The evolution of edge computing has advanced the accessibility of E-health recommendation services, encompassing areas such as medical consultations, prescription guidance, and diagnostic assessments. Traditional meth...
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The evolution of edge computing has advanced the accessibility of E-health recommendation services, encompassing areas such as medical consultations, prescription guidance, and diagnostic assessments. Traditional methodologies predominantly utilize centralized recommendations, relying on servers to store client data and dispatch advice to ***, these conventional approaches raise significant concerns regarding data privacy and often result in computational inefficiencies. E-health recommendation services, distinct from other recommendation domains, demand not only precise and swift analyses but also a stringent adherence to privacy safeguards, given the users' reluctance to disclose their identities or health information. In response to these challenges, we explore a new paradigm called on-device recommendation tailored to E-health diagnostics, where diagnostic support(such as biomedical image diagnostics), is computed at the client *** leverage the advances of federated learning to deploy deep learning models capable of delivering expert-level diagnostic suggestions on clients. However, existing federated learning frameworks often deploy a singular model across all edge devices, overlooking their heterogeneous computational capabilities. In this work, we propose an adaptive federated learning framework utilizing BlockNets, a modular design rooted in the layers of deep neural networks, for diagnostic recommendation across heterogeneous devices. Our framework offers the flexibility for users to adjust local model configurations according to their device's computational power. To further handle the capacity skewness of edge devices, we develop a data-free knowledge distillation mechanism to ensure synchronized parameters of local models with the global model, enhancing the overall accuracy. Through comprehensive experiments across five real-world datasets, against six baseline models, within six experimental setups, and various data distribution scenario
Cervical cancer is a type of cancer in which abnormal cell growth occurs on the surface lining of the cervix. In this study, we propose a novel residual deep convolutional generative adversarial network (RES_DCGAN) fo...
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As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention...
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As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention on privacy-preserving model explanations. This article presents the first thorough survey about privacy attacks on model explanations and their countermeasures. Our contribution to this field comprises a thorough analysis of research papers with a connected taxonomy that facilitates the categorization of privacy attacks and countermeasures based on the targeted explanations. This work also includes an initial investigation into the causes of privacy leaks. Finally, we discuss unresolved issues and prospective research directions uncovered in our analysis. This survey aims to be a valuable resource for the research community and offers clear insights for those new to this domain. To support ongoing research, we have established an online resource repository, which will be continuously updated with new and relevant findings.
Red blood cell (RBC) counts and identification must be done accurately to diagnose various illnesses. Although there are drawbacks to automated image analysis methods compared to hand counting, they include difference...
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In the digital era, the escalation of data generation and cyber threats has heightened the importance of network security. Machine Learning-based Intrusion Detection Systems (IDS) play a crucial role in combating thes...
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In this study, we propose an adaptive fuzzy weight algorithm for the problem of two-class imbalanced learning. Initially, our algorithm finds a set of fuzzy weight values for data samples based on the distance from ea...
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Integrating Non-Orthogonal Multiple Access(NOMA)into Fog Radio Access Networks(F-RANs)has shown to be effective in boosting the spectral efficiency,energy efficiency,connectivity,and reducing the latency,thus attracti...
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Integrating Non-Orthogonal Multiple Access(NOMA)into Fog Radio Access Networks(F-RANs)has shown to be effective in boosting the spectral efficiency,energy efficiency,connectivity,and reducing the latency,thus attracting significant research ***,the performance improvement of the NOMA-enabled F-RANs is at the cost of computational overheads,which are commonly neglected in their design and *** address this issue,in this paper,we propose a hybrid dynamic downlink framework for NOMA-enabled *** this framework,we first develop a novel network utility function,which takes both the network throughput and computational overheads into consideration,thus enabling us to comprehensively evaluate the performance of different access schemes for *** on the developed network utility function,we further formulate a network utility maximization problem,subject to practical constraints on the decoding order,power allocation,and *** solve this NP-hard problem,we decompose it into two subproblems,namely,a user equipment association and subchannel assignment subproblem and a power allocation *** matching and sequential convex programming-based algorithms are designed to solve these two subproblems,*** numerical results,we show how our proposed algorithms can achieve a good balance between the network throughput and computational overheads by judiciously adjusting the maximum transmit power of fog access *** also show that the proposed NOMA-enabled F-RAN framework can increase,by up to 89%,the network utility,compared to OMA-based F-RANs.
This study investigates dopamine-grafted activated carbon (DAC) composites synthesized via chemical bonding for use as biodegradable supercapacitor (SC) electrodes. This composite approach leverages both electrical do...
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As the use of court-connected mediations has received a permanent status as an intrajudicial conflict resolution method, the purpose of this study (n = 38/44 Finnish judges) was to elucidate how listening is used in m...
Purpose:The motivation of this study is to identify whether the overall rating of a banking app actually reflects the customer opinion and to find the causes for reduced ***,these causes lead to the dissatisfaction of...
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Purpose:The motivation of this study is to identify whether the overall rating of a banking app actually reflects the customer opinion and to find the causes for reduced ***,these causes lead to the dissatisfaction of ***,these insights reflect the overall rating of the app and it is a source of information to the executive management to contemplate on their services and take timely and effective decisions to improve their mobile ***/methodology/approach:This research was conducted on ten reputed Sri Lankan mobile banking apps to analyze the textual opinions of the *** were collected from the Google Play Store considering the higher Android consumers in Sri *** review was automatically classified into a relevant sentiment(positive,negative or neutral).These classified reviews were examined along with its rating to identify any *** trends of the positive and negative reviews of each app were observed separately along with *** modeling techniques were used to identify the causes of such ***:Although banks expect to perpetuate good customer reviews all the time,there were aberrant negative trends observed during certain time *** results revealed that unstable versions after recent updates,bad customer service,erroneous functional and nonfunctional features are the root causes toward the dissatisfaction of the ***/value:No previous study has been done on the textual reviews of Sri Lankan mobile banking *** studies had considered analyzing the reviews of the app on the entire period of its usage,whereas this research finds the trends where negative reviews surpass the positive reviews and analyze the causes of such behavior.
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