Improved Energy Detector for Wideband Spectrum Sensing in Cognitive Radio Networks

In this paper, an improved energy detector for a wideband spectrum sensing is proposed. For a better detection of the spectrum holes the overall band is divided into equal non-overlapping sub-bands. The main objective is to determine the detection thresholds for each of these subbands jointly. By defining the problem as an optimization problem, we aim to find the maximum aggregated opportunistic throughput of cognitive radio networks. Introducing practical constraints to this optimization problem will change the problem into a convex and solvable one. The results of this paper show that the proposed improved energy detector will increase the aggregated throughput considerably

Estimation of nearshore wave transmission for submerged breakwaters using a data-driven predictive model

The functional design of submerged breakwaters is still developing, particularly with respect to modelling of the nearshore wave field behind the structure. This paper describes a method for predicting the wave transmission coefficients behind submerged breakwaters using machine learning algorithms. An artificial neural network using the radial-basis function approach has been designed and trained using laboratory experimental data expressed in terms of non-dimensional parameters. A wave transmission coefficient calculator is presented, based on the proposed radial-basis function model. Predictions obtained by the radial-basis function model were verified by experimental measurements for a two dimensional breakwater. Comparisons reveal good agreement with the experimental results and encouraging performance from the proposed model. Applying the proposed neural network model for predictions, guidance is given to appropriately calculate wave transmission coefficient behind two dimensional submerged breakwaters. It is concluded that the proposed predictive model offers potential as a design tool to predict wave transmission coefficients behind submerged breakwaters. A step-by-step procedure for practical applications is outlined in a user-friendly form with the intention of providing a simplified tool for preliminary design purposes. Results demonstrate the model’s potential to be extended to three dimensional, rough, permeable structures

Association of characteristics of delivery and medical conditions during the first month of life with developmental defects of enamel.

BACKGROUND: Developmental defects of enamel (DDE) may be influenced by health problems and illness in children. The aim of the study was to identify the main characteristics of birth (delivery) and adverse medical conditions during the first month of life that may be related to DDE in permanent teeth. METHODS: 1000 schoolchildren between the ages of 9 and 11 years were selected for this cross-sectional study by multistage randomization from four educational zones in Shiraz in 2013. Intraoral examination was used to diagnose DDE according to World Health Organization screening guidelines and the Modified DDE Index. The data on seven birth factors as well as health and nutritional conditions during the first month of life were collected by a questionnaire completed by the parents, and were analyzed with the chi-squared test, Spearman's correlation and binary logistic regression. RESULTS: 469 (48.2%) out of 974 schoolchildren had at least one permanent tooth with DDE. The defects were significantly related with Apgar score at birth <7 (p = 0.003) and illness during the first month (p = 0.035). The frequency of DDE was significantly lower in the third child in families compared to the first and second child (p = 0.005). However, DDE showed no significant relationship with gestational age, delivery type, birth weight, gender or type of feeding during early infancy. CONCLUSIONS: Three associated factors were identified (birth Apgar score, illness during the first month of life, birth order) for DDE in permanent teeth. No specific illness was found to be significantly associated with DDE

A novel real-time detailed feedback collection and interaction tool for large classes

CONTEXT The existing approaches towards interactive student feedback and question collection have two major drawbacks. First, instructors are only provided with generic feedback, typically at the end of a teaching period. Second, students are not provided with opportunity to give content-specific feedback or raise questions on specific sections of content during the lecture. The latter is especially important in large classes with students from non-English speaking background who are generally less likely to actively participate in discussions. PURPOSE This paper aims to develop and test a user-friendly and automated platform, with efficient data management structure, which facilitates real-time collection and addressing of students’ feedback on a specific part of topics discussed during the class. APPROACH A web-based software has been developed using annotation technologies which assists students in providing anonymous and content-specific comments on lecture materials. The software equips lecturers with a real-time platform for retrieval of comments classified based on their area, type and frequency. The platform contains features that enable users, teachers, for analytical assessment of both teaching and learning performance. RESULTS The trial use of the designed platform has primarily increased engagement of students in the class discussions. This trend is specifically observed amongst international students who have gained confidence to raise more questions, compared to the traditional teaching methods. Concurrently, the lecturer has dramatically decreased his response period to students’ queries to nearly real-time through receiving classified comments adhered to a particular part of the lecture. CONCLUSIONS The software allows for structured analysis of course materials and students’ feedback which can be further used to update teaching standards. Moreover, it improves teacher-student relationships through timely and purposeful addressing of instructional issues

A Novel Demand Response Management Model to Reduce Smart Grid Costs

DRM means leveling demand curve based on electricity prices. Indeed, using variable price rates, electricity consumers are encouraged to use electricity in periods with cheap electricity price ranges. Therefore, total system cost would decrease efficiently. Motivations: To model dynamics between electricity end-users and utility companies. To present a model with simple implementation on smart households. To reduce electricity production costs and to maximize social welfare.Electrical and Computer Engineering, Department o

Modelling the transport and decay processes of microbial tracers released in a macro-tidal estuary

The Loughor Estuary is a macro-tidal coastal basin, located along the Bristol Channel, in the South West of the U.K. The maximum spring tidal range in the estuary is up to 7.5 m, near Burry Port Harbour. This estuarine region can experience severe coastal flooding during high spring tides, including extreme flooding of the intertidal saltmarshes at Llanrhidian, as well as the lower industrial and residential areas at Llanelli and Gowerton. The water quality of this estuarine basin needs to comply with the designated standards for safe recreational bathing and shellfish harvesting industries. The waterbody however, potentially receives overloading of bacterial inputs that enter the estuarine system from both point and diffuse sources. Therefore, a microbial tracer study was carried out to get a better understanding of the faecal bacteria sources and to enable a hydro-environmental model to be refined and calibrated for both advection and dispersion transport. A two-dimensional hydro-environmental model has been refined and extended to predict the highest water level covering the intertidal floodplains of the Loughor Estuary. The validated hydrodynamic model for both water levels and currents, was included with the injected mass of microbial tracer, i.e. MS2 coliphage from upstream of the estuary, and modelled as a non-conservative tracer over several tidal cycles through the system. The calibration and validation of the transport and decay of microbial tracer was undertaken, by comparing the model results and the measured data at two different sampling locations. The refined model developed as a part of this study, was used to acquire a better understanding of the water quality processes and the potential sources of bacterial pollution in the estuary