An integrated system to remote monitor and control anaerobic wastewater treatment plants through the internet.

The TELEMAC project brings new methodologies from the Information and Science Technologies field to the world of water treatment. TELEMAC offers an advanced remote management system which adapts to most of the anaerobic wastewater treatment plants that do not benefit from a local expert in wastewater treatment. The TELEMAC system takes advantage of new sensors to better monitor the process dynamics and to run automatic controllers that stabilise the treatment plant, meet the depollution requirements and provide a biogas quality suitable for cogeneration. If the automatic system detects a failure which cannot be solved automatically or locally by a technician, then an expert from the TELEMAC Control Centre is contacted via the internet and manages the problem.     

Silhouette-based human action recognition using SAX-Shapes

Human action recognition is an important problem in Computer Vision. Although most of the existing solutions provide good accuracy results, the methods are often overly complex and computationally expensive, hindering practical applications. In this regard, we introduce the combination of time-series representation for the silhouette and Symbolic Aggregate approXimation (SAX), which we refer to as SAX-Shapes, to address the problem of human action recognition. Given an action sequence, the extracted silhouettes of an actor from every frame are transformed into time series. Each of these time series is then efficiently converted into the symbolic vector: SAX. The set of all these SAX vectors (SAX-Shape) represents the action. We propose a rotation invariant distance function to be used by a random forest algorithm to perform the human action recognition. Requiring only silhouettes of actors, the proposed method is validated on two public datasets. It has an accuracy comparable to the related works and it performs well even in varying rotation.     

Time optimization of ultraviolet–ozone pretreatment for improving wool fabrics properties

Wool fabrics were exposed to ultraviolet (UV)–ozone treatment for different periods. After exposure, the fabrics were analyzed by Fourior transform infrared spectroscopy (FTIR). Also, the crystallinity and amorphousity regions were followed by an X‐ray diffraction technique. The results were correlated by mechanical properties measurements. After a certain period of exposure, the dyeability and printability were improved because these abilities are strongly related to the percentage ratio of crystallinity regions to amorphousity regions in wool fabrics. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 85: 1469–1476, 2002     

IESK-ArDB: a database for handwritten Arabic and an optimized topological segmentation approach

Even though a lot of researches have been conducted in order to solve the problem of unconstrained handwriting recognition, an effective solution is still a serious challenge. In this article, we address two Arabic handwriting recognition-related issues. Firstly, we present IESK-arDB, a new multi-propose off-line Arabic handwritten database. It is publicly available and contains more than 4,000 word images, each equipped with binary version, thinned version as well as a ground truth information stored in separate XML file. Additionally, it contains around 6,000 character images segmented from the database. A letter frequency analysis showed that the database exhibits letter frequencies similar to that of large corpora of digital text, which proof the database usefulness. Secondly, we proposed a multi-phase segmentation approach that starts by detecting and resolving sub-word overlaps, then hypothesizing a large number of segmentation points that are later reduced by a set of heuristic rules. The proposed approach has been successfully tested on IESK-arDB. The results were very promising, indicating the efficiency of the suggested approach.     

A branch and bound algorithm for extracting smallest minimal unsatisfiable subformulas

Explaining the causes of infeasibility of Boolean formulas has practical applications in numerous fields, such as artificial intelligence (repairing inconsistent knowledge bases), formal verification (abstraction refinement and unbounded model checking), and electronic design (diagnosing and correcting infeasibility). Minimal unsatisfiable subformulas (MUSes) provide useful insights into the causes of infeasibility. An unsatisfiable formula often has many MUSes. Based on the application domain, however, MUSes with specific properties might be of interest. In this paper, we tackle the problem of finding a smallest-cardinality MUS (SMUS) of a given formula. An SMUS provides a succinct explanation of infeasibility and is valuable for applications that are heavily affected by the size of the explanation. We present (1) a baseline algorithm for finding an SMUS, founded on earlier work for finding all MUSes, and (2) a new branch-and-bound algorithm called Digger that computes a strong lower bound on the size of an SMUS and splits the problem into more tractable subformulas in a recursive search tree. Using two benchmark suites, we experimentally compare Digger to the baseline algorithm and to an existing incomplete genetic algorithm approach. Digger is shown to be faster in nearly all cases. It is also able to solve far more instances within a given runtime limit than either of the other approaches.     

A novel distributed scheduling scheme for OFDMA uplink using channel information and probabilistic transmission

Distributed uplink scheduling in OFDMA systems is considered. In the proposed model, mobile terminals have the responsibility of making their own transmission decisions. The proposed scheme is based on two dimensional reservation in time and frequency. Terminals use channel state information in order to favor transmissions over certain subchannels, and transmission is done in a probabilistic manner. The proposed approach provides more autonomy to mobile devices in making transmission decisions. Furthermore, it allows avoiding collisions during transmission since it leads to collision detection during the resource reservation phase. The proposed approach is compared to other random access methods and shown to be superior in terms of increasing sum-rate, reducing the number of users in outage, and reducing the collision probability in the reservation phase.     

Impact of Coronavirus Pandemic Crisis on Technologies and Cloud Computing Applications

In light of the coronavirus disease 2019 (COVID-19) outbreak caused by the novel coronavirus, companies and institutions have instructed their employees to work from home as a precautionary measure to reduce the risk of contagion. Employees, however, have been exposed to different security risks because of working from home. Moreover, the rapid global spread of COVID-19 has increased the volume of data generated from various sources. Working from home depends mainly on cloud computing (CC) applications that help employees to efficiently accomplish their tasks. The cloud computing environment (CCE) is an unsung hero in the COVID-19 pandemic crisis. It consists of the fast-paced practices for services that reflect the trend of rapidly deployable applications for maintaining data. Despite the increase in the use of CC applications, there is an ongoing research challenge in the domains of CCE concerning data, guaranteeing security, and the availability of CC applications. This paper, to the best of our knowledge, is the first paper that thoroughly explains the impact of the COVID-19 pandemic on CCE. Additionally, this paper also highlights the security risks of working from home during the COVID-19 pandemic.     

Array-index: a plug&search K nearest neighbors method for high-dimensional data

Previous algorithms of data partitioning methods (DPMs) to find the exact K-nearest neighbors (KNN) at high dimensions are outperformed by a linear scan method [J.M. Kleinberg, Two algorithms for nearest neighbor search in high dimensions, 29th ACM Symposium on Theory of computing, 1997; R. Weber, H.-J. Schek, S. Blott. A quantitative analysis and performance study for similarity-search methods in high-dimensional spaces. in: Proc. of the 24th VLDB, USA, 1998]. In this paper, we present a “plug&search” method to greatly speed up the exact KNN search of existing DPMs. The idea is to linearize the data partitions produced by a DPM, rather than the points themselves, into a one-dimensional array-index, that is simple, compact and fast. Unlike most DPMs that support KNN search, which require storage space linear, or exponential [J.M. Kleinberg, Two algorithms for nearest neighbor search in high dimensions, 29th ACM Symposium on Theory of computing, 1997; M. Hagedoom, Nearest neighbors can be found efficiently if the dimension is small relative to the input size, ICDT 2003], in dimensions, the array-index requires a storage space that is linear in the number of mapped partitions.     

AASHTO-LRFD Live Load Distribution for Beam-and-Slab Bridges: Limitations and Applicability

This paper presents a comparison between the live load distribution factors of simple span slab-on-girders concrete bridges based on the current AASHTO-LRFD and finite-element analysis. In this comparison, the range of applicability limits specified by the current AASHTO-LRFD is fully covered and investigated in terms of span length, slab thickness, girder spacing and longitudinal stiffness. All the AASHTO-PCI concrete girders (Types I–VI) are considered to cover the complete range of longitudinal stiffness specified in the AASHTO-LRFD. Several finite-elements linear elastic models were investigated to obtain the most accurate method to represent the bridge superstructure. The bridge deck was modeled as four-node quadrilateral shell elements, whereas the girders were modeled using two-node space frame elements. The live load used in the analysis is the vehicular load plus the standard lane load as specified by AASHTO-LRFD. The live load is positioned at the longitudinal location that produced the extreme effect, and then it is moved transversely across the bridge width in order to investigate all possibilities of one-lane, two-lane and three-lane design loads. A total of 886 bridge superstructure models were built and analyzed using the computer program SAP2000 to perform this comparison. The results of this study are presented in terms of figures to be practically useful to bridge engineers. This study showed that the AASHTO-LRFD may significantly overestimate the live load distribution factors compared to the finite-element analysis.