Miracle-dz/UniFAR-FTUs huggingface dataset:
Darwin Core: An Evolving Community-Developed Biodiversity Data Standard

Biodiversity data derive from myriad sources stored in various formats on many distinct hardware and software platforms. An essential step towards understanding global patterns of biodiversity is to provide a standardized view of these heterogeneous data sources to improve interoperability. Fundamental to this advance are definitions of common terms. This paper describes the evolution and development of Darwin Core, a data standard for publishing and integrating biodiversity information. We focus on the categories of terms that define the standard, differences between simple and relational Darwin Core, how the standard has been implemented, and the community processes that are essential for maintenance and growth of the standard. We present case-study extensions of the Darwin Core into new research communities, including metagenomics and genetic resources. We close by showing how Darwin Core records are integrated to create new knowledge products documenting species distributions and changes due to environmental perturbations.
A Probabilistic Approach to Tweets' Sentiment Classification

Prior to 2003, mankind generated a total of about 5 Exabyte's of contents. Now, we generate this amount of contents in about two days! The spread of generic (as Twitter, Facebook or Google+) or specialized (as Linked In or Viadeo) social networks allows sharing opinions on different aspects of life every day. Therefore this information is a rich source of data for opinion mining and sentiment analysis. This paper introduces a novel approach to the sentiment analysis based on the Weighted Word Pairs obtained by the use of the Latent Dirichlet Allocation (LDA) approach. The proposed methodology aims at identifying a word-based graphical model for depicting and mining a positive or negative attitude towards a topic. For the evaluation of the proposed approach a challenging scenario has been set: the real-time analysis of tweets. The experimental evaluation shows how the proposed approach is effective and satisfactory.
ASSESSING PUBLIC ATTITUDES AND BEHAVIOUR TOWARD TOURISM DEVELOPMENT IN BARBADOS : SOCIO-ECONOMIC AND ENVIRONMENTAL IMPLICATIONS

This research discusses the negative social, enviro nmental and economic impacts of tourism development in Barbados; describes the perceptions of residents and tourists to such; and measures their preferences for environmental manage ment changes using the island’s lone marine reserve, the Folkestone Marine Reserve, as a c e study. This research is underpinned by a number of policy and methodological objectives wh ich were formulated with a view to better inform social decision-making about environmental m anagement in the tourism industry in Barbados, and to better understand the factors asso ci ted with the successes or the pitfalls of tourism development. The research outcomes demonstr ated that environmental management within the context of tourism development in Barbad os requires the balancing of public needs with the environmental and economic consequences of development. As such, the results reinforced some of the theoretical and empirical re velations in the field of tourism and environmental management and further cemented the a ss rtion that environmental management becomes onerous because of the presence of a number of innately complex and interlinked inferences: that preserving an environment that sat isfies the divergent needs of users incurs both social and economic costs; that perceptions of tour ism’s impacts are not mutually exclusive, which makes the issue of support for tourism develo pment complex; that both the positive and negative impacts of tourism should be considered; t hat prudent environmental management is arguably the sine qua non for a viable tourism product; and that concerns re main as to whether the country can absorb the environmental and socioe onomic shocks associated with tourism.
An Approach to Position Sensorless Control System for Brushless DC Motor

This paper describes a control system of sensorless brushless DC(BLDC) motor.Firstly,the back-EMF is adopted to detect rotor position. Secondly,the back-EMF is very small in the motor starting process,and it is difficult to obtain rotor position efficiently. A re-setting method of the rotor is proposed in the paper,and current closed loop is used for high-speed and safety in the motor starting process.Finally,a good speed and current double closed loops system is designed.The current commutation and motor speed withdraw problem without the position sensor is discussed in details.The experimental results have shown the validity of the sensorless control system and the accuracy of the detective position signal obtained from a prototype BLDC motor of 400 W rating.
The Role of Semantics in Automatic Summarization : A Feasibility Study

State-of-the-art methods in automatic summarization rely almost exclusively on extracting salient sentences from input texts. Such extractive methods succeed in producing summaries which capture salient information but fail to produce fluent and coherent summaries. Recent progress in robust semantic analysis makes the application of semantic techniques to summarization relevant. We review in this paper areas in the field of summarization that can benefit from the introduction of the type of semantic analysis that has become available. The main pain points that semantic information can alleviate are: aiming for more fluent summaries by exploiting logical form representation of the source text; identifying salient information and avoiding redundancy by relying on textual entailment and paraphrase identification; and generating a coherent summary while relying on rhetorical structure and discourse structure information extracted from the source documents. In addition, we review the possibility to perform automatic Pyramid evaluation of summarization quality that relies on robust semantic similarity measures.
A pulse model neuron with high accurate calculation and its application to two-dimensional binary classification

In order to scale down circuit size for the hardware realization of neural network systems, there has been much research on the conventional pulse model neuron, in which a conventional numerical calculation is replaced by a stochastic calculation. In the conventional stochastic calculation, a linear feedback shift register (LFSR) has been used as a random number generator. In general, a good randomness is required for an exact calculation result. However, since random numbers generated by LFSR are lacking in randomness, there is a problem which affects the accuracy of the conventional stochastic calculation which uses LFSR to generate random numbers. In order to improve the accuracy of the conventional calculation, we propose to use GLFSR (generalized LFSR) which generates random numbers which are rich in randomness. The accuracy of the stochastic calculation is evaluated using a root-mean-square error (RMS) and a maximum error. As a result, the proposed stochastic calculation, which uses GLFSR as the random number generator, shows a highly accurate calculation result. Moreover, when it is applied to a neural network to solve a two-dimensional binary classification problem, the network shows better classification results than those of the neural network which uses the conventional stochastic calculation.
Analysing Growth in FacesR

We examine the changes in the proole of the human face with age. First the medial plane running down the middle of the face is found using a variant of the Iterative Closest Point Algorithm, optimis-ing over the set of reeections. The boundary of the silhouette as viewed from the side is extracted. Landmarks are found using bi-tangent lines and extremals of distance. A representation of size and shape is found using Procrustes Analysis. Principal Component Analysis is used to examine how size and shape varies with growth. Promising early results are presented.
Bootstrapping for hierarchical document classification

Managing the hierarchical organization of data is starting to play a key role in the knowledge management community due to the great amount of human resources needed to create and maintain these organized repositories of information. Machine learning community has in part addressed this problem by developing hierarchical supervised classifiers that help maintainers to categorize new resources within given hierarchies. Although such learning models succeed in exploiting relational knowledge, they are highly demanding in terms of labeled examples, because the number of categories is related to the dimension of the corresponding hierarchy. Hence, the creation of new directories or the modification of existing ones require strong investments.This paper proposes a semi-automatic process (interleaved with human suggestions) whose aim is to minimize (simplify) the work required to the administrators when creating, modifying, and maintaining directories. Within this process, bootstrapping a taxonomy with examples represents a critical factor for the effective exploitation of any supervised learning model. For this reason we propose a method for the bootstrapping process that makes a first hypothesis of categorization for a set of unlabeled documents, with respect to a given empty hierarchy of concepts. Based on a revision of Self-Organizing Maps, namely TaxSOM, the proposed model performs an unsupervised classification, exploiting the a-priori knowledge encoded in a taxonomy structure both at the terminological and topological level. The ultimate goal of TaxSOM is to create the premise for successfully training a supervised classifier.
A multimedia recommender system based on enriched user profiles

In this paper, we propose a multimedia recommender system which is based on user profiles enriched with peer-level annotations. Our annotation-based filtering algorithm is able to reduce the effects of two well-known problems inherent to recommender systems: the new user problem and over-specialization. In the first case, we propose a mechanism to enrich new user profiles with concepts gathered from folksonomies. In the second, our system uses genres and/or categories associated to each item in order to accomplish better recommendations. We present the results comparing our approach with other systems previously reported on literature.
Comparative analysis between 3D-TLM Nodes in the frequency domain

This paper presents a comparative analysis of the numerical dispersion of 3D FD-TLM (Frequency Domain Transmission Line Matrix) nodes. Three principal nodes are considered for this analysis: The Symmetrical Condensed Node (SCN), The Hybrid Symmetrical Condensed Node (HSCN) and the Super Symmetrical Condensed Node (SSCN). Numerical results are obtained for a rectangular waveguide with dielectric discontinuity. Both cubic and parallelepiped meshes were used to model the structure. It has been found that characteristics of those nodes depend on the cell aspect ratio and their performances seem to confirm those found with TD-TLM (Time Domain Transmission Line Matrix).
SPIRIT 2013 explanation and elaboration: guidance for protocols of clinical trials

High quality protocols facilitate proper conduct, reporting, and external review of clinical trials. However, the completeness of trial protocols is often inadequate. To help improve the content and quality of protocols, an international group of stakeholders developed the SPIRIT 2013 Statement (Standard Protocol Items: Recommendations for Interventional Trials). The SPIRIT Statement provides guidance in the form of a checklist of recommended items to include in a clinical trial protocol. This SPIRIT 2013 Explanation and Elaboration paper provides important information to promote full understanding of the checklist recommendations. For each checklist item, we provide a rationale and detailed description; a model example from an actual protocol; and relevant references supporting its importance. We strongly recommend that this explanatory paper be used in conjunction with the SPIRIT Statement. A website of resources is also available (www.spirit-statement.org). The SPIRIT 2013 Explanation and Elaboration paper, together with the Statement, should help with the drafting of trial protocols. Complete documentation of key trial elements can facilitate transparency and protocol review for the benefit of all stakeholders.
PHENOLIC AND SUGAR COMPOSITIONS OF SOME Hieracium L. (ASTERACEAE) LEAVES IN NORTH EAST ANATOLIA

Summary: In this study, the contents of total phenolic substances, hexose and pentose, glucose and reducing sugar in leaves of four endemic species of Hieracium (H. hypopityforme, H. karogoellense, H. microtum and H. gentiliforme) were analysed. The highest content of total phenols was quantified in the leaves of H. karogoellense (31.78 mg/g DW) while the highest contents of pentoses, hexoses and glucose were found in the leaves of H. microtum. Reducing sugar levels in the leaves of H. hypopifyforme, and H. gentiliforme were richer than those of H. karogoellense and H. microtum. The results showed that leaves of the Hieracium species were very rich in phenolic substances and sugars.
Mining Streaming Emerging Patterns from Streaming Data

Mining streaming data is an essential task in many applications such as network intrusion, marketing, manufacturing and others. The main challenge in the streaming data model is its unbounded size. This makes it difficult to run traditional mining techniques on this model. In this paper, we propose a new approach for mining emerging patterns (EPs) in data streams. Our method is based on mining EPs in a selective manner. EPs are those itemsets whose frequencies in one class are significantly higher than their frequencies in the other classes. Our experimental evaluation proves that our approach is capable of gaining important knowledge from data streams.
A correlation study applied to biomarkers of internal and effective dose for acrylonitrile and 4-aminobiphenyl in smokers

Abstract The urinary metabolites 2-cyanoethylmercapturic acid and 4-aminobiphenyl have been correlated with tobacco smoke exposure. Similarly, 2-cyanoethylvaline and 4-aminobiphenyl haemoglobin adducts have been used as biomarkers of effective dose for the exposure to acrylonitrile and 4-aminobiphenyl, respectively. Each pair of biomarkers is derived from the same parent chemical; however, the correlation between the urinary and the haemoglobin biomarkers has not been investigated. Using clinical study samples, we report a weak correlation between urinary and haemoglobin biomarkers due to different accumulation and elimination rates. Time course analysis showed that a reduction in exposure was paralleled by a delayed reduction in haemoglobin adducts.
The Spammed Code Offset Method

Helper data schemes are a security primitive used for privacy-preserving biometric databases and physical unclonable functions. One of the oldest known helper data schemes is the code offset method (COM). We propose an extension of the COM: the helper data are accompanied by many instances of fake helper data that are drawn from the same distribution as the real one. While the adversary has no way to distinguish between them, the legitimate party has more information and can see the difference. We use a low-density parity check code in order to improve the efficiency of the legitimate party's selection procedure. Our construction provides a new kind of tradeoff: more effective use of the source entropy, at the price of increased helper data storage. We give a security analysis in terms of Shannon entropy and order-2 Rényi entropy. We also propose a variant of our scheme in which the helper data list is not stored but pseudorandomly generated, changing the tradeoff to source entropy utilization versus computation effort.
LIMSI: Translations as Source of Indirect Supervision for Multilingual All-Words Sense Disambiguation and Entity Linking

We present the LIMSI submission to the Multilingual Word Sense Disambiguation and Entity Linking task of SemEval-2015. The system exploits the parallelism of the multilingual test data and uses translations as source of indirect supervision for sense selection. The LIMSI system gets best results in English in all domains and shows that alignment information can successfully guide disambiguation. This simple but effective method can serve to generate high quality sense annotated data for WSD system training.
Placement Algorithm for FPGA Circuits

Field-Programmable Gate Arrays (FPGAs) are flexible and reusable circuits that can be easily reconfigured by the designer. One of the steps involved in the logic design with FPGA circuits is placement. In this step, the logic functions are assigned to specific cells of the circuit. In this paper we present a placement algorithm for FPGA circuits. In traditional min-cut based placement algorithms, the only metric in the cost function is the cut size. The proposed algorithm not only reduces the cut size and balances the size of the two portions, but also evenly distributes the connections among them. We also propose another sequence of slicing lines which reduces the maximum cut size and the total wirelength of the circuit.
Compliance testing for wrapper-based API migration

Wrapping is an established technique for API migration: the use of a given API within the system under migration is replaced by the use of a wrapper-based re-implementation of said API while using a different (preferred) API underneath. Except for some special cases, wrapper development is a craft. In particular, the compliance of a wrapper with the original API is hard to assess and guidance of wrapper development is very limited. In this paper, we describe a method for wrapper development that is essentially inspired by notions of scenario-based differential testing, API contracts as well as selective capture and replay of program executions. The method supports compliance testing of the wrapper under development against the original API; it guides the developer in improving compliance incrementally; it also allows for precise capture of unresolved differences between original API and wrapper. The method is evaluated by a study of wrapper development with different wrappers in the domains of XML processing, byte-code engineering, and GUI
Mental Fatigue after Very Severe Closed Head Injury: Sustained Performance, Mental Effort and Distress at Two Levels of Workload in a Driving Simulator

In patients with very severe closed head injury (CHI), returning to work is often problematic. The present study focuses on a persistent complaint of these patients, viz. mental fatigue. To study this, the effect of sustained workload is assessed in a continuous dynamic divided attention task. Three types of measures are employed: performance loss with time-on-task, and subjective reports and cardiovascular measures of mental effort and distress. Eight very severe CHI patients (mean post-traumatic amnesia duration 51 days, mean age 23 years, (SD 6.4) and eight hospital controls (mean age 29 years, (SD 5.9) were tested. No differences were found between the patients and controls in the effects of task load on performance and the amount of mental effort, even in very demanding simulated work conditions. This parallels previous findings in less demanding laboratory tasks of sustained attention. Effects of CHI were found on both subjective and physiological indicators of distress. Compared to the controls, patients showed stronger effects on systolic blood pressure and subjectively experienced load.
Apples, oranges and hosting providers: Heterogeneity and security in the hosting market

Hosting services are associated with various security threats, yet the market has barely been studied empirically. Most security research has relied on routing data and equates providers with Autonomous Systems, ignoring the complexity and heterogeneity of the market. To overcome these limitations, we combined passive DNS data with WHOIS data to identify providers and some of their properties. We found 45,434 hosting providers, spread around a median address space size of 1,517 IP addresses. There is surprisingly little consolidation in the market, even though its services seem amenable to economies of scale. We applied cluster analysis on several measurable characteristics of providers. This uncovered a diverse set of business profiles and an indication of what fraction of the market fits each profile. The profiles are associated with significant differences in security performance, as measured by the uptime of phishing sites. This suggests the approach provides an effective way for security researchers to take the heterogeneity of the market into account.
Reconnection of non-abelian cosmic strings

Cosmic strings in non-abelian gauge theories naturally gain a spectrum of massless, or light, excitations arising from their embedding in colour and flavour space. This opens up the possibility that colliding strings miss each other in the internal space, reducing the probability of reconnection. We study the topology of the non-abelian vortex moduli space to determine the outcome of string collision. Surprisingly we find that the probability of classical reconnection in this system remains unity, with strings passing through each other only for finely tuned initial conditions. We proceed to show how this conclusion can be changed by symmetry breaking effects, or by quantum effects associated to fermionic zero modes, and present examples where the probability of reconnection in a U(N) gauge theory ranges from 1/N for low-energy collisions to one at higher energies.
Discovery of user frequent access patterns on Web usage mining

This paper proposes a method that can discover users' frequent access patterns underlying users' browsing Web behaviors. Firstly, the paper introduces the concept of access pattern according to a user's access path, and secondly puts forward a revised algorithm (FAP-Mining) based on the FP-tree algorithm to mine frequent access patterns. The new algorithm first constructs a frequent access pattern tree and then mines users' frequent access patterns on the tree. The algorithm is accurate and scalable for mining frequent access patterns with different lengths.