Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterisation of heritage masonry construction in NSW – State heritage register

Numerous low to moderate magnitude earthquakes have been recorded across the state of New South Wales (NSW) since European settlement in 1788. Of these, significant damage was caused by the moderate M5.6 Newcastle earthquake in December 1989, causing the deaths of 13 people and extensive damage to unreinforced masonry (URM) buildings. The majority of the building structures listed by the Heritage Council of NSW on the State Heritage Register were constructed using URM before the development of earthquake design standard guidelines. Therefore, to help protect and preserve these invaluable historical assets, characterisation of the building typologies and materials adopted in their construction is needed in order to better understand their seismic performance and inform strategies for strengthening, where required, in a cost-effective way. This paper presents the results of an analysis of NSW heritage URM building stock listed on the State Heritage Register by the Heritage Council of NSW. The most significant parameters considered for characterisation are the URM materials, the number of stories, roof type (shapes and materials), construction year, geographic location and the past and current use for the buildings. Religious URM buildings are also classified according to their use and construction materials.
Utilization Of Students Team Achievement Division And Team Game Tournament: Effective Ways To Increase Students’ Mathematics Ability

This research aims at finding out the differences of the mathematics learning outcomes of the students who learnt through Students Team Achieveement Division (STAD) and Team Game Tournament (TGT). A quasy experimental research with posttest only for control group design was implemented where the sampling technique used was simple random sampling. The research found that: STAD and expository learning showed a significant difference where count = 28.65 which means that the results of the students who learnt through STAD were higher than the ones with expository learning. There was a significant difference as well in the results of the students in TGT and expository learning where count = 7.33 which means that the result of the students who learnt through TGT were higher than the ones with expository learning method. There was significant difference of the results or outcomes of the students learning through STAD and ones who learnt through TGT in which count = 6.80.
Antecedents of the adoption of building information modeling technology in Korea

Purpose Although the notable and significant role of building information modeling (BIM) technologies in construction industries has gained user attention, only few studies have been examined on the user adoption of the technologies. The purpose of this paper is to introduce an acceptance model for BIM technologies and investigate how external factors which were extracted by in-depth interviews promote the adoption of such technologies. Design/methodology/approach An on-line survey was conducted by two South Korean survey agencies to test the acceptance model for BIM technologies. Then, the structural equation modeling (SEM) and confirmatory factor analysis (CFA) methods were used. Findings The results of the SEM and CFA methods from on-site construction employees (n=818) in Korea collected by the online survey indicate that compatibility and organizational support play a core role in positively and significantly affecting both perceived ease of use and usefulness, and that the connections introduced by the origin technology acceptance model are mainly confirmed. Originality/value Using the findings of the results, both implications and notable limitations are presented. Moreover, practical developers, as well as academic researchers can employ the results when they attempt to conduct future research.
One-Dimensional CNN-Based Intelligent Recognition of Vibrations in Pipeline Monitoring With DAS

The vibration recognition along the fiber is still a challenging problem in pipeline monitoring with distributed optical-fiber acoustic sensor (DAS), because the burying environments in a wide range are complicated, and there are many different vibration sources interfering at different fiber locations, which are unpredictable and changing from time to time. Conventional machine learning methods with fixed hand-crated feature extraction are always time-consuming and laborious, and the recognition is relying heavily on expert knowledge, which has poor generalization ability. Thus, deep learning algorithms have been tried in this area. However, in this paper, it is found that one-dimensional (1-D) CNN can extract the distinguishable properties of the vibration signals of DAS with better performance and efficiency than the 2-D CNN through real field data experiments. And there are two main increment of the work: First, we try to use an efficient 1-D CNN to replace the 2-D CNN for feature extraction, which can improve the computation efficiency by directly feeding raw or the denoised data without any transformation or other manual work, and using simpler network structure; second, we optimize the classification further by replacing the softmax layer by the support vector machine (SVM) classifier, which is selected optimally from several typical classifiers, such as SVM, random forest, and extreme gradient boosting. Finally, the proposed method (1-D CNN+SVM) can achieve an average recognition accuracy of over 98% for five main classes of typical DAS signals in the oil pipeline monitoring application, which is superior to the conventional machine learning methods with fixed hand-crated feature. At the same time, both accuracy and efficiency of the method are better than those of the 2-D CNN.
Teachers’ assignments as indicators of classroom practice in elementary schools (CSE Technical Report 545)

This report describes ongoing research investigating the use of teachers' assignments as an indicator of classroom practice. The purpose of this work is to develop a measure of students' learning environments that could potentially be used to help monitor the influence of school reform efforts on the quality of the classroom learning environment and support the improvement of instructional practice. Past research indicated good results in regard to the technical quality and feasibility of the method for describing practice in urban school environments. This report describes additional research investigating the reliability and validity of this method for describing the quality of students' learning environments in schools serving higher achieving and middle-class elementary school students as well. Results indicated good reliability between raters, but not within raters over time. Results also indicated that the quality of assignments was statistically significantly associated with the quality of observed instruction and student work. Finally, results indicated that at least three assignments would need to be collected from teachers to determine a stable estimate of quality.
A HISTORY OF ASHRAE STANDARDS 152P.

The American Society of Heating, Refrigerating, and Air-conditioning Engineers (ASHRAE) has been developing a standard test method for evaluating the efficiency of ducts and other types of thermal distribution systems in single-family residential buildings. This report presents an overview of the structure, function, and historical development of this test method.
A Review of Binarized Neural Networks

In this work, we review Binarized Neural Networks (BNNs). BNNs are deep neural networks that use binary values for activations and weights, instead of full precision values. With binary values, BNNs can execute computations using bitwise operations, which reduces execution time. Model sizes of BNNs are much smaller than their full precision counterparts. While the accuracy of a BNN model is generally less than full precision models, BNNs have been closing accuracy gap and are becoming more accurate on larger datasets like ImageNet. BNNs are also good candidates for deep learning implementations on FPGAs and ASICs due to their bitwise efficiency. We give a tutorial of the general BNN methodology and review various contributions, implementations and applications of BNNs.
Going Fishing: Serendipity in Library and Information Science

This research examined the concept of serendipity within the context of library and information science. Serendipity was defined as a happy accident in which an information seeker unexpectedly stumbled across relevant information. This research addressed the following questions: What information seeking strategies do experienced searchers employ in order to provide opportunities for the serendipitous discovery of information? The purpose of this research was to study the experiences and ideas of experienced information seekers in order to better understand and provide opportunities for serendipitous discoveries. To address this research question and purpose, I conducted qualitative interviews with five faculty members of the School of Information and Library Science at the University of North Carolina Chapel Hill and six public librarians. The interviews were audiotaped, transcribed, and analyzed. The major findings of this study were that experienced searchers defined serendipity as an instance that is both unplanned and useful, and that the participants overwhelmingly did not attach a stigma to serendipity. The participants identified many sources of serendipity, including shelf-browsing and coworkers, made suggestions for improving serendipity in the physical library, particularly increasing displays and facing books out, and they also made suggestions for improving serendipity in information retrieval systems, particularly attaching some type of recommender system to the library catalog.
MOOC using cloud-based tools: a study of motivation and learning strategies in Latin America

This study describes the motivational and cognitive learning strategies used by students of the large-scale MOOC titled‘‘Cloud-based Tools for Learning,’’ which consists of using free Web 2.0 tools for learning. It is intended to be used byteachers and training professionals who want to innovate their educational practice.A sample of 230 students (11.2% of the2045 total students enrolled) participated in the study. They answered the motivated strategies for learning questionnaire(MSLQ). The MSLQ has questions about motivation and cognitive learning strategies used by students in a course. Themean scores of the 5 subscales are classified as low, medium, or high. Students ranked motivational strategies high, withrelevance to highlight task value, intrinsic goal orientation, and self-efficacy for learning performance, all of them with a‘‘high’’ classification. The cognitive learning strategies were also classified ‘‘high’’ but slightly lower than motivationalsection, which had higher ranks in elaboration, organization, and metacognitive self-regulation. Furthermore, we found acorrelation between motivation and cognitive strategies. We provide results from a MOOC given by the Telescope project(an initiative with a similar objective as Coursera or EdX) at Galileo University, Guatemala, a technological universitywith the longest tradition of computer science within the region. The Telescope project is an initiative carried out by theGalileo Educational System (GES) Department, which is in charge of Educational Technology R&D at the University. Weexamine the importance and relation between the two components, motivation and learning strategies. Hence, such resultscontribute to a better understanding of the learning process in this particular MOOC and will enable further discussion andinsights to improve didactic strategies and the use of innovative cloud-based tools in future MOOCs.
Energy-Efficient Adaptive Cruise Control for Electric Connected and Autonomous Vehicles

This paper presented an energy-efficient adaptive cruise control, called Energy-Efficient Electric Driving Model (E3DM), for electric, connected, and autonomous vehicles (e-CAVs) in a mixed traffic stream. E3DM is able to maintain high energy efficiency of regenerative braking by adjusting the spacing between the leading and the following vehicles. Moreover, a power-based energy consumption model is proposed to estimate the on-road energy consumption for battery electric vehicles, considering the impact of ambient temperature on auxiliary load. Using the proposed energy consumption model, the impact of E3DM on vehicle energy consumption is investigated. In particular, single-lane vehicle dynamics in a traffic stream with a mixed of e-CAVs and human-driven vehicles are simulated. The result shows that E3DM outperforms existing adaptive cruise control (i.e. Nissan-ACC) and cooperative adaptive cruise control (i.e. Enhanced-IDM and Van Arem Model) strategies in terms of energy consumption. Moreover, higher market penetration of e-CAVs may not result in better energy efficiency of the entire fleet. The reason is that more e-CAVs in the traffic stream results in faster string stabilization which decreases the regenerative energy. Considering mix traffic streams with battery electric (BEVs) and internal-combustion engine (ICEVs) vehicles, the energy consumption of entire fleet reduces when the market penetration of BEV (contains both e-CAV and human-driven BEV) increases. A higher ratio of e-CAV to human-driven BEV results in higher energy efficiency.
Influence of Acetone and Sodium Chloride Additives on Cooling Efficiency of Water Droplets Impinging onto Hot Metal Surfaces

In the present work, the cooling efficiency of water droplets falling onto hot aluminum and stainless steel discs from heights of 12.5 cm, 25 cm, 50 cm and 100 cm, corresponding to speeds of 1.5 m/s, 2.2 m/s, 3.1 m/s and 4.4 m/s, respectively, were studied. The discs were aligned at 0° (horizontal), 30° and 60° inclination. The water application rate was 0.022 g/s and the droplet diameters studied were 2.5 mm, 3.2 mm and 3.7 mm. Acetone solutions (300 ppm and 700 ppm) as well as a NaCl (35 g/kg) solution, emulating seawater, were tested to evaluate the influence of an active surfactant on the recorded cooling efficiency. The droplets with higher impact speed resulted in lower cooling efficiency, especially at disc temperatures above the Leidenfrost temperature, likely due to more vigorous droplets bouncing. Larger inclination did, as expected, result in lower cooling efficiency. At temperatures associated with nucleate boiling, the water droplets with NaCl conspicuously displayed higher cooling efficiency at about 110 °C. However, at temperatures between 120 °C and the Leidenfrost temperature, acetone and NaCl additives did not significantly alter the cooling efficiency of the water droplets. Above the Leidenfrost temperature, a minor increase in cooling efficiency was observed for the acetone solutions. Overall, the additives only marginally changed the water droplet cooling efficiency. The standard industrial water application rate (i.e., 10 L/min∙m2) is shown to be insufficient compared to the heat fluxes expected in pool and jet fires (i.e., 250 kW/m2 and 350 kW/m2, respectively).
Local economic development agencies and peripheral small town development: Evidence from Somerset East, South Africa

The activities of Local Economic Development Agencies (LEDAs) represent a channel for place-based development. In South Africa national government has supported the expansion of LEDAs to improve the weak performance of local economic development planning, one of the cornerstones of the developmental state. This article investigates the evolution and operations of a small town LEDA which is situated in one of South Africa’s peripheral regions. The local development facilitation and project work undertaken by the Blue Crane Development Agency (BCDA) in the small town of Somerset East in Eastern Cape Province is discussed. It is shown that this LEDA was innovative in development initiatives which were launched during the period 2004- 2014 for Somerset East and its surrounds. In terms of the projects and operations of BCDA considerable effort was made to identify catalytic opportunities and to support the unlocking of projects in this small town through development facilitation and project management. Nevertheless, the evidence from this case study demonstrates that despite successes, development agencies in South Africa have a strong dependence on parent municipalities which can determine the future direction and sustainability of LEDAs.
Effect of Alkaline Solutions on Engineering Properties of Alkali-Activated GGBFS Paste

In this study, two kinds of alkaline solutions, sodium hydroxide (NaOH) and sodium silicate (Na2SiO3), with three dosages of 0.5, 1.0 and 1.5% by weight were used to produce the alkali-activated ground granulated blast furnace slag (GGBFS) paste at three different liquid-solid ratios by weight of 0.45, 0.5 and 0.55. Most engineering properties of the paste were examined at age of 3, 7, 14, 28 and 56 days. Experimental results show that a mixed alkaline solution of sodium hydroxide and sodium silicate is necessary to produce an alkali-activated GGBFS paste with adequate workability and strength. Both the liquid-solid ratio and the amount of the alkaline solution affect the compressive strength in the range of 30.38 to 166.22 MPa at age of 28 days. After curing 28 days, alkali-activated GGBFS paste has the coefficient of thermal conductivity and volumetric heat capacity in range of 0.585-0.791 W/m．K and 1.583-1.8 J/m3．K, respectively, which are lower than/close to those of normal weight concrete and thus can be used as a proper material for heat insulation. The microstructural porosity of alkali-activated GGBFS paste is closely related to its engineering and thermal properties.
Preparing undergraduate students for the Major Field Test in Business

ABSTRACT Many business programs address the learning of undergraduate students with an exit exam. A reference librarian and the business school faculty created an online test preparation study guide (or LibGuide) which included no-cost resources that were readily available yet academically authoritative to aid students in studying for the Educational Testing Service Major Field Test in Business at an Association to Advance Collegiate Schools of Business–accredited college in northwest Georgia. The findings indicated that while some graduating business seniors did use the LibGuide materials, many were overwhelmed with the amount of material available and believed studying would not be beneficial to their performance on the exit exam. Discussion and areas for future research are presented.
ComBox: library-based generation of VHDL modules

We describe the automated generation of components for high throughput data-flow dominated VLSI-systems in digital communications. By means of a hierarchically organized library both behavioural models with high simulation efficiency and corresponding hardware generators that produce sophisticated VHDL descriptions are made easily accessible to the system designer. The structured approach allows the evaluation of the trade-offs between alternatives at each design step and guarantees a fast and reliable design flow towards hardware. The design environment ComBox enhances reusability and enables rapid implementation of complex systems starting from a system level description.
A Neural Network-Based Model of Radio Frequency Energy Harvesting Characteristics in a Self-Powered Food Monitoring System

Most radio frequency (RF) energy harvesters exhibit extremely nonlinear behavior during the harvesting phase, which renders the simulation of these circuits most challenging in design. This paper proposes a method of efficient modeling this nonlinearity based on empirically achieved characteristics of RF energy harvesting. A model using a multi-layer artificial neural network (ANN) is introduced to approximate this behavior. A harvester prototype that uses the far-field RF energy harvesting technique at 915 MHz is developed to verify the proposed model. The results highlight good agreement between the predicted and the observed outcomes of the harvester. With its flexibility, the proposed model can be further applied to characterize any nonlinear device. In addition, a self-powered system embedded with a fully-passive sensor device to monitor food storage profile is presented in the paper. An analysis of the power harvesting performance shows that the device can self-start its operation where the RF power is as low as −10.5 dBm, and the maximum achievable power conversion efficiency is 43%. To demonstrate the applicability of the proposed self-powered food monitoring system, an experiment is carried out using pork. Support vector machine (SVM) classifiers with two types of features are investigated to compare their performance of classifying three levels of food condition. As a result, the best classification accuracy of 95.7% is achieved.
Enhancing Student Learning Through Scaffolded Client Projects

This article reports on the current status of client projects (CPs) in business communication courses, provides a scaffolded model for implementing CP, and assesses student learning in CPs. Using a longitudinal mixed method research design, survey data and qualitative materials from six semesters are presented. The instructor survey indicated need for a model for CPs, assistance identifying community partners, and advice on tailoring CPs to course objectives, all of which are provided here. Results from assessing the model’s application indicate that students expressed higher levels of confidence as communicators and felt better prepared to engage in workplace communication.