A Joint Routing and Time-Slot Assignment Algorithm for Multi-Hop Cognitive Radio Networks with Primary-User Protection

Cognitive radio has recently emerged as a promising technology to improve the utilization efficiency of the radio spectrum. In cognitive radio networks, secondary users (SUs) must avoid causing any harmful interference to primary users (PUs) and transparently utilize the licensed spectrum bands. In this paper, we study the PUprotection issue in multi-hop cognitive radio networks. In such networks, secondary users carefully select paths and time slots to reduce the interference to PUs. We formulate the routing and time-slot assignment problem into a mixed integer linear programming (MILP). To solve the MILP which is NP-Hard in general, we propose an algorithm named RSAA (Routing and Slot Assignment Algorithm). By relaxing the integral constraints of the MILP, RSAA first solves the max flow from the source to the destination. Based on the max flow, RSAA constructs a new network topology. On the new topology, RSAA uses branch and bound method to get the near optimal assignment of time slots and paths. The theoretical analyses show that the complexity of our proposed algorithm is O(N^4). Also, simulation results demonstrate that our proposed algorithm can obtain near-optimal throughputs for SUs

Preferential Treatments Of State-Owned Enterprises In China

Do state-owned enterprises (SOEs) enjoy preferential treatments in China? This thesis extends the political economy approach of Branstetter and Feenstra (2002)[2] by introducing domestic tax rates in addition to import tariffs, and derive a corresponding government objective function that can be estimated using data on domestic tax rates, both de jure and de facto, respectively determined at the level of the central government and provincial governments. We find that for both the central and provincial governments, the political weights on SOEs are greater than those on FIEs. However, the magnitude of this difference varies across regions and various groups of provinces. In addition, withinregion/group, the political weights of the provincial governments on both SOEs and FIEs tend to be smaller than those of the central government, implying less governmental interference at the provincial governmental dimension

A Novel Cooperative Multicast Scheme Based on Fountain Code

Multicast is an efficient way to support emerging multimedia services over wireless network. Fountain codes are used in multicast systems to enable a robust transmission without CSI feedback and ARQ. We propose a cooperative multi-cast scheme based on fountain code to improve the performance of multicast. The users are coordinated with each other to decode the message at different time slots within the data transmission of a multicast session. Specifically, we take the local channel state information (CSI) and the local residual energy information (REI) into consideration, and apply a relay-selection and power-allocation strategy in our cooperative multicast scheme to prolong the network lifetime, while keeping the transmission delay as low as possible. The simulation results show that the proposed scheme can achieve a good tradeoff between transmission delay and network lifetime

Research on Bridge Sensor Validation Based on Correlation in Cluster

In order to avoid the false alarm and alarm failure caused by sensor malfunction or failure, it has been critical to diagnose the fault and analyze the failure of the sensor measuring system in major infrastructures. Based on the real time monitoring of bridges and the study on the correlation probability distribution between multisensors adopted in the fault diagnosis system, a clustering algorithm based on k-medoid is proposed, by dividing sensors of the same type into k clusters. Meanwhile, the value of k is optimized by a specially designed evaluation function. Along with the further study of the correlation of sensors within the same cluster, this paper presents the definition and corresponding calculation algorithm of the sensor’s validation. The algorithm is applied to the analysis of the sensor data from an actual health monitoring system. The result reveals that the algorithm can not only accurately measure the failure degree and orientate the malfunction in time domain but also quantitatively evaluate the performance of sensors and eliminate error of diagnosis caused by the failure of the reference sensor

BBS Posts Time Series Analysis based on Sample Entropy and Deep Neural Networks

The modeling and forecasting of BBS (Bulletin Board System) posts time series is crucial for government agencies, corporations and website operators to monitor public opinion. Accurate prediction of the number of BBS posts will assist government agencies or corporations in making timely decisions and estimating the future number of BBS posts will help website operators to allocate resources to deal with the possible hot events pressure. By combining sample entropy (SampEn) and deep neural networks (DNN), an approach (SampEn-DNN) is proposed for BBS posts time series modeling and forecasting. The main idea of SampEn-DNN is to utilize SampEn to decide the input vectors of DNN with smallest complexity, and DNN to enhance the prediction performance of time series. Selecting Tianya Zatan new posts as the data source, the performances of SampEn-DNN were compared with auto-regressive integrated moving average (ARIMA), seasonal ARIMA, polynomial regression, neural networks, etc. approaches for prediction of the daily number of new posts. From the experimental results, it can be found that the proposed approach SampEn-DNN outperforms the state-of-the-art approaches for BBS posts time series modeling and forecasting

A comprehensive review of the applications of hybrid evaporative cooling and solar energy source systems

Recent advancements in single-stage evaporative cooling (EC) have showcased their effectiveness as an energy-efficient and sustainable air-conditioning (AC) solution. However, several challenges hinder the widespread adoption of EC in various applications. These challenges include climate sensitivity, substantial spatial requirements, and limitations in achieving desired output temperatures. To address these concerns, there has been a growing focus on integrating EC with solar energy (SE) systems. With traditional energy resources being depleted, the use of SE has gained prominence as a sustainable solution to meet future energy demands while mitigating environmental pollution. This paper presents a comprehensive review of hybrid EC–SE systems, aiming to elucidate the potential synergies, benefits, and challenges associated with this integration. The review explores the principles and mathematical approaches of various configurations of EC systems to assess their compatibility with SE sources. Furthermore, the review delves into the mathematical model of SE, encompassing both solar power generation and thermal collectors, with the aim of integrating it into the EC model. It delves into key aspects of energy consumption and performance, showcasing advancements in achieving higher efficiency and enhanced cooling capacity through the hybrid systems. Additionally, the review highlights research gaps in the existing literature, emphasizing the need for further exploration in this interdisciplinary field. In conclusion, this paper offers valuable insights into the potential of EC–SE systems to address energy and cooling requirements while promoting sustainable development

Data_Sheet_1_Analysis of characteristics of movement disorders in patients with anti-N-methyl-D-aspartate receptor encephalitis.docx

ObjectiveMovement disorders (MDs) are common in anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis but are poorly studied. This study aimed to investigate the clinical characteristics of MDs and the clinical differences between patients with and without MDs in anti-NMDAR encephalitis.MethodsA retrospective study was conducted on patients with anti-NMDAR encephalitis who were first diagnosed and treated in the First People’s Hospital of Yunnan Province from January 2017 to September 2022. According to the presence or absence of MDs, all patients were divided into two groups, and the clinical manifestations, auxiliary examinations, and prognosis of the two groups were compared. Patients in the MDs group were further subgrouped by different ages (Results(1) In our study there were 64 patients, of whom 76.6% (49/64) presented with MDs; the median age of onset in patients with MDs was 21 (15,35) years and 65.3% (32/49) were female. The three most common MDs were orofacial dyskinesia (OFLD) (67.3%), dystonia (55.1%), and stereotypies (34.7%). Patients ConclusionMDs associated with anti-NMDAR encephalitis were predominantly hyperkinetic. Chorea occurred more commonly in patients aged <12 years. Patients with MDs were prone to autonomic dysfunction, consciousness disorders, pulmonary infection, and gastrointestinal dysfunction; they had more intense inflammation, more severe disease, and a poorer short-term prognosis.</p

A Novel Method to Directly Analyze Dissolved Acetic Acid in Transformer Oil without Extraction Using Raman Spectroscopy

Analyzing the concentration of low molecular acids dissolved in oil is vital in the oil-paper insulation aging diagnostic procedure of power transformers. The existing methods cannot distinguish between different acid types and their strengths. In this study, an improved solution Raman detection platform is fabricated. The direct measurement of dissolved acetic acid, a kind of low molecular acids, is observed in transformer oil without extraction. The Raman shift line of oil-dissolved acetic acid at 891 cm−1 corresponding to H–C–H symmetrical swing and O–H swing modes is taken as its characteristic value. Taking Raman shift line of pure oil at 932 cm−1 as an internal standard, a linear regression curve for quantitative analysis is obtained with a slope of 0.19. The best platform parameter of accumulation number is 300, which is determined by Allan deviation analysis. The current concentration detection limit and accuracy for oil-dissolved acetic acid are obtained at about 0.68 mg/mL and 91.66%, separately. The results show that Raman spectroscopy could be a useful alternative method for evaluation insulation aging state of an operating power transformer in the future

Analysis of SF6 decomposed products by fibre‐enhanced Raman spectroscopy for gas‐insulated switchgear diagnosis

Abstract Sulphur hexafluoride (SF6) decomposed products analysis is highly critical in the early‐stage fault diagnosis of gas‐insulated switchgear (GIS). Spectrum technology outperforms traditional methods on non‐invasiveness, no sample preparation, and no consumption. Here, the authors present an improved fibre‐enhanced Raman spectroscopy (FERS) as a comprehensive analytical tool to detect a suite of SF6 decomposed products (SO2F2, SOF2, SO2, H2S, CF4, OCS, CO2, and CO). The FERS approach is combined with two iris diaphragms for spatial filtering and a rear‐end reflector for additional Raman signal enhancement. Limits of detection down to 1 × 10−6–8 × 10−6 are achieved for different SF6 decompositions, and quantification of an undefined multigas, sampled from an 800 kV GIS in service, is realised utilising SF6 as the internal standard gas and with a maximum error of 5.5 %. The GIS is diagnosed according to the results and confirmed by an on‐site check. The authors foresee that this technique will provide a route for trace gas analysis in the power industry

Charge Transfer Effect on Raman and Surface Enhanced Raman Spectroscopy of Furfural Molecules

The detection of furfural in transformer oil through surface enhanced Raman spectroscopy (SERS) is one of the most promising online monitoring techniques in the process of transformer aging. In this work, the Raman of individual furfural molecules and SERS of furfural-Mx (M = Ag, Au, Cu) complexes are investigated through density functional theory (DFT). In the Raman spectrum of individual furfural molecules, the vibration mode of each Raman peak is figured out, and the deviation from experimental data is analyzed by surface charge distribution. In the SERS of furfural-Mx complexes, the influence of atom number and species on SERS chemical enhancement factors (EFs) are studied, and are further analyzed by charge transfer effect. Our studies strengthen the understanding of charge transfer effect in the SERS of furfural molecules, which is important in the online monitoring of the transformer aging process through SERS