Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved boundary and silhouette enhancement in volume illustration

Structure cues are the dominant information in a rendered image. And conveying structure accurately and automatically is a problem still not fully solved in volume rendering. The presence of volume illustration allows a more flexible way in conveying structure information compared with the traditional transfer function. This paper presents two improved approaches in volume illustration, namely the distance weight boundary enhancement and gradient weight silhouette enhancement. In these approaches, the enhancing parameters vary with the samples' position and local gradient. As a result, they are more flexible in rendering various data sets and are able to convey clear structure cues without missing of small features.
Being Sad Is Not Always Bad: The Influence of Affect on Expository Text Comprehension

ABSTRACT We investigated how affective states influence expository text comprehension and whether text valence moderates the effects (i.e., mood congruency). In Experiment 1 participants were randomly assigned to a happy or sad affective state (elicited via films) before reading a positive or negative version of a scientific text on animal adaptations. Participants (n = 79) in the sad (film) group had higher scores on deep-reasoning (d = .312) but not surface-level questions on a subsequent multiple-choice comprehension assessment; there was also no evidence for mood congruence. Using a neutral version of the same text, in Experiment 2 participants (n = 52) in a fearful condition performed better on surface-level comprehension questions (d = .594) compared with a sad condition, but the groups were on par for deep-reasoning questions. Experiment 3 (n = 595) did not replicate the findings from Experiment 2 (no comprehension differences between the sad and fear groups) and there were no differences between the fear and happy groups. However, the sad group outperformed the happy group on deep-reasoning questions (d = .210), thereby replicating Experiment 1. The overall findings were confirmed after pooling the data from the three experiments to increase power.
An effective category classification method based on a language model for question category recommendation on a cQA service

Classiying user's question into several topics helps respondents answering the question in a cQA service. The word weighting method must estimate the appropriate weight of a word to improve the category (or topic) classification. In this paper, we propose a novel effective word weighting method based on a language model for automatic category classification in the cQA service. We first calculate the occurrence probability of a word in each category by using a language model and then the final weight of each word is estimated by ratio of the occurrence probability of the word on a category to the occurrence probability of the word on the other categories. As a result, the proposed method significantly improves the performance of the category classification.
Sensorless Rotor Position Detection Capability of a Dual Three-Phase Fractional-Slot IPM Machine

The interest for fractional-slot permanent-magnet (PM) synchronous machines has been more and more increasing in recent years. Particularly attractive is the interior PM (IPM) machine, since it is characterized by two torque components: the PM torque and the reluctance torque. Owing to this feature, the IPM machine is able to operate under flux-weakening conditions, as required by many applications, such as automotive, machine tools, washing machines, and so on. Another feature is that the rotor position can be detected without sensor even at zero speed, by means of techniques based on high-frequency signal injection. The aim of this paper is to investigate the torque components and the sensorless position detection capability of an IPM dual three-phase machine equipped with two fractional-slot windings. These two windings are designed to be supplied by two separate converters, yielding an increase of the fault-tolerant capability of the machine. The analysis and the tests deal with the capability of the machine when it operates under healthy as well as faulty conditions, i.e., when the supply of one three-phase winding set is switched off and only one winding continues to be supplied.
Family and school social capital, school burnout and academic achievement: a multilevel longitudinal analysis among Finnish pupils

Abstract Research on the associations between family and school social capital, school burnout and academic achievement in adolescence is scarce and the results are inconclusive. We examined if family and school social capital at the age of 13 predicts lower school burnout and better academic achievement when graduating at the age of 16. Using data from 4467 Finnish adolescents from 117 schools and 444 classes a three-level multilevel analysis was executed. School social capital, the positive and supportive relationships between students and teachers, predicted lower school burnout and better academic achievement among students. Classmates’ family social capital had also significance for students’ academic achievement. Our results suggest that building school social capital is an important aspect of school health and education policies and practices.
Optimal-Scaling-Factor Assignment for Patch-wise Image Retargeting

Image retargeting adjusts images to arbitrary sizes such that they can be viewed on different displays. Content-aware image retargeting has been receiving increased attention. In particular, researchers have improved a patch-wise scaling method for image retargeting at the object level. The scaling partitions the image into rectangular patches of adaptive sizes, which are comparable to the sizes of the salient objects in the image. This partitioning is based on a visual-saliency map; accordingly, the method labels the patches as important or unimportant. Then, the method scales the important patches as uniformly as possible and stretches or squeezes the unimportant patches to fit the target size. A patch-based image-similarity measure finds the optimal set of scaling factors. In experiments, the improved method performed well for three image types: lines and edges, foreground objects, and geometric structures.
Quality management on Amazon Mechanical Turk

Crowdsourcing services, such as Amazon Mechanical Turk, allow for easy distribution of small tasks to a large number of workers. Unfortunately, since manually verifying the quality of the submitted results is hard, malicious workers often take advantage of the verification difficulty and submit answers of low quality. Currently, most requesters rely on redundancy to identify the correct answers. However, redundancy is not a panacea. Massive redundancy is expensive, increasing significantly the cost of crowdsourced solutions. Therefore, we need techniques that will accurately estimate the quality of the workers, allowing for the rejection and blocking of the low-performing workers and spammers. However, existing techniques cannot separate the true (unrecoverable) error rate from the (recoverable) biases that some workers exhibit. This lack of separation leads to incorrect assessments of a worker's quality. We present algorithms that improve the existing state-of-the-art techniques, enabling the separation of bias and error. Our algorithm generates a scalar score representing the inherent quality of each worker. We illustrate how to incorporate cost-sensitive classification errors in the overall framework and how to seamlessly integrate unsupervised and supervised techniques for inferring the quality of the workers. We present experimental results demonstrating the performance of the proposed algorithm under a variety of settings.
Feature Extraction from Double Task Timed Up and Go Signals Applied to the Identification of Elderly Fallers

Devices and sensors for identification of fallers can be used to implement actions to prevent these falls and to allow the elderly to live an independent life while reducing the long-term care costs. In previous studies the feature extraction is often dependent on step detection, the collected datasets are often unavailable, and a large number of features are attempted in order to sufficiently represent the faller and non-faller classes. In this study we present results of feature extraction on accelerometer data with the aim of identifying fallers among a group of health elderly. The features are extracted from three different Timed Up and Go (TUG) tests combined with simultaneous manual and cognitive tasks. As a result, a set of features is described to discriminate fallers from non-fallers based on the segmentation of the TUG trials, in particular using TUG with cognitive task, while conventional functional tests fail to do so. In addition, we show that the features can be generalised for unseen subjects, demonstrating the relevance of the study. We concluded that features extracted from segmented TUG trials acquired with simultaneous tasks has potential to improve performance when identifying fallers via accelerometer sensors.
Effects of Communicative Pressures on Novice L2 Learners’ Use of Optional Formal Devices

We conducted an Artiﬁcial Language Learning experiment to examine the production behavior of language learners in a dynamic communicative setting. Participants were exposed to a miniature language with two optional formal devices and were then asked to use the acquired language to transfer information in a cooperative game. The results showed that language learners optimize their use of the optional formal devices to transfer information efﬁciently and that they avoid the production of ambiguous information. These re-sults could be used within the context of a language model such that the model can more accurately reﬂect the production behavior of human language learners.
Typing migration control in lsdπ

This paper presents a type system to control the migration of code between sites in a concurrent distributed framework. The type system constitutes a decidable mechanism to ensure specific security policies, which control remote communication, process migration, and channel creation. The approach is as follows: each network administrator specifies its sites privileges, and the type system checks that both processes and the composition of sites respect these policies. At runtime, well-typed networks do not violate the security policies declared for each site.
A novel algorithm for ontology matching

Ontology matching is an essential aspect of the Semantic Web with a goal of finding alignments among the entities of given ontologies. Ontology matching is a necessary step for establishing interoperation and knowledge sharing among Semantic Web applications. In this study we present an algorithm and a tool developed based on this algorithm to find correspondences among entities of input ontologies. The proposed algorithm uses a new lexical similarity measure and also utilizes structural information of ontologies to determine their corresponding entities. The lexical similarity measure generates a bag of words for each entity based on its label and description information. The structural approach creates a grid for each node in the ontologies. The combination of lexical and structural approaches creates the similarity matrix between the source and target ontologies. The proposed algorithm was tested on a well known benchmark and also compared to other algorithms presented in the literature. Our experimental results show the proposed algorithm is effective and outperforms other algorithms.
Enriching E-Learning meta data with user generated playlists

Playlists are a concept commonly known from music players. Building on the concept of mix tapes they enable the user to select and group their favorite music and thereby creating new compilations of music. Web video portals have adopted this idea to let users create custom combinations of videos. This paper will focus on the task of adding playlist functionality in an E-Learning context. We describe how we implement the playlist solution as well as the use cases in which user of our portal can take advantage of playlists.
Mining generalized fuzzy association rules from Web logs

Discovery the association between web pages is an important task as the rapid growth of web data. This article uses the fuzzy method to discover generalized fuzzy association rules among theWeb pages fromWeb logs. In the paper, whether a web page is visited or not and time duration on it are considered two important factors to reflect users' interest and preference. Numerical time duration is fuzzified into a corresponding fuzzy variable with membership values. The mined rule has the form as page(fuzzy duration) → page(fuzzy duration). These rules can reflect association among Web pages with fuzzy duration. By the analysis of the example, the generalized fuzzy association rules can be effectively mined in a sustainable computational period from Web user access patterns in Web logs.
Unveiling Obscured Accretion in the Chandra Deep Field-South

We make use of deep HST, VLT, Spitzer, and Chandra data on the Chandra Deep Field-South to constrain the number of Compton-thick AGNs in this field. We show that sources with high 24 μm-to-optical flux ratios and red colors form a distinct source population, and that their infrared luminosity is dominated by AGN emission. Analysis of the X-ray properties of these extreme sources shows that most of them (80% ± 15%) are indeed likely to be highly obscured, Compton-thick AGNs. The number of infrared-selected, Compton-thick AGNs with 5.8 μm luminosity higher than 1044.2 ergs s−1 turns out to be similar to that of X-ray-selected, unobscured, and moderately obscured AGNs with 2-10 keV luminosity higher than 1043 ergs s−1 in the redshift bin 1.2-2.6. This “factor of 2” source population is exactly what is needed to solve the discrepancies between model predictions and X-ray AGN selection.
Mining Websites Preferences on Web Events in Big Data Environment

On the web, there are numerous websites publishing web pages to cover the events occurring in society. The web events data satisfies the well-accepted attributes of big data: Volume, Velocity, Variety and Value. As a great value of web events data, website preferences can help the followers of web events, e.g. peoples or organizations, to select the proper websites to follow their interested aspects of web events. However, the big volume, fast evolution speed, multisource and unstructured data all together make the value of website preferences mining very challenging. In this paper, website preference is formally defined at first. Then, according to the hierarchical attribute of web events data, we propose a hierarchical network model to organize big data of a web event from different organizations, different areas and different nations at a given time stamp. With this hierarchical network structure in hand, two strategies are proposed to mine the value of websites preferences from web events data. The first straightforward strategy utilizes the communities of keyword level network and the mapping relations between websites and keywords to unveil the Value in them. By taking the whole hierarchical network structure into consideration, an iterative algorithm is proposed in second strategy to refine the keyword communities like the first strategy. At last, an evaluation criteria of website preferences is designed to compare the performances of two proposed strategies. Experimental results show the proper combination of horizontal relations (each level network) with vertical relations (mapping relations between three level networks) can extract more value from web events data and then improve the efficiency on website preferences mining.
Incorporating CMMI with Agile Methods: Using Change Management

— Agile development approaches promise increased customer satisfaction, faster development, and a solution to rapidly changing requirements. On the other hand, CMMI approaches promise predictability, stability, and high assurance. The topic talked over many times is that “Agile development methods and CMMI best practices are fundamentally often perceived to be at odds with each other”; however, according to a technical document of SEI in the late of 2008 [1] , it is now clear that these two approaches are compoundable. Now the main challenge is when and how to compound the two approaches in a way that takes advantage of their strengths while compensating for their weaknesses [2, 16] . More precisely, one of the main causes of failure in agile projects is stable requirements that have not been planned in initial designs, versus one of the main reasons of failure in CMMI projects are being highly variable requirements. In this paper, we provide a method for Projects structure based on the change management which clarifies when to incorporate agile and CMMI regarding features of a project. Based on our findings, we conclude that using agile approaches is appropriate for those systems which have small or medium size with a lot of changes and flexibility. In contrast, for very large and certain systems, with small or medium size and flexibility, we should use CMMI approach. Finally, for the systems with significant flexibility and changes, we could apply incorporating agile and CMMI approaches.
Synthesis and Evaluation of Ion Imprinted Mercapto-Functionalized Nano Alumina as a Selective Sorbent for Nd(III) Removal from Water Samples

In this study a Nd(III) ion imprinted mercapto-functionalized nano alumina sorbent was synthesized via a surface imprinting technique as selective adsorbent for removal of Nd(III) ion from aqueous sample. The effects of different variables such as solution pH, sorption time, adsorbent dosage and initial metal ion concentration upon adsorption characteristics were investigated.The equilibrium data obtained from Nd(III) ions sorption capacity onto the adsorbent were fitted to Langmuir, Freundlich, Temkine and Dobenian-Radushkevich isotherms. The Resultsrevealedthat the adsorption process obeyed the Langmuir model and the maximum monolayer capacity (q ) and the Langmuir constant (K ) (were calculated from the max L Langmuir model as 416.7 mg g and 0.273 L mg , respectively. Kinetic studies indicated the adsorption 11 process followed a pseudo-second-order model. After optimization the parameters, the synthesized sorbent can be utilizedsuccessfully for selective removal of Nd(III) ions from variouscations in dilute aqueous solution.
The improved passive dynamic model with high stability

The self-adjusted limit cycle gait, integrating continuous swings with intermittent heelstrike collision, can make a completely uncontrolled and unactuated passive walker walk stably down a gentle slope, only powered by the gravity. However, this natural and high energy-efficient gait is also highly susceptible to its specific variable parameters and any slight perturbations. Thus, reasonable parameter configurations and proper feet shape are significant for the robot to attain better stability and disturbance rejection, which determine whether the robot can walk stably and how fast the walker recovers from external disturbances. Because of the continuity of disturbances and the periodicity of the gait, the robustness is determined not only how much the disturbance is, but also, how fast the robot can recover from a disturbance to be capable of next disturbance rejection in order to continue to walk. Thus, the local stability is focused on in the paper. Moreover, the effects of parameter variation on the local stability and characteristic of gait of passive walking models are discussed. Mechanical parameters of model are carefully tuned. The simulation results show that the model could endure larger continuous disturbances and recover faster than ever discovered.
Lira stabilisation, construction boom and the level of economic activity: the Shift in Favour of Non-Traded Goods Prices and Urban Rents

Lira convertibility in the 19th century was mainly advocated due to the need to attract foreign capital, to avoid the temptation of monetizing the huge state debt, to keep the state budget under control and to limit the uncertainties in trade settlements with Italy's main partners, which were gold-standard countries. However, going back to gold had various consequences. Urban rents and the sheltered sectors of the economy, as well as construction activity were favoured by a significant, relative price shift, while industrial and agricultural exporters were subject to additional stress. Two resumption episodes are studied and some conclusions for the present process of European monetary unification and enlargement are discussed.
Capture, Annotate, Browse, Find, Share: Novel Interfaces for Personal Photo Management

The vision of ubiquitous digital photos has arrived. Yet, despite their broad popularity, significant shortfalls remain in the tools used to manage them. We believe that with a bit more creativity and effort, the photo industry can solve many of these problems, offering tools which better support accurate, rapid, and safe shared annotations with comfortable and efficient browsing and search. In this article, we review a number of projects of ours and others on interfaces for photo management. We describe the problems that we see in existing tools and our vision for improving them.
Pulsatile Stretch Remodels Cell-to-Cell Communication in Cultured Myocytes

Mechanical stretch is thought to play an important role in remodeling atrial and ventricular myocardium and may produce substrates that promote arrhythmogenesis. In the present work, neonatal rat ventricular myocytes were cultured for 4 days as confluent monolayers on thin silicone membranes and then subjected to linear pulsatile stretch for up to 6 hours. Action potential upstrokes and propagation velocity (&THgr;) were measured with multisite optical recording of transmembrane voltage of the cells stained with the voltage-sensitive dye RH237. Expression of the gap junction protein connexin43 (Cx43) and the fascia adherens junction protein N-cadherin was measured immunohistochemically in the same preparations. Pulsatile stretch caused dramatic upregulation of intercellular junction proteins after only 1 hour and a further increase after 6 hours (Cx43 signal increased from 0.73 to 1.86 and 2.02% cell area, and N-cadherin signal increased from 1.21 to 2.11 and 2.74% cell area after 1 and 6 hours, respectively). This was paralleled by an increase in &THgr; from 27 to 35 cm/s after 1 hour and 37 cm/s after 6 hours. No significant change in the upstroke velocity of the action potential or cell size was observed. Increased &THgr; and protein expression were not reversible after 24 hours of relaxation. Nonpulsatile (static) stretch produced qualitatively similar but significantly smaller changes than pulsatile stretch. Thus, pulsatile linear stretch in vitro causes marked upregulation of proteins that form electrical and mechanical junctions, as well as a concomitant increase in propagation velocity. These changes may contribute to arrhythmogenesis in myocardium exposed to acute stretch.
A Configurable Energy Aware Resource Management Technique for Optimization of Performance and Energy Consumption on Clouds

This paper focuses on devising a configurable resource management technique for use in clouds for processing batches of MapReduce jobs associated with Service Level Agreements (SLAs). The proposed technique permits cloud service providers to make resource management decisions which consider client quality of service requirements, system performance, and energy consumption which directly affects data center operation costs. This research models the resource management problem as an optimization problem using Constraint Programming (CP). A simulation-based performance analysis that demonstrates the effectiveness of the approach is provided.