Miracle-dz/UniFAR-FTUs huggingface dataset:
A framework for optimal design of low-power FIR filters

Banerjee, Aparajita M.S.E.C. E, Purdue University, August 2015. A Framework for Optimal Design of Low-power FIR Filters. Major Professor: Kaushik Roy. Approximate Computing has emerged as a new low-power design approach for application domains characterized by intrinsic error resilience. Digital Signal Processing (DSP) is one such domain where outputs of acceptable quality can be produced even though the internal computations are carried out in an approximate manner. With the ever increasing need for data rates at lower power usage; the need for improved complexity reduction schemes for DSP systems continues. One of the most widely performed steps in DSP is FIR filtering. FIR filters are preferred due to their linear phase, stability and ease of implementation. In order to build low-power DSP systems; there have been many efforts to reduce the implementation cost of FIR filters with little loss of quality. However most of the implementations fail to guarantee an optimum solution. In this thesis, we developed a new mathematical framework for designing FIR Filter with reduced complexity so as to improve performance at reduced power. Given some approximate circuits, the idea is to make the design process aware of them. The proposed methodology is formulated as a linear programming problem that minimizes the Chebyshev error. The impact of hardware approximations is quantified as a function of filter coefficients and converted into the frequency domain. This error can be potentially recovered by intelligently designing a framework that solves the filter design problem with “error due to complexity reduction” as an additional constraint. The design methodology generates a set of filter coefficients that satisfies the filter specifications and adheres to a low-power implementation.By doing this in a systematic and guided manner, we can achieve energy efficiency at acceptable quality.
Higher order weak Galerkin methods for the Navier–Stokes equations with large Reynolds number

In this article, we provide a class of numerical schemes to solve the steady state and non‐steady state Navier–Stokes equations with large Reynolds number. The high order weak Galerkin methods are numerically proposed and tested. We numerically find that the stabilizing term has a great impact on the robustness of the Jacobian matrices associated with the Newton's method in the procedure of solving the discrete nonlinear systems generated by weak Galerkin discretizations, especially for the case with large Reynolds number. The numerical investigations of several benchmarks are then carried out to demonstrate the efficiency and robustness of our proposed numerical methods. The errors for the Taylor–Green vortex flow are computed and compared with different weak Galerkin techniques. The lid driven flow and the flow around a cylinder are further numerically investigated and compared with existing references. The Navier–Stokes equations with large Reynolds number can be efficiently solved by the high order weak Galerkin methods with proper stabilizers.
A review of applications of artificial intelligence techniques to naval ESM signal processing

The Admiralty Research Establishment (ARE) is supporting research into ESM (electronic support measures) digital signal processing techniques to provide the functions of automatic detection, surveillance and identification of radar emitters for application in future naval ESM systems. The use of artificial intelligence techniques is believed to be the solution to current ESM signal processing problems. Initial ARE work has confirmed this belief and more extensive projects are now being pursued. The value of this software work to the development of operational ESM system is, however, highly dependent on the success of parallel research work to implement such software on real time hardware. >
Predicting CBR value of stabilized pond ash with lime and lime sludge using multivariate adaptive regression splines

In this study, multivariate adaptive regression splines (MARS) model with order two and three were developed for predicting the California bearing capacity (CBR) value of pond ash stabilized with lime and lime sludge. To this aim, the model had five variables named maximum dry density, optimum moisture content, lime percentage, lime sludge percentage, and curing period as inputs, and CBR as output variable. MARS-O3 has the best results, which its R2 stood at 0.9565 and 0.9312, and PI 0.0709 and 0.1061 for the training and testing phases, respectively. In both developed models, the estimated CBR values in training and testing stages specify acceptable agreement with experimental results, representing the workability of proposed equations for predicting the CBR values with high accuracy. Comparison of two developed equations supplied that MARS-O3 has a better result than MARS-O2. Based on error curves, the MARS-O3 model results in the lowest error percentage in the CBR predicting process, providing roughly accurate prediction than those of the rest developed methods specified. Therefore, MARS-O3 could be recognized as the proposed model.
Bulk water treatment unit performance: For the cameras or the community?

As humanitarians we must be deeply concerned about using the most effective solutions for saving lives and reducing morbidity, whilst working within reasonable cost envelopes. In this respect it is critical to place the brightest spotlight upon the practice of using bulk water treatment units (BWTU), as witnessed most recently on a massive scale in the Pakistan floods of 2010. There, as in other huge crises, many BWTUs were deployed by donors and other agencies, sometimes as a knee-jerk reaction to an overwhelming crisis. These appear to offer neat ‘plug and play’ solutions that also happen to be very media friendly. However, some of the BWTUs sent to flood-affected areas of Pakistan in 2010 demonstrate that there is an absence of appropriate selection criteria for BWTUs and the significant limitations on their use are not fully understood. Though the evidence gathered is partial, there is enough to suggest that some agencies are engaging in poor practice.
Disentangling the Impact of the Transatlantic Slave Trade in African Diaspora Populations from a Genomic Perspective

study of the four major Noir Marron communities. The authors analysed genome-wide SNP data (around five million SNPs) of 107 African-descendants (71 Noir Marron from French Guiana and Suriname: 23 Alukus, 23 Ndjukas, 19 Saramakas, and 6 Paramakas; 16 African-Brazilians from Rio de Janeiro; and 20 African-Colombians the Chòco and Antioquia departments in Colombia). The authors compared their African genomic diversity with genome-wide SNP data of 124 individuals from West Africa (Benin, Ivory Coast, and Mali) analysed for the first time in that study, and genomic data of 2,054 African individuals obtained from previous studies.
The evolution of choice set formation in dwelling and location with rising prices: A decadal panel analysis in the Greater Toronto Area

Home location choice is based on both the characteristics of the dwelling (e.g., size, style, number of bedrooms) and the location (e.g., proximity to work, quality of schools, accessibility). Recent years have seen a steep increase in the price of housing in many major cities. In this research, we examine how these price increases are affecting the types of dwelling and locations considered by households. A large sample of real estate listings from 2006 and 2016 from the Greater Toronto Area is used to develop the empirical models. Two recently developed discrete choice models are used in the study: a nested logit model with latent class feedback (LCF) and a semi-compensatory independent availability logit (SCIAL) model. A method of alternative aggregation is proposed to overcome the computational hurdle that often impedes the estimation of choice set models. We find a significant increase in the probability of larger households considering townhouses and apartments over detached single-family dwellings between 2006 and 2016.
How Driving Simulator Data Quality Can Be Improved

This paper examines problems commonly found in fixed-based driving simulators that have lead to imperfect replication of real driver behavior and performance, and solutions for those problems. Those problems include (1 and 2) the standard deviation of lane position is either too small or too large, (3) subjects drive all over the world, and (4) too fast, (5) subjects slow down too much of follow a lead vehicle from too far when distracted, (6) speeds are too steady, and (7) drivers take too long to respond to signs. Some of those problems occur because sometimes vehicles are too stable (time-to-time crossing values are too large) or, because there are no handling imperfections (e.g., mismatched tire pressures), road imperfections (e.g., potholes), or environmental imperfections (lateral or head/tailwinds)). Also worth considering is adjusting the feedback to the dirver (e.g., boost the steering wheel torque to compensate for the lack of motion cues and shaking the steering wheel when driving on a rough surface such as a shoulder or off-the-road) to encourage subject to drive on the road.
Virtual Clay Modeling System with 6-DOF Haptic Feedback

This paper describes an innovative free-form modeling system, Virtual Clay Modeling System (VCMS), in which users can directly manipulate the shape of a virtual object like a clay model in real world. With this system, some disadvantages of interaction with computer aided industry design (CAID) systems can be resolved. In order to enhance the immersion feelings and improve the controlling abilities to cut, paste, and compensate of VCMS, we use Spaceball 5000 and PHANTOM Desktop to assign the set of interaction tasks. During the process of realizing 6 degree-of-freedom (DOF) haptic feedback modeling control, we developed and accomplished the device interfaces with Open Inventor and Qt application framework. VCMS provides us a good immersion of allowing for effective modeling in a virtual world.
Seismic Vulnerability Assessment of Reinforced Concrete Buildings Using Hierarchical Fuzzy Rule Base Modeling

A reliable building vulnerability assessment is required for developing a risk-based assessment and retrofit prioritization. Tesfamariam and Saatcioglu (2008) proposed a simple building vulnerability module where the building performance modifiers are in congruence with FEMA 154. This paper is an extension of the building vulnerability assessment that include detailed performance modifier in congruence with FEMA 310 that is represented in a heuristic based hierarchical structure. Some of the input parameters are obtained through a walk down survey and are subject to vagueness uncertainty that is modelled through fuzzy set theory. A knowledge base fuzzy rule base modeling is developed and illustrated for reinforced concrete buildings damaged in the 1 May 2003 Bingöl, Turkey earthquake.
Energy and Emission Benefit Comparison of Stationary and In-Vehicle Advanced Driving Alert Systems

Automobiles powered by fossil fuels are one of the major contributors to both criteria pollutant and greenhouse gas—in particular, carbon dioxide (CO2)—emissions. Previous studies revealed that unnecessary acceleration and hard braking in response to sudden changes of traffic signals may cause a significant amount of wasted energy and increased emissions. Altering the behavior of drivers approaching signalized intersections potentially could reduce energy consumption and emissions from motor vehicles without increasing travel time or delay. Two types of advanced driving alert systems (ADAS) are proposed: stationary ADAS [based on roadside infrastructure, such as changeable message signs (CMSs)] and in-vehicle ADAS [driven by advanced communication technology, such as vehicle-infrastructure integration (VII)]. These systems can help drivers avoid hard braking at intersections by providing real-time information on traffic signal status. A state-of-the-art modal emissions model is used to evaluate and compare the effects of these two types of ADAS on the reduction of vehicle fuel consumption and CO2 emissions. A numerical analysis of a single vehicle shows that ADAS can help reduce vehicle fuel consumption and CO2 emissions by up to 40% in the tested hypothetical conditions. The benefits of these systems are further investigated in a traffic simulation environment with various levels of congestion and posted speed limits. The simulation results reveal that both CMS-based ADAS and VII-driven ADAS can provide fuel and CO2 savings; VII ADAS offer greater savings in most cases.
New Approach to 2D Braille Device Design

When blind operator is moving the electromagnet by his finger on ferromagnetic surface, he can “read” the visual information’s (height, colour, shadow) variation in some point of the surface by the force, which acts on the electromagnet in this point. The force can be varied by varying the electromagnet excitation current, depending on the point coordinates. The dependence of the force on the excitation current, magnetic circuit parameters and magnetic properties is obtained. For the accurate formation of the relief height, the bottom of the electromagnet must be separated at ferromagnetic surface by a small nonmagnetic gap. The modeling results are presented. Ill. 5, bibl. 9 (in English; abstracts in English, Russian and Lithuanian).
The effect of neutron irradiation on mechanical properties of CuCrZr alloys processed by cryorolling

Research and development of construction materials for fusion reactors is an important international task. CuCrZr material is a promising material for fabrication of coolant tubes inside the divertor and other components. In recent decade, materials with ultrafine-grained (UFG) structure are widely used due to their unique physical and mechanical properties. To be used in fusion technology, the material of the coolant tube should withstand pressure, show sufficient corrosion properties and neutron irradiation resistance. The UFG materials are known to improve the strength, ductility, heat and corrosion resistance, and according to the recent studies, they are expected to provide improved irradiation resistance. The aim of this study is to investigate the cryorolled UFG CuCrZr material behavior after neutron irradiation and to relate it to the microstructural changes. The post-irradiation evaluation was performed in Hot-cells facilities in Research Centre Řež. Mechanical properties were tested by static tensile test at ambient temperature, supplemented by microstructural analysis using SEM-EBSD. The results were compared with material processed by convention rolling method at ambient temperature.
Unsupervised Deep Hyperspectral Video Target Tracking and High Spectral-Spatial-Temporal Resolution (H³ Benchmark Dataset

Target tracking has received increased attention in the past few decades. However, most of the target tracking algorithms are based on RGB video data, and few are based on hyperspectral video data. With the development of the new ``snapshot'' hyperspectral sensors, hyperspectral videos can now be easily obtained. However, hyperspectral video target tracking datasets are still rare. In this article, a high spectral-spatial-temporal resolution hyperspectral video target tracking algorithm framework (H³Net) based on deep learning is proposed. The proposed framework consists of two main parts: 1) an unsupervised deep learning-based target tracking training framework for hyperspectral video; and 2) a dual-branch network structure based on a Siamese network. Using the dual-branch network, the H³Net framework can utilize both the spatial and spectral information. The combination of deep learning and a discriminative correlation filter (DCF) makes the features extracted by deep learning more suitable for the DCF. Compared with hyperspectral images, hyperspectral video data require more manpower to annotate, so we propose an unsupervised approach to train H³Net, without any annotation. To solve the problem of the lack of hyperspectral video datasets, we built a 25-band hyperspectral video dataset (the high spectral-spatial-temporal resolution hyperspectral video dataset: the WHU-Hi-H³ dataset) for target tracking. The experimental results obtained with the WHU-Hi-H³ dataset confirm the potential of unsupervised deep learning in hyperspectral video target tracking.
Beyond the Interface: Encountering Artifacts in Use

This paper is written by two people who come from rather different backgrounds, yet who, at the same time, share similar concerns about the human-computer interaction (HCI) area. One of us has a background in computing and cognitive science. The other person has a background in software engineering and computer systems design. As both of us are concerned with making more useful and usable computer applications we decided to look further for frameworks to help us. In this paper we shall try to expose some of the problems that we encountered in our joint effort to understand the HCI area and contribute to it, and to discuss some of the tensions and alternative viewpoints that we met on the way. The paper does not contain a solution to the problems of HCI. Rather, it contains a dialogue with ourselves about the matters of our concern, and we invite the reader to join this dialogue: our focus is on technology in use, where we emphasize the setting in which a piece of technology is used.
Space use, interaction and recursion in a solitary specialized herbivore: a red panda case study

: Better understanding of ecology is crucial for the success of endangered species conservation programmes. Little information is available on space use, conspecific interactions and recursions by one such species, the red panda Ailurus fulgens. To address this deficiency, we used GPS telemetry to examine their home range, core area, home-range overlap, dynamic interactions and recursive movement, and investigated the effect of sex, age and body mass on these behaviours across seasons. The median annual home range size was 1.41 km 2 , with nearly a quarter of this range being used as the core area. Sex and reproductive status were the key determinants of space use patterns on a seasonal scale, while body mass and age remained significant correlates for the core area. The home range of males was nearly double that of females, likely because of the polygynous mating system in red pandas. Females avoided overlapping home ranges, while males overlapped home range with up to 4 females, and neighbouring males overlapped nearly half of their ranges. We found rare interactions between males and females outside the mating season. Red pandas showed site fidelity within their territory, with seasonal variation across sex classes. We also observed high individual variation in patterns of both space use and recursive movement. Taken together, these results suggest that differences in biological requirements across seasons determine red panda space use patterns, conspecific interactions and recursion. However, forage availability and quality, climatic factors, disturbances and habitat fragmentation are also likely to influence these behaviours, and these factors need to be investigated.
The evolution of urban traffic control: changing policy and technology

Abstract The history of urban traffic control (UTC) throughout the past century has been a continued race to keep pace with ever more complex policy objectives and consistently increasing vehicle demand. Many benefits can be observed from an efficient UTC system, such as reduced congestion, increased economic efficiency and improved road safety and air quality. There have been significant advances in vehicle detection and communication technologies which have enabled a series of step changes in the capabilities of UTC systems, from early (fixed time) signal plans to modern integrated systems. A variety of UTC systems have been implemented throughout the world, each with individual strengths and weaknesses; this paper seeks to compare the leading commercial systems (and some less well known systems) to highlight the key characteristics and differences before assessing whether the current UTC systems are capable of meeting modern transport policy obligations and desires. This paper then moves on to consider current and future transport policy and the technological landscape in which UTC will need to operate over the coming decades, where technological advancements are expected to move UTC from an era of limited data availability to an era of data abundance.
A generalization of the Drenick-Shinozuka model for bounds on the seismic response of a single-degree-of-freedom system

This paper deals with seismic excitation of linearly elastic structures. It is well known that dynamical structural response is very sensitive to random fluctuations of the excitation; the consequence is that the identification of the forcing function on the basis of a few ‘global’ parameters does not allow to predict exhaustively stresses in seismically excited structures. In the paper, a convex model is established to treat uncertainty associated with the ‘details’ of the excitation, in order to set bounds on the response parameters of a SDOF system, assuming that only rough information is available for expected earthquakes at a given site. In particular, we assume that the maximum expected ‘energy’ of the accelerogram, and the maximum ‘distance’ of its power spectrum from the target spectrum, typical for the site under construction, are specified. © 1998 John Wiley & Sons, Ltd.
Metodología para la Implantación de un Sistema de Medición del Rendimiento Empresarial

The performance measurement system based on a set of indicators is a method for evaluating the efficiency of a company. This paper describes the CMI-IRIS methodology for the design and implementation of a control management system inside the ambit of the enterprises’ integration, combining strategic and technological elements. The method includes activities related with the enterprise environment, the definition and validation of the indicator system, the design and improvement of the process, and the implementation and monitoring of the system. Finally, a computer system that supports the methodology is presented. This enables to interact with the operational systems of the company to control the behaviour of the system of indicators.