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2nd IEEE Conference on Information Technology and Data Science, CITDS 2022

作者： Tashu, Tsegaye Misikir Fattouh, Sara Kiss, Peter Horvath, Tomas Elte - Eötvös Loránd University Faculty of Informatics Department of Data Science and Engineering Pázmány Péter sétány 1/C Budapest1117 Hungary Faculty of Science Institute of Computer Science Pavol Jozef Šafárik University Jesenná5 Košice040 01 Slovakia College of Informatics Kombolcha Institute of Technology Wollo University Kombolcha208 Ethiopia

ISBN: (数字)9781665496537

ISBN: (纸本)9781665496537

In this work, we present a multi-modal model for commercial product classification, that combines features extracted by multiple neural network models from textual (Camem-BERT and FlauBERT) and visual data (SE-ResNeXt-50), using simple fusion techniques. The proposed method significantly outperformed the performance of the unimodal models, as well as the reported performance of similar models on our specific task. We made experiments with multiple fusing techniques, and found, that the best preforming technique to combine the individual embedding of the unimodal network is based on the combination of concatenation and averaging the feature vectors. Each modality complemented the shortcomings of the other modalities, demonstrating that increasing the number of modalities can be an effective method for improving the performance of multi-label and multimodal classification problems. © 2022 IEEE.

关键词： Neural network models

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Metagrad: Adaptive Gradient Quantization with Hypernetworks

Metagrad: Adaptive Gradient Quantization with Hypernetworks

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IEEE International Conference on Image Processing

作者： Kaixin Xu Alina Hui Xiu Lee Ziyuan Zhao Zhe Wang Min Wu Weisi Lin Institute for Infocomm Research A*STAR Singapore School of Computer Science and Engineering Nanyang Technological University Singapore National University of Singapore Artificial Intelligence Analytics And Informatics (AI3) A*STAR Singapore

A popular track of network compression approach is Quantization aware Training (QAT), which accelerates the forward pass during the neural network training and inference. However, not much prior efforts have been made to quantize and accelerate the backward pass during training, even though that contributes around half of the training time. This can be partly attributed to the fact that errors of low-precision gradients during backward cannot be amortized by the training objective as in the QAT setting. In this work, we propose to solve this problem by incorporating the gradients into the computation graph of the next training iteration via a hypernetwork. Various experiments on CIFAR-10 dataset with different CNN network architectures demonstrate that our hypernetwork-based approach can effectively reduce the negative effect of gradient quantization noise and successfully quantizes the gradients to INT4 with only 0.64 accuracy drop for VGG-16 on CIFAR-10.

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GMOCSO: Multi-objective Cat Swarm Optimization Algorithm based on a Grid System

arXiv

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arXiv 2025年

作者： Ahmed, Aram M. Hassan, Bryar A. Rashid, Tarik A. Noori, Kaniaw A. Saeed, Soran Ab.M. Ahmed, Omed H. Umar, Shahla U. Computer Science and Engineering Department University of Kurdistan Hewlêr Erbil Iraq Department of Computer Science College of Science Charmo University Chamchamal Sulaimani Iraq Database Technology Department Technical College of Informatics Sulaimani Polytechnic University Sulaimani Iraq Department of Information Technology University of Human Development Sulaymaniyah Iraq Network Department College of Computer Science and Information Technology Kirkuk University Kirkuk Iraq

This paper presents a multi-objective version of the Cat Swarm Optimization Algorithm called the Grid-based Multiobjective Cat Swarm Optimization Algorithm (GMOCSO). Convergence and diversity preservation are the two main goals pursued by modern multi-objective algorithms to yield robust results. To achieve these goals, we first replace the roulette wheel method of the original CSO algorithm with a greedy method. Then, two key concepts from Pareto Archived Evolution Strategy Algorithm (PAES) are adopted: the grid system and double archive strategy. Several test functions and a real-world scenario called the Pressure vessel design problem are used to evaluate the proposed algorithm's performance. In the experiment, the proposed algorithm is compared with other well-known algorithms using different metrics such as Reversed Generational Distance, Spacing metric, and Spread metric. The optimization results show the robustness of the proposed algorithm, and the results are further confirmed using statistical methods and graphs. Finally, conclusions and future directions were presented.. © 2025, CC BY.

关键词： Pressure vessels

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Successful Simple Side Channel Analysis: Vulnerability of an atomic pattern $kP$ algorithm implemented with a constant time crypto library to simple electromagnetic analysis attacks

Successful Simple Side Channel Analysis: Vulnerability of an...

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Mediterranean Conference on Embedded Computing (MECO)

作者： Alkistis Aikaterini Sigourou Ievgen Kabin Peter Langendörfer Nicolas Sklavos Zoya Dyka IHP — Leibniz-Institut für Innovative Mikroelektronik Frankfurt (Oder) Germany Computer Engineering and Informatics Dept. SCYTALE Group University of Patras Hellas BTU Cottbus-Senftenberg Cottbus Germany

Elliptic curve cryptosystem is a widely-used public key cryptosystem that is vulnerable to physical attacks, especially to Side Channel Analysis (SCA) attacks. This paper investigates a version of the atomic patterns $\boldsymbol{kP}$ algorithm for elliptic curves over prime finite fields. The atomic patterns for Elliptic Curve (EC) point doublings and additions are well-known countermeasures against simple SCA attacks. We implemented a binary left-to-right $\boldsymbol{kP}$ algorithm corresponding to the atomic patterns as proposed by Rondepierre and using the FLECC open-source cryptographic library. The library provides constant-time functions for the implementation of different mathematic operations in prime finite fields, making it suitable for SCA-aware implementations of cryptographic protocols, at a theoretical level. We were able to reveal the scalar k processed during a $\boldsymbol{kP}$ execution analyzing the measured electromagnetic trace of the $\boldsymbol{kP}$ execution. We determined at least two parts in the measured trace where the distinction between EC point doublings and EC point additions is good observable.

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Anomaly Detection Employing a 5G Core Data Analytics Framework

Anomaly Detection Employing a 5G Core Data Analytics Framewo...

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IEEE International Conference on Cloud Networking (CLOUDNET)

作者： Júnia Maísa Oliveira Jônatan Almeida Erik De Britto e Silva Larissa Ferreira Rodrigues Moreira Rodrigo Moreira Flávio O. Silva Daniel F. Macedo José Marcos Nogueira Computer Science Department Universidade Federal de Minas Gerais Department of Electrical Electronic and Information Engineering University of Bologna Electrical Engineering Department Universidade Federal de Minas Gerais Institute of Exacts and Technological Sciences Federal University of Viçosa (UFV) Department of Informatics University of Minho (UMINHO)

ISBN: (数字)9798350376562

ISBN: (纸本)9798350376579

The Network Data Analytics Function (NWDAF) within the 5G core is not an inherent feature of open-source 5G cores, making its implementation necessary based on provider demands. However, for those seeking to integrate NWDAF into the core but lacking expertise in core architecture or application programming interface (API) integration, this task can be daunting, potentially resulting in the abandonment of data analytics implementation efforts. While the current version of NWDAF specifies certain use cases, it does not provide alternatives for developing new analytics scenarios. To fill this gap, this paper proposes a framework for 5G network data analytics designed to facilitate algorithmic modifications and the addition of new analytical contexts. The framework was developed considering the 3GPP technical specifications related to data analytics. Its evaluation was performed through a use case focused on cybersecurity anomaly detection applied to a 5G network core. The results demonstrated that the framework simplifies installation, increases flexibility for new algorithms, and integrates seamlessly into the 5G network core, effectively addressing previously identified shortcomings.

关键词： Analytical models Data analysis Machine learning algorithms 5G mobile communication Source coding Inspection 3GPP computer security Anomaly detection Application programming interfaces

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Distributed quantum architecture search

arXiv

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arXiv 2024年

作者： Situ, Haozhen He, Zhimin Zheng, Shenggen Li, Lvzhou College of Mathematics and Informatics South China Agricultural University Guangzhou510642 China School of Electronic and Information Engineering Foshan University Foshan528000 China Shenzhen518045 China Institute of Quantum Computing and Software School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China

Variational quantum algorithms, inspired by neural networks, have become a novel approach in quantum computing. However, designing efficient parameterized quantum circuits remains a challenge. Quantum architecture search tackles this by adjusting circuit structures along with gate parameters to automatically discover high-performance circuit structures. In this study, we propose an end-to-end distributed quantum architecture search framework, where we aim to automatically design distributed quantum circuit structures for interconnected quantum processing units with specific qubit connectivity. We devise a circuit generation algorithm which incorporates TeleGate and TeleData methods to enable nonlocal gate implementation across quantum processing units. While taking into account qubit connectivity, we also incorporate qubit assignment from logical to physical qubits within our quantum architecture search framework. A two-stage progressive training-free strategy is employed to evaluate extensive circuit structures without circuit training costs. Through numerical experiments on three VQE tasks, the efficacy and efficiency of our scheme is demonstrated. Our research into discovering efficient structures for distributed quantum circuits is crucial for near-term quantum computing where a single quantum processing unit has a limited number of qubits. Distributed quantum circuits allow for breaking down complex computations into manageable parts that can be processed across multiple quantum processing units. Copyright © 2024, The Authors. All rights reserved.

关键词： Qubits

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Flood Evacuation Route Recommendation Using Particle Swarm Optimization Algorithm

Flood Evacuation Route Recommendation Using Particle Swarm O...

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Information Technology and Computing (ICITCOM), International Conference on

作者： Ricky Mahendra Teuku Muh. Haedir M. Adnan Nur Nur Khaerat Nur Hazriani Dept. of Informatics Handayani University of Makassar Makassar Indonesia Dept. of Civil Engineering Fajar University Makassar Indonesia Dept. of Computer System Handayani University of Makassar Makassar Indonesia

Equipping the society with an evacuation route assistant is important as a preventive action in order to minimize anxiety as well as number of victims when disaster strike. Therefore, research on best route determination to the shelter is a noble task. Evacuation routes mean routes to pass in order to reach the gathering point or shelter safely. This study aims to implement the particle swarm optimization (PSO) algorithm in finding the optimal path to the designated shelter. PSO is a metaheuristic algorithm inspired by the behaviour of flocks of birds or fish to optimize the search for the best route. Taking into account the details of the PSO implementation, including initialization of the random particle position and velocity, selection of the best particle (Pbest) and Global Best (Gbest), and updating the speed and position of the particle using the specified formula. The objective function is recalculated based on the total distance of the particle route as well as the condition weight of the affected areas. The results showed that out of ten experiments with 100 iterations, six valid routes were found with the highest fitness value of 1,935, which indicates that PSO can provide optimal solutions in the context of finding flood evacuation routes.

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Implementation of Artificial Ant Colony Algorithm (AACA) in dynamic labyrinth generation for android-based 2D games

Implementation of Artificial Ant Colony Algorithm (AACA) in ...

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2019 International Conference on Science Education and Technology, ICOSETH 2019

作者： Herumurti, Darlis Kuswardayan, Imam Khotimah, Wijayanti Nurul Yunanto, Andhik Ampuh Yusuf, Andi Akram Department of Informatics Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Informatics and Computer Engineering Politeknik Elektronika Negeri Surabaya Indonesia

Playing games can make people feel fun. Players can be more fun if you have a lot of variations, for example, variations of items, maps, or enemies. Map variations can be fulfilled by implementing a dynamic labyrinth generator. In this research, the game has a feature called Dynamic labyrinth generation using the Artificial Ant Colony Algorithm (AACA) method. For deployment, this game is implemented on the Android mobile platform. The evaluation is conducted by testing functionality in system games. The result indicates AACA can generate dynamic mazes and with optimal time with less than five seconds. So, the conclusion from this research that the AACA method can generate dynamic labyrinth quickly and well for Android Game. © Published under licence by IOP Publishing Ltd.

关键词： Android (operating system)

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Wheelchair Wheel Design with Transformable “Wheel-Leg” Configuration for Climbing Stairs and Various Surfaces

Wheelchair Wheel Design with Transformable “Wheel-Leg” Con...

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International Russian Smart Industry Conference (SmartIndustryCon)

作者： Islam Magomedov Timur Aygumov Anzor A. Kanametov Bissnes informatics Kadyrov Chechen state university Grozny Russia Department of software engineering computer technology and automated systems Dagestan State Technical University Dagestan Russia Department of Electronics and Digital Information Technologies Kabardino-Balkarian State University Nalchik Russia

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

The dynamic and uneven terrain of our environment introduces complexity for locomotion vehicles to navigate easily across different settings. Wheelchairs belong to the category of vehicles that require locomotion across various uneven terrains, such as stairs and other partitions. Therefore, the aim of this work is to design a wheel that can travel through various environments without using complex mechanisms. This aim was achieved by creating a novel transformable wheel. This wheel can turn into a legged wheel without using a complex mechanism and, when unnecessary, transform back into a normal wheel. Several simulations were carried out to understand the design's capability to overcome obstacles. In this case, the stair was the obstacle, and the results illustrated that the wheel is capable of climbing stairs without serious issues. Different parameters, such as speed and force, were examined with various values. The results showed that the weight on the wheelchair plays a significant role in climbing. For instance, with lighter weight, the structure moves without major slipping. The roughness of the surface is also related to the wheelchair's ability to reach the top of the stairs. A finer depth of cuts on the surface of the stairs increases the chance of the legged wheel firmly gripping and moving up the stairs.

关键词： Shape Navigation Wheelchairs Wheels Rotors Transforms Stairs Surface roughness Rough surfaces Vehicle dynamics

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Image Retargeting Techniques Identification Using Supervised Deep Learning

Image Retargeting Techniques Identification Using Supervised...

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Intelligent Data Science Technologies and Applications (IDSTA), International Conference on

作者： Ruba Kharsa Rouaa Alzoubi Mohammad Alsmirat Mahmoud Al-Ayyoub Department of Computer Science College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates Artificial Intelligence Research Center (AIRC) College of Engineering and Information Technology Ajman University Ajaman UAE

Image retargeting involves the adjustment of an image's dimensions to ensure that its content and visual quality are preserved when the image is resized to fit various screens or devices. This process retains all essential visual elements and details. Different techniques have been developed for this purpose, including cropping (CR), scaling (SCL), seam carving (SC), warping (WARP), scale-and-stretch (SNS), multi-operator (MULTI), and shift-map (SM). However, determining the most suitable method for retargeting a specific image with particular dimensions remains a challenge. Therefore, this research introduces initial work on developing CNN based deep learning model and a transfer learning model based on InceptionV3,to predict the optimal retargeting method for a given image and resolution. The study employed a dataset consisting of 46,716 images with varying resolutions, created using different retargeting techniques, categorized into six groups. Results demonstrates a promising effectiveness of the proposed approach for selecting the appropriate retargeting techniques.

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