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学者姓名：朱敏琛
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本发明涉及一种基于动态间隔损失函数和概率特征的视频人脸识别方法，包括以下步骤：步骤S1：通过人脸识别训练集训练识别网络；步骤S2：采用已训练的识别网络作为特征提取模块，并通过同一个训练集训练不确定性模块；步骤S3：利用学习到的不确定性作为特征的重要程度，对输入的视频特征集合进行聚合，得到聚合后的特征；步骤S4：采用互似然分数对聚合后的特征进行比对，完成最终的识别。该方法能够有效地对视频中的人脸进行识别。
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| GB/T 7714 | 柯逍 , 郑毅腾 , 朱敏琛 . 基于动态间隔损失函数和概率特征的视频人脸识别方法 : CN202010166807.8[P]. | 2020/3/11 . |
| MLA | 柯逍 等. "基于动态间隔损失函数和概率特征的视频人脸识别方法" : CN202010166807.8. | 2020/3/11 . |
| APA | 柯逍 , 郑毅腾 , 朱敏琛 . 基于动态间隔损失函数和概率特征的视频人脸识别方法 : CN202010166807.8. | 2020/3/11 . |
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According to the American Academy of Sleep Medicine (AASM), patients with apnea of 10 seconds or more, and more than 5 times per hour can be diagnosed with sleep disorders. The current gold standard for detecting this type of people with sleep disorder is Polysomnography (PSG). But more than 80% Obstructive Sleep Apnea(OSA) patients of the Sleep Disorder(SD) have not been detected. The reason is that the current configuration of PSG is insufficient in more than 2,500 sleep labs in the United States, and that the lack of manpower of sleep professional technicians who analyze PSG signal has caused many OSA patients to be diagnosed in a timely and effective manner. It is no effective measures to reduce the risk even after OSA patients have been diagnosed. Current medical treatments are either surgical or a lifelong Continuous positive dual channel air pressure ventilator(CPAP). Domestic research shows that OSA patients have poor sleep at night and sleepiness during the day. It often results in inefficient work and causes many traffic accidents. Therefore, how to take effective monitoring measures for these already diagnosed OSA patients has become an urgent problem to be solved. This paper extracts an interactive monitoring system for patients with OSA based on the Internet of Things(IoT) framework. It can reduce the timely rescue of OSA patients when they are in danger in field operations. At the same time, through the interactive function of this indicator mark, the anxiety during the waiting process can be reduced. It is also convenient for the peers to report the progress of the patient in time. The specific method is to use the existing IoT framework. The IoT data acquisition layer uses wearable sensors to collect vital signs of patients, with emphasis on ECG and SpO2 signals. The network layer transmits the collected physiological signals to the Beidou indicator using the Bluetooth Low Energy (BLE) protocol. The platform layer adopts the mature rescue interaction platform of Beidou&GPS. The previous GPS indicator has no short message function, and the patient can only passively wait for rescue. Positional standard is improved through Beidou model, and the short message interaction function has been added. Then the patient can report the progress of the disease in time while waiting for the rescue. After our simulation test, the effectiveness of the OSA patient rescue monitoring system based on the IoT framework has been greatly improved, especially in outdoor work, where the mobile phone signal coverage is relatively weak. The short message function added by the Beidou indicator can be used to provide timely progress of the patient's condition, and provide the medical rescue team with the data support to offer a more accurate rescue plan. After a comparative trial, the rescue rate of the OSA patients with the detection device of this article increased by 10 percentage points compared with the rescue rate with only GPS satellite phones.
Keyword ：
Beidou&GPS indicator Beidou&GPS indicator BLE BLE CPAP CPAP IoT IoT OSA OSA rescue system rescue system
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| GB/T 7714 | Cai, Liangming , Jiang, Jinping , Liu, Xin et al. OSA patient monitoring system based on the Internet of Things framework [C] . 2019 : 12-15 . |
| MLA | Cai, Liangming et al. "OSA patient monitoring system based on the Internet of Things framework" . (2019) : 12-15 . |
| APA | Cai, Liangming , Jiang, Jinping , Liu, Xin , Zhu, Minchen , Cheng, Kai , Du, Min et al. OSA patient monitoring system based on the Internet of Things framework . (2019) : 12-15 . |
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Aiming at the problem that the map operation time occupies more resources in the embedded system. By studying the digital map, then the corresponding map is drawn and the map is optimized. Using the GPS/BEIDOU module to locate and use the Dijkstra algorithm to achieve the shortest path of the navigation module design, the use of the map database to remove the corresponding area of the data mapping map information, in a translation to a certain distance when the scene clear the data, draw a map. In this way, there will be no data left in the view. Since the Dijkstra algorithm is based on the graph, it is necessary to link the roads in the area to create an indirect graph to find the shortest path to the end point. If the point of the line as an indirect node, the composition of the indirect map will be very large. Moreover, the use of the line as an indirect node, we can reduce the number of nodes without the map, to improve the efficiency of Dijkstra algorithm traversal. Based on the open system platform and data standard, this paper designs and develops a secure, stable and low cost embedded GPS/BEIDOU navigation and navigation system. The experimental results are optimized. The results show that the proposed method is efficient for navigation.
Keyword ：
BEIDOU BEIDOU Embedded navigation system Embedded navigation system GPS GPS map optimization map optimization
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| GB/T 7714 | Cai, Liangming , Chen, Chunqiang , Wang, Xiaoling et al. An Open Source Map Optimization Platform for efficient navigation [C] . 2019 : 61-65 . |
| MLA | Cai, Liangming et al. "An Open Source Map Optimization Platform for efficient navigation" . (2019) : 61-65 . |
| APA | Cai, Liangming , Chen, Chunqiang , Wang, Xiaoling , Lin, Shurui , Cheng, Kai , Huang, Jiefeng et al. An Open Source Map Optimization Platform for efficient navigation . (2019) : 61-65 . |
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Abstract ：
Aiming at the problem that the map operation time occupies more resources in the embedded system. By studying the digital map, then the corresponding map is drawn and the map is optimized. Using the GPS/BEIDOU module to locate and use the Dijkstra algorithm to achieve the shortest path of the navigation module design, the use of the map database to remove the corresponding area of the data mapping map information, in a translation to a certain distance when the scene clear the data, draw a map. In this way, there will be no data left in the view. Since the Dijkstra algorithm is based on the graph, it is necessary to link the roads in the area to create an indirect graph to find the shortest path to the end point. If the point of the line as an indirect node, the composition of the indirect map will be very large. Moreover, the use of the line as an indirect node, we can reduce the number of nodes without the map, to improve the efficiency of Dijkstra algorithm traversal. Based on the open system platform and data standard, this paper designs and develops a secure, stable and low cost embedded GPS/BEIDOU navigation and navigation system. The experimental results are optimized. The results show that the proposed method is efficient for navigation. © 2019 IEEE.
Keyword ：
Global positioning system Global positioning system Graph theory Graph theory Maps Maps Open systems Open systems Radio navigation Radio navigation Ubiquitous computing Ubiquitous computing
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| GB/T 7714 | Cai, Liangming , Datta, Rituparna , Li, Yurong et al. An open source map optimization platform for efficient navigation [C] . 2019 : 61-65 . |
| MLA | Cai, Liangming et al. "An open source map optimization platform for efficient navigation" . (2019) : 61-65 . |
| APA | Cai, Liangming , Datta, Rituparna , Li, Yurong , Huang, Jingshan , Chen, Chunqiang , Wang, Xiaoling et al. An open source map optimization platform for efficient navigation . (2019) : 61-65 . |
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Adequate sleep is significant for human to actively pursue daily activity. On the other hand, insomnia is directly proportional to aging and health deterioration. Sleep disorder classification is important for medical scientists as well as machine learning researchers. In the paper, we have developed a sleep disorder classification method for Electrocardiogram (ECG) data. The data set have two labels; sleep disorder or not, which can be categorized as binary output. As a result, logistic regression is used as classification technique. For initial experimentation, an existing data set is used. The data set consists of every 10 second data up to 6000 seconds for 35 patients. We have used 70% data for training, and 30% data for testing purpose. Our results from logistic regression show that the logistic regression method is efficient to detect sleep disorders. The prediction result is found to be 59%. The future research in this direction would be to take data from hospitals and use our developed algorithm for sleep disorder classification and prediction. © 2019 Association for Computing Machinery.
Keyword ：
Artificial intelligence Artificial intelligence Classification (of information) Classification (of information) Deterioration Deterioration Electrocardiography Electrocardiography Manufacture Manufacture Regression analysis Regression analysis Sleep research Sleep research
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| GB/T 7714 | Cai, Liangming , Chen, Chunqiang , Wang, Xiaoling et al. Sleep Disorder Classification Method based on Logistic Regression with Apnea-ECG Dataset [C] . 2019 . |
| MLA | Cai, Liangming et al. "Sleep Disorder Classification Method based on Logistic Regression with Apnea-ECG Dataset" . (2019) . |
| APA | Cai, Liangming , Chen, Chunqiang , Wang, Xiaoling , Yang, Xiong , Lin, Shurui , Huang, Jiefeng et al. Sleep Disorder Classification Method based on Logistic Regression with Apnea-ECG Dataset . (2019) . |
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Abstract ：
According to the American Academy of Sleep Medicine (AASM), patients with apnea of 10 seconds or more , and more than 5 times per hour can be diagnosed with sleep disorders. The current gold standard for detecting this type of people with sleep disorder is Polysomnography (PSG). But more than 80% Obstructive Sleep Apnea(OSA) patients of the Sleep Disorder(SD) have not been detected. The reason is that the current configuration of PSG is insufficient in more than 2,500 sleep labs in the United States , and that the lack of manpower of sleep professional technicians who analyze PSG signal has caused many OSA patients to be diagnosed in a timely and effective manner. It is no effective measures to reduce the risk even after OSA patients have been diagnosed. Current medical treatments are either surgical or a lifelong Continuous positive dual channel air pressure ventilator(CPAP). Domestic research shows that OSA patients have poor sleep at night and sleepiness during the day. It often results in inefficient work and causes many traffic accidents. Therefore, how to take effective monitoring measures for these already diagnosed OSA patients has become an urgent problem to be solved.This paper extracts an interactive monitoring system for patients with OSA based on the Internet of Things(IoT) framework. It can reduce the timely rescue of OSA patients when they are in danger in field operations. At the same time, through the interactive function of this indicator mark, the anxiety during the waiting process can be reduced. It is also convenient for the peers to report the progress of the patient in time. The specific method is to use the existing IoT framework. The IoT data acquisition layer uses wearable sensors to collect vital signs of patients, with emphasis on ECG and SpO2 signals. The network layer transmits the collected physiological signals to the Beidou indicator using the Bluetooth Low Energy (BLE) protocol. The platform layer adopts the mature rescue interaction platform of BeidouGPS. The previous GPS indicator has no short message function, and the patient can only passively wait for rescue. Positional standard is improved through Beidou model, and the short message interaction function has been added. Then the patient can report the progress of the disease in time while waiting for the rescue. After our simulation test, the effectiveness of the OSA patient rescue monitoring system based on the IoT framework has been greatly improved, especially in outdoor work, where the mobile phone signal coverage is relatively weak. The short message function added by the Beidou indicator can be used to provide timely progress of the patient's condition, and provide the medical rescue team with the data support to offer a more accurate rescue plan. After a comparative trial, the rescue rate of the OSA patients with the detection device of this article increased by 10 percentage points compared with the rescue rate with only GPS satellite phones. © 2019 University of Split, FESB.
Keyword ：
Data acquisition Data acquisition Global positioning system Global positioning system Internet of things Internet of things Low power electronics Low power electronics mHealth mHealth Network layers Network layers Patient monitoring Patient monitoring Power management (telecommunication) Power management (telecommunication) Radio navigation Radio navigation Risk assessment Risk assessment Sleep research Sleep research Telephone sets Telephone sets
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| GB/T 7714 | Cai, Liangming , Jiang, Jinping , Liu, Xin et al. OSA patient monitoring system based on the Internet of Things framework [C] . 2019 . |
| MLA | Cai, Liangming et al. "OSA patient monitoring system based on the Internet of Things framework" . (2019) . |
| APA | Cai, Liangming , Jiang, Jinping , Liu, Xin , Zhu, Minchen , Cheng, Kai , Du, Min et al. OSA patient monitoring system based on the Internet of Things framework . (2019) . |
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数据分类在网络安全防护与监测预警中发挥着重要作用.随着网络系统规模的扩大、网络速度的提高以及网络安全事件的增多,安全数据的数量急剧增加,极大影响了数据分类的准确性,从而给入侵检测、安全评估、攻击意图识别等安全应用带来极大挑战.文章提出一种结合SMOTE-SVM算法和XGBoost算法的数据分类模型.首先,针对数据不平衡的情况,采用过采样和下采样相结合的方法,设计一种基于SMOTE-SVM算法的数据特征平衡方法,提高了训练数据分布的合理性和训练精度.然后,针对多源异构的安全数据的多样性特点,采用独热编码技术实现数据的规范化.最后,基于XGBoost算法对数据集进行特征提取和分类.实验结果表明,该方法在数据分类查准率、召回率和综合有效性方面具有明显优势,能有效提高网络安全大数据的分析能力,对网络安全态势感知具有重要的应用意义.
Keyword ：
SMOTE SMOTE XGBoost XGBoost 不平衡数据 不平衡数据 网络空间安全 网络空间安全
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| GB/T 7714 | 刘延华 , 高晓玲 , 朱敏琛 et al. 基于数据特征学习的网络安全数据分类方法研究 [J]. | 信息网络安全 , 2019 , (10) : 50-56 . |
| MLA | 刘延华 et al. "基于数据特征学习的网络安全数据分类方法研究" . | 信息网络安全 10 (2019) : 50-56 . |
| APA | 刘延华 , 高晓玲 , 朱敏琛 , 苏培煌 . 基于数据特征学习的网络安全数据分类方法研究 . | 信息网络安全 , 2019 , (10) , 50-56 . |
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At present, with the increase of automated attack tools and the development of the underground industrial chain brought by network attack, even well-managed network is vulnerable to complex multi-step network attack, which combines multiple network vulnerabilities and uses the causal relationship between them to achieve the attack target. The detection of such attack intention is very difficult. Therefore, in order to solve the problem that the real attack intention of the attackers in complex network is difficult to be recognized, this paper proposes to assume the possible targets in the network according to the important asset information in the network. By constructing the hierarchical attack path graph, the probability of each hypothetical attack intention target is calculated, and the real attack intention and the most likely attack path of the attacker are deduced. The hierarchical attack path graph we use can effectively overcome the cognitive difficulties caused by network complexity and large scale, and can quantitatively and qualitatively analyze the network status. It is of great importance to make the protection and strategy of network security.
Keyword ：
Attack intention Attack intention Attack path graph Attack path graph Critical assets Critical assets
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| GB/T 7714 | Li, Shijin , Zhu, Minchen , Qiu, Yanbin . Attack Intent Analysis Method Based on Attack Path Graph [C] . 2018 : 27-31 . |
| MLA | Li, Shijin et al. "Attack Intent Analysis Method Based on Attack Path Graph" . (2018) : 27-31 . |
| APA | Li, Shijin , Zhu, Minchen , Qiu, Yanbin . Attack Intent Analysis Method Based on Attack Path Graph . (2018) : 27-31 . |
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Smart home is an important application area of the Internet of things (IoT). However, the diversification of smart home application scenarios increases the difficulty of understanding the scenarios for developers. And the heterogeneity of the programming interfaces of smart devices as well as the close coupling of the code to the underlying systems is still an important work for the developers. Furthermore, the complexity and variability of business requirements poses a great challenge to the development of applications logic. In this paper, we present a runtime knowledge graph based approach to smart home application development. First, a conceptual model describing the smart home scenarios is defined. Second, the manageability of smart devices is abstracted as runtime knowledge graphs that are automatically connected with the corresponding systems. Last, a method of automatically generating smart home applications is proposed. Our approach can reduce code by about 85 percent at least, and an experiment on a real-world application scenario demonstrates the feasibility, effectiveness, and benefits of the new approach to smart home application development.
Keyword ：
Internet of things Internet of things models at runtime models at runtime software architecture software architecture
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| GB/T 7714 | Zhu, Minchen , Ye, Xinshu , Xiang, Tao et al. Runtime knowledge graph based approach to smart home application development [C] . 2018 : 110-117 . |
| MLA | Zhu, Minchen et al. "Runtime knowledge graph based approach to smart home application development" . (2018) : 110-117 . |
| APA | Zhu, Minchen , Ye, Xinshu , Xiang, Tao , Ma, Yun , Chen, Xing . Runtime knowledge graph based approach to smart home application development . (2018) : 110-117 . |
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针对海量数据背景下K-means聚类结果不稳定和收敛速度较慢的问题,提出了基于MapReduce框架下的K-means改进算法.首先,为了能获得K-means聚类的初始簇数,利用凝聚层次聚类法对数据集进行聚类,并用轮廓系数对聚类结果进行初步评价,将获得数据集的簇数作为K-means算法的初始簇中心进行聚类;其次,为了能适应于海量数据的聚类挖掘,将改进的K-means算法部署在MapReduce框架上进行运算.实验结果表明,在单机性能上,该方法具有较高的准确率和召回率,同时也具有较强的聚类稳定性;在集群性能上,也具有较好的加速比和运行速度.
Keyword ：
K-means算法 K-means算法 MapReduce框架 MapReduce框架 数据挖掘 数据挖掘 聚类分析 聚类分析
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| GB/T 7714 | 阴爱英 , 吴运兵 , 朱敏琛 et al. 基于MapReduce框架下K-means的改进算法 [J]. | 计算机应用研究 , 2018 , 35 (8) : 2295-2298 . |
| MLA | 阴爱英 et al. "基于MapReduce框架下K-means的改进算法" . | 计算机应用研究 35 . 8 (2018) : 2295-2298 . |
| APA | 阴爱英 , 吴运兵 , 朱敏琛 , 张莹 . 基于MapReduce框架下K-means的改进算法 . | 计算机应用研究 , 2018 , 35 (8) , 2295-2298 . |
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