Miracle-dz/UniFAR-FTUs huggingface dataset:
MACROECONOMICS IN PRACTICE: USING WIKIS FOR COLLABORATIVE LEARNING

This project is based on the creation of collaborative wikis for students of Macroeconomics to elaborate a final work in which they apply the theoretical knowledge learnt in the subject to the real world. The initiative was implemented during the course 2015-2016 and aimed at 140 students enrolled in the subject at the Degree of Finance and Accountancy of the University of Cadiz. To emphasize the link between the theories explained in class and the real world, in previous courses we have already used news and other resources. With this project, we now introduce the use of wikis, which consist on the creation of a website to allow collaborative creation and modification of contents and structure from the web browser. Students were organized in 44 teams, of about 3 members, to examine data on a certain macroeconomic variable (i.e. inflation or GDP), in a particular geographical context (i.e. G20 or EU countries). The objectives of the project include: i) to enhance learning and comprehension of theoretical knowledge and ii) to contribute to the development of skills related to the subject, such as the skill to apply the acquired knowledge, the skill to analyze and search information and teamwork. Students’ opinions gathered from a survey at the end of the course suggest that these objectives have been achieved.
Sounds from the Past the Acoustics of Sultan Hassan Mosque and Madrasa

The Sultan Hassan Mosque and Madrasa is considered to be stylistically the most compact and unified of all of Cairo's Islamic monuments. Beside its main function as a place for prayer, its design also allows separate schools for teaching the four Sunni rites; both functions imply the importance of phonological cognition and intelligibility of speech. The acoustical environment within the main Iwan of the Madrasa and Mosque of Sultan Hassan has been investigated and examined through field measurements and room simulation utilizing ODEON to assess the degree of speech intelligibility. The significance of acoustical performance within this space is highlighted in relation to form and texture. Criteria for good acoustics are compared with the spatial requirements and design guidelines. Although field measurements show high reverberation time and echoes at some of the points examined, it does not badly affect the ability of worshipers to follow and understand clearly what is said either in the Mihrab, a half cylinder directed to the Holy Ka'aba in Macca, or Minber (Pulpit). On the contrary it adds the depth and width required for this kind of spiritual performance.
A Research Survey of Devnagari Handwritten Word Recognition

Devnagari is the most popular script in India it is used by over 400 million people all over world. Recognition of Devnagari handwritten word has been a popular research area for many years because of its various applications. This paper describes different techniques for pre-processing, segmentation, feature extraction and classification which play an important role for recognition of word.
Ontological Considerations When Modeling Missing Data With Relational Databases

SQL’s use of nulls to indicate missing data in relational databases has been criticized as violating the relational model. In this article, I review this critique and two popular recommendations of resolution. The first is to retire SQL’s multivalued logic and replace it with a conventional binary logic. The second is to revise SQL’s implementation of multivalued logic so that it can recognize tautological propositions. I argue that underlying this debate is an ontological disagreement about how to properly model missing data and, more generally, social reality. I demonstrate that the relational model provides useful tools for modeling different types of missing data in different ways and, furthermore, offers a useful foundation upon which to conduct social research, one that supports both variable-oriented and case-oriented analysis.
Multifeature biometric system based on EEG signals

This paper focuses on the person authentication problem based on EEG signals. Many features extracted from EEG recordings have proved to be unique enough among subjects for biometric application. However, different features show different discriminative power for different subjects and different trials. We present here an authentication system, which make use of a multifeature fusion architecture. The results demonstrate to improve the system performance. Depending on the security level, different thresholds can be applied. The influence of different thresholds on system performance is discussed.
Optimization Model for Railway Freight Station Layout Based on Agent

An optimization model of China railway freight station layout based on agent and human-element-model has been put forward to solve the problems that have hindered the normal product, such as too many railway freight stations and too clear distance between stations, and so on. The model uses the classical Sugars cape as the reference and integrates the intelligence of Agent and the combination of subjectivity and objectivity of Human-element. The owners are regarded as autonomic Agents and the freight stations are regarded as resources in the model. The Agent energy can change during it seeks the resources, and its value is decided by its own energy. According to the set rules, a freight station layout in a definite scope is obtained through stimulation analysis, and the existing processes of different owner are analyzed. The simulation results show that the model has the characteristics of intelligence and autonomy, and it is meaningful to optimize the freight station layout and set the strategic cargo-loading and logistics strategy.
Lossless compression of color halftone images using color channel adaptive templates

A novel lossless compression scheme is presented for color halftone images dithered by a clustered dot ordered scree. In the encoder, the context template is designed according to the line pattern of each color channel image. Based on the designed template, then, each channel image is compressed by a context-based arithmetic encoder. Finally, both the compressed image data and the template information are transmitted to the decoder. In the decoder, the template shape information is reconstructed, and then, the halftone image is decoded losslessly. Based on the adaptiveness of the template to the input image, the proposed system yields better compression performance than the conventional JBIG, which saves 35% of the JBIG bitstream.
2011 IEEE Conference on Computational Intelligence and Games

work put in by the team from Rees Management Group led by Jane Shepa-rd was also instrumental in the successful organization of the conference. In addition to the proceedings, IJCNN 2011 also generated other useful multimedia. The IEEE CIS VP for Education, Jennie Si, organized the recording of all plenary talks, which will be available through the IEEE Computational Intelligence Society. All talks in the " From Brains to Machines " symposium were also recorded, and will be made available to the public. A special issue of Neural Networks with expanded versions of selected IJCNN papers will be published in mid-2012, edited by Jean-Philippe Thivierge and the members of the IJCNN 2011 Executive Committee. Three decades ago, the computer revolution took root and flourished in the fertile soil of what came to be known as Silicon Valley. It is appropriate that those who are igniting another technological revolution to create truly lifelike intelligence assembled in the heart of Silicon Valley once again to exchange ideas and celebrate the future. It was a great honor for me to be a part of this exciting event. I am sure that IJCNN 2011 will be the prelude to greater growth and success for the entire field of neural networks. O ut of the economic and climatic turmoil, we had a dreamy summer end with game fever in Seoul, South Korea, which is famous for the popularity of enthusiastic young gamers as well as traditional board games. GO is so popular that it is not difficult to find private GO academies and playing rooms in Seoul (called as KI-WON). StarCraft is one of the most popular games in Korea; there are plenty of professional gamers sponsored by major companies and a few TV channels specialized for games. When we got appointed as the host of the CIG, General Chair Sung-Bae Cho and Local Chair Kyung-Joong Kim felt a strong responsibility to make the synergy between the CIG community and the Korean game culture. CIG 2011 features three keynote addresses and four tutorials from prominent experts, 46 full papers accepted for oral presentation and six competitions. Keynote speakers include Greg Ashe from Blizzard Entertainment, Nathan Sturtevant from University of Denver and Jong-Hwan Kim from KAIST. Four tutorials are provided at the first day of the conference: Bob In total, we received 75 papers from 27 countries that have been reviewed by at least three domain …
A weighted closeness-based trust combination model

The trusted computing has become an effective method to resolve trust related problems in current network security environment. In order to improve the trustworthiness of trust evaluation, a model based on weighted closeness of trust combination (WCTC) is presented. The model chooses the trusted path with considering the transition fading, time decay, weight of the path and so on. The model decreases the time complexity in the search of the trusted paths. The model uses weighted closeness to combine the recommendation paths. Through building the trusted network, the validity of the model is analyzed by mathematics method, and the policy to inhibit the malicious recommendation is given. Finally, the experiment has shown that this model has improved the trustworthiness of trust evaluation, the trust combination based on weighted closeness of the trust combination can be used in various trust models and it has better adaptability.
An evolutionary approach for high dimensional attribute selection

We present a method to select a relevant dimension subset (with few or no loss of information) for clustering and outlier detection in high dimensional datasets. We use a heuristic search for relevant dimension subset selection based on genetic algorithm. The genetic algorithm fitness function for clustering uses the validity indexes of classification algorithms. We first use these validity indexes to select a dimension subset and then, to evaluate the clustering quality in this subspace. For outlier detection, the genetic algorithm fitness function is an individual distance-based function. The performances of our new approach of dimension selection are evaluated on simulations with different high dimensional datasets for the two applications (clustering and outlier detection). Furthermore, as the number of dimensions is low, it is possible to display the datasets in order to visually evaluate and interpret the obtained results.
Comparison of dynamic hip screw and proximal femoral nail in intertrochanteric femur fractures and cost analysis

Purpose: The study was planned to compare the results of dynamic hip screw (DHS) and proximal femoral nail antirotation (PFNA) applications to femur intertrochanteric fractures and to implement a cost analysis. Materials and methods: A retrospective evaluaton was made of 75 patients who were treated for intertrochanteric femur fracture between May 2009 and December 2012. Evaluation was made of differences between the groups in reduction quality, mean duration of hospitalization, complication rates, functional outcomes and treatment costs. Results: Thirty patients were treated with DHS and forty five patients with PFNA. The average follow-up period was 21.5 (12-49) months. Functional outcomes were similar, with no significant difference between the groups. Length of hospital stay was shorter in the PFNA group, the treatment and care costs were lower compared to the DHS group. Conclusion: Although PFNA is a much more expensive implant than DHS, there is no significant difference between total hospital costs. Nevertheless, as DHS has similar functional results, it is still a preferrable treatment method for intertrochanteric femur fractures.
rotl: an R package to interact with the Open Tree of Life data

While phylogenies have been getting easier to build, it has been difficult to reuse, combine and synthesize the information they provide because published trees are often only available as image files, and taxonomic information is not standardized across studies. The Open Tree of Life (OTL) project addresses these issues by providing a digital tree that encompasses all organisms, built by combining taxonomic information and published phylogenies. The project also provides tools and services to query and download parts of this synthetic tree, as well as the source data used to build it. Here, we present rotl, an R package to search and download data from the Open Tree of Life directly in R. rotl uses common data structures allowing researchers to take advantage of the rich set of tools and methods that are available in R to manipulate, analyse and visualize phylogenies. Here, and in the vignettes accompanying the package, we demonstrate how rotl can be used with other R packages to analyse biodiversity data. As phylogenies are being used in a growing number of applications, rotl facilitates access to phylogenetic data and allows their integration with statistical methods and data sources available in R.
On the Convergence of Chord Network

Due to the churn, the P2P overlay network can not be static. The dynamic environment may degrade the services provided by distributed hash table (DHT), then the convergence of the overlay is very important. In this paper, we try to analyze the convergence of Chord network. We prove that the generic structures of Chord network is a pseudo-tree, which can be converged to a circle by algorithm stabilize. The ring in Chord has more meanings than a circle in graph theory, and the ring requires all nodes in the network permuted by their ids. An efficient strong_stabilize algorithm is proposed to make the network converge to a ring rapidly.
Novel Face Detection Technique

This paper proposes a classification-based face detection method using Gabor filter features. Considering the desirable characteristics of spatial locality and orientation selectivities of the Gabor filter, we design filters for extracting facial features from the local image. The feature vector based on Gabor filters is used as the input of the classifier, which is a Feed Forward neural network (FFNN) on a reduced feature subspace learned by an approach simpler than principal component analysis (PCA). The effectiveness of the proposed method is demonstrated by the experimental results on testing a large number of images and the comparison with the state-of-the-art method. The image will be convolved with Gabor filters by multiplying the image by Gabor filters in frequency domain. To save time they have been saved in frequency domain before Features is a cell array contains the result of the convolution of the image with each of the forty Gabor filters. The input vector of the network will have large values, which means a large amount of computation. So we reduce the matrix size to one-third of its original size by deleting some rows and columns. Deleting is not the best way but it save more time compare to other methods like PCA.Face detection and recognition has many applications in a variety of fields such as security system, videoconferencing and identification. Face classification is currently implemented in software. A hardware implementation will allow us real-time processing but has higher cost and time to-market. The objective of this work is to implement a classifier based on neural networks (Multi-layer Perceptron) for face detection. The ANN is used to classify face and non-face patterns.
An Interactive Whiteboard Model Survey: Reliable Development

Applications and practices of interactive whiteboards (IWBs) in school learning is important focus and development trend for developmented countries in recent years. There are rare researches and discussions about IWB teaching materials for course teaching and teaching effectiveness. As for the aspect of academic studies, there is more practical teaching sharing for subjects such as language learning, mathematical learning and physical science learning; however, it is rarely seen empirical research on the application of IWB for educational acceptances of interactive whiteboards. Based on its imporatances, we summarize previous literatures to establish a theoretical model for interactive whiteboards (IWBs). Variables in this model are then discussed to find out the interaction between each other. The contribution of the study develops an innovative model for educational acceptances of interactive whiteboards using hybrid TAM, ECM, and Flow models.
A Trade-off Pareto Solution Algorithm for Multi-objective Optimization

Most optimization problems in real life are multiobjective optimization problems. The difficulity of multiobjective programming lies in the fact that the objectives are in conflict with each other and an improvement of one objective may lead to the reduction of other objectives.While achieving the global optimal in all objective at the same time is impossible. we use particle swarm optimization to improve the multiobjective patero solution and get the multi-objective trade-off patero optimal solutions. Numerical experiments show that our algorithms are effective, we can get multi-objective patero solutions set and multi-objective trade-offs patero optimal solution at the same time. Keywords-Multi-bjective;Optimization,Patero optimal; PSO;elitism set;
Estimation of genetic parameters and genetic trends for weight and body measurements at birth in sheep populations in Thailand

The main objective of this study was to estimate the genetic parameters and genetic trends for birth weight (BW), heart girth (HG), and body length (BL) at birth of sheep populations in Thailand. Data were collected during 1998 to 2011 from four livestock research and testing stations. Fixed effect testing showed that sex, herd, contemporary group and breed group greatly influenced on the investigated traits (P<0.05). The log likelihood ratio test showed that all traits significantly affected by maternal additive genetic effect as well as covariance between animal effects. Estimated direct heritabilities from multivariate analysis of the model for BW, HG and BL were 0.32, 0.52 and 0.54, while estimated maternal heritabilities were 0.23, 0.14 and 0.14, respectively. Positive correlations were found among direct additive genetic (0.29 to 0.97), maternal additive genetic (0.23 to 0.95), and phenotype (0.18 to 0.96). Direct-maternal correlations within traits (-0.68 for BW, -0.92 for HG and -0.89 for BL) and between traits (-0.89 to -0.08) were antagonistic effect. Direct additive genetic trends for BW, HG and BL in the second period (2005 to 2011) were significantly increased (0.02 kg/year, 0.89 and 0.73 cm/year) while maternal additive genetic trends characteristically depicted significantly decreased (-0.01 kg/year, -0.92 and -0.72 cm/year).
The 4 th International Conference on Ambient Systems , Networks and Technologies ( ANT 2013 ) SARP : Synchronous Adaptive Routing Protocol for MANETs

The aim of a routing protocol is to compute valid routes allowing every couple of nodes in the network to communicate at anytime. When the network topology is evolving over time, routing decisions should be constantly reconsidered. The main goal is to ensure a valid routing through time at the lowest possible cost. Conventional proactive routing protocols periodically recompute their routing tables; but due to their inherent nature based on shortest paths, they select longer links that ensure faster routing but are amenable to rapid breakages as nodes move around. Using short periods certainly allows a better tracking of the topology changes; however, it induces a higher control signaling overhead. An adequate trade-off between the routing period size and the traffic overhead should be found. In this paper, we propose a new mechanism that keeps sensing the network mobility level to properly adjust the routing period size. It relies on a distributed algorithm that collects the network cartography which is then used to self-regulate the routing period size. Simulation results show that our proposed scheme correctly tracks changes and properly adjusts the current routing period size leading to much better performances. c © 2011 Published by Elsevier Ltd.
Positive Organizational Behavior Variables And The Effects Of Boredom Proneness On Perceived Organizational Support

The goal of this study is to emphasize the importance of positive organizational behavior (POB) and boredom proneness for businesses and to analyze their impact on employee behavior. The study is expected to show that positive organizational behavior variables have a positive explanatory power on perceived organizational support (POS) and that boredom proneness has a negative explanatory power. The study also investigates whether the organizational climate has a mediation effect on the effect of positive organizational behavior variables and boredom proneness on perceived organizational support.
Performance Analysis of Differential Frequency Hopping System with Multi-tone Jamming Over Rayleigh-fading Channels

Differential Frequency Hopping (DFH) is a novel technique for the frequency-hopping system in HF (High Frequency) bands. The frequency transition function (FTF) and the signal detection methods are the key issues for DFH system. Symbol-by-symbol detection and sequence detection are adopted in DFH system. With these two detection methods, the symbol error rate (SER) performances of DFH system are analyzed over a Rayleigh-fading channel with Multi-tone Jamming (MTJ) and additive white Gaussian noise (AWGN). Simulations validate the analyses. The results of analyses and simulations prove that the DFH system with sequence detection can achieve better anti-jam (AJ) performance than that of conventional frequency-hopping (FH) system.
Automatic Knowledge Transfer for Agent-based Bilateral Negotiation Tasks

Learning opponents is an important problem in multi-issue automated negotiation. However it is a difficult problem due to (1) the indirect way the target function can be observed, and (2) the limited amount of experience available to learn from an unknown opponent at a single session. To address these difficulties we propose to adapt two approaches from transfer learning. Both approaches transfer knowledge from previous sessions to current negotiation session of an agent when learning the latent behaviour model of the opposing agent. The first approach transfers by weighting the encounter offers of previous and ongoing sessions while the second one by weighting the models learnt from the previous negotiation sessions and the model learnt from the current negotiation session. Experimental results show the applicability and effectiveness of both approaches. Moreover, the robustness of the proposed approaches is evaluated using empirical game theoretic analysis.
/spl chi/-SCTL/MUS: a formal methodology to evolve multi-perspective software requirements specifications

The objective of this thesis is to extend the formal methodology of refinement of requirements specifications SCTL/MUS to a multi-perspective environment where coexist requirements specifications which belong to each stakeholder involved in the software development of the system. To reach this goal, the new methodology (referred to as /spl chi/-SCTL/MUS) bets on using a viewpoint-based approach which allows to gather and maintain (possibly inconsistent and incomplete) information gathered from multiple sources. It explicitly separates the descriptions provided by different stakeholders, and concentrates on identifying and resolving conflicts between them.