Ontology-based sentiment analysis of twitter posts

The emergence of Web 2.0 has drastically altered the way users perceive the Internet, by improving information sharing, collaboration and interoperability. Micro-blogging is one of the most popular Web 2.0 applications and related services, like Twitter, have evolved into a practical means for sharing opinions on almost all aspects of everyday life. Consequently, micro-blogging web sites have since become rich data sources for opinion mining and sentiment analysis. Towards this direction, text-based sentiment classifiers often prove inefficient, since tweets typically do not consist of representative and syntactically consistent words, due to the imposed character limit. This paper proposes the deployment of original ontology-based techniques towards a more efficient sentiment analysis of Twitter posts. The novelty of the proposed approach is that posts are not simply characterized by a sentiment score, as is the case with machine learning-based classifiers, but instead receive a sentiment grade for each distinct notion in the post. Overall, our proposed architecture results in a more detailed analysis of post opinions regarding a specific topic.     

Lost in translation? An actor-network approach to HRIS implementation

Available evidence suggests that the adoption of IT-enabled Human Resource Information Systems (HRIS) has not produced the widely predicted transformation of Human Resources (HR) to a strategic business partner. We examine the relationship between HRIS and the HR function by applying actor-network theory (ANT) to an HRIS implementation project. The focus on how actor networks are formed and reformed during implementation may be particularly well suited to explaining why the original aims of the HRIS can be displaced or lost in translation. We suggest that the approach afforded by ANT enables us to better understand the ongoing and contingent process of HRIS implementations.     

Optimal band selection from hyperspectral data for Lantana camara discrimination

The primary objective of this research was to determine the optimal hyperspectral wavelengths based on spectroscopy data over the spectral range of 450–2500 nm for the detection of the invasive species Lantana camara L. (lantana) from seven of its co-occurring species. A procedure based on statistical analysis of the reflectance and the first derivative reflectance (FDR) identified 86 and 18 bands, respectively, where lantana significantly differed from its co-occurring species. The effectiveness of the identified optimal bands was then evaluated using Hyperion imagery. The original Hyperion image with 155 bands gave an overall accuracy of 80% compared to 77% and 76% from the 86- and 18-band spectral subsets, respectively. A pairwise comparison of the three error matrices showed no significant difference in the accuracy achieved. The FDR analysis combined with the statistical analysis proved to be a useful procedure for data reduction by refining the discrimination to fewer optimal bands for lantana detection with no adverse impact on classification accuracy.     

Modeling culture in intelligent virtual agents

This work addresses the challenge of creating virtual agents that are able to portray culturally appropriate behavior when interacting with other agents or humans. Because culture influences how people perceive their social reality it is important to have agent models that explicitly consider social elements, such as existing relational factors. We addressed this necessity by integrating culture into a novel model for simulating human social behavior. With this model, we operationalized a particular dimension of culture—individualism versus collectivism—within the context of an interactive narrative scenario that is part of an agent-based tool for intercultural training. Using this scenario we conducted a cross-cultural study in which participants from a collectivistic country (Portugal) were compared with participants from an individualistic country (the Netherlands) in the way they perceived and interacted with agents whose behavior was either individualistic or collectivistic, according to the configuration of the proposed model. In the obtained results, Portuguese subjects rated the collectivistic agents more positively than the Dutch but both countries had a similarly positive opinion about the individualistic agents. This experiment sheds new light on how people from different countries differ when assessing the social appropriateness of virtual agents, while also raising new research questions on this matter.     

Low-Pressure Flame Deposition of Nanostructured Oxide Films

The influence of electroless nickel plating on lead-based relaxor ferroelectric multilayer ceramic capacitors (MLCs) was studied by a comparison experiment. It was found that the influence is related to reactions in the electroless plating. It is proposed that adsorbed hydrogen atoms generated in electroless plating can diffuse into the ceramic bodies of MLCs and undergo some reduction reaction with them, resulting in the failure of electroless nickel plating. The implications for the negative influence of electroplating on MLCs and for the degradation in MLCs are also included, in which much attention is paid to the reduction reaction of hydrogen atoms generated by electrolysis of water.     

Investigation of direct load management scheme with consideration of end‐user comfort

A direct load management scheme with two‐way communication, with consideration of end‐user comfort, is proposed. First, the control algorithm is developed and the data required to be transmitted between system operator and controllable loads are identified. Then, the actions of controllable air conditioners and the power adjustment of dispersed generators to eliminate overloads in a substation transformer are simulated. The results indicate that the proposed load management technique performs effectively to reduce overloads on the transformer while maintaining energy consumption in each load, and the performance is improved by coordination with the output of dispersed generators. © 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 176(3): 19–28, 2011; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21139     

The regular polygon detector

This paper describes a robust regular polygon detector. Given image edges, we derive the a posteriori probability for a mixture of regular polygons, and thus the probability density function for the appearance of a set of regular polygons. Likely regular polygons can be isolated quickly by discretising and collapsing the search space into three dimensions. We derive a complete formulation for efficiently recovering the remaining dimensions using maximum likelihood at the locations of the most likely polygons. Results show robustness to noise, the ability to find and differentiate different shape types, and to perform real-time sign detection for driver assistance.     

Very low-noise ENG amplifier system using CMOS technology.

In this paper, we describe the design and testing of a system for recording electroneurographic signals (ENG) from a multielectrode nerve cuff (MEC). This device, which is an extension of the conventional nerve signal recording cuff, enables ENG to be classified by action potential velocity. In addition to electrical measurements, we provide preliminary in vitro data obtained from frogs that demonstrate the validity of the technique for the first time. Since typical ENG signals are extremely small, on the order of 1 1 microV, very low-noise, high-gain amplifiers are required. The ten-channel system we describe was realized in a 0.8 microm CMOS technology and detailed measured results are presented. The overall gain is 10 000 and the total input-referred root mean square (rms) noise in a bandwidth 1 Hz-5 kHZ is 291 nV. The active area is 12 mm(2) and the power consumption is 24 mW from +/-2.5 V power supplies.     

Solar-plus-storage economics: What works where,and why?

This paper explores the economics of solar-plus-storage projects for commercial-scale, behind-the-meter applications. It provides insight into the near-term and future solar-plus-storage market opportunities across the U.S. We explore the impacts of location, building load profile, technology cost, utility rate structure, and policies on solar-plus-storage economic viability, and identify which factors are most significant to project economics. While savings from storage-only projects are largely derived from demand charge reductions, solar combined with storage also provides significant energy charge savings. A common assumption is that load profiles with peaks are likely candidates for savings from storage, due to the opportunity for demand charge reduction. Our results indicate that potential for savings from combining solar with storage is independent of building load variability, likely due to the energy cost reductions from the solar. Systems are more often economical under time of use and demand charge rates, particularly when demand charges are >$10 per kilowatt. Where systems were found to be economical, expected lifetime savings averaged between 7%–10%, with savings of 30% in numerous cases. Near term markets exist for solar-plus-storage in locations such as California and New York. As technology prices drop, the number of building types that can benefit increase, and additional markets appear in Colorado, New Mexico, and Alaska. All data from the study and interactive modeling results are available at: https://openei.org/wiki/Solar+Storage.     

一种适用于VLSI实现的谐波电能计量算法

提出了一种适用于超大规模集成电路(以下简称VLSI)实现的谐波电能计量算法.该算法以电网中能量的分布为出发点,对基波和谐波分量采用了不同的数字滤波处理,并且通过一个前馈控制系统实现了滤波器中心频率对电网频率的跟随,达到了同步采样的效果,解决了在电网频率不准确时快速傅里叶变换(以下简称FFT)频谱泄漏造成的计量误差问题.与用小波包分解实现谐波电能计量的算法相比,该算法需要的滤波器更少,更节省硬件面积,因而更适合VLSI的设计实现.网表级仿真结果表明电网频率在±5%范围内波动时基波有功功率计量误差小于0.1%,各次谐波有功功率计量误差小于1%,完全能满足谐波电能计量的商业要求.集成了该算法的谐波电能计量芯片已投片生产.