Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationships between wood properties of small clear specimens and structural-sized boards in three softwood species

Abstract Research on the mechanical and physical properties of wood is commonly carried out on either small clear specimens or structural-sized boards. The first approach was more frequently utilized in the past, while the latter is more commonly used nowadays. However, there is very little information on how the two approaches relate with one another. This study aimed to quantify the relationships between the mechanical [modulus of elasticity (MOE) and bending strength] and physical properties (density) of both specimen sizes. A total of 1376 structural-sized boards from three different species (Douglas-fir, Norway spruce and Sitka spruce) were tested in bending, after which a small clear specimen was extracted from the undamaged portion of each board and re-tested in bending. Prior to destructive testing, all boards and clear specimens were evaluated using non-destructive technology. Poor-to-moderate relationships were found between all measured mechanical and physical properties of structural-sized timber and small clear specimens. In both specimen sizes, the properties correlated with one another within the same specimen size, as well as across the two sizes. The strength of correlations appears to be somewhat species dependent. Relatively good relationships were identified when comparing the mean tree values of the properties examined, suggesting either method can be used for a tree-level comparison. The non-destructive evaluation of specimens was shown to reflect the measured properties moderately well, with the relationships changing significantly depending on which measured property was being predicted.
Assessment and E-Learning: Current Issues and Future Trends.

This paper is a survey of selected literature which identifies issues and challenges facing teachers and institutions that wish to use digital technology to assess student e-learning of second and foreign languages. After a brief description of the use of technology for language learning three key trends in assessment using technology in language learning and education are identified: the widening of assessment practices using Web 2.0 tools; an increasing focus on collaborative digital projects; and, the growing importance of assessing digital literacy. The paper concludes with implications for pedagogy and changing teacher roles
Lexical bundles in legal texts corpora – Selection,classification and pedagogical implications

This paper analyzes lexical bundles with the aim of determining specific features of the linguistic competence of the selected research population and drawing some pedagogical implications from the fi ndings. The study focuses on lexical bundles retrieved from four legal genre-based corpora (Flowerdew 2005) compiled from texts submitted by respondents who are all legal professionals. In an eff ort to provide a more comprehensive view of lexical bundles, the phenomenon has been treated using both the conventional register analysis approach (Biber & Conrad 2009) and an approach adopted especially for legal texts by Breeze (2013). The study also attempts to submit proposals for the teaching of lexical bundles (O’Keeff e et al. 2007: 216) in the context of reading comprehension. Within the context of needs analysis, this study has been conducted as part of a larger study aiming to examine communicative competence of legal professionals from the four language skills perspective.
Adaptive tracking control of a class of linear systems with constrained actuators

In this paper, the problem of adaptive tracking control for a class of linear continuous time-invariant systems subject to constrained actuators is investigated. A novel control strategy is developed to ensure the bounded tracking of the systems. Based on Lyapunov stability theory, a result that indicates the tracking bound can be reduced as small as desired via adjusting control parameters is obtained. Then the control strategy is improved to guarantee that actuator action behaves in the limitation of maximum magnitude of actuators. Finally, simulation results of a cruise keeping marine vehicle are given to illustrate the proposed procedures and their effectiveness.
Teaching Talk Strategies For Production And Assessment

teaching talk strategies for production and assessment is available in our digital library an online access to it is set as public so you can download it instantly. Our digital library hosts in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the teaching talk strategies for production and assessment is universally compatible with any devices to read.
A quantitative study of vocabulary development of foreign students learning Chinese as a foreign language

This article reports a quantitative study of vocabulary development of students of Chinese as a foreign language (CFL). Through random sampling and diagnostic testing the current empirical study investigated the difficulties of CFL students in learning Chinese vocabulary and identified some important pedagogical aspects that need adequate attention in the teaching and learning of Chinese vocabulary. Meanwhile it attempts to point out some new directions on the research and teaching of Chinese vocabulary.
Effects of problem presentation durations on arithmetic strategies: a study in young and older adults

ABSTRACT Young and older adults were asked toaccomplish a computational estimation task (i.e. provide approximate sums to two-digit addition problems like 38 + 74) under a short versusa longer presentation duration condition. In a choice condition, participants selected the better strategy more often under a long than undera short presentation duration and after an easier than after a harder problem. In the no-choice condition, influence of presentation durationon strategy execution depended on the preceding problems, as participants showed sequence poorer strategy effects. That is, participantswere slower while executing the poorer than while executing the better strategy on current problems following better strategy problems (butequally fast after poorer strategy problems) only under short presentation duration condition. These findings have important theoreticalimplications, as current assumptions of computational models of strategies cannot explain how problem presentation durations influencestrategy selection and strategy execution.
ParMAC: distributed optimisation of nested functions, with application to binary autoencoders

Many powerful machine learning models are based on the composition of multiple processing layers, such as deep nets, which gives rise to nonconvex objective functions. A general, recent approach to optimise such "nested" functions is the "method of auxiliary coordinates (MAC)". MAC introduces an auxiliary coordinate for each data point in order to decouple the nested model into independent submodels. This decomposes the optimisation into steps that alternate between training single layers and updating the coordinates. It has the advantage that it reuses existing single-layer algorithms, introduces parallelism, and does not need to use chain-rule gradients, so it works with nondifferentiable layers. We describe ParMAC, a distributed-computation model for MAC. This trains on a dataset distributed across machines while limiting the amount of communication so it does not obliterate the benefit of parallelism. ParMAC works on a cluster of machines with a circular topology and alternates two steps until convergence: one step trains the submodels in parallel using stochastic updates, and the other trains the coordinates in parallel. Only submodel parameters, no data or coordinates, are ever communicated between machines. ParMAC exhibits high parallelism, low communication overhead, and facilitates data shuffling, load balancing, fault tolerance and streaming data processing. We study the convergence of ParMAC and its parallel speedup, and implement ParMAC using MPI to learn binary autoencoders for fast image retrieval, achieving nearly perfect speedups in a 128-processor cluster with a training set of 100 million high-dimensional points.
COLLABORATIVE PROBLEM-BASED LEARNING IN ONLINE ENVIRONMENTS

ABSTRACT Yun-Jo An COLLABORATIVE PROBLEM-BASED LEARNING IN ONLINE ENVIRONMENTS Collaborative problem-based learning (PBL) in online environments has become one of the important areas for research with the rapid growth of online learning and the need for innovation in instruction. Although current literature provides interesting and useful insights, it does not provide practical guidelines for designing and implementing collaborative PBL in online environments. Thus, this study sought to provide a first step in creating a more comprehensive and useful knowledge base to guide practitioners, such as instructors and instructional designers, who design online PBL courses or use the PBL approach in online courses. Utilizing the formative research methodology, which is a kind of qualitative case study, and the grounded theory methodology with multiple case studies, this research examined three graduate-level online courses that utilize collaborative PBL: (1) “Technology: Use and Assessment,” (2) “Introduction to Reference,” and (3) “Advanced Problems in Librarianship: Collection Development. ” From each case, two kinds of data were collected: descriptive and evaluative. These data were co llected from multiple sources, including interviews, observations, and document review. The data collection began at the start of the Fall 2005 semester and ended about two weeks after the end of the semester. Data analysis was intertwined with data
Education And Learning To Think

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Doing Surveys Online

Chapter 1: Introduction to Online Surveys Chapter 2: Developing the Survey: Questions and Answers Chapter 3: Ethical Considerations Chapter 4: Sampling Chapter 5: Using a Panel in Your Research Chapter 6: Comparative Survey Research Chapter 7: Incentives for Respondents Chapter 8: Selecting Survey Software Chapter 9: Programming the Survey Chapter 10: Fieldwork Chapter 11: Processing and Cleaning the Data Chapter 12: Weighting Survey Data Chapter 13: Reporting Survey Results Chapter 14: Making Data Available to Others Chapter 15: The Future of Web Surveys
THE EFFECTIVENESS OF E-LAB TO IMPROVE GENERIC SCIENCE SKILLS AND UNDERSTANDING THE CONCEPT OF PHYSICS KEEFEKTIFAN E-LAB UNTUK MENINGKATKAN KETERAMPILAN GENERIK SAINS DAN PEMAHAMAN KONSEP FISIKA

The aimed of this sudy are: (1) investigate the effectiveness of E-Lab to improve generic science skills and understanding the concepts oh physics; and (2) investigate the effect of generic science skills towards understanding the concept of students after learning by using the E-Lab. The method used in this study is a pre-experimental design with one group pretest-posttest. Subjects were students of Physics Education in University PGRI Semarang with methode random sampling. The results showed that: (1) learning to use E-Lab effective to increase generic science skills of students; and (2) Generic science skills give positive effect on student conceptual understanding on the material of the photoelectric effect, compton effect, and electron diffraction.
Playing In The Dark

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Interaction features for prediction of perceptual segmentation: Effects of musicianship and experimental task

As music unfolds in time, structure is recognised and understood by listeners, regardless of their level of musical expertise. A number of studies have found spectral and tonal changes to quite successfully model boundaries between structural sections. However, the effects of musical expertise and experimental task on computational modelling of structure are not yet well understood. These issues need to be addressed to better understand how listeners perceive the structure of music and to improve automatic segmentation algorithms. In this study, computational prediction of segmentation by listeners was investigated for six musical stimuli via a real-time task and an annotation (non real-time) task. The proposed approach involved computation of novelty curve interaction features and a prediction model of perceptual segmentation boundary density. We found that, compared to non-musicians’, musicians’ segmentation yielded lower prediction rates, and involved more features for prediction, particularly more interaction features; also non-musicians required a larger time shift for optimal segmentation modelling. Prediction of the annotation task exhibited higher rates, and involved more musical features than for the real-time task; in addition, the real-time task required time shifting of the segmentation data for its optimal modelling. We also found that annotation task models that were weighted according to boundary strength ratings exhibited improvements in segmentation prediction rates and involved more interaction features. In sum, musical training and experimental task seem to have an impact on prediction rates and on musical features involved in novelty-based segmentation models. Musical training is associated with higher presence of schematic knowledge, attention to more dimensions of musical change and more levels of the structural hierarchy, and higher speed of musical structure processing. Real-time segmentation is linked with higher response delays, less levels of structural hierarchy attended and higher data noisiness than annotation segmentation. In addition, boundary strength weighting of density was associated with more emphasis given to stark musical changes and to clearer representation of a hierarchy involving high-dimensional musical changes.
Evolution of Recommender Systems from Ancient Times to Modern Era: A Survey

Recommender systems were introduced in the mid-1990s to help people select the most suitable product for them from the plethora of options available with them. The idea that led to their development was that we people often rely on the opinions of our peers before trying something new, say it be before buying a smart phone, a laptop, before going for a movie, before going to a new restaurant and even before visiting a doctor. Till date, we have numerous recommender systems developed for various areas, using different recommendation approaches. Yet, there are still a few limitations of recommender systems that need to be worked on. In this paper, we present an overview of recommender systems, the various approaches of recommender systems, the application areas for which various recommender systems have been developed and we also present the limitations of recommender systems.
Encoding Color Difference Signals for High Dynamic Range and Wide Gamut Imagery

High dynamic range and wide color gamut are currently being introduced to television and cinema. This extended information requires not only more efficient signal encodings, but also improved color spaces. Due to the increasing variation in display capabilities, it is desirable to have a color signal encoding that is not only suitable for efficient quantization but also for color volume mapping. While an efficient method for high dynamic range luminance encoding has been put forward, a similar encoding scheme for color difference signals is not yet available. We address this with a novel color space representation that can be used for both efficient encoding of high dynamic range and wide gamut color difference signals as well as color volume mapping. We compare the performance, robustness and complexity against other color spaces in a variety of usage scenarios.
Adsorption isotherms of CO2 – CH4 binary mixture using IAST for optimized ECBM recovery from sub-bituminous coals of Jharia coalfield: an experimental and modeling approach

ABSTRACT Prediction of adsorption equilibria of methane (CH4)/carbon dioxide (CO2) on coal at various feed gas composition is essential for the commercial development of primary and enhanced coalbed methane (ECBM) recovery by CO2 sequestration from coal reservoirs. In this article, an attempt is made to determine the adsorption equilibria of CH4 and CO2 mixture over a wide range of pressure and free gas compositions with the help of developed computational approach using the Ideal Adsorption Solution theory (IAST) for multicomponent adsorption. The advantage of the model is that it can predict the adsorption equilibrium of the mixture from the pure gas equilibrium data. Considering the complex adsorption during gas transportation and efficient gas injection modes at constant pressure or constant composition, the two different computational approaches were developed to solve the iterative calculation of IAST, i.e. constant mole fraction with variable pressure (P = 0 to 1000 psi) and constant pressure with mole fraction as a variable (y = 0 to 1). Individual adsorption isotherm of CH4 and CO2 for the two different sub-bituminous coal samples was determined up to a pressures of 1250 psi. Pure gas isotherms reveal that volume wise CO2 has 2.00 to 2.63 times more adsorption capacity than CH4 for the samples respectively. Computational model developed using ideal solution theory can predict the adsorbed gas volume at any pressure on the experimentally studied samples collected from Indian CBM fields. The developed computational code using MATLAB© software was validated using the binary adsorption data for the two coal samples from global CBM fields published in the literatures, with calculated error lying within the permissible limit.
Multimedia Annotation, Querying, and Analysis in Anvil

While the availability of multimedia data, including human movement recording by motion capture, is steadily growing, the integrated viewing, annotation, and analysis of such complex data is still a challenge. The ANVIL tool, a widely used multi-track video and audio annotation tool, has now been extended to allow the synchronized handling of multiple media, especially the 3D viewing of motion capture data, to perform SQL queries and to conduct automated statistical analysis. The underlying database in conjunction with association detection allow analysis across tracks and modalities. This can be exploited in many contexts, from qualitative behavior analysis to the collection of training data for information extraction. Apart from describing the underlying methods and their realization in ANVIL, we discuss open issues like tool interoperabilty and scheme standardization.
On the Combination of Genetic Algorithm and Ant Algorithm

Genetic algorithm has the ability of doing a global searching quickly and stochastically But it can't make use of enough system output information It has to do a large redundancy repeat for the result when solving to certain scope So the efficiency to solve precision results is reduced Ant algorithm converges on the optimization path through information pheromone accumulation and renewal It has the ability of parallel processing and global searching The speed at which the ant algorithm gives the solution is slow, because there is little information pheromone on the path early The algorithm in this paper is based on the combination of genetic algorithm and ant algorithm First, it adopts genetic algorithm to give information pheromone to distribute Second, it makes use of the ant algorithm to give the precision of the solution Finally, it develops enough advantage of the two algorithms The simulation results show that very nice effects are obtained
Distributed edge event‐triggered consensus protocol of multi‐agent systems with communication buffer

This paper proposes a distributed edge event‐triggered (DEET) scheme of multi‐agent systems via a communication buffer to reduce unnecessary update of controllers induced by fast information transmission. This edge scheme avoids a synchronous phenomenon in node event‐triggered mechanism, in which the triggering of one agent activates information transmission of all edges linked with this agent. Hence, the node event‐triggered scheme leads to unnecessary update of control protocols while the DEET provides a new approach without constrains on synchronous phenomenon of edge information exchange. That is, the communication on each edge is independent with other edges. In addition, we investigate another case where edge information transmission is subject to quantization and a quantized edge event‐triggered control protocol is proposed. Note that such a quantized protocol guarantees asymptotical consensus instead of bounded consensus in most of the existing literature. Meanwhile, both DEET and quantized edge event‐triggered schemes have nontrivial properties of excluding Zeno behavior. Furthermore, an algorithm is provided to avoid continuous event detection; hence, the communication traffic of the whole network is reduced significantly. Copyright © 2016 John Wiley & Sons, Ltd.
Antibacterial activity of some medicinal plant oils against Escherichia coli and Salmonella species in -vitro

A total of 100 samples were collected (75 samples from diseased broiler chickens and 25 samples fromrecently dead broiler chickens). The samples were examined bacteriological, fifty two isolates of E.coli(52%) and seven isolates of Salmonellae (7%) were found. ten random samples of E.coli were serogrouped where five were E.coli O78, two O157 and untyped and seven isolates of salmonellae wereserotyped where three S.Enteritidis, one S.Charity, one S.Remiremont and two untyped . Antibacterialactivity of five medicinal plant oils from Eucalyptus, Mint, Cinnamon, Garlic and Thyme were evaluatedagainst the isolated strains using micro-titer plate to determine the minimum inhibitory concentration(MIC) and minimum bactericidal concentration (MBC) for these oils. MIC results proved that for Mint,Cinnamon, and Garlic oils were ranged from 5-5120 μg/ml, for Eucalyptus 20-5120 μg/ml and forThyme 5-2560 μg/ml. While results of MBC of Thyme and Cinnamon oils were ranged from 10-2560μg/ml. but MBC of Eucalyptus ranged from 40-5120 μg, MBC of Mint and Garlic oils were rangedfrom 5-2560μg |ml, 20-2560μg |ml respectively