SPEED BUMP DETECTION FOR AUTONOMOUS VEHICLES USING SIGNAL-PROCESSING TECHNIQUES

Autonomous vehicle (AV) is one of the emerging technologies that have far-reaching applications and implications in smart cities. Among the current challenges of the Smart City, Traffic management is of utmost importance. AV technologies can decrease transportation cost and can be used for efficient management and control of traffic flows. Traffic management strongly depends on the road surface condition. Abnormalities in the road, such as manholes and potholes, can cause accidents when not identified by the drivers. Furthermore, human-induced abnormalities, such as speed bumps, could also cause accidents. Detecting road abnormalities provide safety to human and vehicles. Current researches on speed bump detection are based on using sensors, accelerometer and GPS. This makes them vulnerable to GPS error, network overload, delay and battery draining. To overcome these problems, we propose a novel method for speed bump detection that combines both image and signal processing techniques. The advantage of the proposed approach consists in detecting speed bumps accurately without using any special sensors, hardware, Smartphone and GPS

Comparative Evaluation of Sentiment Analysis Methods Across Arabic Dialects

Sentiment analysis in Arabic is challenging due to the complex morphology of the language. The task becomes more challenging when considering Twitter data that contain significant amounts of noise such as the use of Arabizi, code-switching and different dialects that varies significantly across the Arab world, the use of non-Textual objects to express sentiments, and the frequent occurrence of misspellings and grammatical mistakes. Modeling sentiment in Twitter should become easier when we understand the characteristics of Twitter data and how its usage varies from one Arab region to another. We describe our effort to create the first Multi-Dialect Arabic Sentiment Twitter Dataset (MD-ArSenTD) that is composed of tweets collected from 12 Arab countries, annotated for sentiment and dialect. We use this dataset to analyze tweets collected from Egypt and the United Arab Emirates (UAE), with the aim of discovering distinctive features that may facilitate sentiment analysis. We also perform a comparative evaluation of different sentiment models on Egyptian and UAE tweets. These models are based on feature engineering and deep learning, and have already achieved state-of-The-Art accuracies in English sentiment analysis. Results indicate the superior performance of deep learning models, the importance of morphological features in Arabic NLP, and that handling dialectal Arabic leads to different outcomes depending on the country from which the tweets are collected.This work was made possible by NPRP 6-716-1-138 grant from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu

Unsupervised Data Selection for TTS: Using Arabic Broadcast News as a Case Study

Several high-resource Text to Speech (TTS) systems currently produce natural, well-established human-like speech. In contrast, low-resource languages, including Arabic, have very limited TTS systems due to the lack of resources. We propose a fully unsupervised method for building TTS, including automatic data selection and pre-training/fine-tuning strategies for TTS training, using broadcast news as a case study. We show how careful selection of data, yet smaller amounts, can improve the efficiency of TTS system in generating more natural speech than a system trained on a bigger dataset. We adopt to propose different approaches for the: 1) data: we applied automatic annotations using DNSMOS, automatic vowelization, and automatic speech recognition (ASR) for fixing transcriptions' errors; 2) model: we used transfer learning from high-resource language in TTS model and fine-tuned it with one hour broadcast recording then we used this model to guide a FastSpeech2-based Conformer model for duration. Our objective evaluation shows 3.9% character error rate (CER), while the groundtruth has 1.3% CER. As for the subjective evaluation, where 1 is bad and 5 is excellent, our FastSpeech2-based Conformer model achieved a mean opinion score (MOS) of 4.4 for intelligibility and 4.2 for naturalness, where many annotators recognized the voice of the broadcaster, which proves the effectiveness of our proposed unsupervised method

A proteomic analysis unravels novel CORVET and HOPS proteins involved in Toxoplasma gondii secretory organelles biogenesis

Apicomplexans use the endolysosomal system for the biogenesis of their secretory organelles, namely, micronemes, rhoptries, and dense granules. In Toxoplasma gondii, our previous in silico search identified the HOPS tethering but not the CORVET complex and demonstrated a role of Vps11 (a common component for both complexes) in its secretory organelle biogenesis. Herein, we performed Vps11‐GFP‐Trap pull‐down assays and identified by proteomic analysis, not only the CORVET‐specific subunit Vps8 but also a BEACH domain‐containing protein (BDCP) conserved in eukaryotes. We show that knocking‐down Vps8 affects targeting of dense granule proteins, transport of rhoptry proteins, and the localization of the cathepsin L protease vacuolar compartment marker. Only a subset of micronemal proteins are affected by the absence of Vps8, shedding light on at least two trafficking pathways involved in microneme maturation. Knocking‐down BDCP revealed a restricted and particular role of this protein in rhoptry and vacuolar compartment biogenesis. Moreover, depletion of BDCP or Vps8 abolishes parasite virulence in vivo. This study identified BDCP as a novel CORVET/HOPS‐associated protein, playing specific roles and acting in concert during secretory organelle biogenesis, an essential process for host cell infection. Our results open the hypothesis for a role of BDCP in the vesicular trafficking towards lysosome‐related organelles in mammals and yeast

EMT Markers in Locally-Advanced Prostate Cancer: Predicting Recurrence?

Background: Prostate cancer (PCa) is the second most frequent cause of cancer-related death in men worldwide. It is a heterogeneous disease at molecular and clinical levels which makes its prognosis and treatment outcome hard to predict. The epithelial-to-mesenchymal transition (EMT) marks a key step in the invasion and malignant progression of PCa. We sought to assess the co-expression of epithelial cytokeratin 8 (CK8) and mesenchymal vimentin (Vim) in locally-advanced PCa as indicators of EMT and consequently predictors of the progression status of the disease.Methods: Co-expression of CK8 and Vim was evaluated by immunofluorescence (IF) on paraffin-embedded tissue sections of 122 patients with PCa who underwent radical prostatectomies between 1998 and 2016 at the American University of Beirut Medical Center (AUBMC). EMT score was calculated accordingly and then correlated with the patients' clinicopathological parameters and PSA failure.Results: The co-expression of CK8/Vim (EMT score), was associated with increasing Gleason group. A highly significant linear association was detected wherein higher Gleason group was associated with higher mean EMT score. In addition, the median estimated biochemical recurrence-free survival for patients with < 25% EMT score was almost double that of patients with more than 25%. The validity of this score for prediction of prognosis was further demonstrated using cox regression model. Our data also confirmed that the EMT score can predict PSA failure irrespective of Gleason group, pathological stage, or surgical margins.Conclusion: This study suggests that assessment of molecular markers of EMT, particularly CK8 and Vim, in radical prostatectomy specimens, in addition to conventional clinicopathological prognostic parameters, can aid in the development of a novel system for predicting the prognosis of locally-advanced PCa

Protein-protein interaction based on pairwise similarity

<p>Abstract</p> <p>Background</p> <p>Protein-protein interaction (PPI) is essential to most biological processes. Abnormal interactions may have implications in a number of neurological syndromes. Given that the association and dissociation of protein molecules is crucial, computational tools capable of effectively identifying PPI are desirable. In this paper, we propose a simple yet effective method to detect PPI based on pairwise similarity and using only the primary structure of the protein. The PPI based on Pairwise Similarity (PPI-PS) method consists of a representation of each protein sequence by a vector of pairwise similarities against large subsequences of amino acids created by a shifting window which passes over concatenated protein training sequences. Each coordinate of this vector is typically the E-value of the Smith-Waterman score. These vectors are then used to compute the kernel matrix which will be exploited in conjunction with support vector machines.</p> <p>Results</p> <p>To assess the ability of the proposed method to recognize the difference between "<it>interacted</it>" and "<it>non-interacted</it>" proteins pairs, we applied it on different datasets from the available yeast <it>saccharomyces cerevisiae </it>protein interaction. The proposed method achieved reasonable improvement over the existing state-of-the-art methods for PPI prediction.</p> <p>Conclusion</p> <p>Pairwise similarity score provides a relevant measure of similarity between protein sequences. This similarity incorporates biological knowledge about proteins and it is extremely powerful when combined with support vector machine to predict PPI.</p

Contribution to multiplatform deployement of muttitasking applications by high-Level execution services behavioral modeling

Face à la complexité des logiciels multitâches, liée aux contextes économique et concurrentiel très pressants, la portabilité des applications et la réutilisabilité des processus de déploiement sont devenues un enjeu majeur. L'ingénierie dirigée par les modèles est une approche qui aspire répondre à ces besoins en séparant les préoccupations fonctionnelles des systèmes multitâches de leurs préoccupations techniques, tout en maintenant la relation entre eux. En pratique, cela se concrétise par des transformations de modèles capables de spécialiser les modèles pour des plates-formes cibles. Actuellement, les préoccupations spécifiques à ces plates-formes sont décrites implicitement dans les transformations eux même. Par conséquence, ces transformations ne sont pas réutilisables et ne permettent pas de répondre aux besoins hétérogènes et évolutifs qui caractérisent les systèmes multitâches. Notre objectif est alors d'appliquer le principe de séparation de préoccupation au niveau même de la transformation des modèles, une démarche qui garantie la portabilité des modèles et la réutilisabilité des processus de transformation.Pour cela, cette étude propose premièrement une modélisation comportementale détaillée des plates-formes d'exécutions logicielles. Cette modélisation permet d'extraire les préoccupations spécifiques à une plate-forme de la transformation de modèle et les capturer dans un modèle détaillé indépendant et réutilisable. Dans un second temps, en se basant sur ces modèles, elle présente un processus générique de développement des systèmes concurrents multitâches. L'originalité de cette approche réside dans une véritable séparation des préoccupations entre trois acteurs à savoir le développeur des chaînes de transformation, qui spécifient une transformation de modèle générique, les fournisseurs des plates-formes qui fournissent des modèles détaillés de leurs plates-formes et le concepteur des applications multitâche qui modélise le système. A la fin de cette étude, une évaluation de cette approche permet de montrer une réduction dans le coût de déploiement des applications sur plusieurs plates-formes sans impliquer un surcoût de performance.Given the complexity of multitasked software, linked to very pressing economic and competitive contexts, application portability and deployment process reusability has become a major issue. The model driven engineering is an approach that aspires to meet these needs by separating functional concerns of multitasking systems from their technical concerns, while maintaining the relationship between them. In practice, this takes the form of model transformations that specializes models for target platforms. Currently, concerns specific to these platforms are described implicitly in the transformations themselves. Consequently, these transformations are not reusable and do not meet the heterogeneous evolutionary needs that characterize multitasking systems. Our objective is then to apply the principle of separation of concern even at the level of transformation models, an approach that guarantees portability and reusability of models transformation process.To do this, this study provides first a detailed behavioral modeling of software execution platform. This modeling allows to extract specific concerns from model transformation and to capture them in a detailed platform model independent and reusable. In a second step, based on these models, it presents a generic process for developing concurrent systems. The originality of this approach is a true separation of concerns between three actors: the developer of transformation tool, who specifies a generic model transformation, platform providers that provide detailed models of their platforms and the multitasked system designer that models the system. At the end of this study, an evaluation of this approach shows a reduction in the cost of deploying applications on multiple platforms without incurring an additional cost of performance

Déploiement multiplateforme d'applications multitâche par la modélisation

Given the complexity of multitasked software, linked to very pressing economic and competitive contexts, application portability and deployment process reusability has become a major issue. The model driven engineering is an approach that aspires to meet these needs by separating functional concerns of multitasking systems from their technical concerns, while maintaining the relationship between them. In practice, this takes the form of model transformations that specializes models for target platforms. Currently, concerns specific to these platforms are described implicitly in the transformations themselves. Consequently, these transformations are not reusable and do not meet the heterogeneous evolutionary needs that characterize multitasking systems. Our objective is then to apply the principle of separation of concern even at the level of transformation models, an approach that guarantees portability and reusability of models transformation process.To do this, this study provides first a detailed behavioral modeling of software execution platform. This modeling allows to extract specific concerns from model transformation and to capture them in a detailed platform model independent and reusable. In a second step, based on these models, it presents a generic process for developing concurrent systems. The originality of this approach is a true separation of concerns between three actors: the developer of transformation tool, who specifies a generic model transformation, platform providers that provide detailed models of their platforms and the multitasked system designer that models the system. At the end of this study, an evaluation of this approach shows a reduction in the cost of deploying applications on multiple platforms without incurring an additional cost of performance.Face à la complexité des logiciels multitâches, liée aux contextes économique et concurrentiel très pressants, la portabilité des applications et la réutilisabilité des processus de déploiement sont devenues un enjeu majeur. L'ingénierie dirigée par les modèles est une approche qui aspire répondre à ces besoins en séparant les préoccupations fonctionnelles des systèmes multitâches de leurs préoccupations techniques, tout en maintenant la relation entre eux. En pratique, cela se concrétise par des transformations de modèles capables de spécialiser les modèles pour des plates-formes cibles. Actuellement, les préoccupations spécifiques à ces plates-formes sont décrites implicitement dans les transformations eux même. Par conséquence, ces transformations ne sont pas réutilisables et ne permettent pas de répondre aux besoins hétérogènes et évolutifs qui caractérisent les systèmes multitâches. Notre objectif est alors d'appliquer le principe de séparation de préoccupation au niveau même de la transformation des modèles, une démarche qui garantie la portabilité des modèles et la réutilisabilité des processus de transformation.Pour cela, cette étude propose premièrement une modélisation comportementale détaillée des plates-formes d'exécutions logicielles. Cette modélisation permet d'extraire les préoccupations spécifiques à une plate-forme de la transformation de modèle et les capturer dans un modèle détaillé indépendant et réutilisable. Dans un second temps, en se basant sur ces modèles, elle présente un processus générique de développement des systèmes concurrents multitâches. L'originalité de cette approche réside dans une véritable séparation des préoccupations entre trois acteurs à savoir le développeur des chaînes de transformation, qui spécifient une transformation de modèle générique, les fournisseurs des plates-formes qui fournissent des modèles détaillés de leurs plates-formes et le concepteur des applications multitâche qui modélise le système. A la fin de cette étude, une évaluation de cette approche permet de montrer une réduction dans le coût de déploiement des applications sur plusieurs plates-formes sans impliquer un surcoût de performance