Collaborative Interorganizational Relationships in a Project-Based Industry

The project-based construction industry finds itself in a paradoxical situation: while it weighs heavily in the world economy, it does have a history of low productivity. One important issue that plagues the industry is related to the challenges that stem from collaborative efforts (or lack thereof) between actors. The objective of this paper is to explore how actors of the construction industry organize their inter-firm relationships while examining the characteristics of such interactions and the elements affecting them (drivers, barriers, facilitators, outcomes). These interactions and elements were uncovered using a systematic literature review. A qualitative content analysis was carried out to categorize these elements and to generate dimensions describing the forms. The 139 articles retrieved depicted 12 relational forms established between construction companies (in descending order of citation): partnering, alliancing, project delivery methods, supply chain integration, joint ventures, integrated project delivery, joint risk management, collaborative design, contingent collaboration, quasi-fixed network, resource sharing, and collaborative planning. A multitude of drivers, barriers, facilitators, and outcomes were found. An analysis of the results led to the conceptualization of a multidimensional profile, which allows for a practical and flexible identification of the relationship form potential partners in the construction sector intend to establish. To provide guidelines for the implementation of this profile, a three-step framework was developed

Deep Multi-modal Object Detection for Autonomous Driving

International audienc

A Distributed Rate-Control Approach to Reduce Communication Burdens in VSNs

In visual sensor networks, the analyze-then-compress paradigm, where each camera process data and extract local features, is proved to be an efficient approach to reduce the amount of transmitted information. The bitrate can be further reduced by efficiently compressing the extracted features using a distributed feature coding technique. However, since the rate control is performed at the decoder, an abundant use of the feedback channel is needed to adjust the coding rate. Moreover, transmitting all extracted features, including irrelevant ones with no further contribution to the application accuracy, overloads the network. In this paper, we propose a novel feature selection and distributed coding rate control strategies that cope with these issues. The proposed strategies are designed to significantly reduce the transmitted bitrate and the communication burden with the sink, which implicitly reduces the energy consumption and the decoding delay. We show that, wisely selecting at the camera sensors level only the features effectively contributing to the application accuracy reduces the amount of transmitted information up to 34% while preserving accuracy. Furthermore, the cameras can collaborate periodically, by exchanging small amount of information about their selected features, to estimate the minimum transmission rate required for each feature based on a linear fitting model that takes into consideration the inter-camera correlation and the channel conditions. Significant average bitrate savings, reaching up to 37.71%, are achieved

A Comparative Evaluation of Well-known Feature Extractors for Multi-view Vehicle Tracking in VSNs

The choice of local features to use for feature-based vehicle tracking application is of great importance since the tracking accuracy depends directly on the robustness of the extracted features. Aside of the efficiency of features in terms of analysis accuracy, considering the computation speed and the required transmission bitrate in the choice of the feature extraction algorithm is crucial in order to design a system suitable for the constrained resources of visual sensor networks. In this paper, we evaluate the performance of the four most well-know algorithms for feature detection and extraction, SIFT, SURF, ORB, and BRISK, according to their contribution to the multi-view vehicle matching accuracy, to their computational speed, and to their demands in transmission bitrate. From the obtained results, we deduce that SIFT is the most accurate feature extractor for matching vehicle from two different views, but at the same time, is the most expensive algorithm. ORB is the fastest algorithm with lower matching accuracy compared to SIFT. BRISK represents a good compromise between the computation cost and the matching accuracy

Fast Converging ADMM Penalized Algorithm for LDPC Decoding

International audienceThe alternate direction method of multipliers (ADMM) approach has been recently considered for LDPC decoding. It has been approved to enhance the error rate performance compared with conventional message passing (MP) techniques in both the waterfall and error floor regions at the cost of a higher computation complexity. In this letter, a formulation of the ADMM decoding algorithm with modified computation scheduling is proposed. It increases the error correction performance of the decoding algorithm and reduces the average computation complexity of the decoding process thanks to a faster convergence. Simulation results show that this modified scheduling speeds up the decoding procedure with regards to the ADMM initial formulation while enhancing the error correction performance. This decoding speed-up is further improved when the proposed scheduling is teamed with a recent complexity reduction method detailed in [1] (Wei et al. IEEE Communications Letters 2015)

The diagnosis of tuberculosis in dialysis patients

The incidence of tuberculosis (TB) is high in patients undergoing chronic dialysis than it is in the general population. The diagnosis of TB is often difficult and extrapulmonary involvement is predominant. This study investigates the spectrum of clinical presentations and outcome in dialysis patients during a nine-year period. TB was diagnosed in 41 patients. Anti-TB drugs, adverse effects of therapy, and outcome were noted. Thirty-eight patients (92.6%) were on hemodialysis and three were on peritoneal dialysis (7.3%). The mean age at diagnosis was 50.8 years and the male/female ratio was 1.16. Four patients had a history of pulmonary TB. Extrapulmonary involvement was observed in 32 (78 %) patients. The bacteriological confirmation was made in 41.46% and histological confirmation was made in 26.83%, and in the rest, the diagnosis was retained on the criterion presumption. Nineteen patients (46.34%) developed adverse effects of antitubercular drugs. Eight patients (19.51%) died during the study from TB or adverse effects of treatment. Low urea reduction ratio and female sex were associated with poor prognosis in our study. The clinical manifestations of TB in patients on dialysis are quite nonspecific, making timely diagnosis difficult, and delaying the initiation of curative treatment, which is a major determinant of the outcome