Miracle-dz/UniFAR-FTUs huggingface dataset:
MUTUAL COUPLING IN ARRAY ANTENNAS

Abstract : The report summarizes the current level of understanding of the performance of arrays of real radiators. The extent and nature of the effects of mutual coupling (element pattern distortion, element impedance variation with scan angle, and polarization variation with scan angle) in array antennas are investigated for a variety of array geometries and for several types of radiating elements. Both finite and infinite arrays of regularly spaced, uniformly illuminated, and progressively phased elements are considered. The effects of coupling on unequally spaced arrays, arrays with coupled feed networks, and circularly polarized arrays are also discussed. Finally, the results of a study of the effects of coupling on the radiation patterns of multiple-beam optical-type antennas are presented. Although most of the numerical results are based on thin, dipole radiating elements with and without ground planes (the dipole without a ground plane is the exact dual of an array of slots in a ground plane), both theoretical and experimental investigations of the sensitivity of the results to the element type are included. Emphasis is placed on the results of various analyses and their implications to the array designer. The derivations of some of the more important results are briefly outlined, but in most instances, only the relevant conclusions are given.
Scalability of Robotic Controllers: Effects of Progressive Levels of Autonomy on Robotic Reconnaissance Tasks

Abstract : This investigation of the effects of progressive levels of autonomy on robotic reconnaissance task performance was a cooperative effort between the U.S. Army Research Laboratory/Human Research and Engineering Directorate (ARL/HRED) and Space and Naval Warfare Systems Center San Diego (SSC Pacific). Thirty Soldiers served as participants. After training on the operation of the robotic system, each Soldier completed building reconnaissance exercises using three different levels of robotic automation (teleoperation, semi-autonomous, and autonomous operation). The participants' primary tasks were to map the floor plan of the building, and to identify and photograph objects of interest (situational awareness tasks). In order to increase the cognitive demand, Soldiers responded to requests for information while operating the robot. Dependent variables included objective performance data, data collector observations, and Soldier questionnaires. Reconnaissance times were significantly faster and there were significantly fewer driving errors when the robot was in the autonomous mode than when it was in the other two modes. Performance in the semi-autonomous mode was significantly better than in the teleoperation mode. As the level of autonomy increased, workload, reconnaissance times, and driving errors decreased and mapping accuracy increased. There were no significant differences among the conditions in situational awareness or target identification.
Real-Time Traffic Management to Maximize Throughput of Automated Vehicles

In intelligent transportation systems, most of the research work has focused on lane change assistant systems. No existing work considers minimizing the disruption of traffic flow by maximizing the number of lane changes while eliminating the collisions. In this thesis, the authors develop qualitative and quantitative approaches for minimizing the disruption of traffic flow for three lane scenarios and show that this approach can be extended to an arbitrary number of lanes. The proposed algorithm is able to achieve the maximum number of lane changes. Simulation results show that this approach provides much better performance when compared with different lane change algorithms without incurring large overhead, and is hence suitable for online use.
Habitat Ecology and Analysis

Habitat is crucial to the survival and reproduction of individual organisms as well as persistence of populations. As such, species-habitat relationships have long been studied, particularly in the field of wildlife ecology and to a lesser extent in the more encompassing discipline of ecology. The habitat requirements of a species largely determine its spatial distribution and abundance in nature. One way to recognize and appreciate the over-riding importance of habitat is to consider that a young organism must find and settle into the appropriate type of habitat as one of the first challenges of life. This process can be cast in a probabilistic framework and used to better understand the mechanisms behind habitat preferences and selection. There are at least six distinctly different statistical approaches to conducting a habitat analysis – that is, identifying and quantifying the environmental variables that a species most strongly associates with. These are (1) comparison among group means (e.g., ANOVA), (2) multiple linear regression, (3) multiple logistic regression, (4) classification and regression trees, (5) multivariate techniques (Principal Components Analysis and Discriminant Function Analysis), and (6) occupancy modelling. Each of these is lucidly explained and demonstrated by application to a hypothetical dataset. The strengths and weaknesses of each method are discussed. Given the ongoing biodiversity crisis largely caused by habitat destruction, there is a crucial and general need to better characterize and understand the habitat requirements of many different species, particularly those that are threatened and endangered.
Students as producers: Designing games to teach social science research methods and ethics

In this paper we explore our experiences of a staff-student collaborative project that sought to design games and learning resources that could be used to 'liven-up' research methods and ethics teaching in the social sciences. Final and second year undergraduate social science students were encouraged to reflect on their own experiences of both research methods teaching and the process of doing primary research, in order to design games resources that would be useful for future cohorts of students. The concept of games was applied twofold in the project: the development of the teaching resources was itself set up in a games format: we based our initial workshops on the style of the BBC's "Apprentice" programme in order to come up with ideas for the games resources and to introduce a competitive element into the design process. Two groups of students were given a brief to design a games resource that would 'liven up' social science research methods and ethics teaching. Groups then spent an intensive day working on the brief alongside an academic facilitator before pitching their final game concept in a presentation at the end of the day when a winner was announced. In subsequent workshops students worked collaboratively to further develop both games before piloting them on further groups of students prior to production. The second application of the games concept lay in the development of an actual learning resource to be used in future research methods and ethics teaching. The premise of developing an undergraduate dissertation, its (realistic) design and the potential ethical and methodological problems encountered when doing research underpinned the learning objectives for the games developed. The developed games resources have been introduced into the curriculum to supplement the existing (more traditional) learning and teaching strategies and to add a 'fun' element into research methods teaching. Developing a game-based learning approach themselves has thereby increased students' influence on the design of teaching and learning strategies and helped produce a useful learning resource for future cohorts. The paper highlights the benefits of staff-student collaboration in the design and production of game resources, and in particular, the potential for harnessing students' experiences of teaching and learning through feeding it into curriculum development. The paper also demonstrates the benefits of gamification - through a discussion of the positive student feedback and evaluation received by the developed games.
Six Sigma for Financial Professionals

Preface. Acknowledgments. Introduction. Chapter 1: Customer Service and Satisfaction. Typical Tools and Methodologies. Notes. Selected Bibliography. Chapter 2: Overview of Six Sigma. Q and A. Notes. Selected Bibliography. Chapter 3: DMAIC Model. Define. Measure. Analyze. Improve. Control. Selected Bibliography. Chapter 4: Design for Six Sigma. Define. Characterize. Optimize. Verify. Special Note. Notes. Selected Bibliography. Chapter 5: Project Management. Project Management for Black Belts. Team Management. Change Management. Orientation. Strategies for Reviewing and/or Presenting Projects. Selected Bibliography. Chapter 6: Six Sigma and Statistics. Deductive and Inductive Statistics. Stages of a Sample Study. Measurement. Statistical Tools Used in the Six Sigma Methodology. Notes. Selected Bibliography. Chapter 7: Roles and Responsibilities. Roles and Responsibilities in a Typical Six Sigma. The DMAIC Model. Generic Areas for Possible Project Selection. Areas for Possible Project Selection in the Financial World. DCOV Model. Selected Bibliography. Chapter 8: Six Sigma and Transactional Business: Service Industries. Why Six Sigma in Transactional Business? The DCOV Model. Why DFSS in Transactional Business? Typical Areas Where Six Sigma May Be Beneficial in the Service Industry. Project Priority Hierarchy. Deployment of Six Sigma in Transactional Business: Service Industries. Note. Selected Bibliography. Chapter 9: Implementation Strategy, Training, and Certification. Six Sigma DMAIC Implementation Strategy. DCOV Implementation Strategy. Training. Typical Cost. Certification. Notes. Selected Bibliography. Appendix A: Common Abbreviations in Six Sigma. Appendix B: Core Competencies of Six Sigma Methodology. Glossary. Selected Bibliography. Index.
Planar HBV triplers and quintuplers for millimetre wavelengths

In this paper, various fixed tuned tripler and quintupler designs are presented. Measurement of a microstrip tripler, using antipodal finline for transition to waveguide, shows a good result with a output power of -0.8 dBm at 128 GHz compared to simulation. Furthermore, a quintupler realised with coplanar-waveguide have been simulated to provide a conversion efficiency of 6.7% at 100 GHz.
Research on Drinking Behavior in the Feed Consumption Time in Romanian Black and White Primiparous Cows

The study was carried out on 9 Romanian Black and White cows in their first one hundred days of lactation. The aim of this study was to determine some aspect of drinking behavior of the cows in the feed consumption time. The forages (hay, silage and beet) were administered in 3 portions (P 1 , P 2 , and P3) per day, in 2 equal feedings (F 1 , F 2) per portion. During the experiments, the following drinking behavior aspects were determined: the number of drinkings, the length of drinking periods (sec.) and average duration of one drinking (sec.). Data was computed by ANOVA/MANOVA. Results showed that the feedings had an influence on the number of water intakes and their duration in all three portions. Between F1 and F2, very significant differences (p<0.001) were in P 1 and P3 for number of drinkings and their duration, and significant differences (p<0.01) were for average duration of one drinking. In the P 2 portion, the differences between F1 and F2 were very significant (p<0.001) for all indicators
Modeling and Simulation in Support of Network Centric Warfare Analysis

Abstract : The Space and Naval Warfare Systems Center San Diego (SSC San Diego) Code 2822, Network Centric Warfare Analysis Branch, has been developing and integrating models of Navy communications systems. These models are used for assessing communications performance in networked operations and the accompanying impact of communications on C4ISR operations. This paper provides an overview and highlights some of our recently completed tasks and ongoing efforts.
Influence of Fluctuating Groundwater Table on Volatile Organic Chemical Emission Flux at a Dissolved Chlorinated‐Solvent Plume Site

Groundwater elevation fluctuation has been recognized as one mechanism causing temporal indoor air volatile organic chemical (VOC) impacts in vapor intrusion risk assessment guidance. For dissolved VOC sources, groundwater table fluctuation shortens/lengthens the transport pathway, and delivers dissolved contaminants to soils that are alternating between water saturated and variably saturated conditions, thereby enhancing volatilization potential. To date, this mechanism has not been assessed with field data, but enhanced VOC emission flux has been observed in lab‐scale and modeling studies. This work evaluates the impact of groundwater elevation changes on VOC emission flux from a dissolved VOC plume into a house, supplemented with modeling results for cyclic groundwater elevation changes. Indoor air concentrations, air exchange rates, and depth to groundwater (DTW) were collected at the study house during an 86‐d constant building underpressurization test. These data were used to calculate changes in trichloroethylene (TCE) emission flux to indoor air, during a period when DTW varied daily and seasonally from about 3.1 to 3.4 m below the building foundation (BF). Overall, TCE flux to indoor air varied by about 50% of the average, without any clear correlation to changes in DTW or its change rate. To complement the field study, TCE surface emission fluxes were simulated using a one‐dimensional model (HYDRUS 1D) for conditions similar to the field site. Simulation results showed time‐averaged surface TCE fluxes for cyclic water‐table elevations were greater than for stationary water‐table conditions at an equivalent time‐averaged water‐table position. The magnitudes of temporal TCE emission flux changes were generally less than 50% of the time‐averaged flux, consistent with the field site observations. Simulation results also suggested that TCE emission flux changes due to groundwater fluctuation are likely to be significant at sites with shallow groundwater (e.g., < 0.5 m BF) and permeable soil types (e.g., sand).
Time Domain Interference Cancellation for Cognitive Radios and Future Wireless Systems

Author(s): Yang, Jing | Advisor(s): Brodersen, Robert W. | Abstract: The discrepancy between perceived spectrum shortage and the actual availability by measurements motivates the use of cognitive radio concepts. In this approach the radio locates and then transmits in unused or lightly used bands. If a wideband digital approach (on the order of GHz) to channel selection is taken to provide the necessary radio flexibility, there is a stringent dynamic range and speed requirement in the analog to digital conversion process. This arises from the large interfering signals which are effectively in-band since they are not removed by analog pre-filters. Given this extremely challenging wideband dynamic range goal, a fundamentally different mixed signal architecture has been pursued which is based on time domain signal cancellation. The objective of this thesis is therefore to analyze and implement critical aspects of this approach, with particular focus on the power requirements and silicon area. This approach explores the use of a mixed analog with digital assistance architecture which uses multiple low to medium resolution ADCs with digital adaptive filters. The effective dynamic range of the front-end is enhanced by cancelling the unwanted interference in the time domain. Interference cancellation performance is improved using oversampling and a digital dual adaptive signal processing technique that provides a low mean squared error for cancellation together with a large processing gain. The system could achieve at least 11 bit equivalent dynamic range for the desired weak signals using two 5-bit ADC's and a 7-bit DAC. In general, the Effective Bits from Dynamic Range Reduction (EBDR) for the system is equal to, or more than N+M bits, where N and M are resolutions of the two ADC's used. The key components of the system are high speed medium resolution ADC's and they have been implemented to demonstrate the path to a low power small area solution. An asynchronous 1GS/s ADC with a peak SNDR of 31.5dB, ENOB 5.0 bits, is achieved by time interleaving two ADC's based on the binary equivalent successive approximation (SA) algorithm using a series capacitive ladder with input capacitance of 84fF. A simple extension of the SA algorithm essentially removes the ENOB degradation due to metastability from the comparator. The ADC's are fabricated in 65nm CMOS with an active area of 0.11mm2, with a total power consumption of 6.7mW. It is believed that the time domain approach for wideband, high dynamic range applications which has been explored in this thesis is a step towards the goal of a future radio system, in which the A/D conversion process is directly after the front-end low noise amplifiers.
Recycling and use of waste materials and by-products in highway construction: A synthesis of highway practice. Final report

The report on recycling and use of waste materials and by-products in highway construction will be of interest to administrators and policy makers; pavements, materials, geotechnical, and environmental engineers; and other professionals involved with highway design, construction, and maintenance. Information is provided on the technical, economic, and environmental aspects (including legislative and regulatory considerations) of recycling and on the specific applications of waste materials and by-products. Information is also provided on the quantities, characteristics, possible uses, current and past research activities, and actual highway construction use of each waste material or by-product. This information is classified into four broad categories based on source: agricultural, domestic, industrial, and mineral wastes.
Invisible experience to real-time assessment in elite tennis athlete training: Sport-specific movement classification based on wearable MEMS sensor data

This study examined the reliability of a tennis stroke classification and assessment platform consisting of a single low-cost MEMS sensor in a wrist-worn wearable device, smartphone, and computer. The data that was collected was transmitted via Bluetooth and analyzed by machine learning algorithms. Twelve right-handed male elite tennis athletes participated in the study, and each athlete performed 150 strokes. The results from three machine learning algorithms regarding their recognition and classification of the real-time data stream were compared. Stroke recognition and classification went through pre-processing, segmentation, feature extraction, and classification with Support Vector Machine (SVM), including SVM without normalization, SVM with Min–Max, SVM with Z-score normalization, K-nearest neighbor (K-NN), and Naive Bayes (NB) machine learning algorithms. During the data training process, 10-fold cross-validation was used to avoid overfitting and suitable parameters were found within the SVM classifiers. The best classifier was achieved when C = 1 using the RBF kernel function. Different machine learning algorithms’ classification of unique stroke types yielded highly reliable clusters within each stroke type with the highest test accuracy of 99% achieved by SVM with Min–Max normalization and 98.4% achieved using SVM with a Z-score normalization classifier.
An Approach to the Acquisition of Expert Knowledge

: This article presents the approach to the acquisition of expert knowledge and includes the following stages: (1) observation-verbal reporting, (2) obtainment of a record of the observation, (3) protocol analysis, (4) formal record of expert knowledge. The first part of the article discusses each element of our approach based on a real-time case study. Next, the structure and exemplar functionalities of the proposed information system for the acquisition of expert knowledge are presented. Our information system supporting the acquisition of expert knowledge, as presented here, is based on the example of service department workers but may be used in other areas where the procedures for performing any given activity are definable.
Artificial Neural Network Prediction of Chemical-Disease Relationships Using Readily Available Chemical Properties

Abstract : The natural environment is burdened with a broad range of toxic chemicals, and there is a need to develop a tool that can accelerate the pace at which we learn how chemicals impact disease. This work developed an artificial neural network (ANN) based model that constructed chemical-disease relationships for chemicals found in the Comparative Toxicogenomics Database. A new chemical classification system, based on the molecular weight, hydrogen donors, and hydrogen acceptors, was created to identify chemicals with a unique number that is directly related to these structural properties of the chemical. Diseases were grouped into 27 categories and the chemical-disease associations were made between the chemical and its associated disease category. The ANN model was successfully trained and tested to associated 75 chemical with the 27 disease categories. Simulations with training-validation-testing ratios of 70-15-15 percent produced coefficients of determination equal to 0.99, and the Levenberg-Marquardt backpropagation function provided the best network performance. To help validate the model, the ANN was also used to evaluate chemical-disease relationships for three uncurated chemicals. Results showed that ANNs have the potential to predict disease associations for uncurated chemicals and to guide research for curated chemicals that may require further toxicological testing.
Simulating Mistakes

The transmission of text by scribes introduces errors that often compound over time. Using the first book of Homer’s Iliad as a case study, we would like to propose a method to simulate this process using agent based models. In this paper we will first briefly explain general information about text transmission and the nature of the text we are working with. Then we will discuss the creation of an agent based model (ABM) in detail, as well as the problems encountered during development. We will continue by evaluating the results of the model and studying the influence of its parameters. To end this thesis we will then contrast this method with other Natural Language Processing approaches such as Machine Learning and Evolutionary Algorithms. The results seem to indicate that while ABMs could be useful in a text transmission context, the surrounding research needs further development to improve the quality of the model. On the whole, the usage of ABMs in text transmission is deemed a fruitful approach worthy of further investigation.
Study on Transport Airplane Unplanned Water Contact

Abstract : This study provides for an identification of accident scenario(s) and associated occupant risks and survival equipment needs, relating to the inadvertent or unplanned water contact of transport category airplanes. This identification was obtained, in part, from the results of contractual studies of transport accident data. The subject study concludes that while the unplanned water contact of a transport airplane occurs less frequent than corresponding ground contact, the impact loads are often higher, leading to greater fuselage damage. Also, the unplanned water contact occurs more frequent than a planned water landing (ditching) and usually involves adverse flooding conditions. These conditions, in turn, affect the ability of occupants to retrieve, deploy and/or don on-board floatation equipment.