IT Governance are one of the needs in managing Enterprise Level IT. This study shows part of the decision domain of IT Governance Help, which are IT Investment and Prioritization. The purpose of this study is to deter...
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We demonstrate a precision time protocol (PTP) used to synchronize clocks in industrial wireless local area network (iWLAN) communication systems. The implementation of the system on FPGA boards for accurate verificat...
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This paper introduces CompressedMediQ, a novel hybrid quantum-classical machine learning pipeline specifically developed to address the computational challenges associated with high-dimensional multi-class neuroimagin...
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ISBN:
(数字)9798331519315
ISBN:
(纸本)9798331519322
This paper introduces CompressedMediQ, a novel hybrid quantum-classical machine learning pipeline specifically developed to address the computational challenges associated with high-dimensional multi-class neuroimaging data analysis. Standard neuroimaging datasets, such as large-scale MRI data from the Alzheimer’s Disease Neuroimaging Initiative and Neuroimaging in Frontotemporal Dementia, present significant hurdles due to their vast size and complexity. CompressedMediQ integrates classical HPC nodes for advanced MRI pre-processing and Convolutional Neural Network (CNN)-PCA-based feature extraction and reduction, addressing the limited-qubit availability for quantum data encoding in the NISQ era. This is followed by Quantum Support Vector Machine (QSVM) classification. By utilizing quantum kernel methods, the pipeline optimizes feature mapping and classification, enhancing data separability and outperforming traditional neuroimaging analysis techniques. Experimental results highlight the pipeline’s superior accuracy in dementia staging, validating the practical use of quantum machine learning in clinical diagnostics. Despite the limitations of NISQ devices, this proof-of-concept demonstrates the transformative potential of quantum-enhanced learning, paving the way for scalable and precise diagnostic tools in healthcare and signal processing.
Convolution neural networks (CNNs) have succeeded in compressive image sensing. However, due to the inductive bias of locality and weight sharing, the convolution operations demonstrate the intrinsic limitations in mo...
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We put forward an approach for automated skeleton rigging of 3D point cloud models of segmented characters. Unlike earlier systems that fit predetermined skeleton templates or forecast predetermined sets of joints, ou...
We put forward an approach for automated skeleton rigging of 3D point cloud models of segmented characters. Unlike earlier systems that fit predetermined skeleton templates or forecast predetermined sets of joints, our approach generates an animation skeleton that is tuned to the structure and geometry of the input 3D model. Our architecture is built on a stack of hourglass models trained using a large dataset of 3D-rigged characters mined from the web. It works with a volumetric representation of the input 3D shapes enhanced with geometric shape elements that provide different indications for joint and bone positions. The proposed method also allows straightforward user customization of the output skeleton’s level of detail. Our study shows that, compared to many alternatives and baselines, our approach predicts animation skeletons that are significantly more comparable to those made by people.
Most of the oil palm smallholders operate independently. As a result of this lack of support and assistance, oil palm owned by independent smallholders has the lowest productivity compared to large private (corporatio...
Most of the oil palm smallholders operate independently. As a result of this lack of support and assistance, oil palm owned by independent smallholders has the lowest productivity compared to large private (corporation) plantations and large state plantations. In addition, smallholder-owned plantations often operate without paying attention to sustainability aspects. There is a need for an effective, efficient, and user-friendly mentoring tool for oil palm farmers that are accessed independently. The Android-based platform was developed by applying an expert system to support increased production of oil palm cultivation for smallholders. Several stages of the expert system implementation, including the identification of planters and land profiles, were carried out using the direct interview method. The expert system includes land preparation management, planting material selection, seeding, weeds control, pests and diseases, fertilization, harvesting and transport, plantation administration, chat platforms, and data scrapping from data providers. The type of expert system is a data-driven Decision Support System (DSS).
Single-photon avalanche photodiodes (SPADs) based on silicon are widely considered for quantum satellite communications but suffer from an increasing dark count rate (DCR) due to displacement damage in their active ar...
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KAGRA, the underground and cryogenic gravitational-wave detector, was operated for its solo observation from February 25 to March 10, 2020, and its first joint observation with the GEO 600 detector from April 7 to Apr...
KAGRA, the underground and cryogenic gravitational-wave detector, was operated for its solo observation from February 25 to March 10, 2020, and its first joint observation with the GEO 600 detector from April 7 to April 21, 2020 (O3GK). This study presents an overview of the input optics systems of the KAGRA detector, which consist of various optical systems, such as a laser source, its intensity and frequency stabilization systems, modulators, a Faraday isolator, mode-matching telescopes, and a high-power beam dump. These optics were successfully delivered to the KAGRA interferometer and operated stably during the observations. The laser frequency noise was observed to limit the detector sensitivity above a few kilohertz, whereas the laser intensity did not significantly limit the detector sensitivity.
The production gap between oil palm smallholder-owned plantations and corporations shows a real problem in the national palm oil industry. To reduce the gap, user-friendly assistance for smallholder-owned plantations ...
The production gap between oil palm smallholder-owned plantations and corporations shows a real problem in the national palm oil industry. To reduce the gap, user-friendly assistance for smallholder-owned plantations is needed for the cultivation of sustainable palm oil production. Android-based software can be a platform for bridging the transfer of knowledge and technology, transfer of problems, and transfer of solutions between planters and experts. The platform development was formulated in five stages which began with Learning Management System (LMS) application development, identification of Good Agricultural Practices (GAP) and Best Management Practices (BMP) materials, development of digital contents, uploading the digital content to the LMS server, and dissemination. The curriculum in the application platform was prepared based on the needs of the growers according to the identification results of the farmers' profiles. The curriculum consists of GAP and BMP material blocks. Each block was divided into discussion topics. The digital contents related to GAP and BMP were set in the LMS, which was built using Moodle platform.
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