Miracle-dz/UniFAR-FTUs huggingface dataset:
Turbulent Stability of Emergent Roles: The Dualistic Nature of Self-Organizing Knowledge Coproduction

Increasingly, new forms of organizing for knowledge production are built around self-organizing coproduction community models with ambiguous role definitions. Current theories struggle to explain how high-quality knowledge is developed in these settings and how participants self-organize in the absence of role definitions, traditional organizational controls, or formal coordination mechanisms. In this article, we engage the puzzle by investigating the temporal dynamics underlying emergent roles on individual and organizational levels. Comprised of a multilevel large-scale empirical study of Wikipedia stretching over a decade, our study investigates emergent roles in terms of prototypical activity patterns that organically emerge from individuals’ knowledge production actions. Employing a stratified sample of 1,000 Wikipedia articles, we tracked 200,000 distinct participants and 700,000 coproduction activities, and recorded each activity’s type. We found that participants’ role-taking behavior is turbulent.
On Buyer Selection of Service Providers in Online Outsourcing Platforms for IT Services

The Internet has presumably created a level playing field that allows any service provider across the globe to compete for contracts on online outsourcing platforms for information technology IT services. In this paper, we empirically examine a how country language, time zone, cultural differences and the country's IT development affect buyers' selection of service providers in online outsourcing platforms; and b how the reputation of service providers moderates the proposed effects of country differences and the country's IT development. We integrated a unique data set formed by a sample of 11,541 software development projects from an online outsourcing platform matched with archival sources on the language, time zone, culture, and IT development of countries. Since price is typically endogenous in any supply demand system, we used the exogenous variation of the normalized exchange rate of the currency among countries, as a "cost-shifter" type instrumental variable IV for econometric identification. Our panel data analyses results both with and without IV show that buyers are negatively affected by country differences in terms of language, time zone, and culture, and prefer service providers from countries with higher IT development. Notably, the reputation of service providers attenuates the negative effects of language and cultural but not time zone differences, while it substitutes the positive effect of the country's IT development. We discuss the study's theoretical and managerial implications for understanding the global dynamics of online outsourcing platforms and better designing these platforms. The online appendix is available at https://doi.org/10.1287/isre.2017. 0709 .
Face detection based on AdaBoost algorithm with Local AutoCorrelation image

This paper proposes a novel concept of Local AutoCorrelation (LAC), which is converted to LAC images for robust face detection under varying illumination conditions. We have applied LAC images to face detection based on AdaBoost algorithm. MIT CBCL images are used for training, while CMU PIE face database including a variety of illumination directions is used for detection. As a result, the LAC is found to be so effective that face detection rate is improved by up to 4.7%.
Inductive Model Analysis Systems: Enhancing Model Analysis in Decision Support Systems

After building and validating a decision support model, the decision maker frequently solves often many times different instances of the model. That is, by changing various input parameters and rerunning different model instances, the decision maker develops insights into the workings and tradeoffs of the complex system represented by the model. The purpose of this paper is to explore inductive model analysis as a means of enhancing the decision maker's capabilities to develop insights into the business environment represented by the model. The justification and foundation for inductive model analysis is based on three distinct literatures: 1 the cognitive science theory of learning literature, 2 the decision support system literature, and 3 the model management system literature. We also propose the integration of several technologies that might help the modeler gain insights from the analysis of multiple model instances. Then we report on preliminary tests of a prototype built using the architecture proposed in this paper. The paper concludes with a discussion of several research questions. Much of the previous MIS/DSS and management science research has focused on model formulation and solution. This paper posits that it is time to give more attention to enhancing model analysis.
A Taxonomy of Care for Youth

Purpose: Statements about potentially effective components of interventions in child and youth care are hard to make because of a lack of a standardized instruments for classifying the most salient care characteristics. The aim of this study is to present an empirically developed taxonomy of care for youth (Tocfy) which is feasible for use in daily practice, including an explanation of the developmental process itself. Methods: The development procedure, comprising of different stages, contributed significantly to the foundation of the taxonomy. Results: The operational version consists of six domains: (1) contents of the intervention; (2) judicial context; (3) duration of the intervention; (4) intensity of the intervention; (5) intervention recipients; and (6) expertise of professionals. The terminologies used to describe treatment programs and the levels of classification were standardized for each organization participating in our study. By doing so, the feasibility and manageability of the taxonomic system in daily practice increased. Discussion: Using tocfy in daily practice provides the opportunity to gather information on care and treatment characteristics within care organizations. The strength of tocfy is that its framework can be extended to other care organizations within child and youth care. Replication of the findings of our study in other child and youth care settings is needed, because this study only covered one province in the Netherlands.
Capacitação dos trabalhadores de saúde na atenção básica: impactos e perspectivas

During the worker's technical-political training development, some troubles must be surpassed in order to implement permanent education proposals on health services. Frequently, courses, trainings and other types of education happen disarticulated of the context services and sometimes they don’t respond the needs of managers and workers. The aim of this study was to analyze the impact of training and workers permanent education from the Primary Health Care of the city of Sao Carlos/SP 2003 onwards. It is an analytic qualitative research that was developed, through structured interviews with 14 managers and 24 workers from the health sector. The thematic category analysis, based on the Social Representation Theory was used to data analysis. To this of health workers group, the Social Representation on training is a technical-professional update process that needs to be (un) built to change the health practices. Contextualization is necessary in training proposals on the health sector reality and implemented with valorization politics of the worker. Permanent education in health embraces these features and may be an important changing strategy on service education.
The Sri Lankan Personal Genome Project: an overview

The first Sri Lankan Personal Genome was sequenced heralding the entry of Sri Lanka into the new era of whole genome sequencing. This paper explains the background and the rationale for the project, gives a brief overview of what was found in the Sri Lankan Personal Genome, and discusses the future directions of the project. DOI: http://dx.doi. org/10.4038/sljbmi.v2i1. 3711 Sri Lanka Journal of Bio-Medical Informatics 2011; 2 :4-8
Research Note - Competitive Brand Salience

Brand salience---the extent to which a brand visually stands out from its competitors---is vital in competing on the shelf, yet is not easy to achieve in practice. This study proposes a methodology to determine the competitive salience of brands, based on a model of visual search and eye-movement recordings collected during a brand search experiment. We estimate brand salience at the point of purchase, based on perceptual features color, luminance, edges and how these are influenced by consumers' search goals. We show that the salience of brands has a pervasive effect on search performance, and is determined by two key components: The bottom-up component is due to in-store activity and package design. The top-down component is due to out-of-store marketing activities such as advertising. We show that about one-third of salience on the shelf is due to out-of-store and two-thirds due to in-store marketing. The proposed methodology for competitive salience analysis exposes the optimal visual differentiation level of a brand versus its competitors, and of each SKU versus the other SKUs of the same brand. The model of the visual search process and methodology for competitive salience analysis enable diagnostic analyses of the current levels of visual differentiation of brands and SKUs at the point of purchase, and provide directions for increasing these.
PowerForecaster: Predicting Smartphone Power Impact of Continuous Sensing Applications at Pre-installation Time

Today's smartphone application (hereinafter 'app') markets miss a key piece of information, power consumption of apps. This causes a severe problem for continuous sensing apps as they consume significant power without users' awareness. Users have no choice but to repeatedly install one app after another and experience their power use. To break such an exhaustive cycle, we propose PowerForecaster, a system that provides users with power use of sensing apps at pre-installation time. Such advanced power estimation is extremely challenging since the power cost of a sensing app largely varies with users' physical activities and phone use patterns. We observe that the time for active sensing and processing of an app can vary up to three times with 27 people's sensor traces collected over three weeks. PowerForecaster adopts a novel power emulator that emulates the power use of a sensing app while reproducing users' physical activities and phone use patterns, achieving accurate, personalized power estimation. Our experiments with three commercial apps and two research prototypes show that PowerForecaster achieves 93.4% accuracy under 20 use cases. Also, we optimize the system to accelerate emulation speed and reduce overheads, and show the effectiveness of such optimization techniques.
eMotion: retrospective in-car user experience evaluation

Well-established self-reporting methods in HCI such as the Experience Sampling Method (ESM) prove rather limited for sampling in-car experiences, as they distract the driver from the primary task of driving. In this work we present eMotion, a mobile application that provides a lightweight alternative to Experience Sampling. eMotion uses the front and back facing cameras of a mobile device with the goal of unobtrusively capturing drivers' facial expressions along with 10-sec videos of the outside landscape, the location, and the speed of the car at the moment of sampling. All these logs are later presented to the user with the goal of helping her recall her experience (e.g. experienced stress) at that moment. We report on the design of eMotion as well as a study design, with which we will try to assess the validity of the elicited data.
20-Gb/s QPSK W-band (75-110GHz) wireless link in free space using radio-over-fiber technique

We demonstrate 20-Gb/s W-band wireless transmission in free space with a distance of 30mm using optical signal generation. Optically synthesized QPSK signal and direct optical upconversion technique ease generation of W-band RoF signals for dual purpose of wireline and wireless transmission link. A W-band radio receiver with W-band frequency downconversion and digital signal processing will be applicable for any W-band radio detection.
Investigating the Relationship Between the Content of Online Word of Mouth, Advertising, and Brand Performance

We study the relative importance of online word of mouth and advertising on firm performance over time since product introduction. The current research separates the volume of consumer-generated online word of mouth OWOM from its valence, which has three dimensions---attribute, emotion, and recommendation oriented. Firm-initiated advertising content is also classified as attribute or emotion advertising. We also shed light on the role played by advertising content on generating the different types of OWOM conversations. We use a dynamic hierarchical linear model DHLM for our analysis. The proposed model is compared with a dynamic linear model, vector autoregressive/system of equations model, and a generalized Bass model. Our estimation accounts for potential endogeneity in the key measures. Among the different OWOM measures, only the valence of recommendation OWOM is found to have a direct impact on sales; i.e., not all OWOM is the same. This impact increases over time. In contrast, the impact of attribute advertising and emotion advertising decreases over time. Also, consistent with prior research, we observe that rational messages i.e., attribute-oriented advertising wears out a bit faster than emotion-oriented advertising. Moreover, the volume of OWOM does not have a significant impact on sales. This suggests that, in our data, “what people say” is more important than “how much people say. ” Next, we find that recommendation OWOM valence is driven primarily by the valence of attribute OWOM when the product is new and driven by the valence of emotion OWOM when the product is more mature. Our brand-level results help us classify brands as consumer driven or firm driven, depending on the relative importance of the OWOM and advertising measures, respectively.
Database Submission - Market Dynamics and User-Generated Content About Tablet Computers

Our Tablet Computer data set, collected from various websites, contains market dynamics related to 2,163 products, characteristics of 794 products, more than 40,000 consumer-generated product reviews, and information about 39,278 reviewers. The market dynamic information was collected weekly for 24 weeks starting February 1, 2012. Our Tablet Computer data set comprises four tables: the Market Dynamics of Products, Product Characteristic Information, Consumer-Generated Product Reviews, and Reviewer Information tables. In turn, it offers three unique properties. First, it contains both structured product information and unstructured product reviews. Second, it comprises product characteristic information and market dynamic information. Third, this data set integrates user-generated content with manufacturer-provided content. This integrated data set available at http://pubsonline.informs. org/page/mksc/online-databases is valuable for both academics and practitioners who conduct research related to marketing, information systems, computer science, and other fields using digital data readily available through the Internet.
Correlation of heart rate variability with ST changes during 24 hour Holter monitoring

Heart rate variability (HRV), which is related to the activity of the automatic nervous system, was monitored during 24-h Holter recordings in 26 normal subjects. The power spectrum (PS) was obtained and the fluctuations in heart rate in three frequency bands were correlated with ST segment changes. Significant variations in HRV and ST segment amplitude were found during the night. ST level and the power of the HRV in the low- (0-0.05 Hz) and high- (0.2-0.35 Hz) frequency bands were increased significantly during the night in the majority of the subjects. The PS in the mid- (0.05-0.2 Hz) frequency range was significantly reduced at night. The heart rate and its global variability also decreased significantly during the night. The nocturnal changes in the PS in the low-frequency band and in the ST level may be related to alterations of the autonomic nervous system. <<ETX>>
An ultra-low-power pseudo-random number generator based on biologically inspired chaotic silicon neuron circuit

This work presents an ultra-low-power, biologically inspired pseudo-random number generator based on the Hodgkin-Huxley silicon neuron circuit. The chaotic phenomenon observed in neurons is exploited to generate random numbers. The random sequence generated by the proposed system passed the statistical tests specified by Federal Information Processing Standard. The proposed random number generator circuit provides an ultra-low-power alternative for pseudo-random number generation with 180 nW power consumption.
E-Commerce Item Recommendation Based on Field-aware Factorization Machine

The RecSys 2015 contest [1] seeks the best solution to a top-N e-commerce item recommendation problem. This paper describes the team Random Walker's approach to this challenge, which won the 3rd place in the contest. Our solution consists of the following components. Firstly, we cast the top-N recommendation task into a binary classification problem and extract original features from the raw data. Secondly, we learn derived features using field-aware factorization machines (FFM) and gradient boosting decision tree (GBDT). Lastly, we train 2 FFM models with different feature sets and combine them by a non-linear weighted blending. This solution is the result of numerous tests and the scheme turns out to be effective. Our final solution achieved a score of 61075.2, ranking in the third place on the public leaderboard.
Machine Learning Algorithms for Environmental Sound Recognition: Towards Soundscape Semantics

This paper investigates methods aiming at the automatic recognition and classification of discrete environmental sounds, for the purpose of subsequently applying these methods to the recognition of soundscapes. Research in audio recognition has traditionally focused on the domains of speech and music. Comparatively little research has been done towards recognizing non-speech environmental sounds. For this reason, in this paper, we apply existing techniques that have been proved efficient in the other two domains. These techniques are comprehensively compared to determine the most appropriate one for addressing the problem of environmental sound recognition.
Food Image Recognition by Using Bag of SURF: Color Features

The importance of researches in the old days is the retrieval of similar objects. Content-Based Image Retrieval (CBIR) system uses low-level features such as texture, color, and shape to extract the features, but when it comes to food images it is hard to get satisfactory accurate results. Recognition of food images has recently become very important and challenging due to people's health care, religious or cultural reasons. In this paper, we propose a system that recognizes small food images consist of 10 categories by using bag of features (BoF) based on SURF detection features. In addition, we achieved up to 78% accuracy rate, and try to improve the feature detection by using color features at the same time with the SURF feature detection. This experiment shows that more accurate rate of results will be obtained than the existing methods.
Facial Expression Training System using Bilinear Shape Model

We introduce a facial expression training system using the bilinear shape model which helps people to practice making a facial expression. The user face on the camera preview screen is reconstructed into a 3D face model and the model is transformed to blend shape model which represents the facial expression. This way, the system can precisely analyze the facial expression of the user. With target 3D face model appearing on the screen, the 3D face model changes its facial expression, it leads the user to change his facial expression to become look like same. The system recognizes whether the facial expression of the user is same with the one of 3D face model. As the system gives the various missions to user to change his facial expression, user can practice the facial expression. It can be used for bell's palsy patient who needs face rehabilitation exercise or someone who need to practice unique facial expression such as stewardess smile or facial mimicry.
Customer Choice and Routing in Queueing Networks

We study self-interested routing in stochastic networks, taking into account the discrete stochastic dynamics of such networks. We analyze a two-station multiclass queueing network in which the system manager chooses the scheduling rule and individual customers choose routes in a self-interested manner. We show that this network can be unstable in Nash equilibrium under some scheduling rules. We also design a nontrivial scheduling rule that negates the performance degradation resulting from self-interested routing and achieves a Nash equilibrium with performance comparable to the first-best solution.
The Landscape of Electronic Market Design

This paper presents an introductory survey for this special issue of Management Science on electronic markets. We acquaint the reader with some fundamental concepts in the study of electronic market mechanisms, while simultaneously presenting a survey and summary of the essential literature in this area. Along the way, we position each of the papers presented in this special issue within the existing literature, demonstrating the deep impact of these 14 articles on an already broad body of knowledge.
Prevalence of camel ( Camelus dromedaries ) mastitis in Jijiga Town, Ethiopia

A cross sectional study of camel mastitis was conducted on 384 lactating camels from Jijiga between November 2011 to April 2012 to estimate the prevalence and causes of mastitis, as well the risk factors involved on disease. Prevalence of mastitis was assessed by using California mastitis test (CMT). An overall prevalence of camel mastitis was found to be 30.2% (116/384) out of which, 4.9% (19/384), 25.3% (97) were clinical and sub-clinical mastitis, respectively. The overall quarter level prevalence was 25.8% (397/1536). There was significant (P<0.05) in prevalence between camels with teat lesion, tick infestation, parity or age to mastitis than those without these factors. Microbiological examination of 174 randomly selected CMT positive milk samples from clinical quarters, revealed that the majority of the isolates were coagulase negative Staphylococci (39.6%), followed by Streptococcus dysagalactiae (22.2%), Corynebacteria spp. (9%), Bacillus spp. (7.6%), Streptococcus uberis (7.6%), Escherichia coli (6.3%), Staphylococcus aureus (4.2%) and Streptococcus agalactiae (3.5%). The prevalence of camel mastitis in the study area was found to be significantly high. Therefore, implementation of integrated approaches has great importance in the study sites for the prevention and control of mastitis hence minimizing economic loss and prevents significant public health risks.
Nutritional considerations in intravenous drug misusers: a review of the literature and current issues for dietitians

Poor nutritional status and inadequate dietary intake in intravenous drug misusers (IVDMs) is a well-recognized problem among those involved in their care. However, there are very few published studies to substantiate these observations. This paper provides a review of the current literature and outlines the aims of dietary advice for IVDMs.