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Advancing cancer diagnosis and prognostication through deep learning mastery in breast, colon, and lung histopathology with ResoMergeNet

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computers in Biology and Medicine 2025年 185卷 109494-109494页

作者： Ejiyi, Chukwuebuka Joseph Qin, Zhen Agbesi, Victor K. Yi, Ding Atwereboannah, Abena A. Chikwendu, Ijeoma A. Bamisile, Oluwatoyosi F. Bakanina Kissanga, Grace-Mercure Bamisile, Olusola O. College of Nuclear Technology and Automation Engineering & Sichuan Industrial Internet Intelligent Monitoring and Application Engineering Research Center Chengdu University of Technology Sichuan Chengdu China Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Sichuan Chengdu China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Life Science University of Electronic Science and Technology of China Chengdu China

Cancer, a global health threat, demands effective diagnostic solutions to combat its impact on public health, particularly for breast, colon, and lung cancers. Early and accurate diagnosis is essential for successful treatment, prompting the rise of computer-Aided Diagnosis Systems as reliable and cost-effective tools. Histopathology, renowned for its precision in cancer imaging, has become pivotal in the diagnostic landscape of breast, colon, and lung cancers. However, while deep learning models have been widely explored in this domain, they often face challenges in generalizing to diverse clinical settings and in efficiently capturing both local and global feature representations, particularly for multi-class tasks. This underscores the need for models that can reduce biases, improve diagnostic accuracy, and minimize error susceptibility in cancer classification tasks. To this end, we introduce ResoMergeNet (RMN), an advanced deep-learning model designed for both multi-class and binary cancer classification using histopathological images of breast, colon, and lung. ResoMergeNet integrates the Resboost mechanism which enhances feature representation, and the ConvmergeNet mechanism which optimizes feature extraction, leading to improved diagnostic accuracy. Comparative evaluations against state-of-the-art models show ResoMergeNet's superior performance. Validated on the LC-25000 and BreakHis (400× and 40× magnifications) datasets, ResoMergeNet demonstrates outstanding performance, achieving perfect scores of 100 % in accuracy, sensitivity, precision, and F1 score for binary classification. For multi-class classification with five classes from the LC25000 dataset, it maintains an impressive 99.96 % across all performance metrics. When applied to the BreakHis dataset, ResoMergeNet achieved 99.87 % accuracy, 99.75 % sensitivity, 99.78 % precision, and 99.77 % F1 score at 400× magnification. At 40× magnification, it still delivered robust results with 98.85 % accuracy,

关键词： Lung cancer

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A load adaptive IEEE 802.11e EDCA backoff scheme with enhanced service differentiation

A load adaptive IEEE 802.11e EDCA backoff scheme with enhanc...

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2010 IEEE 12th International Conference on Communication Technology, ICCT'2010

作者： Dong, Yongqiang Wang, Yun Xia, Qin School of Computer Science and Engineering Southeast University Nanjing 210096 China Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education Nanjing 210096 China

ISBN: (纸本)9781424468690

In view of the disadvantages of IEEE 802.11e EDCA in QoS guarantee and collision avoidance, an enhanced EDCA scheme called SD-AEDCA is presented which dynamically adjusts two EDCA parameters, namely contention window (CW) and backoff time counter (BC), according to channel load conditions and QoS requirements of network services. SD-AEDCA makes improvements to EDCA backoff scheme from post-backoff, upon-collision and post-transmission phases respectively by differentiating real-time and non real-time frames. Specifically, frozen rate is calculated to estimate the channel load conditions during EDCA backoff process and then used to guide CW and BC adjustment. And the waiting time is explored deliberately to satisfy the transmission latency requirements of real-time frames. Simulation results show that SD-AEDCA improves network throughput by reducing transmission collisions and provides more satisfactory QoS to real-time services at heavy load conditions. © 2010 IEEE.

关键词： Quality of service

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A Meta Meeting Mountain based opportunistic message forwarding strategy

A Meta Meeting Mountain based opportunistic message forwardi...

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作者： Tu, Jinbin Wang, Yun Liu, Yichuan Li, Qing School of Computer Science and Engineering Southeast University Nanjing China Key Lab of Computer Network and Information Integration MOE Nanjing China

The opportunistic network is a type of ad hoc network that relies on the chance encounters between nodes to transmit messages. It also uses store-and-carry-forward techniques for data transfer between nodes. Developing effective message forwarding strategies based on opportunistic network characteristics and node behavior poses a significant challenge. In this paper, we delve into the mobility and social characteristics of nodes using historical encounter information. Furthermore, we calculate the migration degree and community relations to build the Meta Meeting Mountain, which representing node encounter characteristics. Moreover, we introduce the concept of Forwarding Degree to measure the nodes’ ability to deliver messages, enhancing the predictability of message delivery. Furthermore, a new forwarding strategy is proposed, which is equipped with Meta Meeting Mountain and Forwarding degree to improve the delivery rate. Our experimental scenarios include Infocom06, Rome taxi, and Helsinki. Therefore, the impact of buffer size and TTL is discussed in detail regarding the different opportunistic routing algorithms. Finally, extensive experimental results show that the proposed algorithm outperforms UBPR, MaxProp, PRoPHET, Spray And Wait and RAPAR in terms of delivery rate in the above scenarios by 127.905%, 93.7525%, 138.6888%, 175.3663%, and 281.4625%, respectively, while keeping the hopcount value less than 5. © 2023 Elsevier B.V.

关键词： Data transfer

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Ubicast: An enhanced application-level multicast protocol

Ubicast: An enhanced application-level multicast protocol

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6th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2005

作者： Chu, Zi Yang, Yin-Yin Tu, Hao Kong, Wei-Ning Department of Computer Science and Engineering Southeast University Nanjing 210096 China Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University Nanjing 210096 China

ISBN: (纸本)0769524052

This paper presents Ubicast, an enhanced application-level multicast protocol. Ubicast is built upon Pastry, a scalable and self-organizing peer-to-peer substrate overlay, and leverages its merits of reliable application-level routing and object location. Ubicast is mainly applied to such real-time multimedia applications with QoS heterogeneousness as multimedia streaming service, video-on-demand. The paper makes two contributions to the study of application-level multicast: (1) Ubicast extends traditional degree-bound model and satisfies nodes' heterogeneous QoS requirements to provide customizable multicast services. It tries to minimize the delay radius of the multicast tree, while meeting different bandwidth requirements. (2) Priority Joining Algorithm is proposed to limit the number of nodes that a participant needs to probe. The join cost is decreased substantially to guarantee the scalability for a potentially large network topology. Simulation and experimental analysis confirm the performance improvement of Ubicast which is especially suited for small sized multicast groups. © 2005 IEEE.

关键词： network protocols

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Reliable task allocation with load balancing in multiplex networks

Reliable task allocation with load balancing in multiplex ne...

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作者： Jiang, Yichuan Zhou, Yifeng Li, Yunpeng School of Computer Science and Engineering Southeast University Nanjing211189 China Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education Nanjing211189 China

In multiplex networks, agents are connected by multiple types of links;a multiplex network can be split into more than one network layer that is composed of the same type of links and involved agents. Each network link type has a bias for communicating different types of resources;thus, the task's access to the required resources in multiplex networks is strongly related to the network link types. However, traditional task allocation and load balancing methods only considered the situations of agents themselves and did not address the effects of network link types in multiplex networks. To solve this problem, this article considers both link types and agents, and substantially extends the existing work by highlighting the effect of network layers on task allocation and load balancing. Two multiplex network-adapted models of task allocation with load balancing are presented: network layer-oriented allocation and agent-oriented allocation. This article also addresses the unreliability in multiplex networks, which includes the unreliable links and agents, and implements a reliable task allocation based on a negotiation reputation and reward mechanism. Our findings show that both of our presented models can effectively and robustly satisfy the task allocation objectives in unreliable multiplex networks;the experiments prove that they can significantly reduce the time costs and improve the success rate of tasks for multiplex networks over the traditional simplex network-adapted task allocation model. Lastly, we find that our presented network layer-oriented allocation performs much better in terms of reliability and allocation time compared to our presented agent-oriented allocation, which further explains the importance of network layers in multiplex networks. © 2015 ACM.

关键词： network layers

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Fiber-based quantum secure direct communication without active polarization compensation

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Science China(Physics,Mechanics & Astronomy) 2022年第12期65卷 91-96页

作者： Xin Liu Di Luo Guangshen Lin Zihao Chen Chunfeng Huang Shizhuo Li Chengxian Zhang Zhenrong Zhang Kejin Wei Guangxi Key Laboratory for Relativistic Astrophysics School of Physical Science and TechnologyGuangxi UniversityNanning530004China Guangxi Key Laboratory of Multimedia Communications and Network Technology School of ComputerElectronicsand InformationGuangxi UniversityNanning530004China

Quantum secure direct communication(QSDC)that allows people to directly transmit confidential information through insecure channels is an important branch of quantum *** widespread adoption of the QSDC demands the development of simple and stable ***,most of the existent QSDC systems involve a complex self-alignment process at the initial stage and additional hardware to compensate environmental *** this study,we present a fiber-based QSDC system without active polarization *** system comprises a stable transmitter and a novel Sagnac-Mach-Zehnder interferometer for security *** robust system simplifies the self-alignment and is immune to environmental *** robustness of the system was theoretically and experimentally verified,and low bit error rates in a 12 min continuous operation with an active polarization scrambler were *** addition,we performed a proof-of-principle QSDC demonstration,and a secrecy capacity of 3.43 kbps over a 5 km fiber with a detection bit error rate of 0.85%±0.07%and a quantum bit error rate of 0.42%±0.05%were *** results confirm the viability of the proposed QSDC system for practical applications.

关键词： quantum secure direct communication Sagnac-Mach-Zehnder interferometer without active polarization compensation

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Funny words detection via Contrastive Representations and Pre-trained Language Model 2

Funny words detection via Contrastive Representations and Pr...

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2nd International Seminar on Artificial Intelligence, networking and information Technology, AINIT 2021

作者： Du, Yiming Tian, Zelin Key Lab of Computer Network and Information Integration Nanjing China University of British Columbia Dept. Computer Science Vancouver Canada

ISBN: (纸本)9781665412964

Funniness detection of news headlines is a challenging task in computational linguistics. However, most existing works on funniness detection mainly tackle the scenario by simply judging whether a sentence is humorous, whose result is unstable due to factors such as sentence length. To solve this issue, in this paper, our idea is to fine-grained mine the detailed information of the words and the contextual relationship between different words in the sentence, which help to evaluate the correlation between keywords and the funniness of news headlines quantitatively. Specifically, we propose a funny words detection algorithm based on the contrastive representations learning and BERT model. To quantify the impact of different words on the degree of humor, we first subtract the funniness grades of the original news headlines and the funniness grades of the original news headlines with a single word replaced. Both funniness grades are predicted with a pre-trained model, which is supervised by a a threshold to limit the amount of data and ensure the validity of data. To ensure the accuracy of our prediction, we further introduce the contrastive learning to constrain the differences of news headlines before and after word replacement. Finally, according to the Root Mean Square Error (RMSE) matrix in our experiment, we develop a BERT model with mixed sequence embedding to generate a table about words and their corresponding funniness improvement about the news headlines. © 2021 IEEE.

关键词： Mean square error

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FPGA based unified architecture for public key and private key cryptosystems

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Frontiers of computer Science 2013年第3期7卷 307-316页

作者： Yi WANG Renfa LI Embedded Systems and Networking Laboratory Hunan Province Key Laboratory of Network and Information Security Hunan University Changsha 410082 China Department of Electrical and Computer Engineering National University of Singapore Singapore 117576 Singapore

Recently, security in embedded system arises attentions because of modern electronic devices need cau- tiously either exchange or communicate with the sensitive data. Although security is classical research topic in world- wide communication, the researchers still face the problems of how to deal with these resource constraint devices and en- hance the features of assurance and certification. Therefore, some computations of cryptographic algorithms are built on hardware platforms, such as field program gate arrays （FPGAs）. The commonly used cryptographic algorithms for digital signature algorithm （DSA） are rivest-shamir-adleman （RSA） and elliptic curve cryptosystems （ECC） which based on the presumed difficulty of factoring large integers and the algebraic structure of elliptic curves over finite fields. Usu- ally, RSA is computed over GF（p）, and ECC is computed over GF（p） or GF（2P）. Moreover, embedded applications need advance encryption standard （AES） algorithms to pro- cess encryption and decryption procedures. In order to reuse the hardware resources and meet the trade-off between area and performance, we proposed a new triple functional arith- metic unit for computing high radix RSA and ECC operations over GF（p） and GF（2P）, which also can be extended to support AES operations. A new high radix signed digital （SD） adder has been proposed to eliminate the carry propagations over GF（p）. The proposed unified design took up 28.7% less hardware resources than implementing RSA, ECC, and AES individually, and the experimental results show that our proposed architecture can achieve 141.8 MHz using approxi- mately 5.5k CLBs on Virtex-5 FPGA.

关键词： AES RSA ECC signed-digit number FPGA cryptographic algorithms high radix arithmetic unit

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Link prediction in complex networks via modularity-based belief propagation

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Chinese Physics B 2017年第3期26卷 604-614页

作者：赖大荣舒欣 Christine Nardini School of Computer Science and Engineering Southeast University Nanjing 211189 China Key Laboratory of Computer Network and Information Integration of Ministry of Education Southeast University Nanjing 210096 China College of Information Science and Technology Nanjing Agricultural University Nanjing 210095 China CNR-IAC 'Mauro Picone' Via dei Taurini 19 00185 Roma Italy Personalgenomics Via delle Grazie Verona Italy

Link prediction aims at detecting missing, spurious or evolving links in a network, based on the topological information and/or nodes＇ attributes of the network. Under the assumption that the likelihood of the existence of a link between two nodes can be captured by nodes＇ similarity, several methods have been proposed to compute similarity directly or indirectly, with information on node degree. However, correctly predicting links is also crucial in revealing the link formation mechanisms and thus in providing more accurate modeling for networks. We here propose a novel method to predict links by incorporating stochastic-block-model link generating mechanisms with node degree. The proposed method first recov- ers the underlying block structure of a network by modularity-based belief propagation, and based on the recovered block structural information it models the link likelihood between two nodes to match the degree sequence of the network. Experiments on a set of real-world networks and synthetic networks generated by stochastic block model show that our proposed method is effective in detecting missing, spurious or evolving links of networks that can be well modeled by a stochastic block model. This approach efficiently complements the toolbox for complex network analysis, offering a novel tool to model links in stochastic block model networks that are fundamental in the modeling of real world complex networks.

关键词： link prediction complex network belief propagation modularity

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A cost-efficient quantum access network with qubit-based synchronization

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Science China(Physics,Mechanics & Astronomy) 2024年第4期67卷 12-22页

作者： Chunfeng Huang Ye Chen Tingting Luo Wenjie He Xin Liu Zhenrong Zhang Kejin Wei Guangxi Key Laboratory for Relativistic Astrophysics School of Physical Science and TechnologyGuangxi UniversityNanning 530004China Guangxi Key Laboratory of Multimedia Communications and Network Technology School of Computer Electronics and InformationGuangxi UniversityNanning 530004China

Quantum key distribution(QKD)is a physical layer encryption technique that enables two distant parties to exchange secure keys with information-theoretic *** the last two decades,QKD has transitioned from laboratory research to real-world applications,including multi-user quantum access networks(QANs).This network structure allows users to share a single-photon detector at a network node through time-division multiplexing,thereby significantly reducing the network ***,current QAN implementations require additional hardware for auxiliary tasks such as time *** address this issue,we propose a cost-efficient QAN that uses qubit-based *** this approach,the transmitted qubits facilitate time synchronization,eliminating the need for additional synchronization *** tested our scheme by implementing a network for two users and successfully achieved average secure key rates of 53.84 kbps and 71.90 kbps for each user over a 50-km commercial fiber *** addition,we investigated the capacity of the access network under cross-talk and loss *** simulation results demonstrate that this scheme can support a QAN with 64 users with key rates up to 1070 *** work provides a feasible and cost-effective way to implement a multi-user QKD network,further promoting the widespread application of QKD.

关键词： quantum key distribution quantum access network qubit-based synchronization

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