Based on the social network analysis methods and human network, this paper randomly selected 44 students (31 males and 13 females) as the research objects, and it used the UCINET software to analyze the friendship bet...Based on the social network analysis methods and human network, this paper randomly selected 44 students (31 males and 13 females) as the research objects, and it used the UCINET software to analyze the friendship between them of which 43 used WeChat and 44 used QQ, and it also used the tool Netdraw to visualize the network sociogram. By mining the four aspects of density, accessibility, centrality, block model, the results demonstrated that QQ social network and WeChat social network existed the phenomenon of small world, leaders and subgroups, and the key nodes of QQ human network were more than WeChat network. Through using the key nodes, it can push the precise and efficient information and improve the accuracy of information transmission and impact among network members.展开更多
In this paper, we will explain the relevance of the starant graphs, graphs created by us in the year of 2002. They were basically circulant graphs with a star graph that connects to all the vertices of the circulant g...In this paper, we will explain the relevance of the starant graphs, graphs created by us in the year of 2002. They were basically circulant graphs with a star graph that connects to all the vertices of the circulant graphs from inside of them, but they did not exist as a separate object of study in the year of 2002, as for all we knew. We now know that they can be used to model even social networking interactions, and they do that job better than any other graph we could be trying to use there. With the development of our mathematical tools, lots of conclusions will be made much more believable and therefore will become much more likely to get support from the relevant industries when attached to new queries.展开更多
This work aims to implement expert and collaborative group recommendation services through an analysis of expertise and network relations NTIS. First of all, expertise database has been constructed by extracting keywo...This work aims to implement expert and collaborative group recommendation services through an analysis of expertise and network relations NTIS. First of all, expertise database has been constructed by extracting keywords after indexing national R＆D information in Korea （human resources, project and outcome） and applying expertise calculation algorithm. In consideration of the characteristics of national R＆D information, weight values have been selected. Then, expertise points were calculated by applying weighted values. In addition, joint research and collaborative relations were implemented in a knowledge map format through network analysis using national R＆D information.展开更多
The identification of functional motifs in a DNA sequence is fundamentally a statistical pattern recognition problem. This paper introduces a new algorithm for the recognition of functional transcription start sites ...The identification of functional motifs in a DNA sequence is fundamentally a statistical pattern recognition problem. This paper introduces a new algorithm for the recognition of functional transcription start sites （TSSs） in human genome sequences, in which a RBF neural network is adopted, and an improved heuristic method for a 5-tuple feature viable construction, is proposed and implemented in two RBFPromoter and ImpRBFPromoter packages developed in Visual C＋＋ 6.0. The algorithm is evaluated on several different test sequence sets. Compared with several other promoter recognition programs, this algorithm is proved to be more flexible, with stronger learning ability and higher accuracy.展开更多
Short Retraction Notice The authors claim that this paper needs modifications. This article has been retracted to straighten the academic record. In making this decision the Editorial Board follows COPE's Retracti...Short Retraction Notice The authors claim that this paper needs modifications. This article has been retracted to straighten the academic record. In making this decision the Editorial Board follows COPE's Retraction Guidelines. The aim is to promote the circulation of scientific research by offering an ideal research publication platform with due consideration of internationally accepted standards on publication ethics. The Editorial Board would like to extend its sincere apologies for any inconvenience this retraction may have caused. Editor guiding this retraction: Prof. Baozong Yuan(EiC of JSIP) The full retraction notice in PDF is preceding the original paper, which is marked "RETRACTED".展开更多
This paper proposes a new approach for detecting human survivors in destructed environments using an autonomous robot. The proposed system uses a passive infrared sensor to detect the existence of living humans and a ...This paper proposes a new approach for detecting human survivors in destructed environments using an autonomous robot. The proposed system uses a passive infrared sensor to detect the existence of living humans and a low-cost camera to acquire snapshots of the scene. The images are fed into a feed-forward neural network, trained to detect the existence of a human body or part of it within an obstructed environment. This approach requires a relatively small number of images to be acquired and processed during the rescue operation, which considerably reduces the cost of image processing, data transmission, and power consumption. The results of the conducted experiments demonstrated that this system has the potential to achieve high performance in detecting living humans in obstructed environments relatively quickly and cost-effectively. The detection accuracy ranged between 79% and 91% depending on a number of factors such as the body position, the light intensity, and the relative color matching between the body and the surrounding environment.展开更多
With the emerging of sensor networks, research on sensor-based activity recognition has attracted much attention. Many existing methods cannot well deal with the cases that contain hundreds of sensors and their recogn...With the emerging of sensor networks, research on sensor-based activity recognition has attracted much attention. Many existing methods cannot well deal with the cases that contain hundreds of sensors and their recognition accuracy is requisite to be further improved. A novel framework for recognizing human activities in smart home was presented. First, small, easy-to-install, and low-cost state change sensors were adopted for recording state change or use of the objects. Then the Bayesian belief network (BBN) was applied to conducting activity recognition by modeling statistical dependencies between sensor data and human activity. An edge-encode genetic algorithm (EEGA) approach was proposed to resolve the difficulties in structure learning of the BBN model under a high dimension space and large data set. Finally, some experiments were made using one publicly available dataset. The experimental results show that the EEGA algorithm is effective and efficient in learning the BBN structure and outperforms the conventional approaches. By conducting human activity recognition based on the testing samples, the BBN is effective to conduct human activity recognition and outperforms the naive Bayesian network (NBN) and multiclass naive Bayes classifier (MNBC).展开更多
为了减小配电网带电作业的人身安全风险,降低电力系统的运维成本,文中设计了一种面向配电网作业的半人形智能机器人系统,包括硬件结构和控制系统设计。不同于绝缘杆作业法,该系统通过佩戴数据手套和腕部红外追踪器等多模态可穿戴设备来...为了减小配电网带电作业的人身安全风险,降低电力系统的运维成本,文中设计了一种面向配电网作业的半人形智能机器人系统,包括硬件结构和控制系统设计。不同于绝缘杆作业法,该系统通过佩戴数据手套和腕部红外追踪器等多模态可穿戴设备来捕捉人体动作和作业细节,并采用动态运动基元(dynamic movement primitives, DMP)将人体数据映射到半人形机器人的机械臂和末端灵巧手来进行配网作业。测试结果表明:所设计的半人形机器人系统能够稳定跟踪人体演示细节。在模拟配电网线路中可以完成多种作业功能,作业实验成功率可达88.9%。展开更多
An effective blind digital watermarking algorithm based on neural networks in the wavelet domain is presented. Firstly, the host image is decomposed through wavelet transform. The significant coefficients of wavelet a...An effective blind digital watermarking algorithm based on neural networks in the wavelet domain is presented. Firstly, the host image is decomposed through wavelet transform. The significant coefficients of wavelet are selected according to the human visual system （HVS） characteristics. Watermark bits are added to them. And then effectively cooperates neural networks to learn the characteristics of the embedded watermark related to them. Because of the learning and adaptive capabilities of neural networks, the trained neural networks almost exactly recover the watermark from the watermarked image. Experimental results and comparisons with other techniques prove the effectiveness of the new algorithm.展开更多
目的探究人偏肺病毒感染的发病机制,并基于逆向网络药理学思维对其进行中药组方预测。方法于Genecards数据库和OMIM数据库中获取人偏肺病毒的靶点,将所得靶点导入STRING数据库构建蛋白互作网络,利用Cytoscape 3.9.0软件结合R软件获得关...目的探究人偏肺病毒感染的发病机制,并基于逆向网络药理学思维对其进行中药组方预测。方法于Genecards数据库和OMIM数据库中获取人偏肺病毒的靶点,将所得靶点导入STRING数据库构建蛋白互作网络,利用Cytoscape 3.9.0软件结合R软件获得关键靶点。根据GO和KEGG富集分析明确其发病机制与通路。根据度值选取核心靶点,通过Uniprot数据库将核心靶点转换后于traditional Chinese medicine SP数据库逆向收集中药成分及中药。使用Cytoscape 3.9.0软件构建关键靶点-有效成分-中药网络关系图。利用STBYL-2.0软件将核心靶点与核心成分进行分子对接验证,最后确定度值较高中药并分析整理其性、味、归经。结果共获取人偏肺病毒靶点209个,根据度值得到26个关键靶点。GO富集分析主要得出1866个条目,KEGG富集分析显示88条信号通路。根据度值选取的8个核心靶点于traditional Chinese medicine SP数据库中共匹配到29种入血成分及298种中药。将8个核心靶点蛋白与度值较高的4种核心成分进行分子对接验证,结果稳定且良好。整理度值≥10的中药共69种,主要为苦参、连翘、余甘子、半枝莲、木蝴蝶、银杏叶等,以寒性药、苦味药居多,其次为温性药、辛味药,并且肝、肺二经居多。结论运用逆向网络药理学思维及分子对接技术对人偏肺病毒进行靶点、通路、成分和中药预测,为临床治疗及研究提供新思路和理论依据。展开更多
文摘Based on the social network analysis methods and human network, this paper randomly selected 44 students (31 males and 13 females) as the research objects, and it used the UCINET software to analyze the friendship between them of which 43 used WeChat and 44 used QQ, and it also used the tool Netdraw to visualize the network sociogram. By mining the four aspects of density, accessibility, centrality, block model, the results demonstrated that QQ social network and WeChat social network existed the phenomenon of small world, leaders and subgroups, and the key nodes of QQ human network were more than WeChat network. Through using the key nodes, it can push the precise and efficient information and improve the accuracy of information transmission and impact among network members.
文摘In this paper, we will explain the relevance of the starant graphs, graphs created by us in the year of 2002. They were basically circulant graphs with a star graph that connects to all the vertices of the circulant graphs from inside of them, but they did not exist as a separate object of study in the year of 2002, as for all we knew. We now know that they can be used to model even social networking interactions, and they do that job better than any other graph we could be trying to use there. With the development of our mathematical tools, lots of conclusions will be made much more believable and therefore will become much more likely to get support from the relevant industries when attached to new queries.
基金Project(N-12-NM-LU01-C01) supported by Construction of NTIS (National Science & Technology Information Service) Program Funded by the National Science & Technology Commission (NSTC), Korea
文摘This work aims to implement expert and collaborative group recommendation services through an analysis of expertise and network relations NTIS. First of all, expertise database has been constructed by extracting keywords after indexing national R＆D information in Korea （human resources, project and outcome） and applying expertise calculation algorithm. In consideration of the characteristics of national R＆D information, weight values have been selected. Then, expertise points were calculated by applying weighted values. In addition, joint research and collaborative relations were implemented in a knowledge map format through network analysis using national R＆D information.
基金This work was supported by the National Natural Science Foundation of China (No.60374069)
文摘The identification of functional motifs in a DNA sequence is fundamentally a statistical pattern recognition problem. This paper introduces a new algorithm for the recognition of functional transcription start sites （TSSs） in human genome sequences, in which a RBF neural network is adopted, and an improved heuristic method for a 5-tuple feature viable construction, is proposed and implemented in two RBFPromoter and ImpRBFPromoter packages developed in Visual C＋＋ 6.0. The algorithm is evaluated on several different test sequence sets. Compared with several other promoter recognition programs, this algorithm is proved to be more flexible, with stronger learning ability and higher accuracy.
文摘Short Retraction Notice The authors claim that this paper needs modifications. This article has been retracted to straighten the academic record. In making this decision the Editorial Board follows COPE's Retraction Guidelines. The aim is to promote the circulation of scientific research by offering an ideal research publication platform with due consideration of internationally accepted standards on publication ethics. The Editorial Board would like to extend its sincere apologies for any inconvenience this retraction may have caused. Editor guiding this retraction: Prof. Baozong Yuan(EiC of JSIP) The full retraction notice in PDF is preceding the original paper, which is marked "RETRACTED".
文摘This paper proposes a new approach for detecting human survivors in destructed environments using an autonomous robot. The proposed system uses a passive infrared sensor to detect the existence of living humans and a low-cost camera to acquire snapshots of the scene. The images are fed into a feed-forward neural network, trained to detect the existence of a human body or part of it within an obstructed environment. This approach requires a relatively small number of images to be acquired and processed during the rescue operation, which considerably reduces the cost of image processing, data transmission, and power consumption. The results of the conducted experiments demonstrated that this system has the potential to achieve high performance in detecting living humans in obstructed environments relatively quickly and cost-effectively. The detection accuracy ranged between 79% and 91% depending on a number of factors such as the body position, the light intensity, and the relative color matching between the body and the surrounding environment.
基金National Natural Science Foundation of China(No. 70971021)
文摘With the emerging of sensor networks, research on sensor-based activity recognition has attracted much attention. Many existing methods cannot well deal with the cases that contain hundreds of sensors and their recognition accuracy is requisite to be further improved. A novel framework for recognizing human activities in smart home was presented. First, small, easy-to-install, and low-cost state change sensors were adopted for recording state change or use of the objects. Then the Bayesian belief network (BBN) was applied to conducting activity recognition by modeling statistical dependencies between sensor data and human activity. An edge-encode genetic algorithm (EEGA) approach was proposed to resolve the difficulties in structure learning of the BBN model under a high dimension space and large data set. Finally, some experiments were made using one publicly available dataset. The experimental results show that the EEGA algorithm is effective and efficient in learning the BBN structure and outperforms the conventional approaches. By conducting human activity recognition based on the testing samples, the BBN is effective to conduct human activity recognition and outperforms the naive Bayesian network (NBN) and multiclass naive Bayes classifier (MNBC).
文摘为了减小配电网带电作业的人身安全风险,降低电力系统的运维成本,文中设计了一种面向配电网作业的半人形智能机器人系统,包括硬件结构和控制系统设计。不同于绝缘杆作业法,该系统通过佩戴数据手套和腕部红外追踪器等多模态可穿戴设备来捕捉人体动作和作业细节,并采用动态运动基元(dynamic movement primitives, DMP)将人体数据映射到半人形机器人的机械臂和末端灵巧手来进行配网作业。测试结果表明:所设计的半人形机器人系统能够稳定跟踪人体演示细节。在模拟配电网线路中可以完成多种作业功能,作业实验成功率可达88.9%。
基金Supported by the National Natural Science Foun-dation of China ( 60473015)
文摘An effective blind digital watermarking algorithm based on neural networks in the wavelet domain is presented. Firstly, the host image is decomposed through wavelet transform. The significant coefficients of wavelet are selected according to the human visual system （HVS） characteristics. Watermark bits are added to them. And then effectively cooperates neural networks to learn the characteristics of the embedded watermark related to them. Because of the learning and adaptive capabilities of neural networks, the trained neural networks almost exactly recover the watermark from the watermarked image. Experimental results and comparisons with other techniques prove the effectiveness of the new algorithm.
文摘目的探究人偏肺病毒感染的发病机制,并基于逆向网络药理学思维对其进行中药组方预测。方法于Genecards数据库和OMIM数据库中获取人偏肺病毒的靶点,将所得靶点导入STRING数据库构建蛋白互作网络,利用Cytoscape 3.9.0软件结合R软件获得关键靶点。根据GO和KEGG富集分析明确其发病机制与通路。根据度值选取核心靶点,通过Uniprot数据库将核心靶点转换后于traditional Chinese medicine SP数据库逆向收集中药成分及中药。使用Cytoscape 3.9.0软件构建关键靶点-有效成分-中药网络关系图。利用STBYL-2.0软件将核心靶点与核心成分进行分子对接验证,最后确定度值较高中药并分析整理其性、味、归经。结果共获取人偏肺病毒靶点209个,根据度值得到26个关键靶点。GO富集分析主要得出1866个条目,KEGG富集分析显示88条信号通路。根据度值选取的8个核心靶点于traditional Chinese medicine SP数据库中共匹配到29种入血成分及298种中药。将8个核心靶点蛋白与度值较高的4种核心成分进行分子对接验证,结果稳定且良好。整理度值≥10的中药共69种,主要为苦参、连翘、余甘子、半枝莲、木蝴蝶、银杏叶等,以寒性药、苦味药居多,其次为温性药、辛味药,并且肝、肺二经居多。结论运用逆向网络药理学思维及分子对接技术对人偏肺病毒进行靶点、通路、成分和中药预测,为临床治疗及研究提供新思路和理论依据。
