PMU based voltage security assessment of power systems exploiting principal component analysis and decision trees

The need for feature selection and dimension reduction is felt as a fundamental step in security assessment of large power systems in which the number of features representing the state of power grids dramatically increases. These large amounts of attributes are not proper to be used for computational intelligence (CI) techniques as inputs, because it may lead to a time consuming procedure with insufficient results and they are not suitable for on-line purposes and updates.This paper proposes a combined method for an online voltage security assessment in which the dimension of the token data from phasor measurement units (PMUs) is reduced by principal component analysis (PCA). Then, the features with different stability indices are put into several categories and feature selection is done by correlation analysis in each category. These selected features are then given to decision trees (DTs) for classification and security assessment of power systems.The method is applied to 39-bus test system and a part of Iran power grid. It is seen from the results that the DTs with reduced data have simpler splitting rules, better performance in saving time, reasonable DT error and they are more suitable for constant updates.     

Creating formative feedback spaces in large lectures

Large lectures are the predominant way of teaching first-year students at universities in Norway. However, this forum for education is seldom discussed as a context for a formative feedback practice. The purpose of this sequential mixed methods study was to address whether and how a student-response system can open for a formative feedback practice in lectures and thereby support students' ability to monitor their own learning, as well as supply insight into how students engage with the feedback in their course work. The context for the study was large lectures (150–200 students) in a qualitative method course for first-year psychology students. Findings from the survey (n = 149) showed a positive correlation between the extent to which students report that they use clickers to monitor their own learning, and the extent to which they report that they used the feedback in their own course work. However, findings indicate that students valued the process of monitoring their own learning during the lectures to a greater extent than they actually used the feedback in their course work. Findings from interviews (n = 6) illustrated various ways students applied feedback in their course work.     

基于灾度辨识的钢闸门巡视检查研究

巡视检查是对钢闸门要点部位开展定期、定点的信息收集,并对警兆信息做出快速辨识和评估的重要内容。应用灾度辨识的警兆信息评估方法,综合钢闸门巡视检查的各类要素信息,明确工程最大隶属的灾度等级(Ⅰ～Ⅴ级),可作为工程日常巡视检查决策的重要软技术手段。     

Evaluation of fumonisin exposure by determination of fumonisin B1 in human hair and in Brazilian corn products

The aim of this study was to evaluate the dietary exposure to fumonisin B₁ (FB₁) through determination of residual FB₁ in hair and corn products consumed by 56 volunteers from Pirassununga and Erval Velho, Brazil. Data from FB₁ analyses in corn products and a Food Frequency Questionnaire (FFQ) were used for estimating the mean probable daily intake (PDI_M) for FB₁. FB₁ was detected in 4 human hair samples (7.2%), at a mean level of 21.3 ± 12.1 ng g⁻¹. The mean FB₁ level found in corn products was 360.4 ± 555.1 μg kg⁻¹. The PDI_M value of FB₁ in volunteers was 159 ± 47 ng kg⁻¹ body weight day⁻¹ which represents 7.9% of the provisional maximum tolerable daily intake (PMTDI) recommended for fumonisins. The FB₁ levels found in human hair samples from each volunteer were associated with their individual PDI of FB₁, indicating that exposure to FB₁ in the sample studied do not represent a health concern. This is the first report on the incidence of FB₁ in individual human hair in Brazil.     

网络安全等级保护测评中测评结论的度量方法优化

文章分析了网络安全等级保护2.0时期国家标准的新变化对等级测评结论可能产生的影响,并用实际案例和数据论述了以往描述的基于测评指标和基于测评对象的定量分析方法存在的局限性。根据网络安全等级保护国家标准结构和内容的新特点,结合新的等级测评结论表述方法,文章提出了调整和优化定量计算产生等级测评结论的思路,给出了缺陷扣分的原理和缺陷扣分的定量计算方法,并比较了各种定量计算方法在计算结果上的差异,提出了适合新标准的测评结论定量计算公式。     

Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.     

Survey of domestic food purchases and related home handling practices in the Abruzzo region (central Italy): Data collection and analysis through a language-independent classification system

A telephone survey was carried out on 13,486 randomly selected households located in the Abruzzo region (central Italy). Three questionnaires were specifically designed in relation to three different groups of foods (Meat and meat products, Fishery products, Fruit and vegetables). Questions were mainly focused on the amount and number of purchases, type of retailer, and home food handling practices with respect to the week prior to the interview. Data were classified according to a multilingual thesaurus system (LanguaL). Results allowed to estimate domestic purchases (in kg) per capita for different food categories. The category “Red meat/Cattle” accounted for a large part of purchases in the “meat and meat products” group (10.9 kg per capita/year; 32.2% of purchases in the group) while the category “Fish or related organism/Fish” was the most purchased in the “fishery products” group (6.9 kg per capita/year; 63.3%). The aggregation of more detailed characteristics enabled the identification of popular categories of foods, such as “Red meat/Cattle/Divided into pieces” (25% of the “meat and meat products” group). Significant differences (p < 0.05) were found between the four different provinces (L'Aquila, Chieti, Pescara and Teramo) with respect to “Poultry/Chicken” and “Red meat/Cattle” categories. Householders were also asked about post-purchase food handling practices that might be hazardous to food safety. More than 20% of those surveyed stated that they thawed frozen meat at room temperature. The degree of doneness after cooking of different food categories was generally high: over 90% of products purchased in the majority of meat and fish categories were properly cooked. However a noticeable proportion of householders (about 15%) reported medium or rare cooking of “Red meat/Cattle” and “Red meat/Swine”. Differences (p < 0.05) were also found between consumers of different ages, with people over 65 years old being more prone to freeze meat and cook it thoroughly.The survey was carried out in a specific geographic area and on a statistically significant sample of households, thus allowing a collection of data on domestic habits relating to food purchases and home food handling practices. This information should be included in the framework of quantitative microbial risk assessment (QMRA) models as a measure of the actual exposure of consumers to pathogenic microorganism. The LanguaL system also proved to be a practical language-independent method useful not only to identify and describe food items but also to classify them according to specific food safety characteristics.     

Development of structurally modified OER catalysts with enhanced performance and longevity for PEM-based electrolytic air dehumidification

PEM-based electrolytic air dehumidification is innovative in dehumidification that requires high precision and small space due to its high efficiency, compactness, and cleanness. However, the system dehumidification performance and durability are limited by using commercial Anatase-IrO₂ catalysts. In this study, two types of structurally modified OER catalyst materials, ATO-IrO₂ and ND-MnO₂-IrO₂, are developed to improve the performance of the system. System experiments showed that, compared to the commercial catalysts, the use of ATO-IrO₂ and ND-MnO₂-IrO₂ as the anode catalyst can improve the dehumidification performance by 45% and 20%, respectively. Furthermore, in 50-h accelerated aging tests, the attenuation rates of the ATO-IrO₂ and ND-MnO₂-IrO₂ systems are 3% and 8% respectively, which are far lower than the 35% attenuation of commercial catalyst. The results indicate that, as catalysts with a classic core-shell structure, ATO-IrO₂ and ND-MnO₂-IrO₂ still have a significant impact on improving the performance of the electrolytic dehumidification systems.     

Performance discrepancies on the California Verbal Learning Test-Second Edition (CVLT-II) in the standardization sample.

The standardization data for the California Verbal Learning Test-Second Edition (CVLT-II; D. C. Delis, J. H. Kramer, E. Kaplan, & B. A. Ober, 2000) were used to evaluate the base rate of 6 specific discrepancies between various key variables. The results indicated that CVLT-II performance discrepancies should equal or exceed 1 or 1.5 z score points (depending on the individual comparison) in the hypothesized direction to be considered potentially unusual. However, because about 1 in 3 persons in the standardization sample displayed at least 1 such large discrepancy, it is concluded that these base rates should be viewed only as a starting point for interpretation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Using a multicultural lens to understand illnesses among Haitians living in America.

Currently, ethnic and racial minority individuals represent a large proportion of the U.S. population, and researchers expect that they will represent the majority of the population by 2050. This shift in U.S. demographics calls for a greater awareness and integration of cultural issues into the assessment and treatment of ethnically and linguistically diverse clients. This article examines the unique beliefs and manifestations of illnesses among Haitians in connection with the American Psychological Association's (APA, 2002) Multicultural Guidelines. The authors use a common culture-bound syndrome, Séizisman, to illustrate the cultural beliefs, assessment, and treatment of illnesses among Haitians. In so doing, they demonstrate how to incorporate the APA Multicultural Guidelines into treatment with clients of diverse cultural and racial backgrounds. (PsycINFO Database Record (c) 2010 APA, all rights reserved)