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arXiv 2023年

作者： Zhou, Junpeng Zhang, Na Li, Qia School of Computer Sciences and Engineering Sun Yat-Sen University Guangzhou510006 China Department of Applied Mathematics College of Mathematics and Informatics South China Agricultural University Guangzhou510642 China School of Computer Sciences and Engineering Guangdong Province Key Laboratory of Computational Science Sun Yat-Sen University Guangzhou510006 China

In this paper, we consider a class of structured fractional programs, where the numerator part is the sum of a block-separable (possibly nonsmooth nonconvex) function and a locally Lipschitz differentiable (possibly nonconvex) function, while the denominator is a convex (possibly nonsmooth) function. We first present a novel reformulation for the original problem and show the relationship between optimal solutions, critical points and KL exponents of these two problems. Inspired by the reformulation, we propose a flexible framework of multi-proximity gradient algorithms (MPGA), which computes the proximity operator with respect to the Fenchel conjugate associated with the convex denominator of the original problem rather than evaluating its subgradient as in the existing methods. Also, MPGA employs a nonmonotone linear-search scheme in its gradient descent step, since the smooth part in the numerator of the original problem is not globally Lipschitz differentiable. Based on the framework of MPGA, we develop two specific algorithms, namely, cyclic MPGA and randomized MPGA, and establish their subsequential convergence under mild conditions. Moreover, the sequential convergence of cyclic MPGA with the monotone line-search (CMPGA ML) is guaranteed if the extended objective associated with the reformulated problem satisfies the Kurdyka-Lojasiewicz (KL) property and some other mild assumptions. In particular, we prove that the corresponding KL exponents are 12 for several special cases of the fractional programs, and so, CMPGA ML exhibits a linear convergence rate. Finally, some preliminary numerical experiments are performed to demonstrate the efficiency of our proposed algorithms. Copyright © 2023, The Authors. All rights reserved.

关键词： Gradient methods

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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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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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Adrias: Interference-Aware Memory Orchestration for Disaggregated Cloud Infrastructures

Adrias: Interference-Aware Memory Orchestration for Disaggre...

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IEEE Symposium on High-Performance computer Architecture

作者： Dimosthenis Masouros Christian Pinto Michele Gazzetti Sotirios Xydis Dimitrios Soudris Microprocessors and Digital Systems Laboratory School of Electrical and Computer Engineering National Technical University of Athens Greece IBM Research Europe Dublin Ireland Department of Informatics and Telematics Harokopio University of Athens Greece

Workload co-location has become the de-facto approach for hosting applications in Cloud environments, leading, however, to interference and fragmentation in shared resources of the system. To this end, hardware disaggregation is introduced as a novel paradigm, that allows fine-grained tailoring of cloud resources to the characteristics of the deployed applications. Towards the realization of hardware disaggregated clouds, novel orchestration frameworks must provide additional knobs to manage the increased scheduling *** present Adrias, a memory orchestration framework for disaggregated cloud systems. Adrias exploits information from low-level performance events and applies deep learning techniques to effectively predict the system state and performance of arriving workloads on memory disaggregated systems, thus, driving cognitive scheduling between local and remote memory allocation modes. We evaluate Adrias on a state-of-art disaggregated testbed and show that it achieves 0.99 and 0.942 R 2 score for system state and application’s performance prediction on average respectively. Moreover, Adrias manages to effectively utilize disaggregated memory, by offloading almost 1/3 of deployed applications with less than 15% performance overhead compared to a conventional local memory scheduling, while clearly outperforms naive scheduling approaches (random and round-robin), by providing up to ×2 better performance.

关键词： Deep learning Memory management Interference Hardware Resource management

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Communicative Robot Signals: Presenting a New Typology for Human-Robot Interaction

arXiv

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arXiv 2023年

作者： Holthaus, Patrick Schulz, Trenton Lakatos, Gabriella Soma, Rebekka University of Hertfordshire School of Physics Engineering and Computer Science Hatfield United Kingdom Norwegian Computing Center Department of Applied Research in ICT Oslo Norway University of Oslo Department of Informatics Oslo Norway

We present a new typology for classifying signals from robots when they communicate with humans. For inspiration, we use ethology, the study of animal behaviour and previous efforts from literature as guides in defining the typology. The typology is based on communicative signals that consist of five properties: the origin where the signal comes from, the deliberateness of the signal, the signal’s reference, the genuineness of the signal, and its clarity (i.e., how implicit or explicit it is). Using the accompanying worksheet, the typology is straightforward to use to examine communicative signals from previous human-robot interactions and provides guidance for designers to use the typology when designing new robot behaviours. © 2023, CC BY.

关键词： Human robot interaction

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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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A novel approach combined transfer learning and deep learning to predict TMB from histology image

引用

Pattern Recognition Letters 2020年 135卷 244-248页

作者： Wang, Liansheng Jiao, Yudi Qiao, Ying Zeng, Nianyin Yu, Rongshan Department of Computer Science School of Informatics Xiamen University Fujian361005 China School of Informatics Xiamen University Fujian361005 China Department of Instrumental and Electrical Engineering Xiamen University Fujian361005 China

Tumor Mutation Burden(TMB) is a quantifiable clinical indicator that can be used to predict the responses to immunotherapy of a range of tumors. However, the current DNA sequencing-based TMB measurement method represented by Whole Exome Sequencing (WES) is expensive and time-consuming, which limits its utilization in clinical practice. In this paper, we design a method through deep learning in order to predict TMB from available H&E stained whole slide images of gastrointestinal cancer. Experimental results demonstrate that our approach is capable of distinguishing high and low TMB with an AUC higher than 0.75. We further performed post-processing to improve the accuracy on both test sets to above 0.7 (0.71 accuracy for TMB-STAD and 0.77 accuracy for TMB-COAD-DX). Furthermore, the predicted low and high TMB patients with gastric and colon cancer have different survival rates, with p values of 0.348 and 0.8113, respectively, which indicates that our study is potentially helpful for practical treatment. © 2020 Elsevier B.V.

关键词： Tumors

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Custom-made Near Infrared Spectroscope as a Tool for Obtaining Information Regarding the Brain Condition

Custom-made Near Infrared Spectroscope as a Tool for Obtaini...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Anna Wieczorek Edward Jacek Gorzelańczyk Mariusz Pelc Saravanakumar Duraisamy Luis A. Leiva Aleksandra Kawala-Sterniuk Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Institute of Philosophy Kazimierz Wielki University Bydgoszcz Poland Department of Computer Science University of Luxembourg Luxembourg Luxembourg

We can obtain valuable information about the human brain using functional Near Infrared Spectroscopy (fNIRS). This paper describes the theoretical basis associated with this neuroimaging method through a custom-made prototype of a single-channel fNIRS device. The optodes were soldered to a milled Printed Circuit Board (PCB) and enclosed in a 3D printed housing. Using this fNIRS device, we performed a preliminary study to measure emotional responses from participants. Our results suggest that fNIRS allows for accurate measurement of emotions evoked by positive and negative images.

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