A recent psychology study found that people sometimes reject overly generous offers from people because they imagine hidden "phantom costs" must be part of the transaction. Phantom costs occur when a person ...
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Medical image segmentation is a challenging task especially when dealing with unlabeled data. It has been proven that the use of complementary information for co-training is effective for medical image segmentation. W...
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ISBN:
(数字)9798350386226
ISBN:
(纸本)9798350386233
Medical image segmentation is a challenging task especially when dealing with unlabeled data. It has been proven that the use of complementary information for co-training is effective for medical image segmentation. We find that high-confidence regions are easy to segment, but low-confidence regions are difficult to correctly segment, which results in poor segmentation performance. Therefore, accurate segmentation in low-confidence regions is the effective way to enhance the performance of medical image segmentation. To achieve this goal, we propose a novel co-training strategy named low-confidence heterogeneous pixel-prototype contrastive learning with uncertainty-guide cross supervision for semi-supervised medical image segmentation. Specifically, an uncertainty-guided cross supervision module is firstly designed to estimate the confidence score of predictions from multiple outputs and then perform cross supervision between high-confidence regions. Moreover, we design a low-confidence heterogeneous prototype contrastive learning, which builds the relationship between low-confidence pixel and heterogeneous prototype to mine discriminative information in low-confidence regions so as to improve the segmentation performance. Extensive experiments on medical image datasets demonstrate that our method outperforms state-of-the-art methods in segmentation results.
We present a numerical simulation on the effect of leakage paths in the regrown GaN layer in the aperture and above the current blocking layer (CBL) of current aperture vertical electron transistor (CAVET) devices. He...
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We present a numerical simulation on the effect of leakage paths in the regrown GaN layer in the aperture and above the current blocking layer (CBL) of current aperture vertical electron transistor (CAVET) devices. Here, a 2D TCAD modeling is employed to simulate a CAVET device structure considering two main origins of parasitic leakage current from CBL/regrown-GaN interface and gate/regrown-GaN bulk and their degree of detrimental effect on the characteristics of AlGaN/GaN CAVETs.
This research paper describes and extends the outcomes from an in- depth study investigating the difference in the expected skills requirements from junior software engineers to senior software engineers, and reflecti...
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ISBN:
(数字)9798350351507
ISBN:
(纸本)9798350363067
This research paper describes and extends the outcomes from an in- depth study investigating the difference in the expected skills requirements from junior software engineers to senior software engineers, and reflections on the findings from that study. It is a given that senior software engineers have more experience and skills than junior software engineers. However, a focus on their differing competencies and dispositions provides an enhanced mechanism for comparison. Gaps were identified in assessing “professional knowledge” as categorized by the IEEE/ACM Computing Curriculum Overview Report (CC2020), and in assessing “dispositions”. It appeared that the specific scenario of comparing the expected competencies between junior and senior software engineers, tested the framework for assessing competencies developed in the CC2020 project and applied in its mapping to the IEEE/ACM computer Science (CS2013) approved curriculum. In this study into the difference between Junior and Senior software Engineers, an initial review of relevant literature was conducted. The review found that research analyzing job requirements for software engineers of different levels was limited; “experience” as a keyword was seldom mentioned; and a common distinction was made between “soft” and “hard” skills - the latter being skills that were “technical”, such as programming languages, frameworks, libraries, and tools, whereas soft skills referred to skills such as personality traits, attitudes, and teamwork skills. In our extension of that work the notion of soft skills was unpacked into professional skills and dispositions. The process of mapping from the CC2020 competency framework to the CS2013 curriculum had deliberately modelled how to represent a competency-based rather than a knowledge-based curriculum. The critical deficiency identified here was the limitation imposed by adopting a skills framework based on the cognitive taxonomy, and thereby unwittingly omitting the crucial compa
We report a simple, vacuum-compatible fiber attach process for in situ study of grating-coupled photonic devices. The robustness of this technique is demonstrated on grating-coupled waveguides exposed to multiple X-ra...
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ISBN:
(纸本)9798350369311
We report a simple, vacuum-compatible fiber attach process for in situ study of grating-coupled photonic devices. The robustness of this technique is demonstrated on grating-coupled waveguides exposed to multiple X-ray irradiations for aerospace studies.
Using Parallel Objects and Structured Parallel programming, the parallel representation of the Communication Pattern between Processes called Pipeline is shown, whose implementation is carried out through different mo...
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Lip-reading is to utilize the visual information of the speaker's lip movements to recognize words and sentences. Existing event-based lip-reading solutions integrate different frame rate branches to learn spatio-...
This research study examines the evolving ecosystem of network applications for enhancing connectivity and performance in 5G and beyond (B5G) networks. The objective is to streamline large-scale deployment of vertical...
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ISBN:
(数字)9798331530013
ISBN:
(纸本)9798331530020
This research study examines the evolving ecosystem of network applications for enhancing connectivity and performance in 5G and beyond (B5G) networks. The objective is to streamline large-scale deployment of vertical applications through a middleware layer, facilitating interactions among network operators and third parties based on varying trust levels. The proposed model addresses the complexity and computational demands of enabling adaptable, secure, and scalable applications for diverse 5G platforms. In particular, this study highlights the 5G-EPICENTRE project, which enables traffic management and dynamic control, especially for missioncritical Public Protection and Disaster Relief (PPDR) applications. By optimizing resource allocation, the model reduces computational costs while meeting the unique demands of PPDR services, such as high-quality video and data for emergency operations. The model's effectiveness will be evaluated through experiments leveraging 5G Core (5GC) control-plane capabilities, with a focus on quality of service (QoS) and latency. Practical limitations, including the integration challenges of multi-network APIs, are discussed in the conclusion.
A meta-optic platform for accelerating object classification is demonstrated. End-to-end design is used to co-optimize the optical and digital systems resulting in a high-speed and robust classifier with 93.1% accurac...
Many different industries are currently making substantial use of the Internet of Things (IoT). IoT is the process through which electronic devices communicate with their surrounding virtual environment by continuousl...
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