Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Ubiquitous Computing with Quality of Web Service support

Yannis Makripoulias, Chirstos Makris, Yiannis Panagis, Evangelos Sakkopoulos, Poulia Adamopoulou, Miltiadis Lytras and Athanasios Tsakalidis 1 Research Academic Computer Technology Institute Internet and Multimedia Technologies Research Unit N. Kazantzaki Str. 26504 Patras, Greece 2 Computer Engineering & Informatics dpt School of Engineering, University of Patras Rio Campus, 26500 Patras, Greece E-mail: {makripou, makri, panagis, adamopop}@ceid.upatras. gr, {sakkopul,tsak, lytras}@cti.gr ABSTRACT Web services have introduced an new era for distributed application development. WS are based on ubiquitously adopted internet standards, therefore supporting interoperability across different platforms. Further establishment of web services in the IT community demands the capability to dynamically respond to different non functional requirements such as performance, network communication or requirements of maintenance and execution cost. Recent work has been presented mainly towards the support of quality of service (QoS) parameters of the WS selection. Up to now, WS requesting process is supported by a industry standard catalogue, the UDDI [6], which does not take into account QoS requirements In this work, we discuss WS discovery infrastructure that allows ubiquitous consumption of a WS with consideration of quality factors. We build upon the design presented by [1] and we present a more generalized solution that comprises dynamic WS categories. The key target of this work is to combine typical procedures of WS discovery roadmap with the benefit of QoS characteristics without loss in compatibility. To verify and measure functionality, feasibility and effectiveness of the solution presented evaluation in laboratory environment has been performed.
Nominal Cross Recurrence as a Generalized Lag Sequential Analysis for Behavioral Streams

We briefly present lag sequential analysis for behavioral streams, a commonly used method in psychology for quantifying the relationships between two nominal time series. Cross recurrence quantification analysis (CRQA) is shown as an extension of this technique, and we exemplify this nominal application of CRQA to eye-movement data in human interaction. In addition, we demonstrate nominal CRQA in a simple coupled logistic map simulation used in previous communication research, permitting the investigation of properties of nonlinear systems such as bifurcation and onset to chaos, even in the streams obtained by coarse-graining a coupled nonlinear model. We end with a summary of the importance of CRQA for exploring the relationship between two behavioral streams, and review a recent theoretical trend in the cognitive sciences that would be usefully informed by this and similar nonlinear methods. We hope this work will encourage scientists interested in general properties of complex, nonlinear dynamical systems to apply emerging methods to coarse-grained, nominal units of measure, as there is an immediate need for their application in the psychological domain.
Interactive exploration of very large relational datasets through 3D dynamic projections

The grand tour, one of the most popular methods for multi-dimensional data exploration, is based on orthogonally projecting multidimensional data to a sequence of lower dimensional subspaces and then moving continuously from one to another. By running experiments on screen and in the CAVE virtual environment, we were able to use the method for the 3D rendering of very large relational datasets where projections are made onto 3D subspaces. 3D cluster-guided tour is proposed where sequences of projections are determined by centroids of data clusters. It makes inter-cluster-distance-preserving projections in the perspectives that the data clusters are displayed as separate as possible. The exploration of very large datasets is supported by using volume rendering through texture splatting. Volume rendering takes as input only the aggregation or part of data needed for rendering, which can be retrieved eﬃciently by SQL queries in an ad hoc manner while we explore or drill down large datasets. To facilitate interactive picking and brushing, a kd-tree multidimensional indexing mechanism is designed. Access methods for subspace search and range query are proposed to greatly reduce the cost of searching and picking interesting data records. Various add-on features, such as projecting variable axes and cluster similarity graphs, help further the understanding of data.
Designing Optimal UWB Pulse Waveform Directly by FIR Filter

In this paper, we address the optimal mask-constraint UWB pulse waveform design problem. We let the basic pulse waveform to be synthesized by FIR filter. But unlike the optimization of the mask utilization efficiency by way of autocorrelation of filter coefficients in [1][2], we do it directly with respect to the filter coefficients, and get performance improvement, such as larger mask utilization ratio and shorter filter length requirement. We also analyze the influence of the basis pulse's parameters on the synthesized pulse.
On the Truncation Error of Generalized Sampling Expansions in Shift-Invariant Spaces

Any function in a shift-invariant space with stable generator ' can be recovered, under suitable hypotheses, from regular samples of some ltered versions of the function itself. This work concerns with the truncation error for the corresponding sampling expansion. In particular, whenever the generator ' and the impulse responses of the involved lters have compact support we obtain the asymptotic behaviour of the truncation error without a previous knowledge of the sampling functions. We illustrate the obtained results with some examples in the cubic spline space.
A Neuro-fuzzy Approach to Forecast the Electricity Demand

This work presents a neuro-fuzzy model for solving the medium - term electric load-forecasting. The model used a time series of monthly data. The load forecasting is based on Adaptive Neural Fuzzy Inference System (ANFIS). The results are compared to those of an Autoregressive (AR) model and an Autoregressive Moving Average model (ARMA). The ANFIS model gave better results than AR and ARMA model.
Irregular Tree-Structured Bayesian Network for image segmentation

Unsupervised image segmentation algorithms rely heavily on a probabilistic smoothing prior to enforce local homogeneity in the segmentation results. The tree-structured prior [1, 2, 3] is one such prior which allows important multi-scale spatial correlations that exist in natural images to be captured. Two main types of tree structure prior have been previously proposed: 1) fixed quadtree structure [1], which suffers from “blockiness” in the segmentation results and 2) flexible tree structure [2, 3] which can adapt its structure to the natural object boundary but at a significant computational cost. This paper presents a novel probabilistic unsupervised image segmentation framework called Irregular Tree-Structured Bayesian Networks (ITSBN) which introduces the notion of irregular tree structure that combines the merits of the two previous approaches. As in [2, 3], more natural object boundaries can be modeled in our framework since a tree is learned for each input image. Our method, however, does not update the adaptive structure at every iteration which drastically reduces the computation required. We derive a time-efficient exact inference algorithm based on a sum-product framework using factor graphs [4]. Furthermore, a novel methodology for the evaluation of unsupervised image segmentation is proposed. By integrating non-parametric density estimation techniques with the traditional precision-recall framework, the proposed method is more robust to boundary inconsistency due to human subjects.
Wireless Network-Coded Multi-Way Relaying Using Latin Hyper-Cubes

Physical layer network-coding for the $n$-way wireless relaying scenario is dealt with, where each of the $n$ user nodes $X_1,$ $X_2,. ,X_n$ wishes to communicate its messages to all the other $(n-1)$ nodes with the help of the relay node R. The given scheme, based on the denoise-and-forward scheme proposed for two-way relaying by Popovski et al. in \cite{PoY1}, employs two phases: Multiple Access (MA) phase and Broadcast (BC) phase with each phase utilizing one channel use and hence totally two channel uses. Physical layer network-coding using the denoise-and-forward scheme was done for the two-way relaying scenario in\cite{KPT}, for three-way relaying scenario in \cite{SVR}, and for four-way relaying scenario in \cite{ShR}. This paper employs denoise-and-forward scheme for physical layer network coding of the $n$-way relaying scenario illustrating with the help of the case $n = 5$ not dealt with so far. It is observed that adaptively changing the network coding map used at the relay according to the channel conditions reduces the impact of multiple access interference which occurs at the relay during the MA phase. These network coding maps are chosen so that they satisfy a requirement called \textit{exclusive law}. We show that when the $n$ users transmit points from the same $M$-PSK $(M=2^{\lambda})$ constellation, every such network coding map that satisfies the exclusive law can be represented by a $n$-fold Latin Hyper-Cube of side $M$. The singular fade subspaces resulting from the scheme are described and enumerated for general values of $n$ and $M$ and are classified based on their removability in the given scenario. A network code map to be used by the relay for the BC phase aiming at reducing the effect of interference at the MA stage is obtained.
Extreme probability distributions of random / fuzzy sets and p-boxes

Abstract: Uncertain information about a system variable described by a random set or an equivalent Dempster-Shafer structure on a finite space of singletons determines an infinite convex set of probability distributions, given by the convex hull of a finite set of extreme distributions. Extreme distributions allow one to evaluate (through the Choquet integral) exact upper/lower bounds of the expectation of monotonic and non-monotonic functions of uncertain variables, for example in reliability evaluation of engineering systems. The paper considers the simple case of a single variable, and details applications to random sets with nested focal elements (consonant random sets or the equivalent fuzzy set) and to p-boxes. A simple direct procedure to derive extreme distributions from a p-box is described through simple numerical examples.
Online coordinate boosting

We present a new online boosting algorithm for updating the weights of a boosted classifier, which yields a closer approximation to the edges found by Freund and Schapire's AdaBoost algorithm than previous online boosting algorithms. We contribute a new way of deriving the online algorithm that ties together previous online boosting work. The online algorithm is derived by minimizing AdaBoost's loss as a single example is added to the training set. The equations show that the optimization is computationally expensive. However, a fast online approximation is possible. We compare approximation error to edges found by batch AdaBoost on synthetic datasets and generalization error on face datasets and the MNIST dataset.
Detection of operator performance breakdown as an automation triggering mechanism

Performance breakdown (PB) has been anecdotally described as a state where the human operator “loses control of context” and “cannot maintain required task performance. ” Preventing such a decline in performance is critical to assure the safety and reliability of human-integrated systems, and therefore PB could be useful as a point at which automation can be applied to support human performance. However, PB has never been scientifically defined or empirically demonstrated. Moreover, there is no validated objective way of detecting such a state or the transition to that state. The purpose of this work is: 1) to empirically demonstrate a PB state, and 2) to develop an objective way of detecting such a state. This paper defines PB and proposes an objective method for its detection. A human-in-the-loop study was conducted: 1) to demonstrate PB by increasing workload until the subject reported being in a state of PB, and 2) to identify possible parameters of a detection method that objectively captures the performance characteristics that map to the subjectively-reported PB point, and 3) to determine if the parameters are idiosyncratic to an individual/context or are more generally applicable. In the experiment, fifteen participants were asked to manage three concurrent tasks (one primary and two secondary) for 18 minutes. The difficulty of the primary task was manipulated over time to induce PB while the difficulty of the secondary tasks remained static. The participants' task performance data was collected. Three hypotheses were constructed: 1) increasing workload will induce subjectively-identified PB, 2) there exists criteria that identifies the threshold parameters that best captures the performance characteristics at the subjectively-identified PB point, and 3) the criteria for choosing the threshold parameters is consistent across individuals. The results show that increasing workload can induce subjectively-identified PB, although it might not be generalizable-only 12 out of 15 participants declared PB. The PB detection method based on signal detection analysis was applied to the performance data and the results showed that PB can be identified using the method, particularly when the values of the parameters for the detection method were calibrated individually.
HID-1 is required for homotypic fusion of immature secretory granules during maturation

Secretory granules, also known as dense core vesicles, are generated at the trans-Golgi network and undergo several maturation steps, including homotypic fusion of immature secretory granules (ISGs) and processing of prehormones to yield active peptides. The molecular mechanisms governing secretory granule maturation are largely unknown. Here, we investigate a highly conserved protein named HID-1 in a mouse model. A conditional knockout of HID-1 in pancreatic β cells leads to glucose intolerance and a remarkable increase in the serum proinsulin/insulin ratio caused by defective proinsulin processing. Large volume three-dimensional electron microscopy and immunofluorescence imaging reveal that ISGs are much more abundant in the absence of HID-1. We further demonstrate that HID-1 deficiency prevented secretory granule maturation by blocking homotypic fusion of immature secretory granules. Our data identify a novel player during the early maturation of immature secretory granules. DOI: http://dx.doi. org/10.7554/eLife.18134. 001
User adaptive content delivery mechanism on the world wide web

To reduce the user-perceived latency in web content delivery, many techniques have been proposed. One is a transmission time control mechanism that automatically adjusts the quality of inline objects, such as images on a web page, according to the client network bandwidth. Another is a transmission order control mechanism that can transmit inline objects in a specified order preferred by users. In this paper, we describe the development of a user adaptive content delivery mechanism that integrates transmission time control and transmission order control. Based on the user's preference profile, it dynamically prioritizes inline objects in terms of content quality and delivery order, and provides user with adapted inline objects. A prototype system has been implemented in Java, and gives an example of adapted content delivery.
A Research on the Localization Technology of Wireless Sensor Networks Employing TI's CC2530 Instrument

Many applications of wireless sensor networks depend on the location information of sensor nodes and how to obtain the localization has become the focus of research activities in WSN. In order to solve the problem the log-normal shadow model and the trilateration method is used to estimate location of a sensor node in the paper. Many Experiments have been done to reduce the distance error and the experiment results show that the method is a better way for node position.
An Energy Based Excess Pore Pressure Generation Model

In this paper, application of energy-based excess pore pressure generation model proposed by Park et al. (2008) to develop an improved model for the analysis of liquefaction potential and to predict excess pore pressure (EPP) is examined through experimental and analytical investigations. For more realistic description of the dynamic responses of saturated sand undrained dynamic triaxial tests are conducted by using earthquake loading conditions with different relative density. Based on test results, the relative density is the other factor to be addressed in the procedure proposed by Park et al. (2008). The new equations of model parameters with relative density are addressed. From results of additional undrained dynamic triaxial tests, it is seen that predicted EPP generation using the model using new model parameters agrees well with measured results for earthquake loading cases.
Performing chart interpretation using lexical selection in Indonesian language

Recently, Indonesian Health Ministry has problems with interpreting health surveillance chart, because they need experts for interpreting the chart. Since it is difficult to provide experts especially in rural area, intelligent system for interpreting the health surveillance chart is necessary. This paper proposed a method to generate sentences in Indonesian language which is extracted from the chart image (e.g. health surveillance chart). The sentences is used to interpret the chart in Indonesian Language. In order to generate sentences, lexicalization based on image features data is proposed to provide some “seed words”. These words are used by the NLG system to generate sentences. After obtaining the seed words, the lexical selection is conducted and the main topic of the paragraph is determined. Finally, the main topic was determined and furthermore the sentence in Indonesian Language is ready to be generated. There were some methods for interpreting data such as [1][2][3], but this method could not be used in Indonesian Health Ministry case because most of the chart which should be interpreted are in the form of chart image. Therefore, the proposed method uses NLG based on image extraction and pattern abstraction, such that it can be used for interpreting the chart image.
Visual learning by imitation with motor representations

We propose a general architecture for action (mimicking) and program (gesture) level visual imitation. Action-level imitation involves two modules. The viewpoint transformation (VPT) performs a "rotation" to align the demonstrator's body to that of the learner. The visuo-motor map (VMM) maps this visual information to motor data. For program-level (gesture) imitation, there is an additional module that allows the system to recognize and generate its own interpretation of observed gestures to produce similar gestures/goals at a later stage. Besides the holistic approach to the problem, our approach differs from traditional work in i) the use of motor information for gesture recognition; ii) usage of context (e.g., object affordances) to focus the attention of the recognition system and reduce ambiguities, and iii) use iconic image representations for the hand, as opposed to fitting kinematic models to the video sequence. This approach is motivated by the finding of visuomotor neurons in the F5 area of the macaque brain that suggest that gesture recognition/imitation is performed in motor terms (mirror) and rely on the use of object affordances (canonical) to handle ambiguous actions. Our results show that this approach can outperform more conventional (e.g., pure visual) methods.
The Association of Depressive Symptoms with Inflammatory Factors and Adipokines in Middle-Aged and Older Chinese

Background Studies in Western populations find that depression is associated with inflammation and obesity. The present study aimed to evaluate the relation of depressive symptoms with inflammatory factors and adipose-derived adipokines in middle-aged and older Chinese. Methodology/Principal Findings Data were from 3289 community residents aged 50–70 from Beijing and Shanghai who participated in the Nutrition and Health of Aging Population in China project. Depressive symptoms were defined as a Center for Epidemiological Studies of Depression Scale (CES-D) score of 16 or higher. Plasma concentrations of C-reactive protein (CRP), interleukin-6 (IL-6), adiponectin, resistin, plasminogen activator inhibitor-1 (PAI-1) and retinol binding protein 4 (RBP4) were measured. Of the 3289 participants, 312 (9.5%) suffered from current depressive symptoms. IL-6 level was higher in participants with depressive symptoms compared to their counterparts in the crude analyses (1.17 vs. 1.05 pg/mL, p = 0.023) and this association lost statistical significance after multiple adjustments (1.13 vs. 1.10 pg/mL, p = 0.520). Depressive symptoms were not associated with increased mean levels of any other inflammatory factors or adipokines in the unadjusted or adjusted analyses. Conclusions/Significance We found no evidence that depressive symptoms were associated with inflammatory factors and adipokines in the middle-aged and older Chinese populations. Prospective studies and studies in clinically diagnosed patients are needed to confirm our results and clarify the relation of depression with inflammatory factors and adipokines.
Exploring user sociocentric and egocentric behaviors in online and detected social networks

Social ties are increasingly constructed and maintained by online social networking tools. These online tools provide an alternative to the more traditional physical meeting approach of establishing and maintaining social relationships. This paper explores the similarities and the differences between the Bluetooth-based detected social network and the Facebook social network, for a particular set of users. Specifically, we explore and compare the egocentric and the sociocentric behaviors of nodes, highlighting the structural similarities between the two types of networks and the differences in how individuals take part in detected social network and online social network. Performing a sociocentric network analysis, our results indicate that betweenness centrality has a relatively high correlation, while the other users' centrality measures in the online social network and the detected social network vary considerably. Moreover, our results shows that the community structures of the two networks differ. The egocentric analysis further confirms that the detected and the online social networks have different structural characteristics.
It's Just Good Teaching: Creating Inclusive Elementary Classrooms Through Feminist Pedagogy

As Ontario schools become more and more diverse, inclusion in the classroom is becoming an ever more important issue for educators (Ontario Ministry of Education, 2009). This study examines how feminist pedagogy is used in elementary classrooms to contribute to inclusive learning environments. With a lack of current studies on the topic, and a lack of educator’s own voices on the topic, feminist pedagogy in the elementary classroom has been relatively under researched within Ontario (Woodham Digiovanni & Liston, 2015). Using a qualitative research approach, three semi-structured interviews were conducted with educators who identified with using aspects of feminist pedagogy in their practices. Through the interviews, the participants identified key aspects of feminist pedagogy, including acknowledging gender difference, acknowledging the diversity of students, and focusing on critical thinking in the classroom. The study found that student empowerment and student autonomy are key factors of feminist pedagogy that contributes to inclusion in the elementary classroom. From these findings, a major implication for the broad educational community suggests that using strategies focusing on student empowerment and autonomy are effective ways to promote inclusion in elementary classrooms.