Timetable and vehicle scheduling are important for transit operations. Electric buses more environmentally friendly compared with conventional buses, have been developing rapidly may replace in many cities worldwide. This paper focuses on the bus timetabling problem electric develops a multiobjective optimization model single line operated buses. The objectives include smoothing departure intervals minimizing number of vehicles total charging costs. constraints reflect limitations related to...

The prime motivation of our work is to balance the inherent trade-off between resource consumption and accuracy target tracking in wireless sensor networks. Toward this objective, study goes through three phases. First, a cluster-based scheme exploited. At every sampling instant, only one cluster sensors that located proximity activated, whereas other are inactive. To activate most appropriate cluster, we propose nonmyopic rule, which based on not state prediction but also its future...

The tracking of a moving target in wireless sensor network (WSN) requires exact knowledge positions. However, precise information about locations is not always available. Given the observation that series measurements are generated sensors when moves through field, we propose an algorithm exploits these to simultaneously localize detecting and track (SLAT). main difficulties encountered this problem ambiguity locations, unrestricted manner, extremely constrained resources WSNs. Therefore,...

Abstract Analyzing survival rates for lung cancer presently grapples with two significant hurdles. Insufficient available data is the first one, which exacerbated by a large amount of censored information, thereby obstructing effective employment this accurate predictions. Second, patient often exhibit complex temporal feature associations, suggesting patient‐specific traits on outcomes. To address these issues, dataset are augmented integrating semi‐supervised learning, allows more use...

A fundamental assumption underlying most studies of optical burst switched (OBS) networks is that full wavelength conversion available throughout the network. In practice, however, economic and technical considerations are likely to dictate a more limited sparse deployment converters in Therefore, we expect assignment policies be an important component OBS networks. this paper, explain why selection schemes developed for routed (circuit-switched) not appropriate OBS. We then develop suite...

Abstract miRNAs are expected to become potential biomarkers in the diagnosis and prognosis of Esophageal cancer (EC). Through a series screening, miR-34a-5p, miR-148a-3p miR-181a-5p were selected as EC-associated miRNAs. Based on AllGlo probe, novel absolute quantitative RT-qPCR method with high sensitivity, specificity accuracy was established for detecting Then clinical significance these 3 explored 213 patients (166 cases EC 47 benign diseases) 170 normal controls. Compared controls,...

Various cognitive disorders have been reported for mild traumatic brain injury (mTBI) patients during the acute stage. This stage provides an opportunity clinicians to optimize treatment protocols, which are based on evaluation of structural connectivity. So far, most functional magnetic resonance imaging studies focused moderate severe injuries (TBIs). In this study, we prospectively collected resting state data 50 mTBI within 3 days and healthy volunteers analyzed them using Amplitude...

Predicting breast cancer survival and targeting patients at high-risk of mortality is crucial importance. We built a Bayesian Dynamic Cox (BDCox) model for predicting 5-year overall in using data the SEER Cancer Registry with 12,840 women. Four feature selection methods were used to identify predictors enhance parsimony: fast backward variable selection, elastic net, Model Average (BMA), clinical expertise. All resulting models baseline full containing all features internally validated via...

Objective: We evaluated the prognostic value of lymph node ratio (LNR) for survival breast cancer patients using Bayesian inference. Methods: Data on 5,279 women with infiltrating duct and lobular carcinoma cancer, diagnosed from 2006-2010, was obtained NCI SEER Cancer Registry. A modeling framework proposed inference to estimate impact LNR in survival. Based model, we then developed a web application estimating predicting overall Results: The final model outperformed other models considered...

It is usually assumed that optical burst switching (OBS) networks use the shortest path routing along with next-hop forwarding. The minimizes delay and optimizes utilization of resources, however, it often causes certain links to become congested while others remain underutilized. In a bufferless OBS network in which drop probability primary metric interest, existence few highly could lead unacceptable performance for entire network. We take traffic engineering approach selection objective...

Target tracking in wireless sensor networks (WSN) has brought up new practical problems. The limited energy supply and bandwidth of WSN have put stringent constraints on the complexity inter-node information exchange algorithm. In this paper, we propose a binary variational algorithm outperforming existing target algorithms such as Kalman Particle filtering. formulation allows an implicit compression exchanged statistics between leader nodes, enabling thus distributed decision-making. Its...

Soft computing is facing a rapid evolution thanks to the development of artificial intelligence especially deep learning. With video surveillance technologies soft computing, such as image processing, computer vision, and pattern recognition combined with cloud construction smart cities could be maintained greatly enhanced. In this article, we focus on online detection action start task in understanding analysis, which critical multimedia security cities. We propose novel model tackle...

The wind power industry continues to experience rapid growth worldwide. However, the fluctuations in speed and direction complicate turbine control process hinder integration of into electrical grid. To maximize utilization, we propose precisely measure a three-dimensional (3D) space, thus facilitating control. Natural is regarded as 3D vector, whose magnitude correspond wind's speed. A semi-conical ultrasonic sensor array proposed simultaneously space. As signal transmitted between sensors...

In this era, every field requires high availability of network with the least probability data loss. Therefore, redundancy should be involved as much possible for design. However, necessitates higher managerial and operational cost. Redundancy protocols substantially help to solve problem. First Hop Protocols (FHRPs) are implemented overcome traffic loss from source destination in communications. The FHRP consists different types protocols. Each protocol has its own purpose advantages...

A collaborative variational/Monte Carlo scheme is proposed to solve the multi-target tracking (MTT) problem in wireless sensor networks (WSNs). The prime motivation of our work balance inherent trade-off between resource consumption and accuracy target tracking. For sake efficiency, we reduce MTT distributed cluster-based variational when targets are far apart; switch data association only gathered, leading ambiguous measurements. sequential Monte (SMC) method employed assign measurements...

In indoor positioning, signal fluctuation is one of the main factors affecting positioning accuracy. To solve this problem, a new method based on an integration empirical mode decomposition threshold smoothing (EMDT) and improved weighted K nearest neighbor (WKNN), named EMDT-WKNN, proposed in paper. First, nonlinear non-stationary received strength indication (RSSI) sequences are constructed. Secondly, intrinsic functions (IMF) selection criteria energy analysis coefficients proposed....

This paper studies the important fault management issue with focus on fast restoration mechanisms for optical burst switched (OBS) networks. In order to reduce losses during process, effective schemes are necessary. is illustrated via two basic schemes, distributed deflection scheme and local scheme, compared slow global routing update mechanism. A novel priority-based QoS also proposed provide differentiated services. Through detailed descriptive analysis a comprehensive simulation study,...

Abstract The key impediments to a successful wireless sensor network (WSN) application are the energy and longevity constraints of nodes. Therefore, two signal processing oriented cluster management strategies, proactive reactive management, proposed efficiently deal with these constraints. former strategy is designed for heterogeneous WSNs, where sensors organized in static clustering architecture. A non‐myopic activation rule realized reduce number hand‐off operations between clusters,...

Resource limitations in wireless sensor networks have put stringent constraints on distributed signal processing. In this paper, we propose a cluster-based decentralized variational filtering algorithm with minimum resource allocation for simultaneous localization and target tracking. At each sampling instant, only one cluster of sensors is activated according to the prediction state. Slave employ binary proximity observation model reduce energy consumption minimize communication cost. Based...

An efficient, economical and robust strategy for target tracking in binary sensor network is proposed this paper. By adopting the variational filtering algorithm, considerable quality ensured, while decreasing communication between sensors compared to a particle algorithm. Based on proactive clustering, entire subdivided into several clusters. Only cluster heads are configured with more available energy high processing capability, reducing thus hardware expenditure. Furthermore, precise...