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The versatile video coding standard H.266/VVC release has been accompanied with various new contributions to improve the coding efficiency beyond the high-efficiency video coding (HEVC), particularly in the transformation process. The adaptive multiple transform (AMT) is one of the new tools that was introduced in the transform module. It involves five transform types from the discrete cosine transform/discrete sine transform families with larger block sizes. The DCT-II has a fast computing algorithm, while the DST-VII relies on a complex matrix multiplication. This has led to an additional computational complexity. The approximation of the DST-VII can be used for the transform optimization. At the hardware level, this method can provide a gain in power consumption, logic resources use and speed. In this paper, a unifed two-dimensional transform architecture that enables exact and approximate DST-VII computation of sizes

Talaromyces thermophilus galactolipase (TTL) was found to produce alcohol sugar fatty acid diesters. The modulation of the solvent composition was used for the esterification reaction screening of diesters from xylitol and various fatty acids using the immobilized Talaromyces thermophilus galactolipase. The reactions were assessed by LC-MS analysis. The antimicrobial activity assay showed that both xylitol dicaprylate and xylitol dilaurate esters had more ability to inhibit the growth of several bacteria involved in surface contamination in the food industry. The xylitol dilaurate ester has the highest activity against Gram-positive strains with the lowest MIC values of 0.0016 and 0.005 mg mL

International audience; The new video coding standard, Versatile Video Coding (VVC), released by the end of 2020 has increased the coding complexity both at encoder and decoder sides. This complexity increase is due to several coding tools proposed to enhance the coding efficiency. One of these tools is the Multiple Transform Selection (MTS) concept, a new approach for the transform unit. This paper aims at providing a new optimization of the MTS based on dataflow modeling. The proposed approach takes benefit of the different parallelism levels of the MTS in order to create an optimized multicore implementation. Also, this paper study the impact of the dataflow model granularity and the dynamic reconfiguration on the implementation efficiency on x86 multicore architectures. The PREESM tool is used in this study to develop the proposed dataflow models and for the granularity analysis. The dynamic reconfiguration study is here performed using the SPIDER runtime optimized for the multicore execution of applications modeled using Parameterized and Interfaced Synchronous Dataflow (PiSDF) dataflow graphs. Two architectures were used in this work: an x86 architecture with 4 cores and an x86 architecture with 24 cores. The results show that the SPIDER overhead time is almost negligible (0.05%) compared to the execution time of the application. Furthermore, a speed-up of 3.9 and up to 22 for all block sizes was achieved using a 4-core and 24-core machine, respectively.

The additional discrete transforms from cosine (DCT) and sine (DST) families that come with the Adaptive Multiple Transform (AMT) approach is one of the major enhancements involved in the new Versatile Video Coding (VVC) standard. They have increasingly brought additional complexity compared to HEVC standard. The transform module is one of the most consuming stages in terms of time and hardware resources. This paper focuses on the optimization of the DST-VII transform. It deals with a multicriteria optimization algorithm for approximate computing that aims at the identification of the optimal approximation of the DST-VII according to several approximation measures. The resulting transform matrix has extremely low arithmetic complexity as well as close proximity to the exact DST-VII. Moreover, hardware synthesis results denote that the simplified design of DST-VII consumes only a third of the hardware resources used by the original algorithm. Experimental results obtained from joint exploration model simulations show a slight bit-rate increase while maintaining almost the same video quality. Such results confirm the effectiveness of the proposed approximate transform. The latter yields good performance in terms of computational complexity reduction and proximity to the exact transform while exhibiting a video coding performance comparable to the original algorithm.

With the advent of Internet of Vehicles, overhead related to localization services and path discovery step can drain the network resources and overload the large-scale vehicular networks, thus slowing down the routing process, especially with the recent surge of time-sensitive and QoS (Quality of Service) greedy applications. Performing proactively these tasks contributes to reducing the associated overhead by exploiting the vehicular beaconing system, as related data can be piggybacked with beacon messages. In this context, we present ILTS, an Infrastructure Localization service and Tracking Scheme, designed to supply vehicles with contextual information about the infrastructure accessibility and the neighborhood, in order to track available paths and to forward promptly safety and non-safety-related information. Through extensive simulation experiments, we have proven the ability of ILTS to promptly supply vehicles with fresh information about the location of the infrastructure and the availability of paths to reach it. The obtained results show that the vehicles are able to maintain knowledge of full paths towards the infrastructure during an average of 90% of the time spent in an uncovered area.

The compass-gait biped robot is a two-DoF legged mechanical system that has been known by its passive dynamic walking. This kind of passive biped robot is modeled by an impulsive hybrid nonlinear system that exhibits complex behaviors. This paper is concerned with the stabilization of the passive dynamic walking of the compass-gait biped robot by designing an analytical expression of the controlled Poincare map. The suggested analytical method starts with the time-piecewise linearization of the impulsive system augmented with the controller, around a desired one-periodic passive hybrid limit cycle. By virtue of the first-order Taylor series, we design an explicit expression of the controlled Poincare map. We present also a simplified expression of the controlled Poincare map having a reduced dimension. In order to accomplish our goal concerned with the stabilization of the passive walking dynamics of the compass-gait biped robot, we develop first the linearized Poincare map around the period-1 fixed point of the Poincare map and we adopt a state-feedback control law to stabilize it. Furthermore, in order to enhance the effectiveness and robustness of the stabilization process, we adopt an LMI-based optimization approach by considering the controlled Poincare map to design the feedback gain. In the end of this work, we provide some numerical and graphical simulation results, to show the validity of the designed control law by means of the controlled Poincare map in the stabilization of the passive dynamic walking of the compass-gait biped robot.

Background Intrathoracic rupture of hepatic hydatid cyst is a rare but dangerous complication. Its occurrence in children is exceptional as diagnosis and management constitute real challenges. We report two cases of intrathoracic rupture of hepatic hydatid cyst in children. Case presentation Our patients were respectively 12-year-old boy and 9-year-old girl, known cases of respiratory symptoms, diagnosed initially for pleuropneumonia. The CT scan established the diagnosis of intrathoracic rupture of hepatic hydatid cyst in the pleural cavity for the first patient and in the bronchial tree for the second. An emergency surgery was performed for both. The second patient developed broncho-biliary fistulas during the post-operative course which necessitated a re-intervention. A recurrence was noted at follow-up for the second patient. Conclusion Intrathoracic rupture of hepatic hydatid cyst is a serious complication which can occur even in children. Its diagnosis needs a high index of suspicion. The surgical approach remains controversial and there is a lack of consensus about the best way of management. Recurrence may occur despite appropriate treatment.

Discriminative models have been shown to be more advantageous for pattern recognition problem in machine learning. For this study, the main focus is developing a new hybrid model that combines the advantages of a discriminative technique namely the support vector machines (SVM) with the full efficiency offered through covariance multivariate generalized Gaussian mixture models (MGGMM). This new hybrid MGGMM applies the Fisher and Kullback–Leibler kernels derived from MGGMM to improve the kernel function of SVM. This approach is based on two different learning techniques explicitly: the Fisher scoring algorithm and the Bayes inference technique based on Markov Chain Monte Carlo and Metropolis–Hastings algorithm. These learning methods work with two model selection approaches (minimum message length and marginal likelihood) to determine the number of clusters. The effectiveness of the framework is demonstrated through extensive experiments including synthetic datasets, facial expression recognition and human activity recognition.

The Salicornia species have been used for treatment and prevention of a various diseases. To the best of my knowledge, little information is regarding the antioxidant and protective activities of lipid extract from Salicornia Arabica (SALE). The objectives of this present work were designed to determine the in vitro antioxidant activities of SALE against cadmium-induced toxicity in erythrocytes isolated from rats. The distribution of fatty acid reflected the richness in saturated fatty acids that were predominated by palmitic acid. Our analysis showed that the major fatty acid components were palmitic acid (47.78%), linoleic acid (17.75%), followed by nanadecenoic acid (10.96%). Minor fatty acids including lignoseric acid and palmatoleic acid (C16:0). The in vitro antioxidant activity of SALE was evaluated using both test DPPH and ABTS assays. An important antioxidant potential was observed. The protective potential of SALE was evaluated by estimating the levels of stress markers like MDA concentration and SOD, CAT and GPx activities. Our results showed that cadmium significantly decreased the SOD, CAT and GPx activities in erythrocytes homogenates and enhanced lipid peroxidation. The pre-treatment with SALE ameliorated antioxidant status and inhibited MDA level in erythrocytes. In conclusion, the lipid isolated from S. arabica showed protective potential against Cd-induced erythrocytes damage, which could be related to active compounds present in this fraction.

We propose in this paper to recognize human activities through an unsupervised learning of finite multivariate generalized Gaussian mixture model. We address an important cue in finite mixture model which is the estimation of the mixture model’s parameters for a full covariance matrix. We have developed a novel learning algorithm based on Fixed-point covariance matrix estimator combined with the Expectation-Maximization algorithm. Furthermore, we have proposed an appropriate minimum message length (MML) criterion to deal with model selection problem. We evaluated our proposed method on synthetic datasets and a challenging application namely : Human activity recognition from images and videos. The obtained resutls show clearly the merits of our proposed framework which has better capabilities with full covariance matrix when modeling correlated data.

This study characterizes differences in glaucomatous eyes with and without high axial myopia using custom automated analysis of OCT images. 452 eyes of 277 glaucoma patients were stratified into non (n = 145 eyes), mild (n = 214 eyes), and high axial myopia (axial length (AL) > 26 mm, n = 93 eyes). Optic disc ovality index, tilt and rotation angle of Bruch´s membrane opening (BMO) and peripapillary choroidal thickness (PCT) were calculated using automated and deep learning strategies. High myopic optic discs were more oval and had larger BMO tilt than mild and non-myopic discs (both p p p

Background This is a retrospective observational study to show the role of tracheostomy in liberation of mechanical ventilation in adult post cardiac surgery. Methods Between January 2009 and December 2013, all post cardiac surgical patients who were ventilated for ≥7 days were allocated into: group (T) who had tracheostomy or group (PI) who did not have tracheostomy. Both groups were compared for ventilator free days at 30 (VFD-30) and 60 days (VFD-60) post Cardiac Surgical Intensive Care Unit (CSICU) admission, Length of Stay (LOS), and mortality. Results VFD-30 and VFD-60 were statistically significant higher in (PI) group compared to (T) group (7.5 ± 9.2 vs.0.9 ± 3.3, P = 0.000) and (22.3 ± 23.8 vs. 6.7 ± 13.3, P = 0.007) respectively. Comparing VFD at 30 and 60 days post tracheostomy (VFD-30T and VFD-60T) in (T) group to VFD at 30 and 60 days after admission in (PI) group, no difference was found (6.9 ± 8.9 vs. 7.5 ± 9.2, P = 0.8) and (29 ± 22.6 vs. 22.3 ± 23.8, P = 0.5) respectively. CSICU LOS was statistically significant higher in the (T) group compared to the (PI) group (71.6 ± 61.2 vs. 30.3 ± 35.6, P = 0.04). The hospital LOS and CSICU mortality, were not different between the 2 groups. Conclusions Tracheostomy for post cardiac surgery patients with prolonged mechanical ventilation did not improve VFD or CSICU LOS in our institute.

The aims of this study were to determine (1) the effects of microwave irradiation on the drying kinetics of jack pine wood, (2) the phytosanitary efficacy, and (3) the processing energy consumption and mechanical strength of the dried product. Microwave drying experiments were performed at 2.45 GHz frequency and at microwave powers ranging from 300 to 1000 W. Results indicate that higher microwave power and initial wood temperature and lower sample thickness increases the internal sample temperature, improves the drying rate, and reduces both drying time and energy consumption. The microwave irradiation efficacy to sanitize jack pine wood boards was determined in terms of temperature/time combinations based on actual drying kinetics according to standards for phytosanitary measures. The energy required to dry 12 mm thick wood board samples at microwave power ranging from 300 to 1000 W was in the range of 36.4–12.3 MJ/kg of water, respectively, for up to 65% energy consumption savings. The impact of microwave power on the mechanical properties was not statistically significant, although mechanical properties tended to decrease with increasing power.

In recent years, AES is known as the excellent choice between the existing symmetric cryptosystems to encrypt binary or text data. However, this standard encryption algorithm is unsuitable for images regarding the particular features of these kinds of data such as high correlation, high redundancy, and voluminosity. Based on this fact, we have designed a new cryptosystem taking into account the aforementioned characteristics which provides high performance and security level. Actually, the cryposystem adopts a new structure named Outer-Inner structure. This new structure consists of two phases: Outer phase and Inner phase. In the former phase, the image is treated as a single block. The purpose of this phase is to address the correlation and the redundancy issue of images. In order to ensure the efficiency and to avoid the problem of treating an image as a single block where several image encryption algorithms suffer from it, this phase only involves lightweight operations. In the later phase the image is treated as a set of fixed blocks. The aim of this phase is to address the voluminosity issue. In fact, during this phase each block can be encrypted independently through an iterative function. The experiment results show that 7 rounds are sufficient to reach an acceptable security level.

The presence of communication obstructing entities severely degrades the routing efficiency in Mobile Ad hoc Networks (MANET). While several routing protocols have proposed ways to mitigate this degradation essentially by getting around and avoiding obstacles, the detection of obstacle locations and their contours driven by the very signaling of the underlying routing protocol has not been given that much attention. Yet, the integration of such a capability within the routing protocol presents an adequate leverage of the routing efficiency. In this paper, we first propose a distributed autonomic scheme to locate obstructing entities (coined ALOE) within a MANET using the basic signaling of the Cartography Enhanced Optimized Link State routing (CE-OLSR) protocol. Then, we propose ALOE-CE-OLSR the integration of ALOE within CE-OLSR, and show the resulting improvement in routing validity as compared to that of both CE-OLSR with and without a priori knowledge of the obstructing entities map. While the routing validity measures the pertinence of the routes computed by the underlying routing protocol, two new metrics, namely the coverage and the precision ratios, are defined to properly evaluate the efficiency and performance of our proposed detection scheme, in addition to the throughput as well as the end-to-end delay of received data packets. Simulation results show that our proposed CE-OLSR signaling-based obstacle detection scheme accurately localizes and detects the boundaries of the stationary obstructing obstacles. The integrated ALOE-CE-OLSR achieves the same route validity, throughput and delay as CE-OLSR with a priori precise knowledge of the obstacles map.

Phishing attacks have become the preferred vehicle to gather sensitive information as well as to deliver dangerous malware. So far, there is still no phishing detection system that can perfectly detect and progressively self adapt to differentiate between phishing and legitimate websites. This paper proposes the case-based reasoning Phishing detection system (CBR-PDS) that relies on previous cases to detect phishing attacks. CBR-PDS is highly adaptive and dynamic as it can adapt to detect new phishing attacks using rather a small dataset size in contrast to other machine learning techniques. CBR-PDS aims to improve the detection accuracy and the reliability of the results by identifying a set of discriminative features and discarding irrelevant features. CBR-PDS relies on a two stage hybrid procedure using Information gain and Genetic algorithms. The reduction of the data dimensionality amounts to an improved accuracy rate, yet it necessitates a reduced processing time. The CBR-PDS is tested using different scenarios on a various balanced datasets. The obtained performances clearly show the suitability of our proposed hybrid feature selection procedure as well as the efficiency of the proposed CBR-PDS system. The obtained accuracy rates exceed 95%. We also show that the integration of an Online Phishing Threats component into the CBR-PDS system improves further the accuracy rate. Finally, CRB-PDS performances are compared to those of several known competitive classifiers.

A new method for obtaining strong S-boxes based on chaotic map and Teaching–Learning-Based Optimization (TLBO) is presented in this paper. Our method presents eight rounds; each round contains two transformations: row left shifting and columnwise rotation. The vectors for the transformations are different from one round to another, and they are controlled by two keys to the logistic map. These two keys are optimized by using TLBO which aims to construct a strong S-box that satisfies to the criteria set in advance. Test for the following criteria such as bijectivity, nonlinearity, strict avalanche criteria, equiprobable inputs/outputs XOR distribution is analyzed. Additionally, we will provide many comparisons with other S-boxes and test of the sensitivity to keys. The results of performance test show that the proposed design S-boxes presents good cryptography proprieties and can resist to several attacks.