In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the Inter...
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In efficient air cooling systems may cause of wasting energy in a great amount specially in the urban area. Being the most popular cooling system, air-conditioners have been used in domestic usage as well as in indust...
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Kapok predominantly utilized as an adsorbent in removing wastewater such as dye, oil and heavy metals. However, a comparative study between acid-treated and alkali-treated carbonized Kapok fibers has not been carried ...
Kapok predominantly utilized as an adsorbent in removing wastewater such as dye, oil and heavy metals. However, a comparative study between acid-treated and alkali-treated carbonized Kapok fibers has not been carried out in detail. In this study, as-made Kapok fibers were carbonized and subsequently undergo acid (HCL) and alkali (NaOH) treatment. The resultant treated Kapok fibers were characterized using Fourier transform infrared (FTIR) spectroscopy, Elemental Analyzer (EA) and Thermogravimetric Analysis (TGA). As-made carbonized Kapok fibers were tested with oil/water absorption model system. A reduction of band intensity at 1740 cm−1 and 1245 cm−1 occurred for NaOH treated sample compared with HCL. The composition of carbon in Kapok fiber increased after carbonization treatment using NaOH (62.42%) and HCL (66.15%) compared with untreated (0.17%). For oil/water absorption system, the result indicated that HCL-treated Kapok fibre was the highest absorption on 28.10 gg−1 diesel, 27.28 gg−1 petrol and 39.84 gg−1 for used vegetable oil respectively in comparison with NaoH-treated and as-made carbonized Kapor fibers. In conclusion, modification of the surface of carbonized Kapok fibers could significantly alter its textural properties which could enhance its oil absorptive behavior.
The AC/DC hybrid topology for the future smart grid is a promising configuration that allows integrating the energy resources and modern loads of AC and DC type. Understanding the AC/DC hybrid microgrids (HMGs) operat...
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The increasing penetration of variable and uncertain generation from renewable resources poses a challenge for balancing the power system supply and demand. Violations of this constraint seriously impact system reliab...
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The increasing penetration of variable and uncertain generation from renewable resources poses a challenge for balancing the power system supply and demand. Violations of this constraint seriously impact system reliability and thus carry with them a very high cost. In order to address the issues created by variable generation increased system flexibility is required. system operators are considering modifications to the conventional real-time economic dispatch model to provide improved ramp flexibility. In this paper an operational flexibility metric called lack of ramp probability (LORP) is proposed for the real-time economic dispatch. Further, a two-step robust optimization based framework is introduced to simultaneously guarantee LORP flexibility metric and ensure ramp deliverability in a multi-zonal setting. The proposed framework is illustrated on a 3-zone modified IEEE 73 bus (RTS-96) test system.
Transmission lines carrying high-speed I/O signals that traverse through different metal layers in a printed circuit board suffer from return path discontinuities. As a result, significant amount of electromagnetic en...
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Transmission lines carrying high-speed I/O signals that traverse through different metal layers in a printed circuit board suffer from return path discontinuities. As a result, significant amount of electromagnetic energy can couple to surrounding circuits and the power distribution network. In this work, we designed three printed circuit board (PCB) test vehicles using different power distribution topologies. One of them was based on a recently proposed power delivery method using power transmission lines (PTL). The other two were designed according to conventional power-ground plane pair approach. We show through measurement that PTL-based design provides less than -40dB of crosstalk between a signal line with multiple via-transitions and a nearby victim line. Measured data also showed that the PTL-based test vehicle had more than 68% of power supply noise reduction as compared to conventional designs.
Saving energy without causing discomfort and without demanding human intervention is the need of the day. It is important to develop sensor systems which not only satisfy user requirements, but also take energy consum...
ISBN:
(纸本)9781450342636
Saving energy without causing discomfort and without demanding human intervention is the need of the day. It is important to develop sensor systems which not only satisfy user requirements, but also take energy consumption into consideration. In this demo, we present the sensing subsystems of a Smart Academic Environment, based upon the core concept of 'Observability' [1] which -- while satisfying user needs -- helps to reduce the number of sensors required.
Feature representation is the critical factor for the computer-aided Alzheimer's disease (AD) diagnosis. Deep polynomial network (DPN) is a novel deep learning algorithm, which can effectively learn feature repres...
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ISBN:
(纸本)9781479923519
Feature representation is the critical factor for the computer-aided Alzheimer's disease (AD) diagnosis. Deep polynomial network (DPN) is a novel deep learning algorithm, which can effectively learn feature representation from small samples. In this work, a stacked DPN (S-DPN) algorithm is proposed to further improve feature representation. We then propose a multi-modality S-DPN (MM-S-DPN) algorithm to fuse multi-modality neuroimaging data and learn more discriminative and robust feature representation for AD classification. Experiments are performed on ADNI dataset with MRI and PET images as multi-modality data. The results indicate that S-DPN is superior to DPN and stacked auto-encoder algorithms. Moreover, MM-S-DPN achieves best performance compared with single-modality S-DPN and other multi-modality feature learning based algorithms.
The integration of a diagnostic software-based self-test and a software-based self-repair method into a single statically scheduled superscalar processor is presented. The self-test method is used as start-up test in-...
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The integration of a diagnostic software-based self-test and a software-based self-repair method into a single statically scheduled superscalar processor is presented. The self-test method is used as start-up test in-the-field in order to detect and localize permanent faults in the processor. The determined fault state is handed over to a software-based self-repair program. This program adapts the user application, which should be executed on the core, to the current fault state. Thereby both methods are able to cope with multiple permanent faults in the core. For this purpose the self-test programs as well as the self-repair program can be adapted to the current fault state, too. The paper also describes the diagnostic capability of the self-test programs and the achieved fault coverage. The hardware and program memory overhead for the self-test and self-repair programs is reported, too.
The process of using one image to guide the filtering process of another one is called Guided Image Filtering (GIF). The main challenge of GIF is the structure inconsistency between the guidance image and the target i...
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