Input-parallel output-parallel configuration of boost half bridge DC-DC converter with control strategy

The concept of connecting two boost half bridge DC-DC converter modules in input-paral- lel output-parallel configuration is presented. The input-parallel-output-parallel （IPOP） converter consists of multiple boost half bridge （BHB） DC-DC converter modules which are connected in par- allel at the input and output side. This kind of converter is an attractive solution for high power ap- plications. The correlation between input current sharing （ICS） and output current sharing （OCS） of the IPOP converter basic modules is described. Two loop control strategies, consisting of input cur- rent loop and output voltage loop, have been developed to achieve equal ICS and OCS in this present work. The control strategy for the IPOP configuration of boost haft bridge DC-DC converter has been verified for different load conditions （half load and full load）, The IPOP system proposed here is comprising of two modules but it can be extended to three or more. The performance of the pro- posed system along with the control strategy is verified by simulation in MATLAB using Simpower tool. Finally the satisfactory simulation results are obtained.     

大规模MIMO系统下的低复杂度迫零预编码技术

针对大规模天线技术导致传统迫零(zero-forcing, ZF)预编码复杂度上升的问题,提出了一种低复杂度预编码技术。首先利用对称超松弛迭代(semi-iteration symmetric successive overrelaxation method, SSOR)技术优化信道矩阵求逆复杂度的问题;然后利用切比雪夫半迭代法(semi-iteration, SI)加速SSOR迭代(semi-iteration symmetric successive overrelaxation method, SI-SSOR)的收敛速度,使得ZF预编码可以快速的收敛。实验结果表明,SI-SSOR预编码在误码率和传输速率上都有非常好的性能。切比雪夫半迭代法加速的SSOR预编码技术通过2次迭代就可以近似达到传统ZF预编码性能的95%以上,同时利用相对于迫零预编码更少的计算资源,因此,SI-SSOR预编码技术可以作为无线通信抑制干扰的重要手段。     

Siting park-and-ride facilities using a multi-objective spatial optimization model

Park-and-ride services are an important component of many public transportation systems in the United States. Locating park-and-ride facilities is an essential step when planning for these services. In this research we focus on three major siting/modeling concerns that need to be addressed when siting park-and-ride facilities: covering as much potential demand as possible, locating park-and-ride facilities as close as possible to major roadways, and siting such facilities in the context of an existing system. Unfortunately, existing models do not enable each of these concerns to be simultaneously addressed. This paper presents a multi-objective spatial optimization model for integrating these considerations. This model is applied for siting park-and-ride facilities in Columbus, Ohio. Application results show the usefulness of the developed model in supporting transit planning in an urban region.     

Giant Anomalous Hall and Nernst Conductivities in Magnetic All-d Metal Heusler Alloys

All-d Heuslers are a category of novel compounds combining versatile functionalities such as caloric responses and spintronics with enhanced mechanical properties. Despite the promising transport properties (anomalous Hall (AHC) and anomalous Nernst (ANC) conductivities) shown in the conventional Co₂XY Heuslers with p-d hybridization, the all-d Heuslers with only d-d hybridization open a new horizon to search for new candidates with outstanding transport properties. In this work, the AHC and ANC are evaluated for thermodynamically stable ferro/ferri-magnetic all-d-metal regular Heusler compounds based on high-throughput first-principles calculations. It is observed that quite a few materials exhibit giant AHCs and ANCs, such as cubic Re₂TaMn with an AHC of 2011 S cm^-1, and tetragonal Pt₂CrRh with an AHC of 1966 S cm^-1 and an ANC of 7.50 A m^-1K^-1. Comprehensive analysis on the electronic structure reveals that the high AHC can be attributed to the occurrence of the Weyl nodes or gapped nodal lines in the neighborhood of the Fermi level. The correlations between such transport properties and the number of valence electrons are also thoroughly investigated, which provides a practical guidance to tailor AHC and ANC via chemical doping for transverse thermoelectric applications.     

Senti‐CS: Building a lexical resource for sentiment analysis using subjective feature selection and normalized Chi‐Square‐based feature weight generation

Sentiment analysis involves the detection of sentiment content of text using natural language processing. Natural language processing is a very challenging task due to syntactic ambiguities, named entity recognition, use of slangs, jargons, sarcasm, abbreviations and contextual sensitivity. Sentiment analysis can be performed using supervised as well as unsupervised approaches. As the amount of data grows, unsupervised approaches become vital as they cut down on the learning time and the requirements for availability of a labelled dataset. Sentiment lexicons provide an easy application of unsupervised algorithms for text classification. SentiWordNet is a lexical resource widely employed by many researchers for sentiment analysis and polarity classification. However, the reported performance levels need improvement. The proposed research is focused on raising the performance of SentiWordNet3.0 by using it as a labelled corpus to build another sentiment lexicon, named Senti‐CS. The part of speech information, usage based ranks and sentiment scores are used to calculate Chi‐Square‐based feature weight for each unique subjective term/part‐of‐speech pair extracted from SentiWordNet3.0. This weight is then normalized in a range of ?1 to +1 using min–max normalization. Senti‐CS based sentiment analysis framework is presented and applied on a large dataset of 50000 movie reviews. These results are then compared with baseline SentiWordNet, Mutual Information and Information Gain techniques. State of the art comparison is performed for the Cornell movie review dataset. The analyses of results indicate that the proposed approach outperforms state‐of‐the‐art classifiers.     

The effect of computer-assisted cooperative learning methods and group size on the EFL learners’ achievement in communication skills

This study explored the effect of cooperative learning small group size and two different instructional modes (positive interdependence vs. individual accountability) on English as a Foreign Language (EFL) undergraduate learners’ communication skills (speaking and writing) achievement in computer-based environments. The study also examined the effects of disclosing/blinding the participants’ identities while interacting around computers on their post-test. The findings of the study revealed that the computer-based environment enabled the participants to blind their identities and reduce their anxiety from face-to-face debate, and so was very helpful in developing their communication skills. The use of the individual accountability mode was quite useful compared with the positive interdependence mode as it enabled all group members to perform their roles significantly. The 5-student group also significantly outperformed other groups of 2-7 members on the post-test communication skills. In conclusion, the findings of this study bring us a step closer to understanding the technique of cooperative language learning and group size.     

烯丙基酚氧树脂改性双马来酰亚胺体系的优化

通过环氧树脂与二烯丙基双酚A合成了一种烯丙基酚氧树脂,用以增韧双马来酰亚胺。在单因素试验的基础上,根据Box-Benhnken的中心组合试验设计原理,选取改性树脂体系组分为影响因子,应用响应面法进行3因素3水平的18组的设计试验,改性树脂性能(弯曲强度,冲击强度,热变形温度)为响应值,对改性树脂组分配比进行优化。结果表明,改性树脂组分配比BMI、DDS、APO、DABPA、DAP为2∶1∶0.2∶0.84∶0.1(物质的量比)时,综合2性能最好,此时改性双马树脂体系的冲击强度可达到21.4 k J/m,弯曲强度为200.5 MPa,热变形温度为195.8℃。