Due to the drastically expanding use of the Internet of Things, remote monitoring of health data to provide intelligent healthcare has recently attracted much interest within the system. Health Chain is a massively-sc...
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This paper presents a comparison of ELC and IDC resonator-based chipless RFID sensors for soil moisture detection. Three types of resonators are used to measure soil moisture content varied from 0% to 35%. The results...
This paper presents a comparison of ELC and IDC resonator-based chipless RFID sensors for soil moisture detection. Three types of resonators are used to measure soil moisture content varied from 0% to 35%. The results show resonance frequency shifted in range of 10.77% to 14.73% and RCS power decreased in range of 1.86 to 4 dB. These depend on the types of resonators. The results also show that the sensitivity of interdigital capacitor structure (IDC resonator) type could be used for soil moisture detection for precision agriculture in near future.
In computer vision, accurate vehicle recognition and tracking is a challenging research topic. Manual surveillance systems are cumbersome, labor-intensive, and inefficient in today's congested traffic environment....
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Analyzing and developing the safety of DNS-based total Authentication in Wireless Sensor Networks (WSNs) is a critical research vicinity that is being actively pursued. While preceding work has blanketed authenticatio...
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Stroke, a leading global disability cause, affects 12 million people annually, with 6.5 million dying. Preventing at least half of strokes requires public policy action and increased awareness. Early diagnosis is cruc...
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Software testing has been attracting a lot of attention for effective software *** model driven approach,Unified Modelling Language(UML)is a conceptual modelling approach for obligations and other features of the syst...
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Software testing has been attracting a lot of attention for effective software *** model driven approach,Unified Modelling Language(UML)is a conceptual modelling approach for obligations and other features of the system in a model-driven *** tools interpret these models into other software artifacts such as code,test data and *** generation of test cases permits the appropriate test data to be determined that have the aptitude to ascertain the *** paper focuses on optimizing the test data obtained from UML activity and state chart diagrams by using Basic Genetic Algorithm(BGA).For generating the test cases,both diagrams were converted into their corresponding intermediate graphical forms namely,Activity Diagram Graph(ADG)and State Chart Diagram Graph(SCDG).Then both graphs will be combined to form a single graph called,Activity State Chart Diagram Graph(ASCDG).Both graphs were then joined to create a single graph known as the Activity State Chart Diagram Graph(ASCDG).Next,the ASCDG will be optimized using BGA to generate the test data.A case study involving a withdrawal from the automated teller machine(ATM)of a bank was employed to demonstrate the *** approach successfully identified defects in various ATM functions such as messaging and operation.
Background and Objective: Treatment approaches for colorectal cancer (CRC) are highly dependent on the molecular subtype, as immunotherapy has shown efficacy in cases with microsatellite instability (MSI) but is ineff...
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Background and Objective: Treatment approaches for colorectal cancer (CRC) are highly dependent on the molecular subtype, as immunotherapy has shown efficacy in cases with microsatellite instability (MSI) but is ineffective for the microsatellite stable (MSS) subtype. There is promising potential in utilizing deep neural networks (DNNs) to automate the differentiation of CRC subtypes by analyzing hematoxylin and eosin (H&E) stained whole-slide images (WSIs). Due to the extensive size of WSIs, multiple instance learning (MIL) techniques are typically explored. However, existing MIL methods focus on identifying the most representative image patches for classification, which may result in the loss of critical information. Additionally, these methods often overlook clinically relevant information, like the tendency for MSI class tumors to predominantly occur on the proximal (right side) colon. Methods: We introduce ‘CIMIL-CRC’, a DNN framework that: 1) solves the MSI/MSS MIL problem by efficiently combining a pre-trained feature extraction model with principal component analysis (PCA) to aggregate information from all patches, and 2) integrates clinical priors, particularly the tumor location within the colon, into the model to enhance patient-level classification accuracy. We assessed our CIMIL-CRC method using the average area under the receiver operating characteristic curve (AUROC) from a 5-fold cross-validation experimental setup for model development on the TCGA-CRC-DX cohort, contrasting it with a baseline patch-level classification, a MIL-only approach, and a clinically-informed patch-level classification approach. Results: Our CIMIL-CRC outperformed all methods (AUROC: 0.92 ± 0.002 (95% CI 0.91-0.92), vs. 0.79 ± 0.02 (95% CI 0.76-0.82), 0.86 ± 0.01 (95% CI 0.85-0.88), and 0.87±0.01 (95% CI 0.86-0.88), respectively). The improvement was statistically significant. To the best of our knowledge, this is the best result achieved for MSI/MSS classification on this da
We present a perfect all-angle spatially deriving metasurface, overcoming numerical aperture and accuracy limitations of previous devices. While these were designed mainly via qualitative symmetry breaking and heurist...
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ISBN:
(数字)9798350369908
ISBN:
(纸本)9798350369915
We present a perfect all-angle spatially deriving metasurface, overcoming numerical aperture and accuracy limitations of previous devices. While these were designed mainly via qualitative symmetry breaking and heuristic optimizations, we derive exact closed-form susceptibility conditions, highlighting the grazing-angle Huygens' condition as a crucial aspect of this functionality. We tailor proper physical inclusions, based on rigorous electromagnetic specifications beyond symmetry breaking, to validate this concept in simulation. Our excellent results herald a sound paradigm to engineer not only analog computers, but a myriad of novel nonlocal microwave and optical devices.
The bandwidth and latency requirements of modern datacenter applications have led researchers to propose various topology designs using static, dynamic demand-oblivious (rotor), and/or dynamic demand-aware switches. H...
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This paper experimentally demonstrates a near-crossbar memory logic technique called Pinatubo. Pinatubo, an acronym for Processing In Non-volatile memory ArchiTecture for bUlk Bitwise Operations, facilitates the concu...
This paper experimentally demonstrates a near-crossbar memory logic technique called Pinatubo. Pinatubo, an acronym for Processing In Non-volatile memory ArchiTecture for bUlk Bitwise Operations, facilitates the concurrent activation of two or more rows, enabling bitwise operations such as OR, AND, XOR, and NOT on the activated rows. We implement Pinatubo using phase change memory (PCM) and compare our experimental results with the simulated data from the original Pinatubo study. Our findings highlight a significant four-orders of magnitude difference between resistance states, suggesting the robustness of the Pinatubo architecture with PCM technology.
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