2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)最新文献_第2页

Forensic Face Sketch Recognition based on Pre-Selected Facial Regions 基于预选面部区域的法医人脸素描识别

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935651

Nur Nabilah Bahrum, S. Setumin, Edi Afzan Saidon, N. A. Othman, M. F. Abdullah

{"title":"Forensic Face Sketch Recognition based on Pre-Selected Facial Regions","authors":"Nur Nabilah Bahrum, S. Setumin, Edi Afzan Saidon, N. A. Othman, M. F. Abdullah","doi":"10.1109/ICCSCE54767.2022.9935651","DOIUrl":"https://doi.org/10.1109/ICCSCE54767.2022.9935651","url":null,"abstract":"In law enforcement, face sketch recognition has been used to identify the criminal suspect. Usually, when there is no other evidence, a forensic artist will draw the face of the suspect based on the eyewitness description. Then, the forensic sketch will be matched with the mugshot images from the database in order to recognize and identify the potential suspect. However, the matching performance of the forensic sketches could be affected by various factors, and one of the major factors is the occlusion that exists in the sketch itself. This is because most of the suspects usually wear something that could help in hiding their identities, like a face mask, glasses, hoodie, or cap, when they are committing a crime. Since the mugshot images do not include the occlusion, it will make it harder to recognize the suspect in the matching process, even if the sketch and photo are from the same person. This is due to the larger Euclidean distance between the extracted features from these two images, particularly in the occlusion regions. Therefore, this study proposed a method that matches only the pre-selected regions that exclude occlusion in both images. This region of interest is pre-selected on the forensic face sketch before the same region is applied to all mugshot images. In this study, the forensic sketch with their corresponding photo was obtained from the PRIP-HDC dataset, and the Histogram of Gradient (HOG) was used for feature extraction. Based on the result obtained, this study's performance shows some improvement in recognizing the forensic sketches compared to the existing technique.","PeriodicalId":346014,"journal":{"name":"2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130219438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparative Analysis of Empirical Mode Decomposition and Discrete Wavelet Transform as Denoising Methods for Auditory Brainstem Response 经验模态分解与离散小波变换作为听觉脑干响应去噪方法的比较分析

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935643

Allen Lois Lanuza, Roxanne De Leon, C. R. Lucas

{"title":"Comparative Analysis of Empirical Mode Decomposition and Discrete Wavelet Transform as Denoising Methods for Auditory Brainstem Response","authors":"Allen Lois Lanuza, Roxanne De Leon, C. R. Lucas","doi":"10.1109/ICCSCE54767.2022.9935643","DOIUrl":"https://doi.org/10.1109/ICCSCE54767.2022.9935643","url":null,"abstract":"Peak latency measurement of the patient's Auditory Brainstem Response (ABR) essential wave components (Waves I-V) is the usual method in hearing screening to determine the likelihood of hearing impairment. To visualize the peaks of Waves I-V, averaging about 2000 ABR sweeps is necessary for reducing the background noise caused by power line interference and myogenic activity; however, this method is time-consuming and inconvenient for patients and healthcare workers. The study aims to use signal denoising methods to denoise ABRs averaged with fewer sweeps without affecting their functionality. Two deterministic signal denoising approaches, Empirical Mode Decomposition (EMD) and Discrete Wavelet Transform (DWT), were evaluated and compared to determine which could produce functional denoised ABRs using fewer sweeps. For the 1 kHz stimulus frequency, DWT produced functional ABRs with fewer sweeps than EMD for stimulus intensities of 75, 65, 55 and 50 dB peSPL. For the 4 kHz stimulus frequency, only the DWT method could produce functional ABRs with fewer sweeps. DWT method performs better than EMD in producing clinically relevant denoised ABR for most stimulus descriptions. The findings can help audiologists use the DWT denoising approach when averaging noisy ABRs with fewer sweeps to address the problems caused by the time-consuming conventional averaging method.","PeriodicalId":346014,"journal":{"name":"2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)","volume":"272 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117090457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multilayer Perceptron Optimization of ECG Peaks for Cardiac Abnormality Detection 心电峰值多层感知器优化心脏异常检测

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935642

A. A. Jamil, J. Kadir, Johanis Mohd Jamil, F.R. Hashim, S. Shaharuddin, Nazrul Fariq Makmor

{"title":"Multilayer Perceptron Optimization of ECG Peaks for Cardiac Abnormality Detection","authors":"A. A. Jamil, J. Kadir, Johanis Mohd Jamil, F.R. Hashim, S. Shaharuddin, Nazrul Fariq Makmor","doi":"10.1109/ICCSCE54767.2022.9935642","DOIUrl":"https://doi.org/10.1109/ICCSCE54767.2022.9935642","url":null,"abstract":"The development of artificial neural networks (ANNs) was founded on computer alterations of human biology (the concept of neurons). The practicality of applying ANNs to various problems has been the subject of numerous studies, particularly in the field of biomedical engineering. Medical and educational decision-making regularly use applications to ANNs. Using a range of reference data, the ANNs used in the current study were trained to recognise cardiac abnormalities. Typically referred to as reference parameters, electrocardiogram (ECG) signal amplitude and duration are employed as input parameters for cardiac issues. An ECG complex consists of a P peak, QRS wave, and T peak. The amplitude and length of each P peak, QRS wave, and T peak are measured, resulting in a total of six input parameters for the artificial neural network. The artificial neural network (ANN) structure in this study is a multilayer perceptron (MLP), and the training techniques are Bayesian Regularization (BayR), Lavenberg Marquardt (LevM), and Backpropagation (BackP). The influence of the Tansig activation function on the MLP structure. The MLP network that achieved the highest accuracy (94.44%) utilising the BayR training method and Logsig activation function surpassed all others.","PeriodicalId":346014,"journal":{"name":"2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114208299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Voice Conversion of Tagalog Synthesized Speech Using Cycle-Generative Adversarial Networks (Cycle-GAN) 基于循环生成对抗网络(Cycle-GAN)的他加洛语合成语音转换

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935581

Jomari B. Ganhinhin, Maria Donnabelle B. Varona, C. R. Lucas, Angelina A. Aquino

{"title":"Voice Conversion of Tagalog Synthesized Speech Using Cycle-Generative Adversarial Networks (Cycle-GAN)","authors":"Jomari B. Ganhinhin, Maria Donnabelle B. Varona, C. R. Lucas, Angelina A. Aquino","doi":"10.1109/ICCSCE54767.2022.9935581","DOIUrl":"https://doi.org/10.1109/ICCSCE54767.2022.9935581","url":null,"abstract":"Existing Tagalog Text-to-speech (TTS) systems still have room for improvement, and although recent attempts at creating local TTS systems for Philippine spoken languages were able to generate synthesized speech, they still possess relatively low Mean Opinion Scores (MOS), ranging from 1.5 to 3.9 (out of 5), when it comes to naturalness and intelligibility. Improving speech prosody, the main factor for a speech's naturalness or individuality, has been made possible through voice conversion (VC). This project aims to implement a VC system for Tagalog synthesized speech, specifically using Cycle Generative Adversarial Networks (Cycle-GAN), a state-of-the-art neural network architecture used in non-parallel VC. Inter-gender and intra-gender VC were made for two types of inputs: Google's own Tagalog TTS and a locally sourced TTS system built from Mary TTS. Results show that Google TTS and its VC models perform better overall than Mary TTS and its VC models. Mel Cepstral Distortions (MCD) and F0: Root Mean Square Errors (F0:RMSE) vary across all models, reaching an MCD as low as 6.52 dB for Google TTS' intra-gender VC and an F0:RMSE as low as 16.92 Hz from Google TTS' inter-gender VC. Meanwhile, undergoing VC also caused a degradation in perceived speech quality as seen in a decrease in MOS across all VC models. Inter-gender VC for both TTS inputs were subjectively more preferred over intra-gender VC, reaching MOS values of 3.76 and 2.32 for Google TTS and Mary TTS inputs, respectively. Furthermore, it was also shown that male respondents were likely to rate higher opinion scores for intra-gender VC than female respondents, likely due to differences in hearing sensitivities.","PeriodicalId":346014,"journal":{"name":"2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116966207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Classification of Drinking Water Quality using Support Vector Machine (SVM) Algorithm 基于支持向量机的饮用水水质分类

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935657

Z. Muhammad, Nur Aqilah Jak Jailani, N. A. M. Leh, S. A. Hamid

{"title":"Classification of Drinking Water Quality using Support Vector Machine (SVM) Algorithm","authors":"Z. Muhammad, Nur Aqilah Jak Jailani, N. A. M. Leh, S. A. Hamid","doi":"10.1109/ICCSCE54767.2022.9935657","DOIUrl":"https://doi.org/10.1109/ICCSCE54767.2022.9935657","url":null,"abstract":"Water is extremely important in both the environmental and social realms. The consumption of clean water guarantees a quality of life as it provides essential minerals and nutrients to the body. Water pollution posing a threat to human health, ecosystems, plant, and animal life. Today, Malaysia is showing an increasing rate of water pollution as there are currently undergoing tremendous urbanization and population expansion. The Water Quality Index (WQI) must monitor frequently to ensure the level of water cleanliness and safeness. However, monitoring work was conduct manually are time consuming, requires a lot of manpower and high expertise in determining the level of water cleanliness. Due to those issues, the intention of this study is to develop an automatic method in water quality classification for drinking purpose whether it is potable or non-potable using Support Vector Machine (SVM) which is more accurate, fast, and easy. This project used up to 59 samples of data from various location to prepare the SVM with two different kernels. By using MATLAB version R2021A, the implementation of this project was performed. Based on the result obtained, it is discovered that SVM model with RBF kernel has the better performance with high percentage of accuracy, precision, sensitivity, and specificity compared to SVM model with Polynomial kernel. All two types of kernels were accepted to be used in SVM model water quality classifier as their performance's criteria which are accuracy, specificity, sensitivity, and precision were greater than 80%. The findings of the study were benefits to the other or future work, particularly in the water quality classification system.","PeriodicalId":346014,"journal":{"name":"2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122887168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Sign Language Digit Detection with MediaPipe and Machine Learning Algorithm 基于MediaPipe和机器学习算法的手语数字检测

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935659

Safyzan Salim, M. M. A. Jamil, R. Ambar, R. Roslan, M. G. Kamardan

引用次数: 1

Real Time Drowsy Driver Detection Using Image Processing on Python 在Python上使用图像处理的实时困倦驾驶员检测

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935627

Muhammad Adib Faidhi Daud, A. P. Ismail, N. Tahir, K. Daud, Nazirah Mohamat Kasim, Fadzil Ahmad Mohamad

{"title":"Real Time Drowsy Driver Detection Using Image Processing on Python","authors":"Muhammad Adib Faidhi Daud, A. P. Ismail, N. Tahir, K. Daud, Nazirah Mohamat Kasim, Fadzil Ahmad Mohamad","doi":"10.1109/ICCSCE54767.2022.9935627","DOIUrl":"https://doi.org/10.1109/ICCSCE54767.2022.9935627","url":null,"abstract":"Drowsy driving is one of the most common causes of road accidents. Human usually become drowsy when tired and it is dangerous especially during driving on the road. Drowsiness can induce microsleep which can cause a significant decline in driving performance and thus would increase the chance of accidents. Hence, this real time drowsy driver detection is developed that to help minimize the chance of road accidents occurrence when the driver become drowsy. In this proposed method, the drowsy driver can be detected and alerted without using any intrusive instruments that could distract the driver. This drowsy detection is done using real time input image of the driver using a camera and image processing using Python. Next, drowsiness sign can be detected from the facial expression of the driver through the percentage of eyes opened and the frequent yawning. From the facial expression, the calculation of the eye closure known as eye aspect ratio (EAR) and the wideness of mouth opening known as mouth aspect ratio (MAR) can be made. Finally, using the value obtained, the system can determine whether the driver is alert or drowsy.","PeriodicalId":346014,"journal":{"name":"2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122438506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Speed Control of SEDC Motor Using Artificial Neural Network 基于人工神经网络的SEDC电机速度控制

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935655

A. Samat, Muhammad Irfan Bin Ahmad Jaafar, A. I. Tajudin, N. A. Salim, K. Daud, Nornaim Kamarudin

{"title":"Speed Control of SEDC Motor Using Artificial Neural Network","authors":"A. Samat, Muhammad Irfan Bin Ahmad Jaafar, A. I. Tajudin, N. A. Salim, K. Daud, Nornaim Kamarudin","doi":"10.1109/ICCSCE54767.2022.9935655","DOIUrl":"https://doi.org/10.1109/ICCSCE54767.2022.9935655","url":null,"abstract":"This project designed the speed control of a separately excited direct current (DC) motor by using an Artificial Neural Network (ANN). Any conventional controller such as proportional-integral (PI) can be used to control the speed of a DC Motor. However, the limitation of the conventional controller in controlling the speed of the dc motor is inaccuracy in the ability to obtain the actual speed and maintain the stability of the motor speed in the dynamic condition. Thus, the ANN controller had been introduced to solve the problem involving the limitation of another conventional controller. The neural network is used in this project to control or estimate the motor speed by training the neural network and getting the desired result using MATLAB/SIMULINK software. In this project, the ANN has proven its ability to control motor speed compared to the PI controller effectively and has good performance in a nonlinear system. The simulation results show the advantages and efficiency of an ANN with minimum speed error which is approximately zero rpm.","PeriodicalId":346014,"journal":{"name":"2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131383961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Threats and Vulnerabilities Handling via Dual-stack Sandboxing Based on Security Mechanisms Model 基于安全机制模型的双栈沙箱威胁与漏洞处理

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935664

A. Taib, Ariff As-Syadiqin Abdullah, Muhammad Azizi Mohd Ariffin, Rafiza Ruslan

{"title":"Threats and Vulnerabilities Handling via Dual-stack Sandboxing Based on Security Mechanisms Model","authors":"A. Taib, Ariff As-Syadiqin Abdullah, Muhammad Azizi Mohd Ariffin, Rafiza Ruslan","doi":"10.1109/ICCSCE54767.2022.9935664","DOIUrl":"https://doi.org/10.1109/ICCSCE54767.2022.9935664","url":null,"abstract":"To train new staff to be efficient and ready for the tasks assigned is vital. They must be equipped with knowledge and skills so that they can carry out their responsibility to ensure smooth daily working activities. As transitioning to IPv6 has taken place for more than a decade, it is understood that having a dual-stack network is common in any organization or enterprise. However, many Internet users may not realize the importance of IPv6 security due to a lack of awareness and knowledge of cyber and computer security. Therefore, this paper presents an approach to educating people by introducing a security mechanisms model that can be applied in handling security challenges via network sandboxing by setting up an isolated dual stack network testbed using GNS3 to perform network security analysis. The finding shows that applying security mechanisms such as access control lists (ACLs) and host-based firewalls can help counter the attacks. This proves that knowledge and skills to handle dual-stack security are crucial. In future, more kinds of attacks should be tested and also more types of security mechanisms can be applied on a dual-stack network to provide more information and to provide network engineers insights on how they can benefit from network sandboxing to sharpen their knowledge and skills.","PeriodicalId":346014,"journal":{"name":"2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129251121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Investigation of the Optimal Sensor Location and Classifier for Human Motion Classification 人体运动分类中最优传感器定位与分类器的研究

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935635

Anuar Mohamed, N. A. Othman, H. Ahmad, M. Hassan

{"title":"Investigation of the Optimal Sensor Location and Classifier for Human Motion Classification","authors":"Anuar Mohamed, N. A. Othman, H. Ahmad, M. Hassan","doi":"10.1109/ICCSCE54767.2022.9935635","DOIUrl":"https://doi.org/10.1109/ICCSCE54767.2022.9935635","url":null,"abstract":"Human motion monitoring by means of wearable technologies is not uncommon nowadays. This demonstrates the growing awareness of the importance of healthy lifestyle. Human body motion involves the movement of multiple muscles and joints. However, the optimal location of sensor placement on the body to record the motion in daily activities has not been well understood. This study aims to find the best sensor location for this purpose among three locations on the body, that is on the back, shank, or wrist. In addition, this study seeks to find the best classification algorithm for human daily activities. The data recorded at these three locations were analysed using several classification algorithms in both Orange software and MATLAB. The results show that the sensor on the wrist provided the best classification result, thereby suggesting that wrist is the best place on the body to place the sensor for human motion monitoring. With regards to classification algorithm, we found that Neural Network provides the most accurate classification as compared to other algorithms. Future development of wearables should look into integrating classification algorithm in the system, thus the human motion monitoring will provide a richer information and not only limited to number of steps and calories burned.","PeriodicalId":346014,"journal":{"name":"2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)","volume":"558 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117137923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0