On the Triality Theory for a Quartic Polynomial Optimization Problem

This paper presents a detailed proof of the triality theorem for a class of fourth-order polynomial optimization problems. The method is based on linear algebra but it solves an open problem on the double-min duality left in 2003. Results show that the triality theory holds strongly in a tri-duality form if the primal problem and its canonical dual have the same dimension; otherwise, both the canonical min-max duality and the double-max duality still hold strongly, but the double-min duality holds weakly in a symmetrical form. Four numerical examples are presented to illustrate that this theory can be used to identify not only the global minimum, but also the largest local minimum and local maximum.Comment: 16 pages, 1 figure; J. Industrial and Management Optimization, 2011. arXiv admin note: substantial text overlap with arXiv:1104.297

Structure of polydisperse inverse ferrofluids: Theory and computer simulation

By using theoretical analysis and molecular dynamics simulations, we investigate the structure of colloidal crystals formed by nonmagnetic microparticles (or magnetic holes) suspended in ferrofluids (called inverse ferrofluids), by taking into account the effect of polydispersity in size of the nonmagnetic microparticles. Such polydispersity often exists in real situations. We obtain an analytical expression for the interaction energy of monodisperse, bidisperse, and polydisperse inverse ferrofluids. Body-centered tetragonal (bct) lattices are shown to possess the lowest energy when compared with other sorts of lattices and thus serve as the ground state of the systems. Also, the effect of microparticle size distributions (namely, polydispersity in size) plays an important role in the formation of various kinds of structural configurations. Thus, it seems possible to fabricate colloidal crystals by choosing appropriate polydispersity in size.Comment: 22 pages, 8 figure

Life cycle assessment of white roof and sedum-tray garden roof for office buildings in China

White roof (WR) and Sedum lineare tray garden roof (STGR) have been convinced to improve the energy-efficiency and provide various benefits for conventional impervious grey roofs. Some national and local standards have standardized and recommended these technologies in existing building retrofits, however, they do not include assessment and choice of a particular roof retrofit in different climates. This paper presents a 40-year life-cycle cost analysis (LCCA) of an office building roof retrofitted by adding either WR or STGR over an existing grey roof in five cities, located in four Chinese climate zones. The LCCA find that the WR retrofits exhibit positive life-cycle net savings (NS) in warm winter zones, ranging 5.7–35.1 CNY/m 2 , and STGR retrofits have negative NS of -81.3– -16.7 CNY/m 2 in all climate zones. The NS of both WR and STGR generally tend to improve as one moves from the coldest cities to the warmest cities. LCCA results suggest that adding new building codes concerning crediting or prescribing WR and STGR retrofits into office buildings with grey roofs in hot summer climate zones and warm winter zone in China, respectively. And featured by more specific requirements, the localized Technical Norms help promote the implementation of new building codes

Thermal performance and energy savings of white and sedum-tray garden roof: A case study in a Chongqing office building

This study presents the experimental measurement of the energy consumption of three top-floor air-conditioned rooms in a typical office building in Chongqing, which is a mountainous city in the hot-summer and cold-winter zone of China, to examine the energy performance of white and sedum-tray garden roofs. The energy consumption of the three rooms was measured from September 2014 to September 2015 by monitoring the energy performance (temperature distributions of the roofs, evaporation, heat fluxes, and energy consumption) and indoor air temperature. The rooms had the same construction and appliances, except that one roof top was black, one was white, and one had a sedum-tray garden roof. This study references the International Performance Measurement and Verification Protocol (IPMVP) to calculate and compare the energy savings of the three kinds of roofs. The results indicate that the energy savings ratios of the rooms with the sedum-tray garden roof and with the white roof were 25.0% and 20.5%, respectively, as compared with the black-roofed room, in the summer; by contrast, the energy savings ratios were −9.9% and −2.7%, respectively, in the winter. Furthermore, Annual conditioning energy savings of white roof (3.9 kWh/m2) were 1.6 times the energy savings for the sedum-tray garden roof. It is evident that white roof is a preferable choice for office buildings in Chongqing. Additionally, The white roof had a reflectance of 0.58 after natural aging owing to the serious air pollution worsened its thermal performance, and the energy savings reduced by 0.033 kWh/m2·d. Evaporation was also identified to have a significant effect on the energy savings of the sedum-tray garden roof

Searching for high-KK isomers in the proton-rich A∼80A\sim80 mass region

Configuration-constrained potential-energy-surface calculations have been performed to investigate the $K$ isomerism in the proton-rich $A\sim80$ mass region. An abundance of high-$K$ states are predicted. These high-$K$ states arise from two and four-quasi-particle excitations, with $K^{\pi}=8^{+}$ and $K^{\pi}=16^{+}$, respectively. Their excitation energies are comparatively low, making them good candidates for long-lived isomers. Since most nuclei under studies are prolate spheroids in their ground states, the oblate shapes of the predicted high-$K$ states may indicate a combination of $K$ isomerism and shape isomerism

Optimization of cool roof and night ventilation in office buildings: A case study in Xiamen, China

Increasing roof albedo (using a “cool” roof) and night ventilation are passive cooling technologies that can reduce the cooling loads in buildings, but existing studies have not comprehensively explored the potential benefits of integrating these two technologies. This study combines an experiment in the summer and transition seasons with an annual simulation so as to evaluate the thermal performance, energy savings and thermal comfort improvement that could be obtained by coupling a cool roof with night ventilation. A holistic approach integrating sensitivity analysis and multi-objective optimization is developed to explore key design parameters (roof albedo, night ventilation air change rate, roof insulation level and internal thermal mass level) and optimal design options for the combined application of the cool roof and night ventilation. The proposed approach is validated and demonstrated through studies on a six-storey office building in Xiamen, a cooling-dominated city in southeast China. Simulations show that combining a cool roof with night ventilation can significantly decrease the annual cooling energy consumption by 27% compared to using a black roof without night ventilation and by 13% compared to using a cool roof without night ventilation. Roof albedo is the most influential parameter for both building energy performance and indoor thermal comfort. Optimal use of the cool roof and night ventilation can reduce the annual cooling energy use by 28% during occupied hours when air-conditioners are on and reduce the uncomfortable time slightly during occupied hours when air-conditioners are off

The state of the art of medical imaging technology: from creation to archive and back.

Medical imaging has learnt itself well into modern medicine and revolutionized medical industry in the last 30 years. Stemming from the discovery of X-ray by Nobel laureate Wilhelm Roentgen, radiology was born, leading to the creation of large quantities of digital images as opposed to film-based medium. While this rich supply of images provides immeasurable information that would otherwise not be possible to obtain, medical images pose great challenges in archiving them safe from corrupted, lost and misuse, retrievable from databases of huge sizes with varying forms of metadata, and reusable when new tools for data mining and new media for data storing become available. This paper provides a summative account on the creation of medical imaging tomography, the development of image archiving systems and the innovation from the existing acquired image data pools. The focus of this paper is on content-based image retrieval (CBIR), in particular, for 3D images, which is exemplified by our developed online e-learning system, MIRAGE, home to a repository of medical images with variety of domains and different dimensions. In terms of novelties, the facilities of CBIR for 3D images coupled with image annotation in a fully automatic fashion have been developed and implemented in the system, resonating with future versatile, flexible and sustainable medical image databases that can reap new innovations

3D CBIR with sparse coding for image-guided neurosurgery

This research takes an application-specific approach to investigate, extend and implement the state of the art in the fields of both visual information retrieval and machine learning, bridging the gap between theoretical models and real world applications. During an image-guided neurosurgery, path planning remains the foremost and hence the most important step to perform an operation and ensures the maximum resection of an intended target and minimum sacrifice of health tissues. In this investigation, the technique of content-based image retrieval (CBIR) coupled with machine learning algorithms are exploited in designing a computer aided path planning system (CAP) to assist junior doctors in planning surgical paths while sustaining the highest precision. Specifically, after evaluation of approaches of sparse coding and K-means in constructing a codebook, the model of sparse codes of 3D SIFT has been furthered and thereafter employed for retrieving, The novelty of this work lies in the fact that not only the existing algorithms for 2D images have been successfully extended into 3D space, leading to promising results, but also the application of CBIR, that is mainly in a research realm, to a clinical sector can be achieved by the integration with machine learning techniques. Comparison with the other four popular existing methods is also conducted, which demonstrates that with the implementation of sparse coding, all methods give better retrieval results than without while constituting the codebook, implying the significant contribution of machine learning techniques