Search

The soft-switching technology is widely used in DC-DC converters, DC-AC inverters, and AC-DC rectifiers. Soft-switching non-isolated DC/DC converters (Buck, Boost, and Buck-Boost) are the most active research area of the soft-switching technology, and fruitful results are achieved. However, there is currently no comprehensive review for the soft-switching technology of non-isolated DC/DC converters. This paper introduces soft-switching topologies for non-isolated DC/DC converters, and presents classification and characteristic of all kinds of soft-switching technologies. Some soft-switching technologies of derivative converters (non-inverting Buck-Boost converters and multiphase converters) are also presented. Finally future trends and generalized constitution methods of the soft-switching topology for non-isolated DC/DC converters are concluded. The soft-switching theory and constitution methods summarized in this article are expected to be able to guide the proposing of new soft-switching technologies for DC-DC converters.

Model-Based Definition (MBD) is being adopted by the manufacturing industry as a single source for all product information in place of conventional 2D drawings. This paper aims to review the current literature on Model-Based Definition (MBD) and Model-Based Enterprise (MBE) to recognize the main contributions towards the development and implementation of MBD and explore its various perspectives. The publications encompassing technology and applications of MBD are categorized into seven domains. These domains are lifecycle information; design, discrete part manufacturing, and inspection; assembly; maintenance, repair, and overhaul; process planning; engineering change management; and contemporary aspects of digital product definition. The major outcomes of research literature, in these domains, are reviewed and future research directions are identified and formulated. Additionally, the paper highlights the issues and challenges associated with the realization of MBE by the manufacturing industry. These issues are categorized into technical, management, and certification categories. The prevalent issues in each of these categories are further discussed and analyzed.

Hydrogen gas is rapidly approaching a global breakthrough as a carbon-free energy vector. In such a hydrogen economy, safety sensors for hydrogen leak detection will be an indispensable element along the entire value chain, from the site of hydrogen production to the point of consumption, due to the high flammability of hydrogen-air mixtures. To stimulate and guide the development of such sensors, industrial and governmental stakeholders have defined sets of strict performance targets, which are yet to be entirely fulfilled. In this Perspective, we summarize recent efforts and discuss research strategies for the development of hydrogen sensors that aim at meeting the set performance goals. In the first part, we describe the state-of-the-art for fast and selective hydrogen sensors at the research level, and we identify nanostructured Pd transducer materials as the common denominator in the best performing solutions. As a consequence, in the second part, we introduce the fundamentals of the Pd-hydrogen interaction to lay the foundation for a detailed discussion of key strategies and Pd-based material design rules necessary for the development of next generation high-performance nanostructured Pd-based hydrogen sensors that are on par with even the most stringent and challenging performance targets.

[EN] Arc routing problems (ARPs) are defined and introduced. Following a brief history of developments in this area of research, different types of ARPs are described that are currently relevant for study. In addition, particular features of ARPs that are important from a theoretical or practical point of view are discussed. A section on applications describes some of the changes that have occurred from early applications of ARP models to the present day and points the way to emerging topics for study. A final section provides information on libraries and instance repositories for ARPs. The review concludes with some perspectives on future research developments and opportunities for emerging applications, This research was supported by the Ministerio de Economia y Competitividad and Fondo Europeo de Desarrollo Regional, Grant/Award Number: PGC2018-099428-B-I00. The Research Council of Norway, Grant/Award Numbers: 246825/O70 (DynamITe), 263031/O70 (AXIOM).

Considering the growing volume of information and services available on the Web, it has become essential to provide Web sites and applications with tools, such as recommender systems, capable of helping their users to obtain the information and services appropriate to their interests. Due to the complexity of Web adaptation and the ability of multi-agent systems to deal with complex problems, the multi-agent systems technology have been increasing. In this paper, we present a thorough survey of the use of multi-agent-based recommender systems. The results show that the use of multi-agent systems in recommender systems is increasing. The review shows the diversity of applications of multi-agent systems in recommender systems, namely on what concerns to the diversity of domains, different types of approaches, contributing to improving the performance of the recommendation systems. info:eu-repo/semantics/publishedVersion

International audience; Cyber-Physical Systems (CPS) are complex physical systems interacting with a considerable number of distributed computing elements for monitoring, control and management. They are currently becoming larger as Cyber-Physical Systems of Systems (CPSoS), since many industrial companies are transitioning their complex systems of systems to software-intensive solutions in different domains such as production or manufacturing. Following the development and dissemination of DevOps approaches in the Software Engineering world, we propose the Twin-Driven Engineering (TDE) paradigm as a way to upgrade the role of Digital Twins (DT) to become a central point in all the engineering activities on the CPSoS, from design to decommissioning. Since CPSoS can be highly heterogeneous, we rather target the support for producing and maintaining a single integrated virtual representation of the CPSoS (i.e. a System of Twins) on which it is possible to perform global reasoning, analysis and verification. However, such a new paradigm comes with several open research challenges. We provide an overview of the state-of-the-art in key areas related to TDE. We identify under-investigated problems in related work and outline corresponding research directions.

Over the past few years, what might not unreasonably be described as a true revolution has taken place in the field of machine vision, radically altering the way many things had previously been done and offering new and exciting opportunities for those able to quickly embrace and master the new techniques. Rapid developments in machine learning, largely enabled by faster GPU-equipped computing hardware, has facilitated an explosion of machine vision applications into hitherto extremely challenging or, in many cases, previously impossible to automate industrial tasks. Together with developments towards an internet of things and the availability of big data, these form key components of what many consider to be the fourth industrial revolution. This transformation has dramatically improved the efficacy of some existing machine vision activities, such as in manufacturing (e.g. inspection for quality control and quality assurance), security (e.g. facial biometrics) and in medicine (e.g. detecting cancers), while in other cases has opened up completely new areas of use, such as in agriculture and construction (as well as in the existing domains of manufacturing and medicine). Here we will explore the history and nature of this change, what underlies it, what enables it, and the impact it has had - the latter by reviewing several recent indicative applications described in the research literature. We will also consider the continuing role that traditional or classical machine vision might still play. Finally, the key future challenges and developing opportunities in machine vision will also be discussed.

As ever-increasing amounts of renewable electricity enter the energy supply mix on a regional, national and international basis, greater emphasis is being placed on energy conversion and storage technologies to deal with the oscillations, excess and lack of electricity. Hydrogen generation via proton exchange membrane water electrolysis (PEMWE) is one technology that offers a pathway to store large amounts of electricity in the form of hydrogen. The challenges to widespread adoption of PEM water electrolyzers lie in their high capital and operating costs which both need to be reduced through R&D. An evaluation of reported PEMWE performance data in the literature reveals that there are excessive variations of in situ performance results that make it difficult to draw conclusions on the pathway forward to performance optimization and future R&D directions. To enable the meaningful comparison of in situ performance evaluation across laboratories there is an obvious need for standardization of materials and testing protocols. Herein, we address this need by reporting the results of a round robin test effort conducted at the laboratories of five contributors to the IEA Electrolysis Annex 30. For this effort a method and equipment framework were first developed and then verified with respect to its feasibility for measuring water electrolysis performance accurately across the various laboratories. The effort utilized identical sets of test articles, materials, and test cells, and employed a set of shared test protocols. It further defined a minimum skeleton of requirements for the test station equipment. The maximum observed deviation between laboratories at 1 A cm−2 at cell temperatures of 60 °C and 80 °C was 27 and 20 mV, respectively. The deviation of the results from laboratory to laboratory was 2–3 times higher than the lowest deviation observed at one single lab and test station. However, the highest deviations observed were one-tenth of those extracted by a literature survey on similar material sets. The work endorses the urgent need to identify one or more reference sets of materials in addition to the method and equipment framework introduced here, to enable accurate comparison of results across the entire community. The results further imply that cell temperature control appears to be the most significant source of deviation between results, and that care must be taken with respect to break-in conditions and cell electrical connections for meaningful performance data.

International audience; Interoperability is playing an increasing role for today’s logistics and supply chain management (LSCM) because of the trends of cooperation or coopetition. Especially, digital interoperability concerning data or information exchange becomes a key enabler for the next evolutions that will massively rely upon digitalization, artificial intelligence, and autonomous systems. The notion of Physical Internet (PI) is one such evolution, an innovative worldwide logistic paradigm aimed at interconnecting and coordinating logistics networks for efficiency and sustainability. This paper investigates how digital interoperability can help interconnect logistics and supply networks as well as the operational solutions for sustainable development, and examines the new challenges and research opportunities for digital interoperability under the PI paradigm. To this end, we study the most relevant technologies for digital interoperability in LSCM, via a bibliometric analysis based on 208 papers published during 2010−2020. The results reveal that the present state-of-the-art solutions of digital interoperability are not fully aligned with PI requirements and show new challenges, research gaps and opportunities that need further discussion. Accordingly, several research avenues are suggested to advance research and applications in this area, and to achieve interconnection in logistics and supply networks for sustainability.

Infrared small-object segmentation (ISOS) has a persistent trade-off problem—that is, which came first, recall or precision? Constructing a fine balance between of them is, au fond, of vital importance to obtain the best performance in real applications, such as surveillance, tracking, and many fields related to infrared searching and tracking. F1-score may be a good evaluation metric for this problem. However, since the F1-score only depends upon a specific threshold value, it cannot reflect the user’s requirements according to the various application environment. Therefore, several metrics are commonly used together. Now we introduce F-area, a novel metric for a panoptic evaluation of average precision and F1-score. It can simultaneously consider the performance in terms of real application and the potential capability of a model. Furthermore, we propose a new network, called the Amorphous Variable Inter-located Network (AVILNet), which is of pliable structure based on GridNet, and it is also an ensemble network consisting of the main and its sub-network. Compared with the state-of-the-art ISOS methods, our model achieved an AP of 51.69%, F1-score of 63.03%, and F-area of 32.58% on the International Conference on Computer Vision 2019 ISOS Single dataset by using one generator. In addition, an AP of 53.6%, an F1-score of 60.99%, and F-area of 32.69% by using dual generators, with beating the existing best record (AP, 51.42%; F1-score, 57.04%; and F-area, 29.33%).

The research on ion-measuring devices has seen a rapid expansion in the last years as a consequence of the growing interest in wearable sensors for biofluids analysis and in portable devices for remote or in-line water and food quality monitoring. As a result, an increasing number of researchers is approaching the field of ion-selective sensors. Despite the apparently simple transduction principle, the theory behind their working mechanism is far from trivial and a correct understanding is necessary for an optimal exploitation of the technology. In current literature, imprecise characterization procedures lead to the definition of misleading sensors parameters, which cannot be effectively used for comparisons. In fact, some unique definitions and procedures applies to this category of sensors, which significantly differ from the traditional ones applied in sensing research. This tutorial aims at highlighting the basic thermodynamic theory and the correct experimental practice for the accurate and reproducible characterization of potentiometric ion-sensors. The most important requirements and design considerations on hardware and software interfaces will also be discussed to give a complete overview of the various aspects of current technology to people approaching this promising area of sensing.

Contains fulltext : 249131.pdf (Publisher’s version ) (Open Access) BACKGROUND: Currently many healthcare systems are supported by an increasing set of Health Information Sys-tems (HISs), which assist the activities for multiple stakeholders. The literature on HISs is, however, fragmented and a solid overview of the current state of HISs is missing. This impedes the understanding and characterization of the required HISs for the healthcare domain. METHODS: In this article, we present the results of a Systematic Literature Review (SLR) that identifies the HISs, their domains, stakeholders, features, and obstacles. RESULTS: In the SLR, we identified 1340 papers from which we selected 136 studies, on which we performed a full-text analysis. After the synthesis of the data, we were able to report on 33 different domains, 41 stakeholders, 73 features, and 69 obstacles. We discussed how these domains, features, and obstacles interact with each other and presented suggestions to overcome the identified obstacles. We recognized five groups of obstacles: technical problems, operational functionality, maintenance & support, usage problems, and quality problems. Obstacles from all groups require to be solved to pave the way for further research and application of HISs. CONCLUSION: This study shows that there is a plentitude of HISs with unique features and that there is no consensus on the requirements and types of HISs in the literature.

Assembly lines are mass production systems which are significant in the industrial production of both standard and customised products. Currently, industrial companies offer several products and it is common for an assembly system to have multiple assembly lines. Parallel assembly lines are multiple lines located in such a way as to allow improvements in the system’s efficiency through the use of common resources. In recent years several research studies have been made on parallel assembly lines. In this paper, we survey the parallel assembly lines balancing problem (PALBP) studies. Moreover, a classification scheme is provided to ease understanding. Finally, the main gaps in the literature are described and future research directions are presented.

Operation-level vision-based monitoring and documentation has drawn significant attention from construction practitioners and researchers. To automate the operation-level monitoring of construction and built environments, there have been much effort to develop computer vision technologies. Despite their encouraging findings, it remains a major challenge to exploit technologies in real construction projects, implying that there are knowledge gaps in practice and theory. To fill such knowledge gaps, this study thoroughly reviews 119 papers on operation-level vision-based construction monitoring, published in mainstream construction informatics journals. Existing research papers can be categorized into three sequential technologies: (1) camera placement for operation-level construction monitoring, (2) single-camera-based construction monitoring and documentation, and (3) multi-camera-based onsite information integration and construction monitoring. For each technology, state-of-the-art algorithms, open challenges, and future directions are discussed.

The Internet of Things (IoT) has attracted much attention from the Information and Communication Technology (ICT) community in recent years. One of the main reasons for this is the availability of techniques provided by this paradigm, such as environmental monitoring employing user data and everyday objects. The facilities provided by the IoT infrastructure allow the development of a wide range of new business models and applications (e.g., smart homes, smart cities, or e-health). However, there are still concerns over the security measures which need to be addressed to ensure a suitable deployment. Distributed Denial of Service (DDoS) attacks are among the most severe virtual threats at present and occur prominently in this scenario, which can be mainly owed to their ease of execution. In light of this, several research studies have been conducted to find new strategies as well as improve existing techniques and solutions. The use of emerging technologies such as those based on the Software-Defined Networking (SDN) paradigm has proved to be a promising alternative as a means of mitigating DDoS attacks. However, the high granularity that characterizes the IoT scenarios and the wide range of techniques explored during the DDoS attacks make the task of finding and implementing new solutions quite challenging. This problem is exacerbated by the lack of benchmarks that can assist developers when designing new solutions for mitigating DDoS attacks for increasingly complex IoT scenarios. To fill this knowledge gap, in this study we carry out an in-depth investigation of the state-of-the-art and create a taxonomy that describes and characterizes existing solutions and highlights their main limitations. Our taxonomy provides a comprehensive view of the reasons for the deployment of the solutions, and the scenario in which they operate. The results of this study demonstrate the main benefits and drawbacks of each solution set when applied to specific scenarios by examining current trends and future perspectives, for example, the adoption of emerging technologies based on Cloud and Edge (or Fog) Computing.

Nowadays, Internet-of-Things (IoT), big data, and cloud computing technologies allow increasing the throughput and quality of manufacturing systems, bringing to the rise of the Industry 4.0 paradigm. The aim is to leverage the ICT technologies to achieve a flexible customised production with reduced time while avoiding resources waste. In this framework, Zero-Defect Manufacturing (ZDM) concept plays a crucial role in guaranteeing the minimisation of defects and errors in industry processes by trying to act at the first time properly. Due to its importance, this topic has received greater attention during the last two years by the technical literature. Given the increasing number of research works and the several approaches suggested by researcher interested into the topic, this study aims at providing a literature overview of the current trends in the ZDM field from 2018 to 2020. The focus of the work is to provide a state-of-the-art about ZDM strategies, i.e. Detection, Repair, Prediction and Prevention, by analyzing the related most significant works, thus providing a single-strategy analysis and the corresponding most frequently used methods. A brief bibliometric study corroborates the general research patterns and the relevant aspects emerging from each single-strategy analysis. Finally, based on the conducted study, we point out the shortcomings present in the current technical literature to target the future research directions in the ZDM field.

Purpose Over the past 10 years, building on road infrastructure data, crash prediction models (CPMs) have become fundamental scientific tools for road safety management. However, there is a gap between state-of-the-art and state-of-the-practice, with the practical application lagging behind scientific progress. This motivated a review of international experience with CPMs from perspectives of application by practitioners and development by researchers. The objective of the paper is to improve practitioner understanding of modelling road safety performance using CPMs for crash frequency estimation, leading to their greater uptake in improving road safety. In short, why and how should road safety practitioners consider CPMs? Methods Both scientific and practice-oriented literature was retrieved, using academic sources, as well as reports of road agencies or institutes. The selection was limited to English language. Results From the review it is clear that developing CPMs is not a straightforward task: there are many available choices and decisions to be made during the process without definite guidance. This explains the diversity of approaches, techniques, and model types. The paper explains how some fundamental modelling decisions affect practical aspects of modelling safety performance. Conclusions There is a need to identify CPM solutions that will be scientifically sound and feasible in practitioners’ context. Together with increased communication between researchers and practitioners, these solutions will help overcome the identified challenges and increase use of CPMs.

The high and increasing requirements concerning energy consumption and the interior comfort of buildings result in a demand for more efficient façade constructions. In its role as a mediator between the exterior and interior of a building, the façade takes on a multitude of functions with effect on the building’s performance. Intelligent façades offer higher performances compared to static constructions, achieved by dynamic adjustments to changing environmental influences and interior requirements. Such systems are being explored and already applied. The concept of intelligent façades exists since the beginning of the 1980s. Since then, the technological possibilities for the implementation of intelligent systems have multiplied. Today, the fourth industrial revolution is based on the implementation of intelligent and networked production facilities. Considering the current exploration of intelligent technical systems in the industry, the understanding and the demands on the intelligence of a system change. The aim of this study is to examine the comprehension of an intelligent system in the context of the façade and in the context of the industry. This is to provide the basis for subsequent research on the transferability of strategies. The study provides used terms, relevant aspects, current definitions and characteristics of the respective intelligent system.

In recent years the use of UAVs (Unmanned aerial vehicles) have proliferated in the civil sector for purposes such as search and rescue, remote sensing or real-time monitoring of road traffic, among others. In the architecture, engineering and construction fields (AEC) UAVs have demonstrated to be an ideal technology due to their optimal performance in terms of time, precision, safety and cost. Given the rapid growth of interest in this technology, this research presents a critical review of the literature on the use of UAVs in architecture and urbanism to define the most widely used techniques and delimit the fields of application based on the experimentation published by the scientific community. A scientific mapping was carried out in two stages using the VOSviewerTM software: a scientometric and a bibliometric analysis. This technique allowed us to analyse a large body of literature and bibliographic data to obtain trends, patterns and directions of this domain of knowledge. Then, a literature review was presented, highlighting the relevant information identified in the previous analysis. The fields of application of UAVs were delimited and the most commonly used payload types and the most appropriate post-processing techniques were specified, depending on the aerial mission objective. The fields of application identified included different techniques related to the generation of 3D models, land mapping, construction site monitoring, building surveying to detect structural damage and energy losses and urban remote sensing. The literature review showed that UAVs provide a useful multi-tasking tool at any stage of an architectural project. These techniques can be applied to buildings or public spaces from the design and construction processes when the project is initiated to the later stages of maintenance and inspection of the building during its life cycle.

Slurry pipe transport has directed the efforts of researchers for decades, not only for the practical impact of this problem, but also for the challenges in understanding and modelling the complex phenomena involved. The increase in computer power and the diffusion of multipurpose codes based on Computational Fluid Dynamics (CFD) have opened up the opportunity to gather information on slurry pipe flows at the local level, in contrast with the traditional approaches of simplified theoretical modelling which are mainly based on a macroscopic description of the flow. This review paper discusses the potential of CFD for simulating slurry pipe flows. A comprehensive description of the modelling methods will be presented, followed by an overview of significant publications on the topic. However, the main focus will be the assessment of the potential and the challenges of the CFD approach, underlying the essential interplay between CFD simulations and experiments, discussing the main sources of uncertainty of CFD models, and evaluating existing models based on their interpretative or predictive capacity. This work aims at providing a solid ground for students, academics, and professional engineers dealing with slurry pipe transport, but it will also provide a methodological approach that goes beyond the specific application.

The ability of predicting material failure is essential for adequate structural dimensioning in every mechanical design. For ships, and particularly for military vessels, the challenge of optimizing the toughness-to-weight ratio at the highest possible value is essential to provide agile structures that can safely withstand external forces. Exploring the case of underwater explosions, the present paper summarizes some of the fundamental mathematical relations for foreseeing the behavior of naval panels to such solicitation. A broad state-of-the-art survey links the mechanical stress-strain response of materials and the influence of local reinforcements in flexural and lateral-torsional buckling to the hydrodynamic relations that govern the propagation of pressure waves prevenient from blasts. Numerical simulation approaches used in computational modeling of underwater explosions are reviewed, focusing on Eulerian and Lagrangian fluid descriptions, Johnson-Cook and Gurson constitutive materials for naval panels, and the solving methods FEM (Finite Element Method), FVM (Finite Volume Method), BEM (Boundary Element Method), and SPH (Smooth Particle Hydrodynamics). The confrontation of experimental tests for evaluating different hull materials and constructions with formulae and virtual reproduction practices allow a wide perception of the subject from different yet interrelated points of view.

Transition curves are a useful tool for lateral alignment of railway segments. Their design is important to ensure safe and comfortable travel for passengers and cargo. Well designed transition curves can lead to reduced wear of tracks and vehicles, which is beneficial from a maintenance point of view. Extensive studies have been performed through decades to find transition curves that can replace existing railway segments for the purpose of enhancing certain properties. Those studies seek to form curves that satisfy desired evaluation criteria, which are often connected to geometric continuity between the curve segments, and vehicle dynamics, to secure a smooth ride. This research topic is still ongoing and active at present. Recent results and findings are in line with the developments on the topic of vehicle dynamics and within the railway industry. For this reason it is appropriate to collect and discuss the latest work, since there are no up-to-date detailed literature reviews available. This paper explores the present state-of-the-art of railway transition curves, and identifies some of the research challenges and future research opportunities in the field.

Multibody kinematics optimization (MKO) aims to reduce soft tissue artefact (STA) and is a key step in musculoskeletal modeling. The objective of this review was to identify the numerical methods, their validation and performance for the estimation of the human joint kinematics using MKO. Seventy-four papers were extracted from a systematized search in five databases and cross-referencing. Model-derived kinematics were obtained using either constrained optimization or Kalman filtering to minimize the difference between measured (i.e., by skin markers, electromagnetic or inertial sensors) and model-derived positions and/or orientations. While hinge, universal, and spherical joints prevail, advanced models (e.g., parallel and four-bar mechanisms, elastic joint) have been introduced, mainly for the knee and shoulder joints. Models and methods were evaluated using: (i) simulated data based, however, on oversimplified STA and joint models; (ii) reconstruction residual errors, ranging from 4 mm to 40 mm; (iii) sensitivity analyses which highlighted the effect (up to 36 deg and 12 mm) of model geometrical parameters, joint models, and computational methods; (iv) comparison with other approaches (i.e., single body kinematics optimization and nonoptimized kinematics); (v) repeatability studies that showed low intra- and inter-observer variability; and (vi) validation against ground-truth bone kinematics (with errors between 1 deg and 22 deg for tibiofemoral rotations and between 3 deg and 10 deg for glenohumeral rotations). Moreover, MKO was applied to various movements (e.g., walking, running, arm elevation). Additional validations, especially for the upper limb, should be undertaken and we recommend a more systematic approach for the evaluation of MKO. In addition, further model development, scaling, and personalization methods are required to better estimate the secondary degrees-of-freedom (DoF).

In this article, a state-of-the-art review on the impacts of Smart Grid in the operation and planning of the expansion of the Electric Power System is presented. The concept of Smart Grid is increasingly integrated in conventional networks, and the impact that this new technology generates on operation and planning must be investigated. Thus, in this article a survey of the main scientific publications was made with the purpose of determining the impacts and methodologies most used in this analysis. Efforts to analyze impacts are large because of the high degree of uncertainty of this new technology added to the problem. After the bibliographic survey, it was concluded that Robust Optimization and Genetic Algorithms are methodologies that are effective in problems of this nature and are the most adopted methods.

The last two decades have witnessed increasing awareness of the potential of terrestrial laser scanning (TLS) in forest applications in both public and commercial sectors, along with tremendous research efforts and progress. It is time to inspect the achievements of and the remaining barriers to TLS-based forest investigations, so further research and application are clearly orientated in operational uses of TLS. In such context, the international TLS benchmarking project was launched in 2014 by the European Spatial Data Research Organization and coordinated by the Finnish Geospatial Research Institute. The main objectives of this benchmarking study are to evaluate the potential of applying TLS in characterizing forests, to clarify the strengths and the weaknesses of TLS as a measure of forest digitization, and to reveal the capability of recent algorithms for tree-attribute extraction. The project is designed to benchmark the TLS algorithms by processing identical TLS datasets for a standardized set of forest attribute criteria and by evaluating the results through a common procedure respecting reliable references. Benchmarking results reflect large variances in estimating accuracies, which were unveiled through the 18 compared algorithms and through the evaluation framework, i.e., forest complexity categories, TLS data acquisition approaches, tree attributes and evaluation procedures. The evaluation framework includes three new criteria proposed in this benchmarking and the algorithm performances are investigated through combining two or more criteria (e.g., the accuracy of the individual tree attributes are inspected in conjunction with plot-level completeness) in order to reveal algorithms’ overall performance. The results also reveal some best available forest attribute estimates at this time, which clarify the status quo of TLS-based forest investigations. Some results are well expected, while some are new, e.g., the variances of estimating accuracies between single-/multi-scan, the principle of the algorithm designs and the possibility of a computer outperforming human operation. With single-scan data, i.e., one hemispherical scan per plot, most of the recent algorithms are capable of achieving stem detection with approximately 75% completeness and 90% correctness in the easy forest stands (easy plots: 600 stems/ha, 20 cm mean DBH). The detection rate decreases when the stem density increases and the average DBH decreases, i.e., 60% completeness with 90% correctness (medium plots: 1000 stem/ha, 15 cm mean DBH) and 30% completeness with 90% correctness (difficult plots: 2000 stems/ha, 10 cm mean DBH). The application of the multi-scan approach, i.e., five scans per plot at the center and four quadrant angles, is more effective in complex stands, increasing the completeness to approximately 90% for medium plots and to approximately 70% for difficult plots, with almost 100% correctness. The results of this benchmarking also show that the TLS-based approaches can provide the estimates of the DBH and the stem curve at a 1–2 cm accuracy that are close to what is required in practical applications, e.g., national forest inventories (NFIs). In terms of algorithm development, a high level of automation is a commonly shared standard, but a bottleneck occurs at stem detection and tree height estimation, especially in multilayer and dense forest stands. The greatest challenge is that even with the multi-scan approach, it is still hard to completely and accurately record stems of all trees in a plot due to the occlusion effects of the trees and bushes in forests. Future development must address the redundant yet incomplete point clouds of forest sample plots and recognize trees more accurately and efficiently. It is worth noting that TLS currently provides the best quality terrestrial point clouds in comparison with all other technologies, meaning that all the benchmarks labeled in this paper can also serve as a reference for other terrestrial point clouds sources.

We describe a state-of-the-art sentiment analysis system that detects (a) the sentiment of short informal textual messages such as tweets and SMS (message-level task) and (b) the sentiment of a word or a phrase within a message (term-level task). The system is based on a supervised statistical text classification approach leveraging a variety of surface-form, semantic, and sentiment features. The sentiment features are primarily derived from novel high-coverage tweet-specific sentiment lexicons. These lexicons are automatically generated from tweets with sentiment-word hashtags and from tweets with emoticons. To adequately capture the sentiment of words in negated contexts, a separate sentiment lexicon is generated for negated words. The system ranked first in the SemEval-2013 shared task `Sentiment Analysis in Twitter' (Task 2), obtaining an F-score of 69.02 in the message-level task and 88.93 in the term-level task. Post-competition improvements boost the performance to an F-score of 70.45 (message-level task) and 89.50 (term-level task). The system also obtains state-of-the-art performance on two additional datasets: the SemEval-2013 SMS test set and a corpus of movie review excerpts. The ablation experiments demonstrate that the use of the automatically generated lexicons results in performance gains of up to 6.5 absolute percentage points.

International audience; Electronic voting systems are those which depend on some electronic technology for their correct functionality. Many of them depend on such technology for the communication of election data. Depending on one or more communication channels in order to run elections poses many technical challenges with respect to verifiability, dependability, security, anonymity and trust. Changing the way in which people vote has many social and political implications. The role of election administrators and (independent) observers is fundamentally different when complex communications technology is involved in the process. Electronic voting has been deployed in many different types of election throughout the world for several decades. Despite lack of agreement on whether this has been a ‘success', there has been-in the last few years-enormous investment in remote electronic voting (primarily as a means of exploiting the internet as the underlying communication technology). This paper reviews the past, present and future of on-line voting. It reports on the role of technology transfer, from research to practice, and the range of divergent views concerning the adoption of on-line voting for critical elections

Building integrated photovoltaics (BIPVs) are photovoltaic (PV) modules integrated into the building envelope and hence also replacing traditional parts of the building envelope, e.g. the roofing. In this context, the BIPVs integration with the building envelope limits the costs by serving dual purposes. BIPVs have a great advantage compared to non-integrated systems because there is neither need for allocation of land nor stand-alone PV systems. This study seeks to outline various commercially available approaches to BIPVs and thus provides a state-of-the-art review. In addition, possible future research opportunities are explored. The various categories of BIPVs may be divided into photovoltaic foils, photovoltaic tiles, photovoltaic modules and solar cell glazings. Silicon materials are the most commonly used, and a distinction is made between wafer-based technologies and thin-film technologies. In addition, various non-silicon materials are available. The main options for building integration of PV cells are on sloped roofs, flat roofs and facades. The evaluation of the different BIPV products involves, among others, properties such as solar cell efficiency, open circuit voltage, short circuit current, maximum effect and fill factor. It is expected that the BIPV systems will improve in the years to come, regarding both device and manufacturing efficiency. The future seems very promising in the BIPV industry, both concerning new technologies, different solutions and the variety of BIPV options. © 2011 Elsevier B.V. All rights reserved. This is the authors' accepted and refereed manuscript to the article.

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2011 Springer Verlag Olfaction—or smell—is one of the last challenges which multimedia and multimodal applications have to conquer. Enhancing such applications with olfactory stimuli has the potential to create a more complex—and richer—user multimedia experience, by heightening the sense of reality and diversifying user interaction modalities. Nonetheless, olfaction-enhanced multimedia still remains a challenging research area. More recently, however, there have been initial signs of olfactory-enhanced applications in multimedia, with olfaction being used towards a variety of goals, including notification alerts, enhancing the sense of reality in immersive applications, and branding, to name but a few. However, as the goal of a multimedia application is to inform and/or entertain users, achieving quality olfaction-enhanced multimedia applications from the users’ perspective is vital to the success and continuity of these applications. Accordingly, in this paper we have focused on investigating the user perceived experience of olfaction-enhanced multimedia applications, with the aim of discovering the quality evaluation factors that are important from a user’s perspective of these applications, and consequently ensure the continued advancement and success of olfaction-enhanced multimedia applications.

One of the key characteristics that are expected from a contemporary instructor is being able to creatively implement innovation in his/her day-to-day teaching activities. An example of such innovative approaches to teaching is the integrated teaching of, for instance, STEM subjects with foreign languages (FL). The latter can be successfully achieved via technology-enhanced learning (TEL) approach. Currently, there are numerous apps and platforms available or still being developed for teaching STEM subjects, which could be combined with learning FLs in order to ensure successful learning outcomes even more. However, the full educational potential of TEL tools for teaching FLs should be investigated and disclosed beforehand. To this end, the present paper provides an overview of the most recent developments in technology-enhanced language learning (TELL). It firstly surveys state-of-the art and then gives an insight into what to expect from the near future studies on TELL.

International audience; In this paper we present an update on the geometric modeling of urban scenes from physical measurements. This field of research has been studied for more than thirty years, but remains an important challenge in many scientific communi-ties as photogrammetry, computer vision, robotics or computer graphics. After introducing the objectives and difficulties of urban reconstruction, we present an non-exhaustive overview of the approaches and trends that have inspired the research communities so far. We also propose some new research directions that might be worth investigating in the coming years.

Historical analysis of the evolution of context-based approaches in different research communities.Survey and discussion of context representation and techniques in mobile and pervasive computing, image processing, AI.Survey and discussion of context-based approaches in Information Fusion from a JDL perspective.Discussion and insights on key context concepts across different domains and their impacts on fusion systems.Proposal of novel architectural design aspects for context-aware fusion systems. This survey aims to provide a comprehensive status of recent and current research on context-based Information Fusion (IF) systems, tracing back the roots of the original thinking behind the development of the concept of "context". It shows how its fortune in the distributed computing world eventually permeated in the world of IF, discussing the current strategies and techniques, and hinting possible future trends. IF processes can represent context at different levels (structural and physical constraints of the scenario, a priori known operational rules between entities and environment, dynamic relationships modelled to interpret the system output, etc.). In addition to the survey, several novel context exploitation dynamics and architectural aspects peculiar to the fusion domain are presented and discussed.

International audience; The design of sustainable wireless sensor networks (WSNs) is a very challenging issue. On the one hand, energy-constrained sensors are expected to run autonomously for long periods. However, it may be cost-prohibitive to replace exhausted batteries or even impossible in hostile environments. On the other hand, unlike other networks, WSNs are designed for specific applications which range from small-size healthcare surveillance systems to large-scale environmental monitoring. Thus, any WSN deployment has to satisfy a set of requirements that differs from one application to another. In this context, a host of research work has been conducted in order to propose a wide range of solutions to the energy-saving problem. This research covers several areas going from physical layer optimization to network layer solutions. Therefore, it is not easy for the WSN designer to select the efficient solutions that should be considered in the design of application-specific WSN architecture. We present a top-down survey of the trade-offs between application requirements and lifetime extension that arise when designing wireless sensor networks. We first identify the main categories of applications and their specific requirements. Then we present a new classification of energy-conservation schemes found in the recent literature, followed by a systematic discussion as to how these schemes conflict with the specific requirements. Finally, we survey the techniques applied in WSNs to achieve trade-off between multiple requirements, such as multi-objective optimisation.

As an area, Technology Enhanced Learning (TEL) aims to design, develop and test socio-technical innovations that will support and enhance learning practices of individuals and organizations. Information retrieval is a pivotal activity in TEL and the deployment of recommender systems has attracted increased interest during the past years. Recommendation methods, techniques and systems open an interesting new approach to facilitate and support learning and teaching. The goal is to develop, deploy and evaluate systems that provide learners and teachers with meaningful guidance in order to help identify suitable learning resources from a potentially overwhelming variety of choices. Contributions address the following topics: i) user and item data that can be used to support learning recommendation systems and scenarios, ii) innovative methods and techniques for recommendation purposes in educational settings and iii) examples of educational platforms and tools where recommendations are incorporated.

International audience; Line balancing belongs to a class of intensively studied combinatorial optimization problems known to be NP-hard in general. For several decades, the core problem originally introduced for manual assembly has been extended to suit robotic, machining and disassembly contexts. However, despite various industrial environments and line configurations, often quite similar or even identical mathematical models have been developed. The objective of this survey is to analyze recent research on balancing flow lines within many different industrial contexts in order to classify and compare the means for input data modelling, constraints and objective functions used. This survey covers about 300 studies on line balancing problems. Particular attention is paid to recent publications that have appeared in 2007-2012 to focus on new advances in the state-of-the-art.

Self-cleaning technology is used in a variety of products today, with glazing products being the foremost area of application. However, there are several self-cleaning technologies in use and their self-cleaning efficiency may be unclear. This study aims to give a comprehensive state-of-the-art review of the self-cleaning glazing products available on the market today and investigate methods for measuring the self-cleaning effect. Various future research pathways and opportunities for the self-cleaning products of tomorrow are also explored within this study, with emphasis on solar energy application areas such as daylight, solar radiation transmission, electrochromism, building integrated photovoltaics (BIPV), solar cell glazing and solar cells in general. Self-cleaning products from several manufacturers that utilize two different self-cleaning technologies of either photocatalytic hydrophilic or hydrophobic capability are presented. The photocatalytic hydrophilic products in question are self-cleaning glazing products ready-to-use when purchased, whilst the presented hydrophobic products are coatings that must be applied to existing glazing products in order to yield a water-repellent and self-cleaning surface. It is stated that the self-cleaning action of the photocatalytic hydrophilic products is evident through 25–30 years, even during dry spills, and that they are able to maintain a cleaner surface than ordinary untreated float glass. However, the self-cleaning action of hydrophobic-coated products is limited by a relatively short life expectancy of about 3–4 years, and their self-cleaning performance is found to be feeble compared to ordinary untreated float glass. Nonetheless, the potential for future use of both self-cleaning technologies are apparent, with focus on alternative application areas such as solar cells, BIPV and information display devices, which indeed could benefit from utilizing the self-cleaning technology. Visions for future self-cleaning products are also discussed, which combine self-cleaning abilities with photovoltaism and electrochromism, whereupon the applicability of the self-cleaning technology may be greatly increased. (c) 2012Elsevier B.V. All rights reserved. This is the authors' accepted and refereed manuscript to the article, post-print. Released with a Creative Commons Attribution Non-Commercial No Derivatives License.

Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organizations. It is therefore an application domain that generally covers technologies that support all forms of teaching and learning activities. Since information retrieval (in terms of searching for relevant learning resources to support teachers or learners) is a pivotal activity in TEL, the deployment of recommender systems has attracted increased interest. This chapter attempts to provide an introduction to recommender systems for TEL settings, as well as to highlight their particularities compared to recommender systems for other application domains.

Author to whom correspondence should be addressed;E-Mail: delphine.christin@seemoo.tu-darmstadt.de; Tel.: +49 6151 16-70923Received: 30 January 2010; in revised form: 19 March 2010 / Accepted: 24 March 2010 /Published: 8 April 2010Abstract: Wireless Sensor Networks (WSNs) are gradually adopted in the industrial worlddue to their advantages over wired networks. In addition to saving cabling costs, WSNswiden the realm of environments feasible for monitoring. They thus add sensing and act-ing capabilities to objects in the physical world and allow for communication among theseobjects or with services in the future Internet. However, the acceptance of WSNs by theindustrial automation community is impeded by open issues, such as security guarantees andprovision of Quality of Service (QoS). To examine both of these perspectives, we select andsurvey relevant WSN technologies dedicated to industrial automation. We determine QoSrequirements and carry out a threat analysis, which act as basis of our evaluation of the cur-rent state-of-the-art. According to the results of this evaluation, we identify and discuss openresearch issues.Keywords: Wireless Sensor Networks; Industrial Automation; Quality of Service; Security;State-of-the-art; WirelessHART; ISA100.11a-2009; ZigBee; Wireless Interface for Sensorsand Actuators ; 802.15.4e Factory Automation MAC Layer

This paper provides a reference model for mobile social software and uses it to analyse the current state-of-the-art in its applications for learning. A general overview of the literature in the field and the available projects will be given. The reference model for mobile social software helps to (1) find out to what extend mobile social software for learning has already been used to this date, (2) identify gaps and limitations in current research and provide new ideas and innovative approaches for learning based on these gaps, and (3) position our current research work in preparation of a study of applications of mobile social software for learning. After describing the current state-of-the-art, its limitations, and suggestions for future research, an implemented solution of mobile social software for learning is shortly described. The paper concludes with an outlook on possible chances and challenges for future research.

International audience; The work presented in this paper is related to the area of Situational Method Engineering (SME) which focuses on project-specific method construction. We propose a faceted framework to understand and classify issues in system development SME. The framework identifies four different but complementary viewpoints. Each view allows us to capture a particular aspect of situational methods. Inter-relationships between these views show how they influence each other. In order to study, understand and classify a particular view of SME in its diversity, we associate a set of facets with each view. As a facet allows an in-depth description of one specific aspect of SME, the views show the variety and diversity of these aspects.