Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards the automatic assessment of spatial quality in the reproduced sound environment

The research in this thesis describes the creation and development of a method for the prediction of perceived spatial quality. The QESTRAL (Quality Evaluation of Spatial Transmission and Reproduction using an Artificial Listener) model is an objective evaluation model capable of accurately predicting changes to perceived spatial quality. It uses probe signals and a set of objective metrics to measure changes to low-level spatial attributes. A polynomial weighting function derived from regression analysis is used to predict data from listening tests, which employed spatial audio processes (SAPs) proven to stress those low-level attributes. A listening test method was developed for collecting listener judgements of impairments to spatial quality. This involved the creation of a novel test interface to reduce the biases inherent in other similar audio quality assessment tests. Pilot studies were undertaken which established the suitability of the method. Two large scale listening tests were conducted using 31 Tonmeister students from the Institute of Sound Recording (IoSR), University of Surrey. These tests evaluated 48 different SAPs, typically encountered in consumer sound reproduction equipment, when applied to 6 types of programme material. The tests were conducted at two listening positions to determine how perceived spatial quality was changed. Analysis of the data collected from these listening tests showed that the SAPs created a diverse range of judgements that spanned the range of the spatial quality test scale and that listening position, programme material type and listener each had a statistically significant influence upon perceived spatial quality. These factors were incorporated into a database of 308 responses used to calibrate the model. The model was calibrated using partial least-squares regression using target specifications similar to those of audio quality models created by other researchers. This resulted in five objective metrics being selected for use in the model. A method of post correction using an exponential equation was used to reduce non-linearity in the predicted results, thought to be caused by the inability of some metrics to scrutinise the highest quality SAPs. The resulting model had a correlation (r) of 0.89 and an error (RMSE) of 11.06% and performs similarly to models developed by other researchers. Statistical analysis also indicated that the model would generalise to a larger population of listeners.
The New Orleans hurricane protection system : what went wrong and why

On the morning of August 29, 2005, Hurricane Katrina struck southeast Louisiana and triggered what would become one of the worst disasters ever to befall an American city. The devastation was so extensive, and the residual risk looms so ominous, that, more than a year later, the future of New Orleans remains clouded. The members of the ASCE Hurricane Katrina External Review Panel have conducted an in-depth review of the comprehensive work of the United States Army Corps of Engineers (USACE) Interagency Performance Evaluation Taskforce (IPET) to better understand this tragedy and prevent similar disasters from happening again. The report, "The New Orleans Hurricane Protection Systems: What Went Wrong and Why", focuses on the direct physical causes and contributing factors to the hurricane protection system failures. It was developed not to repeat the IPET information, but to interpret the broader significance of the findings. Written for both technical and general audiences, the report gleans valuable information related to the science and technology of hurricane flood protection as well as an overview of what caused the disaster. The "New Orleans Hurricane Protection Systems: What Went Wrong and Why" is a fascinating read, offering hope for not just the future of New Orleans, but for all other hurricane and flood-prone areas of the country.
KPsec: Secure End-to-End Communications for Multi-Hop Wireless Networks

The security of cyber-physical systems, from self-driving cars to medical devices, depends on their underlying multi-hop wireless networks. Yet, the lack of trusted central infrastructures and limited nodes' resources make securing these networks challenging. Recent works on key pre-distribution schemes, where nodes communicate over encrypted overlay paths, provide an appealing solution because of their distributed, computationally light-weight nature. Alas, these schemes share a glaring security vulnerability: the two ends of every overlay link can decrypt---and potentially modify and alter---the message. Plus, the longer overlay paths impose traffic overhead and increase latency. We present a novel routing mechanism, KPsec, to address these issues. KPsec deploys multiple disjoint paths and an initial key-exchange phase to secure end-to-end communications. After the initial key-exchange phase, traffic in KPsec follows the shortest paths and, in contrast to key pre-distribution schemes, intermediate nodes cannot decrypt it. We measure the security and performance of KPsec as well as three state-of-the-art key pre-distribution schemes using a real 10-node testbed and large-scale simulations. Our experiments show that, in addition to its security benefits, KPsec results in $5-15\%$ improvement in network throughput, up to $75\%$ reduction in latency, and an order of magnitude reduction in energy consumption.
RISK AND SAFETY ON THE ROADS: THE OLDER PEDESTRIAN

This report describes a study of the problems faced by the older pedestrian and ways in which such problems could be alleviated. There were 4 phases: (a) interviews to establish a picture of pedestrian activity among older people; (b) experimental measurement of older peoples' judgement of speed and distances; (c) the observation of older pedestrians crossing the road at sites identified as presenting difficulties; and (d) the formulation of recommendations based on an analysis of (a) to (c). A detailed account is given of the methods used in the study which took place in several districts of Newcastle- upon-Tyne. Recommendations are put forward in the areas of drivers' responsibilities, educational materials and publicity and specific improvements.
Assessing Sustainable Freight Policies

The main aim of the study was to examine transportation demand management strategies related to long haul freight. It investigates freight movements and truck vehicle miles traveled (TVMT) changes in response to certain transportation policies, including a national-level and two local policies. In the first scenario, the effects of Panama Canal expansion project and expected shifting of demands between ports on truck volumes of the interstate highway system are studied. This essentially results in a new freight origin and destination matrix that was consequently assigned to the highway network. Such a network analysis reveals the changes in the entire truck network and the congested areas, as well as the total Truck Mileage Traveled. In addition, establishing truck consolidation centers scenario was considered in that shipments that are less than truck load are banned from entering a specific region. The results show that such policies can potentially reduce the total Truck Mileage Traveled, and therefore generating less emission. The last policy prescription was to implement a truck curfew policy in Chicago region. The study examines the effects of such policies and presents sensitivity analysis with respect to each scenario. Furthermore, the study presents an efficient method for disaggregating Freight Analysis Framework (FAF) data. FAF provides estimates of tonnages and values for different types of commodities between states and major metropolitan areas. This database establishes a good resource for analyzing the movements and behavior of freight in the U.S. However FAF data is aggregated and transportation planners and decision makers need to disaggregate the data to obtain more detailed picture of freight movements in the U.S. The study successfully disaggregates FAF data into county level.
Prediction of gaze direction using Convolutional Neural Networks for Autism diagnosis

Autism is a developmental disorder that affects social interaction and communication of children. The gold standard diagnostic tools are very difficult to use and time consuming. However, diagnostic could be deduced from child gaze preferences by looking a video with social and abstract scenes. In this work, we propose an algorithm based on convolutional neural networks to predict gaze direction for a fast and effective autism diagnosis. Early results show that our algorithm achieves real-time response and robust high accuracy for prediction of gaze direction.
Detecting Patterns of Physiological Response to Hemodynamic Stress via Unsupervised Deep Learning

Monitoring physiological responses to hemodynamic stress can help in determining appropriate treatment and ensuring good patient outcomes. Physicians' intuition suggests that the human body has a number of physiological response patterns to hemorrhage which escalate as blood loss continues, however the exact etiology and phenotypes of such responses are not well known or understood only at a coarse level. Although previous research has shown that machine learning models can perform well in hemorrhage detection and survival prediction, it is unclear whether machine learning could help to identify and characterize the underlying physiological responses in raw vital sign data. We approach this problem by first transforming the high-dimensional vital sign time series into a tractable, lower-dimensional latent space using a dilated, causal convolutional encoder model trained purely unsupervised. Second, we identify informative clusters in the embeddings. By analyzing the clusters of latent embeddings and visualizing them over time, we hypothesize that the clusters correspond to the physiological response patterns that match physicians' intuition. Furthermore, we attempt to evaluate the latent embeddings using a variety of methods, such as predicting the cluster labels using explainable features.
A Combined Expert System/Modelling Approach to the Adaptive Scheduling of Stainless Steel Rolling

A knowledge based expert system is outlined which provides consistent reduction schedules for the cold rolling of stainless steel strip. The system combines the heuristic knowledge of the experienced operators with deeper physical models from both the rolling theory and metallurgical domains. The system is being designed to provide the initial mill setup schedule, reactive reschedules and assistance in the subsequent on-line control.
Parameterized Algorithms for Power-Efficiently Connecting Sensor Networks: Theory and Experiments

We study an NP-hard problem motivated by energy-efficiently maintaining the connectivity of a symmetric wireless communication network: Given an edge-weighted $n$-vertex graph, find a connected spanning subgraph of minimum cost, where the cost is determined by letting each vertex pay the most expensive edge incident to it in the subgraph. On the negative side, we show that $o(\log n)$-approximating the difference $d$ between the optimal solution cost and a natural lower bound is NP-hard and that, under the Exponential Time Hypothesis, there are no exact algorithms running in $2^{o(n)}$ time or in $f(d)\cdot n^{O(1)}$ time for any computable function $f$. Moreover, we show that the special case of connecting $c$ network components with minimum additional cost generally cannot be polynomial-time reduced to instances of size $c^{O(1)}$ unless the polynomial-time hierarchy collapses. On the positive side, we provide an algorithm that reconnects $O(\log n)$ connected components with minimum additional cost in polynomial time. These algorithms are motivated by application scenarios of monitoring areas or where an existing sensor network may fall apart into several connected components due to sensor faults. In experiments, the algorithm outperforms CPLEX with known ILP formulations when $n$ is sufficiently large compared to $c$.
Comparing the internet to others sources of information for acquiring knowledge on Takaful among Prudential BSN takaful agents

Malaysian Takaful industry is progressively taking innovative steps to improvise their marketing efforts via the introduction of Wakala system (agency system). Agents as one of the distribution channel for the industry play a prominent role in educating the society about the objectives and concept of Takaful. This effort may increase the awareness of the society about the Islamic insurance which remain low previously. Thus, this study is an attempt (1) to explore the sources of information that influencing the knowledge of Takaful agents; (2) to compare the contribution of the Internet and other sources of information towards understanding the objectives and concepts of Takaful by Takaful agents; and (3) to analyze the relationships between the usage of the Internet and other sources with the acquisition of knowledge on objectives and concepts of Takaful. A preliminary study was conducted with 50 Takaful agents from Prudential BSN Takaful Berhad. Data were collected through survey research design using questionnaire as the research instrument. Data gathered will be analyzed using SPSS WIN 17 for both descriptive statistics (frequency, percentage, mean and standard deviation) and inferential statistics (paired t-test and step-wise regression analysis).
Population Synthesis with Region-Level Control Variable Aggregation

This paper details the development of a new, fully-customizable population synthesis program which has been designed to be used for any geographic area or input variables desired. The design addresses several important issues that have been raised regarding other population synthesis methods. The false zero-cell problem has been a major concern in the development of most population synthesis procedures and can be a source of significant error when many control variables are used. To address this problem, a routine was developed that allows for the aggregation of control variable categories during execution at the region-level based on a user-controlled aggregation threshold parameter input, which reduces the areas where false zero-cells are most likely to occur. This element of the procedure also greatly eases the task of data preparation for use in the model. As part of the study, new validation methods were developed and used to compare the new procedure against other procedures and known test variable distributions. Finally, detailed analysis regarding the trade-off between model complexity and computational effort was also undertaken. The use of these new routines and validation methods along with an understanding of the trade-off between model complexity and computational effort will allow for the development of more realistic synthetic populations.
PROGRESS WITH RURAL TRAFFIC SIMULATION

This paper reviews progress in rural traffic simulation, with particular reference to the Australian Road Research Board Model, TRARR. A number of major simulation packages are identified which have been applied to practical studies of rural traffic performance in at least eight countries around the world. These models have many common features, as well as common areas requiring further research and validation. In this context, the current status of TRARR is discussed. Recent studies have applied the model to investigations of specific road improvement proposals and general concepts such as level of service. The model provides detailed comparisons of the changes in traffic performance which result from changes in road or traffic conditions. While further calibration and validation are required, tests have shown that errors in simulation results are quite small, especially when compared with uncertainties in other estimates required for road evaluation. In applying TRARR to specific studies, the procedures for data input have been refined to enable easier use of the model by unfamiliar users. The simulation package is now in a form which may be used by road authorities to compare alternative strategies (a). The number of the covering abstract of the conference is TRIS No. 368448. (TRRL)
EFFECTS OF DYNAMIC LOADS ON PERFORMANCE OF ASPHALT CONCRETE PAVEMENTS

To determine the influence of dynamic loading on pavement response, an analytical and a laboratory study were undertaken. In the analytical study, temporal and spatial variation of stresses and deformations in a pavement system, resulting from dynamic loading conditions, were estimated using the computer program SAPSI. To compute these stresses and deformations, elastic and damping characteristics of various materials constituting pavement sections were defined by a laboratory investigation that provided such data for an asphalt concrete (AC) and a fine-grained soil (silty clay) for a limited range in service conditions. With the SAPSI program, a representative pavement system consisting of an AC layer resting directly on silty clay subgrade was analyzed to determine the pavement life that might result using actual load histories for three tandem-axle suspensions as compared to that obtained for the same axle with a uniform static load. Results of the dynamic analyses suggest that pavement life is reduced when dynamic effects are considered, and the magnitude of reduction is dependent on the tandem-axle suspension. The largest reduction in pavement life was obtained for the axle with the walking beam suspension. Comparable smaller reductions, as compared to the static case, were obtained for the torsion bar and four-leaf spring suspensions.
Proceedings of the XXVII International Conference on High Energy Physics : 20-27 July 1994, Glasgow Scotland, UK

This two-volume set contains the invited and contributed papers from the 1994 'Rochester' Conference on High Energy Physics, held 20-27 July 1994 in Glasgow, Scotland. This most prestigious of the international conferences on elementary particle physics brought together over 1000 researchers in the field from leading universities and research centres in 47 countries throughout the world. The volumes contain over 250 contributed papers from the parallel sessions of the conference giving details of latest research results in all areas of the subject. These and other recent results were collected and reviewed by the speakers in the 24 plenary sessions, whose talks were subsequently written up in a definitive way and assembled here. These reviews give a comprehensive and state-of-the-art coverage of the entire field in 1994.Important topics include the latest experimental results from electron-proton collisions at HERA and electron-positron collisions at CERN. Of special interest is the first concrete experimental evidence for the 'top' quark, found in proton-proton collisions at Fermilab. This quark completes the set of six that are predicted by the Standard Model, and its confirmation will mark a decisive moment in the history of physics.This book is an essential reference for libraries and researchers in high energy physics, nuclear physics, astrophysics and mathematical physics.
THE WIDE-AREA ENERGY STORAGE AND MANAGEMENT SYSTEM PHASE II Final Report - Flywheel Field Tests

Independent System Operator, for providing the project team with organizational support, advice, and guidance essential to this work. Abstract The higher penetration of intermittent generation resources (including wind and solar generation) in the Bonneville Power Administration (BPA) and California Independent System Operator (CAISO) balancing authorities (BAs) raises the issue of requiring expensive additional fast grid balancing services in response to additional intermittency and fast up and down power ramps in the electric power system. The overall goal of the wide-area energy management system (WAEMS) project is to develop the principles, algorithms, market integration rules, a functional design, and technical specifications for an energy storage system to cope with uncertainties and unexpected rapid changes in renewable generation power output. The resulting WAEMS system will store excess energy, control dispatchable load and distributed generation, and use inter-area exchange of the excess energy between the CAISO and BPA BAs. A further goal is to provide a cost-benefit analysis and develop a business model for an investment-based practical deployment of such a system. A major goal of the WAEMS project is to minimize the balancing effort by developing a centralized control system that operates energy storage devices in conjunction with conventional generators to provide fast balancing services that can be shared among balancing authorities. The idea is based on coordination of traditional services (provided by conventional generation) and energy storage. In Phase II of the project described in this report, a prototype WAEMS configuration consisting of a hydro electric plant and a flywheel energy storage was field tested using actual area-control-error and regulation signals provided by BPA and CAISO. The results were used to evaluate the performance and economics of the flywheel-hydro regulation service. The performance evaluation shows an excellent performance of the WAEMS control algorithm, which separates the faster regulation effort provided by the energy storage from the slower one provided by a conventional regulating unit. The WAEMS combined service is not strictly constrained by energy storage limits because the hydro plant supports the desired flywheel's energy level. In addition, the WAEMS combined service has the same fast-response characteristic (within 6 seconds) as that provided by the flywheel energy storage alone. Furthermore, the WAEMS control algorithm reduces wear and tear on the hydro unit and allows the hydro unit to operate closer to its preferred operating point. The breakeven price for flywheel energy storage to provide bi-directional service (1 MW regulation-up and ± …
SRIN: A New Dataset for Social Robot Indoor Navigation

Generating a cohesive and relevant dataset for a particular robotics application is regarded as a crucial step towards achieving better performance. In this communication, we propose a new dataset referred to as SRIN, which stands for Social Robot Indoor Navigation. This dataset consists of 2D colored images for room classification (termed SRIN-Room) and doorway detection (termed SRIN-Doorway). SRIN-Rooms has 37,288 raw and processed colored images for five main classes: bedrooms, bathrooms, dining rooms, kitchens, and living rooms. The SRIN-Doorway contains 21,947 raw and processed colored images for three main classes: no-door, open-door and closed door. The main feature of SRIN dataset is that its images have been purposefully captured for short robots (around 0.5-meter tall) such as NAO humanoid robots. All images of the first version of SRIN were collected from several houses in Vancouver, BC, Canada. The methodology of collecting SRIN was designed in a way that facilitates generating more samples in the future regardless of where the samples have come from. For a validation purposes, we trained a CNN-based model on SRIN-Room dataset, and then tested it on Nao humanoid robot. The Nao prediction results in this paper are presented and compared with the prediction results using the same model with Places-dataset. The results suggest an improved performance for this class of humanoid robots.
Hydrodemolition for Removing Concrete

Hydrodemolition is a relatively new technology for the removal of concrete. First used in Italy in 1979 -- with prototype equipment -- to remove concrete on the Viadotto del Lago, its development was slow until 1984, when it was introduced in Canada and Sweden. Only within the last decade has it been commonly used. Hydrodemolition involves impingement of a discrete blast of water under very high pressure in a controlled manner. The concrete is disintegrated into generally small rubble as a result of both the impact of the water onto the surface and the pressurization of internal pores, cracks, and voids.