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    Electric vehicle charging situation awareness for charging station ultra-short-term load forecast
    SHI Yiwei1 (史一炜), LIU Zeyu1 (刘泽宇), FENG Donghan1∗ (冯冬涵), ZHOU Yun1∗ (周 云), ZHANG Kaiyu2 (张开宇), LI Hengjie3 (李恒杰)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 28-38.   DOI: 10.1007/s12204-023-2566-2
    Abstract271)      PDF(pc) (1518KB)(1085)       Save
    Electric vehicles (EVs) are expected to be key nodes connecting transportation–electricity–communication networks. Advanced automotive electronics technologies enhance EVs’ perception, computing, and communication capacity, which in turn can boost the operational efficiency of intelligent transportation systems (ITSs). EVs couple the ITS to the power system, providing a promising solution to charging congestion and transformer overload via navigation and forecasting approaches. This study proposes a privacy-preserving EV charging situation awareness framework and method to forecast the ultra-short-term load of charging stations. The proposed method only relies on public information from commercial service providers. In the case study, data are powered by the Baidu LBS cloud and EV-SGCC platform, and the experiment is conducted within an area of Pudong New District in Shanghai. Based on the results, the charging load of charging stations can be adequately forecasted more than 1 min ahead with low communication and computing power requirements. This research provides the basis for further studies on operation optimization and electricity market transaction of charging stations.
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    Numerical Study on Separation of Circulating Tumor Cell Using Dielectrophoresis in a Four-Electrode Microfluidic Device
    WANG Yukuna (王雨坤), DING Xiantingb (丁显廷), ZHANG Zhinana (张执南)
    J Shanghai Jiaotong Univ Sci    2023, 28 (4): 391-.   DOI: 10.1007/s12204-022-2459-9
    Abstract242)      PDF(pc) (1462KB)(255)       Save
    This numerical study proposes a cell sorting technique based on dielectrophoresis (DEP) in a microfluidic chip. Under the joint effect of DEP and fluid drag, white blood cells and circulating tumor cells are separated because of different dielectric properties. First, the mathematical models of device geometry, single cell, DEP force, electric field, and flow field are established to simulate the cell motion. Based on the simulation model, important boundary parameters are discussed to optimize the cell sorting ability of the device. A proper matching relationship between voltage and flow rate is then provided. The inlet and outlet conditions are also investigated to control the particle motion in the flow field. The significance of this study is to verify the cell separating ability of the microfluidic chip, and to provide a logistic design for the separation of rare diseased cells.
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    Review of Key Technologies for Developing Personalized Lower Limb Rehabilitative Exoskeleton Robots
    TAO Jing, (陶璟), ZHOU Zhenhuan (周振欢)
    J Shanghai Jiaotong Univ Sci    2024, 29 (1): 16-28.   DOI: 10.1007/s12204-022-2452-3
    Abstract194)      PDF(pc) (1179KB)(245)       Save
    Rehabilitative training and assistance to daily living activities play critical roles in improving the life quality of lower limb dyskinesia patients and older people with motor function degeneration. Lower limb rehabilitative exoskeleton has a promising application prospect in support of the above population. In this paper, critical technologies for developing lower limb rehabilitative exoskeleton for individualized user needs are identi- fied and reviewed, including exoskeleton hardware modularization, bionic compliant driving, individualized gait planning and individual-oriented motion intention recognition. Inspired by the idea of servitization, potentials in exoskeleton product-service system design and its enabling technologies are then discussed. It is suggested that future research will focus on exoskeleton technology and exoskeleton-based service development oriented to an individual’s physical features and personalized requirements to realize better human-exoskeleton coordination in terms of technology, as well as accessible and high-quality rehabilitation and living assistance in terms of utility.
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    Meso-Scale Tearing Mechanism Analysis of Flexible Fabric Composite for Stratospheric Airship via Experiment and Numerical Simulation
    CHEN Yonglin (陈永霖), YANG Weidong (杨伟东), XIE Weicheng (谢炜程), WANG Xiaoliang (王晓亮), FU Gongyi∗ (付功义)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 873-884.   DOI: 10.1007/s12204-022-2431-8
    Abstract144)      PDF(pc) (4194KB)(227)       Save
    Stratospheric airships are controllable lighter-than-air aircraft and have great potential application in surveillance and communication. The envelopes, one of the main structures of a stratospheric airship, are generally made of flexible fabric composites to be lightweight, high strength, capable of containing lifting gas, and resistant to the harsh stratospheric environment. The composites, however, are prone to tearing. Hence, their tearing behavior has attracted great attention. This paper explores the meso-scale tearing mechanism of an envelope and the temperature influence on its tear strength via experiment and numerical simulation. Biaxial tear tests were conducted on cruciform specimens, which were contacted with liquids (cold alcohol or hot water) at different temperatures including -25, 20, 50, 80 °C. The specimens’ tear stresses were measured and the meso-scale tearing behavior was captured with a microscope. Besides, a novel finite element analysis model based on truss and spring elements was established to simulate the tearing behavior. It was found that the simulation result has a relative agreement with the tests. The simulation results show that the maximum tear stress of the envelope drops by 39.62% as the temperature rises from -60 °C to 80 °C and the tensile properties of yarns and matrix account for stress concentration around a crack tip. This work deeply reveals the meso-scale tearing mechanism of the envelope and provides a valuable reference for exploring tearing properties of flexible fabric composites.
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    Sealing Performance of Pressure-Adaptive Seal
    LI Yuanfeng (李元丰), WANG Yiling (王怡灵), ZHANG Wanxin∗ (张万欣), LIU Jinian (刘冀念), MA Jialu (马加炉)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 747-756.   DOI: 10.1007/s12204-022-2510-x
    Abstract480)      PDF(pc) (2268KB)(177)       Save
    A pressure-adaptive seal is developed to meet the demands of quick assembling and disassembling for an individual protection equipment in aerospace. The analysis model, which reflects the main characteristics of the seal structure, is built based on the finite element method and the Roth’s theory of rubber seal, and verified by the prototype test. The influences of precompression ratio, hardness of the sealing ring rubber, and friction coefficient on the sealing performance are investigated by variable parameter method. Results show that the model can describe the essential characteristics of the pressure-adaptive seal structure, which has good follow-up to the cavity pressure to achieve the purpose of pressure self-adaptive. The leakage rate correlates negatively with the precompression ratio of the sealing ring and the hardness of the sealing ring material, while is positively related to the friction coefficient between the sealing ring and the sealing edge. The maximum contact stress on sealing surface has negative correlation with the precompression ratio of the sealing ring, and positive correlation with the hardness of the seal ring material. The damage risk of the sealing ring increases with the increases of the precompression ratio of sealing ring, hardness of sealing ring material, and friction coefficient.
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    Travel Intention of Electric Vehicle Sharing based on Theory of Multiple Motivations
    BAO Lewen (鲍乐雯), MIAO Rui, ∗ (苗 瑞), CHEN Zhihua (陈志华), ZHANG Bo (张 博), GUO Peng (郭 鹏), MA Yuze (马宇泽)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 1-9.   DOI: 10.1007/s12204-023-2563-5
    Abstract496)      PDF(pc) (467KB)(158)       Save
    Determining the travel intention of residents with shared electric vehicles (EVs) is significant for promoting the development of low-carbon transportation, considering that common problems such as high idle rate and lack of attractiveness still exist. To this end, a structural equation model (SEM) based on the theory of multiple motivations is proposed in this paper. First, the influencing motivations for EV sharing are divided into three categories: consumer-driven, program-driven, and enterprise-driven motivations. Then, the intentions of residents in Shanghai to travel with shared EVs are obtained through a survey questionnaire. Finally, an SEM is constructed to analyze quantitatively the impact of different motivations on the travel intention. The results show that consumer-driven motivations with impact weights from 0.14 to 0.63 have the overwhelming impact on travel intention, compared to program-driven motivations with impact weights from ?0.14 to 0.15 and enterprise-driven motivations with impact weights from 0.02 to 0.06. In terms of consumer-driven motivations, the weight of green travel awareness is the highest. The implications of these results on the policy to enable large-scale implementation of shared EVs are discussed from the perspectives of the resident, enterprise, and government.
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    Integrated Hydraulic-Driven Wearable Robot for Knee Assistance
    ZHAO Yafei (赵亚飞), HUANG Chaoyi (黄超逸), ZOU Yuging(邹玉莹), ZOUKehan(邹可涵), zoU Xiaogang(邹笑阳), XUE .Jiaqi(薛嘉琦), LI Xiaoting(李晓婷), KOH Keng Huat, WANG Xiaojun(王小军), LAI Wai Chiu King(赖伟超), HU Yong(胡勇), XI Ning(席宁), WANG Zheng(王峥)
    J Shanghai Jiaotong Univ Sci    2023, 28 (3): 289-295.   DOI: 10.1007/s12204-023-2602-2
    Abstract355)      PDF(pc) (1156KB)(142)       Save
    Age-related diseases can lead to knee joint misfunction, making knee assistance necessary through the use of robotic wearable braces. However, existing wearable robots face challenges in force transmission and human motion adaptation, particularly among the elderly. Although soft actuators have been used in wearable robots, achieving rapid response and motion control while maintaining portability remains challenging. To address these issues, we propose a soft-robotic knee brace system integrated with multiple sensors and a direct-drive hydraulic actuation system. This approach allows for controlled and rapid force output on the portable hydraulic system. The multi-sensor feedback structure enables the robotic system to collaborate with the human body through human physiological signal and body motion information. The human user tests demonstrate that the knee robot provides assistive torques to the knee joint by being triggered by the electromyography signal and under human motion control.
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    Medicine-Engineering Interdisciplinary Research Based on Bibliometric Analysis: A Case Study on Medicine-Engineering Institutional Cooperation of Shanghai Jiao Tong University
    WANG Qingwen (王庆稳),CUI Tingting (崔婷婷),DENG Peiwen* (邓珮雯)
    J Shanghai Jiaotong Univ Sci    2023, 28 (6): 841-856.   DOI: 10.1007/s12204-022-2418-5
    Abstract66)      PDF(pc) (1829KB)(135)       Save
    This article aims to provide reference for medicine-engineering interdisciplinary research. Targeted at the scientific literature and patent literature published by Shanghai Jiao Tong University, this article attempts to set up co-occurrence matrix of medicine-engineering institutional information which was extracted from address fields of the papers, so as to construct the medicine-engineering intersection datasets. The dataset of scientific literature was analyzed using bibliometrics and visualization methods from multiple dimensions, and the most active factors, such as trends of output, journal and subject distribution, were identified from the indicators of category normalized citation impact (CNCI), times cited, keywords, citation topics and the degree of medicineengineering interdisplinary. Research on hotspots and trends was discussed in detail. Analyses of the dataset of patent literature showed research themes and measured the degree for technology convergence of medicineengineering.
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    Early Detection Methods of Deep Tissue Pressure Injuries: A Systematic Review
    JIA Jingyil (贾菁怡),LI Zhengyi1,2 (李正裔),PENG Linjing1 (彭琳晶),YAO Yifeil* (姚怡飞)
    J Shanghai Jiaotong Univ Sci    2023, 28 (4): 526-.   DOI: 10.1007/s12204-022-2518-2
    Abstract167)      PDF(pc) (552KB)(133)       Save
    Deep tissue pressure injuries (DTPIs) have witnessed a growing prevalence in hospitals and other health care units especially among individuals with pathological conditions that give rise to restricted mobility, impaired sensation, and reduced tissue tolerance. The etiology of DTPIs has been a subject of controversy, to which several explanatory models have been proposed, including direct mechanical insult, ischemia-reperfusion, lymphatic occlusion, and inflammatory cytokines. In line with these pathophysiological scenarios, ultrasound, subepidermal moisture detection, and biomarker technologies have been proposed as potential early detection methods of DTPIs. This paper provides a systematic review involving these three methods. The conclusion is that combining and implementing these methods at different time periods during DTPIs development and progression respectively is likely to be the most universal, effective and promising way for DTPIs diagnosis.
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    Review of Power-Assisted Lower Limb Exoskeleton Robot
    HE Guisong (贺贵松), HUANG Xuegong (黄学功), LI Feng (李峰), WANG Huixing (汪辉兴)
    J Shanghai Jiaotong Univ Sci    2024, 29 (1): 1-15.   DOI: 10.1007/s12204-022-2489-3
    Abstract381)      PDF(pc) (1195KB)(126)       Save
    Power-assisted lower limb exoskeleton robot is a wearable intelligent robot system involving mechanics,materials, electronics, control, robotics, and many other fields. The system can use external energy to provide additional power to humans, enhance the function of the human body, and help the wearer to bear weight that is previously unbearable. At the same time, employing reasonable structure design and passive energy storage can also assist in specific actions. First, this paper introduces the research status of power-assisted lower limb exoskeleton robots at home and abroad, and analyzes several typical prototypes in detail. Then, the key technologies such as structure design, driving mode, sensing technology, control method, energy management, and human-machine coupling are summarized, and some common design methods of the exoskeleton robot are summarized and compared. Finally, the existing problems and possible solutions in the research of power-assisted lower limb exoskeleton robots are summarized, and the prospect of future development trend has been analyzed.
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    Progress in Force-Sensing Techniques for Surgical Robots
    GAO Hongyan1,2(高红岩),AI Xiaojie1,2(艾孝杰),SUN Zhenglong3(孙正隆),CHEN Weidong1,2(陈卫东),GAO Anzhu1,2*(高安柱)
    J Shanghai Jiaotong Univ Sci    2023, 28 (3): 370-381.   DOI: 10.1007/s12204-023-2607-x
    Abstract344)      PDF(pc) (1017KB)(122)       Save
    Force sensing is vital for situational awareness and safe interaction during minimally invasive surgery. Consequently, surgical robots with integrated force-sensing techniques ensure precise and safe operations. Over the past few decades, there has been considerable progress in force-sensing techniques for surgical robots. This review summarizes the existing electrically- and optically-based force sensors for surgical robots, including piezoresistive, piezoelectric, capacitive, intensity/phase-modulated, and fiber Bragg gratings. Their principles, applications, advantages, and limitations are also discussed. Finally, we summarize our conclusions regarding state-of-the-art force-sensing technologies for surgical robotics.
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    Ant Colony Algorithm Path Planning Based on Grid Feature Point Extraction
    LI Erchao∗ (李二超), QI Kuankuan (齐款款)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 86-99.   DOI: 10.1007/s12204-023-2572-4
    Abstract248)      PDF(pc) (1196KB)(121)       Save
    Aimed at the problems of a traditional ant colony algorithm, such as the path search direction and field of view, an inability to find the shortest path, a propensity toward deadlock and an unsmooth path, an ant colony algorithm for use in a new environment is proposed. First, the feature points of an obstacle are extracted to preprocess the grid map environment, which can avoid entering a trap and solve the deadlock problem. Second, these feature points are used as pathfinding access nodes to reduce the node access, with more moving directions to be selected, and the locations of the feature points to be selected determine the range of the pathfinding field of view. Then, based on the feature points, an unequal distribution of pheromones and a two-way parallel path search are used to improve the construction efficiency of the solution, an improved heuristic function is used to enhance the guiding role of the path search, and the pheromone volatilization coefficient is dynamically adjusted to avoid a premature convergence of the algorithm. Third, a Bezier curve is used to smooth the shortest path obtained. Finally, using grid maps with a different complexity and different scales, a simulation comparing the results of the proposed algorithm with those of traditional and other improved ant colony algorithms verifies its feasibility and superiority.
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    Automatic Removal of Multiple Artifacts for Single-Channel Electroencephalography
    ZHANG Chenbei (张晨贝), SABOR Nabil, LUO Junwen (罗竣文), PU Yu (蒲 宇), WANG Guoxing (王国兴), LIAN Yong∗ (连 勇)
    J Shanghai Jiaotong Univ Sci    2022, 27 (4): 437-451.   DOI: 10.1007/s12204-021-2374-5
    Abstract275)      PDF(pc) (2934KB)(120)       Save
    Removing different types of artifacts from the electroencephalography (EEG) recordings is a critical step in performing EEG signal analysis and diagnosis. Most of the existing algorithms aim for removing single type of artifacts, leading to a complex system if an EEG recording contains different types of artifacts. With the advancement in wearable technologies, it is necessary to develop an energy-efficient algorithm to deal with different types of artifacts for single-channel wearable EEG devices. In this paper, an automatic EEG artifact removal algorithm is proposed that effectively reduces three types of artifacts, i.e., ocular artifact (OA), transmission- line/harmonic-wave artifact (TA/HA), and muscle artifact (MA), from a single-channel EEG recording. The effectiveness of the proposed algorithm is verified on both simulated noisy EEG signals and real EEG from CHB- MIT dataset. The experimental results show that the proposed algorithm effectively suppresses OA, MA and TA/HA from a single-channel EEG recording as well as physical movement artifact.
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    Physical Characterization of Ionic Liquid-Modified Polyvinyl Alcohol and Sodium Thiocyanate Polymer Electrolytes for Electrochemical Double-Layer Capacitor Application
    AZEMTSOP Manfo Theodore , MEHRA Ram Mohan , KUMAR Yogesh , GUPTA Meenal
    J Shanghai Jiaotong Univ Sci    2023, 28 (2): 161-171.   DOI: 10.1007/s12204-021-2397-y
    Abstract381)      PDF(pc) (1140KB)(115)       Save
    Novel gel polymer electrolytes (GPEs) composed of polyvinyl alcohol (PVA) and sodium thiocyanate were developed via a solution casting technique. An ionic liquid (IL), 1-ethyl-3-methyl-imidazolium tricyanomethanide ([EMIM][TCM]), was doped into a polymer–salt complex system (PVA + NaSCN) to further enhance the conductivity. IL-doped polymer electrolyte (ILDPE) films were characterized using X-ray diffraction (XRD), polarized optical microscopy (POM), Fourier-transform infrared (FTIR) spectroscopy, and conductivity measurements. XRD was performed to check the degree of crystallinity and amorphicity of the ILDPE films, and the amorphicity of GPEs increased with the increase of the IL content. POM was employed to evaluate the changes in the surface morphology due to the inclusion of salt and IL in the PVA. The compositional nature of the GPE films was examined via FTIR studies. The electrical and electrochemical properties were characterized by cyclic voltammetry and electrochemical impedance spectroscopy. The maximum conductivity for the GPE film was estimated to be 1.10 × 10-5 S/cm for 6% (mass fraction) of IL in the polymer–salt complex. The ionic transference number was approximately 0.97. An electrochemical double-layer capacitor (EDLC) was built from optimized GPE films and reduced graphene oxide-based electrodes. The specific capacitance calculated from the cyclic voltammograms of the EDLC cells was 3 F/g.
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    Adaptive Human-Robot Collaboration Control Based on Optimal Admittance Parameters
    YU Xinyi (禹鑫燚), WU Jiaxin (吴加鑫), XU Chengjun (许成军), LUO Huizhen (罗惠珍), OU Linlin∗ (欧林林)
    J Shanghai Jiaotong Univ Sci    2022, 27 (5): 589-601.   DOI: 10.1007/s12204-022-2460-3
    Abstract343)      PDF(pc) (1674KB)(111)       Save
    In order to help the operator perform the human-robot collaboration task and optimize the task performance, an adaptive control method based on optimal admittance parameters is proposed. The overall control structure with the inner loop and outer loop is first established. The tasks of the inner loop and outer loop are robot control and task optimization, respectively. Then an inner-loop robot controller integrated with barrier Lyapunov function and radial basis function neural networks is proposed, which makes the robot with unknown dynamics securely behave like a prescribed robot admittance model sensed by the operator. Subsequently, the optimal parameters of the robot admittance model are obtained in the outer loop to minimize the task tracking error and interaction force. The optimization problem of the robot admittance model is transformed into a linear quadratic regulator problem by constructing the human-robot collaboration system model. The model includes the unknown dynamics of the operator and the task performance details. For relaxing the requirement of the system model, the integral reinforcement learning is employed to solve the linear quadratic regulator problem. Besides, an auxiliary force is designed to help the operator complete the specific task better. Compared with the traditional control scheme, the security performance and interaction performance of the human-robot collaboration system are improved. The effectiveness of the proposed method is verified through two numerical simulations. In addition, a practical human-robot collaboration experiment is carried out to demonstrate the performance of the proposed method.
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    Entity Relationship Explanation via Conceptualization
    XIE Chenhao(谢晨昊), LIANG Jiaqing(梁家卿), XIA Yanghua(肖仰华), HWANG Seung-won
    J Shanghai Jiaotong Univ Sci    2023, 28 (6): 695-702.   DOI: 10.1007/s12204-021-2394-1
    Abstract170)      PDF(pc) (608KB)(106)       Save
    Finding an attribute to explain the relationships between a given pair of entities is valuable in many applications. However, many direct solutions fail, owing to its low precision caused by heavy dependence on text and low recall by evidence scarcity. Thus, we propose a generalization-and-inference framework and implement it to build a system: entity-relationship finder (ERF). Our main idea is conceptualizing entity pairs into proper concept pairs, as intermediate random variables to form the explanation. Although entity conceptualization has been studied, it has new challenges of collective optimization for multiple relationship instances, joint optimization for both entities, and aggregation of diluted observations into the head concepts defining the relationship. We propose conceptualization solutions and validate them as well as the framework with extensive experiments.
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    Establishment of a Refined Brain Model for Evaluating Implantation Behavior of Neural Electrode and Research of its Simulated Behavior
    HE Yuxcin (贺雨欣), ZHANG Wenguang (张文光), XU Haotian (胥浩天), XU Yifan (徐倚帆), XU Liyue (许李悦)
    J Shanghai Jiaotong Univ Sci    2023, 28 (4): 401-.   DOI: 10.1007/s12204-022-2523-5
    Abstract178)      PDF(pc) (1512KB)(104)       Save
    The long-term reliability of the neural electrode is closely related to its implantation behavior. In orderto realize the quantitative research of the implantation behavior in a low-cost and accurate way, a refined brainmodel containing meninges is proposed. First, the expected simulation material was selected through measuringthe elastic modulus based on the method of atomic force microscope indentation technique. As a result, the 2%(mass fraction) agarose gel simulated the gray and white matter, the 7 : 1 (volume ratio) polydimethylsiloxane(PDMS) sheet simulated the pia mater, and the polyvinyl chloride (PVC) film simulated the dura mater. Second,based on designing a three-layer structure mold, the brain model was prepared by inverted pouring to realizea flat implantation surface. Finally, the simulation behavior of the brain model was investigated with the ratbrain as a reference. For mechanical behavior of implantation, the implantation force experienced two peaks bothin the brain model and the rat brain, maximum values of which were 10.17 mN and 7.69 mN respectively. Thelarger implantation force in the brain model will increase the strength requirement for the electrode, but reducethe risk of buckling of that in practical application. For humoral dissolution behavior, the dissolution rates ofthe polyethylene glycol (PEG) coating of the electrode in the brain model and rat brain were 7 000 μm3/s and5 600 μm3/s, respectively. The faster dissolution rate in the brain model will cause the larger thickness of thecoating design but provide sufficient implantable time in practical application. The establishment of the brainmodel and the research of its simulated behavior are beneficial to the size design of the electrode substrate andcoating, and research of the implantation mechanism, and further increase the functional life of the electrode.
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    Calibration Technology of Optical Fiber Strain Sensor
    CHEN Gang(陈刚), LIU Hongyue(刘宏月), GAO Ruiriang(高瑞翔)
    J Shanghai Jiaotong Univ Sci    2023, 28 (5): 551-559.   DOI: 10.1007/s12204-022-2406-9
    Abstract195)      PDF(pc) (1122KB)(93)       Save
    As one of the hotspots of sensing technology at present, optical fiber sensor has the characteristics of small size, anti-electromagnetic interference, and easy networking, which plays an irreplaceable role in multiphysics parameter monitoring of complex electromagnetic environments. The precise calibration of the optical fiber strain sensor has great practical value in prolonging the survival rate of the sensor, improving the measurement accuracy, and meeting the needs of long-term monitoring. By reviewing the research status of strain sensor calibration method and fiber optic strain sensor calibration method, the advantages and disadvantages of the main methods are analyzed separately from the static and dynamic perspectives, and the development prospect of the calibration technology of optic fiber strain sensor is summarized.
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    Action-aware Encoder-Decoder Network for Pedestrian Trajectory Prediction
    FU Jiawei∗ (傅家威), ZHAO Xu (赵 旭)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 20-27.   DOI: 10.1007/s12204-023-2565-3
    Abstract296)      PDF(pc) (775KB)(92)       Save
    Accurate pedestrian trajectory predictions are critical in self-driving systems, as they are fundamental to the response- and decision-making of ego vehicles. In this study, we focus on the problem of predicting the future trajectory of pedestrians from a first-person perspective. Most existing trajectory prediction methods from the first-person view copy the bird’s-eye view, neglecting the differences between the two. To this end, we clarify the differences between the two views and highlight the importance of action-aware trajectory prediction in the first-person view. We propose a new action-aware network based on an encoder-decoder framework with an action prediction and a goal estimation branch at the end of the encoder. In the decoder part, bidirectional long short-term memory (Bi-LSTM) blocks are adopted to generate the ultimate prediction of pedestrians’ future trajectories. Our method was evaluated on a public dataset and achieved a competitive performance, compared with other approaches. An ablation study demonstrates the effectiveness of the action prediction branch.
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    Novel Visualization Tool for Percutaneous Renal Puncture Training Using Augmented Reality Technology
    YU Jiaqi1 (于佳琪),WANG Shuyi1* (王殊轶),WANG Yuqil (王浴屺),XIE Hua2 (谢华), WU Zhangleil (吴张檑),FU Xiaonil (付小妮),MA Bangfeng1 (马邦峰)
    J Shanghai Jiaotong Univ Sci    2023, 28 (4): 517-.   DOI: 10.1007/s12204-022-2554-y
    Abstract119)      PDF(pc) (1512KB)(92)       Save
    We aim to develop a novel visualization tool for percutaneous renal puncture training based on augmented reality (AR) and compare the needle placement performance of this AR system with ultrasound-guidedfreehand navigation in phantoms. A head-mounted display-based AR navigation system was developed usingthe Unity3D software and Visual Studio to enable the overlay of the preoperative needle path and the complexanatomical structures onto a phantom in real time. The spatial location of the stationary phantom and the percutaneous instrument motion were traced by a Qualisys motion capture system. To evaluate the tracking accuracy,15 participants (7 males and 8 females) performed a single needle insertion using AR navigation (the number ofpunctures n = 75) and ultrasound-guided freehand navigation (n = 75). The needle placement error was measuredas the Euclidean distance between the actual needle tip and the virtual target by MicronTracker. All participantsdemonstrated a superior needle insertion efficiency when using the AR-assisted puncture method compared withthe ultrasound-guided freehand method. The needle insertion error of the ultrasound-guided method showed anincreased error compared with the AR method (5.54 mm ± 2.59 mm, 4.34 mm ± 2.10 mm, respectively, p < 0.05).The ultrasound-guided needle placements showed an increased time compared with the AR method (19.08 s ±3.59 s, 15.14 s ± 2.72 s, respectively, p < 0.000 1). Our AR training system facilitates the needle placement performance and solves hand-eye coordination problems. The system has the potential to increase efficiency andeffectiveness of percutaneous renal puncture training.
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    Further Result on the Observer Design for One-Sided Lipschitz Systems
    YANG Ming1 (杨 明), HUANG Jun1∗ (黄 俊), ZHANG Wei2 (章 伟)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 817-822.   DOI: 10.1007/s12204-020-2252-6
    Abstract239)      PDF(pc) (328KB)(89)       Save
    This paper investigates the problem of observer design for a class of control systems. Different from current works, the nonlinear functions in the system only satisfy the property of the one-sided Lipschitz (OSL) condition but not quadratic inner-boundedness (QIB). Moreover, the case where the OSL constant is negative is specially investigated. Firstly, a full-order observer is constructed for the original system. Then, a reduced-order observer is also designed by using the decomposition method. The advantage and effectiveness of the proposed design scheme are shown in a numerical simulation.
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    Numerical Simulation Method of Scoliosis Orthosis Considering Muscle Factor
    LI Jian1,2(李健),ZHU Ye1 (朱晔),GUAN Tianmin1*(关天民)
    J Shanghai Jiaotong Univ Sci    2023, 28 (4): 486-.   DOI: 10.1007/s12204-022-2535-1
    Abstract88)      PDF(pc) (1382KB)(87)       Save
    Adolescent idiopathic scoliosis seriously affects the physical and mental health of adolescents. In thepast, the research on therapeutic orthosis ignored the influence of muscle factors. Aimed at this problem, basedon the principle of reverse engineering, through the spine computed tomography data model of three-dimensionalreconstruction, muscle forces around the spine are imported into the spinal muscle force model and AnyBodysoftware is used for simulation. The geometric similarity and biomechanical effectiveness of the established modelare verified. In order to obtain the relationship among the applied orthopedic force, Cobb angle and vertebraldisplacement, a finite element model conforming to spinal anatomy is established, and then the biomechanicalanalysis of the finite element model of the scoliosis is carried out. Reasonable control of paravertebral muscles canplay a positive role in orthopedic treatment, and the fitting equation can provide a reference for doctors to applythe orthopedic force on patient.
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    Fault Diagnosis for Rolling Element Bearing in Dataset Bias Scenario
    HOU Liangsheng(侯良生),ZHANG Jundong*(张均东)
    J Shanghai Jiaotong Univ Sci    2023, 28 (5): 638-651.   DOI: 10.1007/s12204-021-2320-6
    Abstract42)      PDF(pc) (1575KB)(86)       Save
    Recently, data-driven methods, especially deep learning, outperform other methods for rolling element bearing (REB) fault diagnosis. Nevertheless, most research work assumes that REB dataset is unbiased. In the real industry applications, the dataset bias exists with REB owing to varying REB working conditions and noise interference. Recently proposed adversarial discriminative domain adaptation (ADDA) is an increasingly popular incarnation to solve dataset bias problem. However, it mainly devotes to realizing domain alignments, and ignores class-level alignments; it can cause degradation of classification performance. In this study, we propose a new REB fault diagnosis model based on improved ADDA to address dataset bias. The proposed diagnosis model realizes domain- and class-level alignments in dataset bias scenario; it consists of two feature extractors, a domain discriminator, and two label classifiers. The feature extractors and domain discriminator are trained in an adversarial manner to minimize the domain difference in feature extractors. The domain discrepancy in label classifier is reduced by minimizing correlation alignment (CORAL) loss. We evaluate the proposed model on the Case Western Reserve University (CWRU) bearing dataset and Paderborn University bearing dataset. The proposed method yields better results than other methods and has good prospects for industrial applications.
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    Lateral Force Characteristics of Cartridge Valve Core
    HAN Heyong1(韩贺永),ZHANG Jianru1(张建茹), PAN Siji1(潘思意),LI Yugui2*(李玉贵),MA Lifeng1(马立峰),LIU Shirui3(刘实睿)
    J Shanghai Jiaotong Univ Sci    2023, 28 (5): 604-610.   DOI: 10.1007/s12204-021-2402-5
    Abstract53)      PDF(pc) (978KB)(85)       Save
    he valve core is readily subjected to a large lateral force which affects the dynamic response speed. Here, a new type of cartridge valve core structure is proposed to solve this problem. The numerical simulation method is applied to analyze the flow characteristics of clearance flow field on velocity distribution, pressure distribution, valve core motion speed, and leakage. The results using computational fluid dynamics (CFD) show that the guide groove is set on the surface of the cartridge valve core, increasing the connecting length of the valve core, forming a uniform radial pressure distribution and velocity distribution, effectively reducing the lateral force, and at the same time ensuring that the leak is not too big. These findings provide theoretical guidance and a basis for optimizing cartridge valve to reduce the occurrence of jamming and improve the response frequency.
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    Dlung: Unsupervised Few-Shot Diffeomorphic Respiratory Motion Modeling
    CHEN Peizhi1,2* (陈培芝), GUO Yifan1 (郭逸凡),WANG Dahan1,2 (王大寒), CHEN Chinling1,3,4* (陈金铃)
    J Shanghai Jiaotong Univ Sci    2023, 28 (4): 536-.   DOI: 10.1007/s12204-022-2525-3
    Abstract133)      PDF(pc) (1720KB)(83)       Save
    Lung image registration plays an important role in lung analysis applications, such as respiratory motion modeling. Unsupervised learning-based image registration methods that can compute the deformation without the requirement of supervision attract much attention. However, it is noteworthy that they have two drawbacks: they do not handle the problem of limited data and do not guarantee diffeomorphic (topologypreserving) properties, especially when large deformation exists in lung scans. In this paper, we present an unsupervised few-shot learning-based diffeomorphic lung image registration, namely Dlung. We employ fine-tuning techniques to solve the problem of limited data and apply the scaling and squaring method to accomplish the diffeomorphic registration. Furthermore, atlas-based registration on spatio-temporal (4D) images is performed and thoroughly compared with baseline methods. Dlung achieves the highest accuracy with diffeomorphic properties. It constructs accurate and fast respiratory motion models with limited data. This research extends our knowledge of respiratory motion modeling.
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    Airframe Damage Region Division Method Based on Structure Tensor Dynamic Operator
    CAI Shuyu∗ (蔡舒妤), SHI Lizhong (师利中)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 757-767.   DOI: 10.1007/s12204-022-2498-2
    Abstract259)      PDF(pc) (1607KB)(81)       Save
    In order to improve the accuracy of damage region division and eliminate the interference of damage adjacent region, the airframe damage region division method based on the structure tensor dynamic operator is proposed in this paper. The structure tensor feature space is established to represent the local features of damage images. It makes different damage images have the same feature distribution, and transform varied damage region division into consistent process of feature space division. On this basis, the structure tensor dynamic operator generation method is designed. It integrates with bacteria foraging optimization algorithm improved by defining double fitness function and chemotaxis rules, in order to calculate the parameters of dynamic operator generation method and realize the structure tensor feature space division. And then the airframe damage region division is realized. The experimental results on different airframe structure damage images show that compared with traditional threshold division method, the proposed method can improve the division quality. The interference of damage adjacent region is eliminated. The information loss caused by over-segmentation is avoided. And it is efficient in operation, and consistent in process. It also has the applicability to different types of structural damage.
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    Applications of Polypeptide Hydrogels in Cartilage-Regeneration Engineering
    HU Yinghan1 (胡颖涵),ZHU Zegu1 (朱泽宇), TENG Lin2 (滕林), HE Yushi3 (何雨石),ZOU Derong1 (邹德荣),LU Jiayu1*(陆家瑜)
    J Shanghai Jiaotong Univ Sci    2023, 28 (4): 468-.   DOI: 10.1007/s12204-022-2507-5
    Abstract110)      PDF(pc) (3066KB)(79)       Save
    Articular cartilage defects are considered to be associated with the development of osteoarthritis. Research on relevant tissue regeneration is important in the treatment of osteoarthritis. The scaffolds applied incartilage regeneration should have good histocompatibility and mechanical properties, as well as no cytotoxicity,and promote the proliferation and differentiation of seed cells. Different combinations of peptide sequences inpolypeptide hydrogels endow them with unique characteristics including excellent biodegradability and accuratesimulation of the extracellular matrix of chondrocytes to maintain the stability of the chondrogenic phenotypeand facilitate articular hyaline cartilage regeneration. Thus, the application of polypeptide hydrogels for cartilage regeneration has a bright future. In this study, the research progress of polypeptide hydrogels used incartilage-regeneration engineering is systematically reviewed. The characteristics, limitations, and prospects ofthese materials are evaluated.
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    High Curvature Stripe Profile Extraction Algorithm of Line Structured Light Measuring System
    SUN Hao (孙昊), DU Xuan (杜宣), LÜ Na(吕娜), CUI Bin(崔斌), ZHA Hui(赵辉)
    J Shanghai Jiaotong Univ Sci    2023, 28 (5): 560-568.   DOI: 10.1007/s12204-022-2476-8
    Abstract108)      PDF(pc) (1375KB)(79)       Save
    In the line structured light measuring system, the accuracy of the process of laser stripe directly affects the measurement results. Therefore, the extraction algorithm for the laser stripe, especially the surface with high reflection and high curvature, is very important. The imaging principle of line structured light, the light intensity distribution law of laser stripe and the extraction algorithm have been studied, and a stripe profile extraction method based on real light intensity distribution has been proposed. In this algorithm, fast region of interest extraction, stripe width estimation, and adaptive filtering on the striped image are performed. Then the energy center of the stripe at the sub-pixel level is extracted. Finally, the low-quality center points are eliminated, and the context information is used to recover the missing central points. Simulated images generated based on the imaging principle of line structured light and real experimental images were used to evaluate the accuracy and repeatability of the proposed method. The results show that the method behaves excellently at the edges of high-curvature stripes; the maximum error is only 1.6 pixels, which is 1/10 of the classic Steger algorithm; the experiment repeatability is only 8.8 μm, which is 2.7 times that of the Steger method. Therefore, the proposed method improves the accuracy of object contour extraction, and it is especially suitable for contour detection of objects with high curvature.
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    Real-Time Calculation Method for Temperature Distribution of Temperature-Controlled Radiofrequency Ablation
    WANG Xuewei (王雪维),WANG Yifei (王逸飞),ZHANG Aili* (张爱丽)
    J Shanghai Jiaotong Univ Sci    2023, 28 (4): 411-.   DOI: 10.1007/s12204-022-2481-y
    Abstract174)      PDF(pc) (1220KB)(78)       Save
    Precise temperature control and temperature distribution prediction are of great significance forradiofrequency ablation. This research proposes a real-time calculation method for the temperature distribution of radiofrequency ablation combined with proportional-integral temperature control. The thermo-electricalcoupling was simplified into a linear relationship based on the study of the influence of temperature-dependentelectrical conductivity and thermal conductivity on the PI-controlled radiofrequency ablation temperature distribution, which increases the computational efficiency by 150 times. The average calculation time for radiofrequencyablation of 10 min is about 23 s, and the difference between the calculation results of this method and that fromCOMSOL Multiphysics is no more than 1 ?C. This method is not only used for single-probe, but also for doubleprobe radiofrequency ablation in this paper.
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    Boosting Unsupervised Domain Adaptation with Soft Pseudo-Label and Curriculum Learning
    ZHANG Shengjia(张晟嘉), LIN Tiancheng(林天成), XU Yi(徐奕)
    J Shanghai Jiaotong Univ Sci    2023, 28 (6): 703-716.   DOI: 10.1007/s12204-022-2487-5
    Abstract128)      PDF(pc) (963KB)(78)       Save
    By leveraging data from a fully labeled source domain, unsupervised domain adaptation (UDA) improves classification performance on an unlabeled target domain through explicit discrepancy minimization of data distribution or adversarial learning. As an enhancement, category alignment is involved during adaptation to reinforce target feature discrimination by utilizing model prediction. However, there remain unexplored problems about pseudo-label inaccuracy incurred by wrong category predictions on target domain, and distribution deviation caused by overfitting on source domain. In this paper, we propose a model-agnostic two-stage learning framework, which greatly reduces flawed model predictions using soft pseudo-label strategy and avoids overfitting on source domain with a curriculum learning strategy. Theoretically, it successfully decreases the combined risk in the upper bound of expected error on the target domain. In the first stage, we train a model with distribution alignment-based UDA method to obtain soft semantic label on target domain with rather high confidence. To avoid overfitting on source domain, in the second stage, we propose a curriculum learning strategy to adaptively control the weighting between losses from the two domains so that the focus of the training stage is gradually shifted from source distribution to target distribution with prediction confidence boosted on the target domain. Extensive experiments on two well-known benchmark datasets validate the universal effectiveness of our proposed framework on promoting the performance of the top-ranked UDA algorithms and demonstrate its consistent superior performance.
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    Improving Colonoscopy Polyp Detection Rate Using Semi-Supervised Learning
    YAO Leyul (姚乐宇),HE Fan1,3 (何凡), PENG Haixia2* (彭海霞), WANG Xiaofeng2 (王晓峰),ZHOU Lu2(周璐), HUANG Xiaolin1,3* (黄晓霖)
    J Shanghai Jiaotong Univ Sci    2023, 28 (4): 441-.   DOI: 10.1007/s12204-022-2519-1
    Abstract143)      PDF(pc) (497KB)(74)       Save
    Colorectal cancer is one of the biggest health threats to humans and takes thousands of lives every year.Colonoscopy is the gold standard in clinical practice to inspect the intestinal wall, detect polyps and remove polypsin early stages, preventing polyps from becoming malignant and forming colorectal cancer instances. In recentyears, computer-aided polyp detection systems have been widely used in colonoscopies to improve the qualityof colonoscopy examination and increase the polyp detection rate. Currently, the most efficient computer-aidedsystems are built with machine learning methods. However, developing such a computer-aided detection systemrequires experienced doctors to label a large number of image data from colonoscopy videos, which is extremelytime-consuming, laborious and expensive. One possible solution is to adopt a semi-supervised learning, which canbuild a detection system on a dataset where part of its data is not necessary to be labeled. In this paper, on thebasis of state-of-the-art object detection method and semi-supervised learning technique, we design and implementa semi-supervised colonoscopy polyp detection system containing four main steps: running standard supervisedtraining with all labeled data; running inference on unlabeled data to obtain pseudo labels; applying a set ofstrong augmentation to both unlabeled data and pseudo label; combining labeled data, and unlabeled data withits pseudo labels to retrain the detector. The semi-supervised learning system is evaluated both on public datasetand our original private dataset and proves its effectiveness. Also, the inference speed of the semi-supervisedlearning system can meet the requirement of real-time operation.
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    Construction on Aerodynamic Surrogate Model of Stratospheric Airship
    QIN Pengfei (秦鹏飞), WANG Xiaoliang∗ (王晓亮)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 768-779.   DOI: 10.1007/s12204-022-2494-6
    Abstract257)      PDF(pc) (3866KB)(72)       Save
    Stratospheric airship can stay at an altitude of 20 km for a long time and carry various loads to achieve long-term stable applications. Conventional stratospheric airship configuration mainly includes a low-resistance streamline hull and inflatable “X”-layout fins that realize the self-stabilization. A fast aerodynamic predictive method is needed in the optimization design of airship configuration and the flight performance analysis. In this paper, a predictive surrogate model of aerodynamic parameters is constructed for the stratospheric airship with “X” fins based on the neural network. First, a geometric shape parameterized model, and a flow field parameterized model were established, and the aerodynamic coefficients of airships with different shapes used as the training and test samples were calculated based on computational fluid dynamics (SA turbulence model). The improved Bayesian regularized neural network was used as the surrogate model, and 20 types of airships with different shapes were used to test the effectiveness of network. It showed that the correlation coefficients of Cx, Cy, Cz, CM,x, CM,y, CM,z were 0.928 7, 0.991 7, 0.991 9, 0.958 2, 0.986 1, 0.984 2, respectively. The aerodynamic coefficient distribution contour at different angles of attack and sideslip angles is used to verify the reliability of the method. The method can provide an effective way for a rapid estimation of aerodynamic coefficients in the airship design.
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    Novel Concentric Tube Robot Based on Double-Threaded Helical Gear Tube
    CHEN Weichi(陈韦池), LIU Haocheng(刘浩城), LI Zijian(李子建), GUO Jing, (郭靖), ZHAI Zhenkun(翟振坤), MENG Wei(孟伟)
    J Shanghai Jiaotong Univ Sci    2023, 28 (3): 296-306.   DOI: 10.1007/s12204-023-2595-x
    Abstract244)      PDF(pc) (2087KB)(70)       Save
    Nasopharyngeal carcinoma is a malignant tumor originating from the nasal mucosa. It is a malignant tumor of the head and neck. Concentric tube robot (CTR), as it can form a complicated shape and access hardto-reach lesions, is often used in minimally invasive surgeries. However, some CTRs are bulky because of their transmission design. In this paper, a light CTR based on double-threaded helical gear tube is proposed. Such a CTR is less cumbersome than the traditional CTR as its actuation unit is compact and miniaturized. The mapping relationship between the gear tube attitude and motor output angle is obtained by kinematic analysis. The precision, stability, and repeatability of the driving mechanism are tested. The experimental results show that the positioning error in the translation test is less than 0.3 mm, the rolling angle error in the stability test is less than 0.6?, and the error in the translation repeatability test is less than 0.005 mm. Finally, a tip-targeting test is performed using the new CTR, which verifies the feasibility of the CTR for surgeries.
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    Review on Anti-Frost Technology Based on Microchannel Heat Exchanger
    YE Zhenhong(叶振鸿), WANG Wei(王炜), LI Xinhua(李新华), CHEN Jiangping(陈江平)
    J Shanghai Jiaotong Univ Sci    2024, 29 (2): 161-178.   DOI: 10.1007/s12204-022-2539-x
    Abstract97)      PDF(pc) (4397KB)(68)       Save
    Frosting is an inevitable adverse phenomenon in many fields such as industrial refrigeration, cryogenics, and heat pump air conditioning, which may influence the efficiency of the equipment and increase the energy consumption of the system. The complicated louvered-fin structure and fluid-channels arrangements of the microchannel heat exchanger (HEX) will affect the heat transfer performance and frosting characteristics. First, this article analyzes different factors such as refrigerant distribution, refrigerant flow pattern, and HEX surface temperature distribution. Further, combined with the features of the microchannel HEX, the existing anti-frosting technologies and various methods of surface treatment for anti-frosting are summarized. The review focuses on the preparation of superhydrophobic surfaces and their superior properties. Furthermore, the internal mechanism is analyzed in conjunction with the relevant research of our group. Superhydrophobic character has excellent anti-frosting performance and heat transfer performance, which is of great significance for improving energy-saving and system performance. Finally, the future development of superhydrophobic surface technology is analyzed and prospected.
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    Gene Expression Profiling Identifies Potential Biomarkers for Colorectal Cancer Using NanoString nCounter Assay
    ZHAO Hui (赵晖),WEN Baiqing (文柏清),KANG Yani*(康亚妮)
    J Shanghai Jiaotong Univ Sci    2023, 28 (4): 432-.   DOI: 10.1007/s12204-022-2440-7
    Abstract108)      PDF(pc) (627KB)(67)       Save
    Colorectal cancer (CRC) is one of the most common malignancies worldwide. Development of predictivemolecular markers may help to achieve the best outcome in clinic. The purpose of this study is to identify thedifferentially expressed genes and new potential predictive and prognostic molecular biomarkers for CRC. Inthis study, CRC and matched normal tissues acquired from the same patient were used to extract total RNA.The NanoString nCounter assay was applied to determine the differentially expressed genes. The results werethen validated by using the Cancer Genome Atlas data. Finally, we identified 27 genes that revealed significantcorrelation with CRC in the tumor tissue. Several genes in the pan-cancer panel showed significant differentialexpression, which were more universal than others in the CRC tissue. Since some of them have not been reportedas being directly related to CRC yet, future mechanism studies can be designed based on this study. Our studydemonstrated NanoString nCounter assay could serve as an alternative approach for gene expression analysis andidentified several unreported differently expressed genes in CRC patients, which may provide some importantclues for more in-depth study of CRC and serve as potential predictive molecular biomarkers for clinical diagnosisapplication.
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    Strength-Toughness Improvement of 15-5PH Stainless Steel by Double Aging Treatment
    TE Rigele (特日格乐), ZHANG Yutuo, ∗ (张玉妥)
    J Shanghai Jiaotong Univ Sci    2023, 28 (2): 270-279.   DOI: 10.1007/s12204-021-2390-5
    Abstract373)      PDF(pc) (3166KB)(67)       Save
    To obtain better strength-toughness balance of 15-5PH stainless steel, a double aging treatment is proposed to investigate the mechanical properties and microstructure evolution. In this study, Cu precipitates and reversed austenite played a determining role to improve strength-toughness combination. The microstructure was observed using electron backscattered diffraction, transmission electron microscopy and scanning transmission electron microscopy. The volume fractions of Cu precipitates and reversed austenite were calculated with Thermo-Calc software and measured by X-ray diffraction. The results showed that the reversed austenite is formed at the martensitic lath boundaries and its volume fraction also increases with the increase of the aging temperature. At the same time, the size of the Cu precipitates gradually increases. Compared with the traditional single aging and double aging treatment, double aging treatment of 15-5PH stainless steel can increase the toughness while retaining the necessary strength. During double aging of 550 ℃ × 4 h + 580 ℃ × 1 h, 15-5PH stainless steel has the best strength and low-temperature (- 40 ℃) toughness match. Its yield strength, ultimate tensile strength and the Charpy impact energy are 1.037 GPa, 1.086 GPa and 179 J, respectively.
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    Novel Scheme for Essential Proteins Identification Based on Improved Multicriteria Decision Making
    LU Pengli1* (卢鹏丽),CHEN Yuntian1 (陈云天), LIAO Yonggang2 (廖永刚)
    J Shanghai Jiaotong Univ Sci    2023, 28 (4): 418-.   DOI: 10.1007/s12204-023-2584-0
    Abstract109)      PDF(pc) (1360KB)(66)       Save
    Identifying essential proteins from protein-protein interaction networks is important for studies onbiological evolution and new drug’s development. Most of the presented criteria for prioritizing essential proteinsonly focus on a certain attribute of the proteins in the network, which suffer from information loss. In order toovercome this problem, a relatively comprehensive and effective novel method for essential proteins identificationbased on improved multicriteria decision making (MCDM), called essential proteins identification-technique fororder preference by similarity to ideal solution (EPI-TOPSIS), is proposed. First, considering different attributes ofproteins, we propose three methods from different aspects to evaluate the significance of the proteins: gene-degreecentrality (GDC) for gene expression sequence; subcellular-neighbor-degree centrality (SNDC) and subcellular-indegree centrality (SIDC) for subcellular location information and protein complexes. Then, betweenness centrality(BC) and these three methods are considered together as the multiple criteria of the decision-making model.Analytic hierarchy process is used to evaluate the weights of each criterion, and the essential proteins are prioritizedby an ideal solution of MCDM, i.e., TOPSIS. Experiments are conducted on YDIP, YMIPS, Krogan and BioGRIDnetworks. The results indicate that EPI-TOPSIS outperforms several state-of-the-art approaches for identifyingthe essential proteins through the performance measures.
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    Reliability Evaluation of Two-Phase Degradation Process with a Fuzzy Change-Point
    LIU Kai1 (刘 凯), DANG Wei1 (党 炜), ZOU Tianji1,2∗ (邹田骥), LÜ Congmin1 (吕从民), LI Peng1,2 (李 鹏), ZHANG Haitao1 (张海涛)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 867-872.   DOI: 10.1007/s12204-021-2323-3
    Abstract232)      PDF(pc) (484KB)(63)       Save
    For some products, degradation mechanisms change during testing, and therefore, their degradation patterns vary at different points in time; these points are called change-points. Owing to the limitation of measurement costs, time intervals for degradation measurements are usually very long, and thus, the value of change-points cannot be determined. Conventionally, a certain degradation measurement is selected as the change-point in a two-phase degradation process. According to the tendency of the two-phase degradation process, the change-point is probably located in the interval between two neighboring degradation measurements, and it is a fuzzy variable. The imprecision of the change-point may lead to the incorrect product’s reliability evaluation results. In this paper, based on the fuzzy theory, a two-phase degradation model with a fuzzy change-point and a statistical analysis method are proposed. First, a two-phase Wiener degradation model is developed according to the membership function of the change-point. Second, the reliability evaluation is carried out using maximum likelihood estimation and a fuzzy simulation approach. Finally, the proposed methodology is verified via a case study. The results of the study show that the proposed methodology can achieve more believable reliability evaluation results compared with those of the conventional approach.
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    Semantic Segmentation-Based Road Marking Detection Using Around View Monitoring System
    XU Hanqing (徐汉卿), YANG Ming∗ (杨 明), DENG Liuyuan (邓琉元), LI Hao (李 颢), WANG Chunxiang, (王春香), HAN Weibin (韩伟斌), YU Yuelong (于跃龙)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 833-843.   DOI: 10.1007/s12204-021-2401-6
    Abstract266)      PDF(pc) (1134KB)(61)       Save
    Road marking detection is an important branch in autonomous driving, understanding the road information. In recent years, deep-learning-based semantic segmentation methods for road marking detection have been arising since they can generalize detection result well under complicated environments and hold rich pixel-level semantic information. Nevertheless, the previous methods mostly study the training process of the segmentation network, while omitting the time cost of manually annotating pixel-level data. Besides, the pixel-level semantic segmentation results need to be fitted into more reliable and compact models so that geometrical information of road markings can be explicitly obtained. In order to tackle the above problems, this paper describes a semantic segmentation-based road marking detection method using around view monitoring system. A semiautomatic semantic annotation platform is developed, which exploits an auxiliary segmentation graph to speed up the annotation process while guaranteeing the annotation accuracy. A segmentation-based detection module is also described, which models the semantic segmentation results for the more robust and compact analysis. The proposed detection module is composed of three parts: vote-based segmentation fusion filtering, graph-based road marking clustering, and road-marking fitting. Experiments under various scenarios show that the semantic segmentation-based detection method can achieve accurate, robust, and real-time detection performance.
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    Lidar-Visual-Inertial Odometry with Online Extrinsic Calibration
    MAO Tianyang (茅天阳), ZHAO Wentao (赵文韬), WANG Jingchuan∗ (王景川), CHEN Weidong (陈卫东)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 70-76.   DOI: 10.1007/s12204-023-2570-6
    Abstract276)      PDF(pc) (988KB)(61)       Save
    To achieve precise localization, autonomous vehicles usually rely on a multi-sensor perception system surrounding the mobile platform. Calibration is a time-consuming process, and mechanical distortion will cause extrinsic calibration errors. Therefore, we propose a lidar-visual-inertial odometry, which is combined with an adapted sliding window mechanism and allows for online nonlinear optimization and extrinsic calibration. In the adapted sliding window mechanism, spatial-temporal alignment is performed to manage measurements arriving at different frequencies. In nonlinear optimization with online calibration, visual features, cloud features, and inertial measurement unit (IMU) measurements are used to estimate the ego-motion and perform extrinsic calibration. Extensive experiments were carried out on both public datasets and real-world scenarios. Results indicate that the proposed system outperforms state-of-the-art open-source methods when facing challenging sensor-degenerating conditions.
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