Neighbor Constraint Assisted Distributed Localization for Wireless Sensor Networks

Localization is one of the most significant technologies in wireless sensor networks (WSNs) since it plays a critical role in many applications. The main idea in most localization methods is to estimate the sensor-anchor distances that are used by sensors to locate themselves. However, the distance information is always imprecise due to the measurement or estimation errors. In this work, a novel algorithm called neighbor constraint assisted distributed localization (NCA-DL) is proposed, which introduces the application of geometric constraints to these distances within the algorithm. For example, in the case presented here, the assistance provided by a neighbor will consist in formulating a linear equality constraint. These constraints can be further used to formulate optimization problems for distance estimation. Then through some optimization methods, the imprecise distances can be refined and the localization precision is improved

Stability of a class of multi-agent tracking systems with unstable subsystems

In this work, we pre-deploy a large number of smart agents to monitor an area of interest. This area could be divided into many Voronoi cells by using the knowledge of Voronoi diagram and every Voronoi site agent is responsible for monitoring and tracking the target in its cell. Then, a cooperative relay tracking strategy is proposed such that during the tracking process, when a target enters a new Voronoi cell, this event triggers the switching of both tracking agents and communication topology. This is significantly different from the traditional switching topologies. In addition, during the tracking process, the topology and tracking agents switch, which may lead the tracking system to be stable or unstable. The system switches either among consecutive stable subsystems and consecutive unstable subsystems or between stable and unstable subsystems. The objective of this paper is to design a tracking strategy guaranteeing overall successful tracking despite the existence of unstable subsystems. We also address extended discussions on the case where the dynamics of agents are subject to disturbances and the disturbance attenuation level is achieved. Finally, the proposed tracking strategy is verified by a set of simulations

A novel industrial intrusion detection method based on threshold-optimized CNN-BiLSTM-attention using ROC curve

In recent years, many researchers have proposed many intrusion detection methods to protect the industrial network. However, there are two existing problems among them: one is that they only consider the overall accuracy rate (AC) while ignoring the problem of class imbalance; another one is that they have considered the problem of class imbalance, but the detection rate (DR) is low and false positive rate (FR) is high for minority classes. In order to improve AC and DR of minority classes, we propose a method called threshold-optimized CNN-BiLSTM-Attention that combines CNN-BiLSTM-Attention model, with threshold modification method based on receiver operating characteristic (ROC) curve. In this method, we use CNN-BiLSTM-Attention model as a classifier and modify threshold of the classifier through ROC curve. To evaluate the proposed method, we have performed experiments on the standard industrial data set. And the experimental results show that the proposed method can improve AC and the DR of minority classes at low FR, which is better than other intrusion detection methods

Glycated Haemoglobin A1c Variability Score Elicits Kidney Function Decline in Chinese People Living with Type 2 Diabetes

Our aim was to investigate the association of glycated haemoglobin A1c (HbA1c) variability score (HVS) with estimated glomerular filtration rate (eGFR) slope in Chinese adults living with type 2 diabetes. This cohort study included adults with type 2 diabetes attending outpatient clinics between 2011 and 2019 from a large electronic medical record-based database of diabetes in China (WECODe). We estimated the individual-level visit-to-visit HbA1c variability using HVS, a proportion of changes in HbA1c of ≥0.5% (5.5 mmol/mol). We estimated the odds of people experiencing a rapid eGFR annual decline using a logistic regression and differences across HVS categories in the mean eGFR slope using a mixed-effect model. The analysis involved 2397 individuals and a median follow-up of 4.7 years. Compared with people with HVS ≤ 20%, those with HVS of 60% to 80% had 11% higher odds of experiencing rapid eGFR annual decline, with an extra eGFR decline of 0.93 mL/min/1.73 m(2) per year on average; those with HVS > 80% showed 26% higher odds of experiencing a rapid eGFR annual decline, with an extra decline of 1.83 mL/min/1.73 m(2) per year on average. Chinese adults with type 2 diabetes and HVS > 60% could experience a more rapid eGFR decline

A Theoretical Study of Phase Equilibria of Pt Doped Calcium Titanate

Previous Experiments reported that precious-metal Pt is able to migrate between perovskite CaTiO_3 surface and bulk with change of the external redox conditions. This novel process can efficiently suppress the agglomeration of precious-metal particles, and maintain the high performance of the so-called " intelligent catalysts" for a long period. However, the study of the interactions between precious-metal and CaTiO_3 substrate is rather limited. The first-principles calculations combined with cluster expansion and Monte Carlo methods were employed to construct the PtO_x-CaO-TiO_x pseudo-ternary phase diagrams to explore the properties of Pt-doped CaTiO_3system. The first-principles phase diagrams show that Pt can be doped in CaTiO_3 and occupy the Ti-site at various concentrations, and the thermodynamic phase diagrams indicate that the doped CaTi, -xPtxO_3 structures evolve to solid solutions at ambient temperatures. More importantly, Pt tends to dissolve into CaTiO_3substrate under oxidizing conditions while precipitating from the perovskite matrix and exist as metallic particles under reducing conditions,which is consistent with the concept of intelligent catalyst". Furthermore,the investigations of the phase diagram indicate the existence of some other oxides and metal alloys in the catalyst system at various conditions. The results might inform the experiments and be helpful for preparing highly efficient catalysts for elimination of harmful exhaust gas

A Context-aware Workflow Framework and Modeling Language

In the pervasive and mobile computing environment, workflow and context information are closely linked, workflow management system have to interact with a variety of sensors. Therefore, the design and development context-aware workflow applications become complex and difficult to migrate to other platforms. In order to simplify the development of context-aware workflow applications and enhance its portability, a new context-aware workflow framework is proposed in this paper. This framework introduced into the context-aware middleware. Context-aware middleware shielding the various bottom sensors work details for the application and make the workflow applications focus on using high-level context, so as to realize the intelligent workflow management. This framework also introduced into ontology based modeling language for context-aware workflow. Case study shows that our proposed modeling language has good adaptability, and can be used to easily describe any sophisticated context-aware workflows

An Extended Virtual Force-Based Approach to Distributed Self-Deployment in Mobile Sensor Networks

Virtual physics based approach is one of the major solutions for self-deployment in mobile sensor networks with stochastic distribution of nodes. To overcome the connectivity maintenance and nodes stacking problems in the traditional virtual force algorithm (VFA), an extended virtual force-based approach is investigated to achieve the ideal deployment. In low- R c VFA, the orientation force is proposed to guarantee the continuous connectivity. While in high- R c VFA, a judgment of distance force between node and its faraway nodes is considered for preventing node stacking from nonplanar connectivity. Simulation results show that self-deployment by the proposed extended virtual force approach can effectively reach the ideal deployment in the mobile sensor networks with different ratio of communication range to sensing range. Furthermore, it gets better performance in coverage rate, distance uniformity, and connectivity uniformity than prior VFA