Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors affecting learners' knowledge sharing intentions in web-based learning

In this study, a framework based on the theory of planned behavior was proposed to find out the major factors which could have influences on learners' knowledge sharing intentions. A field survey has been conducted with 150 learners who had experiences in web-based learning. The proposed hypotheses were examined by structural equation modeling. According to the analysis results, we have found that: 1) the knowledge sharing attitude is mainly influenced by subjective norms, expected contribution, and expected loss; 2) the knowledge sharing attitude is secondarily influenced by disincentives and altruism; 3) the subjective norm is mainly influenced by instructors' expectation; 4) the perceived behavioral control is mainly influenced by the abilities of learners in using information technologies; 5) the knowledge sharing intention is mainly influenced by knowledge sharing attitude and subjective norms. We hope this study is helpful to instructors for designing good teaching strategies to improve knowledge sharing among learners and enhance learning performance in web-based learning.
Deadline-aware load balancing for MapReduce

As cloud computing gains its momentum in big data processing and providing on-line services, there are increasing demands to offer responsive services to users and to improve the effectiveness in server utilization. Most previous work studied the fairness among user requests, the workload balancing among servers, and the support of real-time applications individually. Different from those state-of-the-art work, we focus on the joint considerations of workload balancing and deadline satisfaction in facing user requests for MapReduce. In particular, scheduling algorithms are proposed with a constant approximation bound to balance the server workloads and, at the same time to meet the response time requirements of MapReduce jobs. The proposed scheduling algorithms are then implemented with our proposed resource manager for the open source implementation of Hadoop. We evaluate our design based on performance metrics including balancing server workloads and meeting jobs' response-time requirements. Experimental results show the effectiveness of our design through real testbed implementation.
Performance Comparison of Weed Detection Algorithms

Weed control is essential in agricultural productivity as weeds act as a pest to crops. The conventional methods of weed removal are time-consuming and require more manual labour work. Hence there is a need to automate this process. The objective of the proposed system is to detect weed from crop using machine learning algorithms. The exhaustive dataset is collected for four different commercial crops and two types of weeds such as Para grass and Nutsedge. Excess green method and Otsu’s thresholding is used for masking the soil and extract the region of interest. The shape features of an image are extracted to provide distinguish properties between weed and crop. The classification of weed and crop has experimented with three different classifiers: Support Vector Machine, Artificial Neural Network and Convolutional Neural Network. The performance comparison of weed detection algorithms is executed on the Open CV and Keras platform using python language.
Using Kullback-Leibler Divergence Language Models to Find Experts in Enterprise Corpora

The issue of expert finding within an organization has received increased attention in past few years due to its significant importance in knowledge management. Till now, various solutions have been proposed to solve this problem. Among these solutions,generative probabilistic language modeling techniques are most frequently adopted. In this work, we propose a novel model to find experts in enterprise corpora based on Kullback-Leibler Divergence Language Model which has been shown to have better retrieval performance than basic language model in the ad hoc retrieval task.Besides, our methods set a document cutoff to restrict the number of documents that used as evidence of expertise when estimating the probability of a candidate being an expert. Finally, we take out experiments on the benchmark provided by TREC. Experimental results show that the approaches based on Kullback-Leibler Divergence outperform methods based on basic language model and the incorporation of document cutoff also brings substantial gains to the final results.
Markets changing, changing markets: Institutional work as market shaping

There is increasing interest in the marketing discipline to adopt an institutional perspective when examining markets. This requires seeing markets as complex systems that evolve through time, rather than as preexisting, stable structures. Using a historical, longitudinal case study, we integrate the “institutional work” framework as a lens to understand the process of market change in the novel, historic case of circus in North America through the 20th century. We explore the decline of the market for traditional American circus, and the emergence, in the 1970s, of the adjacent market for new circus, with a specific focus on the world’s preeminent new circus company, Cirque du Soleil. Theoretical contributions of the article include a “market-shaping activities” framework that illustrates market shaping involves considerably more actors than the dyad of producer and consumer. Market-shaping occurs through an interdependent process involving institutionalized practices, beliefs and expectations, and the intentional activities of market actors at any institutional level. Market change is shared, iterative, and recursive, that is cocreated, and undertaken by market actors both formal and informal. Market shapers do not necessarily work in an orchestrated fashion; nevertheless, vibrant networks of complementary actors contribute positively to the construction of shared identities and normative networks. From a managerial perspective, we find implications for policy makers, funders, strategists, and marketers.
Reinventing the inbox: supporting the management of pending tasks in email

Email was originally designed as a tool for asynchronous communication. However, its current usage goes far beyond that. One of the most commonly performed activities in email is the management of pending tasks. This research focuses on how to support this activity in email and explores alternative solutions that use different external representations of messages and associated tasks.
An implementation and performance measurement of the progressive retry technique

The paper describes a recovery technique called progressive retry for bypassing software faults in message passing applications. The technique is implemented as reusable modules to provide application-level software fault tolerance. The paper describes the implementation of the technique and presents results from the application of progressive retry to two telecommunications systems. The results presented show that the technique is helpful in reducing the total recovery time for message-passing applications. <<ETX>>
Rapid Traversability Assessment in 2.5D Grid-based Map on Rough Terrain

This paper presents a rapid traversability assessment approach based on an extended 2.5D grid-based representaion of the rough terrain. Stereo vision system is used to perceive the environment surrounding robot. Conventional 2D, 3D and other 2.5D grid maps determine the traversability indices of the grids directly from the sensor feedback, while our approach attempts to address the indices of terrain from multiple grids instead. By analyzing the properties of multiple grids that the robot is to traverse, passable grids are distinguished, which also takes the robot's size into account. Fuzzy logic framework is applied to extract traversabiltiy indices from the terrain characteristics. A soccer robot equipped with a stereo vision system is adopted for experiments. The results show that our map is capable of speeding the process of traversability assessment and providing an autonomous mobile robot with a appropriate representation of 3D uneven terrain profile.
Full evolutionary models for PG 1159 stars. Implications for the helium-rich O(He) stars

Aims. We present full evolutionary calculations appropriate to post-AGB PG 1159 stars for a wide range of stellar masses. Methods. We take into account the complete evolutionary stages of PG 1159 progenitors starting from the Zero Age Main Sequence. We consider the two kinds of Born Again Scenarios, the very late thermal pulse (VLTP) and the late thermal pulse (LTP), that give rise to hydrogen-deficient compositions. The location of our PG 1159 tracks in the effective temperature-gravity diagram and their comparison with previous calculations as well as the resulting surface compositions are discussed. Results. Our results reinforce the idea that the different abundances of 14 N observed at the surface of those PG 1159 stars with undetected hydrogen is an indication that the progenitors of these stars would have evolved through a VLTP episode, where most of the hydrogen content of the remnant is burnt, or LTP, where hydrogen is not burnt but instead diluted to very low surface abundances. We derive new values for spectroscopical masses based on these models. We discuss the correlation between the presence of planetary nebulae and the 14 N abundance as another indicator that 14 N-rich objects should come from a VLTP episode while 14 N-deficient ones should be the result of a LTP. Finally, we discuss an evolutionary scenario that could explain the existence of PG 1159 stars with unusually high helium abundances and a possible evolutionary connection between these stars and the low mass O(He) stars.
Choosing optimum noise figure and data rate in wireless sensor network radio transceivers

To reduce the energy consumption in wireless sensor network transceivers, we propose an approach which combines two tradeoffs. The first tradeoff is between the receiver sensitivity and transmitter output power. The second one is the duty cycle and data rate of the transceiver. The combined approach gives us the optimum choice of noise figure and data rate for a given application and transceiver architecture. Considering a typical transceiver architecture and perfectly synchronized system, we show that the energy consumption can indeed be reduced with this approach compared to choosing either data rate or noise figure arbitrarily. Moreover, in case of a wakeup receiver architecture and slot based MAC protocol, applying this method, we show that there is a different combination of optimum data rate and noise figure value for the wakeup receivers to minimize the wakeup energy.
Stable isotope analyses of web-spinning spider assemblages along a headwater stream in Puerto Rico

Web-spinning spiders that inhabit stream channels are considered specialists of aquatic ecosystems and are major consumers of emerging aquatic insects, while other spider taxa are more commonly found in riparian forests and as a result may consume more terrestrial insects. To determine if there was a difference in spider taxa abundance between riverine web-spinning spider assemblages within the stream channel and the assemblages 10 m into the riparian forest, we compared abundances for all web-spinning spiders along a headwater stream in El Yunque National Forest in northeast Puerto Rico. By using a nonmetric dimensional scaling (NMDS) abundance analysis we were able to see a clear separation of the two spider assemblages. The second objective of the study was to determine if aquatic insects contributed more to the diet of the spider assemblages closest to the stream channel and therefore stable isotope analyses of δ15N and δ13C for web-spinning spiders along with their possible prey were utilized. The results of the Bayesian mixing model (SIAR) however showed little difference in the diets of riverine (0 m), riparian (10 m) and upland (25 m) spiders. We found that aquatic insects made up ∼50% of the diet for web-spinning spiders collected at 0 m, 10 m, and 25 m from the stream. This study highlights the importance of aquatic insects as a food source for web-spinning spiders despite the taxonomic differences in assemblages at different distances from the stream.
DE TRAVAIL-WORKING PAPERS W . P . 09-31 Cooperation and Competition in Intergenerational Experiments in the Field and the Laboratory

There is economic pressure towards the postponement of the retirement age, but employers are still reluctant to employ older workers. We investigate the comparative behavior of juniors and seniors in experiments conducted both onsite with the employees of two large firms and in a conventional laboratory environment with students and retirees. We show that seniors are no more risk averse than juniors and are typically more cooperative; both juniors and working seniors respond strongly to competition. The implication is that it may be beneficial to define additional incentives near the end of the career to motivate and retain older workers.
Web Page Classification Using Relational Learning Algorithm and Unlabeled Data

Applying relational tri-training (R-tri-training for short) to web page classification is investigated in this paper. R-tri-training, as a new relational semi-supervised learning algorithm, is well suitable for learning in web page classification. The semi-supervised component of R-tri-training allows it to exploit unlabeled web pages to enhance the learning performance effectively. In addition, the relational component of R-tri-training is able to describe how the neighboring web pages are related to each other by hyperlinks. Experiments on Web-Kb dataset show that: 1) a large amount of unlabeled web pages (the unlabeled data) can be used by R-tri-training to enhance the performance of the learned hypothesis; 2) the performance of R-tri-training is better than the other algorithms compared with it.
Automatic melody generation considering chord progression by genetic algorithm

In this research, an automatic melody generation system considering chord progression by genetic algorithm is proposed. In the proposed automatic melody generation system, initial population are generated based on features on rhythm, pitch and chord progression of trained melody. In this system, the trained sample melody is divided into some melody blocks. Here, melody blocks mean verse, bridge, chorus and so on. And some new melodies are generated considering melody features in each block. The features on rhythm and pitch in each melody block of the sample melody are trained in some N-gram models, and they are used in order to calculate fitness in the melody generation by genetic algorithm. Some melodies are generated using the proposed system and confirmed that the proposed system can generate melodies considering features in each melody block of the trained sample melody.
Using startle reflex to compare playing and watching in a horror game

Human startle reflex has been identified as a valid physiological measure of valence and arousal, providing a useful mechanism for evaluating player engagement in video games. In this research, we use electromyography (EMG) recording of the startle reflex of participants to explore the impact of playing, versus watching a play through, of a game. Participants in the research played and watched Parsec Studio's Slender: The Eight Pages, a freely available video game within the horror genre. Experiments were conducted both with participants both playing and watching the game, with results showing a statistically significant difference in startle responses between the two conditions. The results suggest that the fear state of the game is enhanced through player interaction and increased attention.
Medium resolution 2.3 μm spectroscopy of the massive galactic open cluster Westerlund 1

The Galactic open cluster Westerlund 1 was found only a few years ago to be much more massive than previously thought, with evidence suggesting its mass to be in excess of ∼10 5 M� , in the range spanned by young extragalactic star clusters. Unlike those clusters, its proximity makes spatially resolved studies of its stellar population feasible. It is therefore an ideal template for a young, massive star cluster, permitting direct comparison of its properties with measurements of velocity dispersion and dynamical mass for spatially unresolved extragalactic clusters. To this end, we used the long slit near-infrared spectrograph VLT/ISAAC to observe the CO bandhead region near 2.29 µm, scanning the slit across the cluster centre during the integration. Spatially collapsing the spectra along the slit results in a single co-added spectrum of the cluster, comparable to what one would obtain in the extragalactic cluster context. This spectrum was analysed in the same way as the spectra of almost point-like extragalactic clusters, using red superiant cluster members as velocity templates. We detected four red supergiants that are included in the integrated spectrum, and our measured velocity dispersion is 5.8 km s −1 . Together with the cluster size of 0.86 pc, derived from archival near-infrared SOFI-NTT images, this yields a dynamical mass of 6.3 × 10 4 M� .
Multi-Font Rotated Character Recognition Using Periodicity

This paper presents on accuracy improvement of multi-font rotated character recognition. Until now, a recognition method for rotated characters was based on distance criterion on the eigen sub-space. That is, an unknown pattern is projected onto the eigen-subspace of each category. The category which shows the closest distance between the projected point and the category locus is chosen. However, this simple method could not be cope with multi-font characters. Therefore, some unknown patterns were created by rotating the input pattern and projected onto the eigen-subspace of each category. By that method, a good performance was achieved for small size of categories like alphabetic 26 capital letters. However, the performance fell down by increasing the number of categories like 62 alpha-numeric letters. By considering the cause of the misclassification, we found that the distance criterion accidentally caused misclassification. This paper proposes a new feature based on periodic property of projected points on the eigen space. The experimental results showed a considerably high recognition rate.
A Model of Falls Risk in Older Adults

Falls are a significant problem in older adults, with 1/3 of people over the age of 65 falling in a given year. Age-related changes in the systems involved with balance lead to increased reaction time to postural perturbations, decreased postural control, and changes in gait, all resulting in an increased risk of falling. Other factors that can lead to imbalance outside of the primary balance systems increase the risk of falls. Previous research focused on producing a clinically-relevant tool for fall risk assessment; a theoretical falls risk model has yet to be produced. Risk factors were identified from literature review and recommendations from multiple clinical practice guidelines in the area of falls risk. Using data from the National Health and Nutrition Examination Survey, a Poisson regression was performed to determine which risk factors are significant predictors of reported problems with falls in older, community-dwelling adults. An additional Poisson analysis was performed, including interaction terms to see if any risk factors combined to increase the falls risk. Analysis showed that including interaction terms was a significantly better fit in the Poisson model than with the terms omitted. The most predictive risk factor for a reported problem with falls is asking the patient if they have problems with their balance. Many other risk factors will cause a feeling of imbalance, so the primary risk factor for falls is likely having a feeling of imbalance. Additional research is needed on intervention for falls risk and identifying threshold values for when risk factors will likely lead to imbalance.
Dyadic Relations Between Interparental Conflict and Parental Emotion Socialization

This study examined the effects of destructive and constructive interparental conflict on unsupportive parental emotion socialization behaviors (N = 166 parents of toddlers). Both mothers and fathers completed measures of destructive and constructive interparental conflict and emotion dismissing beliefs and unsupportive responses to toddlers’ expressions of negative emotions such as anger, fear, and sadness. Multilevel modeling for the actor–partner interdependence model indicated spillover effect of destructive conflict and crossover effects of constructive conflict on unsupportive parental emotion socialization. In short, mothers’ and fathers’ perceptions of destructive interparental conflict were positively related to their own use of unsupportive emotional socialization behaviors. Mothers’ and fathers’ perceptions of constructive interparental conflict were (marginally/trend level) negatively related to the other parent’s use of unsupportive emotion socialization behaviors. These findings advance the literature on the associations between interparental conflict and parental emotion socialization, examining interdependence between mothers and fathers.
Media ownership and market structures: banes of news media sustainability in Nigeria?

With the mixture of government-owned media outlets and private media establishments, Nigerian news media industry is deemed as one of the leading media industries in Africa. But, in spite of its leading status on the continent, the industry is plagued with a series of multi-faceted challenges of sustainability that is rooted in the socio-economic and political contexts. Consequently, privately owned media outlets have short-life span in Nigeria. This article assesses the challenges of news media sustainability in Nigeria. The article underscores the adverse effects of structural deficit in the democratic norms and institutional capabilities on the news media sustainability in Nigeria.
Discriminant boosted dynamic time warping and its application to gesture recognition

Dynamic time warping (DTW) measures similarity between two data sequences by minimizing an accumulated distance between two sequence samples at each iteration and a cost is computed to assess the level of the similarity. The DTW cost may then be used to assign a sequence to a class if the problem is a classification problem. In machine learning, classification problems are solved using features with good discrimination power, which are generated by exploiting the distribution of data vectors. Linear Discriminant Analysis (LDA) is such a technique and finds discriminative projection directions which are used to generate features as projections of sequence vectors on to these directions. Unfortunately, these techniques are not applicable to warped sequences because the mapping between the test sequences and the training sequences is not known. To solve this problem, we propose a constrained LDA framework that produces direction vectors that repeat unit vectors that have dimensions equal to the dimensions of a single sequence sample. Such projection vectors can be used without knowing the mapping of test sequence vectors to training sequence vectors. Experiment results show that generating features by discriminant analysis improves the performance significantly.