Classification of the cardiotocogram data for anticipation of fetal risks using machine learning techniques

The aim of the research is evaluating the classification performances of eight different machine-learning methods on the antepartum cardiotocography (CTG) data. The classification is necessary to predict newborn health, especially for the critical cases. Cardiotocography is used for assisting the obstetricians’ to obtain detailed information during the pregnancy as a technique of measuring fetal well-being, essentially in pregnant women having potential complications. The obstetricians describe CTG shortly as a continuous electronic record of the baby's heart rate took from the mother's abdomen. The acquired information is necessary to visualize unhealthiness of the embryo and gives an opportunity for early intervention prior to happening a permanent impairment to the embryo. The aim of the machine learning methods is by using attributes of data obtained from the uterine contraction (UC) and fetal heart rate (FHR) signals to classify as pathological or normal. The dataset contains 1831 instances with 21 attributes, examined by applying the methods. In the paper, the highest accuracy displayed as 99.2%.     

Prediction of risk factors of cyberbullying-related words in Korea: Application of data mining using social big data

The study examined a decision tree analysis using social big data to conduct the prediction model on types of risk factors related to cyberbullying in Korea. The study conducted an analysis of 103,212 buzzes that had noted causes of cyberbullying and data were collected from 227 online channels, such as news websites, blogs, online groups, social network services, and online bulletin boards. Using opinion-mining method and decision tree analysis, the types of cyberbullying were sorted using SPSS 25.0. The results indicated that the total rate of types of cyberbullying in Korea was 44%, which consisted of 32.3% victims, 6.4% perpetrators, and 5.3% bystanders. According to the results, the impulse factor was also the greatest influence on the prediction of the risk factors and the propensity for dominance factor was the second greatest factor predicting the types of risk factors. In particular, the impulse factor had the most significant effect on bystanders, and the propensity for dominance factor was also significant in influencing online perpetrators. It is necessary to develop a program to diminish the impulses that were initiated by bystanders as well as victims and perpetrators because many of those bystanders have tended to aggravate impulsive cyberbullying behaviors.     

改进型UDP组播的性能分析及其在实时电源控制系统中的应用

文章通过采用带连接的UDP、I/O复用技术、关闭UDP校验和功能、负载均衡等技术对普通的UDP组播技术进行改进,使之在每个控制周期(1ms)内满足了分布式实时控制系统的实时性和可靠性要求。在将改进型的UDP组播技术应用于实际控制系统之前,文中构建了一个模拟局域网进行测试,对比结果表明改进后的组播技术无论在数据包延迟、丢包率等方面较改进前的UDP组播性能有较大幅度的提高。     

整合式有线电视的视频点播配置方法

提出一种视频点播系统传送数据的结构,结合单播与群播两种数据传送的方法,通过动态改变群播与单播的频道分配比例,让大部分的使用者无需等待即可开始观看影片,进而减少整体使用者的等待时间.     

On Finding the Multicast Protection Tree Considering SRLG in WDM Optical Networks

In this letter, a new sharing mechanism, SRLG sharing, is proposed, which allows the links of the same shared risk link group (SRLG) in a primary light tree to share protections in WDM optical networks. In previous studies, how to share spare resources with SRLG constraints has not been studied in multicast optical networks. In this letter, considering SRLG sharing, we propose a novel algorithm –multicast with SRLG sharing (MSS)– to establish a protection light tree. Finally, the algorithm MSS and the algorithm multicast with no SRLG sharing (MNSS) are compared through a simulation to show that our new sharing scheme of SRLG sharing is more efficient than that of no SRLG sharing in terms of spare resource utilization and blocking probability.     

一种支持QoS的拓扑自适应动态组播路由算法

YAM、QoSMIC、DSDMR等一类支持QoS的动态组播路由算法允许组播成员动态地加入和离开，同时为接收方提供多个可选择的组播接入路径，以满足不同应用的QoS需求。但这些算法普遍存在控制信令开销大和结点加入时延长，可扩展性不好等问题。本文在分析这些算法的基础上，提出改进的支持QoS的动态组播路由算法，即拓扑自适应动态组播路由（Topology Adaptive Dynamic Multicast Routing，TADMR）算法。该算法避免了以往算法中大部分盲目的路径搜索，并使结点加入时延不再受限于固定的等待时钟，而与网络拓扑相自适应。性能分析和仿真结果表明，该算法具有较低的控制信令开销和结点加入时延，适用于各种网络规模和群组规模，具有良好的可扩展性。     

Dynamic Multicast Session Provisioning in WDM Optical Networks with Sparse Splitting Capability

In this work, we study dynamic provisioning of multicast sessions in a wavelength-routed sparse splitting capable WDM network with an arbitrary mesh topology where the network consists of nodes with full, partial, or no wavelength conversion capabilities and a node can be a tap-and-continue (TaC) node or a splitting and delivery (SaD) node. The objectives are to minimize the network resources in terms of wavelength-links used by each session and to reduce the multicast session blocking probability. The problem is to route the multicast session from each source to the members of every multicast session, and to assign an appropriate wavelength to each link used by the session. We propose an efficient online algorithm for dynamic multicast session provisioning. To evaluate the proposed algorithm, we apply the integer linear programming (ILP) optimization tool on a per multicast session basis to solve off-line the optimal routing and wavelength assignment given a multicast session and the current network topology as well as its residual network resource information. We formulate the per session multicast routing and wavelength assignment problem as an ILP. With this ILP formulation, the multicast session blocking probability or success probability can then be estimated based on solving a series of ILPs off-line. We have evaluated the effectiveness of the proposed online algorithm via simulation in terms of session blocking probability and network resources used by a session. Simulation results indicate that our proposed computationally efficient online algorithm performs well even when a fraction of the nodes are SaD nodes.     

可靠组播中的差错检测与恢复技术

在可靠组播的实现中要解决的关键问题之一是如何进行快速有效的差错检测和恢复，主要有重传和纠错两类机制。文章介绍了这两类机制的研究现状，从模型特点、网络负荷、适用悄况等不同角度进行分析，讨沦了本地重传及其范围策略。     

ATM局域网仿真体系结构的研究

本文在简要叙述了基于ＡＴＭ技术进行局域网仿真的原理后，对局域网仿真体系结构作了一些探讨。考虑的重点是无连接服务和群播功能的实现     

A pattern recognition-based approach for phylogenetic network construction with constrained recombination

The tree representation of evolutionary relationship oversimplifies the view of the process of evolution as it cannot take into account the events such as horizontal gene transfer, hybridization, homoplasy and genetic recombination. Several algorithms exist for constructing phylogenetic networks which result from events such as horizontal gene transfer, hybridization and homoplasy. Very little work has been published on the algorithmic detail of phylogenetic networks with constrained recombination. The problem of minimizing the number of recombinations in a phylogenetic network, constructed using binary DNA sequences, is NP-hard. In this paper, we propose a pattern recognition-based O(n²) time approach for constructing the phylogenetic network, where n is the number of nodes or sequences in the input data. The network is constructed with the restriction that no two cycles in the network share a common node.