Transmission Path Research Articles

High-selectivity tri-band bandpass filter with transmission zeros induced by transmission path interference

ABSTRACT This paper presents a tri-band bandpass filter (BPF) based on transversal signal interference concepts. The proposed tri-band BPF is separately constructed by a T-folded-shaped shorted folded stub loaded resonator and parallel coupled square ring loaded resonator. By the odd-even mode analysis method, the presented filter excites eight transmission poles (TPs), where the first two TPs form the first passband, and the last two passbands are both composed of three TPs. Based on the transversal transmission path, seven transmission zeros (TZs) are excited improving the selectivity dramatically. Moreover, it features independently controllable band characteristics for each passband. To validate the proposed filter, a prototype tri-wideband BPF operating at 2.45 GHz, 3.17 GHz, and 4.91 GHz with 3-dB fraction bandwidth (fbw) of 17.6%, 27.1%, and 17.7% for LTE, WiMAX, Wi-Fi, and 5 G applications is designed, manufactured, and measured, showing great agreement with theoretical predictions and excellent performance, including sharp shirts, high band-to-band isolation (Iso), and compact size.

An Efficient Multipath-Based Caching Strategy for Information-Centric Networks

The growing demand for large-scale data distribution and sharing presents significant challenges to content transmission within the current TCP/IP network architecture. To address these challenges, Information-Centric Networking (ICN) has emerged as a promising alternative, offering inherent support for multipath forwarding and in-network caching to improve data transmission performance. However, most existing ICN caching strategies primarily focus on utilizing resources along the default transmission path and its neighboring nodes, without fully exploiting the additional resources provided by multipath forwarding. To address this gap, we propose an efficient multipath-based caching strategy that optimizes cache placement by decomposing the problem into two steps, multipath selection and cache node selection along the paths. First, multipath selection considers both transmission and caching resources across multiple paths, prioritizing the caching of popular content while efficiently transmitting less popular content. Next, along the selected paths, cache node selection evaluates cache load based on cache utilization and available capacity, prioritizing nodes with the lowest cache load. Extensive simulations across diverse topologies demonstrate that the proposed strategy reduces data transmission latency by at least 12.22%, improves cache hit rate by at least 16.44%, and enhances cache node load balancing by at least 18.77%, compared to the neighborhood collaborative caching strategies.

Correlation of instantaneous fading in bidirectional channels of atmospheric laser communication

The instantaneous fading correlation of the bidirectional channel is an important characteristic of the atmospheric random channel. The instantaneous channel state of the transmitting end can be directly obtained through the instantaneous channel state of the receiving end, reducing the overhead of the additional feedback branch. In this paper, an autoregressive (AR) model and an inverse transformation method are used to generate time-dependent optical signals obeying an APD exponential Weibull distribution. Based on the channel reciprocity function, a channel cross-correlation model on the laser communication transmission path is established, and the influence of factors such as transmitting and receiving apertures, zenith angle, transmission distance, altitude, wavelength, and detector responsivity on the cross-correlation coefficient is studied. Based on theoretical research, an experimental system was built to verify the heterogeneous reciprocity model, and the experimental results were basically consistent with the simulation results. A channel state information prediction and evaluation are achieved through a relevant reciprocity theory, providing a basis for the development of adaptive technology in atmospheric laser communications.

Design and Evaluation of Noise Simulation Algorithm Using MATLAB Ray Tracing Engine for Noise Assessment and Prediction

The Malaysian Department of Occupational Safety and Health (DOSH) reported that noise-induced hearing loss (NIHL) accounted for 92% of occupational diseases in 2019. To address this, accurate risk assessment is crucial. The current noise evaluation methods are complex and time-consuming, relying on manual calculations and field measurements. An easy-to-use, open-source noise simulator that directly compares the output with national standards would help mitigate this issue. This research aims to develop an advanced noise evaluation tool to assess and predict unregulated workplace noise, providing tailored safety recommendations. Using a representative plant layout, the Sound Pressure Level (SPL) is calculated using MATLAB’s ray tracing propagation model. The model simulates all possible transmission paths from the source to the receiver to derive the resultant SPL. A noise simulation application featuring a graphical user interface (GUI) built with MATLAB’s App Designer (version: R2024a) automates these computations. The simulation results are validated against the DOSH’s safety standards in Malaysia. Additional safety metrics, such as the recommended maximum exposure time and the required Noise Reduction Rating (NRR) for hearing protection, are calculated based on the SPLs for hazardous locations. The simulation algorithm’s functionality is validated against manual calculations, with an average deviation of just 3.06 dB, demonstrating the model’s precision. This tool can assess and predict indoor noise levels, provide information on optimal exposure limits, and recommend necessary protective measures, ultimately reducing the risk of NIHL in factory environments. It can potentially optimise plant floor operations for existing and new facilities, ensuring safer shift operations and reducing worker noise hazard exposure.

Bearing fault diagnosis method using CNN with denoising structure under strong noise background

Abstract In the monitoring of rotating machinery area, intelligent fault diagnosis based on signal analysis has been widely applied. However, due to modulation of the hardware transmission path and interference from environmental noise, the quality of collected vibration signals is prone to degradation. Convolutional Neural Networks (CNNs) are currently the most widely used models for fault diagnosis. However, their lack of dedicated denoising structures makes them less robust against noise. Therefore, this paper proposes an end-to-end denoising CNN fault diagnosis model. Firstly, a Discrete-wavelet Attention Layer (DAL) and convolutional layers are alternately employed to extract signal features in the wavelet domain. Secondly, according the periodic self-similarity of vibration signals, the Gramian Noise Reduction (GNR) method is utilized to enhance fault features in the signal. Subsequently, GNR and DAL are integrated into the model to simultaneously extract features from the original signal and the vibration signal enhanced by GNR, thereby enhancing the model fault diagnosis performance in noisy environments. Finally, various levels of noise are added to CWRU and DUT data, and compared with other advanced methods, to verify the effectiveness and universality of the proposed method.

ДОСЛІДЖЕННЯ РЕЖИМІВ КОМПЕНСАЦІЇ РЕАКТИВНОЇ ПОТУЖНОСТІ В СИСТЕМІ ЕЛЕКТРОПОСТАЧАННЯ З КАСКАДОМ ТРАНСФОРМАТОРІВ

The modes of reactive power compensation in the power supply system powered by a synchronous generator through a cascade of intermediate transformers have been studied. It is shown that the reactive component of the common complex resistance of the generator and the power transmission path can cause relatively large levels of reactive power in the system. Experiments show that this power remains in the system even after the application of transverse capacitive compensation, which is not able to provide full compensation of reactive power in a power supply system with a cascade of transformers. Under these conditions, the optimal value of the capacitance of the transverse compensation capacitor was found using the search optimization method on the computer model. The results of the study show the possibility of achieving the mode of full compensation of reactive power due to a relatively small increase in the capacity of the compensating capacitor, which provides transverse compensation. References 8, figures 6, table 1.

A study of the impact of urban business credit environment on environmental pollution.

Environmental pollution has become a global concern, so it is critical to find out the elements that influence it. Is the urban business credit environment influencing urban environmental conditions? The study takes the entropy method for calculating the environmental pollution index of 276 prefecture-level cities across China from 2010 to 2021, the CE1 index to describe the urban business credit environment, and a spatial Durbin model to empirically analyze the mechanism and transmission path of the urban business credit environment on environmental pollution. The findings demonstrate that: (1) there is an important positive spatial association between China's urban pollution index and urban business credit index, and that the level of spatial clustering of the two is increasing over time. (2) the urban business credit environment and environmental pollution have an inverted "U" shape relationship and a significant spatial spillover effect, which means that once a certain threshold is reached, improving the urban business credit environment reduces environmental pollution in local and neighboring areas. (3) The influence of the urban business credit environment on environmental deterioration varies by region. The extra heterogeneity test results for the different regions show that the relationship between business credit level and environmental pollution is consistent with the overall situation in the eastern and western regions, the opposite effect was observed in the central region. (4) Changes in the urban business credit environment have an indirect impact on environmental conditions due to the amount of regional financial development and technological innovation potential. To reduce pollution in the region, prefectural-level cities must strengthen the construction of urban business credit systems, strive to create a favorable business credit environment, strengthen the spatial spillover effect, and guide the resource elements of business credit planning to flow into the central and western parts of China reasonably. The study's findings have significant practical implications for modifying the government's development strategy and improving the urban environment.

Efficacious Framework for The Detection of Link Flooding Attack in Mobile Ad Hoc Network

A novel honey pot deception trace back model, or honey pot IDS, is offered. The system is located on the server, which is the site of network intrusion deceptions. From there, it keeps an eye on all incoming traffic and uses nodes that carry out network weight age studies to continuously weigh the data. For every client connected to the server, it serves as a construct to look at the packet analysis and transmission path to which the IP processed the intrusion detection system. This LF-IDS detects intrusions using both anomaly-based and rule-based intrusion detection methods. By gathering and examining the packets from incoming traffic, the system initially collects data on the packet agent monitoring system. The trespasser is led to a honey pot that will be constructed as a mitigation site.

تحسين طول وموقع المضخم الضوئي المشبع بالاربيوم EDFA من اجل زيادة مدى الارسال لنظام الارسال الضوئي في الفضاء الحر FSO

Although free space optical (FSO) communication has a variety of advantages, such as license free, high bandwidth, and high security, its link distance is limited by weather conditions. Incorporating an optical amplifier within the FSO transmission path is one of the most promising methods to mitigate the aforementioned problem. The use of optical amplifiers not only improve signal to noise ratio (SNR), but also increase the link distance of the FSO system. In this paper, the erbium-doped fiber (EDFA)'s length and location were optimized to improve the FSO transmission range. The optimization process was conducted under clear air and light haze conditions using Optisystem. Decisions were taken in the optimization process based on Q-factor. Results confirmed that pre located EDFA with 2m length was the best choice as it gives better Q-factor value. Keywords: Free space optical (FSO), Erbium-Doped Fiber Amplifier (EDFA), FSO link, post arrangement, pre arrangement.

How has the relationship between major financial markets changed during the Russia–Ukraine conflict?

Geopolitics events have a significant impact on financial markets in the process of global economic integration and financial liberalization. Focusing on the 2022 Russia-Ukraine conflict, this paper utilizes the TVP-VAR network connectedness approach to investigate its specific impacts on the connectedness of major global financial markets. It examines the dynamic evolution of high-frequency and low-frequency shocks on market correlations during the pre-conflict, initial, and stalemate stages, revealing the changes in risk transmission paths. Findings show that the conflict led to increased market interconnectedness. Low-frequency became a major part of the total spillover, signaling long-term structural changes. The stock and foreign exchange market initially responded swiftly, serving as starting points for risk diffusion. The commodity market has been risk receivers throughout the conflict period. Intra-market and cross-market linkages have also changed. The German stock market was the main source of risk spillovers in the conflict, influencing international market linkages. In the global financial market network, several stock markets were the primary risk transmitters in the early stage of the conflict, while foreign exchange markets took on this role during the stalemate period. In addition, gold continues to play a safe-haven role. Furthermore, the TVP-VAR model is used to quantitatively assess the extent of the impact of the conflict on the spillover effects of major global financial markets at different time points and lags. Based on these findings, this paper constructs diversified portfolios and proposes a series of targeted risk management recommendations, which provide a theoretical basis for future policy formulation under similar crises.

Research on the Integrated Converter and Its Control for Fuel Cell Hybrid Electric Vehicles with Three Power Sources

Separate DC-DC converters for each energy source are typically configured in fuel-cell hybrid vehicles. This results in a complex control structure of the powertrain system, low energy density of the converter, and high cost due to the large number of components. Conducting research on DC-DC converters with good energy flow management and high integration is a trend to solve such problems. Based on the analysis of the basic functional structure of the converter, this paper designs a buffering unit circuit with energy collection and distribution functions and appropriately connects it with the pulse unit circuit of the converter. Through device optimization reuse and power transmission path integration, a class of non-isolated four-port DC-DC converters is constructed, which consists of an auxiliary energy charging module, input energy source control module, braking energy feedback module and forward bootstrap boost circuit. This converter has two bi-directional ports, a uni-directional input and a bi-directional output, for separate connection to the power batteries, supercapacitors, fuel cells and DC bus. It can adapt to the fluctuation of the vehicle’s driving condition while achieving dynamic and flexible regulation of power flow and can flexibly allocate power according to the load current and voltage level of energy. It can realize a total of 14 operation modes, including six output power supply operation modes, five auxiliary power charging operation modes, and three braking energy regeneration operation modes. Furthermore, the mathematical model of this converter is constructed using the state-average method and the small-signal modeling method in order to achieve the responsiveness and stability of switching multiple operating modalities. The PI control parameters are optimized using the particle swarm optimization algorithm to achieve optimized control of the converter. The simulation system is set up using MATLAB R2024a to verify that the proposed converter topology and algorithm can dynamically allocate appropriate current paths to manipulate the power flow under various operating conditions, effectively improving the utilization rate and efficiency of energy. The converter has the characteristics of high gain and high power density, which is suitable for three-energy fuel cell hybrid electric vehicles.

Mild Focused Ultrasound-Induced Microscopic Heating of Nanoparticles Observed by Lanthanide Luminescence for Precise Sonothermal Cancer Therapy.

Focused ultrasound (FUS) is a recognized tool that can be used clinically for the thermal ablation of tumors. However, excessive heat can cause side effects on the ultrasound transmission path and normal tissues around the tumor. To address the issue, this work detected for the first time the effect of microscopic heating of nanoparticles under the action of FUS through the luminescence intensity ratio (LIR) and luminescence lifetime of temperature-responsive lanthanide-doped nanoparticles. When FUS is applied to the tissue embedded with nanoparticles, the increase in the microscopic temperature of the nanoparticles synchronously monitored by LIR is more obvious than the increase in the macroscopic temperature. Based on this phenomenon, the intensity of focused ultrasound can be finely regulated to avoid overheating while ensuring a therapeutic effect. This work achieves the measurement of the microscopic heating of nanoparticles under FUS, which is of great significance for the development of sonothermal cancer therapy.

Navigating investment risks mode and transmission: a study of China’s participation in the Belt and Road Initiative through the lens of risk society

ABSTRACT The world is experiencing a period of heightened complexity and uncertainty, where risks are interconnected and extend beyond traditional boundaries. This paper delves into the effective identification of investment risks for China’s involvement in the Belt and Road Initiative (BRI), utilizing methodologies rooted in complex networks and Minimum Spanning Tree. It establishes an indicator system for foreign direct investment (FDI) risks across four dimensions: economic, political, social, and bilateral relations, while also developing a risk identification model grounded in complex network theory. The empirical analysis draws from data spanning 2010 to 2019, encompassing 103 co-building countries of the BRI. Key findings include: (1) Political risk emerges as pivotal when Chinese enterprises invest in co-building countries of the BRI. (2) Examining individual country investment risks reveals an increased transmissibility of China’s FDI risks. Notably, Indonesia, Brazil, and Bangladesh showcase internally complex investment risk environments. (3) Analysis of investment risks between countries and regions indicates a rise in risk transmission paths since 2010. Particularly, the South Asian region stands out for harbouring the longest transmission path. This study advances theoretical and empirical understanding of effective identification of China’s overseas investment risks, offering valuable insights for the development of global risk society governance.

Analysis and optimization of whine noise in the front-end gear train

This paper focuses on the gear whine noise problem of this engine, analyses it from two aspects of excitation source and transmission path, and puts forward the corresponding optimization method in combination with the actual product, which mainly includes the enhancement of the intrinsic frequency of the engine assembly, the optimization of the gear macro-parameters and the optimization of the gear micro-parameters. The optimization scheme achieves the objectives of minimizing transmission error and optimizing gear contact surface pressure and improves the NVH performance of the gear while considering the reliability of the gear system. Finally, the feasibility of the optimization scheme is verified by engine noise bench test. The study's results offer valuable insights for the design of diesel engine front-end gear systems, providing an effective approach to address existing product issues and to guide the development of new products.

Weak compound fault identification of gearboxes based on improved symplectic geometric mode decomposition and optimized cyclic kurtosis deconvolution

Abstract Given the complex and harsh operating conditions of gear transmission systems, gearboxes are prone to compound faults. These faults, involving multiple types, often couple together, causing the weak fault pulse characteristics to be entirely masked by strong environmental noise. This significantly complicates the extraction of relevant fault information from the gearbox. To address these issues, this paper proposes a method for extracting compound fault features based on improved symplectic geometric mode decomposition (SGMD) and optimized cyclic bispectrum deconvolution (CYCBD). Firstly, considering the periodic impact characteristics of different fault types, morphological envelope cyclic bispectrum is proposed to cluster the initial components obtained from SGMD decomposition, thereby adaptively separating different fault features contained in the compound fault signals. An adaptive filter length search strategy is subsequently introduced to optimize the CYCBD by deconvolving each initial fault component, thereby eliminating the interference caused by complex transmission paths and substantial environmental noise, which, in turn, enhances weak periodic fault pulses. Following this, the enhanced signals are subjected to envelope demodulation to extract fault characteristic frequencies, enabling the identification of various types of faults. The effectiveness and feasibility of the proposed method are demonstrated through both simulation signals and actual experimental data related to gearbox compound faults. Compared with existing methods, the proposed method demonstrates superior performance in identifying weak compound faults under strong environmental noise.

An Efficient Multi-Topology Construction Method for Scheduling Mobile Data Flows in Software-Defined Networking

In mobile networks, a content server can provide multiple services simultaneously to a mobile device, generating multiple data flows. As the device moves, the transmission path in the wired network may need to be switched to maintain service continuity. However, a single switching path may not be able to accommodate all the flows, potentially leading to congestion and a degraded user experience. To address this challenge, we propose a multi-topology routing-based mobile data scheduling method that dynamically switches flows across multiple paths to enhance flexibility and load balancing. The performance of this method is significantly influenced by the construction of logical topologies. Well-designed topologies provide high-bandwidth, low-latency paths to all possible destination nodes, while poorly designed topologies waste switch capacity and fail to achieve these goals. In this paper, we introduce an efficient multi-topology construction method for scheduling mobile data flows in software-defined networking (SDN). Our approach optimizes and balances transmission capacity for each destination node while adhering to the flow entry constraints of switches. Simulations demonstrate that our method consistently outperforms the single-path switching method and the other two multi-topology construction methods in terms of packet delay, packet loss rate, and network throughput, regardless of the device’s new location.

Construction and analysis of brain functional network of magnetic stimulation acupoints based on graph theory

ABSTRACT New developments in integrating Transcranial Magnetic Stimulation (TMS) in combination with acupuncture from traditional Chinese medicine, and applying graph theory to neuroscience, are opening new frontiers in brain research and neuromagnetic stimulation. In this article, brain functional networks following magnetic stimulation at the Guangming acupoint and the mock acupoint were constructed based on the quantification of the correlation of multi-channel Electroencephalogram (EEG) signals. Results show that, compared with the results under stimulation at the mock acupoint, brain functional connections significantly increase in the occipital lobe and the frontal lobe under stimulation at the Guangming acupoint. In combination with graph theory based on complex network theory and statistical T-tests, we found significant differences in the brain functional network parameters between magnetic stimulation at the Guangming acupoint and the mock acupoint (p < 0.05). Therefore, it can be concluded that magnetic stimulation of the Guangming acupoint can improve the brain functional network’s global and local efficiency, shorten the information transmission path, and achieve more efficient information transmission within the brain.

Impact of atmospheric turbulence on the signal intensity of the laser ranging echo of space debris

Based on the research of laser atmospheric transmission theory, this paper derives the laser radar ranging equation under the influence of turbulence under the condition of slant path transmission, and simulates and analyzes the changes in the number of debris laser ranging (DLR) echo photons under different parameters. The results show that the number of echo photons is inversely proportional to the intensity of atmospheric turbulence and proportional to the relative angular spread. The greater the elevation angle, the more echo photons; among them, under strong, weak atmospheric turbulence, and no turbulence conditions, the ratio of the number of echo photons is approximately between 1/500 and 4/5. The success rate of the DLR system detecting effective echo signals under different turbulence intensities is comparatively analyzed. Finally, based on the comparison of the experimental results of the 700 mm DLR system and the simulation results of the corrected model, the average relative error is found to be 13.43%.

The Shock of Emergencies on Financial Markets and Its Countermeasures

In recent years, the frequent occurrence of major emergencies and their potential impact on the financial market have brought great challenges to the stability and development of the global economy. In this context, it has become an urgent issue to explore how major emergencies affect the financial market and take corresponding measures to deal with them. Through literature research and analysis, this paper concludes the impact of natural disasters, accidents and disasters, public health emergencies and social security emergencies on the financial market respectively, clarifies the transmission path of the impact including the social level, the real economy level and the policy level, and puts forward suggestions for the construction of financial emergency management. That is, to improve the precise prevention and control system, optimize the domestic market environment and the rule of law of financial emergency management rights. The research results are helpful to maintain the stability of the stock market and the overall situation of economic development in major emergencies.

Digital Transformation and Firms' Foreign Direct Investment: Evidence from Chinese Listed Companies

Against the backdrop of a new wave of economic globalization, digital transformation empowers firms' foreign direct investment, becoming a key lever for achieving high-quality international circulation. This paper takes A-share listed companies on the Shanghai and Shenzhen Stock Exchanges from 2011 to 2022 as the research sample to explore the effect and mechanisms of digital transformation in promoting firms' FDI. The study finds that digital transformation significantly promotes firms' FDI, and this conclusion holds after a series of robustness and endogeneity tests. Mechanism tests reveal that alleviating financing constraints and incentivizing green innovation are important transmission paths through which digital transformation promotes firms' FDI. Heterogeneity analysis shows that the effect of digital transformation on FDI is more pronounced in large firms and state-owned enterprises. This paper deepens the theoretical understanding of the internal logical relationship between digital transformation and firms' economic behavior, providing valuable insights for driving firms to better expand into overseas markets.