Hete-CF: Social-Based Collaborative Filtering Recommendation using Heterogeneous Relations

Collaborative filtering algorithms haven been widely used in recommender systems. However, they often suffer from the data sparsity and cold start problems. With the increasing popularity of social media, these problems may be solved by using social-based recommendation. Social-based recommendation, as an emerging research area, uses social information to help mitigate the data sparsity and cold start problems, and it has been demonstrated that the social-based recommendation algorithms can efficiently improve the recommendation performance. However, few of the existing algorithms have considered using multiple types of relations within one social network. In this paper, we investigate the social-based recommendation algorithms on heterogeneous social networks and proposed Hete-CF, a Social Collaborative Filtering algorithm using heterogeneous relations. Distinct from the exiting methods, Hete-CF can effectively utilize multiple types of relations in a heterogeneous social network. In addition, Hete-CF is a general approach and can be used in arbitrary social networks, including event based social networks, location based social networks, and any other types of heterogeneous information networks associated with social information. The experimental results on two real-world data sets, DBLP (a typical heterogeneous information network) and Meetup (a typical event based social network) show the effectiveness and efficiency of our algorithm

PROBABILISTIC APPROACHES TO STABILITY AND DEFORMATION PROBLEMS IN BRACED EXCAVATION

This dissertation is aimed at applying probabilistic approaches to evaluating the basal-heave stability and the excavation-induced wall and ground movements for serviceability assessment of excavation in clays. The focuses herein are the influence of spatial variability of soil parameters and small sample size on the results of the probabilistic analysis, and Bayesian updating of soil parameters using field observations in braced excavations. Simplified approaches for reliability analysis of basal-heave in a braced excavation in clay considering the effect of spatial variability in random fields are presented. The proposed approaches employ the variance reduction technique (or more precisely, equivalent variance method) to consider the effect of spatial variability so that the analysis for the probability of basal-heave failure can be performed using well-established first-order reliability method (FORM). Case studies show that simplified approaches yield results that are nearly identical to those obtained from the conventional random field modeling (RFM). The proposed approaches are shown to be effective and efficient for the probabilistic analysis of basal-heave in a braced excavation considering spatial variability. The variance reduction technique is then used in the probabilistic serviceability assessment in a case study. To characterize the effect of uncertainty in sample statistics and its influence on the results of probabilistic analysis, a simple procedure involving bootstrapping is presented. The procedure is applied to assessing the probability of serviceability failure in a braced excavation. The analysis for the probability of failure, referred to herein as probability of exceeding a specified limiting deformation, necessitates an evaluation of the means and standard deviations of critical soil parameters. In geotechnical practice, these means and standard deviations are often estimated from a very limited data set, which can lead to uncertainty in the derived sample statistics. In this study, bootstrapping is used to characterize the uncertainty or variation of sample statistics and its effect on the failure probability. Through the bootstrapping analysis, the probability of exceedance can be presented as a confidence interval instead of a single, fixed probability. The information gained should enable the engineers to make a more rational assessment of the risk of serviceability failure in a braced excavation. The case study demonstrates the potential of bootstrap method in coping with the problem of having to evaluate failure probability with uncertain sample statistics. Finally, a Bayesian framework using field observations for back analysis and updating of soil parameters in a multi-stage braced excavation is developed. Because of the uncertainties in the initial estimates of soil parameters and in the analysis model and other factors such as construction quality, the updated soil parameters are presented in the form of posterior distributions. In this dissertation, these posterior distributions are derived using Markov chain Monte Carlo (MCMC) sampling method implemented with Metropolis-Hastings algorithm. In the proposed framework, Bayesian updating is first realized with one type of response observation (maximum wall deflection or maximum ground surface settlement), and then this Bayesian framework is extended to allow for simultaneous use of two types of response observations in the updating. The proposed framework is illustrated with a quality excavation case and shown effective regardless of the prior knowledge of soil parameters and type of response observations adopted. The probabilistic approaches presented in this dissertation, ranging from probability-based design of basal heave, to probabilistic analysis of serviceability failure in a braced excavation considering spatial variability of soil parameters, to bootstrapping for characterizing the uncertainty of sample statistics and its effect, and to MCMC-based Bayesian updating of soil parameters during the construction, illustrate the potential of probability/statistics as a tool for enabling more rational solutions in geotechnical fields. The case studies presented in this dissertation demonstrate the usefulness of these tools

Hete-CF : Social-Based Collaborative Filtering Recommendation using Heterogeneous Relations

The work described here was funded by the National Natural Science Foundation of China (NSFC) under Grant No. 61373051; the National Science and Technology Pillar Program (Grant No.2013BAH07F05), the Key Laboratory for Symbolic Computation and Knowledge Engineering, Ministry of Education, China, and the UK Economic & Social Research Council (ESRC); award reference: ES/M001628/1.Preprin

A Study of the Verification of the Effectiveness of Multiple Endings in Learning Novel Games

Today, digital games that incorporate multi-ending scenarios are not uncommon in the entertainment field. However, there is no such application of the multiple endings to learning games and educational situations. Therefore, there are no studies that have examined the learning effects of the multiple endings in learning games. The purpose of this study was to examine the effects of a multiple endings learning game on learners\u27 motivation and learning effectiveness. To test effectiveness of multiple endings, a multiple endings learning novel game was designed in the experiment. The results of the experiment showed that the learners of group with multiple endings practiced more often. In addition, the multi group performed better. And the results also showed that the learners in the multi group had a higher sense of achievement and self-determination than those in the single group. Based on these experiments, this study clarified that the multiple endings can improve the learning effect

Multi-band Reconfigurable Holographic Surface Based ISAC Systems: Design and Optimization

Metamaterial-based reconfigurable holographic surfaces (RHSs) have been proposed as novel cost-efficient antenna arrays, which are promising for improving the positioning and communication performance of integrated sensing and communications (ISAC) systems. However, due to the high frequency selectivity of the metamaterial elements, RHSs face challenges in supporting ultra-wide bandwidth (UWB), which significantly limits the positioning precision. In this paper, to avoid the physical limitations of UWB RHS while enhancing the performance of RHS-based ISAC systems, we propose a multi-band (MB) based ISAC system. We analyze its positioning precision and propose an efficient algorithm to optimize the large number of variables in analog and digital beamforming. Through comparison with benchmark results, simulation results verify the efficiency of our proposed system and algorithm, and show that the system achieves $42\%$ less positioning error, which reduces $82\%$ communication capacity loss.Comment: 6 pages, 4 figures, IEEE IC

Predicted percentage dissatisfied with vertical temperature gradient

A vertical thermally stratified environment provides opportunities for improved ventilation effectiveness and energy efficiency, but vertical temperature gradient can also cause local thermal discomfort. ASHRAE 55 and ISO 7730 prescribe a 3 °C/m limit between head and feet for seated persons. However, an increasing amount of evidence suggests that this limit is too restrictive. To revisit how vertical temperature gradient affects local thermal comfort, we conducted laboratory tests with four nominal vertical temperature gradients (0.4, 2.9, 5.9, and 8.4 °C/m). Ninety-eight seated college-age students participated in a blind within-subject experiment. Cold-feet discomfort is more frequently rated than warm-head discomfort with increasing temperature gradients. By using logistic regression modeling, we show that the whole-body dissatisfaction increases only slightly (< 10 %) with vertical temperature gradient, even up to 8.4 °C/m. Sex does not significantly affect the results except at 8.4 °C/m. Acceptable vertical temperature gradient changes with thermal sensation votes. The results suggest that the vertical temperature gradient could be increased to 5 °C/m between head and feet when the subject is thermally neutral

Development of a Nanomanufacturing Process to Produce Atomically Thin Black Phosphorus

Atomically thin black phosphorus (phosphorene) has both unique and desirable properties that differ from bulk black phosphorus. Unlike graphene, phosphorene has a bandgap, which makes it potentially useful for applications in the next generation of transistors. Large-scale applications of phosphorene, like other 2D materials, are limited by current production methods. The most common method of making phosphorene is mechanical exfoliation, which can only produce small and irregular quantities. In this work we investigate a top-down method of producing phosphorene by using a scanning ultrafast laser to thin black phosphorus flakes. Because the bandgap of phosphorene increases as layers are removed, it is anticipated that the last few layers will be harder to remove using the laser than the upper layers. Hopefully with properly tuned laser parameters, all but the last layer can be removed. Using a custom laser machining setup, the effects of laser power, wavelength, and scanning speed on ablation phenomena are investigated. After laser processing, flakes are characterized using Raman spectroscopy and atomic force microscopy in order to determine the nature and thickness of exposed regions. Tests done at 400 nm wavelength showed removal of material with comparatively weaker Raman peaks in the exposed areas, indicative of thinning. Removal of material was observed at 800 nm and 1500 nm wavelengths, but absence of Raman peaks indicated that thinned regions had melted and recrystallized, becoming amorphous. The present work sets the foundation for future experiments to refine this process and further explore the physics governing the thinning phenomenon