shugla Mussina, Gulnara Tlegen, Meruert L.N. Gumilyov Eurasian National University Dept. of System Analysis and Control Astana Kazakhstan Astana It University Dept. of Computer Engineering Astana Kazakhstan

ISBN: (纸本)9798350335040

The paper examines a new approach to controlling deterministic dynamical chaotic mode of power system with two electric generate-sources. A control law is synthesized in the class of one-parameter structurally stable mappings from catastrophe theory. Analytical calculations and a numerical experiment in MatLab showed that the proposed system excludes the generation of a deterministic chaotic mode for any changes in the uncertain system parameters. The study of the control system is carried out by the gradient-velocity method Lyapunov vector functions © 2023 IEEE.

关键词： Uncertainty analysis

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Stratification of metastatic melanoma patients based on mutational signatures

Stratification of metastatic melanoma patients based on muta...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Alfano, Caterina Farina, Lorenzo Petti, Manuela Sapienza University of Rome Program in Network Oncology and Precision Medicine Rome Italy Sapienza University of Rome Program in Network Oncology and Precision Medicine Dept. of Computer Control and Management Engineering Rome Italy Sapienza University of Rome Dept. of Computer Control and Management Engineering Rome Italy

ISBN: (纸本)9798350337488

Genetic instability is one of the hallmarks of cancer, however mutations can occur for different causes and induce different effects. Mutational signatures are characteristic patterns of somatic mutations in cancer genomes, reflecting the underlying mutational processes. A mutational signature can be determined by studying the kind of mutations a patient has acquired during their life: patient stratification based on mutational signatures has become more and more useful in genomic studies, given its possible clinical implications. In this work we focused on Single Base Substitution (SBS) signatures to study a cohort of 115 metastatic melanoma patients. We inferred and identified two mutational signatures characterizing the patients. Based on these signatures we divided patients into two group: the bigger group was characterized by a signature associated with exposure to ultraviolet light, while the smaller group resulted to be mostly composed of patients which did not respond to immunotherapy (anti-PD1) and that presented a low mutational count. More importantly this second group showed a significantly worse survival outcome. The use of mutational signatures is clearly a powerful tool to identify disease sub-types that have a clinical relevance, however we believe that this topic needs further investigation focused on the characterization of patient subtypes with a multi-omics based approach. © 2023 IEEE.

关键词： computational medicine genomics metastatic melanoma mutational signatures patient stratification precision oncology

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Automated Optical Inspection for Quality control in PCBA assembly lines: a case study for Point of Sale Devices Production Lines 6

Automated Optical Inspection for Quality Control in PCBA ass...

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6th International Congress on Human-computer Interaction, Optimization and Robotic Applications, HORA 2024

作者： Aras, Kerem Saif, Syed Saad Giuseppi, Alessandro Coskun, Vedat R&D Center Token Financial Technologies Istanbul Turkey Dept. of Computer Control and Management of Rome La Sapienza Rome Italy Dept. of Software Engineering Istanbul Atlas University Istanbul Turkey

ISBN: (纸本)9798350394634

This paper reports on the design and development of a customized Automated Optical Inspection (AOI) solution aimed at detecting defects in a production line related to the correct mounting of integrated circuits. Contrary to most solutions avail- able on the market, the developed system relies on deep learning to be able to perform detailed real-time visual inspections of components without the need to compare the captured photos with any reference images/golden sample. The proposed solution was designed to also provide good generalization capabilities, accommodating visual changes in the environment and in the structure of the component being produced. A custom testing machine was built in order to perform real-time inferences and validate the simulation results in a real-world setting. © 2024 IEEE.

关键词： Assembly

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Optimizing Thermo-Electric Generation with Quasi-Z-Source Converter in Energy Harvesting for Wearable Devices 3

Optimizing Thermo-Electric Generation with Quasi-Z-Source Co...

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3rd International Conference on Mechatronics and Automation Technology, ICMAT 2024

作者： Lotfy, Mostafa Wageh Hussein, Aziza I. Dept. of Process Control Technology Faculty of Technology and Education Beni-Suef University Beni-Suef Egypt Electrical and Computer Engineering Department College of Engineering Effat University Jeddah Saudi Arabia

ISBN: (纸本)9781643685649

Recent advances in semiconductors industry and microelectronics have created new opportunities for integrating various technologies in energy harvesting projects. These advancements have simplified the process of capturing energy from different sources, such as thermal energy, and converting it into electrical power. Thermo-Electric Generators (TEGs) are commonly used in many applications such as wearable devices. However Thermo-Electric Generators produce very low output voltages, which is insufficient for most low-power electronic circuits to operate. Therefore, a boost converter is essential to step up the voltage output from the TEG to a usable level. In this paper, a DC-DC converter with a high performance in terms of voltage gain is implemented. The proposed quasi-Z-source (q-ZSC) DC-DC converter not only offers high voltage gain but also several significant advantages. The proposed q-ZSC is capable of both boosting and regulating the voltage output efficiently, even under variable input conditions, making it highly suitable for low-power energy harvesting systems such as Thermo-Electric Generators. The design is simulated using MATLAB Simulink software, focusing on integrated circuits, with a strong emphasis on optimizing the circuit's efficiency. This work underscores critical factors in improving energy harvesting circuits, enhancing their performance and effectiveness in low-power applications for wearable technology. © 2024 The Authors.

关键词： DC generator motors

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Xception CNN-Ensemble Learning Based Facial Emotion Recognition 6

Xception CNN-Ensemble Learning Based Facial Emotion Recognit...

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6th International Conference on Computing, Communication, control and Automation, ICCUBEA 2022

作者： Shirsath, Supriya Vikhe, Vaishali Vikhe, Pratap Pravara Rural Engineering College Dept. of Computer Engineering Ahmednagar India Pravara Rural Engineering College Dept. of Instrumentation & Control Engineering Ahmednagar India

ISBN: (纸本)9781665484510

Emotions in human is an effective medium to study the mindset of a person. Since, expression on the face of human is significant approach to understand the condition and communicate with him to release the pressure or stress of person. The emotions and behavior have a strong relationship and is noteworthy in non-verbal form of communication. The advancement in medical science and use of image processing tools like Artificial Intelligence (AI) and Machine Learning (ML), can be helpful to recognize emotion, detect stress and depression level of a person. Thus, in this research work emotion recognition system is developed using Convolution Neural Networks (CNNs) with increased dept. and width. CNNs have been shown to enhance prediction accuracy. In terms of proper emotion categorization and accurate prediction, the suggested ensemble technique is effective. In this paper Xception CNN architecture is proposed for accurate facial emotions prediction along with an ensemble model, using Max Voting ensemble technique, mainly contributes in accurate classification. In proposed technique trained CNN models were loaded and for each trained model prediction probabilities were generated. Furthermore, it is then used for Max Voting to generate final emotion prediction. The CNN models are trained and evaluated on FER-2013 dataset. © 2022 IEEE.

关键词： Emotion Recognition

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Fuzzy Logic controller for the Chemotherapy of Brain Tumor 9

Fuzzy Logic Controller for the Chemotherapy of Brain Tumor

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9th International Conference on control, Decision and Information Technologies, CoDIT 2023

作者： Zubair, Muhammad Iacoviello, Daniela Mughal, Iqra Shafeeq Sapienza University of Rome Dept. Computer Control and Management Engineering Rome Italy University of Catania Dept. di Ingegneria Electrica Electronica e Informatica Dieei Catania Italy

ISBN: (纸本)9798350311402

An advanced Fuzzy Logic controller (FLC) that considers all the states of the brain tumor system is designed for the chemotherapy treatment. A Mamdani-type FLC is proposed for dynamically controlling the chemotherapy drug for the tumor system;the chemotherapy treatment of brain tumors requires advanced strategies which mainly depend upon the severity of the tumor. In this work, the advanced FLC designed aims both at determining the amount of chemotherapy to eliminate tumor cells, and at preserving the minimum amount of healthy and immune cells. The controller's performance is verified using MATLAB software based on different control parameters, showing its effectiveness in reducing the tumor cells. It has shown favorable results in terms of steady-state error, rate of convergence, and amount of drug consumed. © 2023 IEEE.

关键词： Fuzzy control

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Improvement of Protection Factor for a controlled Laboratory computer Network Using Artificial Intelligence

Improvement of Protection Factor for a Controlled Laboratory...

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2023 International Conference on engineering, Science and Advanced Technology, ICESAT 2023

作者： Daoud, Raid W. Aziz, Enas F. Abdullah, Zaki M. Saleh, Ziyaad H. Northern Technical University Electrical Tech. Dept. Kirkuk Iraq Northern Technical University Computer Systems Dept. Kirkuk Iraq College of Petroleum Processes Engineering Petroleum Systems and Control Dept. Tikrit Iraq

ISBN: (纸本)9798350344400

computer networks provide exceptional privacy, primarily for testing and other educational activities. However, the security of computer networks is an exceptionally touchy subject, mainly when applied in labs and tests for educational purposes. Any software system created on a server typically requires a username and password to access a collection of computers on a particular network. The proposed work devised and implemented a neural network feedback network with four inputs (I.P. address, MAC address, user number, and time) and an output that represents the user's acceptance or rejection. A few instances of the data and numbers needed to train the neural network include the lab's address, the student's name, the academic stage's address, etc. Good results were obtained through the company's training and education, which was tested on more than 200 models, and the response aligned with the data. No user can access the network without first being recognized by the proposed network by comparing the pre-trained data to ensure they are authorized to take the exam or enter for any other reason. © 2023 IEEE.

关键词： Network security

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