Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward a Better Understanding: Three Studies on Diversity in Intercollegiate Athletics

Diversity is one of the most widely discussed topics in society, but is neither clearly defined nor well understood. Given the number and visibility of student-athletes of color, the athletic department is rarely considered as needing to address diversity; yet, diversity goes beyond numerical representation. Indeed, diversity in organizations includes the culture and climate, and must be actively managed through both policy and practice—the congruency of which can be telling. This dissertation sought to examine the organizational context around diversity in Division I athletic departments through three individual yet inter-related studies. The first study investigated what messages athletic departments and universities express regarding diversity through mission statements; the second study examined what athletic departments are doing to address diversity through policy and programming and how these messages fit together; and with the organizational context in mind, the third study explored how athletic staff define and perceive diversity by focusing on what identities are most salient to their understanding of the concept.
Control of Sclerotium rolfsii and weeds in peanuts by solar heating of the soil

Mulching moistened soil with transparent polyethylene sheets, during the hot season, caused an increase in soil temp. which resulted in the control of weeds and soilborne diseases. This solar heating technique was tested in 2 field experiments during 1976-78, in soils naturally infested with S. rolfsii. Soils, mulched for 6 weeks during July-Aug., were sown with groundnut the next spring. This resulted in a significant decrease in the number of diseased plants, rotten pods and weeds, and an increase of 52.8 and 123.5% in the total yield and quality of the crops, respectively. Maintenance of high soil moisture under mulching, or using a drip system, or mulching after a single irrigation, produced similar results. Solar heating also reduced colonization of pods by Aspergillus spp.ADDITIONAL ABSTRACT:Mulching moistened soil with transparent polythene sheets so that solar heating raised soil temp. was tested for the control of weeds and soil-borne diseases in field trials in 1976-8 in soils naturally infected with Sclerotium rolfsii. Soils mulched for 6 wk in July-Aug. and then sown with groundnuts the following spring showed significant decreases in the percentage of diseased plants, rotten pods and weeds and an increase of 52.8% and 123.5% in total yield and crop quality, resp.ADDITIONAL ABSTRACT:Mulching moistened soil with transparent polythene sheets so that solar heating raised soil temp. was tested for the control of weeds and soil-borne diseases in field trials in 1976-8 in soils naturally infected with Sclerotium rolfsii. Soils mulched for 6 wk in July-Aug. and then sown with groundnuts the following spring showed significant decreases in the percentage of diseased plants, rotten pods and weeds and an increase of 52.8% and 123.5% in total yield and crop quality, resp
MetaSense: few-shot adaptation to untrained conditions in deep mobile sensing

Recent improvements in deep learning and hardware support offer a new breakthrough in mobile sensing; we could enjoy context-aware services and mobile healthcare on a mobile device powered by artificial intelligence. However, most related studies perform well only with a certain level of similarity between trained and target data distribution, while in practice, a specific user's behaviors and device make sensor inputs different. Consequently, the performance of such applications might suffer in diverse user and device conditions as training deep models in such countless conditions is infeasible. To mitigate the issue, we propose MetaSense, an adaptive deep mobile sensing system utilizing only a few (e.g., one or two) data instances from the target user. MetaSense employs meta learning that learns how to adapt to the target user's condition, by rehearsing multiple similar tasks generated from our unique task generation strategies in offline training. The trained model has the ability to rapidly adapt to the target user's condition when a few data are available. Our evaluation with real-world traces of motion and audio sensors shows that MetaSense not only outperforms the state-of-the-art transfer learning by 18% and meta learning based approaches by 15% in terms of accuracy, but also requires significantly less adaptation time for the target user.
Renewable Energy Zoning: Cutting Green Tape While Improving Ecological Outcomes for Renewable Energy Projects

Climate change creates an imperative to develop renewable energy infrastructure, and the state of Vermont has committed to developing new renewables. However, renewables pose significant threats to natural systems because of the dramatic changes to ecosystems that occur with development. Public outcry over new developments and dissatisfaction with the current process used for siting indicate that the old regulatory process may be outdated. This thesis seeks to bridge the divide between ecology and law in renewable energy infrastructure siting. Using the state of Vermont as a case study, it suggests a new, proactive energy planning process that would use spatial analysis and public involvement to bring experts and citizens together to evaluate difficult tradeoffs and make hard choices about where to site renewables. In this thesis I use content analysis to determine which issues are important to stakeholders involved in the debate about energy siting. I then develop spatial analysis of Chittenden County to examine four metrics important to siting: generating potential, carbon storage, viewshed, and biodiversity. This spatial analysis could be applied by policy makers to evaluate tradeoffs among these four metrics. Finally, I propose a new regulatory siting process that would use stakeholder engagement and proactive planning to create “Renewable Energy Zones” where development could be fasttracked while safeguards are in place to protect important natural resources and the public interest. A better understanding of public concern, landscape-scale spatial modeling of ecosystem services, and a new proactive energy planning process could pave the way for a more effective siting process that allows for rapid development of renewables to combat climate change and includes local voices.
CONSTRUCTIBLE BIM ELEMENTS -A ROOT CAUSE ANALYSIS OF WORK PLAN FAILURES

The project Building Information Model (BIM), made up of component trade models, can be used to coordinate and sequence building elements prior to construction. The model should serve as a surrogate for prototyping the actual construction process and can also be used to implement the lean practice of filtering work for constraints prior to assigning work. The term ‘constructible BIM element’, referring to an element that can be built exactly as it is modeled, is defined to focus on the use of the model for constraint removal and visual planning. Using an in-depth case study, incomplete assignments from Weekly Work Plans were identified and their root causes were mapped onto their associated BIM objects. This spatial analysis makes explicit and begins to quantify the connection between constructability of BIM elements and the variability of work execution in the field. Learning from the underlying patterns, the authors propose process changes for teams to more effectively identify constructability issues in BIM models, and thus leverage the BIM process to improve the reliability of field work planning.
Multivariate Control Charts for Monitoring Autocorrelated Processes

Hotelling's T2 chart is one of the most popular control charts for monitoring identically and independently distributed random vectors. Recently, Alwan and Alwan (1994) and Apley and Tsung (2002) studied the use of the T2 chart for detecting mean shifts of a univariate autocorrelated process by transforming the univariate variables into multivariate vectors. This paper examines the global properties of the T2 test when shift information is unavailable. When shift directions are known a priori, the efficiency of the T2 test can be improved by a generalized likelihood ratio test (GLRT) taking into consideration the special shift patterns. The proposed control chart has an intrinsic relationship with the residuals-based GLRT procedure studied in Vander Wiel (1996) and Apley and Shi (1999). Retaining the T2 chart's advantages of a wide range sensitivity for mean shift detection, the proposed control chart is shown to outperform the T2 chart and the residual-based GLRT procedure when monitoring the mean of a univariate autocorrelated process. Performance enhancement and deterioration in the face of gradual shifts are also discussed.
Evaluation of Crack Growth Gages for Service Life Tracking

An analysis and test program was performed to evaluate the ability of a crack growth gage to monitor crack growth damage in fatigue-critical areas of F-4C/D aircraft structure. Crack growth gages were designed and manufactured for use on the F-4 lower wing skin. The crack growth behavior of the gage and relationship of gage crack growth to potential crack growth in the wing skin were determined through analysis and test. Eight gages were bonded on the Air Force F-4C/D full-scale fatigue test article at Wright-Patterson Air Force Base. Assessments were made of (1) the capability to predict crack growth behavior of the gages mounted on the fatigue test article, (2) the ability of crack growth gage to monitor potential crack growth damage at specified control points, and (3) the impact of manufacturing, installation, and data collection procedures on the utility of the gage as a damage monitoring device. Sheet thickness was found to have a profound effect on crack growth retardation under spectrum loading in 7075-T6 aluminum.
Life Cycle Theory of Dividend: A Review Literature

The purpose of the paper is to examine the relationship between dividend policy of the company and the life cycle theory. According to the life cycle theory, the company will pay dividend in the third stage, namely the maturity stage. In the early stage, the company has investment opportunities with high profit potential so that it requires large funds. As a result, dividend payments will be delayed. However, dividend payments remain a matter of debate today because dividend payments will be associated with company value. The theory of dividend policy states that paying dividends will increase firm value, but several research results show that dividend payments are not related to firm value.
An Experimental Study on the Swaying Effect of Web-Personalization

The multi-dimensionality of online word-of-mouth not only provides rich attribute-level information but also influences the attribute preference construction of the online consumer. Though prior research affirms that consumer reviews impact the attribute preference assessment of a consumer in a non-personalized single-product environment, in a personalized, multiple alternative environment, consumers' behavior could be completely different and requires separate attention. Building on the information processing approach and constructive preference perspective, our research analyzes how personalization influences this swaying effect, i.e., the influence of personalization on the attribute preference of a consumer. We conducted a multi-group experiment with four different types of personalization - non-personalized information (no personalization), self-referent information, relevant information, and both self-referent and relevant information. Our results show evidence of a swaying effect of personalization on consumers' attribute preference for products. We found that users, when exposed to different types of personalization, experience different levels of the swaying effect on their attribute preferences of the product. This study contributes significantly to the current discourse on the setbacks of web personalization and also informs practicing managers on how to develop recommender system strategies.
Enhanced Biogas Production from Winery Solid Waste through Application of Iron oxide Nanoparticles

 Abstract — Different methods and processes of optimizing the yield of biogas are currently being explored globally. In this study, the use of Iron oxide nanoparticles as an additive to improve the biogas production was carried out. Iron oxide nanoparticles (ION) were synthesized by hydrothermal method. And subsequently, the biomethane potential test was conducted in a 500 mL batch reactor set at mesophilic conditions for a retention time of 15 days. A combination ratio of 100ppm ION to 1.6 g/VS winery solid waste (WSW) was used to run duplicate experiments. Results showed a cumulative biogas yield of 17,17mL /g.VS added for WSW alone (W1) compared to 56,93mL/g.VS added for the combination of WSW and ION (W2) which represents a biogas increase of 232%. In conclusion, ION has chemical properties that boost biogas production irrespective of the type of substrate used. The finding is of interest to the biogas industry along with waste management practitioners. studies made on nanomaterials revealed either negative or positive results with some very low biogas yields in some cases. Otero-Gonzales et al. [9] in 2014 investigated the effect of copper II oxide (CuO) nanoparticles over a long-time period and demonstrated the inhibitive effect of
Role of the engineer in international development : a case study in water supply service delivery models in Sierra Leone

i DECLARATION . iii ACKNOWLEDGEMENTS . iv CONTENTS . vi LIST OF FIGURES . x LIST OF TABLES . xiii NOTATION . xiv 1 CHAPTER 1: SCOPE OF THE RESEARCH . 1 1.1 Part 1: Introduction . 1 1.1.1 Engineering and Sustainable Development . 1 1.1.2 Current Understanding: Development and the Role of the Engineering. 2 1.1.3 Key factors in the Transfer of Technology . 4 1.1. 4 The Sustainability of Engineering Interventions . 4 1.1. 5 Sierra Leone: Selection of the Research Case Study . 7 1.2 Part 2: Research Aims, Objectives and Methodology . 10 1.2.1 Aims and Objectives of the Research . 10 1.2. 2 Systems Analysis of Engineering in International Development . 10 1.2. 3 The Methodology of the Thesis . 11 1.2. 4 Layout of the Thesis . 12 1.3 Part 3: Boundaries of the Research Question . 15 1.3. 1 Parameters of the study . 15 2 CHAPTER 2: LITERATURE REVIEW . 22 2.1 Part 1: The Role of the Engineer in Modern Society . 22 2.1.
Similarity Analysis of Methods for Objective Determination of Weights in Multi-Criteria Decision Support Systems

Decision support systems (DSS) are currently developing rapidly and are increasingly used in various fields. More often, those systems are inseparable from information-based systems and computer systems. Therefore, from a methodical point of view, the algorithms implemented in the DSS play a critical role. In this aspect, multi-criteria decision support (MCDA) methods are widely used. As research progresses, many MCDA methods and algorithms for the objective identification of the significance of individual criteria of the MCDA models were developed. In this paper, an analysis of available objective methods for criteria weighting is presented. Additionally, the authors presented the implementation of the system that provides easy and accessible weight calculations for any decision matrix with the possibility of comparing results of different weighting methods. The results of weighting methods were compared using carefully selected similarity coefficients to emphasise the correlation of the resulting weights. The performed research shows that every method should provide distinctive weights considering input data, emphasising the importance of choosing the correct method for a given multi-criteria decision support model and DSS.
Span-wise wind fluctuations in open terrain as applicable to small flying craft

Abstract Micro air vehicles (MAVs) are typically of low mass and moment of inertia and have flight speeds comparable to birds and the larger insects. Such craft traverse the lower levels of the atmospheric boundary layer (ABL) which is a significantly different environment than that experienced by larger manned aircraft, which spend the majority of their time in relatively clean air and fly at speeds significantly higher than typical wind speeds in the ABL. Here a new series of measurements dedicated to understanding spatial and temporal velocity fields that MAVs experience are presented. Atmospheric wind measurements were taken by sampling four multi-hole dynamic pressure probes spanned perpendicular to the oncoming wind at spans of between 0·014m and up to 0·45m. It was noted that the variation of both longitudinal velocity and flow pitch angle against spacing followed a fractional power law and as such large variations were present even for the smallest inter-probe separations. This effect is thought to explain the increasing piloting difficulties experienced in maintaining good roll control for decreasing scales of craft.
Lean Prototyping of Multi-body and Mechatronic Systems

Major drivers behind increased efforts in product development are the increased competition due to globalisation and the urgent transformation of society towards sustainability. Furthermore, the average product lifetime has been compressed significantly over the last decade. Due to these trends, there is increasing demand for an efficient product development process. Cutting time-to-market, reducing costs and increasing quality are widely accepted as key factors to successful product development. Consideration of sustainability aspects in product development is also becoming increasingly important. Methods and tools that are useful also for small and medium sized enterprises are of particular importance for the Swedish industry. This thesis suggests a definition of lean prototyping and points to its potential for supporting efficient product development. This is done through two case studies: a soil compactor machine treated as a multi-body system and a water jet cutting machine treated as a mechatronic system. Lean prototyping is defined as a coordinated approach to experimentation with the purpose of achieving cost-efficient and accurate enough prediction of product characteristics to support optimisation and well-informed design decisions during product development, especially in the early stages. This often involves an iterative search for and use of a suitable combination of virtual and limited physical prototypes as well as the reuse of knowledge from previous projects. The case studies are performed in cooperation with one small and one medium sized company, indicating the usefulness of the approach for different product types as well as for different company sizes. More specifically, the validated multi-body model of the soil compactor machine describes the dynamics of the machine satisfactorily and the optimisation study shows a significant potential for improved compaction capacity. This potential would not likely been found through traditional physical prototyping. The related comparative study of contact transition conditions is a contribution to consistent impact modelling in multi-body dynamics in general. The real-time virtual machine concept for simulation of the water jet cutting machine, including detailed mechanical component models, is unique. The fully automated concept implementation makes it a promising base for multidisciplinary design optimisation of the water jet cutting machine, and probably of mechatronic products in general.
Artificial Neural Networks and Regression Analysis for Predicting Faulting in Jointed Concrete Pavements Considering Base Condition

Pavement management and maintenance is an important aspect of pavement engineering. Maintenance and rehabilitation treatments should be chosen very carefully, considering financial resources and existing distress types. In jointed concrete pavements, transverse joint faulting is a key distress which considerably influences ride quality and road smoothness. There are many factors affecting joint faulting such as heavy traffic, pavement structure, climatic conditions, pavement age, etc. The condition of the base layer is one of those important factors, having a big effect in the performance of jointed concrete pavements. Base layer takes part in both early-age behaviour and long-term performance of jointed concrete pavements. In this research, Artificial Neural Networks (ANNs) and Multivariate Linear Regression (MLR) have been applied in order to predict joint faulting. Pavement age and different base layer parameters where considered in the analysis that used Long Term Pavement Performance (LTPP) project database. Research results show that ANNs approach can predict joint faulting in jointed concrete pavements successfully and more accurately, showing a high coefficient of multiple determination (R^2) values, besides very low amount of error.
Underwater Radio Communication

In subsea applications, there is a growing demand for high-speed wireless communication links for transmitting data between different equipment. Radio communication is constrained by the high attenuation in seawater. Only a very short range is achievable, even at low frequencies. In this thesis an independent, battery-driven radio frequency transmitter is developed and tested to investigate the properties of, and prove the concept of underwater radio communication. The transmitter is made on the basis of a cNODE Research Midi system from Kongsberg Maritime. A software-defined radio receiver is used to measure and store the received signal for post-processing. BPSK modulated data is transmitted through seawater with a 5 MHz carrier with several data rates from 237 bps to 46.598 kbps. Two tests with approximately 50 m and 11 m depths in Trondheimsfjorden have been conducted. Maximum range was measured to be close to 5 m at 9 m depth with 1 W (+30 dBm) output power. Although, this is believed to be in an area where there might be a lot of freshwater mixed in the seawater, which would in theory improve the range compared to for pure seawater. Data from the software-defined radio has been successfully demodulated with a custom made MATLAB program for all data rates, hence proven the underwater radio communication concept.
Behavioral intervention to conserve energy in the workplace

This study investigates the effect of a large-scale behavioral intervention to conserve energy in the workplace, consisting of an energy-saving competition among a bank’s branches. More than 500 branches were involved for a period of one year. Using a difference-in-difference estimation, we find that the competition significantly reduces monthly consumption outside the work schedule (by 7 percent), but that overall energy use does not change significantly (reduction of 2.5 percent). Branch characteristics do not lead to differentiated program response, in stark contrast with the residential sector. In the same setting, we also evaluate a technological intervention automating building energy management. The renovation leads to significant energy savings (of 18 percent), also concentrated outside the main work schedule. Our results stress the importance of considering contextual characteristics when implementing behavioral programs and show potential overlaps with smart technology investments.