Miracle-dz/UniFAR-FTUs huggingface dataset:
Generalisation of Geographic Information: Cartographic Modelling and Applications

Users have come to expect instant access to up-to-date geographical information, with global coverage - presented at widely varying levels of detail, as digital and paper products; customisable data that can readily combined with other geographic information. These requirements present an immense challenge to those supporting the delivery of such services (National Mapping Agencies (NMA), Government Departments, and private business. "Generalisation of Geographic Information: Cartographic Modelling and Applications" provides detailed review of state of the art technologies associated with these challenges, including the most recent developments in cartometric analysis techniques able to support high levels of automation among multi scale derivation techniques. The book illustrates the application of these ideas within existing and emerging technologies.In addition to providing a comprehensive theoretical underpinning, the book demonstrates how theoretical developments have translated into commercial systems deployed within NMAs. The book explores relevance of open systems in support of collaborative research and open source web based map services. It features state of the art review on multi scale representation techniques. It provides detailed consideration of database requirements and object modeling in support of emerging applications (3D, mobile) and innovative delivery (map generalisation services). It provides illustration through existing map production environment implementations. It contains consolidated bibliography (680 entries), 200 illustrations, author and subject index.
Analysing Finnish with word lists: the DDI approach to morphology revisited

Morphological lexicons for morphologically complex languages provide good text coverage at the cost of overgeneration, difficulty of modification, and sometimes performance issues. Use of simple, manageable lexicon forms – especially lists – for morphologically complex languages may appear unviable because the number of possible word-forms in a morphologically complex language can be prohibitively high. We created and experimented with a list-based lexicon for a morphologically complex language (Finnish), and compared its coverage with that of a mature morphological analyser on new text in two experimental settings. e observed smallish difference in coverage suggests the viability of using simple and easy-to-modify list-based lexicons as an initial part of morphological analysis, to increase developer control on the vast majority of input tokens.
A new distance measure based on the exchange operator for the HFF-AVRP

The Heterogeneous Fixed Fleet Asymmetric Vehicle Routing Prob- lem (HFF-AVRP) is a N P-hard optimization problem. Instances analysis and in particular, fitness landscape analysis, may help problem solving. Such anal- ysis require the definition of a distance between feasible solutions. Such a dis- tance does not exist for the HFF-AVRP and this report aims at proposing a new distance measure defined from the exchange operator. In order to compute the exchange-distance between two solutions, four algorithms are suggested and then experimented. One of them is proved to be robust and to give the exact distance whereas others only compute an upper bound.
Macroeconomic Uncertainty and Private Investment in Developing Countries: An Empirical Investigation

An examination of several case studies in the region suggests that the ability to sustain a credible monetary policy depends on how vulnerable countries are to the impacts of sudden stops. In this respect, four aspects are of vital importance to ameliorate such impacts. Opening up the economy so that there is an increased supply of tradables will reduce the size of the fall in tradable absorption that is typically required by a sudden stop. Reducing the level of indebtedness will ensure that the required RER depreciation will be smaller. Lowering currency mismatches in the composition of debt relative to the composition of output will reduce vulnerability to valuation effects. Finally, the exposition to possible fiscal contingencies should also be addressed to reduce vulnerability of fiscal accounts, such as costly bank bailouts that stem from currency mismatches in the financial sector.
Torque Ripple Minimization in Switched Reluctance Motor Using Passivity-Based Robust Adaptive Control

In this paper by using the port-controlled Hamiltonian (PCH) systems theory, a full-order nonlinear controlled model is first developed. Then a nonlinear passivity-based robust adaptive control (PBRAC) of switched reluctance motor in the presence of external disturbances for the purpose of torque ripple reduction and characteristic improvement is presented. The proposed controller design is separated into the inner loop and the outer loop controller. In the inner loop, passivity-based control is employed by using energy shaping techniques to produce the proper switching function. The outer loop control is employed by robust adaptive controller to determine the appropriate Torque command. It can also overcome the inherent nonlinear characteristics of the system and make the whole system robust to uncertainties and bounded disturbances. A 4KW 8/6 SRM with experimental characteristics that takes magnetic saturation into account is modeled, simulation results show that the proposed scheme has good performance and practical application prospects. Keywords—Switched Reluctance Motor, Port Hamiltonian System, Passivity-Based Control, Torque Ripple Minimization
Parallelism in AI Problem Solving: A Case Study of Hearsay 2

Abstract : The Hearsay II speech-understanding system (HSII) (Lesser, et al., 1974; Fennell, 1975; Erman and Lesser, 1975) is an implementation of a knowledge-based multiprocessing AI problem-solving organization. HSII is intended to represent a problem-solving organization which is applicable for implementation in a multiprocessing environment, and is, in particular, currently being implemented on the C.mmp multiprocessor system (Bell, et al., 1971) at Carnegie-Mellon University. The object of this paper is to explore several of the ramifications of such a problem-solving organization by examining the mechanisms and policies underlying HSII which are necessary for supporting its organization as a multiprocessing problem-solving system. First, an abstract description of a class of problem-solving systems is given using the Production System model of Newell (1973). Then, the HSII problem-solving organization is described in terms of this model. The various decisions made during the course of design necessitated the introduction of various multiprocessing mechanisms (e.g., mechanisms for maintaining data localization and data integrity), and these mechanisms are discussed. Finally, a simulation study is presented which details the effects of actually implementing such a problem-solving organization for use in a particular application area, that of speech understanding.
ON MOBILE DEVICES

This paper presents analysis/synthesis strategies for generating abstract, creative representations via the camera input on a mobile device. Mobile devices are well suited for interactive video processing since they are simultaneously capable of image capture, display, and manipulation. Analysis/synthesis methods are particularly powerful in interactive arts projects as they enable even drastic manipulations of the input image while still maintaining fundamental aspects of its original identity. Moreover, by using abstract synthesis elements (i.e., coherent elements larger than single pixels), we are able to directly interact with the image and to manipulate its final output. We describe some of the exciting capabilities of video processing and interaction on mobile devices and introduce a series of mobile applications that use analysis/synthesis techniques.
HRV Analysis of Arrhythmias Using Linear - Nonlinear Parameters

Heart rate variability (HRV) refers to the beat-to-beat alterations in heart rate. HRV analysis is based on the concept that, fast fluctuations reflect the changes of sympathetic and vagal activity which results in variability of intervals between R waves i.e. “RR intervals”. In the current work HRV was assessed by traditional linear time and frequency-domain indexes, in parallel with the non linear Poincare plot analysis. Initially R peaks are detected from the ECG and RR interval signal is obtained which is further used to get the HRV signal. Spectral analysis of this HRV signal is done to estimate the power content in different frequency bands. Two frequency bands play a vital role in the power spectrum, a low frequency and a high frequency. Simultaneously, for time domain analysis, parameters such as mean of RR interval signal, standard deviation, coefficient of variance, root mean square of standard deviation are evaluated from RR interval signal and analyzed for different arrhythmias. Poincare plot analysis is an emerging quantitative-visual technique whereby the shape of the plot is categorized into functional classes that indicate the different arrhythmia. In this each R-R interval is plotted as a function of the previous one, and the standard deviations of the instantaneous and long-term R-R interval variability are calculated. It is observed that mean of RR interval signal and coefficient of variance plays an important role and can be used in classification along with the power content in low and high frequency bands. Also position and orientation of RR intervals in Poincare plot play an important role in visual identification of arrhythmias. The method is applied to normal sinus rhythm, ST change, CU Ventricular Tachyarrhythmia, Malignant ventricular arrhythmia signals. In this work, the different linear and non linear parameters evaluated show a particular range for various cardiac arrhythmias.
Efficient and Anonymous Authentication for Healthcare Service With Cloud Based WBANs

Wireless body area networks (WBANs) technology nowadays has become a promising networking paradigm in the Internet of Things (IoT) as it can provide people with high quality of life and a high level of medical service. Specifically, to make sure those people with a high incidence of chronic diseases, including hypertension, diabetes, and cardiovascular diseases, are taking care of which further reduces social costs. Thus, both industry and academia in recent years pay widely attention to WBANs technology. After years of research, security, privacy, and efficiency of the healthcare services in WBANs have remained as major challenges. Although different authentication mechanisms have been designed to meet the challenges in recent years, most of them suffer from some functional defects or security problems. To ensure the security and privacy of patients’ sensitive biomedical data and the efficiency of message processing across different devices, it is critical to provide a secure and lightweight authentication scheme for WBANs.
JOINT ANALYSIS OF MULTIPLE PHENOTYPES IN ASSOCIATION STUDIES

viii 1 An Adaptive Fisher’s Combination Method for Joint Analysis of Multiple Phenotypes in Association Studies . 1 1.1 Background . 1 1.2 Methods . 4 1.2.1 Adaptive Fisher’s Combination Method . 4 1.2.2 Comparison of Methods . 5 1.3 Results . 7 1.3.1 Simulation Studies . 7 1.3.2 Simulation Results . 10 1.3. 3 Real Data Analysis . 12 1.4 Discussion . 14 1.5 Tables and Figures . 16 2 Joint Analysis of Multiple Phenotypes in Association Studies Using Allele-based Clustering Approach for Non-Normal Distributions . 23 2.1 Background . 23 2.2 Methods . 25 2.2.1 Allele-Based Clustering Method . 25 2.2.2 Comparison of Methods . 28 2.3 Results . 28 2.3.1 Simulation Studies . 28 2.3.2 Simulation Results . 30 2.4 Discussion . 32 2.5 Tables and Figures . 34 3 A Hierarchical Clustering Method for Dimension Reduction in Joint Analysis of Multiple Phenotypes . 44 3.1 Background . 44 3.2 Methods . 47
Aggregation in Natural Language Generation

The content of real‐world databases, knowledge bases, database models, and formal specifications is often highly redundant and needs to be aggregated before these representations can be successfully paraphrased into natural language. To generate natural language from these representations, a number of processes must be carried out, one of which is sentence planning where the task of aggregation is carried out. Aggregation, which has been called ellipsis or coordination in Linguistics, is the process that removes redundancies during generation of a natural language discourse, without losing any information.
ToBI-Team of Bielefeld : The Human-Robot Interaction System for RoboCup @ Home 2010

The Team of Bielefeld (ToBI) has been founded in 2009. The robocup activities are embedded in a long-term research history towards human-robot interaction with laypersons in regular home environments. The robocup@home competition is an important benchmark and milestone for the overall research goal. For robocup 2010, the team concentrates on mixed-initiative scenarios, person detection capabilities, and more sophisticated scene understanding methods.
Real-Time Tracking of Smartwatch Orientation and Location by Multitask Learning

Arm posture tracking is essential for many applications, such as gesture recognition, fitness training, and motion-based controls. Smartwatches with Inertial Measurement Unit (IMU) sensors (i.e., accelerometer, gyroscope, and magnetometer) provide a convenient way to track the orientation and location of the wrist. Existing orientation estimations are based on predefined data fusion methods that do not consider the variations in the data quality of different IMU sensors. Existing location estimations rely on the estimated orientation results. A small orientation estimation error may cause high inaccuracy in location estimation. Moreover, these location estimation algorithms, e.g., Hidden Markov Model and Particle Filters, cannot provide real-time tracking on commercial mobile devices due to high computation overhead. This paper presents RTAT, a Real-Time Arm Tracking system that tackles the above limitations in a data-driven way. RTAT estimates both orientation and location simultaneously using a multitask learning neural network. It also incorporates a unique attention layer and a dedicated loss function to learn the dynamic relationship among IMU sensors. RTAT supports real-time tracking by performing model inference on smartphones. Finally, to train RTAT's neural network, we develop an easy-to-use labeled data collection system that uses a low-cost virtual reality system to provide orientation and location labels for the smartwatch. Extensive experiments show RTAT significantly outperforms existing state-of-the-art solutions in both accuracy and latency.
Experimental and Simulation Studies of the Effects of Heavy-Ion Irradiation on HfO2-Based RRAM Cells

HfO2-based resistive RAMs have been irradiated with high-linear energy transfer heavy ions and subjected to an extensive characterization, showing that the cells are immune from upsets. No relevant changes were observed in the irradiated cells on resistance distribution and programming voltages. The irradiation experiment has been performed without any applied bias (retention mode). Reasons for the observed hardness are discussed using physics-based simulations. Moreover, simulations put in evidence that the cell might be sensitive if it is struck during a read operation, since the applied read voltage prevents the instantaneous recombination of the generated defects due to the Coulomb interaction between oxygen ions and vacancies.
A FPGA Implementation of a RISC Processorfor Computer Architecture

This paper is concerned with the design and implementation of a 32bit Reduced Instruction Set Computer (RISC) processor on a Field Programmable Gate Arrays (FPGAs). We are designing the processor with VHDL and the simulation using Altera Quartus Plus2, and we will implement on Altera cyclone II in FPGA.The test bench waveforms for the different parts of the processor are presented and the system architecture is demonstrated. Refer ences
Rapid system prototyping with FPGAs

The push to move products to market as quickly and cheaply as possible is fiercer than ever, and accordingly, engineers are always looking for new ways to provide their companies with the edge over the competition. Field-Programmable Gate Arrays (FPGAs), which are faster, denser, and more cost-effective than traditional programmable logic devices (PLDs), are quickly becoming one of the most widespread tools that embedded engineers can utilize in order to gain that needed edge. FPGAs are especially popular for prototyping designs, due to their superior speed and efficiency.This book hones in on that rapid prototyping aspect of FPGA use, showing designers exactly how they can cut time off production cycles and save their companies money drained by costly mistakes, via prototyping designs with FPGAs first. Reading it will take a designer with a basic knowledge of implementing FPGAs to the “next-level” of FPGA use because unlike broad beginner books on FPGAs, this book presents the required design skills in a focused, practical, example-oriented manner.
Learning "Forgiving" Hash Functions: Algorithms and Large Scale Tests

The p r o b lem of effi c ien t ly finding s imil ar i t em s in a l ar ge c o r pu s of high-dimen s ion a l d ata poin ts ar i s e s in m a ny r e a l-wo r ld tas k s , s u c h as mu s i c , im-a ge, a nd video r e tr iev a l. Beyond t he sca ling diffi-c ul t ie s t h at ar i s e wi t h lookup s in l ar ge d ata s e ts , t he c omplexi t y in t he s e dom a in s i s ex ac e rbat ed b y a n imp r e c i s e defini t ion of s imil ar i t y. In t hi s p a pe r , we de scr i b e a me t hod t o le ar n a s imil ar i t y fun ct ion f r om only we a kly l ab eled po s i t ive ex a mple s . On c e le ar ned, t hi s s imil ar i t y fun ct ion i s u s ed as t he bas i s of a h as h fun ct ion t o s eve r ely c on stra in t he num b e r of poin ts c on s ide r ed fo r e ac h lookup. Te st ed on a l ar ge r e a l-wo r ld a udio d atas e t , only a t iny f ract ion of t he poin ts (~0.27%) ar e eve r c on s ide r ed fo r e ac h lookup. To in cr e as e effi c ien c y, no c omp ar i s on s in t he o r igin a l high-dimen s ion a l s p ac e of poin ts ar e r equi r ed. The pe r fo r m a n c e f ar s u r p ass e s , in t e r m s of b o t h effi c ien c y a nd acc u rac
Modelling evaporation processes in soils from the Huasco salt flat basin, Chile

The need to understand and simulate hydrological phenomena and their interactions, and the impact of anthropogenic and climate changes on natural environments have promoted the study of evaporation from bare soils in arid climates. In closed Altiplano basins, such as those encountered in arid and hyper arid basins in northern Chile, evaporation from shallow groundwater is the main source of aquifer depletion, and thus, its study is crucial for water resources management. The objective of this work is to understand the mechanisms of evaporation in saline soils with shallow water tables, in order to better quantify evaporation fluxes and improve our understanding of the water balance in these regions. To achieve this objective, a model that couples fluid flow with heat transfer was developed and calibrated using column experiments with saline soils from the Huasco salt flat basin, Chile. The model enables determination of both liquid and water vapour fluxes, as well as the location of the evaporation front. Experimental results showed that salt transport inside the soil profile modified the water retention curve, highlighting the importance of including salt transport when modelling the evaporation processes in these soils. Indeed, model simulations only agreed with the experimental data when the effect of salt transport on water retention curves was taken into account. Model results also showed that the evaporation front is closer to the soil surface as the water table depth reduces. Therefore, the model allows determining the groundwater level depth that results in disconnection of liquid fluxes in the vadose zone. A sensitivity analysis allowed understanding the effect of water‐flux enhancements mechanisms on soil evaporation. The results presented in this study are important as they allow quantifying the evaporation that occurs in bare soils from Altiplano basins, which is typically the main water discharge in these closed basins. Copyright © 2016 John Wiley & Sons, Ltd.
Title : A Sub-cm 3 Energy-Harvesting Stacked Wireless Sensor Node Featuring a Near-Threshold Voltage IA-32 Microcontroller in 14 nm Tri-gate CMOS for Always-On Always-Sensing Applications

An energy-harvesting wireless sensor node (WSN) integrates a 14nm, 0.79mm, 32-bit Intel Architecture (IA) core-based near-threshold voltage (NTV) microcontroller (MCU) that provides 17μW/MHz always-ON, always-sensing (AOAS) capability. The MCU implements four independent voltage-frequency islands (VFI), managed by an integrated power management unit (PMU) and features a sub-threshold voltage capable on-die oscillator and 42nm fin-pitch, 8.3pA leakage-per-bit SRAM. The MCU operates across a wide frequency (voltage) range from 297MHz (1V) to 0.5MHz (308mV), dissipating 23.5mW to 21μW and achieves 4.8X better energyefficiency at an optimum supply voltage (VOPT) of 370mV, 3.5MHz and 17pJ/cycle. A functional AOAS WSN incorporating the NTV MCU shows promise for sustained μW operation.
Interactive Isosurface Ray Tracing of Time-Varying Tetrahedral Volumes

We describe a system for interactively rendering isosurfaces of tetrahedral finite-element scalar fields using coherent ray tracing techniques on the CPU. By employing state-of-the art methods in polygonal ray tracing, namely aggressive packet/frustum traversal of a bounding volume hierarchy, we can accommodate large and time-varying unstructured data. In conjunction with this efficiency structure, we introduce a novel technique for intersecting ray packets with tetrahedral primitives. Ray tracing is flexible, allowing for dynamic changes in isovalue and time step, visualization of multiple isosurfaces, shadows, and depth-peeling transparency effects. The resulting system offers the intuitive simplicity of isosurfacing, guaranteed-correct visual results, and ultimately a scalable, dynamic and consistently interactive solution for visualizing unstructured volumes.
Research and Application on Medium-term and Long-term Runoff Forecast of Baishan Reservoir

With the application of time series and contributing factors analysis method, a model of successive regression period analysis and a coupled model of successive regression and neural network for medium term and long term runoff forecast have been set up by organically combining cause and effect and statistical analysis with neural network. The result of calculation shows that the models are highly effective and are worth popularization and application.
University of New Hampshire Scholars' Repository University of New Hampshire Scholars' Repository

By combining attention-based mechanisms that have proved beneﬁcial in the ﬁeld of natural language processing with domain-speciﬁc knowledge about the structure of music, better predictions about piece continuations can be made. The goal of this work is to adapt current natural language processing techniques to a musical domain, and to generate new music by predicting continuations on a sequence of notes. An adaptation of traditional attention mechanisms to create a single prediction from sequential input is used to extend musical pieces by appending new elements repeatedly.