Miracle-dz/UniFAR-FTUs huggingface dataset:
Real time pose estimation based on extended Kalman filter for binocular camera

Real-time pose estimation is a challenge in multi-camera vision system due to the demand of rapid response, high accuracy and robustness. Although some works based on multi-camera have been proposed, few works have regarded multi-camera as a fixed integration, which is easier to apply in real robotic application than eye-in-hand/eye-to-hand configuration. This paper proposes a novel Kalman-filter-based pose estimation algorithm for binocular camera that is regarded as a fixed integration. Centralized fusion method is employed to conduct the fusion of the eye-to-hand binocular camera. Extensive simulations are conducted to validate the effective of the proposed fusion method. The results show a higher accuracy and precision compared with traditional algorithms.
FPGA-accelerated Monte-Carlo integration using stratified sampling and Brownian bridges

Monte-Carlo Integration (MCI) is a numerical technique for evaluating integrals which have no closed form solution. Naive MCI randomly samples the integrand at uniformly distributed points. This naive approach converges very slowly. Stratified sampling can be used to concentrate the samples on segments of the integration domain where the integrand has the highest variance. Even with stratified sampling, MCI converges very slowly for multidimensional integrals. In this work, we implement an FPGA-accelerated design for MISER, a widely used adaptive MCI algorithm applying stratified sampling. We show how to eliminate the recursion from MISER and partition the algorithm between CPUs and FPGAs. The CPUs manage the control-heavy stratification strategy, while the FPGA is responsible for sampling the integrand. The integrand is compiled into a deep pipeline on the FPGA, producing one function evaluation per clock cycle. We demonstrate the FPGA-accelerated design by pricing a path dependent financial derivative called an Asian option. To make optimal use of the stratification, we implement a Brownian bridge on the FPGA that produces one entire bridge per clock cycle. The FPGA-accelerated design is up to 880 times faster compared to a software reference using the GSL implementation of MISER. Compared to naive MCI in software, our design even requires up to 3572 times less execution time to achieve the same accuracy.
Competitor analysis and interfirm riva-lry: toward a theoretical integration

This article bridges two important subjects in strategy: competitor analysis and interfirm rivalry. Through a refined conceptualization of competitor analysis, the article introduces two firm-specific, theory-based constructs: market commonality, developed from the literature on multiple-point competition, and resource similarity, derived from the resource-based theory of the firm. The joint consideration of these two constructs shows the complementarity of these two prominent but contrasting strategy theories. Each firm has a unique market profile and strategic resource endowment, and a pair-wise comparison with a given competitor along these two dimensions will help to illuminate the prebattle competitive tension between these two firms and to predict how a focal firm may interact with each of its competitors. The idea of competitive asymmetry is introduced, that is, the notion that a given pair of firms may not pose an equal degree of threat to each other. To illustrate competitor mapping, measures of .
Clustering and concept analysis for software evolution

Software Clustering and Concept Analysis are two types of technique that can be used to determine the structure of a software system. This position paper proposes the use of such techniques to aid the study of software evolution. Basic Software Clustering and Concept Analysis techniques are described. By applying these techniques to different versions of a software system, it is possible that evolutionary trends over the lifetime of the system could be discovered. Work is proposed that will attempt to establish whether this is the case.
Compiled low-level virtual instruction set simulation and profiling for code partitioning and ASIP-synthesis in hardware/software co-design

We present ongoing work and first results in static and detailed quantitative runtime analysis of LLVM byte code for the purpose of automatic procedural level partitioning and co-synthesis of complex software systems. Runtime behaviour is captured by reverse compilation of LLVM bytecode into augmented, self-profiling ANSI-C simulator programs retaining the LLVM instruction level. The actual global data flow is captured both in quantity and value range to guide function unit layout in the synthesis of application specific processors. Currently the implemented tool LLILA (Low Level Intermediate Language Analyzer) focuses on static code analysis on the inter-procedural data flow via e.g. function parameters and global variables to uncover a program's potential paths of data exchange.
CELF pretreatment of corn stover boosts ethanol titers and yields from high solids SSF with low enzyme loadings

A major challenge to economically produce ethanol from lignocellulosic biomass is to achieve industrially relevant ethanol titers (>50 g L−1) to control operating and capital costs for downstream ethanol operations while maintaining high ethanol yields. However, due to reduced fermentation effectiveness at high biomass solids loadings, excessive amounts of enzymes are typically required to obtain reasonable ethanol titers, thereby trading off reduced operating and capital costs with high enzyme costs. In this study, we applied our newly developed Co-Solvent Enhanced Lignocellulosic Fractionation (CELF) pretreatment to produce highly digestible glucan-rich solids from corn stover. Simultaneous saccharification and fermentation (SSF) was then applied to pretreated solids from CELF at 15.5 wt% solids loadings (corresponding to 11 wt% glucan loadings) in modified shake flasks to achieve an ethanol titer of 58.8 g L−1 at 89.2% yield with an enzyme loading of 15 mg-protein per g-glucan-in-raw-corn-stover (-RCS) in only 5 days. By comparison, SSF of corn stover solids from dilute acid pretreatment at 18.3 wt% solids loading (or 10 wt% glucan loading) only achieved an ethanol titer and a yield of 47.8 g L−1 and 73.0%, respectively, despite needing longer fermentation times (∼20 days) and an additional 18 h of prehydrolysis at 50 °C. Remarkably, although longer fermentation times were required at more economical enzyme loadings of 5 and 2 mg-protein per g-glucan-in-RCS, high solids SSF of CELF pretreated corn stover realized final ethanol titers consistently above 50 g L−1 and yields over 80%.
for Sentiment and Affect Extraction

In this chapter we turn to tools for interpreting affective meaning, extending our affective study of sentiment analysis in Chapter 7. We use the word ‘affective’, following the tradition in affective computing (Picard, 1995) to mean emotion, sentiment, personality, mood, and attitudes. Affective meaning is closely related to subjectivity, subjectivity the study of a speaker or writer’s evaluations, opinions, emotions, and speculations (Wiebe et al., 1999). How should affective meaning be defined? One influential typology of affective states comes from Scherer (2000), who defines each class of affective states by factors like its cognition realization and time course:
Paper Special Section on Recent Development of Electromechanical Devices (selected Papers from Icec2006) Study of the Effect of Gassing Material on Arc Behavior in Low Voltage Circuit Breaker *

SUMMARY A two-dimensional compressible magnetohydrodynamic (MHD) computational model has been developed to study the effect of gassing material on air arc behavior in low voltage circuit breaker. The properties of arc plasma and the electric, magnetic and radiative phenomena have been taken into account in the model. Based on the model, steady state solutions have been performed to study the effect of gassing material on the arc radius and electric field in the arc column. Then, the effect of gassing material on the transient process of arc motion also has been simulated. In addition, using the two-dimensional optical fiber measurement system, experiments have been done to measure the average velocity of arc motion with one model chamber and to verify the simulation model and prediction results. It demonstrates that the action of gassing material may yield the stronger electric field, less arc radius and higher arc motion velocity.
Pose invariant face recognition using HMM and SVM using PCA for dimensionality reduction

An embedded system is presented in which face recognition and facial recognition for Human-Robot Interaction are implemented. To detect face with a fast and reliable way, HMM combined with SVM algorithm is used. The full pose from face recognition data base is considered to detect the face recognition. Performance of the face recognition reaches to 99.617%. The two main advantages of our method are that it does not require manually selected facial landmarks or head pose estimation. In order to improve the performance of our pose normalization method in face recognition, an algorithm is presented for classifying whether a given face image is at a frontal or non frontal pose. Experimental results on different datasets are presented to demonstrate the effectiveness of the proposed approach. In addition to the proposed method, a pre processing state of detecting the face is included here. The images which are non faces are detected and eliminated from the database is an another main advantage in of this work.
Visual perception of obstacles and vehicles for platooning

Presents the methods for sensing obstacles and vehicles implemented on the University of Parma experimental vehicle (ARGO). The ARGO project is briefly described along with its main objectives; the prototype vehicle and its functionalities are presented. The perception of the environment is performed through the processing of images acquired from the vehicle. Details about the stereo vision-based detection of generic obstacles are given, along with a measurement of the performance of the method; then a new approach for leading vehicles detection is described, relying on symmetry detection in monocular images. The paper concludes with a description of the current implementation of the control system, based on a gain scheduled controller, which allows the vehicle to follow the road or other vehicles.
Long Non-Coding RNA and Alternative Splicing Modulations in Parkinson's Leukocytes Identified by RNA Sequencing

The continuously prolonged human lifespan is accompanied by increase in neurodegenerative diseases incidence, calling for the development of inexpensive blood-based diagnostics. Analyzing blood cell transcripts by RNA-Seq is a robust means to identify novel biomarkers that rapidly becomes a commonplace. However, there is lack of tools to discover novel exons, junctions and splicing events and to precisely and sensitively assess differential splicing through RNA-Seq data analysis and across RNA-Seq platforms. Here, we present a new and comprehensive computational workflow for whole-transcriptome RNA-Seq analysis, using an updated version of the software AltAnalyze, to identify both known and novel high-confidence alternative splicing events, and to integrate them with both protein-domains and microRNA binding annotations. We applied the novel workflow on RNA-Seq data from Parkinson's disease (PD) patients' leukocytes pre- and post- Deep Brain Stimulation (DBS) treatment and compared to healthy controls. Disease-mediated changes included decreased usage of alternative promoters and N-termini, 5′-end variations and mutually-exclusive exons. The PD regulated FUS and HNRNP A/B included prion-like domains regulated regions. We also present here a workflow to identify and analyze long non-coding RNAs (lncRNAs) via RNA-Seq data. We identified reduced lncRNA expression and selective PD-induced changes in 13 of over 6,000 detected leukocyte lncRNAs, four of which were inversely altered post-DBS. These included the U1 spliceosomal lncRNA and RP11-462G22.1, each entailing sequence complementarity to numerous microRNAs. Analysis of RNA-Seq from PD and unaffected controls brains revealed over 7,000 brain-expressed lncRNAs, of which 3,495 were co-expressed in the leukocytes including U1, which showed both leukocyte and brain increases. Furthermore, qRT-PCR validations confirmed these co-increases in PD leukocytes and two brain regions, the amygdala and substantia-nigra, compared to controls. This novel workflow allows deep multi-level inspection of RNA-Seq datasets and provides a comprehensive new resource for understanding disease transcriptome modifications in PD and other neurodegenerative diseases.
An automatic transition from geographic CIM to Spatial Data Warehouse

Recent modeling approaches were developed to provide a suitable design for Data Warehouses (DW) and Spatial Data Warehouses (SDW) without taking into account spatial decision maker (DM) needs. The generated results are generally not appreciated by DMs. We develop in this paper a spatial DM based approach that integrates automatically DM's standpoints while fulfilling numerous requirements. We use the Model Driven Approach (MDA) in order to automatically generate the design of SDW. Our approach is designed in such a way that the first MDA model scans DM's needs. The second MDA model describes the design of SDW. Then, we make a set of automatic transformations between the two models using the standard Query View Transformations (QVT). Finally, we propose an application describing a DM's needs and the generated design of SDW.
Neural net with two hidden layers for non-linear blind source separation

In this paper, we present an algorithm that minimizes the mutual information between the outputs of a multilayer perceptron (MLP). The neural network is then used as separating system in the nonlinear blind source separation problem. It has been reported that MLPs with one hidden layer are sufficient to achieve desirable performance. However, in some cases, we may prefer approximating nonlinear mappings by using networks with several hidden layers. For the sake of simplicity, the present paper is focused on MLPs with two hidden layers. The performance is illustrated by some experiments.
Detection of video copies based on robust descriptors

In this paper, robust descriptors are extracted to detect video copies generated by complicated transformations. The main contribution of the proposed method lies in three aspects. Firstly, the complicated transformations on video copies are identified and tackled to guarantee the extraction of robust descriptors. Secondly, a motion classification approach is proposed to divide the video into video groups. Thirdly, a two-stage matching scheme is implemented and the support vector machine is utilized to detect video copies. Extensive experiments are carried out using the data from TRECVID 2008 content-based video copy detection task. The proposed framework for video copy detection is very effective, and robust against spatial and temporal variations, in comparison with TRECVID participants and state-of-art algorithms.
An architecture to support intelligent user interfaces for Wikis by means of Natural Language Processing

We present an architecture for integrating a set of Natural Language Processing (NLP) techniques with a wiki platform. This entails support for adding, organizing, and finding content in the wiki. We perform a comprehensive analysis of how NLP techniques can support the user interaction with the wiki, using an intelligent interface to provide suggestions. The architecture is designed to be deployed with any existing wiki platform, especially those used in corporate environments. We implemented a prototype integrating the NLP techniques keyphrase extraction and text segmentation, as well as an improved search engine. The prototype is integrated with two widely used wiki platforms: Media-Wiki and TWiki.
Animals in the Zika Virus Life Cycle: What to Expect from Megadiverse Latin American Countries

Zika virus (ZIKV) was first isolated in 1947 in primates in Uganda, West Africa. The virus remained confined to the equatorial regions of Africa and Asia, cycling between infecting monkeys, arboreal mosquitoes, and occasional humans. The ZIKV Asiatic strain was probably introduced into Brazil in 2013. In the current critical human epidemic in the Americas, ZIKV is transmitted primarily by Aedes aegypti mosquitoes, especially where the human population density is combined with poor sanitation. Presently, ZIKV is in contact with the rich biodiversity in all Brazilian biomes, bordering on other Latin American countries. Infections in Brazilian primates have been reported recently, but the overall impact of this virus on wildlife in the Americas is still unknown. The current epidemic in the Americas requires knowledge on the role of mammals, especially non-human primates, in ZIKV transmission to humans. The article discusses the available data on ZIKV in host animals, besides issues of biodiversity, rapid environmental change, and impact on human health in megadiverse Latin American countries. The authors reviewed scientific articles and recent news stories on ZIKV in animals, showing that 47 animal species from three orders (mammals, reptiles, and birds) have been investigated for the potential to establish a sylvatic cycle. The review aims to contribute to epidemiological studies and the knowledge on the natural history of ZIKV. The article concludes with questions that require urgent attention in epidemiological studies involving wildlife in order to understand their role as ZIKV hosts and to effectively control the epidemic.
Agreeing on expectations: How project management can help balance the ambitions of cooperation

Commitment and trust are often mentioned as important aspects of creating a perception of reliability between counterparts. In the context of university-industry collaborations (UICs), agreeing on ambitions and expectations are adamant to achieving outcomes that are equally valuable to all parties involved. Despite this, our initial probing indicated that such covenants rarely exist. As such, this paper draws on project management theory and proposes the possibility of structuring assessments of potential partners before university-industry collaborations are brought to life. Our analysis suggests that project management can improve the perceived success of the relationships in university-industry collaborations. We also find evidence that the initial stages are vital for collaborative success and we confirm that clearly defined, mutually agreed objectives and realistic aims heighten the chances of value-added for all involved parties. Finally, we convey views of the respondents, which may well constitute fruitful avenues for furthering the success of collaborations between universities and industry but without the backdrop of extra administrative layers.
Cognitive Systems and Question Answering

This paper briefly characterizes the field of cognitive computing. As an exemplification, the field of natural language question answering is introduced together with its specific challenges. A possibility to master these challenges is illustrated by a detailed presentation of the LogAnswer system, which is a successful representative of the field of natural language question answering.
Achievement Emotions in Technology Enhanced Learning: Development and Validation of Self-Report Instruments in the Italian Context

The increased use of technology within the educational field gives rise to the need for developing valid instruments to measure key constructs associated with performance. We present some self-report instruments developed and/or validated in the Italian context that could be used to assess achievement emotions and correlates, within the theoretical framework of Pekrun’s control-value model. First, we propose some data related to the construction of two instruments developed to assess ten achievement emotions: the Brief Achievement Emotions Questionnaire, BR-AEQ, used with college students, and the Graduated Achievement Emotions Set, GR-AES, used with primary school students. Second, we describe some data concerning the validation within the Italian context of two instruments assessing achievement goals as antecedents of achievement emotions: the Achievement Goal Questionnaire-Revised, AGQ-R, and its more recent version based on the 3 X 2 achievement goal model.
The WHIRL Approach to Integration : An

We describe a new integration system, in which information sources are converted into a highly structured collection of small fragments of text. Database-like queries to this structured collection of text fragments are approximated using a novel logic called WHIRL, which combines inference in the style of deductive databases with ranked retrieval methods from information retrieval. WHIRL allows queries that integrate information from information sources, without requiring the extraction and normalization of object identi-ers that can be used as keys; instead, operations that in conventional databases require equality tests on keys are approximated using IR similarity metrics for text. This leads to a reduction in the amount of human engineering required to eld an integration system.
Monte Carlo Simulation for Econometricians

Many studies in econometric theory are supplemented by Monte Carlo simulation investigations. These illustrate the properties of alternative inference techniques when applied to samples drawn from mostly entirely synthetic data generating processes. They should provide information on how techniques, which may be sound asymptotically, perform in finite samples and then unveil the effects of model characteristics too complex to analyze analytically. Also the interpretation of applied studies should often benefit when supplemented by a dedicated simulation study, based on a design inspired by the postulated actual empirical data generating process, which would come close to bootstrapping. This review presents and illustrates the fundamentals of conceiving and executing such simulation studies, especially synthetic but also more dedicated, focussing on controlling their accuracy, increasing their efficiency, recognizing their limitations, presenting their results in a coherent and palatable way, and on the appropriate interpretation of their actual findings, especially when the simulation study is used to rank the qualities of alternative inference techniques.
Near Optimal Line Segment Weak Visibility Queries in Simple Polygons

This paper considers the problem of computing the weak visibility polygon (WVP) of any query line segment pq (or WVP(pq)) inside a given simple polygon P. We present an algorithm that preprocesses P and creates a data structure from which WVP(pq) is efficiently reported in an output sensitive manner. Our algorithm needs O(n^2 log n) time and O(n^2) space in the preprocessing phase to report WVP(pq) of any query line segment pq in time O(log^2 n + |WVP(pq)|). We improve the preprocessing time and space of current results for this problem at the expense of more query time.