An integrated bayesian approach for effective multi-truth discovery

Truth-finding is the fundamental technique for corroborating reports from multiple sources in both data integration and collective intelligent applications. Traditional truthfinding methods assume a single true value for each data item and therefore cannot deal will multiple true values (i.e., the multi-truth-finding problem). So far, the existing approaches handle the multi-truth-finding problem in the same way as the single-truth-finding problems. Unfortunately, the multi-truth-finding problem has its unique features, such as the involvement of sets of values in claims, different implications of inter-value mutual exclusion, and larger source profiles. Considering these features could provide new opportunities for obtaining more accurate truthfinding results. Based on this insight, we propose an integrated Bayesian approach to the multi-truth-finding problem, by taking these features into account. To improve the truth-finding efficiency, we reformulate the multi-truthfinding problem model based on the mappings between sources and (sets of) values. New mutual exclusive relations are defined to reflect the possible co-existence of multiple true values. A finer-grained copy detection method is also proposed to deal with sources with large profiles. The experimental results on three real-world datasets show the effectiveness of our approach.Xianzhi Wang, Quan Z. Sheng, Xiu Susie Fang, Lina Yao, Xiaofei Xu, Xue L

Approximate truth discovery via problem scale reduction

Many real-world applications rely on multiple data sources to provide information on their interested items. Due to the noises and uncertainty in data, given a specific item, the information from different sources may conflict. To make reliable decisions based on these data, it is important to identify the trustworthy information by resolving these conflicts, i.e., the truth discovery problem. Current solutions to this problem detect the veracity of each value jointly with the reliability of each source for every data item. In this way, the efficiency of truth discovery is strictly confined by the problem scale, which in turn limits truth discovery algorithms from being applicable on a large scale. To address this issue, we propose an approximate truth discovery approach, which divides sources and values into groups according to a userspecified approximation criterion. The groups are then used for efficient inter-value influence computation to improve the accuracy. Our approach is applicable to most existing truth discovery algorithms. Experiments on real-world datasets show that our approach improves the efficiency compared to existing algorithms while achieving similar or even better accuracy. The scalability is further demonstrated by experiments on large synthetic datasets.Xianzhi Wang, Quan Z. Sheng, Xiu Susie Fang, Xue Li, Xiaofei Xu, and Lina Ya

A review of process advancement of novel metal spinning

Metal spinning technology has seen a rapid development in recent years. Novel spinning processes, such as non-axisymmetrical spinning, non-circular cross-section spinning and tooth-shaped spinning, are being developed. This has challenged the limitation of traditional spinning technology being used for manufacturing axisymmetrical, circular cross-section, and uniform wall-thickness parts. In this paper, the classification of the traditional spinning processes is proposed based on the material deformation characteristics, the relative position between roller and blank, mandrel spinning and mandrel-free spinning, and temperature of the blank during spinning. The advancement of recently developed novel spinning processes and corresponding tool design and equipment development are reviewed. The classification of the novel spinning processes is proposed based on the relative position between the rotating axes, the geometry of cross-section and the variation of wall-thickness of the spun parts. The material deformation mechanism, processing failures and spun part defects of the aforementioned three groups of novel spinning processes are discussed by analyzing four representative spinning processes of industrial applications. Furthermore, other novel spinning processes and their classification as reported in the literature are summarized

Truth discovery via exploiting implications from multi-source data

Data veracity is a grand challenge for various tasks on the Web. Since the web data sources are inherently unreliable and may provide con icting information about the same real-world entities, truth discovery is emerging as a counter- measure of resolving the con icts by discovering the truth, which conforms to the reality, from the multi-source data. A major challenge related to truth discovery is that different data items may have varying numbers of true values (or multi-truth), which counters the assumption of existing truth discovery methods that each data item should have exactly one true value. In this paper, we address this challenge by exploiting and leveraging the implications from multi-source data. In particular, we exploit three types of implications, namely the implicit negative claims, the distribution of positive/negative claims, and the co-occurrence of values in sources' claims, to facilitate multi-truth discovery. We propose a probabilistic approach with improvement measures that incorporate the three implications in all stages of truth discovery process. In particular, incorporating the negative claims enables multi-truth discovery, considering the distribution of positive/negative claims relieves truth discovery from the impact of sources' behavioral features in the specific datasets, and considering values' co-occurrence relationship compensates the information lost from evaluating each value in the same claims individually. Experimental results on three real-world datasets demonstrate the effectiveness of our approach.Xianzhi Wang, Quan Z. Sheng, Lina Yao, Xue Li, Xiu Susie Fang, Xiaofei Xu, and Boualem Benatalla

Empowering truth discovery with multi-truth prediction

Truth discovery is the problem of detecting true values from the con icting data provided by multiple sources on the same data items. Since sources' reliability is unknown a priori, a truth discovery method usually estimates sources' reliability along with the truth discovery process. A major limitation of existing truth discovery methods is that they commonly assume exactly one true value on each data item and therefore cannot deal with the more general case that a data item may have multiple true values (or multi-truth). Since the number of true values may vary from data item to data item, this requires truth discovery methods being able to detect varying numbers of truth values from the multi source data. In this paper, we propose a multi-truth discovery approach, which addresses the above challenges by providing a generic framework for enhancing existing truth discovery methods. In particular, we redeem the numbers of true values as an important clue for facilitating multi-truth discovery. We present the procedure and components of our approach, and propose three models, namely the byproduct model, the joint model, and the synthesis model to implement our approach. We further propose two extensions to enhance our approach, by leveraging the implications of similar numerical values and values' co-occurrence informa- tion in sources' claims to improve the truth discovery accuracy. Experimental studies on real-world datasets demonstrate the effectiveness of our approach.Xianzhi Wang, Quan Z. Sheng, Lina Yao, Xue Li, Xiu Susie Fang, Xiaofei Xu, and Boualem Benatalla

Magnetic control of the pair creation in spatially localized supercritical fields

We examine the impact of a perpendicular magnetic field on the creation mechanism of electron-positron pairs in a supercritical static electric field, where both fields are localized along the direction of the electric field. In the case where the spatial extent of the magnetic field exceeds that of the electric field, quantum field theoretical simulations based on the Dirac equation predict a suppression of pair creation even if the electric field is supercritical. Furthermore, an arbitrarily small magnetic field outside the interaction zone can bring the creation process even to a complete halt, if it is sufficiently extended. The mechanism for this magnetically induced complete shutoff can be associated with a reopening of the mass gap and the emergence of electrically dressed Landau levels

Exposure to hazardous volatile organic compounds, PM 10 and CO while walking along streets in urban Guangzhou, China

Toxic air pollutants in street canyons are important issues concerning public health especially in some large Asian cities like Guangzhou. In 1998 <18% of Guangzhou citizens used public transportation modes, with a majority commuting on foot (42%) or by bicycle (22%). Of the pedestrians, 57% were either senior citizens or students. In the present study, we measured toxic air pollutants while walking along urban streets in Guangzhou to evaluate pedestrian exposure. Volatile organic compounds (VOCs) were collected with sorbent tubes, and PM 10 and CO were measured simultaneously with portable analyzers. Our results showed that pedestrian exposure to PM 10 (with an average of 303 μg m -3 for all samples) and some toxic VOCs (for example, benzene) was relatively high. Monocyclic aromatic hydrocarbons were found to be the most abundant VOCs, and 71% of the samples had benzene levels higher than 30 μg m -3. Benzene, PM 10 and CO in walk-only streets were significantly lower (p<0.05) than in traffic streets, and the differences in exposure levels between new urban streets and old urban streets were highly significant (p<0.01). Pedestrian exposure to toxic VOCs and PM 10 was higher than those reported in other public transportation modes (bus and subway). The good correlations between BTEX, PM 10 and CO in the streets indicated that automotive emission might be their major source. Our study also showed that the risk to pedestrians due to air pollution was misinterpreted by the reported air quality index based on measurement of SO 2, NO x and PM 10 in the government monitoring stations. An urban roadside monitoring station might be needed by air quality monitoring networks in large Asian cities like Guangzhou, in order to survey exposure to air toxics in urban roadside microenvironments. © 2004 Elsevier Ltd. All rights reserved

Effect of Suspension Freeze-concentration Technology on the Quality of Wine

One of the factors that inhibits the development of the Chinese wine industry is that the sugar content ofthe grape feedstock is insufficient. In order to produce wine with better qualities using these materials,concentrating the grape juice could be a good alternative to adding sugars. In this study, suspension freezeconcentrationtechnology was applied to concentrating grape juice with a low sugar content. The freezeconcentratedgrape juice was made into red and white wines separately. In the control group, red andwhite wines were made from chaptalized (sugar-enriched) grape juice. The physical and chemical indexes,sensory evaluation results and polyphenolic content of the wine were analysed to evaluate the practicalityof applying the freeze-concentration technology in the wine industry. The results show that, after removingice every 30 min for approximately 14 h with a -18°C coolant, grape juice with an initial sugar content of14°Brix reached 23°Brix. Both the red wines and white wines made from freeze-concentrated grape juicewere of a higher quality than the wines made from chaptalised grape juice. Moreover, the phenolic contentwas concentrated, which may provide health benefits. Thus, suspension freeze-concentration technology isa promising alternative to traditional chaptalisation technology

Achieving economically sustainable subcontracting through the hotelling model by considering the spillover effect

In the process of internationalization of construction contractors, international enterprises as main contractors (IMC) need to consider whether part of the contract should be subcontracted to local subcontractors (LSC) to gain a competitive advantage when competing with local main contractors (LMC). The involvement of local subcontractors can usually help reduce cost through the cost spillover effect. However, it should be noted that the share of local subcontractors with local main contractors with an inferior quality may lead to quality spillover. The Hotelling model is therefore adopted to investigate the subcontracting decisions of main contractors considering both cost and quality spillover effects. Many scenarios are simulated and the results show that LMCs with inferior quality can always choose the subcontracting strategy to obtain increased profit regardless of the strategy that IMCs adopt. On the other hand, IMCs need to balance the cost spillover of subcontracting and the quality spillover for improving the quality level of LSCs. The results are useful for contractors to make decisions that are relevant to the adoption of subcontracting strategies to obtain competitive advantages

Visualization of facet-dependent pseudo-photocatalytic behavior of TiO2 nanorods for water splitting using In situ liquid cell TEM

We report an investigation of the pseudo-photocatalytic behavior of rutile TiO2 nanorods for water splitting observed with liquid cell transmission electron microscopy (TEM). The electron beam serves as a “light” source to initiate the catalytic reaction and a “water-in-salt” aqueous solution is employed as the electrolyte. The observation reveals that bubbles are generated preferentially residing near the {110} facet of a rutile TiO2 nanorod under a low electron dose rate (9.3–18.6 e-/Å2·s). These bubbles are ascribed to hydrogen gas generated from the pseudo-photocatalytic water splitting. As the electron beam current density increases to 93 e-/Å2 ·s, bubbles are also found at the {001} and {111} facets as well as in the bulk liquid solution, demonstrating the dominant effects of water electrolysis by electron beam under higher dose rates. The facet-dependent pseudo-photocatalytic behavior of rutile TiO2 nanorods is further validated using density functional theory (DFT)calculation. Our work establishes a facile liquid cell TEM setup for the study of pseudo-photocatalytic water splitting and it may also be applied to investigation of other photo-activated phenomena occurring at the solid-liquid interfaces