Miracle-dz/UniFAR-FTUs huggingface dataset:
Territorial Diagnosis of Ecotourism in Tunisian Mountain Protected Areas: Stakeholders, Positions and Power Relations

Since the 2000s, projects and studies have been multiplied for the development of ecotourism in Tunisian protected areas. Despite these efforts, the Tunisian case faces several failures. As part of this study, we aim to provide elements of reflection on a contractual scheme for a sustainable territorial development plan by ecotourism, around mountain protected areas in Tunisia. For this reason, we adopted the strategic prospective analysis revealing and analyzing the relationships between the different actors involved in ecotourism in the protected area. A Matrix of Alliances, Conflicts, Tactics and Objectives among MACTOR actors was developed in a participatory way to analyze the actors' strategies. After doing a triangular analysis which consists in to an inventory of the projects and studies about the protected area of Ichkeul and Cape Negro-Jbel Chitana, semi-structured interviews with personals from different sectors, we invited the actors met on the field or mentioned in the projects in a workshop organized in partnership with the General Directorate of Forests in Tunis in order to identify the different categories of actors and analyze the balance of power between them. This analysis is done through a matrix notation system. Eight categories of actors have been identified: international cooperation, resource managers, politic policy etc. Thanks to the matrix notation systems, we have been able in a participative way to classify these eight categories of actors into four types: dominant actors, relay actors, autonomous actors and dominated actors. Thus, the MACTOR method allowed us to identify actors who played a role in the development of ecotourism projects in Tunisia and to be able to diagnose their balance of power. This allowed showing the multidisciplinarity and complexity of the sector as well as the strong influence of certain actors such as international cooperation and public decision-makers. To conclude, the MACTOR analysis of the ecotourism actors in the protected area of Ichkeul and Cap Negro-Jbel Chitana enters into a methodology of prospective territorial analysis in this area to understand the points that caused the failure of several experiments.
Chapter-6 DATA ANALYSIS AND INTERPRETATION — II: PERFORMANCE EVALUATION AND PRODUCTIVITY CHANGE

Performance evaluation, slack estimation, target setting and productivity change of the power plants are undertaken to achieve the objectives detailed at § 4.2. 2 and § 4.2. 3. The criteria adopted for selection of DMUs and variables (inputs and outputs), profile of DMUs, descriptive statistics of performance parameters, technical efficiencies (TE) and productivity change of the power plants are discussed in this chapter. TE of the plants are estimated using Data Envelopment Analysis (DEA). Distribution of TE, technical and scale efficiencies (SE), ranking of , power plants, excess consumption of inputs as input slacks, and benchmarking for performance are further analysed. The influence of categorical variables like average age and average unit capacity, geographical regions and management structures are further investigated using DEA and Post hoc Games Howell test. The total factor productivity changes (TFPCH) of the power plants are estimated using Malmquist Productivity Index (MPI) and further decomposed into technical change (TECHCH) and efficiency change (EFFCH).
G3AN: This video does not exist. Disentangling motion and appearance for video generation

Creating realistic human videos introduces the challenge of being able to simultaneously generate both appearance, as well as motion. To tackle this challenge, we propose the novel spatio-temporal GAN-architecture $G^3AN$, which seeks to capture the distribution of high dimensional video data and to model appearance and motion in disentangled manner. The latter is achieved by decomposing appearance and motion in a three-stream Generator, where the main stream aims to model spatio-temporal consistency, whereas the two auxiliary streams augment the main stream with multi-scale appearance and motion features, respectively. An extensive quantitative and qualitative analysis shows that our model systematically and significantly outperforms state-of-the-art methods on the facial expression datasets MUG and UvA-NEMO, as well as the Weizmann and UCF101 datasets on human action. Additional analysis on the learned latent representations confirms the successful decomposition of appearance and motion.
Fake Review Detection using Data Mining

Online spam reviews are deceptive evaluations of products and services. They are often carried out as a deliberate manipulation strategy to deceive the readers. Recognizing such reviews is an important but challenging problem. In this work, I try to solve this problem by using different data mining techniques. I explore the strength and weakness of those data mining techniques in detecting fake review. I start with different supervised techniques such as Support Vector Machine (SVM), Multinomial Naive Bayes (MNB), and Multilayer Perceptron. The results attest that all the above mentioned supervised techniques can successfully detect fake review with more than 86% accuracy. Then, I work on a semi-supervised technique which reduces the dimensionality of the input features vector but offers similar performance to existing approaches. I use a combination of topic modeling and SVM for the implementation of the semi-supervised technique. I also compare the results with other approaches that consider all the words of a dataset as input features. I found that topic words are enough as input features to get similar accuracy compared to other approaches where researchers consider all the words as input features. At the end, I propose an unsupervised learning approach named as Words Basket Analysis for fake review detection. I utilize five Amazon products review dataset for an experiment and report the performance of the proposed on these datasets.
SZENT ISTVÁN UNIVERSITY THE DIAGNOSTICS AND SURVEY OF TILLETIA SPECIES ON WINTER WHEAT IN HUNGARY PhD thesis

English) Körmöczi P., Halász Á. , Kredics L. and Magyar D. (2012): Presence of fungal spores associated with farmer's lung disease in the air of a grain warehouse. In: A. Gácser, I. Pfeiffer, C. Vágvölgyi and K. Nagy (eds.): 3rd CESC 2012, Central European Summer Course on Mycology, Biology of pathogenic fungi. (9-13 July, 2012, Szeged) JATE Press. p. 64. ISBN: 978-963-315-078-8
Modeling and Analysis of a Ceramic matrix composites with strain induced damage using F. E. Method

A computationally efficient FE model has been developed to predict the mechanical behavior of ceramic matrix composites with strain-induced damage. The effects of different damage modes and their interactions on mechanical behavior have been considered. The non-linear longitudinal material properties are discretised to a multi-linear elastic curve. The constitutive equations for orthotropic materials are used to update the stresses for each increment of the analysis. The model is implemented by a Finite Element package, ANSYS with a user defined subroutine, UMAT. In all analyses, the expected mechanical behavior has been obtained. Strain induced damage modes and their interactions are modeled using the finite element method for Ceramic Matrix Composites (CMC) tows and 0o/90o laminates. For both situations, bi-axial straining is addressed, together with the degradation of Young’s moduli and Poisson’s ratios. In all cases, the expected stress-strain behavior is calculated.
Wearable Sensors to Characterize the Autonomic Nervous System Correlates of Food-Like Odors Perception: A Pilot Study

Background: The sense of smell has been recently recognized as one of the most important sensory features in the human being, representing a reliable biomarker for a number of clinical conditions. The relationship between olfactory function and the person’s attitude towards food has frequently been investigated, often using questionnaires. The administration of minimally invasive methods for characterizing autonomic nervous system (ANS) functionality could help in objectivizing such measurements. Methods: The present study assessed ANS activation through the analysis of the electrocardiogram (ECG) and galvanic skin response (GSR) signals, in response to olfactory stimuli using non-invasive wearable devices. The ANS activation was also studied with respect to the odor familiarity, as well as with other olfactory and food dimensions (e.g., odor identification, odor pleasantness, food neophobia). Results: We demonstrated a significant activation of the ANS, in particular of its sympathetic branch, during the olfactory stimulation, with the ECG signal seen as more sensitive to detect ANS response to moderate olfactory stimuli rather than the GSR. Conclusions: When applied to a greater number of subjects, or to specific groups of patients, this methodology could represent a promising, reliable addition to diagnostic methods currently used in clinical settings.
DO MATURE FIRMS HAVE MORE EARNINGS INFORMATIVENESS? EVIDENCE FROM TAIWAN

Previous studies have demonstrated that higher levels of individual trading are more subject to decision biases, thereby causing market mispricing and inefficiency. This study examines how the Taiwan stock exchange market, which is characteristic of higher levels of individual trading, prices earnings information across different life cycle stages. Our findings indicate that earnings persistence and value relevance are conditional on the life cycle. In addition, we examine the market valuation consequences of the life cycle stage, finding that positive future excess returns are earned for mature and shakeout firms. Our findings indicate that a profitable trading strategy is possible when the market does not fully recognize the fundamental life cycle information embodied in the financial statements in Taiwan.
A Spatially-Filtered Mixture of -Convergence Regressions for European Regions, 1980-2002

Assessing regional growth and convergence across Europe is a matter of primary relevance. Empirical models that not account for structural heterogeneities and spatial effects may face serious misspecification problems. In this work, a mixture regression approach is applied to the -convergence model, in order to produce an endogenous selection of regional growth patterns. A priori choices, as North-South or centre-periphery divisions, are avoided. In addition to this, we deal with the spatial dependence existing in the data, applying a local filter to the data. The results indicate that spatial effects matter, and either absolute, conditional, or club convergence, if extended to the whole sample, might be assumptions too much restrictive. Excluding a small number of regions that behave as outliers, only few regions show an appreciable rate of convergence. The majority of data exhibits slow convergence, or no convergence at all. In addition, a dualistic phenomenon seems to be present inside some States, reinforcing the “diverging-convergence” paradox.
UNIVERSITY OF ALGARVE FACULTY OF SOCIAL AND HUMAN SCIENCE THE UNIVERSITY OF WOLVERHAMPTON SCHOOL OF LAW, SOCIAL SCIENCES AND COMMUNICATIONS

Structural ambiguity resolution in natural language text is an active field of research. Ambiguity is where a structural element in a text causes the interpretation of the text in more than one way. Prepositional Phrases (PP) introduce significant amount of structural ambiguity since how a PP modifies another phrase can often be traced beyond the syntactic scope of a sentence. It is rather intuitive that semantic knowledge is important to model the phenomenon properly. Proper semantic interpretation though can be difficult to achieve. Moreover lexical and syntactic information based approaches has been proven to be quite effective. One such approach was dependency based resolution of PP attachment ambiguity. We propose a heuristic based modeling of data from two different parsers namely Constraint Grammar (CG) based parser PALAVRAS and Phrase Structure Grammar (PSG) based Finite-State Parser (FSP) used as the parsing backbone of the STRING Natural Language Processing (NLP) chain for Portuguese. Different models using two parser output will be produced and put together in a linear combination for performance maximization. For the development of the research, a processing framework is also proposed and its development is presented. A dependency annotation tool is also developed within the scope of the research. The models performance was satisfactory if not extraordinary, although the primary objective was to present the modeling possibilities rather than the absolute performance.
Non-Employment Activity Type Imputation from Points of Interest and Mobility Data at an Individual Level: How Accurate Can We Get?

Human activity type inference has long been the focus for applications ranging from managing transportation demand to monitoring changes in land use patterns. Today’s ever increasing volume of mobility data allow researchers to explore a wide range of methodological approaches for this task. Such data, however, lack reference observations that would allow the validation of methodological approaches. This research proposes a methodological framework for urban activity type inference using a Dirichlet multinomial dynamic Bayesian network with an empirical Bayes prior that can be applied to mobility data of low spatiotemporal resolution. The method was validated using open source Foursquare data under different isochrone configurations. The results provide evidence of the limits of activity detection accuracy using such data as determined by the Area Under Receiving Operating Curve (AUROC), log-loss, and accuracy metrics. At the same time, results demonstrate that a hierarchical modeling framework can provide some flexibility against the challenges related to the nature of unsupervised activity classification using trajectory variables and POIs as input.
hape variation of prey-catching structures in geophilomorph entipedes: A preliminary investigation using geometric orphometrics

Geophilomorph centipedes are common arthropod soil predators, but very little is known about their preying behaviour and their diet. Here we develop an exploratory morpho-functional approach to better understand their feeding habits, based on the morphology of feeding-related structures. Through geometric morphometrics, in a sample of five geophilomorph species, we investigated morphological variation in the three most conspicuous component structures of their prey-catching apparatus. At intra-specific level, we found no strong evidence for sexual dimorphism, left-right directional asymmetries and allometry across adult stages. At inter-specific level, shape differences in the feeding apparatus among the sample species were highly significant and large, even between two congeneric species. We also found irectional asymmetry eeding ecology orphological integration a significant covariation between the shapes of the three structures, including those that do not directly articulate with each other, suggesting some degree of morphological integration between the different structures of the prey-catching apparatus. This study suggests the effectiveness and power of geometric morphometrics for the quantitative study of centipede functional morphology and provides a basis for wider comparative investigations on their phenotypic evolution. © 2017 Elsevier GmbH. All rights reserved.
Effects of Tablet Devices on Reading to Support Discussion: Comparison of Conversation Processes involving Paper, a Tablet, a Laptop PC

Discussion processes involving the use of paper, tablet devices, and laptop PCs, were experimentally compared from the viewpoint of verbal interaction. In task discussions, 24 participants (12 groups of two people) were asked to plan a one-day sightseeing trip by using guidebooks presented on paper, an iPad2, or a laptop PC. According to the results of the tests, the frequency of essential conversations to attain the goal of the task was the highest when the participants used paper and not significantly different in the cases that iPads and PCs were used. Moreover, the frequency of asking redundant questions such as, “Which one are you talking about? ” due to not understanding a partner’s intent was higher when iPads and PCs were used than when paper was used. These results suggest that tablet devices should be used with caution in scenarios in which a topic needs to be thoroughly discussed in a short amount of time.
How likely are adaptive responses to mitigate the threats of climate change for amphibians globally?

Whether species are capable of adapting to rapid shifts in climate raises considerable interest. Analyses based on niche models often assume niche conservatism and equilibrium with climate, implying that species will persist only in regions where future climatic conditions match their current conditions and that they will colonize these regions promptly. However, species may adapt to changing climate and persist where future climates differ from their current optimum. Here, we provide a first macroecological generalization to the approach of evolutionary rescue, by comparing the expected shift in mean temperature within the geographic range of 7193 species of amphibians worldwide, under alternative warming scenarios. Expected evolutionary change is expressed in units of standard deviations of mean temperature, per generation (Haldanes) and compared with theoretical models defining the maximum sustainable evolutionary rates (MSER) for each species. For the pessimistic emission scenario RCP8.5, shifts in mean temperature vary between near-zero and 6°C within the geographic ranges for most species, with a median equal to 3.75°C. The probability of evolutionary rescue in temperature peaks is higher than 0.05 for about 55% of the species and higher than 0.95 for only 12% of the species. Therefore, the predicted shift in mean temperature would be too extreme to deal with for almost half of the species. When evolutionary plasticity is incorporated, this scenario becomes more optimistic, with about 44% of the species being likely to shift their thermal peaks tracking future warming. These figures are not random in geographical space: evolutionary rescue would be unlikely in the tropics, especially in South America (Amazonia), parts of Africa, Indonesia, and in the Mediterranean region. Given the uncertainty in demographic and genetic parameters for species’ responses to climate change, we caution that it remains difficult to assess the realism of the macroecological generalization. In any case, it may be precautionary to assume that our results are not liberal, showing low probability of adaptation for most of the species and thus that the persistence of populations by evolutionary rescue may, in general, be unlikely in the long term.
Are Incumbents Advantaged? Evidences from Brazilian Municipalities using a Quasi-Experimental Approach

This paper examines the incumbency effect on mayoral elections in Brazil since executive officers were allowed the possibility to be reelected for one consecutive term. By adapting the regression discontinuity design of close electoral races to a multi-party system, it shows whether incumbent mayors and parties were advantaged in comparison to their challengers. The causal effects of being in office are estimated with the use of a repeated interaction in between the incumbent and one or more candidates (parties) in consecutive elections. In contrast with the incumbency advantages that have been largely documented for elections in the United States, in Brazil there were significant negative incumbency effects for the elections of 2000 and 2004, indicating that, when there was a strong alternative political force, citizens preferred to penalize incumbents. This phenomenon ceased in the 2008 elections but was not reversed into significantly positive effects.
A Survey on Data Plane Flexibility and Programmability in Software-Defined Networking

Software-defined networking (SDN) has attracted the attention of the research community in recent years, as evidenced by a large number of survey and review papers. The architecture of SDN clearly recognizes three planes: application, control, and data planes. The application plane executes network applications, the control plane regulates the rules for the entire network based on the requests generated by network applications, and based on the set rules, the controller configures the switches in the data plane. The role of the switch in the data plane is to simply forward packets based on the instructions given by the controller. By analyzing the SDN-related research papers, it is observed that research, from the very beginning, is insufficiently focused on the data plane. Therefore, this paper gives a comprehensive overview of the data plane survey with a particular emphasis on the problem of programmability and flexibility. The first part of the survey is dedicated to the evaluation of actual data plane architectures through several definitions and aspects of data plane flexibility and programmability. Then, an overview of the SDN-related research was presented with the aim of identifying the key factors influencing the gradual deviation from the original data plane architectures given with ForCES and OpenFlow specifications. In this paper, we used the term data plane evolution for this deviation. By establishing a correlation between the treated problem and the problem-solving approaches, the limitations of ForCES and OpenFlow data plane architectures were identified. Based on the identified limitations, a generalization of approaches to addressing the problem of data plane flexibility and programmability has been made. By examining the generalized approaches, open issues have been identified, establishing the grounds for future research directions proposal.
A Theory for Multiresolution Signal Decomposition : The Wavelet Representation

Multiresolution representations are very effective for analyzing the information content of images. We study the properties of the operator which approximates a signal at a given resolution. We show that the difference of information between the approximation of a signal at the resolutions 2 + ’ and 2 can be extracted by decomposing this signal on a wavelet orthonormal basis of L z ( R n ) . In L z ( R ) , a wavelet orthonormal basis is a family of functions ( @ \v ( 2 /x n ) ) , J , n ) E z ~ , which is built by dilating and translating a unique function I + (x). This decomposition defines an orthogonal multiresolution representation called a wavelet representation. It is computed with a pyramidal algorithm based on convolutions with quadrature mirror filters. For images, the wavelet representation differentiates 5everal spatial orientations. We study the application of this representation to data compression in image coding, texture discrimination and fractal analysis.