Search results for: Zhihao Zheng

Authors: Zhihao Zheng, Zhilin Wang, Linxin Liu

Abstract:

In the research of automated knowledge question-answering systems, accuracy and efficiency are critical challenges. This paper proposes a knowledge graph-enhanced Retrieval-Augmented Generation (RAG) method, combined with a Graph Neural Network (GNN) structure, to automatically determine the correctness of knowledge competition questions. First, a domain-specific knowledge graph was constructed from a large corpus of academic journal literature, with key entities and relationships extracted using Natural Language Processing (NLP) techniques. Then, the RAG method's retrieval module was expanded to simultaneously query both text databases and the knowledge graph, leveraging the GNN to further extract structured information from the knowledge graph. During answer generation, contextual information provided by the knowledge graph and GNN is incorporated to improve the accuracy and consistency of the answers. Experimental results demonstrate that the knowledge graph and GNN-enhanced RAG method perform excellently in determining the correctness of questions, achieving an accuracy rate of 95%. Particularly in cases involving ambiguity or requiring contextual information, the structured knowledge provided by the knowledge graph and GNN significantly enhances the RAG method's performance. This approach not only demonstrates significant advantages in improving the accuracy and efficiency of automated knowledge question-answering systems but also offers new directions and ideas for future research and practical applications.

Keywords: knowledge graph, graph neural network, retrieval-augmented generation, NLP

Procedia PDF Downloads 2

Authors: Zhilin Wang, Zhihao Zheng, Linxin Liu

Abstract:

This study proposes a low-code model-building approach that aims to simplify the development and deployment of artificial intelligence (AI) models. With an intuitive way to drag and drop and connect components, users can easily build complex models and integrate multiple algorithms for training. After the training is completed, the system automatically generates a callable model service API. This method not only lowers the technical threshold of AI development and improves development efficiency but also enhances the flexibility of algorithm integration and simplifies the deployment process of models. The core strength of this method lies in its ease of use and efficiency. Users do not need to have a deep programming background and can complete the design and implementation of complex models with a simple drag-and-drop operation. This feature greatly expands the scope of AI technology, allowing more non-technical people to participate in the development of AI models. At the same time, the method performs well in algorithm integration, supporting many different types of algorithms to work together, which further improves the performance and applicability of the model. In the experimental part, we performed several performance tests on the method. The results show that compared with traditional model construction methods, this method can make more efficient use, save computing resources, and greatly shorten the model training time. In addition, the system-generated model service interface has been optimized for high availability and scalability, which can adapt to the needs of different application scenarios.

Keywords: low-code, model building, artificial intelligence, algorithm integration, model deployment

Procedia PDF Downloads 0

Authors: Mengjiao Hu

Abstract:

Nowadays, China's consumption pattern is entering the "experience era"; people's consumption behavior is no longer simply "buy, buy, buy" but the transition from "consumption in space" to "consumption of space". The street is a basic public product and an important public space in the city, and commerce along the street is an important space for people to consume in the "experience era". Therefore, in this way, it is particularly important to create the vitality of the gray space along the street. From the perspective of vitality construction, this paper takes Sha Zheng Street in Chongqing as the empirical object, combined with the theoretical knowledge of behavioral architecture, and based on the current situation of the commercial gray space along Sha Zheng Street, this paper explores the influence factors and the constraints behind the spatial vitality and then puts forward a general strategy to improve the spatial vitality of the commercial gray space along the street. The author hopes that through the exploration of the vitality of commercial gray space along the street, environmental design can be introduced into the integrated design vision of the urban public environment, and the urban designers can be inspired to create a street environment with a living atmosphere with a small start.

Keywords: vitality creation, gray space, street commerce, sha zheng street

Procedia PDF Downloads 78

Authors: Wenfu Zheng, Guanghe Zheng

Abstract:

The discussion on the social sustainability in existing literature is limited to two-dimension epistemology space with only two elements: the human and nature. Using the revelation of the Bible God, the paper adds a moral component to the two-dimension space. With the new variable being introduced, the authors formulate a to three-dimension epistemology space and discuss its implications. Based on the space, the authors explore the hierarchical structure of order principles for a sustainable society. The social order principle system hierarchically consists of three principles: moral, relational, and rational. The justification of every principle is analyzed briefly. The paper concluded that all these order principles are necessary assurance of building a sustainable society.

Keywords: common grace, saving grace, sustainable society, the image of God

Procedia PDF Downloads 175

Authors: William Ceurvels, Dong-Di Zhang

Abstract:

The true nature of the mechanism by which the pharmaceuticals of the Shang-Han Lun act has been a topic of debate since Wuji Cheng published the first commentary during the Northern Song. Subsequent commentaries employed a number of methodologies in their analysis of pharmaceutical mechanisms, but no commentator was able to garner universal acceptance. During the Qing Dynasty, the proliferation and development of Neo-Confucian scholarship produced a new generation of scholars possessed of rigorous and inventive research methods, one of whom was the famed materia medica scholar, Run-an Zou. Run-an Zou and his successor Zhou Yan advocated analyzing the mechanism of Treatise pharmaceuticals based upon the understanding of those pharmaceuticals during the time period in which the Treatise was written and thereby focused on the Han Dynasty materia medica tract Shen-nong Ben-cao Jing (The Divine Husbandman’s Herbal Foundation Canon). Zou Run-an’s commentary, Ben-jing Shu-zheng won nearly universal praise among materia medica scholars for its scholastic rigor and innovative research methods. However, because Ben-jing Shu-zheng only focuses on individual herbs, as opposed to formulas, its value in analyzing the Shang-Han Lun has limitations. The purpose of this study is to combine Zou Run-an’s single-pharmaceutical commentaries to generate theoretical full formula analyses to gain a fuller picture of Zou’s understanding of the healing mechanism of Shang-Han Lun formulas. Commentaries were gathered from Ben-jing Shu-zheng and Zhou Yan’s Ben-cao Si-bian Lun and combined to produce theoretical full formula model mechanisms of Treatise formulas. Through this study, a new picture of the mechanistic basis of Shang-han formulas emerges, which is based on qi-xue changes as opposed to organ or meridian theory. The author hopes that this modest research study will be of service to scholars of the Shang-han and clinical doctors alike in their pursuit of the true pharmacomechanisms of this great Han dynasty tome.

Keywords: Materia medica, Shang-han Lun, Shen-nong Ben-cao Jing, neo-Confucian scholarship

Procedia PDF Downloads 300

Authors: Kenny Chi Man Chui

Abstract:

Background: In Chinese culture, the traditional equivalent term for English dementia is chi dai zheng, which, whether translated as ‘insanity’ or ‘idiocy’ carries a sharply negative connotation. In fact, even though the traditional name for dementia has evolved, from chi dai zheng to shi zhi zheng, nao tui hua zheng or ren zhi zhang ai zheng, educating the population about more respectful terms for the condition and promoting a positive understanding about people with dementia in society have proven to be time-intensive endeavors. By extension, the use of such terms promotes the perception that people with dementia undergo a ‘total loss of self’ or experience a ‘living death’ or ‘social death’. Both in Asia and elsewhere, the appropriate nomenclature for dementia remains controversial, and different medical and healthcare professionals in Hong Kong have taken various stances on how to refer to the condition there. Indeed, how this negative perception affects the interaction between people with dementia and the surrounding others? Methodology: Qualitative research with the concept of postmodernism, interpretivism, and Foucauldian theory was adopted as frameworks in applying participatory observations, in-depth interviews, and other qualitative methods. First, ten people with dementia—one man and nine women—living in two residential care homes in Hong Kong were interviewed, as were ten members of the care staff, all of whom were women. Next, to coach the staff in understanding the feelings and self-perceptions of people with dementia, two reflective training sessions were provided. Afterward, to assess the impact of the training sessions on the staff, two focus groups were held. Findings: The findings revealed that residents with dementia did not perceive themselves as being ‘demented’ and were confused by not getting responses from the others. From the understanding of care staff, they perceived the residents as being ‘demented’, desolate troublemakers. They described people with dementia as ‘naughty children’ who should be controlled and be punished while treated them as ‘psychiatric patients’ who could be ignored and be mute. “Psychosocial restraint” happened regarding the discrepancy of perception between people with dementia and the care staff. People with dementia did not think that their confusion of memory was related to dementia or, frankly speaking, they did not know what dementia was. When others treated them as ‘demented patients, the residents with mild to moderate dementia fiercely rejected that designation and reported a host of negative feelings, hence the fluctuations of mood and emotion noted by the care staff. Conclusion: As the findings revealed, the people with dementia were also discontent with the care arrangements in the care homes, felt abandoned by others and worried about bothering others. Their shifting emotional states and moods were treated as the Behavioral and Psychological symptoms of Dementia (BPSD), which nothing can do reported by the care staff in the residential care homes. People with dementia become social withdrawal or isolated in daily living, which should be alert and be changed by the social work professionals about the occurrence of “psychosocial restraint” in dementia care.

Keywords: psychosocial restraint, qualitative research, social work with dementitude, voice of people with dementia

Procedia PDF Downloads 161

Authors: Zhihao Zhao, Ali El-Nagger, Johnson Kau, Chris Olson, Douglas Tomlinson, Scott X. Chang

Abstract:

One strategy to reduce CO₂ emissions from cement production is to reduce the amount of Portland cement produced by replacing it with supplementary cementitious materials (SCMs). Biochar is a potential SCM that is an eco-friendly and stable porous pyrolytic material. However, the effects of biochar addition on the performances of Portland cement composites are not fully understood. This meta-analysis investigated the impact of biochar addition on the 7- and 28-day compressive strength of Portland cement composites based on 606 paired observations. Biochar feedstock type, pyrolysis conditions, pre-treatments and modifications, biochar dosage, and curing type all influenced the compressive strength of Portland cement composites. Biochars obtained from plant-based feedstocks (except rice and hardwood) improved the 28-day compressive strength of Portland cement composites by 3-13%. Biochars produced at pyrolysis temperatures higher than 450 °C, with a heating rate of around 10 °C/min, increased the 28-day compressive strength more effectively. Furthermore, the addition of biochars with small particle sizes increased the compressive strength of Portland cement composites by 2-7% compared to those without biochar addition. Biochar dosage of < 2.5% of the binder weight enhanced both compressive strengths and common curing methods maintained the effect of biochar addition. However, when mixing the cement, adding fine and coarse aggregates such as sand and gravel affects the concrete and mortar's compressive strength, diminishing the effect of biochar addition and making the biochar effect nonsignificant. We conclude that appropriate biochar addition could maintain or enhance the mechanical performance of Portland cement composites, and future research should explore the mechanisms of biochar effects on the performance of cement composites.

Keywords: biochar, Portland cement, constructure, compressive strength, meta-analysis

Procedia PDF Downloads 49

Authors: Yuanchao Sang, Zhihao Gong, Longsheng Chen, Long Chen

Abstract:

Clothing fashion represents a human’s aesthetic appreciation towards everyday outfits and appetite for fashion, and it reflects the development of status in society, humanity, and economics. However, modelling fashion by machine is extremely challenging because fashion is too abstract to be efficiently described by machines. Even human beings can hardly reach a consensus about fashion. In this paper, we are dedicated to answering a fundamental fashion-related problem: what image feature best describes clothing fashion? To address this issue, we have designed and evaluated various image features, ranging from traditional low-level hand-crafted features to mid-level style awareness features to various current popular deep neural network-based features, which have shown state-of-the-art performance in various vision tasks. In summary, we tested the following 9 feature representations: color, texture, shape, style, convolutional neural networks (CNNs), CNNs with distance metric learning (CNNs&DML), AutoEncoder, CNNs with multiple layer combination (CNNs&MLC) and CNNs with dynamic feature clustering (CNNs&DFC). Finally, we validated the performance of these features on two publicly available datasets. Quantitative and qualitative experimental results on both intra-domain and inter-domain fashion clothing image retrieval showed that deep learning based feature representations far outweigh traditional hand-crafted feature representation. Additionally, among all deep learning based methods, CNNs with explicit feature clustering performs best, which shows feature clustering is essential for discriminative fashion feature representation.

Keywords: convolutional neural network, feature representation, image processing, machine modelling

Procedia PDF Downloads 126

Authors: Wang Xiaoqing, Fang Youyuan, Zheng Yanxing, Gu Tianyang, Zong Jianjian, Tong Jinrong

Abstract:

Compared with traditional distributed environment, the net-centric environment brings on more demanding challenges for information sharing with the characteristics of ultra-large scale and strong distribution, dynamic, autonomy, heterogeneity, redundancy. This paper realizes an information sharing model and a series of core services, through which provides an open, flexible and scalable information sharing platform.

Keywords: net-centric environment, information sharing, metadata registry and catalog, cross-domain data access control

Procedia PDF Downloads 552

Authors: Enoch Kudoahor, Nan Zheng

Abstract:

We describe the use of readily available self-doped TiO2 and visible light, under a mild condition to synthesize a class of monocyclic, bicyclic, and benzocyclobutene amino compounds containing the endoperoxide bridges; their derivatives and further test their effective clinical activities against malaria, cancer, and their resistances. Considering their stable under photooxidation conditions and recyclability, we use a self-doped TiO2 under a visible condition to synthesize these classes of amino endoperoxides. These amino endoperoxides are stable over a period compared to classes of endoperoxides.

Keywords: catalysis, endoperoxides, titanium dioxide, visible light

Procedia PDF Downloads 139

Authors: Zheng Miao, Dennis Fernandez

Abstract:

CRISPR research has the potential to completely transform life science, agriculture, live-stock and the health care industry. The Intellectual Property derived from its research has raised significant attention in the academic as well as the biopharmaceutical industry culminating an urgent need for strategic IP protection. We review the rudimentary concepts and key competitors of CRISPR technologies as well as the paramount strategies for intellectual property protection. Further, we elaborate on prosecution issues related to CRISPR patents as well as possible solutions to various patent laws, interferences and litigation. Finally, we address how the bioinformatics of the CRISPR technology begs an inquiry into issues of privacy and a host of ethical concerns.

Keywords: bioinformatics, CRISPR, biotechnology, intellectual property

Procedia PDF Downloads 239

Authors: Jian Zheng, Xinhua Ni, Xiequan Liu

Abstract:

According to isotropy of parallel fiber eutectic, the no- damage strain field in parallel fiber eutectic is obtained from the flexibility tensor of parallel fiber eutectic. Considering the damage behavior of parallel fiber eutectic, damage variables are introduced to determine the strain field of parallel fiber eutectic. The damage strains in the matrix, interphase, and fiber of parallel fiber eutectic are quantitatively analyzed. Results show that damage strains are not only associated with the fiber volume fraction of parallel fiber eutectic, but also with the damage degree.

Keywords: damage strain, initial strain, fiber volume fraction, parallel fiber eutectic

Procedia PDF Downloads 558

Authors: Yali Zheng, Peipei Luo, Shinan Chen, Jiasheng Hao, Hong Cheng

Abstract:

Most of traditional visual indoor navigation algorithms and methods only consider the localization in ordinary daytime, while we focus on the indoor re-localization in low light in the paper. As RGB images are degraded in low light, less discriminative infrared and depth image pairs are taken, as the input, by RGB-D cameras, the most similar candidates, as the output, are searched from databases which is built in the bag-of-word framework. Epipolar constraints can be used to relocalize the query infrared and depth image sequence. We evaluate our method in two datasets captured by Kinect2. The results demonstrate very promising re-localization results for indoor navigation system in low light environments.

Keywords: indoor navigation, low light, RGB-D camera, vision based

Procedia PDF Downloads 440

Authors: Meimei Zheng

Abstract:

Product personalization could not only bring new profits to companies but also provide the direction of long-term development for companies. However, the characteristics of personalized product cause some new problems. This paper investigates how companies make decisions on the supply of personalized products when facing different customer attitudes to personalized product and service, constraints due to limited capacity and updates of personalized demand information. This study will provide optimal decisions for companies to develop personalized markets, resulting in promoting business transformation and improving business competitiveness.

Keywords: demand forecast updating, limited capacity, personalized products, optimization

Procedia PDF Downloads 242

Authors: Jian Zheng, Yoshiyasu Takahashi, Yuichi Kobayashi, Tatsuhiro Sato

Abstract:

In the study, we present a conceptual framework for developing a scheduling system that can generate self-explanatory and easy-understanding schedules. To this end, a user interface is conceived to help planners record factors that are considered crucial in scheduling, as well as internal and external sources relating to such factors. A hybrid approach combining machine learning and constraint programming is developed to generate schedules and the corresponding factors, and accordingly display them on the user interface. Effects of the proposed system on scheduling are discussed, and it is expected that scheduling efficiency and system understandability will be improved, compared with previous scheduling systems.

Keywords: constraint programming, factors considered in scheduling, machine learning, scheduling system

Procedia PDF Downloads 308

Authors: Yiqiang Ni, Xuanlong Chen, Enliang Li, Linting Zheng, Shizheng Yang

Abstract:

Bipolar ICs are playing an important role in military applications, mainly used in logic gates, such as inverter and NAND gate. The defect of metal break located on the step is one of the main failure mechanisms of bipolar ICs, resulting in open-circuit or functional failure. In this situation, general failure localization methods like optical beam-induced resistance change (OBIRCH) and photon emission microscopy (PEM) might not be fully effective. However, active voltage contrast (AVC) can be used as a voltage probe, which may pinpoint the incorrect potential and thus locate the failure position. Two case studies will be present in this paper on how to implement AVC for failure localization, and the detailed failure mechanism will be discussed.

Keywords: bipolar IC, failure localization, metal break, open failure, voltage contrast

Procedia PDF Downloads 271

Authors: Xia Yang, Zheng Yang, Haiyong Sun, Yan Fang, Jingyu Liu, Jia Song

Abstract:

The smart contract in Ethereum is a unique program deployed on the Ethereum Virtual Machine (EVM) to help manage cryptocurrency. The security of this smart contract is critical to Ethereum’s operation and highly sensitive. In this paper, we present a formal model for smart contract, using the separated term-obligation (STO) strategy to formalize and verify the smart contract. We use the IBM smart sponsor contract (SSC) as an example to elaborate the detail of the formalizing process. We also propose a formal smart sponsor contract model (FSSCM) and verify SSC’s security properties with an interactive theorem prover Coq. We found the 'Unchecked-Send' vulnerability in the SSC, using our formal model and verification method. Finally, we demonstrate how we can formalize and verify other smart contracts with this approach, and our work indicates that this formal verification can effectively verify the correctness and security of smart contracts.

Keywords: smart contract, formal verification, Ethereum, Coq

Procedia PDF Downloads 660

Authors: Kah-Hyong Chang, Xin Liu, Jia Hao Cheong, Saisundar Sankaranarayanan, Dexing Pang, Hongzhao Zheng

Abstract:

A digital baseband Application-Specific Integrated Circuit (ASIC) is developed for a microchip transponder to transmit signals and temperature levels from biomedical monitoring devices. The transmission protocol is adapted from the ISO/IEC 11784/85 standard. The module has a decimation filter that employs only a single adder-subtractor in its datapath. The filtered output is coded with cyclic redundancy check and transmitted through backscattering Load Shift Keying (LSK) modulation to a reader. Fabricated using the 0.18-μm CMOS technology, the module occupies 0.116 mm² in chip area (digital baseband: 0.060 mm², decimation filter: 0.056 mm²), and consumes a total of less than 0.9 μW of power (digital baseband: 0.75 μW, decimation filter: 0.14 μW).

Keywords: biomedical sensor, decimation filter, radio frequency integrated circuit (RFIC) baseband, temperature sensor

Procedia PDF Downloads 378

Authors: Yufu Yin, Tao Lin, Shanghong Zhao, Zihang Zhu, Xuan Li, Wei Jiang, Qiurong Zheng, Hui Wang

Abstract:

In this paper, a frequency-dependent and tunable phase shifter is proposed and numerically analyzed. The key devices are the dual-polarization binary phase shift keying modulator (DP-BPSK) and the fiber Bragg grating (FBG). The phase-frequency response of the FBG is employed to determine the frequency-dependent phase shift. The simulation results show that a linear phase shift of the recovered output microwave signal which depends on the frequency of the input RF signal is achieved. In addition, by adjusting the power of the RF signal, the full range phase shift from 0° to 360° can be realized. This structure shows the spurious free dynamic range (SFDR) of 70.90 dB·Hz^2/3 and 72.11 dB·Hz^2/3 under different RF powers.

Keywords: microwave photonics, phase shifter, spurious free dynamic range, frequency-dependent

Procedia PDF Downloads 275

Authors: Yuanqing Li, Changyi Lei, Zhaopeng Xue, Zhuo Zheng, Yanbo Long

Abstract:

In agricultural production and breeding, implementing automatic picking robot in orchard farming to reduce human labour and error is challenging. The core function of it is automatic identification based on machine vision. This paper focuses on apple detection and counting in orchards and implements several deep learning methods. Extensive datasets are used and a semi-automatic annotation method is proposed. The proposed deep learning models are in state-of-the-art YOLO family. In view of the essence of the models with various backbones, a multi-dimensional comparison in details is made in terms of counting accuracy, mAP and model memory, laying the foundation for realising automatic precision agriculture.

Keywords: agricultural object detection, deep learning, machine vision, YOLO family

Procedia PDF Downloads 183

Authors: Zheng Baichuan, Li Shenghui, Li Bingqian, Zhang Ning, Chen Kai

Abstract:

Entity alignment (EA) tasks in knowledge graphs often play a pivotal role in the integration of knowledge graphs, where structural differences often exist between the source and target graphs, such as the presence or absence of attribute information and the types of attribute information (text, timestamps, images, etc.). However, most current research efforts are focused on improving alignment accuracy, often along with an increased reliance on specific structures -a dependency that inevitably diminishes their practical value and causes difficulties when facing knowledge graph alignment tasks with varying structures. Therefore, we propose a universal knowledge graph alignment approach that only utilizes the common basic structures shared by knowledge graphs. We have demonstrated through experiments that our method achieves state-of-the-art performance in fair comparisons.

Keywords: knowledge graph, entity alignment, transformer, deep learning

Procedia PDF Downloads 31

Authors: Shiyin He, Zheng Huang

Abstract:

In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.

Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet

Procedia PDF Downloads 169

Authors: Li Qiang, Yang Ze-Ming, Liu Bao-Xu, Jiang Zheng-Wei

Abstract:

With the increasing complexity of cyberspace security, the cyber-attack attribution has become an important challenge of the security protection systems. The difficult points of cyber-attack attribution were forced on the problems of huge data handling and key data missing. According to this situation, this paper presented a reasoning method of cyber-attack attribution based on threat intelligence. The method utilizes the intrusion kill chain model and Bayesian network to build attack chain and evidence chain of cyber-attack on threat intelligence platform through data calculation, analysis and reasoning. Then, we used a number of cyber-attack events which we have observed and analyzed to test the reasoning method and demo system, the result of testing indicates that the reasoning method can provide certain help in cyber-attack attribution.

Keywords: reasoning, Bayesian networks, cyber-attack attribution, Kill Chain, threat intelligence

Procedia PDF Downloads 434

Authors: Salvador Garcia Bernal, Chi Zheng, Keqi Zhang, Lei Mao

Abstract:

Circulating Tumor Cells (CTC) is used to detect tumoral cell metastases using blood samples of patients with cancer (lung, breast, etc.). Using an immunofluorescent method a three channel image (Red, Green, and Blue) are obtained. These set of images usually overpass the 11 x 30 M pixels in size. An aided tool is designed for imaging cell analysis to segmented and identify the tumorous cell based on the three markers signals. Our Method, it is cell-based (area and cell shape) considering each channel information and extracting and making decisions if it is a valid CTC. The system also gives information about number and size of tumor cells found in the sample. We present results in real-life samples achieving acceptable performance in identifying CTCs in short time.

Keywords: Circulating Tumor Cells (CTC), cell analysis, immunofluorescent, medical image analysis

Procedia PDF Downloads 202

Authors: Xiao-Jing Zhu, Liang Zhou, Shi-Zhong Zheng

Abstract:

Various studies have shown that diallyl trisulfide (DATS) can protect the liver injury, and DATS has a strong antioxidant property. The aim of this study is to evaluate the in vivo role of DATS in protecting the liver against injury and fibrogenesis and further explores the underlying mechanisms. Our results demonstrated that DATS protected the liver from CCl4-caused injury by suppressing the elevation of ALT and AST activities, and by improving the histological architecture of the liver. Treatment with DATS or colchicine improved the liver fibrosis by sirius red staining and immunofluorescence. In addition, immunohistochemistry, western blot, and RT-PCR analyses indicated that DATS inhibited HSC activation. Furthermore, DATS attenuated oxidative stress by increasing glutathione and reducing lipid peroxides and malondialdehyde. These findings suggest that the protective effect of DATS on CCl4-caused liver injury and liver fibrogenesis was, at least partially, attributed to its antioxidant activity.

Keywords: liver fibrogenesis, liver injury, oxidative stress, DATS

Procedia PDF Downloads 415

Authors: Yang Zhou, Kangfeng Zheng, Wei Ni, Ren Ping Liu

Abstract:

Software-defined networking (SDN) provides a solution for scalable network framework with decoupled control and data plane. However, this architecture also induces a particular distributed denial-of-service (DDoS) attack that can affect or even overwhelm the SDN network. DDoS attack detection problem has to date been mostly researched as entropy comparison problem. However, this problem lacks the utilization of SDN, and the results are not accurate. In this paper, we propose a DDoS attack detection method, which interprets DDoS detection as a signature matching problem and is formulated as Earth Mover’s Distance (EMD) model. Considering the feasibility and accuracy, we further propose to define the cost function of EMD to be a generalized Kullback-Leibler divergence. Simulation results show that our proposed method can detect DDoS attacks by comparing EMD values with the ones computed in the case without attacks. Moreover, our method can significantly increase the true positive rate of detection.

Keywords: DDoS detection, EMD, relative entropy, SDN

Procedia PDF Downloads 319

Authors: Po-Chen Chen, Tsung-Han Yang, Zhi-Wei Zheng, Shih-Tsang Tang

Abstract:

Falls are the most common accidents during mountain hiking, especially in high-altitude environments with unstable terrain or adverse weather. Balance ability is a crucial factor in hiking, effectively ensuring hiking safety and reducing the risk of injuries. If balance ability can be assessed simply and effectively, hikers can identify their weaknesses and conduct targeted training to improve their balance ability, thereby reducing injury risks. With the widespread use of smartphones and their built-in inertial sensors, this project aims to develop a simple Inertial Measurement Unit (IMU) balance measurement technique based on smartphones. This will provide hikers with an easy-to-use, low-cost tool for assessing balance ability, monitoring training effects in real-time, and continuously tracking balance ability through uploading cloud data uploads, facilitating personal athletic performance.

Keywords: balance, IMU, smartphone, wearable devices

Procedia PDF Downloads 6

Authors: Baoshan Huang, Fanbiao Bao, Bing Li, Lianghua Zeng, Yi Zheng

Abstract:

Parameter control strategy based on statistical characteristics can analyze the choice of the transmission ratio of an automobile transmission. According to the difference of the transmission gear, the number and spacing of the gear can be determined. Transmission ratio distribution of transmission needs to satisfy certain distribution law. According to the statistic characteristics of driving parameters, the shift control strategy of the vehicle is analyzed. CVT shift schedule adjustment algorithm based on statistical characteristic parameters can be seen from the above analysis, if according to the certain algorithm to adjust the size of, can adjust the target point are in the best efficiency curve and dynamic curve between the location, to alter the vehicle characteristics. Based on the dynamic characteristics and the practical application of the vehicle, this paper presents the setting scheme of the transmission ratio.

Keywords: vehicle dynamics, transmission ratio, transmission parameters, statistical characteristics

Procedia PDF Downloads 377

Authors: Xingguo Feng, Hui Zhou, Kaifeng Zhang, Zhao Jiang, Hanjun Hu, Jun Zheng, Hong Hao

Abstract:

TiN and TiC films have been prepared on Ti6Al4V alloy substrates by plasma-based ion implantation. The effect of N+C and Ti+N hybrid ion implantation at 50 kV, and Ti+C hybrid ion implantation at 20 kV, 35 kV and 50 kV extraction voltages on mechanical properties at a dose of 2×10¹⁷ ions / cm² was studied. The chemical states and microstructures of the implanted samples were investigated using X-ray photoelectron (XPS), and X-ray diffraction (XRD), together with the mechanical and tribological properties of the samples were characterized using nano-indentation and ball-on-disk tribometer. It was found that the modified layer by Ti+C implanted at 50 kV was composed of mainly TiC and Ti-O bond and the layer of Ti+N implanted at 50 kV was observed to be TiN and Ti-O bond. Hardness tests have shown that the hardness values for N+C, Ti+N, and Ti+C hybrid ion implantation samples were much higher than the un-implanted ones. The results of wear tests showed that both Ti+C and Ti+N ion implanted samples had much better wear resistance compared un-implanted sample. The wear rate of Ti+C implanted at 50 kV sample was 6.7×10⁻⁵mm³ / N.m, which was decreased over one order than unimplanted samples.

Keywords: plasma ion implantation, x-ray photoelectron (XPS), hardness, wear

Procedia PDF Downloads 394

Authors: Wei-Bo Hua, Zhuo Zheng, Xiao-Dong Guo, Ben-He Zhong

Abstract:

The layered structure LiNi1/3Co1/3Mn1/3-xAlxO2 (x = 0 ~ 0.04) series cathode materials were synthesized by a carbonate co-precipitation method, followed by a high temperature calcination process. The influence of Al substitution on the microstructure and electrochemical performances of the prepared materials was investigated by X-Ray diffraction (XRD), scanning electron microscopy (SEM), and galvanostatic charge/discharge test. The results show that the LiNi1/3Co1/3Mn1/3-xAlxO2 has a well-ordered hexagonal "α" -NaFeO2 structure. Although the discharge capacity of Al-doped samples decreases as x increases, LiNi1/3Co1/3Mn1/3-0.02Al0.02O2 exhibits superior capacity retention at high voltage (4.6 V). Therefore, LiNi1/3Co1/3Mn1/3-0.02Al0.02O2 is a promising material for “green” vehicles.

Keywords: lithium ion battery, carbonate co-precipitation, doping, microstructure, electrochemical properties

Procedia PDF Downloads 317