Miracle-dz/UniFAR-FTUs huggingface dataset:
Load Distribution for Telecommunications Networks Using Revenue Management

In this paper we propose a new approach to the problem of routing for telecommunications networks, which is based on the control of the demand for different routes, using a price-based mechanism to segment the users to different categories according to their needs. We study how a service provider can make use of the relation between a user's quality requirements and the maximum price a user is willing to pay to maximise their income. We develop an approach where the pricing decisions of the service provider are based on characteristics of demand, especially the mean arrival rate of connections with respect to the prices and Q.oS level for each class.
Estimating Confusions in the ASR Channel for Improved Topic-based Language Model Adaptation

Human language is a combination of elemental languages/domains/styles that change across and sometimes within discourses. Language models, which play a crucial role in speech recognizers and machine translation systems, are particularly sensitive to such changes, unless some form of adaptation takes place. One approach to speech language model adaptation is self-training, in which a language model's parameters are tuned based on automatically transcribed audio. However, transcription errors can misguide self-training, particularly in challenging settings such as conversational speech. In this work, we propose a model that considers the confusions (errors) of the ASR channel. By modeling the likely confusions in the ASR output instead of using just the 1-best, we improve self-training efficacy by obtaining a more reliable reference transcription estimate. We demonstrate improved topic-based language modeling adaptation results over both 1-best and lattice self-training using our ASR channel confusion estimates on telephone conversations.
Glycated haemoglobin as a predictor for metabolic syndrome in non-diabetic Korean adults

Aims With increasing prevalence of diabetes mellitus and metabolic syndrome (MS), the importance of early detection of insulin resistance is emphasized. However, a simple and practical method of measurement is not readily available. Therefore, we examined the sensitivity and specificity of HbA1c for predicting impaired fasting glucose (IFG) and MS and its association with cardiovascular risk factors, particularly in the normal range of HbA1c levels in non‐diabetic Korean subjects.
Bacterial exopolysaccharide and biofilm formation stimulate chickpea growth and soil aggregation under salt stress

To compensate for stress imposed by salinity, biofilm formation and exopolysaccharide production are significant strategies of salt tolerant bacteria to assist metabolism. We hypothesized that two previously isolated salt-tolerant strains Halomonas variabilis (HT1) and Planococcus rifietoensis (RT4) have an ability to improve plant growth, These strains can form biofilm and accumulate exopolysacharides at increasing salt stress. These results showed that bacteria might be involved in developing microbial communities under salt stress and helpful in colonizing of bacterial strains to plant roots and soil particles. Eventually, it can add to the plant growth and soil structure. We investigated the comparative effect of exopolysacharide and biofilm formation in two bacterial strains Halomonas variabilis (HT1) and Planococcus rifietoensis (RT4) in response to varying salt stress. We found that biofilm formation and exopolysaccharide accumulation increased at higher salinity. To check the effect of bacterial inoculation on the plant (Cicer arietinum Var. CM-98) growth and soil aggregation, pot experiment was conducted by growing seedlings under salt stress. Inoculation of both strains increased plant growth at elevated salt stress. Weight of soil aggregates attached with roots and present in soil were added at higher salt concentrations compared to untreated controls. Soil aggregation was higher at plant roots under salinity. These results suggest the feasibility of using above strains in improving plant growth and soil fertility under salinity.
Topology ascendancy in mobile ad hoc networks with accommodating connections

Supportive communication has conventional tremendous attention for wireless networks. Most existing works on supportive infrastructure are focused on link- level corporeal layer issues. Consequently, the impacts of supportive infrastructure on network-level upper layer issues, such as topology control, map-reading and network capacity, are largely disregarded. In this article, we propose a Capacity-Optimized Supportive (COS) topology manage scheme to improve the network capability in MANETs by jointly bearing in mind both upper layer system capacity and physical layer supportive communications. Through simulations, we show that physical layer supportive infrastructure have important impacts on the network capacity, and the planned topology organize scheme can considerably improve the network capacity in MANETs with supportive infrastructure.
A Directed-Multicast Routing Approach with Path Replication in Content Addressable Network

In order to improve the efficiency of routing and resource location under large scale failure of Content Addressable Network, a directed-multicast routing approach is proposed to solve the backtrack problem of the traditional greedy approach. Possessing the advantages of directed routing approach and multicast, this new approach also has an extending coefficient to increase its feasibility. Meanwhile, we explore a new replication approach that we term Path Replication. Combining with Path Replication, the directed-multicast routing approach is more efficient in routing process. The efficiency of directed-multicast routing was proved in the simulations on PlanetSim.
Where do bugs come from?

"Where do bugs in programs come from? "---this is one of the pivotal research questions in software engineering. To answer it, one can find out which parts of a program are more defect-prone than others, and then investigate which properties correlate with defect density. In other words, once we can measure the effect, we can search for its causes. Bug databases of open-source projects are a good place to begin search because they record all the problems that occurred during the projects's lifetime. However, the location of the fix (and thus the defect) is hidden in version archives and has to be extracted separately [5]. As a result one obtains a mapping from defects to code locations.
Randomized Swap Matching in O(m Log M Log Jj) Time

We give a randomized algorithm for the Pattern Matching with Swaps problem which runs in O(m log m log jj) time on a text of length 2m? 1 and a pattern of length m drawn from an alphabet set of size jj. This algorithm gives the correct answer with probability at least 1? 1 m and does not miss a match. The best deterministic algorithm known for this problem takes O(m 4=3 polylog(m)) time.
A Cluster-based priority Scheduling Algorithm for MAC Layer in Wireless Sensor Networks

Based on the ideas of conflict-free transmission with high-efficiency, cluster-based networking model, and priority service, this article proposes a new scheduling algorithm of MAC protocol of WSNs, which has made possible the polling service capable of differentiating tasks of cluster nodes of two priority levels. The high-priority service of the cluster head is responsible for communication between the different clusters via exhaustive service policy, while the low-priority services of the cluster head node, for communication within the local cluster through limited service policy with good fairness. The theoretical model of this scheme is established through Markov chain, probability generating function, and Laplace-Stieltjes transformation. Mathematical analysis is made on the mean queue length, the mean inquiry cyclic time and the mean delay time. It is found that the findings from theoretical analysis correspond well with those from simulated experiments. The analyses demonstrate that this scheme enables an effective allocation of channel resources for different tasks, guarantee transmission quality of the communication between the different clusters, which further improve the cluster node's energy efficiency.
Weighted autocorrelation-based F0 estimation for distant-talking interaction with a distributed microphone network

A distant-talking scenario is addressed, where a distributed microphone network provides multi-channel input sequences to process for speaker modeling purposes. Possible related applications are speaker tracking and distant-talking speech recognition, given a noisy and reverberant environment with one or more speakers. The paper investigates on the use of a multi-channel version of a weighted autocorrelation (WAUTOC) based F0 estimation method, with the purpose of deriving a common excitation model. Experiments conducted on a real database show the advantages and the robustness of the proposed method in extracting the fundamental frequency with no regard about the microphone and talker position as well as head orientation.
Performance considerations for an embedded implementation of OMA DRM 2

As digital content services gain importance in the mobile world, digital rights management (DRM) applications will become a key component of mobile terminals. The paper examines the effect dedicated hardware macros for specific cryptographic functions have on the performance of a mobile terminal that supports version 2 of the open standard for DRM defined by the Open Mobile Alliance (OMA). Following a general description of the standard, the paper contains a detailed analysis of the cryptographic operations that have to be carried out before protected content can be accessed. The combination of this analysis with data on execution times for specific algorithms realized in hardware and software has made it possible to build a model which has allowed us to assert that hardware acceleration for specific cryptographic algorithms can significantly reduce the impact DRM has on a mobile terminal's processing performance and battery life.
Events Describe Places: Tagging Places with Event Based Social Network Data

Location based services and Geospatial web applications have become popular in recent years due to wide adoption of mobile devices. Search and recommendation of places or Points of Interests (PoIs) are prominent services available on them. The effectiveness of these services crucially depends on the availability of tags that are descriptive of places. The major geospatial databases that contain data about places suffer from the lack of descriptive tags for places, since writing them is a time-consuming process and only a few users do it despite having knowledge about places. In order to tackle this issue and automatically generate descriptive tags for places, we propose a solution that utilizes data about a set of events that happen in a specific place and use it to extract meaningful descriptive tags for that place. We use data about events held at places on Meetup, a well known event based social network and apply Latent Dirichlet Allocation (LDA) to derive sets of probable descriptive tags for any place. In order to evaluate our approach, we measure semantic relatedness between tags derived for places on Meetup and manually assigned tags from Foursquare, a location based service. Results show that event data can be used to derive semantically relevant place tags. This shows that location based services can benefit from capturing data about events to derive place tags.
Geosynchronous SAR Tomography: Theory and First Experimental Verification Using Beidou IGSO Satellite

Synthetic aperture radar (SAR) tomography (TomoSAR) techniques exploit multipass acquisitions of the same scene with slightly different view angles, and allow generating fully 3-D images, providing an estimation of scatterers’ distribution along range, azimuth, and elevation directions. This paper extends TomoSAR to geosynchronous SAR (GEO TomoSAR). First, the potential and performance of GEO TomoSAR were analyzed from the perspective of orbital perturbation and the resulting large spatial baseline. Then, the rotation-induced decorrelation problems induced by the along-track baseline component were analyzed. In addition, the optimized acquisition geometry and tomographic processing flow were given, and the computer simulation verification was also completed. Finally, the equivalent validation experiment based on Beidou inclined geosynchronous orbit (IGSO) navigation satellite was carried out to demonstrate the feasibility and effectiveness of GEO TomoSAR. The experimental system employs the Beidou IGSO satellite as illuminator of opportunity and a ground system collecting and processing reflected echoes. This is the first time to employ the data from repeat-track Beidou IGSO satellites for tomographic processing. The 3-D imaging of the urban area using this experimental system was presented and then verified using LiDAR cloud data as reference. The results show that GEO TomoSAR can form the baseline of the order of hundreds of kilometers in elevation, which has the ability to achieve a resolution of 5 m in elevation.
Detecting precise behavioral models

Models of the dynamic behavior of program executions can support testing and analysis activities. Deriving complete and precise models is hard, and model imprecision and incompleteness affect the effectiveness of model-based testing and analysis. In my PhD thesis, I aim to develop a framework to generate precise behavioral models. The approach combines dynamic analysis, static analysis and hybrid analysis. In this paper, I describe the core elements of the approach that should be applicable to multiple types of models and systems.
Early semantic and phonological effects on temporal‐ and muscle‐specific motor resonance

Previous studies using functional magnetic resonance imaging and transcranial magnetic stimulation (TMS) explored the relationships between linguistic processing and motor resonance, i.e. the activation of the motor system while perceiving others performing an action. These studies have mainly investigated a specific linguistic domain, i.e. semantics, whereas phonology has been largely neglected. Here we used single‐pulse TMS to compare the effects of semantic and phonological processing with motor resonance effects. We applied TMS to the primary motor hand area while subjects observed object‐oriented actions and performed semantic and phonological tasks related to the observed action. Motor evoked potentials were recorded in two hand muscles, one of them more involved in the execution of the observed actions than the other one, at three different timepoints (0, 200 and 400 ms after stimulus onset). The results demonstrated increased corticospinal excitability that was muscle‐specific (i.e. restricted to the hand muscle involved in the observed action), hemisphere‐specific (left), and time‐specific (400 ms after stimulus onset). The results suggest an additive effect of independent semantic and phonological processing on motor resonance. The novel phonological effect reported here expands the links between language and the motor system and is consistent with a theory of shared control for hand and mouth. Furthermore, the timing of the semantic effect suggests that motor activation during semantic processing is not an ‘epiphenomenon’ but rather is essential to the construction of meaning.
New dyes for ocular surgery : synthesis and preclinical testing

In cases of vitreoretinal interface diseases, such as macular hole or macular pucker, the inner limiting membrane (ILM) or epiretinal membranes (ERM) need to be surgically removed. The challenging step in the surgery is the transparency of ILM and ERM that makes the membranes difficult to identify and to peel without risk of damaging the retina. Only a few vital dyes have been proposed to stain the ILM and ERM and no perfect dye is available that would stain the tissue of interest sufficiently, while being non-toxic and stable in aqueous solution. During cataract surgery a dye to stain outer part of a capsule of the lens is used when the red reflex from the fundus is absent. Dyes used for capsulorhexis need to be safe for corneal endothelial cells. Phototoxicity needs to be tested for dyes intended to be used in vitreoretinal surgery. A very strong source of light is present during the surgery, that can cause the dyes to become toxic while illuminated. A set-up for testing phototoxicity on a 96-well plate has been developed. New models for staining ability of dyes for ILM and ERM are suggested, as porcine eye was proved not reliable for those studies. Instead, a model for ILM and ERM was developed with good correlation to staining of human ILM and human ERM. Pig eyes can, however, serve as a useful model for capsule staining when cataract is induced in them. A new dye for capsulorhexis is presented. No safe, green dye that would stain the capsule had been suggested before. The new dye is an alternative to the currently used Trypan Blue and provides as strong staining while being slightly less toxic to corneal endothelial cells. Fourteen new dyes, that belong to the cyanine family, were synthesized and investigated for staining ability, toxicity, and stability in aqueous solution. Two of the new substances were found to stain the model for ILM in green, while being safe to retinal epithelial cells. Their stability in aqueous solution can be achieved with additives.
Visualized comparison for CFP datasets by structure identification and ontology

This paper proposes a method to visualize relations and keywords of two Call For Paper (CFP) datasets for comparison or trend research. Based on our previous works on information extraction from CFP files and trend visualization system (FACT-Graph), this paper describes the contribution and usefulness of the different methods of data input into the visualization system. Using two CFP datasets from two academic societies in order to support our theory, we compare three input data processes from basic plain text data to structured data made from selected relevant data along with the contribution of external data from ontology models.
Parameter estimation solving a weak constraint variational formulation for an Ekman model

A weak constraint variational formulation is used for inverse calculations and parameter estimation in a one-dimensional Ekman model. When parameters in the model are allowed to contain errors, the inverse problem becomes nonlinear even if the model itself is linear. It is shown that a convergent iteration can be defined for the nonlinear system of Euler-Lagrange equations and that improved estimates of the poorly known parameters can be calculated by solving the inverse problem for each of the linear iterates using the representer method. The formulation of the variational problem and the solution methods are illustrated using a simple example. The use of a simple dynamical model makes it possible to give an instructive presentation of the representer method. The method is finally used in an example using real current meter data. It is shown that the weak constraint formulation results in smooth solutions in good agreement with the data all through the water column and that it is superior to the traditional strong constraint inverse estimate.
Finding the 'Needle': Locating Interesting Nodes Using the K-shortest Paths Algorithm in MapReduce

Understanding how nodes interconnect in large graphs is an important problem in many fields. We wish to find connecting nodes between two nodes or two groups of source nodes. In order to find these connecting nodes in huge graphs, we have devised a highly parallelized variant of a k-shortest path algorithm that levies the power of the Hadoop distributed computing system and HBase distributed key/value store. We show how our system enables previously unobtainable graph analysis by finding these connecting nodes in graphs as large as one billion nodes or more on modest commodity hardware in a time frame of just minutes.
A Single-Hop Mobile Peer-to-Peer Network Model Based on TD-SCDMA

In this paper, we propose a new hybrid network model which is based on TD-SCDMA with P2P technology of ad hoc network. Mobile terminals can communicate directly with each other and build the single-hop ad hoc network. The proposed hybrid network can effectively improve the power consumption and smooth switching. Analysis and simulation concerning both routing protocol and system capacity have been performed. The simulation results show that with the proposed system, cellular system capacity can be enhanced and energy consumption can be reduced. The simulation results show that our approach can result in a 12% improvement in system capacity and a 37% decrease in energy consumption.
STUDENTS’ EXPERIENCES OF DESIGN THINKING AND DISTRIBUTED SCAFFOLDING IN A MIDDLE SCHOOL SOCIAL STUDIES CLASSROOM

Recently, design thinking as a method to solve ill-defined problems has increased in middle school curricula. In this qualitative case study consisting of 23 participants in seven middle school student groups, this study sought to understand how students experienced and responded to design thinking and distributed scaffolding as students navigated a design challenge of creating a public art installation honoring a person or group that promoted human rights. Additionally, this research sought to explain how the distributed scaffolding embedded within each phase of design thinking further aided students in their learning and work production. This study reported how design thinking promoted critical thinking and problem solving, how students experienced and responded to distributed scaffolds that were placed into curriculum units to help students reflect, how students demonstrated social studies skill and content knowledge, and how students worked through real-world human-centered problems towards a viable solution.
A Drosophila KCNQ Channel Essential for Early Embryonic Development

The mammalian voltage-dependent KCNQ channels are responsible for distinct types of native potassium currents and are associated with several human diseases. We cloned a novel Drosophila KCNQ channel (dKCNQ) based on its sequence homology to the mammalian genes. When expressed in Chinese hamster ovary cells, dKCNQ gives rise to a slowly activating and slowly deactivating current that activates in the subthreshold voltage range. Like the M-current produced by mammalian KCNQ channels, dKCNQ current is sensitive to the KCNQ-specific blocker linopirdine and is suppressed by activation of a muscarinic receptor. dKCNQ is also similar to the mammalian channels in that it binds calmodulin (CaM), and CaM binding is necessary to produce functional currents. In situ hybridization analysis demonstrates that dKCNQ mRNA is present in brain cortical neurons, the cardia (proventriculus), and the nurse cells and oocytes of the ovary. We generated mutant flies with deletions in the genomic sequence of dKCNQ. Embryos produced by homozygous deletion females exhibit disorganized nuclei and fail to hatch, suggesting strongly that a maternal contribution of dKCNQ protein and/or mRNA is essential for early embryonic development.
Towards a lexicon of event-selecting predicates for a French FactBank

This paper presents ongoing work for the construction of a French FactBank and a lexicon of French event-selecting predicates (ESPs), by applying the factuality detection algorithm introduced in (Saurí and Pustejovsky, 2012). This algorithm relies on a lexicon of ESPs, specifying how these predicates influence the polarity of their embedded events. For this pilot study, we focused on French factive and implicative verbs, and capitalised on a lexical resource for the English counterparts of these verbs provided by the CLSI Group (Nairn et al., 2006; Karttunen, 2012).