An approach of Bursty event detection in social networks based on topological features

User relations and information propagation on social networks can reflect events in real society. Online detection of bursty events is of great significance to studying the evolution of social networks and cyberspace security. Current research works focus on building an event recognition model based on text information and then utilizing clustering or topic model methods to extract features from the data stream and then detect events that have not existed before. The text-based method is designed for specific content, and it does not consider the features of network dynamic evolution. It is restricted by the type and quality of text in social networks, limiting its practical application scenarios. However, there exist remarkable correlations between the occurrence of events and the evolution of the network. In this paper, we consider mining the network structure changes to identify bursty events, the superiority which is that it is sensitive and widely used. We integrate snapshot network topology indexes to quantify its structural features. Then we can judge whether there is a burst event by investigating the change degree of the network structure features of the adjacent snapshots. The effectiveness and efficiency of our approach are further confirmed by experimental studies on four real social network data sets. In addition, we also discuss the salient features of the bursty events and compare the impact of the bursty events on the network structure with that of the scheduled events.

     

An ergonomics approach for work in the next millennium in an IT world

This article begins by giving the background to different the approaches in trying to predict what the labour market will look like in the future. Ongoing changes in the labour market are then discussed, together with their consequences in the slightly longer term. We then look at various ways in which we can steer changes in the labour market into a direction desirable to both society and the workforce. Finally, the needs for new research are reviewed, followed by some concluding remarks.     

An ergonomics approach for work in the next millennium in an IT world

This article begins by giving the background to different the approaches in trying to predict what the labour market will look like in the future. Ongoing changes in the labour market are then discussed, together with their consequences in the slightly longer term. We then look at various ways in which we can steer changes in the labour market into a direction desirable to both society and the workforce. Finally, the needs for new research are reviewed, followed by some concluding remarks.     

A novel approach for process mining based on event types

Despite the omnipresence of event logs in transactional information systems (cf. WFM, ERP, CRM, SCM, and B2B systems), historic information is rarely used to analyze the underlying processes. Process mining aims at improving this by providing techniques and tools for discovering process, control, data, organizational, and social structures from event logs, i.e., the basic idea of process mining is to diagnose business processes by mining event logs for knowledge. Given its potential and challenges it is no surprise that recently process mining has become a vivid research area. In this paper, a novel approach for process mining based on two event types, i.e., START and COMPLETE, is proposed. Information about the start and completion of tasks can be used to explicitly detect parallelism. The algorithm presented in this paper overcomes some of the limitations of existing algorithms such as the α-algorithm (e.g., short-loops) and therefore enhances the applicability of process mining.

基于攻击症状的安全事件关联方法研究

提出一套基于攻击症状的安全事件关联方法.根据攻击和症状间因果关系构建了安全事件关联模型,提出了依据关联模型自动计算产生安全事件关联规则的思想,并用特征代码匹配法实现事件关联.     

CPL+: An improved approach for evaluating the local completeness of event logs

Process mining aims at deriving order relations between tasks recorded by event logs in order to construct their corresponding process models. The quality of the results is not only determined by the mining algorithm being used, but also by the quality of the provided event logs. As a criterion of log quality, completeness measures the magnitude of information for process mining covered by an event log. In this paper, we focus on the evaluation of the local completeness of an event log. In particular, we consider the direct succession (DS) relations between the tasks of a business process. Based on our previous work, an improved approach called CPL+ is proposed in this paper. Experiments show that the proposed CPL+ works better than other approaches, on event logs that contain a small amount of traces. Finally, by further investigating CPL+, we also found that the more distinct DSs observed in an event log, the lower the local completeness of the log is.     

Real-world production scheduling for the food industry: An integrated approach

The present paper offers an integrated approach to real-world production scheduling for the food processing industries. A manufacturing execution system is very appropriate to monitor and control the activities on the shop floor. Therefore, a specialized scheduler, which is the focus of this paper, has been developed to run at the core of such a system. The scheduler builds on the very general Resource Constrained Project Scheduling Problem with Generalized Precedence Relations. Each local decision step (e.g. choosing a route in the plant layout) is modeled as a separate module interconnected in a feedback loop. The quality of the generated schedules will guide the overall search process to continuously improve the decisions at an intermediate level by using local search strategies. Besides optimization methods, data mining techniques are applied to historical data in order to feed the scheduling process with realistic background knowledge on key performance indicators, such as processing times, setup times, breakdowns, etc. The approach leads to substantial speed and quality improvements of the scheduling process compared to the manual practice common in production companies. Moreover, our modular approach allows for further extending or improving modules separately, without interfering with other modules.     

An empirical study of variations in COTS-based software development processes in the Norwegian IT industry

More and more software projects use Commercial-Off-The-Shelf (COTS) components. Although previous studies have proposed specific COTS-based development processes, there are few empirical studies that investigate how to use and customize COTS-based development processes for different project contexts. This paper describes an exploratory study of state-of-the-practice of COTS-based development processes. Sixteen software projects in the Norwegian IT companies have been studied by structured interviews. The results are that COTS-specific activities can be successfully incorporated in most traditional development processes (such as waterfall or prototyping), given proper guidelines to reduce risks and provide specific assistance. We have identified four COTS-specific activities—the build vs. buy decision, COTS component selection, learning and understanding COTS components, and COTS component integration – and one new role, that of a knowledge keeper. We have also found a special COTS component selection activity for unfamiliar components, combining Internet searches with hands-on trials. The process guidelines are expressed as scenarios, problems encountered, and examples of good practice. They can be used to customize the actual development processes, such as in which lifecycle phase to put the new activities into. Such customization crucially depends on the project context, such as previous familiarity with possible COTS components and flexibility of requirements.

An emergency event detection approach in real-time for efficient vehicle safety in Smart City

Multimedia Tools and Applications - Nowadays, the Internet of things (IoT) provides various services to drivers by equipped with smart devices. In this regard, the next generation of vehicles...     

A metric for quantifying the ripple effects among requirements

Software Quality Journal - During software maintenance, it is often costlier to identify and understand the artifacts that need to be changed, rather than to actually apply the change. In addition...     

A clustering approach for identifying and quantifying irregularities in interconnection networks

Support for arbitrary topologies has become more popular for system-area networks but very little has been done in trying to characterize their behavior and performance. Traditional parameters like diameter and bisection width are not sufficient for characterizing the irregularities that abound in such networks and fail to give much insight into throughput performance. A clustering approach for partitioning a network into clusters of richly-connected regions is proposed as a means of defining two performance-correlated characterization metrics: intercluster bandwidth index and intercluster link-cost index. The two characterization metrics are shown to have a strong correlation to saturation throughput when link and load distribution of a network is imbalanced. Simulation results also show that the clustering algorithm can be applied to a variety of network configurations and traffic scenarios, particularly irregular ones. With the proposed characterization metrics that correlate more strongly with performance, it is possible to classify networks into categories having similar performance.     

A performance comparison of event calendar algorithms: An empirical approach

We propose a suite of tests based on two-state Markov chains for experimentally assessing the dynamic performance of a variety of simulation event calendar implementations. In contrast to previous studies based on the standard hold model for evaluation of performance statically, the proposed Markov hold model is more general and can be used to examine how different implementations respond dynamically to dependent sequences of insertion and deletion requests. The Markov hold model is used to conduct tests based on random, stressed, and correlated input sequences of requests, with performance measures including completion times, sensitivity to correlations, sensitivity to duplication, and efficiency of data-handling. We apply these tests to fourteen different event calendar implementations. To demonstrate the utility of the proposed model, we also include a comparison of the event calendar algorithms on a token ring protocol with bursty Markovian packet-traffic.     

基于LHMM的聚众异常事件实时检测改进方法

提出了一种改进的分层隐马尔科夫模型(LHMM)结合熵值的聚众异常事件实时检测方法。使用直方图均衡化对视频帧做预处理,增加图像质量;以分块区域中的人数和总速度作为观察值分两层训练出聚众事件的LHMM。当观察值序列与模型的相似度大于设定阈值时,利用光流法计算该帧熵值,当熵值大于设定阈值时,则认为聚众事件发生;否则,为非聚众事件,继续下一帧的处理。大量实验结果表明:改进的方法具有较高的识别率、较好的鲁棒性和高的处理速度,并且应用环境更广。     

An integrated approach for head gesture based interface

The head pose and movement of a user is closely related with his/her intention and thought, recognition of such information could be useful to develop a natural and sensitive user-wheelchair interface. This paper presents an original integrated approach to a head gesture based interface (HGI) which can perform both identity verification and facial pose estimation. Identity verification is performed by two-factor face authentication which is implemented by the combination of topographic independent component analysis (TICA) and multispace random projection (MRP). Modified synergetic computer with melting (Modified SC-MELT) is introduced to classify facial poses. Motion profile generator (MPG) is thoroughly developed during the integration to convert each estimated facial pose sequence into motion control signal to actuate motor movements. The HGI is intended to be deployed as a user-wheelchair interface for disabled and elderly users in which only users with genuine face and valid token may be granted authorized access and hence pilot an electric powered wheelchair (EPW) using their faces. The integration has been verified under a number of experiments to justify the feasibility and performance of the proposed face-based control strategy.     

An FAR-SW based approach for webpage information extraction

Automatically identifying and extracting the target information of a webpage, especially main text, is a critical task in many web content analysis applications, such as information retrieval and automated screen reading. However, compared with typical plain texts, the structures of information on the web are extremely complex and have no single fixed template or layout. On the other hand, the amount of presentation elements on web pages, such as dynamic navigational menus, flashing logos, and a multitude of ad blocks, has increased rapidly in the past decade. In this paper, we have proposed a statistics-based approach that integrates the concept of fuzzy association rules (FAR) with that of sliding window (SW) to efficiently extract the main text content from web pages. Our approach involves two separate stages. In Stage 1, the original HTML source is pre-processed and features are extracted for every line of text; then, a supervised learning is performed to detect fuzzy association rules in training web pages. In Stage 2, necessary HTML source preprocessing and text line feature extraction are conducted the same way as that of Stage 1, after which each text line is tested whether it belongs to the main text by extracted fuzzy association rules. Next, a sliding window is applied to segment the web page into several potential topical blocks. Finally, a simple selection algorithm is utilized to select those important blocks that are then united as the detected topical region (main texts). Experimental results on real world data show that the efficiency and accuracy of our approach are better than existing Document Object Model (DOM)-based and Vision-based approaches.     

An agent based approach for the implementation of cooperative proactive S-Metaheuristics

This paper introduces several cooperative proactive S-Metaheuristics, i.e. single-solution based metaheuristics, which are implemented taking advantage of two singular characteristics of the agent paradigm: proactivity and cooperation. Proactivity is applied to improve traditional versions of Threshold Accepting and Great Deluge Algorithm metaheuristics. This approach follows previous work for the definition of proactive versions of the Record-to-Record Travel and Local Search metaheuristics. Proactive metaheuristics are implemented as agents that cooperate in the environment of the optimization process with the goal of avoiding stagnation in local optima by adjusting their parameters. Based on the environmental information about previous solutions, the proactive adjustment of the parameters is focused on keeping a minimal level of acceptance for the new solutions. In addition, simple forms of cooperation by competition are used to develop cooperative metaheuristics based on the combination of the four proactive metaheuristics. The proposed metaheuristics have been validated through experimentation with 28 benchmark functions on binary strings, and several instances of knapsack problems and travelling salesman problems.     

A risk based model for quantifying the impact of information quality

Information quality is one of the key determinants of information system success. When information quality is poor, it can cause a variety of risks in an organization. To manage resources for information quality improvement effectively, it is necessary to understand where, how, and how much information quality impacts an organization's ability to successfully deliver its objectives. So far, existing approaches have mostly focused on the measurement of information quality but not adequately on the impact that information quality causes. This paper presents a model to quantify the business impact that arises through poor information quality in an organization by using a risk based approach. It hence addresses the inherent uncertainty in the relationship between information quality and organizational impact. The model can help information managers to obtain quantitative figures which can be used to build reliable and convincing business cases for information quality improvement.     

An approach to product variety management in the painted sheet metal industry

In the painted sheet metal industry, offering a great variety of colors is an important competitive factor. However, an excessive number of colors can lead to excessive setup costs/times, inventory costs, and administrative complexity. In this paper, we address the case of a large manufacturer of painted sheet metal products located in northern Mexico. Several methods, both exact and heuristic, are proposed to optimize the variety of colors the firm offers. The exact method is based on mixed integer programming and the heuristic methods are variations of greedy algorithms. The methods are tested with real company data. The methods that perform better are identified and considerations are discussed which can affect the choice of method in a practical setting.