Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors contributing to pedestrian involvement in road crashes

An important segment of a recent in depth, on scene investigation of road crashes involving pedestrians was the isolation of factors contributing to the crash. These factors were classified as: (a) main, (b) aggravating, or (c) uncertain, the last classification indicating a high level of uncertainty surrounding either the existence or the contribution of a particular factor. The distinction between (a) and (b) factors was aimed at separating those factors (a) which were considered to have precipitated the crash from those factors (b) which aggravated the situation. The results indicated that nearly all the (a) factors were behaviourally oriented and that more of these factors were attributed to the pedestrians themselves than to the drivers/ riders who collided with them. When the (b) factors were considered, there were again a large number of behavioural factors. These were more evenly distributed between the pedestrians and the motorists. There were also seen to be a large number of traffic engineering (b) factors and most of these were driver/ rider related. Mutual visibility factors stood out and this was consistent with the relatively large number of collisions attributable to obscured vision carelessness. The actual distribution of factors is presented and the details are discussed. Finally the special psychological consequences of pedestrian collisions as they arose in this in depth study, are discussed.
Implication of Buffer Zones Delineation Considering the Landscape Connectivity and Influencing Patch Structural Factors in Nature Reserves

Since habitat fragmentation results in species losses worldwide, considering the influence of buffer zones on the maintenance of connectivity provides a new perspective for buffer delimitation. In our study, the implications of buffer zones around nature reserves were studied at four sites in Fuzhou from the perspective of landscape connectivity based on a distance threshold of 1 km. We applied Graph-based connectivity indices at the landscape level and patch level to reveal the overall connectivity and patterns of change in patch importance for maintaining connectivity with various buffer zones. Based on the results of these analyses, we showed the relationship between structural factors and changes in patch importance by Spearman correlation analysis and redundancy analysis. The results indicate that in the sites with smaller habitat proportion (HP), the connectivity is relatively lower, and the changes in patch importance will be greater when the buffer zone increases. Different buffer zone sizes are suggested in four sites to maximize its benefits. Relatively small patches with high shape complexity and close proximity to patches outside the boundary contribute greatly to connectivity by acting as stepping stones.
MOTORIST UNDERSTANDING OF AND PREFERENCES FOR LEFT-TURN SIGNALS

A survey of licensed drivers was conducted at the 1988 Indiana State Fair to determine motorists' understanding of and preferences for left-turn signal alternatives including permissive, protected, and both protected and permissive (p/p) signals, and leading and lagging phase sequences. Survey responses were received from a diverse but generally representative sample of over 400 people. Statistics such as the respondent error rate during the understanding portion of the survey consistently indicated that the survey data were not biased in any substantive way. Several notable results emerged from the analysis of the survey responses. The protected signal was by far the best understood, whereas the p/p was the most often misunderstood. The Left Turn Yield on Green sign proved more confusing than the other p/p sign conditions tested, including the no sign condition. Among signals, the protected was most often preferred, and the permissive proved the least popular. For many reasons, the leading sequence was preferred by more respondents than the lagging sequence.
Voltage Control using Artificial Neural Network in A DC/AC Microgrid with Distributed Generation

Microgrid is gaining importance and attraction by researchers all over the world as a replacement for conventional grid especially in the remote areas. But due to the continuously varying nature of the renewable energy sources as well as the load, the control of microgrid is a vital task both in standalone mode and grid connected mode. This paper investigates the application of Artificial Neural Network (ANN) for Voltage control in a DC/AC microgrid. The system considered consists of PV, boost converter and an Inverter. The triggering pulse for the boost converter connected to the PV system is obtained by the ANN which is trained to track the maximum power point (MPP) under variable insolation as well as variable temperature conditions. Compared to other conventional methods, ANN trained MPPT is able to track the changes in the load with lesser oscillations and peak overshoot. Also this paper investigates the control of inverter in the grid forming mode by applying ANN. The performance and the stability of the microgrid is enhanced by adopting additional control strategies like getting the reference current signal also from the AC grid, feeding the integration of error signals along with the error themselves as well as by giving the disturbance voltage at the ANN output for better control. The result shows that the ANN controlled inverter is able to maintain the voltage at the required nominal value following the disturbance.
HOV compliance monitoring and the evaluation of the HERO hotline program. Final report

This report discusses the development of recommended and alternative systems for monitoring the use of HOV lanes and compliance with HOV occupancy regulations in the Seattle metropolitan area. The report includes a state-of-the-art review of techniques for monitoring HOV lane use and the results of tests of the most promising of these techniques. In addition, the report presents a review of the existing HERO (HOV violation reporting hotline) program, including the results of a 500-person telephone survey on the public's awareness of and attitude toward the HERO program and HOV facilities in general. Finally, the report describes software written to ease the storage of HERO data and improve the reporting of HERO statistics.
Improving pedestrian navigation on iPhone in urban environments using deduced reckoning and turn detection

Pedestrian navigation on an iPhone today does not provide the accuracyto place the pedestrian on the correct side of a street. A deciding issuethat prevents sufficient accuracy is the errors that occur when usingsatellite positioning in urban environments. Another big problem isthat heading data has shown a tendency to be inaccurate.Chapter 2 explains satellites navigation, navigation techniques, andsensors. Chapter 4 describes how a prototype was developed. The prototypeuses deduced reckoning and turn detection to navigate a pedestrianroad network, without relying on satellite signals. The prototype is intendedto run on iPhone 5 and utilizes accelerometer, magnetometer(compass), and gyroscope data together with detailed data about thepedestrian network to accurately track a pedestrian. It features a turndetection method that makes it possible to perform a logical traversalof the road network, together with step detection and step length estimationto move around.The turn detection method was very effective and gave good resultswhen combined with logical traversal. For the two routes that weretested the total error in distance estimation was about 3~7 % and forboth routes a close fit to the actual routes was achieved. For individualparts of the routes the largest distance estimation errors varied between3 and 15 %.
Technology, Management and Society

The relationship of humans to technology and management is an ever-growing theme in today's world of ubiquitous mobile devices, constant Internet access, and omnipresent digital business tools. Fifty years ago Peter F. Drucker was already at the forefront of these questions, probing the ways in which management and technology struggle with the shared task of making us more productive. His thinking on how management and technology affect quality of life, what efficiency means versus productivity, and whether management can ever be a true science is as relevant today as it was then. These twelve essays exhibit, as do all Peter Drucker's writings, crisp reasoning, projection and analysis of short-term realities and examination of long-range goals and possibilities, and a unique voice that makes all these ideas accessible.
Accelerated brain tumor dynamic contrast‐enhanced MRI using Adaptive Pharmaco‐Kinetic Model Constrained method

In brain tumor, dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) spatiotemporally resolved high‐quality reconstruction which is required for quantitative analysis of some physiological characteristics of brain tissue. By exploiting some kind of sparsity priori, compressed sensing methods can achieve high spatiotemporal DCE‐MRI image reconstruction from undersampled k‐space data. Recently, as a kind of priori information about the contrast agent (CA) concentration dynamics, Pharmacokinetic (PK) models have been explored for undersampled DCE‐MRI reconstruction. This paper presents a novel dictionary learning‐based reconstruction method with Adaptive Pharmaco‐Kinetic Model Constraints (APKMC). In APKMC, the priori knowledge about CA dynamics is incorporated into a novel dictionary, which consists of PK model‐based atoms and adaptive atoms. The PK atoms are constructed based on Patlak model and K‐SVD dimension reduction algorithm, and the adaptive ones are used to resolve PK model inconsistencies. To solve APKMC, an optimization algorithm based on variable splitting and alternating iterative optimization is presented. The proposed method has been validated on three brain tumor DCE‐MRI data sets by comparing with two state‐of‐the‐art methods. As demonstrated by the quantitative and qualitative analysis of results, APKMC achieved substantially better quality in the reconstruction of brain DCE‐MRI images, as well as in the reconstruction of PK model parameter maps.
Prediction of Option Price using Ensemble of Machine Learning Algorithms for Indian Stock Market

The non-deterministic behavior of stock market creates ambiguities for buyers. The situation of ambiguities always finds the loss of user financial assets. The variations of price make a very difficult task to predict the option price. For the prediction of option used various non-parametric models such as artificial neural network, machine learning, and deep neural network. The accuracy of prediction is always a challenging task of for individual model and hybrid model. The variation gap of hypothesis value and predicted value reflects the nature of stock market. In this paper use the bagging method of machine learning for the prediction of option price. The bagging process merge different machine learning algorithm and reduce the variation gap of stock price.
Mechanical Fault Diagnosis Using Support Vector Machine

The Support Vector Machine (SVM) is a machine learning algorithm based on the Statistical Learning Theory ( SLT) , which can get good classification effects even with a few learning samples. SVM represents a new approach to pattern classification and has been shown to be particularly successful in many fields such as image identification and face recognition. It also provides us with a new method to develop intelligent fault diagnosis. This paper presents a SVM-based approach for fault diagnosis of rolling bearings. Experimentation with vibration signals of bearings is conducted. The vibration signals acquired from the bearings are used directly in the calculating without the preprocessing of extracting its features. Compared with the methods based on Artificial Neural Network (ANN), the SVM-based meth-od has desirable advantages. It is applicable for on-line diagnosis of mechanical systems.
Spatial Ontology for the Production Domain of Petroleum Geology

The availability of useful information for research strongly depends on well structured relationships between consistently defined concepts (terms) in that domain. This can be achieved through ontologies. Ontologies are models of the knowledge of specific domain such as petroleum geology, in a computer understandable format. Knowledge is a collection of facts. Facts are represented by RDF triples (subject-predicate-object). A domain ontology is therefore a collection of many RDF triples, which represent facts of that domain. The SWEET ontologies are upper or top-level ontologies (foundation ontologies) consisting of thousands of very general concepts. These concepts are obtained from of Earth System science and include other related concepts. The work in this thesis deals with scientific knowledge representation in which the SWEET ontologies are extended to include wider, more specific and specialized concepts used in Petroleum Geology. Thus Petroleum Geology knowledge modeling is presented in this thesis. INDEX WORDS: Ontology, Semantic Web, OWL, Class, Subclass, Petroleum Geology, SWEET ontology SPATIAL ONTOLOGY FOR THE PRODUCTION DOMAIN OF PETROLEUM GEOLOGY
Anti-Stigma Interventions to Encourage HIV Testing in Vulnerable Households in Mozambique

This document outlines the pre-analysis plan for the project “Anti-Stigma Interventions to Encourage HIV Testing in Vulnerable Households in Mozambique. ” The primary objective of the study is to test whether providing information that intends to relieve individuals concerns about HIV-related social stigma improves HIV testing rates in vulnerable households in Mozambique. Participants were randomly assigned at the household level to one of the two study groups:
The Story of Metro: Transportation and Politics in the Nation's Capital

This book provides a brief history of Washington DC's transportation story, from the first horse drawn streetcars which appeared in 1862 to the design, construction and opening of the city's metro. Covered are such topics as the city before metro, the early plans, metro's engineering and architectural design plans and metro as an operational and viable transit alternative. Of particular interest are details about the operations of metro. Important dates, routes, how the trains work and what Central Control does provides an enlightening account of the functioning aspect of this immense and multifaceted project which has been so basic to the development and lifestyle of the nation's capital and surrounding metropolitan region.
Psychological Features in Breast Cancer Patients, Depending on the Presence of Comorbid Post-Traumatic Stress Disorder

The paper presents the results of a clinical-psychopathological and experimental psychological study carried out on 91 women with breast cancer (aged 35—65, mean age 55.8±11.08 years). The sample was divided into two groups, 51 women with a diagnosed posttraumatic stress disorder (PTSD) developed as a result of their illness and 40 stress-resistant women. The author’s semi-structured anamnestic interview was used to study the clinical and socio-psychological characteristics of patients. Methods: Trauma Screening Questionnaire (Brewin et al., 2002), Impact of Event Scale (Tarabrina, 2001), Type of Attitude to the Disease measure (Vasserman et al., 2014), G. Ammon’s Ego Structure Test (Tupitsyn et al., 1998), Mental Health Assessment measure (Bocharov, Tupitsyn, 1999), The Personal Views Survey III- R (Leontiev, Rasskazova, 2006), Experiences in Close Relationships (Kazantseva, 2008). Results: In patients with PTSD, low parameters of resilience, the dominance of maladaptive types of attitude to the disease, and deficient and destructive personality structures (aggression, anxiety, deficient external and internal boundaries of the self, and destructive narcissism and sexuality) were revealed.
Prediction of the inversion load of a circular tube

This study i s concerned with t h e p l a s t i c deformation process encountered i n t h e inversion or turning inside out of a circular tube. The load required t o cause inversion i s derived analytically from elementary expressions f o r p l a s t i c energy absorbed during uniaxial p l a s t i c straining. Analytical results a r e compared w i t h the r e s u l t s of experiments conducted concurrently, and with previously reported results. Experimental values of inversion load agreed with analytical predictions within 10 t o 30 percent.
Stand Up and Fight! The Creation of U.S. Security Organizations, 1942-2005

Abstract : Starting a new security organization is a difficult business. Hundreds of questions come in staccato bursts; each requires a decision and each decision takes on the permanence of tradition. Tradition becomes culture and a new organization becomes the sum of those early decisions. In this collection of essays, historians, most of them military officers, try to grapple with the challenges of creating new security organizations. Our aim is to help those few men and women who start new governmental bodies charged with protecting the American people to make sound and historically informed decisions by highlighting several common themes for consideration. We began this project in early-2011 when Colonel Greg Conti of West Point s Information Technology Operations Center asked us to assist the fledgling Cyber Command (USCYBERCOM) as it sprang into existence under the command of General Keith Alexander. A series of cyber attacks around the world had galvanized Congress and the Department of Defense to act. Colonel Conti, working for General Alexander, wondered if historians might offer useful perspectives as USCYBERCOM made quick decisions about its future. In response to Colonel Conti s request, 14 historians at West Point, NY, volunteered to look at a variety of security organizations created since World War II. We looked at functional commands and regional commands, commands that thrived and commands that died, commands created in response to technological changes and those created during bursts of reform. We chose a wide variety of different commands to allow for the broadest view possible. Our analysis produced no easy answers on how to create an effective, efficient, stable and politically viable security organization. There proved to be no readymade, shake and bake formula. Smart people made the best decisions they could with limited information and time. Often, those decisions helped create great organizations.
The effect of road roughness (and test speed) on GripTester measurements

This research investigated the effect of road roughness, macrotexture and testing speed on GripTester measurements. Field tests were conducted by the GripTester at various test speeds on sites with varying road roughness in South Auckland. The variables - road roughness, texture and test speeds - were measured and plotted against each other along with grip number (GN) as obtained from the GripTester. Tests with the DF Tester were also carried out at one site and directly correlated with GripTester results at various towing speeds. It was found the GN might not be dependent on test speeds while testing at speeds lower than 75km/h; however, an inverse relationship occurred at higher speeds, on a limited number of test sites. Road roughness was found to have no effect on GripTester measurements and texture appeared to be a minor factor. In conclusion, the explanatory variables on the GN are test speed and perhaps texture. However, unaccounted factors that are specific to test sites proved to have some degree of effect. Future research recommendations include searching for better controlled test sites and larger samples to clarify the effect of texture on the GN and to expose unidentified factors that can influence GripTester output.
ANALYSIS AND BEHAVIOR OF BURIED CULVERTS WITH SLOTTED JOINTS

Corrugated metal culverts with circumferentially slotted bolt-hole-connections, a new concept in culvert technology, have the potential to significantly reduce thrust stress (ring compression) in deep embankment installations. From a design viewpoint, this means that deeper burial depths can be achieved or lighter-gauge metal can be used or both. The results of a comprehensive investigation on the structural behavior, analysis, and design of slotted-joint culvert installations are summarized. The scope includes data gathering, experimental testing, analytical model development, verification with field data, and guidelines for design. Based on laboratory load-deformation tests, slotted-joint behavior is simulated with a five-parameter model and incorporated into the CANDE computer program with two methods for solving the culvert-soil boundary value problem: a modified elastic solution and a finite-element procedure. The latter method, which offers sophisticated modeling capabilities (e.g., incremental construction, nonlinear soil models, and frictional interfaces), is shown to correlate well with experimental field data. The former method, although more idealized, provides a keen insight into fundamental behavioral aspects of slotted-joint culverts and is an extremely useful design aid. Both analytical and experimental findings demonstrate that the slotted bolt-hole concept is extraordinarily successful in reducing ring compression. In many cases allowable fill height may be increased 40 ft or more.
Using primary afferent neural activity for predicting limb kinematics in cat

Kinematic state feedback is important for neuroprostheses to generate stable and adaptive movements of an extremity. State information, represented in the firing rates of populations of primary afferent neurons, can be recorded at the level of the dorsal root ganglia (DRG). Previous work in cats showed the feasibility of using DRG recordings to predict the kinematic state of the hind limb using reverse regression. Although accurate decoding results were attained, these methods did not make efficient use of the information embedded in the firing rates of the neural population. This dissertation proposes new methods for decoding limb kinematics from primary afferent firing rates. We present decoding results based on state-space modeling, and show that it is a more principled and more efficient method for decoding the firing rates in an ensemble of primary afferent neurons. In particular, we show that we can extract confounded information from neurons that respond to multiple kinematic parameters, and that including velocity components in the firing rate models significantly increases the accuracy of the decoded trajectory. This thesis further explores the feasibility of decoding primary afferent firing rates in the presence of stimulation artifact generated during functional electrical stimulation. We show that kinematic information extracted from the firing rates of primary afferent neurons can be used in a 'real-time' application as a feedback for control of FES in a neuroprostheses. It provides methods for decoding primary afferent neurons and sets a foundation for further development of closed loop FES control of paralyzed extremities. Although a complete closed loop neuroprosthesis for natural behavior seems far away, the premise of this work argues that an interface at the dorsal root ganglia should be considered as a viable option.