Miracle-dz/UniFAR-FTUs huggingface dataset:
The impact of resource title on tags in collaborative tagging systems

Collaborative tagging systems are popular tools for organization, sharing and retrieval of web resources. Their success is due to their freedom and simplicity of use. To post a resource, the user should only define a set of tags that would position the resource in the system's data structure -- folksonomy. This data structure can serve as a rich source of information about relations between tags and concepts they represent. To make use of information collaboratively added to folksonomies, we need to understand how users make tagging decisions. Three factors that are believed to influence user tagging decisions are: the tags used by other users, the organization of user's personal repository and the knowledge model shared between users. In our work we examine the role of another potential factor -- resource title. Despite all the advantages of tags, tagging is a tedious process. To minimize the effort, users are likely to tag with keywords that are easily available. We show that resource title, as a source of useful tags, is easy to access and comprehend. Given a choice of two tags with the same meaning, users are likely to be influenced by their presence in the title. However, a factor that seems to have stronger impact on users' tagging decisions is maintaining the consistency of the personal profile of tags. The results of our study reveal a new, less idealistic picture of collaborative tagging systems, in which the collaborative aspect seems to be less important than personal gains and convenience.
An application framework for evaluating methods in biometrics systems

In recent years, research in biometrics is focused on the development of new methods/algorithms to improve the accuracy of existing biometrics systems. Researchers are often required to do comparisons of their new methods/algorithms with existing/similar methods/algorithms and to make evaluations to show the performance of their biometrics systems. Currently, a universal environment in which researchers can compare and evaluate openly and objectively their biometrics methods/algorithms is rare since researchers tend to focus more on the biometrics methods/algorithms instead of providing such environment for other researchers. This paper presents Biometrika Framework: an application framework that can be used to evaluate various biometrics methods/algorithms. It is found that biometrics systems share a common topology consisting of: capturing, preprocessing, feature extraction, post-processing, matching and a data storage modules. A generic architecture of the framework is described in this paper. The framework has been tested and used to implement and evaluate two biometrics systems on fingerprint and palm-print data.
BGP is high on SDN : Improving BGP Convergence and Security using SDN and reassertions

Border Gateway Protocol (BGP) is the de facto protocol for inter-domain routing in the Internet. BGP performance has historically been accepted but rapidly evolving internet demands better performance guarantees from BGP. BGP convergence time is notorious for its unpredictable and unbounded limits. We present a novel way where we dissipate BGP state change messages from multiple Autonomous Systems (ASes). This results in multiplication of BGP propagation effort. We used OpenFlow capable routers distributed across the internet to optimally automate this process. Our approach also helps to mitigate IP prefix hijack and Multiple Origion Autonomous System (MOAS) conflicts (quantify). We used Oregon RouteViews in our simulations. Experimental results showed that this scheme can significantly increase BGP propagation (quantify) and alleviate BGP security issues (quantify). It is applicable to most of the internet. Our approach is also endorsed by mathematical models.
The Research of MapReduce Load Balancing Based on Multiple Partition Algorithm

In this paper, we propose a strategy to solve the load imbalance problem at MapReduce stage that caused from using the default partition algorithm of Hadoop platform. Through using multiple partitioning technique, this proposed strategy can refine the tasks and balance the inputs of reduce stage in the map phase. Furthermore, this proposed strategy can fully employ idle nodes to balance the high load nodes, in order to achieve the optimized job scheduling during the execution process of reduce stage.
Arabic Text Recognition in Video Sequences

In this paper, we propose a robust approach for text extraction and recognition from Arabic news video sequence. The text included in video sequences is an important needful for indexing and searching system. However, this text is difficult to detect and recognize because of the variability of its size, their low resolution characters and the complexity of the backgrounds. To solve these problems, we propose a system performing in two main tasks: extraction and recognition of text. Our system is tested on a varied database composed of different Arabic news programs and the obtained results are encouraging and show the merits of our approach.
Citrus/Cydonia Compositum Subcutaneous Injections versus Nasal Spray for Seasonal Allergic Rhinitis: A Randomized Controlled Trial on Efficacy and Safety

Background. Clinical experiences in vitro and clinical studies have demonstrated the curative potency and safety of Citrus/Cydonia compositum in seasonal allergic rhinitis treatment. Objectives. To compare the efficacy and safety of two routes of administration (nasal spray versus subcutaneous injections). Methodology: Design. a national, randomised, comparative clinical trial with two parallel groups. Participants. 23 patients fulfilled the study requirements. Intervention. after a one- or two-week wash-out period, 23 patients were randomized, to a 6-week treatment period. Outcomes. immunological and symptom severity changes and safety. Immunologic outcome assessments were blinded to group assignment. 23 patients were randomized and from 22/23 patients (11 in each group) blood samples were analyzed before and after treatment. Conclusion. Both routes of administration demonstrate immunological and clinical effects, with larger inflammatory and innate immunological effects of the nasal spray route and larger allergen-specific clinical effects of the subcutaneous route, and are safe.
Signal Transduction Protein PII Is Required for NtcA-Regulated Gene Expression during Nitrogen Deprivation in the Cyanobacterium Synechococcus elongatus Strain PCC 7942

ABSTRACT The transcription factor of the cyclic AMP receptor protein/FNR family, NtcA, and the PII signaling protein play central roles in global nitrogen control in cyanobacteria. A dependence on PII for NtcA-regulated transcription, however, has not been observed. In the present investigation, we examined alterations in gene expression following nitrogen deprivation in Synechococcus elongatus strain PCC 7942 and specifically the roles of NtcA and PII. Global changes in de novo protein synthesis following combined-nitrogen deprivation were visualized by in vivo [35S]methionine labeling and two-dimensional polyacrylamide gel electrophoresis analysis. Nearly all proteins whose synthesis responded specifically to combined-nitrogen deprivation in wild-type cells of S. elongatus failed to respond in PII- and NtcA-deficient mutants. One of the proteins whose synthesis was down-regulated in a PII- and NtcA-dependent manner was RbcS, the small subunit of RubisCO. Quantification of its mRNA revealed that the abundance of the rbcLS transcript following combined-nitrogen deprivation rapidly declined in wild-type cells but not in PII and NtcA mutant cells. To investigate further the relationship between PII and NtcA, fusions of the promotorless luxAB reporter genes to the NtcA-regulated glnB gene were constructed and these constructs were used to transform wild-type cells and PII− and NtcA− mutants. Determination of bioluminescence under different growth conditions showed that NtcA represses gene expression in the presence of ammonium in a PII-independent manner. By contrast, NtcA-dependent activation of glnB expression following combined-nitrogen deprivation was impaired in the absence of PII. Together, these results suggest that under conditions of combined-nitrogen deprivation, the regulation of NtcA-dependent gene expression requires the PII signal transduction protein.
Cognitive coherence relations and hypertext: from cinematic patterns to scholarly discourse

In previous work we argued that cinematic language may provide insights into the construction of narrative coherence in hypertext, and we identified in the shot juxtaposition of rhetorical patterns the source of coherence for cinematic discourse. Here we deepen our analysis, to show how the mechanisms that underpin cinematic rhetorical patterns are the same as those providing coherence in written text. We draw on computational and psycholinguistic analyses of texts which have derived a set of relationships that are termed Cognitive Coherence Relations (CCR). We validate this by re-expressing established cinematic patterns, and relations relevant to scholarly hypertext, in terms of CCR, and with this conceptual bridge in place, present examples to show how cinematic techniques could assist the presentation of scholarly discourse. This theoretical work also informs system design. We describe how an abstract relational layer based on CCR is being implemented as a semantic hypertext system to mediate scholarly discourse.
Soft-input soft-output lattice sphere decoder for linear channels

Soft output detection for signals transmitted on linear channels is investigated. A particular emphasis is made for signal detection on multiple antenna channels. The a posteriori information at the detector output is evaluated from a shifted spherical list of point candidates. The spherical list is centered on the maximum likelihood point, which has the great advantage of stabilizing the list size. Thus, the sphere radius is selected in order to control the list size and to cope with the boundaries of the finite multiple antenna constellation. Our new soft output sphere decoder is then applied to the computation of constrained channel capacity and to the iterative detection of a coded transmission. For example, we achieved a signal-to-noise ratio at 1.25 dB from capacity limit on a 4/spl times/4 MIMO channel with 16-QAM modulation and a 4-state rate 1/2 parallel turbo code.
The Important Dimensions for Assessing Organizations' Readiness toward Business Intelligence Systems from the Perspective of Malaysian Organization

Nowadays, Business Intelligence (BI) is becoming as a necessity for a lot of organizations. Figures show that billions of US dollars are spent on BI systems annually. Unfortunately, according to statistics, more than half of BI projects are ending with unrealized benefit. Many researchers tried to investigate the reasons behind this failure rate, they found one the main reasons is that many organizations are not yet ready for such systems. Therefore, it is highly encouraged to assess organization's readiness toward BI systems to avoid any losses and to enhance the overall revenue. At the same time, it was noticed that although many studies have been done, but none of them were done empirically on Malaysian context. So, an initiative has been taken, by the authors, to develop a model for assessing organization's readiness toward BI systems, based on the context of Malaysian Organizations (CMOs). This paper will uncover some results of the first round survey of this study. A brief introduction on BI systems and the challenges of their implementation will be presented. In addition, a review and analysis of models for assessing organizations' readiness toward BI systems is provided.
Essais sur la psychologie économique du comportement d’évasion fiscale

Le premier Chapitre utilise les acquis de la psychologie differentielle et de la psychometrie pour correler le comportement d’evasion fiscale observe dans le laboratoire aux traits de personnalite individuels, mesure grâce a des questionnaires psychometriques standardises. Ces questionnaires de personnalite sont lies aux emotions morales, aux jugements moraux et a la soumission a la norme. Les resultats montrent d’abord que les questionnaires mesurant les emotions morales expliquent mieux les comportements d’evasion que les autres questionnaires. Ensuite, le pouvoir explicatif de ces traits de personnalite reste tres modeste. Cette absence de relation forte met donc l’accent sur l’importance du contexte institutionnel dans lequel la soumission fiscale est mesuree. Les deuxieme et troisieme Chapitres tentent de mieux prendre en compte ce contexte institutionnel, en utilisant la psychologie sociale de l’engagement. Le second Chapitre montre que la modification de l’environnement du contribuable, a travers l’exposition a un serment a dire la verite, accroit le niveau d’honnetete des declarations fiscales qui lui font suite. Le troisieme Chapitre tente d’expliquer la cause du phenomene suivant : la democratie directe, comme presente dans certains cantons en Suisse, serait la source d’une plus grande soumission fiscale. D’apres la litterature existante, sa cause pourrait etre soit une coordination sociale entre les agents, soit un effet d’engagement du vote en lui-meme. Les resultats montrent que la coordination sociale entre les contribuables ne permet pas d’expliquer ce phenomene, qui reflate plutot un effet d’engagement de la participation au processus electoral.
Combining Morphological Feature Extraction and Geometric Hashing for Three-Dimensional Object Recognition Using Range Images

This paper presents a new approach for model-based object recognition with range images by combining morphological feature extraction and geometric hashing. In low-level processing, range images are segmented into 3D-connected surface patches. In middle-level processing, each connected component is processed by using morpho- logical operations to extract the skeletons of high-variation regions. These skeleton points can be viewed as invariant salient feature primitives. In high-level processing, geometric hashing is used to recognize objects. We also use a basis-similarity con- straint to reduce the number of spurious hypotheses. Experimental results have shown that the proposed method is effective and has great potential for model-based object recognition using range images.
Xaao: A Novel Approach To Reify "Community Linked" and Enable Data Self - Governance

In this paper we present a novel and noble approach to revitalize the sense of community that began to diminish due to our modern and fast pace life style. In order for any community to flourish, members have to collaborate and work together. Innovative and cutting edge technologies should be used to benefit and not harm our personal lives, families and the society we live in. Community Linked is a framework that relies on cutting edge technologies and our innovative solution to embrace the community spirit and help achieve its goals. In this paper, we review the different link patterns in the World Wide Web. Then, we provide a partial list of user stories to prescribe the desired functionalities of the system. Next, we present a thorough literature review on the related key areas of the framework and finally present the framework including our innovative XaaO (everything as an object) annotation that we used in Community Linked framework.
Trypanosoma cruzi GP63 Proteins Undergo Stage-Specific Differential Posttranslational Modification and Are Important for Host Cell Infection

ABSTRACT The protozoan Trypanosoma cruzi expresses multiple isoforms of the GP63 family of metalloproteases. Polyclonal antiserum against recombinant GP63 of T. cruzi (TcGP63) was used to study TcGP63 expression and localization in this organism. Western blot analysis revealed that TcGP63 is 61 kDa in epimastigotes, amastigotes, and tissue culture-derived trypomastigotes but 55 kDa in metacyclic trypomastigotes. Antiserum specific for Leishmania amazonensis GP63 specifically reacted with a 55-kDa TcGP63 form in metacyclic trypomastigotes, suggesting stage-specific expression of different isoforms. Surface biotinylation and endoglycosidase digestion experiments showed that TcGP63 is an ecto-glycoprotein in epimastigotes but is intracellular and lacking in N-linked glycans in metacyclic trypomastigotes. Immunofluorescence microscopy showed that TcGP63 is localized on the surfaces of epimastigotes but distributed intracellularly in metacyclic trypomastigotes. TcGP63 is soluble in cold Triton X-100, in contrast to Leishmania GP63, which is detergent resistant in this medium, suggesting that GP63 is not raft associated in T. cruzi. Western blot comparison of our antiserum to a previously described anti-peptide TcGP63 antiserum indicates that each antiserum recognizes distinct TcGP63 proteins. Preincubation of trypomastigotes with either TcGP63 antiserum or a purified TcGP63 C-terminal subfragment reduced infection of host myoblasts. These results show that TcGP63 is expressed at all life stages and that individual isoforms play a role in host cell infection.
Automatic 3D facial expression recognition based on polytypic Local Binary Pattern

Most of the existing methods adopted in 3D facial expression recognition require manual-intervention, which should be avoided in automatic systems. In this paper, we propose an automatic data normalization method based on the point-to-point mapping between the depth value and the texture information of the facial data. Based on this, we further construct a new kind of 3D facial expression feature, namely polytypic Local Binary Patterns (p-LBP), which involves both the irregular divisions to keep the integrity of local faces and the fusion of depth and texture information of 3D models to enhance the recognition accuracy. The proposed strategy is tested on BU-3DFE database, and three kinds of classifiers are employed. Their remarkable results outperform the state of the art, and show the effectiveness of proposed features for 3D facial expression recognition. Therefore, p-LBP is validated and its simplicity opens a promising direction for automatic 3D facial expression recognition.
Robust stability test for uncertain discrete-time systems: a descriptor system approach

This paper presents a new and less conservative condition for the robust sta- bility test of discrete-time polytopic systems by using a descriptor system approach. The sta- bility condition is formulated in terms of a set of linear matrix inequalities and can be easily adapted for robust controller synthesis. The developed results can be viewed as a discrete- time counterpart of the continuous-time one proposed by Cao and Lin (2004). This also en- ables us to ofier a unifled framework, namely the so-called descriptor system approach, for the analysis and synthesis of both discrete-time and continuous-time uncertain linear systems. Simulation examples are given to illustrate the theoretical results we established.
Longitudinal Analysis of Low-Level Web Interaction through Micro Behaviours

To truly understand how people learn to navigate and use a Web site or application, we need to collect real usage data over extended periods of time. Detailed Web interaction data gathered in the wild (from URLs visited, to keystrokes and mouse movements) has the potential to provide an in-depth, ecologically valid view of interaction, and enable an understanding of how behaviour evolves over time. Interpreting such data is extremely challenging, however. We present a longitudinal data-driven analysis of fine-grained interaction data captured from 14,000 recurrent users over 12 months. At the core of our approach is the aggregation of low-level interaction data into micro behaviours. By analysing changes in these behaviours as a function of users' accumulated interaction time, we were able to demonstrate how users' interaction evolves as they become more familiar with a Web page. The results demonstrate that monitoring micro behaviours offers a simple and easily extensible post hoc means of understanding how Web-based behaviour evolves over time.
Case study: bringing social intelligence into home dialogue systems

new technology does not always have to increase a sense of something “standing in between” two parties in a relationship. Next Steps. Media Lab Europe, which was established in 2000 and housed ten research groups at its height, closed its doors in January 2005 due to unfortunate political circumstances stemming from a lack of an agreement between its stakeholders on how its activities would be funded and managed going forward . Nevertheless, the vision of the Human Connectedness group is still alive and some of the projects discussed above are moving forward on independent tracks of commercialization or further research.
RsmA Regulates Aspergillus fumigatus Gliotoxin Cluster Metabolites Including Cyclo(L-Phe-L-Ser), a Potential New Diagnostic Marker for Invasive Aspergillosis

Dimeric basic leucine zipper (bZIP) proteins are conserved transcriptional enhancers found in all eukaryotes. A recently reported and novel function for bZIPs is association of these proteins with secondary metabolite production in filamentous fungi. In particular a Yap-like bZIP termed RsmA (restorer of secondary metabolism A) was identified in Aspergillus nidulans that positively regulates the carcinogen sterigmatocystin. To assess for conserved function for RsmA, we examined a role of this protein in secondary metabolism in the pathogen A. fumigatus. RsmA was found to positively regulate gliotoxin where overexpression (OE) of rsmA led to 2–100 fold increases of twelve gli cluster metabolites in culture medium including the newly identified gli metabolite cyclo(L-Phe-L-Ser). Lungs from both wild type and OErsmA infected mice contained gliotoxin (2.3 fold higher in OErsmA treatment) as well as the gliotoxin precursor cyclo(L-Phe-L-Ser) (3.2 fold higher in OErsmA treatment). The data here presents a conserved role for RsmA in secondary metabolite cluster activation and suggests cyclo(L-Phe-L-Ser) may serve as an alternative marker for diagnosis of invasive aspergillosis.
Enhancing Speech Recognition Using Improved Particle Swarm Optimization Based Hidden Markov Model

Enhancing speech recognition is the primary intention of this work. In this paper a novel speech recognition method based on vector quantization and improved particle swarm optimization (IPSO) is suggested. The suggested methodology contains four stages, namely, (i) denoising, (ii) feature mining (iii), vector quantization, and (iv) IPSO based hidden Markov model (HMM) technique (IP-HMM). At first, the speech signals are denoised using median filter. Next, characteristics such as peak, pitch spectrum, Mel frequency Cepstral coefficients (MFCC), mean, standard deviation, and minimum and maximum of the signal are extorted from the denoised signal. Following that, to accomplish the training process, the extracted characteristics are given to genetic algorithm based codebook generation in vector quantization. The initial populations are created by selecting random code vectors from the training set for the codebooks for the genetic algorithm process and IP-HMM helps in doing the recognition. At this point the creativeness will be done in terms of one of the genetic operation crossovers. The proposed speech recognition technique offers 97.14% accuracy.