Miracle-dz/UniFAR-FTUs huggingface dataset:
International Software Product Development for World Markets in a Software Start-up

This study investigates software companies’ international software development approaches for world markets. It has been conducted by a) analyzing the resource-based theory and cooperation and network theories, b) reviewing the literature in the field of international software product development for world markets, c) performing a case analysis of a software startup company’s international software product development for world markets, and d) interviewing experts and practitioners in the field of international software product development. This study contributes both in terms of theory and practice. At the theoretical level, the study introduces a framework of international software product development for world markets. It can be used as a basis for further research. This study presents an empirical case analysis of international software product development of a start-up company, which is using innovative technologies and a holistic approach to develop software for wireless telecommunications industry. Their software product development spreads over two continents (i.e., USA and India) and targets world markets from the outset. At the practical level, the research results will help small software companies to avoid the problems and obtain benefits from international software product development. This study also suggests directions for future research.
Working Papers in Economics and Statistics Social Norms, Third-party Observation and Third-party Reward Social Norms, Third-party Observation and Third-party Reward

This paper examines the influence of third-party observation and third-party reward on behavior in an experimental prisoner's dilemma (PD) game. Whereas the existing literature on third-party intervention as a means to sustain social norms has dealt almost exclusively with third-party punishment, we show that both third-party observation and third-party reward have positive effects on cooperation rates, compared to a treatment where no third party is involved. Third-party reward is more effective in increasing cooperation than third-party observation. However, rewards are given too late to prevent a steady downward trend of cooperation rates.
Study of Application of Network Coding on NoCs for Multicast Communications

Embedded Systems-on-Chips are becoming more complex and multi-functional, consist of tens or hundreds of integrated IPs supporting one or several applications. For such systems, Network-on-Chip (NoC) is proposed to overcome the communication challenges and bandwidth bottlenecks. In this work, we propose the use of Network Coding (NC) for NoC-based SoC to improve performance in terms of latency and power consumption. Network coding is a technique allows nodes to combine arriving packets into encoded packets instead of simply forwarding them. NC aims to optimize data flow leading to improve network throughput and reliability. This paper discusses the feasibility of NC for multicast communication in NoC and presents a set of algorithms to select intermediate nodes in order to apply NC, also introduces a heuristic to rapidly identify the applicability of NC according to the relative positions of sources and destinations nodes. Moreover we evaluate NC potential for multicast communication over various NoC sizes under different evaluation parameters (number of hops, steps and live packets). It was possible to achieve performance improvement by reducing the total number of hops by 24% and total number of live packets by 35%. These results demonstrate the potential of NC to enhance NoC performance.
Weighted Support Vector Machine Based Clustering Vector

In order to set the weights of weighted support vector machine, the method that based the clustering vector was proposed in this paper. The clustering vector was brought in and the weights were set by calculating the distances between the data of every class and their clustering vector. In SVM, the data were mapped into a higher dimensional feature space and the distribution of data was changed, so the clustering vectors and distances were calculated in the feature space. It was confirmed by simulation that the rate of accuracy was promoted in this way, and the classification accuracy for the class with small training size was improved for the uneven training data. The effect of outliers can also be alleviates by using this method.
Polypharmacy and Health-Related Quality of Life Among US Adults With Arthritis, Medical Expenditure Panel Survey, 2010–2012

Introduction Our objective was to determine the relationship between polypharmacy (treatment with prescription drugs from 6 or more drug classes concurrently) and health-related quality of life (HRQoL) among US adults with arthritis. Methods We conducted a retrospective cohort study that used 2-year longitudinal data from the Medical Expenditure Panel Survey to analyze a cohort of 6,132 adults aged over 21 years with arthritis. Measures of HRQoL were the summary scores from the mental component summary (MCS) and physical component summary (PCS) of the 12-item short-form health survey. Unadjusted and adjusted regression models were used to evaluate the association between polypharmacy and HRQoL measures. We used SAS, version 9.4, (SAS Institute Inc) to conduct all analyses. Results In unadjusted analyses, adults with arthritis taking prescription drugs from 6 or more drug classes concurrently had significantly lower MCS and PCS scores (β, −3.11, P < .001 and β, −10.26, P < .001, respectively) than adults taking prescription drugs from fewer than 6. After controlling for the demographic characteristics, number of mental and physical chronic conditions, and baseline MCS and PCS scores, adults taking prescription drugs from 6 or more drug classes concurrently had significantly lower PCS scores (β, −1.68, P < .001), than those taking prescription drugs from fewer than 6. However, no significant difference in MCS scores was found between adults taking prescription drugs from 6 or more drug classes concurrently and those taking prescription drugs from fewer than 6 (β, −0.27, P = .46). Conclusion Polypharmacy is significantly associated with lower PCS scores among adults with arthritis. Because polypharmacy can lead to drug–drug and drug–disease interactions, health care providers need to consider the risk and adopt a cautious approach in prescribing multiple drugs to manage chronic conditions and in choosing therapies to improve HRQoL among adults with arthritis.
A Susceptible-Infected-Susceptible Model with Reintroduction for Computer Virus Epidemics

We consider a modification of the susceptibleinfected-susceptible (SIS) epidemiological model for modeling the spread of computer viruses. The model includes a reintroduction or reinfection parameter, which models the re-release of a computer virus or the introduction of a new virus. We analyze the behavior of the model, and compare the results to previous research and to simulations.
Stereo Image Processing for ADAS and Pre-Crash Systems

Stereovision is a technique for range detection able to provide accurate 3D description of the environment in real time. In the last years due to the progresses in computer and camera technology the stereovision have became a robust alternative for environment sensing in driving assistance systems. The dense stereo sensor presented in this paper answers to the divers requirements of the urban scenario through a multitude of detection modules, built on top of a hybrid (hardware plus software) dense stereo reconstruction engine. The sensor is able to detect, track and classify clothoid and non-clothoid lanes, drivable areas in the absence of lane markings, cars, pedestrians and road maintenance signs. The hybrid stereovision engine and the proposed detection algorithms allow accurate sensing of the demanding urban scenario at a high frame rate being suitable for use in ADAS. The presented sensor is tested for precrash applications.
International Journal of Computer Mathematics a Variational Model for Spect Reconstruction with a Nonlinearly Transformed Attenuation Prototype a Variational Model for Spect Reconstruction with a Nonlinearly Transformed Attenuation Prototype

This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. In single photon emission computed tomography (SPECT) reconstruction, the objective is to reconstruct the density of a radioactive marker inside a patient from projections. In this work, state-of-the-art reconstruction models for SPECT reconstruction with a so-called attenuation prototype are discussed. A multimodal correspondence problem is brought up and a novel variational model for SPECT reconstruction is presented that addresses the correspondence problem. This is followed by a description of a numerical realization. Numerical results show the necessity of the proposed SPECT reconstruction model.
An evolving network model with consideration of node differences

In many real networks, the importance of the nodes is different from each other due to their different functions. Considering this reason, a new evolving network model is proposed in this paper, which introduces the node differences. By ranking the new nodes according to their importance, they are designed to connect different numbers of the existing nodes. The model analysis and simulation results show the proposed network yields a scale free and small world properties. Moreover, the new model has large cluster coefficient which is in conformity with the real networks. Therefore, it is suitable to model many real networks.
Artificial Neural Networks in Auditing : State of the Art

Very many things in our business and auditing environment are changing at an increasing rate. One central theme in auditing is how information technology developments affect the nature of the audit process and the audit skills. Auditors have to ask how to operate in new environments. New information technology support systems for monitoring and controlling operations could be useful. Artificial neural network (ANN) based information systems are proposed as one possible solution as a support tool for auditors. This article introduces the ANN technology and reviews the literature on auditing ANN applications. The review showed that the main application areas in auditing were material errors, management fraud, and support for going concern decision. ANNs have also been applied to internal control risk assessment, audit fee, and financial distress problems. In addition the paper summarises modeling issues of the ANN applications pertaining to auditing problems. Finally, the paper outlines possible tasks were ANN based support systems could be used within auditing.
Insight into the Properties of the UK Power Consumption Using a Linear Regression and Wavelet Transform Approach

In this paper, the relationship between the Gross Domestic Product (GDP), air temperature variations and power consumption is evaluated using the linear regression and Wavelet Coherence (WTC) approach on a 1971-2011 time series for the United Kingdom (UK). The results based on the linear regression approach indicate that some 66% variability of the UK electricity demand can be explained by the quarterly GDP variations, while only 11% of the quarterly changes of the UK electricity demand are caused by seasonal air temperature variations. WTC however, can detect the period of time when GDP and air temperature significantly correlate with electricity demand and the results of the wavelet correlation at different time scales indicate that a significant correlation is to be found on a long-term basis for GDP and on an annual basis for seasonal air-temperature variations. This approach provides an insight into the properties of the impact of the main factors on power consumption on the basis of which the power system development or operation planning and forecasting the power consumption can be improved.
Performance modelling and evaluation of an adaptation management system

Communication systems are becoming more complex due to the advancements and heterogeneity in device and network technologies. The diversity of content and services offered to users is increasing and services have become an important source of revenue for network operators. However, the success of service providers depends on the adaptability of their services to user environments and preferences. Hence content and service adaptation is of paramount importance. In an adaptation manager is proposed. This paper presents the performance model of the adaptation management system developed in the high level formalism PEPA, and its evaluation. The model is derived from the adaptation manager design and system interactions. The results from the evaluation are presented and analysed to determine the factors that affect system performance and how the latter can be improved.
FROM THE BRUNN–MINKOWSKI INEQUALITY TO A CLASS OF POINCARÉ-TYPE INEQUALITIES

We present an argument which leads from the Brunn–Minkowski inequality to a Poincare-type inequality on the boundary of a convex body K of class in Rn. We prove that for every ψ ∈ C1(∂K) Here denotes the (n - 1)-dimensional Hausdorff measure, νK is the Gauss map of K and DνK is the differential of νK i.e. the Weingarten map.
An Energy-aware Routing Scheme in Delay Tolerant Mobile Sensor Networking

In Delay Tolerant Mobile Sensor Networking (DTMSN), mobile sensor nodes are usually limited to their energy capacity, one important concern in routing design of DTMSN is energy consumption. This paper presents a number of variations of the Epidemic Routing Protocol (ERP) to extend the DTMSN lifetime. It introduces the analytical model for ERP, after introducing the concepts behind the Target Delivery Probability and Minimum Delivery Probability, it defines the network lifetime. In this paper, it firstly studies many variations of the Epidemic Routing Protocol to extend the lifetime of the DTMSN. Secondly, based on the Epidemic Routing Protocol, three schemes are introduced. Those schemes rely on the limiting the times of message allowed for propagation (LT scheme), directly controlling the number of the copies (LC scheme), split the copies to the residual energies of the nodes (LE scheme). Finally, with the experiment and the validation of the simulation, the LE scheme can significantly maximize the lifetime of DTMSN, because it minimizes the number of copies and that shifts the generation of the copies to the nodes with larger residual energy. Copyright © 2014 IFSA Publishing, S. L.
Segmentation of strain-encoded magnetic resonance images using graph-cuts

Imaging of the heart anatomy and function using Strain Encoded (SENC) magnetic resonance imaging (MRI) is a powerful tool for diagnosing a number of heart diseases. Despite excellent sensitivity to tissue deformation, the technique inherently suffers from elevated noise level which hinders proper automatic segmentation using conventional techniques. In this work, we propose a method to accurately segment the left ventricle myocardium from strain encoded-MR short axis images. The method is based on a modified formulation of the graph cuts algorithm. A novel cost function based on a probabilistic model for blood and tissue signals is used to achieve proper segmentation results. The method is tested on datasets for eleven human subjects (5 normal and 6 patients). Quantitative evaluation of the proposed method is compared against manual segmentation and the native graph cut algorithm. The results show that the adopted probabilistic model significantly improves the segmentation accuracy compared to the typical cost function of the native graph cuts algorithm. A True Positive and True Negative rates of 92% and 95% respectively have been achieved using the proposed method.
Minimum Phone Error and I-smoothing for improved discriminative training

In this paper we introduce the Minimum Phone Error (MPE) and Minimum Word Error (MWE) criteria for the discriminative training of HMM systems. The MPE/MWE criteria are smoothed approximations to the phone or word error rate respectively. We also discuss I-smoothing which is a novel technique for smoothing discriminative training criteria using statistics for maximum likelihood estimation (MLE). Experiments have been performed on the Switchboard/Call Home corpora of telephone conversations with up to 265 hours of training data. It is shown that for the maximum mutual information estimation (MMIE) criterion, I-smoothing reduces the word error rate (WER) by 0.4% absolute over the MMIE baseline. The combination of MPE and I-smoothing gives an improvement of 1 % over MMIE and a total reduction in WER of 4.8% absolute over the original MLE system.
Specific amino-acid residues in the N-terminus and TM3 implicated in channel function and oligomerization compatibility of connexin43

To identify signals that convey connexin oligomerization compatibility, we have aligned amino-acid sequences of α and β group connexins (Cx) and compared the physico-chemical properties of each homologous amino-acid residue. Four positions were identified that consistently differed betweenα and β-type connexins; two are located in the N-terminal domain (P1 and P2, corresponding to residues 12 and 13 of the Cx43 sequence), and two in the third trans-membrane-spanning domain TM3 (P3 and P4, corresponding to residues 152 and 153 of the Cx43 sequence). Replacement of each of these residues in Cx43 (an α-type connexin) with the corresponding residues of Cx32 (a β-type connexin) resulted in the assembly of all variants into gap junctions; however, only the P4 variant was functional, as indicated by lucifer yellow dye transfer assays. The other three variants exerted a moderate to severe dose-dependent, dominant-negative effect on co-expressed wild-type (wt) Cx43 channel activity. Moreover, a significant dose-dependent, trans-dominant inhibition of channel activity was observed when either one of the N-terminal variants was co-expressed with wt Cx32. Assembly analyses indicated that dominant and trans-dominant inhibitory effects appeared to be based on the oligomerization of wt and variant connexins into mixed connexons. Interestingly, the identified N-terminal amino acids coincide with the position of naturally occurring, disease-causing missense mutations of severalβ -connexin genes (Cx26, Cx30, Cx31, Cx32). Our results demonstrate that three of the identified discriminative amino-acid residues (positions 12, 13 and 152) are crucial for Cx43 channel function and suggest that the N-terminal amino-acid residues at position 12/13 are involved in the oligomerization compatibility of α and β connexins.
The calibration of BEPC beam position monitors

The basic requirement for the BEPC beam position monitor is the measurement of the beam orbit with 0.1 mm precision near the collision point. To improve the measurement accuracy, the response of the beam position monitor pickups was mapped in the laboratory before they were installed in the BEPC ring. The microcomputer-controlled test set consists of high frequency coaxial switches to select each pickup electrode, a movable antenna to simulate the beam, a signal source, a spectrum analyzer to measure the pickup signals, and analysis software. The signal source operates well below the −3 dB cutoff frequency of the pickups (buttons). We believe that the low-frequency measurement yields the same information as the real beam. The button signals were clear. This calibration technique is satisfactory for BEPC operation.
Analysis of the effect of attitude on the selection of Kinesiology program female student of Faculty of Economics and Business, University of Zagreb

Na uzorku od 332 studentice Ekonomskog fakulteta Zagreb, 1. i 2. godine studija proveden je motivacijski upitnik sportske orijentacije od 25 cestica. Sve ispitanice podijeljene su u 3 kategorije, obzirom na kineziolosku aktivnost kojom se bave na nastavi TZK na fakultetu: odbojka (117 ispitanica), kosarka (35 ispitanica) i aerobika (180 ispitanica). Primijenjena je diskriminacijska analiza za obradu podataka. Grupe se statisticki znacajno razlikuju najvise u cesticama koje opisuju motiv kompetitivnosti. Odbojkasice su odstupile od kosarkasica i studentica aerobika u smjeru iskljucive orijentiranosti na motivaciju i uspjeh u natjecanjima. Cini se da nastavu TZK ne treba suvise usmjeravati prema natjecateljskim oblicima sportskih igara.
Literacy programs efficacy for developing children’s early reading skills in familiar language in Zambia

This study investigated the comparative efficacy of a phonics-based reading program and a language experience approach based literacy program to develop reading skills among Zambian early childhood school learners. The learners (n = 1 986; Grade 2 level; females = 50.1%) took either the phonics-based reading program (n = 1 593) or the alternative language experience approach based program (n = 393). They were all assessed for reading skills utilising the Early Grade Reading Assessment test (EGRA) in four languages (Cinyanja, Icibemba, Kiikaonde, and Silozi). Results suggest that learners in phonics-based literacy program were significantly better in letter-sound knowledge in all the four languages. Additionally, they were significantly better in reading skills (non-word reading, oral passage reading, and reading comprehension), yet only in Icibemba and Silozi, as compared to those who took the alternative program. Results reveal that children in the Primary Literacy Program (PLP) had significantly better performance in most reading skills than in the Primary Reading Program (PRP). However, the effect sizes were small or medium. The high floor effect in all reading-related measures is an indication that by following either PRP or the recently implemented PLP, most children do not acquire basic reading skill of the transparently written language they are familiar with. Instruction of the sounds of letters requires special attention where digital training tools (such as GraphoGame) may provide the most effective help to both teachers and children.
An implementation framework of mapreduce email social network analysis

In this paper, we introduce our own implementation of MapReduce graph-theoretic algorithms for Email social network analysis on the Hadoop platform. Graph theory is a powerful tool for social network analysis and MapReduce is a well-known paradigm for distributed parallel computing. However, based on our own experience, unlike writing conventional Java/C++ programs, writing Java programs to implement MapReduce graph-theoretic algorithms is not straight-forward, even for some fundamental graph-theoretic algorithms. In this paper, for the problem of Email social network analysis, we compare the performance of cloud computing programs with that of conventional computer programs. We show that as long as the size of the input data exceeds a threshold, the cloud computing programs outperform their conventional counterparts.