Experimental Exploration of RSSI Model for the Vehicle Intelligent Position System

Zhichao Cao,ZhenzhouYuan,Silin Zhang 보안공학연구지원센터 2015 International Journal of Smart Home Vol.9 No.2

Vehicle intelligent position systems based on Received Signal Strength Indicator (RSSI) in WirelessSensor Networks (WSNs) areefficientlyutilized. The vehicle’s position accuracy is of great importance for transportation behaviors, such as dynamic vehicle routing problems and multiple pedestrian routing choice behaviors and so on. Therefore, a precise position and available optimization is necessary for total parameters of conventional RSSI model. In this papar, we investigate the experimental performance of translating the power measurements to corresponding distance between eachpair of nodes. The priori knowledge about the environment interference could impact the accuracy of vehicles’s position and the reliability of paremeters greatly. Based on the real-world outdoor experiments, we compares different regression analysis of the RSSI model, in order to establish a calibration scheme on RSSI model. Empirical experimentation shows that the average errors of RSSI model is able to decrease throughout therules of environmental factor n and shadowing factor ηrespectively. Moreover, the calculation complexity is reduced, as aninnovative approach. Since variation tendency of environmental factor n, shadowing factor η with distance and signal strength could be simulated respectively, RSSI model fulfills the precision of the vehicle intelligent position system.

Study on flow fields of centrally fuel rich swirl burner and its applications

Zhichao Chen,Zhengqi Li,Jianping Jing,Lizhe Chen,Shaohua Wu,Yang Yao 한국화학공학회 2009 Korean Journal of Chemical Engineering Vol.26 No.5

Experiments on a single-phase test facility were done to optimize primary air outlet cones of a centrally fuel rich swirl coal combustion burner. On the basis of optimized results from the single-phase test, a three-component particle-dynamics anemometer was used to measure, in the near-burner region, the characteristics of gas/particle two-phase flows for the burner with two primary air outlet cones, on a gas/particle two-phase test facility. Velocities, RMS velocities and particle volume flux profiles were obtained. According to the results, the primary air outlet cone structure of the centrally fuel rich burner was matching a 670 ton per hour boiler. The performance of the burner on a 670 ton per hour boiler was studied.

Driver Fatigue Detection System based on Eye Blinking by Convolutional Neural Network

Zhichao Sun,Yinan Miao,전준영,박규해 한국자동차공학회 2022 한국자동차공학회 지부 학술대회 논문집 Vol.2022 No.12

Cell-Based Biosensors : A Quartz Crystal Microbalance Approach to the Study of Carbohydrate-Protein Interactions

Zhichao Pei,Yuxin Pei,Julien Saint-Guirons,Teodor Aastrup 한국당과학회 2012 한국당과학회 학술대회 Vol.2012 No.1

The Attana Cell 200 biosensor measures label-free, full kinetics in real time with the target in its biological context. In our study, a novel approach to the study of molecular interactions on the surface of mammalian cells using a QCM biosensor was developed, where an epidermoid carcinoma cell line (A-431) and a breast adenocarcinoma cell line (MDA-MB-468) were immobilized onto polystyrene-coated quartz crystals. The binding and dissociation between the lectin Con A and the cells as well as the inhibition of the binding by monosaccharides were monitored in real time and provided an insight into the complex avidic recognition of cell glycoconjugates. The real-time lectin screening of a range of lectins enabled the accurate study of the glycosylation changes between cells, such as changes associated with cancer progression and development. Furthermore, the kinetic parameters of the interaction of Con A with MDA-MB-468 cells were studied. This application provides investigators in the field of glycobiology with a novel tool to study cell surface glycosylation and may also have impacts on drug discovery.

Optimal modulation strategy based on fundamental reactive power for dual‑active‑bridge converters

Zhichao Zhu,Fei Xiao,Jilong Liu,Peng Chen,Zhaojie Huang,Qiang Ren 전력전자학회 2021 JOURNAL OF POWER ELECTRONICS Vol.21 No.12

Dual-active-bridge (DAB) converters are widely used in bidirectional power transmission and voltage conversion. At present, phase-shift (PS) control is one of the most common and mature control methods for DAB converters. To improve the efficiency and performance of DAB converters, the soft switching and current stress are optimized by increasing the inner phaseshift ratio. However, under different PS controls, it is difficult to establish a unified mathematical model using the traditional instantaneous integral method. To solve this problem, based on the approximate equivalence of the fundamental component of a high-frequency link decomposed by Fourier series, an optimal fundamental modulation strategy is proposed, which takes the fundamental reactive power as the objective of optimization. The trajectories for each of the electrical parameters are analyzed intuitively through a vector diagram of the phasor. A practical optimal control strategy scheme for engineering is obtained. Finally, the effectiveness of the theoretical analysis and the proposed method are verified by experimental results.

Imbalanced sample fault diagnosis method for rotating machinery in nuclear power plants based on deep convolutional conditional generative adversarial network

Zhichao Wang,Hong Xia,Jiyu Zhang,Bo Yang,Wenzhe Yin Korean Nuclear Society 2023 Nuclear Engineering and Technology Vol.55 No.6

Rotating machinery is widely applied in important equipment of nuclear power plants (NPPs), such as pumps and valves. The research on intelligent fault diagnosis of rotating machinery is crucial to ensure the safe operation of related equipment in NPPs. However, in practical applications, data-driven fault diagnosis faces the problem of small and imbalanced samples, resulting in low model training efficiency and poor generalization performance. Therefore, a deep convolutional conditional generative adversarial network (DCCGAN) is constructed to mitigate the impact of imbalanced samples on fault diagnosis. First, a conditional generative adversarial model is designed based on convolutional neural networks to effectively augment imbalanced samples. The original sample features can be effectively extracted by the model based on conditional generative adversarial strategy and appropriate number of filters. In addition, high-quality generated samples are ensured through the visualization of model training process and samples features. Then, a deep convolutional neural network (DCNN) is designed to extract features of mixed samples and implement intelligent fault diagnosis. Finally, based on multi-fault experimental data of motor and bearing, the performance of DCCGAN model for data augmentation and intelligent fault diagnosis is verified. The proposed method effectively alleviates the problem of imbalanced samples, and shows its application value in intelligent fault diagnosis of actual NPPs.

Sports injury treatment and sports rehabilitation employing the Nanoparticles containing zinc oxide

Zhichao Ma,Jie Qi,Weiwei Xun,Yaonan Li Techno-Press 2023 Advances in nano research Vol.15 No.1

The combination of physical activities and individual skills in sports creates an entertaining and competitive environment governed by a set of rules. In today's world, sports attract significant attention and are approached differently by various groups. Inevitably, injuries occur in sports, significantly impacting an athlete's performance and ability to participate in exercises and competitions. Addressing this issue, one of the crucial measures involves restoring the athlete's ability to engage in sports and compete. Sports rehabilitation serves as a treatment to mitigate the effects of injuries, and when combined with surgery, it can expedite the recovery process. Therefore, the primary objective of this study is to utilize a biocompatible technology for synthesizing zinc oxide (ZnO) nanoparticles in sports rehabilitation, ensuring minimal harm to the environment.

Bridge weigh-in-motion through bidirectional Recurrent Neural Network with long short-term memory and attention mechanism

Zhichao Wang,Yang Wang 국제구조공학회 2021 Smart Structures and Systems, An International Jou Vol.27 No.2

In bridge weigh-in-motion (BWIM), dynamic bridge response is measured during traffic and used to identify overloaded vehicles. Most past studies of BWIM use mechanics-based algorithms to estimate axle weights. This research instead investigates deep learning, specifically the recurrent neural network (RNN), toward BWIM. In order to acquire the large data volume to train a RNN network that uses bridge response to estimate axle weights, a finite element bridge model is built through the commercial software package LS-DYNA. To mimic everyday traffic scenarios, tens of thousands of randomized vehicle formations are simulated, with different combinations of vehicle types, spacings, speeds, axle weights, axle distances, etc. Dynamic response from each of the randomized traffic scenarios is recorded for training the RNN. In this paper we propose a 3-stage Bidirectional RNN toward BWIM. Long short-term memory (LSTM) and attention mechanism are embedded in the BRNN to further improve the network performance. Additional test data indicates that the BRNN network achieves high accuracy in estimating axle weights, in comparison with a conventional moving force identification (MFI) method.

Enhanced morphology and hydrophilicity of PVDF flat membrane with modified CaCO3@SMA additive via thermally induced phase separation method

Zhichao Zhang,Wei Wang,Xin Xu,Xi Liu,Yuanling Li,Peng Zhang 한국공업화학회 2022 Journal of Industrial and Engineering Chemistry Vol.107 No.-

Modified CaCO3@SMA nanoparticles obtained by coordination reaction between poly(styrene-co-maleicanhydride) (SMA) and calcium carbonate (CaCO3) nanoparticles were adopted as additive to preparepolyvinylidene fluoride (PVDF) flat membrane via thermally induced phase separation (TIPS) methodwith dioctyl phthalate (DOP) and dibutyl phthalate (DBP) as mixed diluent. The CaCO3 nanoparticlesmodified by SMA effectively reduced the adverse agglomeration of nanoparticles and made the additivedisperse evenly in PVDF matrix. The presence of modified CaCO3@SMA changed the membrane morphologyfrom dispersed spherulites with large pores to fuzzy dendrite structures with uniform pore sizes. Themembrane pore sizes, pore size distribution and tensile strength were significantly improved comparedto both virgin membranes and those containing unmodified CaCO3 nanoparticles. After the CaCO3 waspickled, the porosity and the connectivity between membrane pores were greatly enhanced, resultingin a significant increase in pure water flux. At the same time, the amphiphilic SMA fixed in and on themembrane surface improved the hydrophilic and anti-fouling properties demonstrated in a three-cycletest. The present study provided a potential TIPS method for the fabrication of PVDF membrane combinedwith a simple strategy of modified inorganic particle additive.

Legal Issues Regarding Foreign Investment and the Implementation of the Japan-Indonesia Economic Partnership Agreement

Zhichao Chen 이준국제법연구원 2011 Journal of East Asia and International Law Vol.4 No.1