Miracle-dz/UniFAR-FTUs huggingface dataset:
ARIVU: Power-aware middleware for multiplayer mobile games

With the improved processing power, graphic quality and high-speed wireless connection in recent generations of mobile phone, it looks more attractive than ever to introduce networked games on these devices. While device features and application resource requirements are rapidly growing, the battery technologies are not growing at the same pace. Networked Mobile games are a class of application, which consume higher levels of energy, as they are naturally more computationally intensive and use hardware components including audio, display and network to their fullest capacities. Therefore, the main concern is the limitation of the battery power of such portable devices to support the potentially long-hour of game play. In this paper we present ARIVU, a power aware middleware that dynamically controls the energy consumption of wireless interface based on the game and system state while maintaining the user experience. ARIVU provides the relevant API for game developers to easily integrate the middleware. We measure power consumption of game play over different wireless interfaces including 3.5G (HSPA), 802.11g and ZigBee. The middleware is able to save up to 40% of the total energy consumed by the wireless interfaces (802.11g and ZigBee). In addition, we show the efficiency of ZigBee interface as potential low power interface for networked game applications.
A review of paradigm shift from conventional to personalized e-learning

E-learning is a continuously evolving and rapidly progressing interdisciplinary field, which explores use of ICT in education to impart knowledge effectively by improving learner's experience. Most of the researchers are exploring the concept of Adaptive Educational Hypermedia Systems (AEHS) to attain personalization especially in distance mode of e-learning. Researchers have experimented with different aspects of personalization that demonstrate a paradigm shift from synchronous approach to an adaptive approach of e-learning. In this paper we propose taxonomy of e-learning. Models of teaching-learning process and learning approaches are also discussed in this paper. We reviewed several methodologies used in adaptive/personalized e-learning and in conclusion presented our view of personalized e-learning.
California community colleges : a study of administrators' support of classified staff during organizational change

Organizational change has become a frequent occurrence within institutions of higher education. Certainly, change initiatives are not new to community colleges. In light of the recent financial crisis, colleges and universities are facing hard budget decisions which impact student enrollment, faculty assignments, and facility improvements and maintenance. Concomitantly, changing student population, influx of private and corporate colleges, and rapidly increasing technology are also creating conditions for organizational changes within community colleges. The vast number of internal and external forces pushing higher education institutions into large organizational changes has created a difficult and stressful working environment for many employees. This study investigated the role of community college administration in creating a culture of support, communication, and trust among classified staff during times of organizational change. Survey data explored classified staff members and administrators' perceptions of support, communication, and trust, while interview data provided insight into classified staff members and administrators' perceptions of organizational change. The results of this qualitative study suggested that although there are areas for improvement, both College S and College N are providing support and communication, and maintaining trust with employees. Classified staff members perceived that leadership supported them, provided them with satisfactory communication, and were trustworthy. Administrators perceived that they supported their staff, provided communication, and were trusted by their employees, though there were some discrepancies between their espoused behaviors and their actions as perceived by staff. Both classified staff members and administrators felt that there was support, communication, and trust during organizational change, whether financially driven or not. Surprisingly, at least two other factors emerged from employees as influential to organizational change. Some employees expressed that administrators can strengthen trust and create an environment of successful and sustainable change by expanding their support efforts and increasing their communication through constant evaluation
The Illusion of Explanatory Depth in a Misunderstood Field: The IOED in Mental Disorders

Humans fail to understand the world around them and also fail to recognize this lack of understanding. The illusion of explanatory depth (IOED) exemplifies these failures: people believe they understand the world more deeply than they actually do and only realize that this belief is an illusion when they attempt to explain elements of the world. An unexplored factor of the IOED is how people may become overconfident by confusing their own understanding with others’ understanding. In two experiments, we examine the IOED in mental disorders, a domain where society has a limited understanding. In Experiment 1, we demonstrate that people display an IOED for mental disorders as well as devices, but that it is smaller for mental disorders. In Experiment 2, we show that exposing the IOED is specifically linked to generating an explanation, rather than more generally thinking about a phenomenon.
Design and Synthesis Methodology for UHF-RFID Tags Based on the T-Match Network

A new systematic methodology for the design of T-match based UHF-RFID tags is proposed. The great majority of commercial UHF-RFID tags are based on dipole antennas using a modification of a T-match network. The literature contains examples of models that describe the T-match, but they are not sufficiently accurate to synthesize the tag geometry. Using the proposed methodology, a global band UHF-RFID tag based on a folded dipole antenna and matched to the RFID integrated circuit by means of a T-match network is designed and fabricated. Very good agreement between the measured and simulated read range is achieved within the entire UHF-RFID band, which reveals that the proposed method is amenable for accurate analysis and synthesis of T-match based UHF-RFID tags.
Teaching Global Software Engineering and International Project Management - Experiences and Lessons Learned from Four Academic Projects

As part of the ongoing globalization process, software is no longer developed by a sole enterprise which is based at one single location only. In turn, distributed engineering teams are continuously modifying software by bringing in their local knowledge and country-specific expertise. Due to this cooperation on a globalscale, today’s software engineers require distinct skills and capabilities allowing them to face a paradigm called Global Software Engineering (GSE). However, regarding today’s universities curricula, the teaching of GSE can be seen as an emerging discipline which is increasingly gaining attention. This paper depicts the progression and lessons learned from four different globally distributed software engineering projects executed by late bachelor and master students from five different universities. In doing so, the article facilitates future GSE endeavors in academia and industry.
Dissecting the Transcriptional Regulatory Properties of Human Chromosome 16 Highly Conserved Non-Coding Regions

Non-coding DNA conservation across species has been often used as a predictor for transcriptional enhancer activity. However, only a few systematic analyses of the function of these highly conserved non-coding regions (HCNRs) have been performed. Here we use zebrafish transgenic assays to perform a systematic study of 113 HCNRs from human chromosome 16. By comparing transient and stable transgenesis, we show that the first method is highly inefficient, leading to 40% of false positives and 20% of false negatives. When analyzed in stable transgenic lines, a great majority of HCNRs were active in the central nervous system, although some of them drove expression in other organs such as the eye and the excretory system. Finally, by testing a fraction of the HCNRs lacking enhancer activity for in vivo insulator activity, we find that 20% of them may contain enhancer-blocking function. Altogether our data indicate that HCNRs may contain different types of cis-regulatory activity, including enhancer, insulators as well as other not yet discovered functions.
Automatic Sleep Stage Scoring with Wavelet Packets Based on Single EEG Recording

— Sleep stage scoring is the process of classifying the stage of the sleep in which the subject is in. Sleep is classified into two states based on the constellation of physiological parameters. The two states are the non-rapid eye movement (NREM) and the rapid eye movement (REM). The NREM sleep is also classified into four stages (1-4). These states and the state wakefulness are distinguished from each other based on the brain activity. In this work, a classification method for automated sleep stage scoring based on a single EEG recording using wavelet packet decomposition was implemented. Thirty two ploysomnographic recording from the MIT-BIH database were used for training and validation of the proposed method. A single EEG recording was extracted and smoothed using Savitzky-Golay filter. Wavelet packets decomposition up to the fourth level based on 20 th order Daubechies filter was used to extract features from the EEG signal. A features vector of 54 features was formed. It was reduced to a size of 25 using the gain ratio method and fed into a classifier of regression trees. The regression trees were trained using 67% of the records available. The records for training were selected based on cross validation of the records. The remaining of the records was used for testing the classifier. The overall correct rate of the proposed method was found to be around 75%, which is acceptable compared to the techniques in the literature.
Title: Applied Federation Technology: The Charging of Roaming Students

SAML federations provide students the possibility to use their home university’s account even in case they decide to study one or more semesters abroad. The visited university can rely on the identity information transmitted via the federation’s mechanisms. However, when services at the visited university require payment, such as using a printer, the roaming student is nevertheless required to have a local account, since the federation does not support payment. Therefore, the purpose of this research paper is to provide information about changes and enhancements to the federation’s architecture as well as to the used protocol, i.e., SAML, to enable payment within SAML federations. Thus, the SAML definitions have been taken as fundamentals for payment related enhancements. Furthermore, the enhanced federation was validated and prototypically implemented to prove correctness and real-life usage. This led to the result that it is feasible to provide payments within a SAML federation as long as the modifications proposed within this paper are carried out.
Generalized Measures of Information Transfer

Transfer entropy provides a general tool for analyzing the magnitudes and directions---but not the \emph{kinds}---of information transfer in a system. We extend transfer entropy in two complementary ways. First, we distinguish state-dependent from state-independent transfer, based on whether a source's influence depends on the state of the target. Second, for multiple sources, we distinguish between unique, redundant, and synergistic transfer. The new measures are demonstrated on several systems that extend examples from previous literature.
Evolutionary computation extracts a super sEMG feature to classify localized muscle fatigue during dynamic contractions

This study developed a new muscle fatigue feature based on sEMG signals. The evolved feature is combining 11 traditional muscle fatigue sEMG parameters to optimally classify the sEMG signals. The myoelectric signals were recorded from 13 subjects performing biceps brachii contractions until fatigue. By utilizing the 11 features and a combination of randomly selected mathematical operators a Genetic Algorithm (GA)evolved a novel composite feature. Davies Bouldin Index (DBI) was used by the GA during the seeding and evolution process in its fitness function to measure the separation of the combined feature. Classification results show an average of 75.4% correct classification and a significant improvement (P <; 0.01) of 11.94% when compared with the averages of eight standard sEMG features that are used in current muscle fatigue studies.
Multivariate Analysis of Customer Satisfaction: A Case Study of Bangkok’s Mass Rapid Transit (MRT) Passengers

One of the service quality indicators for urban rail transit system is the service evaluation from a passenger’s viewpoint. The key objective of service quality analysis is to improve services such that user expectations and needs can be met. This study aims to analyze customer satisfaction of Bangkok’s mass rapid transit (MRT) system. Data was collected from 661 respondents by means of questionnaire survey. Based on 31 service quality attributes, relationships between the overall customer satisfaction and service quality attributes are analyzed using factor analysis and structural equation modeling. Results indicate that travel convenience is the most significant factor affecting the overall satisfaction. Other factors include transit fare, service and information, cleanliness and safety, transit facilities, and access/egress to stations. Furthermore, market segmentation analysis reveals distinct findings across four categories of MRT users. It is expected that results can be used to enhance the overall performance of urban rail system.
Investigation of radar localization system accuracy for human gastro intestine (GI) tract

Recent developments in capsule endoscopy have highlighted the need for accurate techniques to estimate the location of a capsule endoscope. A high accuracy localization of the order of millimeters is required for endoscopic applications. Location estimation of a capsule endoscope in the gastrointestinal (GI) tract is a challenging problem, as radio frequency signals encounter a high loss and highly dynamic channel propagation environment. In this paper, the characteristics of radio frequency signal absorption inside the human body are investigated with the aim of developing an accurate propagation model. Furthermore, the possibility of using a radar system for capsule localization is investigated and compared to its operation in the 2.4G Hz ISM band.
Sound field reproduction using multiple linear arrays based on wave field reconstruction filtering in helicalwave spectrum domain

For with-height reproduction of a sound field, an efficient technique is to record and reproduce the sound field at lower resolution at an elevation angle than that at a horizontal angle based on auditory perception. To achieve this, developing a method using multiple horizontal linear arrays of microphones and loudspeakers is necessary. We propose a sound field reproduction method for a cylindrical array configuration which is based on a wave field reconstruction (WFR) filter analytically derived in the helical wave spectrum domain. The filter is stabilized by introducing a model in which microphones are mounted on a rigid cylindrical baffle. Numerical simulation results indicated that the reproduction accuracy of the proposed method was well preserved in the near-field region along the central axis of the cylinder even when the number of elements at angular position is small.
Guided Emotional State Regulation: Understanding and Shaping Players' Affective Experiences in Digital Games

Designing adaptive games for individual emotional experiences is a tricky task, especially when detecting a player’s emotional state in real time requires physiological sensing hardware and signal processing software. There is currently a lack of software that can identify and learn how emotional states in games are triggered. To address this problem, we developed a system capable of understanding the fundamental relations between emotional responses and their eliciting events. We propose time-evolving Affective Reaction Models (ARM), which learn new affective reactions and manage conflicting ones. These models are then meant to provide information on how a set of predetermined game parameters (e.g., enemy and item spawning, music and lighting effects) should be adapted, to modulate the player’s emotional state. In this paper, we propose and describe a framework for modulating player emotions and the main components involved in regulating players’ affective experience. We expect our technique will allow game designers to focus on defining high-level rules for generating gameplay experiences instead of having to create and test different content for each player type.
Model Selection for Nonparametric Regression Model Selection for Regression

Risk bounds are derived for regression estimation based on model selection over a unrestricted number of models. While a large list of models provides more exibility, sig-niicant selection bias may occur with bias-correction based model selection criteria like AIC. We incorporate a model complexity penalty term in AIC to handle the selection bias. Resulting estimators are shown to achieve a trade-oo among approximation error, estimation error and model complexity automatically without prior knowledge about the true regression function. As applications, we demonstrate adaptation property of these estimators over full and sparse approximation function classes with diierent smoothness. For high-dimensional function estimation by tensor product splines, we show with number of knots and spline order adaptively selected, least squares estimator converges at anticipated rates simultaneously for Sobolev classes with diierent interaction orders and smoothness parameters.
I2R-NUS-MSRA at TAC 2011: Entity Linking

In this paper, we report the joint participation of I2R-NUS team and MSRA team in entity linking task for Knowledge Base Population at Text Analysis Conference 2011. I2R-NUS team submitted two results with the full system and the partial system for diagnosis purpose. Both results incorporate the new technologies: acronym expansion, instance selection and topic modeling proposed in our recent papers. In clustering step, three clustering algorithms: spectral graph partitioning (SGP), hierarchical agglomerative clustering (HAC) and latent Dirichlet allocation (LDA) are combined for the full system. The full system achieves a competitive F-score 0.831 1 . The partial system uses only Wikipedia Source to generate candidates for KB linking and only LDA for clustering , which leads to 0.813 Fscore. Although due to the time constrain, the combined result of I2R-NUS full system with MSRA KB linking result was not submitted, it shows 0.828 F-score afterwards.
If sharing is everything, then it is nothing: a multidisciplinary survey on basic terms, views and current research topics

[Introduction . ] The paper is organized as follows: Chapter 2 depicts the state-of-the-art of sharing research and outlines the practical and scientific relevance of sharing. Furthermore, the contribution of the paper is defined. Chapter 3 describes the participants and the survey design. Chapter 4 presents commonalities and controversies in the participants’ feedbacks, including sharing examples, definitions and key statements. Chapter 5 focuses on the definition problem and provides a typology that enables researchers to specify their own sharing paradigm. Chapter 6 summarizes the results and their practical benefits.
A hybrid approach for identifying sentiments around aspects

In this paper, we have discussed the development of a complete solution for identification of Voice of Customer (VOC) at the mobile domain. We have defined 27 possible aspects and 3 possible sentiments in this domain. The task is to identify the aspects a specific reviewer is talking about and the sentiments he conveys. The words (terms) and the types (tags) of aspects are identified using a statistical sequence leveling technique (based on CRF) trained on 950 manually annotated sentences and the sentiments of a sentence are identified using a statistical bag-of-word technique (based on SVM) trained on 5450 manually annotated sentences. The association of sentiments with aspects is carried out using rules. The system identifies sentiment around aspect with 70.08% accuracy. This would help the customers to get the insight of the product he or she is looking for and the company to get the real VOC.
Enhanced anti-jamming capability for cyclostationary algorithms in weak signal environments

Aiming at the cyclostationary property of most communication signals, two cyclostationary algorithms are analyzed in detail, which are obtained by using the Lagrange multiplier method based on different combinations of optimization objectives and constraints, and a novel adaptive implementation method called forgetting factor method is proposed to improve the anti-jamming capability in weak signal environments. These algorithms have a computational complexity of O(n2) complex multiplications and can avoid the computationally expensive eigenvalue decomposition or singular value decomposition problem. The results based on computer simulation show that the output SINR and beampatterns using the proposed method are better.
Variation of a benthic heterotrophic bacteria community with different respiratory metabolisms in Coyuca de Benítez coastal lagoon (Guerrero, Mexico).

The fluctuations of the number, biomass and composition of the heterotrophic community were studied daily for two days, according to depth, pH, Eh, O2 and organic carbon concentration within a zone of the canal between the Coyuca de Benitez lagoon (Guerrero, Mexico) and the coastal waters. At the three moments of the day studied (6 am, 2 pm and 10 pm), the oxygen concentrations in the overlying water and in the superficial sediment layer were near air-saturation in the diurnal samplings (582 microM at 6 am and 665 microM at 2 pm), and sub-satured during the night (158 microM). In the sediments, the models of vertical distribution of Eh and organic carbon distributions were very irregular due to the bio-perturbation of the benthic, meio- and macrofauna, whose activity allows the superficial organic carbon to migrate towards sediment deeper layers. Vertical distribution of the different viable bacteria populations seems to be related to the hydrodynamic patterns of the communicating canal and sediments heterogeneity. In the sediment column, the heterotrophic bacteria total number varied from 6.8 to 20.3 x 108 cells cm(-3). The highest heterotrophic bacterial biomass values were encountered during the diurnal samplings (39.2 microgC.l(-1) at 6 am and 34.4 microgC. (l(-1) at 2 pm) and the lowest during the night (9.7 microgC.l(-1). The fluctuations of viable heterotrophic bacteria populations with different respiratory metabolisms (aerobic, microaerophilic and anaerobic) can be explained by the existence of suboxic microniches that appear when particles of sediment are resuspended due to the water circulation and the benthic infauna excavating activity, that allows the supernatant water oxygen to penetrate through its galleries towards deeper sediment zones. The statistical analysis (Multiple lineal regression model r2 > or = 0.5) showed that the on the whole, the hydrological parameters are not influence over the bacterial number and bacterial biomass distribution (r2 < or = 0.5), Nevertheless, the variations of the heterotrophic bacteria community observed in the two days sampling, seem to be governed (with F-values of 0.6 to 0.9) by the irregular flows of bio-available organic material and the sediment porosity.