Electronic commerce infrastructure

Electronic commerce (E-commerce) is all the rage these days. About 100 million users and at least one million businesses already reachable via the Internet have made it that way. This critical mass compares to the market economy of North America, Japan or Europe. But doing business electronically means shifting critical business processes to open networks. It also means connecting back-end business applications in a secure and flexible way. Is there anything preventing the continued proliferation of this economy? Yes. A software infrastructure that allows all participants to carry out business transactions is still lacking. As a result, specialty market reference architectures are still needed to help identify important players, roles and relationships of the various markets and their participants. These architectures define the major components these participants require to carry out business transactions in that particular market. By defining interfaces and the semantics of the involved services, reference architectures provide patterns for software developers. These patterns help the software developers to implement coherent pacts to the overall electronic market system     

Influence of atmospheric pressure plasma treatment on various fibrous materials: Performance properties and surface adhesion analysis

Atmospheric pressure plasma treatment using oxygen gas was applied to wool fibrous materials. The plasma-treated fibrous materials were characterised using advanced instrumental techniques including scanning electron microscopy and X-ray photoelectron spectroscopy. They were also tested for performance properties including tensile and tearing strength as well as change in yellowness using international standard testing methods. Wettability analysis was conducted to study the surface area and surface energy of the plasma-treated fibrous materials. Surface modification regarding the enhancement of their adhesion to other substance, i.e. microcapsule treatment, was investigated.     

A method to improve and automate flat defect detection during ultrasonic inspection

In the nondestructive testing of materials, ultrasonic imagery can detect and characterize defects that are present in a structure. Data are displayed in the form of images, and processing algorithms can be applied for automatic detection and characterization. However, when using diffracted waves, the amplitude is often too low, and the signals are difficult to distinguish from the noise. Other times, the volume of data requires significant computation time. In this paper, we propose a method that can avoid image formation by replacing it with a sparse matrix and significantly reducing the amount of data to process; this allows for the enhancement and the automation of the detection of thin and flat defects such as cracks. The elements of the sparse matrix form a curve, which is sufficient to characterize defects in many cases. These elements are selected from diffracted signals using the split‐spectrum processing method. In this way, the signal‐to‐noise ratio is improved, and the position of the echo signal is accurately determined. When a crack is present in a material, the points of the sparse matrix form a parabola and classical tools of pattern recognition such as the Hough transform can detect it, thus providing significant help in decision‐making processes. Copyright © 2011 John Wiley & Sons, Ltd.     

A Stretchable Solid Ionic Electrode-Based Triboelectric Nanogenerator for Biomechanical Energy Harvesting and Self-Powered Sensors

Stretchable power devices and self-powered sensors have become increasingly desired for wearable electronics and artificial intelligence. In this study, an all-solid-state triboelectric nanogenerator (TENG) is reported, whose one solid-state structure prevents delamination during stretch and release cycles and increasing the patch adhesive force (3.5 N) and strain (586% elongation at break). Through the synergetic virtues of stretchability, ionic conductivity, and excellent adhesion to the tribo-layer, reproducible open-circuit voltage (V_OC) of 84 V, charge (Q_SC) of 27.5 nC, and short-circuit current (I_SC) of 3.1 µA after drying at 60°C or 20,000 contact-separation cycles are obtained. Apart from contact-separation, this device shows unprecedented electricity generation through stretch–release of solid materials leading to a linear relationship between V_OC and strain. For the first time, this work provides a clear explanation of the working mechanism of contact-free stretching–releasing and investigates the relationships of exerted force, strain, thickness of the device, and electric output. Benefitting from the one solid-state structure, this contact-free device remains stable even after repeated stretch–release cycling, maintaining 100% of its V_OC after 2500 stretch–release cycles. These findings provide a strategy toward highly conductive and stretchable electrodes for harvesting mechanical energy and health monitoring.     

SIMAD: Secure Intelligent Method for IoT-Fog Environments Attacks Detection

The Internet of Thing IoT paradigm has emerged in numerous domains and it has achieved an exponential progress. Nevertheless, alongside this advancement, IoT networks are facing an ever-increasing rate of security risks because of the continuous and rapid changes in network environments. In order to overcome these security challenges, the fog system has delivered a powerful environment that provides additional resources for a more improved data security. However, because of the emerging of various breaches, several attacks are ceaselessly emerging in IoT and Fog environment. Consequently, the new emerging applications in IoT-Fog environment still require novel, distributed, and intelligent security models, controls, and decisions. In addition, the ever-evolving hacking techniques and methods and the expanded risks surfaces have demonstrated the importance of attacks detection systems. This proves that even advanced solutions face difficulties in discovering and recognizing these small variations of attacks. In fact, to address the above problems, Artificial Intelligence (AI) methods could be applied on the millions of terabytes of collected information to enhance and optimize the processes of IoT and fog systems. In this respect, this research is designed to adopt a new security scheme supported by an advanced machine learning algorithm to ensure an intelligent distributed attacks detection and a monitoring process that detects malicious attacks and updates threats signature databases in IoT-Fog environments. We evaluated the performance of our distributed approach with the application of certain machine learning mechanisms. The experiments show that the proposed scheme, applied with the Random Forest (RF) is more efficient and provides better accuracy (99.50%), better scalability, and lower false alert rates. In this regard, the distribution character of our method brings about faster detection and better learning.     

Seed‐Assisted Growth for Low‐Temperature‐Processed All‐Inorganic CsPbIBr2 Solar Cells with Efficiency over 10%

All‐inorganic CsPbIBr₂ perovskite has recently received growing attention due to its balanced band gap and excellent environmental stability. However, the requirement of high‐temperature processing limits its application in flexible devices. Herein, a low‐temperature seed‐assisted growth (SAG) method for high‐quality CsPbIBr₂ perovskite films through reducing the crystallization temperature by introducing methylammonium halides (MAX, X = I, Br, Cl) is demonstrated. The mechanism is attributed to MA cation based perovskite seeds, which act as nuclei lowering the formation energy of CsPbIBr₂ during the annealing treatment. It is found that methylammonium bromide treated perovskite (Pvsk‐Br) film fabricated at low temperature (150 °C) shows micrometer‐sized grains and superior charge dynamic properties, delivering a device with an efficiency of 10.47%. Furthermore, an efficiency of 11.1% is achieved for a device based on high‐temperature (250 °C) processed Pvsk‐Br film via the SAG method, which presents the highest reported efficiency for inorganic CsPbIBr₂ solar cells thus far.     

Towards a graph-based user profile modeling for a session-based personalized search

Most Web search engines use the content of the Web documents and their link structures to assess the relevance of the document to the user’s query. With the growth of the information available on the web, it becomes difficult for such Web search engines to satisfy the user information need expressed by few keywords. First, personalized information retrieval is a promising way to resolve this problem by modeling the user profile by his general interests and then integrating it in a personalized document ranking model. In this paper, we present a personalized search approach that involves a graph-based representation of the user profile. The user profile refers to the user interest in a specific search session defined as a sequence of related queries. It is built by means of score propagation that allows activating a set of semantically related concepts of reference ontology, namely the ODP. The user profile is maintained across related search activities using a graph-based merging strategy. For the purpose of detecting related search activities, we define a session boundary recognition mechanism based on the Kendall rank correlation measure that tracks changes in the dominant concepts held by the user profile relatively to a new submitted query. Personalization is performed by re-ranking the search results of related queries using the user profile. Our experimental evaluation is carried out using the HARD 2003 TREC collection and showed that our session boundary recognition mechanism based on the Kendall measure provides a significant precision comparatively to other non-ranking based measures like the cosine and the WebJaccard similarity measures. Moreover, results proved that the graph-based search personalization is effective for improving the search accuracy.     

Evaluation of contextual information retrieval effectiveness: overview of issues and research

The increasing prominence of information arising from a wide range of sources delivered over electronic media has made traditional information retrieval systems less effective. Indeed, users are overwhelmed by the information delivered by such systems in response to their queries, particularly when the latter are ambiguous. In order to tackle this problem, the state-of-the-art reveals that there is a growing interest towards contextual information retrieval which relies on various sources of evidence issued from the user’s search background and environment like interests, preferences, time and location, in order to improve the retrieval accuracy. Contextual information retrieval systems are based on different definitions of the core concept of user’s context, various user’s context modeling approaches and several techniques of document relevance measurement, but all share the goal of providing the most useful information to the users in accordance with their context. However, the evaluation methodologies conceived in the past several years for traditional information retrieval and widely used in the evaluation campaigns have been challenged by the consideration of user’s context in the information retrieval process. Thus, we recognize that a critical review of existing evaluation methodologies in contextual information retrieval area is needed in order to design and develop standard evaluation frameworks. We present in this paper a comprehensive survey of contextual information retrieval evaluation methodologies and provide insights into how and why they are appropriate to measure the retrieval effectiveness. We also highlight some of the research challenges ahead that would constitute substantive research area for future research.     

Impact of Treated Wastewater Reuse on Agriculture and Aquifer Recharge in a Coastal Area: Korba Case Study

Treated wastewater (TWW) reuse has increasingly been integrated in the planning and development of water resources in Tunisia. The present study aimed the evaluation of the environmental and health impact that would have the reuse of TWW for crops direct irrigation or for the recharge of the local aquifer in Korba (Tunisia). For this purpose water analyses were carried on the TWW intended for the aquifer recharge and on underground water of this area. As for underground water before recharge, no contamination by organic matter or heavy metals is shown but high salinity, nitrate, potassium and chloride concentrations are detected. The bacteriological analyses show the occurrence of faecal streptococcus, thermo-tolerant coliforms, total coliforms and E coli, but absence of salmonella. These results indicate that this water is not suitable for irrigation worse still for drinking purpose. The monitoring of TWW pollutants has demonstrated that oxygen demands (COD and BOD) do not exceed the Tunisian standards for TWW used in agriculture (NT 106.03) except for August when samples reach high values (COD = 139 mg O₂ L^− 1, BOD = 34). It is also the case for temperature, electrical conductivity (EC), salinity and pH. Heavy metal concentrations are under the detection limit. The determination of nutrients shows relatively low concentrations of nitrates, nitrites and orthophosphate (the maxima in mg L^− 1 are respectively 6.6, 5.6 and 0.92) whereas the potassium levels are high (up to 48.8 mg L^− 1) and the ammonia levels very high, reaching 60.6 mg L^− 1. As for bacteriological pollution, while no salmonella and intestinal nematods are detected, high concentrations of total coliforms, thermo-tolerant coliforms, faecal streptococci and E. coli are analysed. Consequently, the better use of TWW in this region would be the use of infiltration basins for the recharge of the deteriorated aquifer by TWW. It would give the opportunity to better the quality of the TWW reaching the groundwater by an additional treatment for bacteriological and suspended solid (TSS) contaminants while being an alternative water for the aquifer recharge and a coastal barrier against seawater intrusion.     

NAVIG: augmented reality guidance system for the visually impaired

Navigating complex routes and finding objects of interest are challenging tasks for the visually impaired. The project NAVIG (Navigation Assisted by artificial VIsion and GNSS) is directed toward increasing personal autonomy via a virtual augmented reality system. The system integrates an adapted geographic information system with different classes of objects useful for improving route selection and guidance. The database also includes models of important geolocated objects that may be detected by real-time embedded vision algorithms. Object localization (relative to the user) may serve both global positioning and sensorimotor actions such as heading, grasping, or piloting. The user is guided to his desired destination through spatialized semantic audio rendering, always maintained in the head-centered reference frame. This paper presents the overall project design and architecture of the NAVIG system. In addition, details of a new type of detection and localization device are presented. This approach combines a bio-inspired vision system that can recognize and locate objects very quickly and a 3D sound rendering system that is able to perceptually position a sound at the location of the recognized object. This system was developed in relation to guidance directives developed through participative design with potential users and educators for the visually impaired.