An Investigation of Parallel Road Map Inference from Big GPS Traces Data

AbstractWith the increased use of GPS sensors in several everyday devices, persons trip data are be- coming very abundant. Many opportunities for exploration of the wealth GPS data and in this paper, we inferred, the geometry of road maps in Tunisia and the connectivity between them. This phenomenon is known as map generation and also map inference procedure. For that, we gathered big GPS data from about ten thousands of vehicles equipped with GPS receivers and circulating in Tunisia, which does not have a road map like other developing countries. We collected a big database with approximately 100 gigabytes. After preprocessing it, we were obliged to partition data in order to facilitate handling an unstructured database with a such size. In fact, we used for that K-means with its sequential mode and the parallel mode based on Mapreduce, which is one of the most famous proposed solution to analyse the rapidly growing data. The proposed parallel k-means algorithm was tested with our GPS data and the results are efficient in processing large datasets. It is a parallel data processing tool which is gathering significant importance from industry and academia especially with appearance of a new term to describe massive datasets having large-volume, high-complexity and growing data from different sources, “big data”

Translation into Arabic and validation of the ASES index in assessment of shoulder disabilities

AbstractObjectiveTo translate into Arabic and validate the “American Shoulder and Elbow Surgeons Evaluation Form” (ASES) for use in a Tunisian population presenting with periarticular pathologies of the shoulder.BackgroundNo functional index assessing the functional capacities of the shoulder is presently available in Arabic.Patients and methodsThe translation was achieved by means of forward/backward translation. Adaptations were carried out subsequent to a preliminary test involving 15 persons. Patients with periarticular shoulder disabilities were included. Clinical measurements evaluated pain and functional disability by means of the visual analogue scale (VAS). Interrater concordance (repeatability) was assessed using the intraclass correlation coefficient (ICC) and the Bland and Altman method. Construct validity (convergent and discriminant validity) was investigated using the Spearman rank correlation coefficient and a factorial analysis followed by orthogonal rotation. The internal consistency of each factor was graded in terms of the Cronbach alpha coefficient.ResultsEighty (80) patients were included in the study. Interrater concordance was excellent (ICC=0.96). The Bland and Altman method showed a low-variability mean difference. Correlations of the index score with the pain VAS (r=−0.49) and functional disability (r=−0.58) suggested satisfactory convergent validity, and our index likewise showed good discriminant validity. Factorial analysis led to the extraction of two factors with a cumulative variance rate of 92.6% that could not be explained.ConclusionTranslated into Arabic, the ASES index was found to possess high metrological qualities. While the index has been satisfactorily validated with regard to a Tunisian population, additional studies are needed to verify its applicability to other Arab populations

Towards the Formal Reliability Analysis of Oil and Gas Pipelines

It is customary to assess the reliability of underground oil and gas pipelines in the presence of excessive loading and corrosion effects to ensure a leak-free transport of hazardous materials. The main idea behind this reliability analysis is to model the given pipeline system as a Reliability Block Diagram (RBD) of segments such that the reliability of an individual pipeline segment can be represented by a random variable. Traditionally, computer simulation is used to perform this reliability analysis but it provides approximate results and requires an enormous amount of CPU time for attaining reasonable estimates. Due to its approximate nature, simulation is not very suitable for analyzing safety-critical systems like oil and gas pipelines, where even minor analysis flaws may result in catastrophic consequences. As an accurate alternative, we propose to use a higher-order-logic theorem prover (HOL) for the reliability analysis of pipelines. As a first step towards this idea, this paper provides a higher-order-logic formalization of reliability and the series RBD using the HOL theorem prover. For illustration, we present the formal analysis of a simple pipeline that can be modeled as a series RBD of segments with exponentially distributed failure times.Comment: 15 page

Translation in Arabic, adaptation and validation of the SF-36 Health Survey for use in Tunisia

AbstractObjectiveTo translate into Arabic and validate the SF-36 quality of life index in a Tunisian Arabic population.BackgroundNo validated Arabic quality of life index is published.DesignArabic translation of the SF-36 scale was obtained by the “forward/backward translation” method. Adaptations were made after a pilot study involving 22 subjects from general population. Inter-rater reliability was assessed by use of intraclass correlation coefficient (ICC) and Bland and Altman method. Construct validity was assessed by Spearman rank correlation coefficient (convergent and divergent validity), and factor analysis with Varimax rotation. Internal consistency was assessed by Cronbach alpha coefficient.ResultsWe note that 130 Tunisian subjects were included in the validation study. No items were excluded. Inter-rater reliability was excellent (ICC=0.98). Cronbach alpha coefficient was 0.94 conferring to translated index a good internal consistency. Expected divergent and convergent validity results suggested good construct validity. Two main factors were extracted by factor analysis and explained 62.3% of the cumulative variance: the first factor represented mental component, the second physical component. The Cronbach alpha coefficient was 0.88 and 0.91 respectively for factor 1 and factor 2.ConclusionWe translated into Arabic language and adapted the SF-36 scale for use in Tunisian population. The Arabic version is reliable and valid. Although the scale was validated in a Tunisian population, we expect that it is suitable for other Arab populations, especially North Africans. Further studies are needed to confirm such a hypothesis

TOWARDS AN EFFICIENT TRAFFIC CONGESTION PREDICTION METHOD BASED ON NEURAL NETWORKS AND BIG GPS DATA

ABSTRACT: The prediction of accurate traffic information such as speed, travel time, and congestion state is a very important task in many Intelligent Transportations Systems (ITS) applications. However, the dynamic changes in traffic conditions make this task harder. In fact, the type of road, such as the freeways and the highways in urban regions, can influence the driving speeds and the congestion state of the corresponding road. In this paper, we present a NNs-based model to predict the congestion state in roads. Our model handles new inputs and distinguishes the dynamic traffic patterns in two different types of roads: highways and freeways. The model has been tested using a big GPS database gathered from vehicles circulating in Tunisia. The NNs-based model has shown their capabilities of detecting the nonlinearity of dynamic changes and different patterns of roads compared to other nonparametric techniques from the literature. ABSTRAK: Ramalan maklumat trafik yang tepat seperti kelajuan, masa perjalanan dan keadaan kesesakan adalah tugas yang sangat penting dalam banyak aplikasi Sistem Pengangkutan Pintar (ITS). Walau bagaimanapun, perubahan keadaan lalu lintas yang dinamik menjadikan tugas ini menjadi lebih sukar. Malah, jenis jalan raya, seperti jalan raya dan lebuh raya di kawasan bandar, boleh mempengaruhi kelajuan memandu dan keadaan kesesakan jalan yang sama. Dalam makalah ini, kami membentangkan model berasaskan NN untuk meramalkan keadaan kesesakan di jalan raya. Model kami mengendalikan input baru dan membezakan corak trafik dinamik dalam dua jenis jalan raya yang lebuh raya dan jalan raya. Model ini telah diuji menggunakan pangkalan data GPS yang besar yang dikumpulkan dari kenderaan yang beredar di Tunisia. Model berasaskan NNs telah menunjukkan keupayaan mereka untuk mengesan ketiadaan perubahan dinamik dan pola jalan yang berbeza berbanding dengan teknik nonparametrik yang lain dari kesusasteraan

Mutations in SPG11, encoding spatacsin, are a major cause of spastic paraplegia with thin corpus callosum.

Autosomal recessive hereditary spastic paraplegia (ARHSP) with thin corpus callosum (TCC) is a common and clinically distinct form of familial spastic paraplegia that is linked to the SPG11 locus on chromosome 15 in most affected families. We analyzed 12 ARHSP-TCC families, refined the SPG11 candidate interval and identified ten mutations in a previously unidentified gene expressed ubiquitously in the nervous system but most prominently in the cerebellum, cerebral cortex, hippocampus and pineal gland. The mutations were either nonsense or insertions and deletions leading to a frameshift, suggesting a loss-of-function mechanism. The identification of the function of the gene will provide insight into the mechanisms leading to the degeneration of the corticospinal tract and other brain structures in this frequent form of ARHSP

Inhibition of Fungi and Gram-Negative Bacteria by Bacteriocin BacTN635 Produced by Lactobacillus plantarum sp. TN635

The aim of this study was to evaluate 54 lactic acid bacteria (LAB) strains isolated from meat, fermented vegetables and dairy products for their capacity to produce antimicrobial activities against several bacteria and fungi. The strain designed TN635 has been selected for advanced studies. The supernatant culture of this strain inhibits the growth of all tested pathogenic including the four Gram-negative bacteria (Salmonella enterica ATCC43972, Pseudomonas aeruginosa ATCC 49189, Hafnia sp. and Serratia sp.) and the pathogenic fungus Candida tropicalis R2 CIP203. Based on the nucleotide sequence of the 16S rRNA gene of the strain TN635 (1,540 pb accession no FN252881) and the phylogenetic analysis, we propose the assignment of our new isolate bacterium as Lactobacillus plantarum sp. TN635 strain. Its antimicrobial compound was determined as a proteinaceous substance, stable to heat and to treatment with surfactants and organic solvents. Highest antimicrobial activity was found between pH 3 and 11 with an optimum at pH = 7. The BacTN635 was purified to homogeneity by a four-step protocol involving ammonium sulfate precipitation, centrifugal microconcentrators with a 10-kDa membrane cutoff, gel filtration Sephadex G-25, and C18 reverse-phase HPLC. SDS-PAGE analysis of the purified BacTN635, revealed a single band with an estimated molecular mass of approximately 4 kDa. The maximum bacteriocin production (5,000 AU/ml) was recorded after a 16-h incubation in Man, Rogosa, and Sharpe (MRS) medium at 30 °C. The mode of action of the partial purified BacTN635 was identified as bactericidal against Listeria ivanovii BUG 496 and as fungistatic against C. tropicalis R2 CIP203