Energy balanced data gathering approaches,issues and research directions

Telecommunication Systems - Wireless sensor networks (WSNs) and Internet of Things domain comprise of numerous small sized battery powered sensor nodes. Energy efficiency and energy balancing are...     

RAPTAP: a socio-inspired approach to resource allocation and interference management in dense small cells

Wireless Networks - Femto Cells offer higher data rates to users within closed spaces. Dense deployment of small cells is a characteristic of pre-5G/LTE-Advanced Pro (LTE-A Pro) networks and is a...     

Medical image detection and azithromycin in the treatment of pelvic inflammation based on intelligent hospital system

The pelvic infection and people genital tract inflammation, infertility, chronic pain, and reasons for detecting ectopic pregnancy. Diagnostic and management challenges, from different signs and symptoms and a variety of microbial etiology is not fully delineated largely responsible. Because of the potential for serious things of the network, it is recommended for the diagnosis and treatment of low barriers to entry. One of pelvic inflammatory infection of pregnant woman of childbearing age is not the most testing an important public pelvic problem remains. This is the main long-term internet of things, such as tubal factor infertility, ectopic pregnancy and chronic pelvic pain. Also, acute care and its complications lead to significant pelvic care costs. These long-term preventions of the internet of things depend on the microbial cause of acute knowledge of strategies based on treatment. All aware that it is a polymicrobic acute infection. Organisms, Chlamydia trachomatis and Neisseria gonorrhoeae sexually transmit presence, in many cases, including the endogenous vaginal and cervical flora often associated with microorganisms. It contains anaerobic and facultative bacteria similar to those associated with bacterial most importantly mycoplasma has also recently been involved in acute reasons. Therefore, a therapeutic regimen for acute should provide a wide spectral range that is effective against these microorganisms.     

Research on topology control based on Voronoi diagram algorithm in FSO networks

Telecommunication Systems - In a wireless sensor network (WSN) where positioning information is not assumed or is partially available, efficient data access is a very challenging issue especially...     

Correction to: Cloud-based vehicular networks: a taxonomy,survey, and conceptual hybrid architecture

Wireless Networks - The original version of this article unfortunately contained a mistake in the title. The correct title has been published with this erratum.     

ANT-colony based disjoint set assortment in wireless sensor networks

Wireless Networks - Wireless sensor network (WSN) consists of small sized devices containing different sensors to monitor physical, environmental and medical conditions during surveillance of...     

Maximum Data Generation Rate Routing Protocol Based on Data Flow Controlling Technology for Rechargeable Wireless Sensor Networks

For rechargeable wireless sensor networks, limited energy storage capacity, dynamic energy supply, low and dynamic duty cycles cause that it is unpractical to maintain a fixed routing path for packets delivery permanently from a source to destination in a distributed scenario. Therefore, before data delivery, a sensor has to update its waking schedule continuously and share them to its neighbors, which lead to high energy expenditure for reestablishing path links frequently and low efficiency of energy utilization for collecting packets. In this work, we propose the maximum data generation rate routing protocol based on data flow controlling technology. For a sensor, it does not share its waking schedule to its neighbors and cache any waking schedules of other sensors. Hence, the energy consumption for time synchronization, location information and waking schedule shared will be reduced significantly. The saving energy can be used for improving data collection rate. Simulation shows our scheme is efficient to improve packets generation rate in rechargeable wireless sensor networks.     

Multiple Empirical Kernel Learning with Majority Projection for imbalanced problems

Traditional Multiple Empirical Kernel Learning (MEKL) expands the expressions of the sample and brings better classification ability by using different empirical kernels to map the original data space into multiple kernel spaces. To make MEKL suit for the imbalanced problems, this paper introduces a weight matrix and a regularization term into MEKL. The weight matrix assigns high misclassification cost to the minority samples to balanced misclassification cost between minority and majority class. The regularization term named Majority Projection (MP) is used to make the classification hyperplane fit the distribution shape of majority samples and enlarge the between-class distance of minority and majority class. The contributions of this work are: (i) assigning high cost to minority samples to deal with imbalanced problems, (ii) introducing a new regularization term to concern the property of data distribution, (iii) and modifying the original PAC-Bayes bound to test the error upper bound of MEKL-MP. Through analyzing the experimental results, the proposed MEKL-MP is well suited to the imbalanced problems and has lower generalization risk in accordance with the value of PAC-Bayes bound.     

A robust locating multi-optima approach for damage identification of plate-like structures

This paper proposes a robust optimization approach for multiple damage identification of plate-like structures. Different from traditional particle swarm optimizations (PSOs), a combined PSO and niche technique (NPSO) is proposed to solve multimodal optimization problems, with the full consideration of subswarm creation, merging and absorbing mechanism. As a hypersensitive parameter to damage, the curvature mode shape is adopted to construct the objective function. Case studies are conducted to investigate the effectiveness and robustness of the algorithm on multi-damage identification. Simulation results show that the proposed algorithm exhibits robust search performance on identifying damage locations accurately with good convergence behavior. It is hoped that this study can provide guidance on robust damage detection, especially when the structure is subject to multiple damages and external disturbances.