Miracle-dz/UniFAR-FTUs huggingface dataset:
Biogeography-Based Optimization Algorithm for Automatic Extractive Text Summarization

Given the increasing number of documents, sites, online sources, and the users’ desire to quickly access information, automatic textual summarization has caught the attention of many researchers in this field. Researchers have presented different methods for text summarization as well as a useful summary of those texts including relevant document sentences. This study selects extractive method out of different summarizing methods (e.g. abstract method). Extractive method involves summarizing text through objective extraction of some parts of a text like word, sentence, and paragraph. A summarization issue would be unsolvable by exact methods in a reasonable time with considering documents with high amount of information (NP complete). These kinds of issues are usually solved using metaheuristic methods. A biogeography - based optimization algorithm (BBO), which is a new metaheuristic method in the domain of extractive text summarization is used in this article. This method is tested on a set of Doc’s standard documents in 2002 and is analyzed, using ROUGE software. The obtained results of these tests show that this kind of method can be used as an effective method for text summarization .
Study of fermion pair productions at the ILC with center-of-mass energy of 250 GeV

Precise measurements of electroweak processes at the International Linear Collider (ILC) will provide unique opportunities to explore new physics beyond the Standard Model. Fermion pair productions are sensitive to a new contact interaction or a new heavy gauge boson by comparing cross section and angular distribution with expectations of the new physics models. In this proceedings we report a simulation study of fermion pair productions at a center-of-mass energy of 250 GeV, with a focus on lepton pairs, to demonstrate the potential of the first phase of the ILC.
Collaborative trails in e-Learning environments

This deliverable focuses on collaboration within groups of learners, and hence collaborative trails. We begin by reviewing the theoretical background to collaborative learning and looking at the kinds of support that computers can give to groups of learners working collaboratively, and then look more deeply at some of the issues in designing environments to support collaborative learning trails and at tools and techniques, including collaborative filtering, that can be used for analysing collaborative trails. We then review the state-of-the-art in supporting collaborative learning in three different areas – experimental academic systems, systems using mobile technology (which are also generally academic), and commercially available systems. The final part of the deliverable presents three scenarios that show where technology that supports groups working collaboratively and producing collaborative trails may be heading in the near future.
A New Model for Intrusion Detection based on Reduced Error Pruning Technique

The increasing counterfeit of the internet usage has raised concerns of the security agencies to work very hard in order to diminish the presence of the abnormal users from the web. The motive of these illicit users (called intruders) is to harm the system or the network either by gaining access to the system or prohibiting genuine users to access the resources. Hence in order to tackle the abnormalities Intrusion Detection System (IDS) with Data Mining has evolved as the most demanding approach. On the one end IDS aims to detect the intrusions by monitoring a given environment while on the other end Data Mining allows mining of these intrusions hidden among genuine users. In this regard, IDS with Data Mining has been through several revisions in consideration to meet the current requirements with efficient detection of intrusions. Also several models have been proposed for enhancing the system performance. In context to improved performance, the paper presents a new model for intrusion detection. This improved model, named as REP (Reduced Error Pruning) based Intrusion Detection Model results in higher accuracy along with the increased number of correctly classified instances.
Multiresolution Wavelet Analysis of the Dynamics of a Cracked Rotor

We examine the dynamics of a healthy rotor and a rotor with a transverse crack, which opens and closes due to its self weight. Using discrete wavelet transform, we perform a multiresolution analysis of the measured vibration signal from each of these rotors. In particular, the measured vibration signal is decomposed into eight frequency bands, and the rms amplitude values of the healthy and cracked rotors are compared in the three lowest-frequency bands. The results indicate that the rms vibration amplitudes for the cracked rotor are larger than those of the healthy rotor in each of these three frequency bands. In the case of externally applied harmonic force excitation to the rotor, the rms values of the vibration amplitude of the cracked rotor are also found to be larger than those of a healthy rotor in the three lowest-frequency bands. Furthermore, the difference in the rms values between the healthy and cracked rotors in each of the three lowest-frequency bands is more pronounced in the presence of external excitation than that with no excitation. The obtained results suggest that the present multiresolution approach can be used effectively to detect the presence of a crack in a rotor.
GIS AND BIM INTEGRATION AT DATA LEVEL: A REVIEW

Abstract. City Geography Markup Language (CityGML) and Industry Foundation Class (IFC) are the two most popular data exchange format for the integration of Geographic Information System (GIS) and Building Information Modelling (BIM) respectively and has been identified by many researchers as an auspicious means of data interoperability between the two domains but with challenges on the compatibility between them. The main issue is the data loss in the process of information transformation. The success of integrating these two domains (GIS and BIM objects) is a great achievement toward solving problems in Architecture, Engineering and Construction (AEC), Facility Management (FM), Disaster Management (DM) sectors. Nevertheless, as we all know GIS and BIM are different fields used by different professionals using different software packages, used for different purposes, it is definitely face with many challenges including data interoperability, mismatch and loss of semantic information are bound to occur during the process of integration. In order to comprehend the two domains and their data models of CityGML and IFC. This paper review existing models on GIS and BIM developed by different researchers, the complementarity and compatibility of GIS and BIM on the previous integration techniques were also reviewed and finally, the paper review the integration of GIS and BIM at the data level aimed at solving different problems surrounding it by considering the transformation of coordinates at geometric level from CityGML to IFC, in order to achieve flow of information between GIS and BIM.
A Link Prediction Strategy for Personalized Tweet Recommendation through Doc2Vec Approach

Nowadays with growth of using Internet as a principle way of communication, likes different social medias channels (Twitter, Facebook, etc . ) and also access to huge amount of information like News, there appear a main research subject to help users to find his/her interests among vast amount of relevant and irrelevant information. Recommender systems are helped to handle information overload problem and in this paper we introduce our Tweet Recommendation System that implement user ’ s Twitter information (Tweets, Retweet, Like,.) as a source of user’s information. In this work the semantic of tweets that regard as a User’s Explicit Interests (e.g. , person, events, product mentioned in user’s tweets) are identified with the Doc2vec approach and recommend similar tweets through link-prediction strategy. The experiment results show that Doc2Vec approach is a better approach than the other previous approaches.
C allocation among fine roots, above-, and belowground wood in a deciduous forest and its implication to ecosystem C cycling: a modelling analysis

Abstract. Knowledge about allocation of carbohydrates among tree organs with different life times and decomposition rates is crucial in determining the residence time of carbon (C) in forests and the overall ecosystem C cycling rate. A new model (named CAF) able to simulate C allocation among fine roots, above-, and belowground wood in deciduous forests was developed and integrated into the net ecosystem exchange model FORUG. CAF draws on growth rules and source-sink relationships. Maintenance and growth of the modelled sinks i.e. fine roots, coarse roots, stems, and branches, are controlled by phenology, environment, and by the reserve of non-structural carbohydrates. CAF was parameterized for 2-y and tested against 6-y observations from a beech (Fagus sylvatica L.) stand in North-East France, experiencing summer droughts of different intensities. The model reproduced well (i) the C fluxes allocated annually to assimilation, respiration and biomass production, and (ii) the interannual pattern of wood biomass accumulation. Seasonality of C reserve and wood growth was captured, but some discrepancies were detected at the onset of the growing season. The allocation pattern differed among years, although the overall net primary production decreased only in case of severe drought. During a year with severe drought, the fraction of C allocated to production of fast-decomposing C pools (e.g. fine roots, C reserve) increased by +13% than years without drought, whereas the same fraction increased on average by +18% in case of low to moderate drought. Carbon invested in biomass during a year with summer drought has therefore a shorter residence time in the ecosystem than the C stored during a year without summer drought.
Descriptor sub-representations in semantic equalisation

In semantic equalisation, descriptions of audio transformations can be used to control low-level audio effect parameters. In this paper, we explore sub-representations of these descriptions in order to suggest more contextually relevant processing parameters to users, based on external influence. We propose a methodology for finding sub-representations, and an intuitive low-dimensional interface, which can be used to recommend equalisation curves based on proximity to cluster centroids.
Design of Photosynthetically Active Radiation Sensor

Humans tend to regard plants as passive organisms because of their immobility. But plants are very active and they respond to environment very well. The process called photosynthesis plays a vital role in growth of a plant. In photosynthesis process one of the major requirements would be Sunlight. The whole spectrum of sunlight is not used by plants it is just a part of a band which is in visible region (400nm-700nm). In the other words it is called as Photo synthetically Active Radiation (PAR).
Accounting for Similarity-Based Reasoning within a Cognitive Architecture

This work explores the importance of similarity-based processes in human everyday reasoning, beyond purely rule-based processes prevalent in AI and cognitive science. A unified framework encompassing both rulebased and similarity-based reasoning may provide explanations for a variety of human reasoning data. The paper implements this analysis in a cognitive architecture Clarion, which has previously succeeded in capturing a variety of human learning data in simulations. The exploration of similarity-based reasoning in this architecture leads to a more complete and more comprehensive framework of human reasoning and learning. The simulation within this architecture accurately captures human reasoning data, including numerical measures and verbal protocols. This work demonstrates the significant role played by similarity-based reasoning. Furthermore, it demonstrates how such a reasoning process falls out of the existing structure in the cognitive architecture Clarion.
Transcending the status quo: a communication perspective for improving health behaviors at Eastern Washington University

There is a belief known as the ‘college experience;’ an experience that some understand as a right of passage. This notion continues to be passed from generation to generation; what happens without our noticing is that the demands of that ‘college experience’ are changing. Survey results indicate that this ‘experience’ continues to perpetuate, that college students have skewed perceptions of vulnerabilities and are willing to take unhealthy risks, all as part of the ‘college experience. ’ Through a mixed methods approach, this research demonstrates that advances in remedial health education are positively affecting students ‘abilities’ to “gain access to, understand and use information in ways which promote and maintain good health” (World Health Organization, as cited in Nutbeam, 2000, p.264 and Ratzan, 2000, p. 210). This research also identifies the disparity between having the ‘ability’ and having the ‘motivation’ to mitigate risk. This research further substantiates an exigent need for a holistic approach to improving health literacy, and designing health messages for improving health behaviors at Eastern Washington University.
Modelling the Transition Towards the Renminbi's Full Convertibility: Implications for China's Growth

There is a widespread consensus that China’s growth paradigm needs a rebalancing away from investment and external demand and towards consumption and domestic demand. This rebalancing process is supposed to be accompanied by the transition towards Renminbi’s full convertibility. In contrast, it is controversial to what extent this adjustment will accelerate the slowdown of China’s growth, which will likely occur because of other structural factors. We address these issues by means of a two-country two-stage (before and after Renminbi’s full convertibility) model, which reproduces some qualitative features of China’s growth pattern and its relationship with the US. We analyze to what extent altering the Chinese exchange rate policy, as well as other structural and policy variables, may have (short-, medium- and long-term) effects on the evolution of the Chinese economy. The paper shows that by lifting the controls on the capital account and letting the currency float, the Chinese authorities will not only expose the economy to the risks of free capital mobility, but will also renounce to important policy instruments for controlling the dynamics of China’s economy and the allocation of the national resources.
Suppressing Resonant Vibrations Using Nonlinear Springs and Dampers

The transmitted force around the resonant region of a system can be significantly reduced by introducing designed nonlinearities into the system. The basic choice of the nonlinearity can be either a nonlinear spring element or a nonlinear damping element. A numerical algorithm to compute and compare the transmitted force reduction produced by these two types of designed elements is proposed in this study. Analytical results are used to demonstrate the procedure. The numerical results indicate that the designed nonlinear damping element produces low levels of higher-order harmonics and no bifurcations in the system output response. In contrast, the nonlinear spring-based designs induce significant levels of harmonics in the transmitted force and can produce bifurcation behaviour. The conclusions provide an important basis for the design of nonlinear materials and nonlinear engineering systems.
A Cost-Efficient Job Scheduling Algorithm in Cloud Resource Broker with Scalable VM Allocation Scheme

Cloud service users request dedicated virtual computing resource from the cloud service provider to process jobs in independent environment from other users. To optimize this process with automated method, in this paper we proposed a framework for workflow scheduling in the cloud environment, in which the core component is the middleware called broker mediating the interaction between users and cloud service providers. To process jobs in on-demand and virtualized resources from cloud service providers, many papers propose scheduling algorithms that allocate jobs to virtual machines which are dedicated to one machine one job. With this method, the isolation of being processed jobs is guaranteed, but we can`t use each resource to its fullest computing capacity with high efficiency in resource utilization. This paper therefore proposed a cost-efficient job scheduling algorithm which maximizes the utilization of managed resources with increasing the degree of multiprogramming to reduce the number of needed virtual machines; consequently we can save the cost for processing requests. We also consider the performance degradation in proposed scheme with thrashing and context switching. By evaluating the experimental results, we have shown that the proposed scheme has better cost-performance feature compared to an existing scheme.
EFFICIENT EXTRACTION OF EVOKED POTENTIALS FROM NOISY BACKGROUND EEG

The primary goal of this work is to introduce temporal artifact detection strategy to detect non responsive channels and trials in evoked potentials by tracing out the signals with very low energy and to remove artifacts in multichannel evoked potentials. The non responsive channels and trials are identified by calculating the energy of the average evoked potential of each channel, and the energy of the average evoked potential of each trial. Then channel wise and trial wise median test is conducted to detect and remove non-responsive channels and trials. An artifact is defined as any signal that may lead to inaccurate classifier parameter estimation. Temporal domain artifact detection tests include: a standard deviation (STD) test that can detect signals with little or abnormal variations in each channel, a clipping (CL) test detect amplitude clipped EPs in each channel and a kurtosis (KU) test to detect unusual signals that are not identified by STD and CL tests. An attempt has been made to apply these techniques to 14-channel visual evoked potentials (VEPs) obtained from different subjects.
Processing Capability of Maize Varieties Through Free Sorting and CATA Methodologies and Physicochemical Characteristics

Maize varieties have specific food processing abilities, with reference to the production of gambari-lifin , lifin , mawe and ogi , four major intermediate products in Benin. Except for the gambari-lifin , these products are widely known in the most of African countries. The recent development of gambari-lifin in relation with the maize grains quality suggests the screening of appropriate maize cultivars for minimizing failure during processing. Panelists comprising 77 maize food processors sorted fifteen maize varieties of which fourteen improved and one local ecotype, and then described each group with their own words. Additionally, 70 maize food processors performed the CATA (Check All That Apply) questions test with a list of sensory terms on the maize varieties. Furthermore, selected physicochemical and rheological parameters were determined on seven representative maize varieties. Multidimensional scaling (MDS) and hierarchical cluster analysis and multiple factorial analyses (MFA) were performed on sensory descriptors and instrumental data. Based on MDS, four groups of maize varieties were identified being specifically appropriate for one or more of these intermediate products. Grains size and weight, endosperm texture and in a lesser extent colour were the major group descriptors of maize varieties. Vitreous character or average size were positively correlated to processing yield as far as gambari-lifin is concerned while floury character was associated to “ability for pasting”. This study confirms that food processors perception is very helpful and useful tools for maize breeders since it early provides consistent information for the end-uses products.
Numerically reliable identification of complex systems

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New approach towards predicting local f0 movements using Linear Least Squares by SVD

Gegenstand der vorliegenden Arbeit ist die Anwendung von Linear Least Squares by SVD auf die Analyse der lokalen Akzentkonturen der Grundfrequenz (f0) des Walliserdeutschen. Ein zentraler Vorteil dieser Methode liegt darin, dass die Wichtigkeit der verschiedenen Varianten von kategorischen Variablen separat berechnet wird und zudem auch numerische Variablen verwendet werden können. Ausgehend von den walliserdeutschen Sprachdaten von Leemann (2012) im Rahmen des Fujisaki-Modell Ansatzes konnten Parameter errechnet werden, die 80% der Positionen von lokalen Akzenten in einem Testdatensatz korrekt voraussagen können (Peter, 2011). Dies ist insofern erstaunlich, als die Intonationsstrukturen des Walliserdeutschen landläufig als "unverständlich" (Ris, 1992), "exotisch" (Werlen und Matter, 2004) oder "hochgradig variabel" (Leemann, 2012) gelten.
Study of Swarm Behavior in Modeling and Simulation of Cluster Formation in Nanofluids

Modeling the multiagents cooperative systems inspired from biological self-organized systems in the context of swarm model has been under great considerations especially in the field of the cooperation of multi robots. These models are trying to optimize the behavior of artificial multiagent systems by introducing a consensus, which is a mathematical model between the agents as an intelligence property for each member of the swarm set. The application of this novel approach in the modeling of nonintelligent multi agents systems in the field of cohesion and cluster formation of nanoparticles in nanofluids has been investigated in this study. This goal can be obtained by applying the basic swarm model for agents that are more mechanistic by considering their physical properties such as their mass, diameter, as well as the physical properties of the flow. Clustering in nanofluids is one of the major issues in the study of its effects on heat transfer. Study of the cluster formation dynamics in nanofluids using the swarm model can be useful in controlling the size and formation time of the clusters as well as designing appropriate microchannels, which the nanoparticles are plunged into.