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2025 SIAM Symposium on Algorithm engineering and Experiments, ALENEX 2025

作者： García-Castellanos, Alejandro Medbouhi, Aniss Aiman Marchetti, Giovanni Luca Bekkers, Erik J. Kragic, Danica Amsterdam Machine Learning Lab University of Amsterdam Netherlands School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden School of Engineering Sciences KTH Royal Institute of Technology Sweden

ISBN: (纸本)9798331311995

We propose HyperSteiner – an efficient heuristic algorithm for computing Steiner minimal trees in the hyperbolic space. HyperSteiner extends the Euclidean Smith-Lee-Liebman algorithm, which is grounded in a divide-and-conquer approach involving the Delaunay triangulation. The central idea is rephrasing Steiner tree problems with three terminals as a system of equations in the Klein-Beltrami model. Motivated by the fact that hyperbolic geometry is well-suited for representing hierarchies, we explore applications to hierarchy discovery in data. Results show that HyperSteiner infers more realistic hierarchies than the Minimum Spanning Tree and is more scalable to large datasets than Neighbor Joining. Copyright © 2025 by SIAM.

关键词： Trees (mathematics)

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Empowering Semantic Segmentation with Selective Frequency Enhancement and Attention Mechanism for Tampering Detection

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第6期5卷 3270-3283页

作者： Xu, Xu Lv, Wenrui Wang, Wei Zhang, Yushu Chen, Junxin Dalian University of Technology School of Software Dalian116621 China Northeastern University School of Computer Science and Engineering Shenyang110004 China Shenzhen MSU-BIT University Guangdong-Hong Kong-Macao Joint Laboratory for Emotion Intelligence and Pervasive Computing Artificial Intelligence Research Institute Shenzhen518172 China Beijing Institute of Technology School of Medical Technology Beijing100081 China Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing210016 China

Nowadays, massive amounts of multimedia contents are exchanged in our daily life, while tampered images are also flooding the social networks. Tampering detection is therefore becoming increasingly important for multimedia integrity, and it is generally realized by designing specific convolutional neural networks. From a new perspective, this article proposes two pluggable modules for empowering existing semantic segmentation models for tampering detection. First, a selective frequency enhancement (SFE) module is developed to suppress the semantic information and selectively enhance the tamper information. Second, a boundary enhanced attention (BEA) module is designed to highlight the edge information of tempered area. Our SFE and BEA modules are combined with five mainstream semantic segmentation networks for performance evaluation. The experiment results demonstrate that our modules are able to empower the semantic segmentation networks for tampering detection, and their combinations even perform better than state-of-the-art algorithms in certain datasets. © 2020 IEEE.

关键词： Semantics

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A Secure Multi-factor Authentication Protocol for Healthcare Services Using Cloud-based SDN

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computers, Materials & Continua 2023年第2期74卷 3711-3726页

作者： Sugandhi Midha Sahil Verma Kavita Mohit Mittal Nz Jhanjhi Mehedi Masud Mohammed A.AlZain Department of Computer Science and Engineering Chandigarh UniversityMohali140413India Chandigarh Engineering College Jhanjeri Mohali140307India School of Computer Science and Engineering SCETaylor’s UniversitySubang Jaya47500Malaysia FITTaylor’s UniversitySubang Jaya47500Malaysia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Cloud-based SDN(Software Defined Network)integration offers new kinds of agility,flexibility,automation,and speed in the *** and Cloud providers both leverage the benefits as networks can be configured and optimized based on the application *** integration of cloud and SDN paradigms has played an indispensable role in improving ubiquitous health care *** has improved the real-time monitoring of patients by medical ***’data get stored at the central server on the cloud from where it is available to medical practitioners in no *** centralisation of data on the server makes it more vulnerable to malicious attacks and causes a major threat to patients’*** recent days,several schemes have been proposed to ensure the safety of patients’*** most of the techniques still lack the practical implementation and safety of *** this paper,a secure multi-factor authentication protocol using a hash function has been ***(Body Area Network)logic has been used to formally analyse the proposed scheme and ensure that no unauthenticated user can steal sensitivepatient *** Protocol Animator(SPAN)–Automated Validation of Internet Security Protocols and Applications(AVISPA)tool has been used for *** results prove that the proposed scheme ensures secure access to the database in terms of spoofing and *** comparisons of the proposed scheme with other related historical schemes regarding time complexity,computation cost which accounts to only 423 ms in proposed,and security parameters such as identification and spoofing prove its efficiency.

关键词： Multi-factor authentication hash function BAN logic SPANAVISPA

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Amine-functionalized hierarchically porous carbon supported Pd nanocatalysts for highly efficient H2 generation from formic acid with fast-diffusion channels

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Journal of Energy Chemistry 2023年第1期76卷 249-258,I0007页

作者： Xianzhao Shao Xinyi Miao Fengwu Tian Miaomiao Bai Xiaosha Guo Wei Wang Zuoping Zhao Xiaohui Ji Miyi Li Fangan Deng Shaanxi Key Laboratory of Catalysis School of Chemistry and Environment ScienceShanxi University of TechnologyHanzhong 723001ShaanxiChina School of Mathematics and Computer Science Shanxi University of TechnologyHanzhong 723001ShaanxiChina State Key Laboratory of Qinba Bio-Resource and Ecological Environment Shaanxi University of TechnologyHanzhong 723001ShaanxiChina School of Chemistry and Chemical Engineering Beijing Institute of TechnologyBeijing 102488China

Formic acid(FA)has come to be considered a potential candidate for hydrogen storage,and the development of efficient catalysts for H2releasing is crucial for realizing the sustainable process from ***,we have developed the ultrafine Pd nanoparticle(NPs)with amine-functionalized carbon as a support,which was found to show an excellent catalytic activity in H_(2)generation from FA *** synergetic mechanism between amine-group and Pd active site was demonstrated to facilitate H2generation byβ-hydride ***,the texture of support for Pd NPs also plays an important role in determining the reactivity of FA,since the diffusion of gaseous products makes the kinetics of diffusion as a challenge in this high performance Pd *** a result,the as-prepared Pd/NH_(2)-TPC catalyst with the small sized Pd nanoparticles and the hierarchically porous structures shows a turnover of frequency(TOF)value of 4312 h^(-1)for the additive-free FA dehydrogenation at room temperature,which is comparable to the most promising heterogeneous *** results demonstrated that the intrinsic catalytic activities of active site as well as the porous structure of support are both important factors in determining catalytic performances in H2generation from FA dehydrogenation,which is also helpful to develop high-activity catalysts for other advanced gas-liquid-solid reactions systems.

关键词： Hierarchically carbon Diffusion Formic acid Hydrogen production Palladium nanoparticles

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Seeing the World in Dots: A Machine Learning Adventure in Colorblind Perception

Seeing the World in Dots: A Machine Learning Adventure in Co...

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

作者： Rahman, Shah Rafatur Islam, Md Rashedul Chakrabortty, Aditya Hajee Mohammad Danesh Science and Technology University Department of Computer Science and Engineering Dinajpur5200 Bangladesh Deakin University School of Information Technology Melbourne Australia

ISBN: (纸本)9798331529765

Color is a vital communication element, conveying the message's meaning and differentiating the contents. Nevertheless, color vision deficit (CVD), called colorblindness, affects 8% of the global population. This impairment alters color perception, making reading and understanding the message difficult. This issue becomes increasingly significant with the expanding accessibility of multimedia content in digital environments, including web browsers, digital images, entertainment media, and social media. One of the methods of identifying CVD is the Ishihara Color-blind Test. Ishihara images consist of a red-green background and a hidden number. Color-blind persons won't recognize the number as they cannot recognize the red and green colors. Using color glasses or contact lenses this deficiency can be overcome. The main point is that there is no cure for this deficiency. This research explores machine learning's potential to overcome this challenge. We trained a neural network to detect and classify numbers from Ishihara images, successfully "passing"the test. With an impressive 96.42% accuracy, this technology offers promising hope for bridging the communication gap for colorblind individuals. © 2024 IEEE.

关键词： Color vision

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I $^{2}$ RNN: An Incremental and Interpretable Recurrent Neural Network for Encrypted Traffic Classification

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IEEE Transactions on Dependable and Secure Computing 2023年 1-14页

作者： Song, Zhuoxue Zhao, Ziming Zhang, Fan Xiong, Gang Cheng, Guang Zhao, Xinjie Guo, Shize Chen, Binbin College of Computer Science and Technology Zhejiang University Hangzhou China Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Science and Engineering Southeast University Nanjing China Information Systems Technology and Design Singapore University of Technology and Design Singapore

Traffic classification occupies a significant role in cybersecurity and network management. The widespread of encryption transmission protocols such as SSL/TLS has led to the dominance of deep learning based approaches. In cybersecurity, strong adversaries often complicate their strategies by constantly developing emerging attacks. Meanwhile, security practitioners desire to grasp the reasons for inference results. However, existing deep learning approaches lack efficient adaptation for incremental traffic types and often have less interpretability. In this paper, we propose I $^{2}$ RNN, an Incremental and Interpretable Recurrent Neural Network for encrypted traffic classification. The I $^{2}$ RNN proposes a novel propagation process to extract the sequence fingerprints from sessions with local robustness. Meanwhile, this proposal provides interpretability including time-series feature attribution and inter-class similarity portrait. Moreover, we design I $^{2}$ RNN in an incremental manner to adapt to emerging traffic types. The I $^{2}$ RNN only needs to train an additional set of parameters for the newly added traffic type rather than retraining the whole model with the entire dataset. Extensive experimental results show that our I $^{2}$ RNN can achieve remarkable performance in traffic classification, incremental learning, and model interpretability. Compared with other local interpretability methods, our I $^{2}$ RNN exhibits excellent stability, robustness, and effectiveness in the interpretation of network traffic data. IEEE

关键词： Cryptography

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Presentation Analysis of Reasoning Radio-Based Routing Protocols in Wireless Mesh Networks

Presentation Analysis of Reasoning Radio-Based Routing Proto...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Kumar, Ritesh Kharbas, Vikas Kumar Mehta, Deepak Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Application Jaipur India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350383348

Reasoning radio-based total routing protocols present a promising technique for permitting powerful conversation in wi-fi mesh networks. By using the spectrum sensing capabilities of Reasoning radio, routers can intelligently pick out and pick out spectrum assets to ahead records, thereby allowing for improved network throughput and reliability. In this paper, we carry out a comprehensive Presentation evaluation of routing protocols primarily based on Reasoning radio in wi-fi mesh networks. Mainly, we Presentation metrics including packet shipping fee, latency, jitter, and energy Presentation. We examine various routing protocols from an empirical and theoretical angle and speak about the strengths and weaknesses of every technique. Subsequently, our consequences provide insights into the capability advantages and tradeoffs of Reasoning radio-based routing protocols in wireless mesh networks, offering practical steerage to designers and engineers within the subject. © 2024 IEEE.

关键词： Consequences Engineers Networks Practical Reasoning Routing Spectrum

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Corruption Robust Dynamic Pricing in Liner Shipping under Capacity Constraint 40

Corruption Robust Dynamic Pricing in Liner Shipping under Ca...

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40th IEEE International Conference on Data engineering, ICDE 2024

作者： Hu, Yongyi Lit, Xueyan Wei, Xikai Shi, Yangguang Gao, Xiaofeng Chen, Guihai Shanghai Jiao Tong University MoE Key Lab of Artificial Intelligence Department of Computer Science and Engineering China School of Computer Science and Technology Shandong University China

ISBN: (纸本)9798350317152

The shipping industry has irreplaceable importance in international trade and commerce. How to dynamically price different containers has long been a hot topic due to its direct connection to the final revenue. Two critical observations have been made after a comprehensive survey within a top liner company, China Ocean Shipping Company (COSCO). (1) Each type of container carried on a liner ship has its maximum capacity. (2) The sales volume is occasionally subject to huge fluctuations due to rare uncontrollable factors, such as COVID. Based on the above two points and the liner routine's periodic nature, we model the dynamic pricing problem as an episodic MDP model integrating with both capacity constraints and adversarial corruption, named C3-MDP. To maximize the cumulative revenue in the C3-MDP setting, we propose a programming framework, Bonus-Exploration based Episodic Programming (BEEP). This framework can directly accommodate the linear programming algorithm to form the algorithm BEEP-LP, which provides the episode-wise greedy optimal strategy. Furthermore, a detailed regret analysis is provided, showing that BEEP-LP has a regret that is sublinear in the number of episodes. Combining deep techniques, we also present an approximation algorithm BEEP-DQN in the case of large state-action space to strike a balance between the running time and the performance. Abundant experiments based on real container sales data exhibit the rationality of C3-MDP and the effectiveness of BEEP. © 2024 IEEE.

关键词： Linear programming

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Prediction of the Caenorhabditis elegans body posture and strains

Prediction of the Caenorhabditis elegans body posture and st...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Chen, Weiyang Li, Ning Qufu Normal University School of Cyber Science and Engineering Qufu China Qilu University of Technology School of Computer Science and Technology Jinan China

ISBN: (纸本)9798350337488

Caenorhabditis elegans is a model organism with a simple and well-connected nervous system. Phenotype is the manifestation of nematodes in various environments, and the accurate extraction of phenotypes is of great significance for the study of locomotion behavior, physiological changes and life expectancy of C. elegans. Here, we propose an efficient, low-cost and automated nematode phenotypic feature extraction method based on shape mathematical representation and image processing technology, and combine with nematode movement models to analyze the movement differences of different strains. We also proposed a posture prediction model based on the mathematical representation of nematode shape and deep learning method (Time2vec-LSTM-Attention). Through the results of experiment, it can be seen that our method can achieve good performance. © 2023 IEEE.

关键词： Behavior analysis Caenorhabditis elegans Classification Posture prediction

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IoT Based Smart Framework Monitoring System for Power Station

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computers, Materials & Continua 2023年第3期74卷 6019-6037页

作者： Arodh Lal Karn Panneer Selvam Manickam R.Saravanan Roobaea Alroobaea Jasem Almotiri Sudhakar Sengan Department of Financial and Actuarial Mathematics School of ScienceXi’an Jiaotong-Liverpool UniversityChina Department of Electrical and Electronics Engineering Sona College of TechnologySalem636005Tamil NaduIndia Department of Computer Science and Engineering Vel Tech Multi Tech Dr RR Dr SR Engineering CollegeChennai600062Tamil NaduIndia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Computer Science and Engineering PSN College of Engineering and TechnologyTirunelveli627152Tamil NaduIndia

Power Station(PS)monitoring systems are becoming critical,ensuring electrical safety through early warning,and in the event of a PS fault,the power supply is quickly *** technologies are based on relays and don’t have a way to capture and store user data when there is a *** proposed framework is designed with the goal of providing smart environments for protecting electrical types of *** paper proposes an Internet of Things(IoT)-based Smart Framework(SF)for monitoring the Power Devices(PD)which are being used in power substations.A Real-Time Monitoring(RTM)system is proposed,and it uses a state-of-the-art smart IoT-based System on Chip(SoC)sensors,a Hybrid Prediction Model(HPM),and it is being used in Big Data Processing(BDP).The Cloud Server(CS)processes the data and does the data analytics by comparing it with the historical data already stored in the ***-Structural Query Language Mongo Data Base(MDB)is used to store Sensor Data(SD)from the *** proposed HPM combines the Density-Based Spatial Clustering of Applications with Noise(DBSCAN)-algorithm for Outlier Detection(OD)and the Random Forest(RF)classification algorithm for removing the outlier SD and providing Fault Detection(FD)when the PD isn’t *** suggested work is assessed and tested under various fault circumstances that happened in *** simulation outcome proves that the proposed model is effective in monitoring the smooth functioning of the ***,the suggested HPM has a higher Fault Prediction(FP)*** means that faults can be found earlier,early warning signals can be sent,and the power supply can be turned off quickly to ensure electrical safety.A powerful RTM and event warning system can also be built into the system before faults happen.

关键词： System-on-chip cloud server apache kafka apache strom NoSQL MongoDB

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