Reliable H ∞ filtering for stochastic spatial–temporal systems with sensor saturations and failures

This study is concerned with the reliable H∞ filtering problem for a class of stochastic spatial–temporal systems with sensor saturations and failures. Different from the continuous spatial–temporal systems, the dynamic behaviour of the system under consideration evolves in a discrete rectangular region. The aim of this study is to estimate the system states through the measurements received from a set of sensors located at some specified points. In order to cater for more realistic signal transmission process, the phenomena of sensor saturations and sensor failures are taken into account. By using the vector reorganisation approach, the spatial–temporal system is first transformed into an equivalent ordinary differential dynamic system. Then, a filter is constructed and a sufficient condition is obtained under which the filtering error dynamics is asymptotically stable in probability and the H∞ performance requirement is met. On the basis of the analysis results, the desired reliable H∞ filter is designed. Finally, an illustrative example is given to show the effectiveness of the proposed filtering scheme.Deanship of Scientific Research (DSR) at King Abdulaziz University in Saudi Arabia under Grant 16-135-35-HiCi, the National Natural Science Foundation of China under Grants 61329301, 61134009 and 61473076, the Shanghai Rising-Star Program of China under Grant 13QA1400100, the Shu Guang project of Shanghai Municipal Education Commission and Shanghai Education Development Foundation under Grant 13SG34, the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning, the Fundamental Research Funds for the Central Universities, the DHU Distinguished Young Professor Program, and the Alexander von Humboldt Foundation of German

Case report: Neoadjuvant systemic therapy for melanoma

We report a case of rapidly enlarging metastatic melanoma in 45-year-old White male following primary resection of thin melanoma five years ago. Location and large size of the lesion possessed significant risk of complications from surgery, therefore provided a challenge in treatment options. Neoadjuvant targeted chemotherapy was commenced and resulted in a significant reduction in size of the lesion, which allowed subsequent safe surgical resection with no residual disease on histopathology results. This case provides a good example of successful utilization of neoadjuvant systemic therapy in advanced metastatic melanoma

Advanced IoT Technology and Protocols: Review and Future Perspectives

The Internet of Things (IoT) has emerged as a disruptive paradigm, altering how we interact with our surroundings and enabling a plethora of novel applications across multiple sectors. This literature review provides a complete overview of the Internet of Things, including applications, technology, protocols, modeling tools, and future directions. The assessment begins by looking at a wide range of IoT applications, such as smart cities, healthcare, industrial automation, smart homes, and more. It then looks into the underlying technologies that enable IoT deployments, including low-power wireless communication protocols, edge computing, and sensor networks. Protocols and routing methods designed expressly for IoT networks are also described, as well as simulation tools used to simulate and evaluate IoT systems. The discussion focuses on critical insights and consequences for the future of IoT, including challenges and potential in security, interoperability, edge intelligence, and sustainability. By tackling these obstacles and using emerging technologies, IoT can create disruptive change across businesses while also improving quality of life. This review seeks to give scholars, practitioners, and stakeholders a thorough grasp of IoT and its implications for the future

Recursive State Estimation for Stochastic Complex Networks under Round-Robin Communication Protocol: Handling Packet Disorders

This paper investigates the recursive state estimation problem for a class of discrete-time stochastic complex networks with packet disorders under Round-Robin (RR) communication protocols. The phenomenon of packet disorders results from the random transmission delays during the signal propagation process due to the unpredictable fluctuations of the network load, and such random delays are modeled by a set of random variables satisfying certain known probability distributions. For the sake of lessening the communication burden and abating the data collisions, the RR protocol is introduced to govern the order of the nodes for data transmission. Under the scheduling of the RR protocol, only one node is allowed to gain the access to the network at each time instant. Then, a recursive estimator is devised to guarantee an upper bound for the estimation error covariance, and then the obtained upper bound is locally minimized by adequately choosing the estimator parameters. Furthermore, the boundedness of estimation error is analyzed in the sense of mean square with the help of stochastic analysis techniques. At last, a simulation example is presented to show the applicability of the proposed estimator design scheme.10.13039/501100004054-King Abdulaziz University (Grant Number: RG-19-611-42); 10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 61773017, 61873148, 61873230 and 61933007); Royal Society of the U.K.; Alexander Von Humboldt Foundation of German

Nonfragile H∞Fuzzy filtering with randomly occurring gain variations and channel fadings

This paper is concerned with the nonfragile filtering problem for a class of discrete-Time Takagi-Sugeno (T-S) fuzzy systems with both randomly occurring gain variations (ROGVs) and channel fadings.The phenomenon of the ROGVs is introduced into the system model so as to account for the parameter fluctuations occurring during the filter implementation. Two sequences of random variables obeying the Bernoulli distribution are employed to describe the phenomenon of the ROGVs bounded by prescribed norms. In addition, the Rice fading model is utilized to describe the phenomena of channel fadings, where the occurrence probabilities of the random channel coefficients are allowed to time varying. Through stochastic analysis and Lyapunov functional approach, sufficient conditions are established under which the filtering error dynamics is exponentially mean-square stable with a prespecified ∞ performance. The set of the desired nonfragile ∞ filters is characterized by solving a convex optimization problem via the semidefinite programming method. An illustrative example is given to show the usefulness and effectiveness of the proposed design method in this paper.This work was supported in part by the National Natural Science Foundation of China under Grants 61134009, 61329301, 61203139, 61374127 and 61422301, the Hujiang Foundation of China under Grant C14002, the Royal Society of the U.K., and the Alexander von Humboldt Foundation of Germany

Distributed fault estimation with randomly occurring uncertainties over sensor networks

This paper is concerned with the distributed fault estimation problem for a class of uncertain stochastic systems over sensor networks. The norm-bounded uncertainty enters into the system in a random way governed by a set of Bernoulli distributed white sequence. The purpose of the addressed problem is to design distributed fault estimators, via available output measurements from not only the individual sensor, but also its neighbouring sensors, such that the fault estimation error converges to zero exponentially in the mean square while the disturbance rejection attenuation is constrained to a give level by means of the H∞ performance index. Intensive stochastic analysis is carried out to obtain sufficient conditions for ensuring the exponential stability as well as prescribed H∞ performance for the overall estimation error dynamics. Simulation results are provided to demonstrate the effectiveness of the proposed fault estimation technique in this paper.This work was supported in part by the National Natural Science Foundation of China [ grant number 61329301], [grant number 61422301], [grant number 61374127]; the Outstanding Youth Science Foundation of Heilongjiang Province [grant number JC2015016]; the Alexander von Humboldt Foundation of Germany

VIKOR method for multiple criteria group decision making under 2-tuple linguistic neutrosophic environment

In this article, the VIKOR method is proposed to solve the multiple criteria group decision making (MCGDM) with 2-tuple linguistic neutrosophic numbers (2TLNNs). Firstly, the fundamental concepts, operation formulas and distance calculating method of 2TLNNs are introduced. Then some aggregation operators of 2TLNNs are reviewed. Thereafter, the original VIKOR method is extended to 2TLNNs and the calculating steps of VIKOR method with 2TLNNs are proposed. In the proposed method, it’s more reasonable and scientific for considering the conflicting criteria. Furthermore, the VIKOR are extended to interval-valued 2-tuple linguistic neutrosophic numbers (IV2TLNNs). Moreover, a numerical example for green supplier selection has been given to illustrate the new method and some comparisons are also conducted to further illustrate advantages of the new method

Estimation, filtering and fusion for networked systems with network-induced phenomena: New progress and prospects

In this paper, some recent advances on the estimation, filtering and fusion for networked systems are reviewed. Firstly, the network-induced phenomena under consideration are briefly recalled including missing/fading measurements, signal quantization, sensor saturations, communication delays, and randomly occurring incomplete information. Secondly, the developments of the estimation, filtering and fusion for networked systems from four aspects (linear networked systems, nonlinear networked systems, complex networks and sensor networks) are reviewed comprehensively. Subsequently, some recent results on the estimation, filtering and fusion for systems with the network-induced phenomena are reviewed in great detail. In particular, some latest results on the multi-objective filtering problems for time-varying nonlinear networked systems are summarized. Finally, conclusions are given and several possible research directions concerning the estimation, filtering, and fusion for networked systems are highlighted

The role of strict patient-positioning during nursing in the management of intracerebral migration of gravitational bullet injury

The intracranial migration of bullet was described in literature since Cushing time and the First World War [1]. The literature is still away from delivering a clear guideline and constitutes more of case reports rather than comprehensive well-designed studies [2-13], this mostly due to the variability and diversity in the presentation and management of such cases. The migration of bullet can be a sequel of any type of penetrating injury to the skull [14]. Intracranial migration after gravitational (falling) bullet injury is a unique type of injury that constitutes of significant human and material losses with differences in biomechanics and structural brain changes after the insult especially regarding the velocity of impact and the degree of yaw for the intracranially settled bullet [15]. The gravitational bullets injuries are considered by the international disease classification system as celebratory firing, that is quite common and is part of the traditional happy (marriage) or funeral event in the middle east in general and in rural areas of Iraq in particular, and also reported in some areas around the world (South America, North Africa, and middle of Asia) [15,16]