A formula of evaluating structural safety based on fuzzy set theory

This article presents an approach to assess safety levels of structures. A new formula for determining the fuzzy reliability of structures is proposed for the case where the set of loading effect and set of structural durability are general fuzzy sets. Illustration example concerning the bending strength evaluation of a simple-beam structure, is presented with the choice of triangular fuzzy sets for loading effect and structural durability

SUGGESTIONS FOR PROMOTING STUDENTS’ PARTICIPATION IN ENGLISH SPEAKING CLASSES: STUDENTS’ PERCEPTIONS

EFL high school students’ low level of participation is reported as a problem commonly found in English speaking classes. This study aims to investigate high school students’ perceptions of suggestions for promoting students’ participation in English speaking classes. Questionnaires and interviews were employed as data collection instruments of the study. 206 EFL high school students from three grades in a high school in the Mekong Delta, Vietnam responded to the questionnaire and then 6 of them participated in the semi-structured interview sessions. The results strongly endorsed that “promote students’ self-confidence”, “make learning tasks stimulating and the way teachers present tasks”, “establish a supportive and caring relationship”, and “create a pleasant classroom climate” were significant strategies promoting students’ participation. The results of the study are expected to contribute to the comprehension of teachers’ strategies to enhance students’ participation in English speaking classes. Article visualizations

Reliability - safety set of structures

Based on the results of A. D. Rzanitsin and V. D. Raizer in the references of [1] and [2], this paper gives other definitions of the confidence level of subjected loads βs and the confidence level of the strength of materials βR, then studies the relationship between the load factor k, the material factor m and the safety factor n in the traditional models with the factors of βs, βR and βs in the random models in the structural design. The research results show that physical meaning of two factors of βs, βR is the same as the factors of k and m, however it gives more clearly assessments on effects of the over load state and the material inhomogeneous state of the safety working state of the structures. Since the reliability - safety set is also determined from the research results. Some numerical examples are carried out to show the relationship between these above factors.

A fuzzy finite element algorithm based on response surface method for free vibration analysis of structure

This paper introduces an improved response surface-based fuzzy finite element analysis of structural dynamics. The free vibration of structure is established using superposition method, so that fuzzy displacement responses can be presented as functions of fuzzy mode shapes and fuzzy natural frequencies. Instead of direct determination of these fuzzy quantities by modal analysis which will involve the calculation of the whole finite element model, the paper proposes a felicitous approach to design the response surface as surrogate model for the problem. In the design of the surrogate model, complete quadratic polynomials are selected with all fuzzy variables are transformed to standardized fuzzy variables. This methodology allows accurate determination of the fuzzy dynamic outputs, which is the major issue in response surface based techniques. The effectiveness of the proposed fuzzy finite element algorithm is illustrated through a numerical analysis of a linear two-storey shear frame structure

AutoPruner: Transformer-Based Call Graph Pruning

Constructing a static call graph requires trade-offs between soundness and precision. Program analysis techniques for constructing call graphs are unfortunately usually imprecise. To address this problem, researchers have recently proposed call graph pruning empowered by machine learning to post-process call graphs constructed by static analysis. A machine learning model is built to capture information from the call graph by extracting structural features for use in a random forest classifier. It then removes edges that are predicted to be false positives. Despite the improvements shown by machine learning models, they are still limited as they do not consider the source code semantics and thus often are not able to effectively distinguish true and false positives. In this paper, we present a novel call graph pruning technique, AutoPruner, for eliminating false positives in call graphs via both statistical semantic and structural analysis. Given a call graph constructed by traditional static analysis tools, AutoPruner takes a Transformer-based approach to capture the semantic relationships between the caller and callee functions associated with each edge in the call graph. To do so, AutoPruner fine-tunes a model of code that was pre-trained on a large corpus to represent source code based on descriptions of its semantics. Next, the model is used to extract semantic features from the functions related to each edge in the call graph. AutoPruner uses these semantic features together with the structural features extracted from the call graph to classify each edge via a feed-forward neural network. Our empirical evaluation on a benchmark dataset of real-world programs shows that AutoPruner outperforms the state-of-the-art baselines, improving on F-measure by up to 13% in identifying false-positive edges in a static call graph.Comment: Accepted to ESEC/FSE 2022, Research Trac

Simple thermal-electrical model of photovoltaic panels with cooler-integrated sun tracker

This paper presents a simple thermal-electrical model of a photovoltaic panel with a cooler-integrated sun tracker. Based on the model and obtained weather data, we analyzed the improved overall efficiency in a year as well as the performance in each typical weather case for photovoltaic panels with fixed-tilt systems with a tilt angle equal to latitude, fixed-tilt systems with cooler, a single-axis sun tracker, and a cooler-integrated single-axis sun tracker. The results show that on a sunny summer day with few clouds, the performance of the photovoltaic panels with the proposed system improved and reached 32.76% compared with the fixed-tilt systems. On a sunny day with clouds in the wet, rainy season, because of the low air temperature and the high wind speed, the photovoltaic panel temperature was lower than the cooler’s initial set temperature; the performance of the photovoltaic panel with the proposed system improved by 12.55% compared with the fixed-tilt system. Simulation results show that, over one year, the overall efficiency of the proposed system markedly improved by 16.35, 13.03, and 3.68% compared with the photovoltaic panel with the fixed-tilt system, the cooler, and the single-axis sun tracker, respectively. The simulation results can serve as a premise for future experimental models

Chemical diversity of essential oils of rhizomes of six species of Zingiberaceae family

In this study, the essential oils from the rhizomes of six species belonging to the Zingiberaceae family, including Zingiber zerumbet, Curcuma pierreana, Globba macrocarpa, Alpinia conchigera, Stahlianthus campanulatus and Amomum sp., collected in Binh Chau-Phuoc Buu Nature Reserve were isolated using hydrodistillation, and their constituents were identified via Gas Chromatography-Mass Spectrometry. A total of 91 constituents have been identified from essential oils. These compounds were classified into 4 clusters by Agglomerative Hierarchical Clustering (AHC) and Principal Component Analysis (PCA) analysis. The principal constituents of the essential oils isolated from four species, C. pierreana, S. campanulatus, A. conchigera, and Z. zerumbet contained camphene (18.82%), α-copaene (11.75%), p-xylene (21.86%), and α-santalene (17.91%), which were significantly different from those in previous reports. Furthermore, this study revealed the chemical constituents of essential oils of G. macrocarpa and Amomum sp. for the first time. Accordingly, artemisia triene (22.21%), β-pinene (13.57%), 4,6,8-trimethylazulene (11.1%), 2-tert-butylquinoline (9.86%), β-patchoulene (7.06%), α-elemene (6.93%), and β-ocimene (6.0%) were the major compounds in essential oils of G. macrocarpa rhizomes whereas the oil of Amomum sp. was found to be rich in 2-carene (21.82%), fenchyl acetate (14.26%), 3-carene (8.28%), bornyl acetate (7.7%), and D-limonene (7.13%)

PRELIMINARY STUDY OF THE ANTIOXIDANT PROPERTIES OF OPHIOCORDYCEPS SOBOLIFERA

The aim of study was to determine preliminary phytochemical analysis and the antioxidant potential of Ophiocordyceps sobolifera. The antioxidant activity of Ophiocordyceps sobolifera was evaluated using 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging and total antioxidant activity methods. Phytochemical analyses revealed the presence of steroids, triterpenoids, alkaloids, phenolics, flavoinods, protein, carbohydarte and saponins. The antioxidant activity of the ethanol extracts and water extracts showed high antioxidant activity with the lowest half maximal inhibitory concentration (IC50) values to 0.70 from 0.95mg/mL, realtively. Total antioxidant capacity of the O. sobolifera showed contained from 5.52 ± 0.14 to 12,71 ± 0.23 mg GA/g or from 3.55 ± 0.15 to 7.87 ± .05 μmol AS/g. These data suggest that O. sobolifera is a natural source of antioxidants