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Generative Adversarial Networks as Weight Generators in Ensemble Classification 4

Generative Adversarial Networks as Weight Generators in Ense...

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4th International Conference on Artificial Intelligence, Robotics and Control, AIRC 2023

作者： Yehia, Asmaa Fahmy, Sherif Fahmy, Ahmed AASTMT Basic Applied Science Dept. Giza Egypt AASTMT Computer Engineering Dept. Cairo Egypt

ISBN: (纸本)9798350348248

Ensemble classifiers are constructed from various component classifiers by aggregating the results of the individual classifiers in some manner. While there are many ways to do this, one of the least computationally intensive is to use a voting ensemble, where the vote of each classifier is weighted by a number representing its performance. Choosing the appropriate weights is an involved process, that ranges from using trial and error to using sophisticated machine learning algorithms. In this paper, we proposed a novel technique that uses generative adversarial networks to customize the weights used for each individual input to the ensemble. Specifically, we propose to use conditional generative adversarial networks to generate the weights, with the input image acting as the label to the network and the appropriate weight being the output. We test the proposed system on an image classification task and show that the proposed method produces better results than using fixed weights by 2.43 percent. © 2023 IEEE.

关键词： Image recognition

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Grammatical Evolution of Synthesizable Finite State Machine-Based Behavioural Level Hardware Description Language Codes 16th

Grammatical Evolution of Synthesizable Finite State Machine-...

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16th International Joint Conference on Computational Intelligence, IJCCI 2024

作者： Majeed, Bilal McEllin, Jack Sarma, Rajkumar Youssef, Ayman Mota Dias, Douglas Ryan, Conor BDS Labs Dept. of CSIS University of Limerick Limerick Ireland Dept. of Computers and Systems Electronics Research Institute Cairo Egypt Department of Computer Science & Applied Physics Atlantic Technological University Galway Ireland

ISBN: (纸本)9789897587214

The importance of designing efficient and accurate digital circuits has grown due to the widespread use of wearable, ready-made, and custom electronic products. These digital circuits are typically sequential and designed using synthesizable Hardware Description Languages (HDLs) that can be translated into hardware. A large part of this exercise comprises designing synthesizable HDLs for sequential circuits, which are challenging to design and test, thus requiring much time for the engineers to construct them. This paper proposes using Grammatical Evolution (GE) to evolve the synthesizable HDL codes for sequential circuits on the behavioural or algorithmic level in SystemVerilog. The codes evolved in this work are of JK-Flip Flop (JK-FF), 3-bit UpDown Counter (UDC), and 8-Floor Elevator (8FE), all from the perspective of Finite State Machines (FSMs). Circuits such as 3-bit UDC and JK-FF are the basic blocks in many circuits in the industry, while 8FE is a real-life example mimicking 3-bit UDC but with a few practical exceptions. All circuits are evolved using two types of grammars. The G1 Type Grammar evolves parts of the code, while the more powerful and generic G2 Type Grammar evolves the full HDL codes for these sequential circuits. The GE-based evolution of these synthesizable design codes using both types of grammar achieves a success rate of over 86% for all circuits. Moreover, all the solution circuits evolved with the best achieved success score under the respective hyperparameter settings for G1 and G2 Type Grammar are synthesised, and their synthesis reports are compared against the synthesis reports of Gold (human-designed) circuits. The synthesis is performed using Cadence Genus at Generic Process Design Kit (GPDK) 45, 90, and 180 nm technology libraries. The synthesis results show that machine-generated designs often perform as well as or better than human-designed circuits. © 2024 by SCITEPRESS – science and Technology Publications, Lda.

关键词： Flip flop circuits

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Automatic transformation of UML-RT models into nuXmv model checker 7

Automatic transformation of UML-RT models into nuXmv model c...

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7th International Symposium on Innovative Approaches in Smart Technologies, ISAS 2023

作者： Schorr, Ruth Frankfurt Unviersity of Applied Sciences Dept. of Computer Science and Engineering Frankfurt Germany

ISBN: (纸本)9798350383065

The use of diagram-based development approach especially Model Driven Development (MDD), where the executable code can be generated directly from the diagrammatic system model, has gained much popularity in the recent years. The use of automated code generation allows to focus primarily on the core design aspects of system design without having to deal with the developmental challenges. Moreover, the approach also avoids any gap between the system design and the developed system, which can be very common when code development is manual. However, at present, these generated programs have to be manually checked for semantics correctness and hence, the possibility of an automated model level verification of such MDD artifacts is the next big step in this domain. There are multiple tools today that implement MDD and are being used by the research world for exploring the possible verification alternatives. In this paper we look closely into the verification of one such standardized profile, UML for Real-Time (UML-RT), developed particularly for MDD of Real-Time systems. Eclipse Papyrus-RT is an open-source modeling tool that supports UML-RT for specifying software systems. nuXmv is a model checker, that can verify system models against a set of properties defined using temporal logics. This paper presents a system that automatically translates Papyrus-RT models into a behaviorally equivalent nuXmv model. © 2023 IEEE.

关键词： Real time systems

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ChatGPT Act as an Intelligence Officer

ChatGPT Act as an Intelligence Officer

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2023 IEEE International Workshop on Technologies for Defense and Security, TechDefense 2023

作者： Snidaro, Lauro Computer Science and Physics University of Udine Dept. Mathematics Udine Italy

ISBN: (纸本)9798350319392

This paper explores the potential of Large Language Models (LLMs), specifically ChatGPT, to facilitate the work of intelligence officers. LLMs have demonstrated remarkable capabilities in natural language processing and generation, making them valuable tools for information retrieval, analysis, and decision-making. This paper presents an initial overview of the capabilities of LLMs in intelligence operations. Through a case study on ChatGPT, we illustrate how intelligence officers can leverage LLMs to enhance their work, including data collection, fusion, analysis, report generation, and information sharing. The results showcase the vast potential and the limits of LLMs in supporting intelligence officers in their complex and demanding tasks. © 2023 IEEE.

关键词： Decision making

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An Integrated Monitoring System for Aerial Drones and Underwater ROVs

An Integrated Monitoring System for Aerial Drones and Underw...

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2023 IEEE International Workshop on Technologies for Defense and Security, TechDefense 2023

作者： Cecchinato, Niccolo Toma, Andrea Scagnetto, Ivan Drioli, Carlo Foresti, Gian Luca University of Udine Dept. of Mathematics Computer Science and Physics Udine Italy

ISBN: (纸本)9798350319392

We present an integrated and intelligent cooperative platform for the detection, recognition and tracking of objects in the air, underwater and on the surface. The system is based on a data integration process driven by the coordinated use of Unmanned Aerial Vehicles (UAVs) and Unmanned Underwater Vehicles (UUVs) equipped with heterogeneous sensors (e.g., magnetometers, electro-optical sensors, cameras and microphones) sending the acquired data to a centralized Ground Control Station (GCS). When the area to be monitored is large, it is needed to partition it, assigning each part to different UAVs/UUVs. Thus, those UAVs and UUVs are the nodes of a communication network where data exchange is aimed at the communication of information relating to the detection/recognition/tracking of objects. This kind of messages is very important when, for example, the object being tracked moves out of the area of competence of a given UAV/UUV to enter another area surveyed by a different UAV/UUV. The system will be useful for ISTAR (Intelligence, Surveillance, Target Acquisition, Reconnaissance) applications including both the identification of static objects positioned on the seabed (e.g., unexploded bombs, underwater infrastructures, etc.) and the identification and tracking of objects moving underwater, on the surface or flying in the area of interest. A study on a secure and encrypted wireless connection between the fleet of drones and the GCS is also addressed and an effective method for changing data encryption keys during the mission is illustrated. © 2023 IEEE.

关键词： Internet of things

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Unleashing Machine Learning for Hepatitis C Prediction: A Holistic Exploration of Clinical Insights

Unleashing Machine Learning for Hepatitis C Prediction: A Ho...

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2024 IEEE International Conference on Computing, Applications and Systems, COMPAS 2024

作者： Al-Amain Janin, Fatema Tuj Ahmed Robin, Faizul Ahmed, Shifat Mohi Uddin, Khandaker Mohammad Southeast University Dept. of Computer Science and Engineering Dhaka Bangladesh Hamburg University of Applied Sciences Dept. of Information and Electrical Engineering Hamburg Germany

ISBN: (纸本)9798331529765

Chronic diseases, characterized by long-term effects and persistent symptoms, pose significant challenges to human health and well-being. The hepatitis C virus (HCV) is the cause of chronic hepatitis C, which affects 58 million people globally. It also causes 290,000 deaths annually due to liver cancer and cirrhosis, two conditions connected to HCV. Taking advantage of machine learning (ML) algorithms' ability to analyze large datasets and identify patterns and relationships that aid in diagnosis, this effort focuses on employing algorithms for machine learning to identify and forecast hepatitis C precisely. Various techniques were utilized, including Random Forest, Cat Boost, SVM, and others to create predictive models using blood values from 615 patients, including both hepatitis patients and healthy blood donors. The dataset underwent comprehensive preprocessing, including handling missing values, scaling, and dimensionality reduction via Principal Component Analysis (PCA). Various ML algorithms were evaluated, and the Cat Boost classifier achieved the highest accuracy of 99.17%, recall of 92.00%, precision of 100.00% and F1-score is 96.00%. This study demonstrates the potential of ML in enhancing HCV diagnosis, offering less invasive and cost-effective alternatives to traditional methods, and providing predictive insights for personalized treatment plans. The findings underscore the importance of advanced data preprocessing and feature selection in improving model efficiency. This study adds to the ongoing efforts to lessen the prevalence of hepatitis C worldwide, aligning with the World Health Organization's goal to significantly decrease new HCV cases and related deaths by 2030. © 2024 IEEE.

关键词： Adversarial machine learning

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Secure Risk Management Approach for Enhancing the Performance of Cloud-based Cooperative Spectrum Sensing CRNs 22

Secure Risk Management Approach for Enhancing the Performanc...

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22nd International Symposium on Network Computing and Applications, NCA 2024

作者： Balogun, Victor Paquette, Xavier Sarumi, Oluwafemi A. Dept. of Applied Computer Science University of Winnipeg WinnipegMB Canada Institute of Computer Science Heinrich-Heine-University Duesseldorf DuesseldorfD-40215 Germany

ISBN: (纸本)9798331510183

The increasing demand for radio spectrum, spurred by an upsurge in interconnected devices, necessitates innovative management solutions. Cognitive Radio Networks (CRN) offer a promising approach to dynamically allocate spectrum resources. This study examines the Cooperative Spectrum Sensing (CCSS) architecture, leveraging cloud computing and big data analytics, to enhance CRN efficacy. We present a risk analysis identifying key vulnerabilities, explore regulatory considerations within the Canadian spectrum landscape, and propose an augmented architecture incorporating preventative and defensive strategies. We also discuss challenges encountered in the implementation phase and suggest future research trajectories for cloud-assisted CCSS systems. ©2024 IEEE.

关键词： Risk assessment

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The Rational Construction of a Wheeler DFA 35

The Rational Construction of a Wheeler DFA

引用

35th Annual Symposium on Combinatorial Pattern Matching, CPM 2024

作者： Manzini, Giovanni Policriti, Alberto Prezza, Nicola Riccardi, Brian Dept. of Computer Science University of Pisa Italy Dept. of Mathematics Computer Science and Physics University of Udine Italy Dept. of Environmental Sciences Informatics and Statistics Ca’ Foscari University of Venice Italy Dept. of Informatics Systems and Communication University of Milano-Bicocca Italy

ISBN: (纸本)9783959773263

Deterministic Finite Wheeler Automata are a natural generalisation to regular languages of the theory of compressed data structures originated by the introduction of the Burrows-Wheeler transform. Indeed, if we can find a Wheeler automaton recognizing a given language L, such automaton can be used to design time and space efficient algorithms for representing and searching L. In this paper we introduce an alternative representation of Deterministic Wheeler Automata by showing that a natural map between strings and rational numbers in Qr0, 1q can be extended to represent the automaton’s states as intervals in Qr0, 1q. Using this representation it emerges a natural relationship between automata properties and some properties of real numbers. In addition, such representation enables us to formulate problems related to automata in a numerical setting. Although at the moment the numerical approach does not lead to time efficient algorithms, we believe this new perspective deserves further consideration. As a further demonstration of the convenience of this new representation, we use it to provide a simple proof of an unexpected result on regular languages. More precisely, we compare the size of the smallest Wheeler automaton recognizing a given language L with respect to the size of the smallest automaton, possibly non-Wheeler, recognizing the same language. We show settings in which there can be an exponential gap between the two sizes, and we discuss the implications of this result on the problem of representing regular languages. © Giovanni Manzini, Alberto Policriti, Nicola Prezza, and Brian Riccardi.

关键词： Finite automata

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Vehicle To Vehicle and Vehicle To Ground Communication - Speech Encryption Algorithm

Vehicle To Vehicle and Vehicle To Ground Communication - Spe...

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2023 International Conference on Electrical, computer, Communications and Mechatronics Engineering, ICECCME 2023

作者： Al-Hazaimeh, Obaida M. Al-Smadi, Ma'moun A. Al-Balqa Applied University Dept. of Computer Science Irbid Jordan Al-Balqa Applied University Dept. of Electrical Engineering Irbid Jordan

ISBN: (纸本)9798350322972

Vehicle to vehicle (V2V) communication has many applications in intelligent transportation system (ITS) like smart grid systems, fleet management and traffic light control. It aims to interconnect several components like road infrastructures, wireless networks, sensors, and vehicles. Therefore, it can be utilized to reduce congestion, accidents and fuel consumption. This paper propose a speech encryption system based on a one-dimensional logistic map for vehicle to vehicle communication (V2V) communication in intelligent transportation systems (ITS) to improve road safety and efficiency, where encryption and security play a major role. This study employs a symmetric key cryptography technique for chaotic ciphering. In this approach, a random key table lookup criterion was paired with a one-dimensional chaotic map in order to encrypt speech samples with a high level of security and acceptable speed. XOR encryption and speech row shuffling are used in the proposed technique. Using the difference between the old and new row locations, a combination of variable rotation and inversion was performed to each shuffled row in order to increase the level of security. As a consequence of the testing, the proposed approach was shown to be both efficient and usable. Combining key table and logistic map illustrates the advantages of both high-level security and large random key space. The encrypted speech produced is suitable for practical usage especially in vehicle to vehicle and vehicle to base transmission. © 2023 IEEE.

关键词： Roads and streets

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Dimensional discoveries: Unveiling the potential of 3d heritage point clouds with a robust ontology framework 10

Dimensional discoveries: Unveiling the potential of 3d herit...

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

作者： Codiglione, Matteo Mazzacca, Gabriele Remondino, Fabio University of Trento Italy Trento Italy Dept. Mathematics Computer Science and Physics University of Udine Italy

3D point clouds feature valuable geometric and, often, radiometric and semantic information to support studies, analyses and understanding of the surveyed scene. Due to their generally large size, the use and interpretation of point clouds could be problematic. User-friendly and quick approaches for querying these valuable datasets and retrieving information could surely support end-users, in particular in the heritage sector. This work presents an ontology-based approach to facilitate the query and use of 3D heritage point clouds by means of sets of rules in order to infer properties and characteristics of the surveyed scene. Our approach is focused on linking together 3D spatial data and expert knowledge, in a way that the ontology can elaborate, represent, enrich and query a given point cloud. Results show how different queries can be set-up and how the procedure can be replicated to various queries and datasets. © 2024 International Society for Photogrammetry and Remote Sensing. All rights reserved.

关键词： Ontology

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