Miracle-dz/UniFAR-FTUs huggingface dataset:
Commonalities and contrasts: an Investigation of ERP Usability in a Comparative User Study

In recent years, several user studies have examined specific usability problems in the field of Enterprise Resource Planning (ERP). These studies focused on different branches, various usability aspects, and several user groups. In spite of this diversification, some common and essential usability problems have become apparent, which are related to system complexity and difficulties in finding required information. However, these findings are based on the situation in a specific country, a singular ERP system and few data samples. Therefore, this paper aims at complementing the related work by results from a comparative user survey from two different European countries: Germany and Latvia. The survey is based on 184 ERP users from Germany and 24 ERP users from Latvia. The results indicated that both countries have several contrasts, but also diverse commonalities in industry, ERP market and culture. However, users in both countries are very homogenous with regard to the assessment of usability problems in their ERP interfaces. This paper investigates elementary usability problems derived from the related work and examines to which extent they are valid in both countries today. The main hypothesis claims that diverse national characteristics do not necessarily lead to a different assessment of usability problems in ERP systems.
Coupled drive leg of quadrupedal robot mechanism design and analysis of energy consumption

The system mechanical properties play an important role in dynamic quadrupedal robot control reseach. This paper describes a new coupled drive leg for quadrupedal robot. Numerical studies have been done to investigate the mechanical power and energy of the coupled drive leg and direct drive leg in the same control algorithms . When the robot is walking at speed of 0.13m / s, the robot of the coupling legs than the direct drive in the unit time saving energy ratio η = 15. 24%, while at a speed of 0.19m / s, η = 22. 59%. The results show that the coupled leg design has higher efficiency.
Parameter Optimal Iterative Learning Control with Application to a Robot Arm

In this paper the parameter optimization ILC algorithm is used for trajectory tracking of the robot arm. This control scheme is based on the parameter optimization through a quadratic performance index which its solution will converge in norm to zero. The control design is very simple in the sense that the only requirement is to reduce the error of the movement of the robot arm for picking up the object at the desired target. Forward and Inverse kinematics analysis are applied to find the joint angles at the desired position and it will be compared with the current position to obtain the error value. The ILC algorithm will finally be used to correct the error trial to trial until the position of the robot arm is completely closed to the target.
The platin Tool Kit-The T-CREST Approach for Compiler and WCET Integration

The construction of safety-critical real-time applications requires predictable computer platforms that enable a safe and tight static analysis of those systems. The worst-case performance and the availability of tight bounds on the worst-case execution time (WCET) of the tasks of the applications are of central importance in such systems. The compiler tool-chain plays an integral part in a real-time platform infrastructure. Not only is the compiler responsible for relating source code level annotations such as flow facts to the generated machine code – a task necessary to achieve high-quality bounds on optimised code. Also, the analysis tools profit from program information that is readily available in the compiler but difficult to retrieve from the generated binary alone. Therefore, the compiler should export internal knowledge about the program to the analysis. Furthermore, compilation for hard real-time systems requires optimisations that specifically aim at reducing the worst-case execution path instead of reducing the average case performance. This requires feedback from the worst-case analysis back to the compiler. In this paper we describe the our approach to the compiler tool integration that has been realised in the platin tool kit, developed in the EU FP7 T-CREST project. The platin tool kit is a portable glue tool that interfaces our LLVM-based T-CREST compiler with several research and industrial strength analysis tools. Our approach is transferable to other compiler tool-chains and minimises the effort for adapting them for the requirements of real-time platforms.
Recognizing Human Activity in Still Images by Integrating Group-Based Contextual Cues

Images with wider angles usually capture more persons in wider scenes, and recognizing individuals' activities in these images based on existing contextual cues usually meet difficulties. We instead construct a novel group-based cue to utilize the context carried by suitable surrounding persons. We propose a global-local cue integration model (GLCIM) to find a suitable group of local cues extracted from individuals and form a corresponding global cue. A fusion restricted Boltzmann machine, a focal subspace measurement and a cue integration algorithm based on entropy are proposed to enable the GLCIM to integrate most of the relevant local cues and least of the irrelevant ones into the group. Our experiments demonstrate how integrating group-based cues improves the activity recognition accuracies in detail and show that all of the key parts of GLCIM make positive contributions to the increases of the accuracies.
Segmentation of blood vessels in fundus color images by Radon transform and morphological reconstruction

In this paper we have presented an algorithm for vessel detection in retinal color images which works based on local Radon transform and morphological reconstruction. In our previous work, the algorithm was applied to conjunctival images and the performance was evaluated subjectively. In this work an extended version of the algorithm is applied to retinal images and our aim is to detect vessels in retinal images of patient people and make a good discrimination between blood vessels and other pathological elements like microaneurysms and hemorrhages which have the same color as vessels. The algorithm performance was evaluated numerically by applying it to DRIVE image database and the achieved ROC curve demonstrates its high accuracy.
Pengaruh Extrinsic Motivation, Absorptive Capacity, Channel Richness Dan Level of IT Usage Terhadap Sikap Individu Atas Perilaku Sharing Knowledge

Abstrak Penelitian ini bertujuan untuk menguji pengaruh motivasi ekstrinsik, daya serap, kekayaan saluran dan tingkat penggunaan TI pada sikap individu terhadap perilaku berbagi pengetahuan.Responden dalam penelitian ini adalah mahasiswa informatika Negeri Semarang rekayasa University dan Universitas Diponegoro. Metode pengumpulan data dalam penelitian ini menggunakan metode survei. Sampel diambil secara purposive sampling dengan mengambil responden yang akan digunakan sebagai sampel dari 135 mahasiswa. Alat analisis yang digunakan dalam penelitian ini adalah regresi linier berganda. Hasil dari penelitian ini menunjukkan bahwa variabel motivasi ekstrinsik tidak memiliki pengaruh pada sikap individu terhadap perilaku berbagi pengetahuan. Sedangkan daya serap variabel, kekayaan saluran, dan tingkat penggunaan TI memiliki pengaruh positif pada sikap individu terhadap perilaku berbagi pengetahuan. Kata kunci : motivasi ekstrinsik, daya serap, kekayaan saluran, tingkat penggunaan itu, berbagi pengetahuan Abstract This study aims to examine the effect of extrinsic motivation, absorptive capacity, channel richness and level of IT usage on individual attitudes towards knowledge sharing behavior. Respondents in this study were students of informatics engineering Semarang State University and the University of Diponegoro. Methods of data collection in this study using survey methods. Samples were taken by purposive sampling by taking the respondent to be used as a sample of 135 students. Analysis tools used in this study is multiple linear regression. The results of this study indicate that variables extrinsic motivation does not have an influence on individual attitudes on knowledge sharing behavior. While the variable absorptive capacity, channel richness, and the level of IT usage has a positive influence on individual attitudes on knowledge sharing behavior. Key word : extrinsic motivation, absorptive capacity, channel richness , level of it usage, sharing knowledge
Monitors , Mammals , and Wallace ’ s Line

Although varanid lizards have achieved parity with mammals in many parts of the world, they exploit very different metabolic strategies and sensory mechanisms, and are properly regarded as convergent on the lifestyle of small predatory mammals. In parts of island southeast Asia and in Australia small monitors appear to fill ecological niches occupied by cats, mustelids and viverrids in other parts of the world. Species diversity of large monitor species (>.3 m TL) does not change across Wallace’s Line, which is the distributional boundary for nearly all small, carnivorous placental mammals, but the diversity of small monitor species (<.2 m TL) increases abruptly from this line east. Small monitor species can coexist with dasyurid marsupial carnivores, but apparently not with placental carnivores (this is being tested now with the establishment of feral cats in Australia). Because juveniles of large monitor species can survive in communities with placental carnivores to the west of Wallace’s Line, we speculate that predation rather than resource competition has influenced the observed pattern. Large monitors produce large clutches and their juveniles soon grow out of the vulnerable size range, whereas small monitor species (despite being more fecund, when body size is factored out) produce fewer eggs, are always subject to mammalian predation, and may not be able to coexist over evolutionary time with placental carnivores.
Rich feature hierarchies for cell detecting under phase contrast microscopy images

R-CNN (region-convolutional neural network) has recently achieved very outstanding results in variety of visual detecting fields, and its function of object-proposal-generation can achieve effective training models by using as small samples as possible in the field of machine learning. In this paper, a modified R-CNN is proposed and applied to detect cells under phase contrast microscopy images by adopting multiple object-proposal-generations instead of a single one to extract candidate regions. The results show that the proposed method can obtain better performance than the traditional method by using a single object-proposal-generation.
A Compressive Sensing Based Mobile Video Communication System

A compressive sensing (CS) based mobile video communication system is proposed to meet the requirement that video service needs low-complexity video encoder in the mobile internet. In this system, the mobile client uses CS based video encoder having low computational complexity and power, and then its output bit-stream is decoded using CS recovery algorithm in the fixed base station or network server. The decoded video signal is transformed again as bits by the traditional H.264/MPEG video encoder, and the central base station transmits them to mobile clients so as to realizing low-complexity video decoding. The simulation experiments show that the proposed CS based mobile video communication system has the better rate-distortion performance, and can ensure high quality video reconstruction at low measurement rates. Copyright © 2013 IFSA.
Avoidance Coupling

We examine the question of whether a collection of random walks on a graph can be coupled so that they never collide. In particular, we show that on the complete graph on n vertices, with or without loops, there is a Markovian coupling keeping apart Omega(n/log n) random walks, taking turns to move in discrete time.
Spatial and polarisation correlation characteristics for UWB impulse radio

Correlation between diversity branches is the key parameter in determining the diversity performance of wireless systems. In this paper, measurements in a temporally and spatially stationary indoor environment are carried out to obtain the channel impulse responses for the UWB impulse radio using receivers with different positions or different polarisation states. A two-dimension (2D) RAKE receiver with post-detection equal gain combining (EGC) diversity is assumed to be used. Three definitions of correlation coefficients of the diversity branches are considered: correlation coefficient, normalized correlation and channel profile correlation, are analysed in this paper. The results show that the normalised correlation is more effective to ascertain the degree of similarity of the correlated diversity branches where medium scale fading dominates.
High-Throughput, Amplicon-Based Sequencing of the CREBBP Gene as a Tool to Develop a Universal Platform-Independent Assay

High-throughput sequencing technologies are widely used to analyse genomic variants or rare mutational events in different fields of genomic research, with a fast development of new or adapted platforms and technologies, enabling amplicon-based analysis of single target genes or even whole genome sequencing within a short period of time. Each sequencing platform is characterized by well-defined types of errors, resulting from different steps in the sequencing workflow. Here we describe a universal method to prepare amplicon libraries that can be used for sequencing on different high-throughput sequencing platforms. We have sequenced distinct exons of the CREB binding protein (CREBBP) gene and analysed the output resulting from three major deep-sequencing platforms. platform-specific errors were adjusted according to the result of sequence analysis from the remaining platforms. Additionally, bioinformatic methods are described to determine platform dependent errors. Summarizing the results we present a platform-independent cost-efficient and timesaving method that can be used as an alternative to commercially available sample-preparation kits.
Shearlet transform based image denoising using histogram thresholding

This paper presents an efficient image denoising method by incorporating shearlet-based histogram thresholding. Nowadays, digital images are used in wide range of applications but most of these images are degraded during transmission and acquisition process. Removal of noise from images is still a challenging task for many researchers because there is always a trade-off between noise removal and fine edge preservation. This paper is based on image denoising using shearlet transform. Shearlets have excellent features for data analysis and processing, which overcomes the limitation of traditional methods. They are optimally sparse and have multi-scale and multi-directional properties which are optimal in representing image containing edges. In this paper, the proposed method is found to produce superior peak signal-to-noise ratio (PSNR) over the conventional denoising algorithms.
Twins in Cardiovascular Genetic Research

Twin studies have been largely responsible for showing the effects of genetic variance on a quantitative trait. The model is based on the fact that monozygotic twins share all genes in common, whereas dizygotic twins are related as siblings and share “on average” half their genes. Environmental confounders are minimized because twin children are usually exposed to similar environments. Blood pressure was first shown to be heritable in a twin study. However, intermediary phenotypes, such as components of the renin-angiotensin system, sympathetic nervous system, renal function, and the facility in excreting electrolytes, are also heritable. The advent of molecular genetics has made twin studies more useful than ever because of the power of quantitative trait loci analyses. Recruitment of the parents of dizygotic twins greatly facilitates this effort. Gene loci linked to blood pressure, intermediate phenotypes, cardiac dimensions, lipid concentrations, and even components of the ECG have been identified. The use of single-nucleotide polymorphisms then allows for novel association approaches within the cohort. Twin studies will continue to gain in importance and utility, particularly in elucidating normal human genetic diversity.
The Dark and Bright Sides of Personal Use of Technology at Work: A Job Demands–Resources Model

As employees increasingly use technology for personal purposes in the workplace, tensions between proponents of control versus flexibility are rising. Proponents of control emphasize negative consequences and argue for employee restrictions and monitoring, whereas those for flexibility highlight positive consequences and advocate for employee discretion. We build consensus between these two approaches by adopting the job demands–resources model to show why the personal use of technology at work has both negative and positive effects on organizational outcomes, and then, we theorize about several boundary conditions that mitigate or strengthen these effects. We discuss implications for human resource development (HRD) scholars and professionals.
Unusual events detection based on multi-dictionary sparse representation using kinect

Unusual events detection plays a crucial role in surveillance applications, which is becoming more and more urgent need for public security. However, illumination and scale changing, lacking of sufficient training data and subjective of abnormality definition are some of the severe difficulties, which are hard to deal with by widely used traditional cameras. In order to solve these problems, first, a novel feature is proposed in this paper, which is named random local feature (RLF) to describe the spatial-temporal information of depth image detected by the Kinect sensor. Then, we expand the sparse representation framework to a multi-dictionary sparse representation framework, based on the intuition that that anomaly of a same event may vary a lot in different regions in a scene. We split the depth video into several regions and use detected RLF features in each region to train dictionary by K-SVD algorithm, and use the OMP algorithm to sparse-represent each feature. Finally, an objective function is introduced to evaluate the anomaly of features in each region according to reconstruction errors. Unusual events are defined as those incidences that occur very rarely in the entire video sequence in our system, which is tested on real data and demonstrates promising results in unusual events detection.
Involutive constrained systems and Hamilton-Jacobi formalism

In this paper, we study singular systems with complete sets of involutive constraints. The aim is to establish, within the Hamilton-Jacobi theory, the relationship between the Frobenius’ theorem, the infinitesimal canonical transformations generated by constraints in involution with the Poisson brackets, and the lagrangian point (gauge) transformations of physical systems.
Analytic PCA construction for theoretical analysis of lighting variability , including attached shadows , in a single image of a convex Lambertian object

We analyze theoretically the subspace best approximating images of a convex Lambertian object under different distant illumination conditions. Since the lighting is an arbitrary function, the space of all possible images is formally infinite-dimensional. However, previous empirical work by Hallinan [7] and Epstein et al. [4] has shown that images of largely diffuse objects actually lie very close to a 5-dimensional subspace. In this paper, we analytically construct the principal component analysis for images of a convex Lambertian object, explicitly taking attached shadows into account, and find the principal eigenmodes and eigenvalues with respect to lighting variability. Our analysis makes use of an analytic formula for the irradiance in terms of spherical-harmonic coefficients of the illumination [1, 14], and shows, under appropriate assumptions, that the principal components or eigenvectors are identical to the spherical harmonic basis functions evaluated at the surface normal vectors. Our main contribution is in extending these results to the single-image case, showing how the principal eigenmodes and eigenvalues are affected when only a limited subset (the upper hemisphere) of normals is available, and the spherical harmonics are no longer orthonormal over the restricted domain. Our results are very close, both qualitatively and quantitatively, to previous empirical observations and represent the first valid theoretical explanation of these observations. Our analysis is also likely to be of interest in other areas of computer vision and image-based rendering. In particular, our results indicate that using complex illumination for photometric problems in computer vision is not significantly more difficult than using directional sources.
Biochemical isolation and physiological identification of the egg- laying hormone in Aplysia californica

It has been determined that the bag cells of Aplysia californica produce two polypeptide species that comigrate on electrophoretic gels containing sodium dodecyl sulfate. By this separation procedure both species can be assigned a molecular weight of approximately 6,000. One of these molecules has an Rf of 0.65 on alkaline discontinuous electrophoresis gels, an isoelectric point at pH 4.8, a gel filtration molecular weight of approximately 12,000, and has no known biological function. The other does not enter alkaline disk gels, has an isoelectric point at approximately pH 9.3, shows a gel filtration molecular weight consistent with that determined by SDS gel electrophoresis, and is the egg-laying hormone.
AuDis: an automatic CRF-enhanced disease normalization in biomedical text

Diseases play central roles in many areas of biomedical research and healthcare. Consequently, aggregating the disease knowledge and treatment research reports becomes an extremely critical issue, especially in rapid-growth knowledge bases (e.g. PubMed). We therefore developed a system, AuDis, for disease mention recognition and normalization in biomedical texts. Our system utilizes an order two conditional random fields model. To optimize the results, we customize several post-processing steps, including abbreviation resolution, consistency improvement and stopwords filtering. As the official evaluation on the CDR task in BioCreative V, AuDis obtained the best performance (86.46% of F-score) among 40 runs (16 unique teams) on disease normalization of the DNER sub task. These results suggest that AuDis is a high-performance recognition system for disease recognition and normalization from biomedical literature. Database URL: http://ikmlab.csie. ncku.edu. tw/CDR2015/AuDis.html
Gangs in School: Exploring the Experiences of Gang-Involved Youth

This study explores three questions: (1) What are the criteria that current or formerly gang-involved youth use to identify the presence of gangs in school? (2) Do gang activities produce incivilities and victimizations within the school context? and (3) What is the impact of a gang presence on youth in the school, specifically with respect to the presence or absence of fear? We examine the influence of gangs in schools through qualitative analysis of 180 in-depth semistructured interviews. The sample includes youth with varying levels of gang involvement who attended schools across the United States. Youth relied on personal knowledge and visual cues to identify gangs in their school. Despite the occurrence of vicarious victimizations and incivilities at the hands of gang youth, respondents indicated that gangs did not impact their school life. These youth frequently used normalization and delimitation processes to deal with gangs in their school.