[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Anomaly detection is an important problem that has been researched within diverse research areas and application domains. Many anomaly detection techniques have been specifically developed for certain application domains, while others are more generic. This survey tries to provide a structured and comprehensive overview of the research on anomaly detection. We have grouped existing techniques into different categories based on the underlying approach adopted by each technique. For each category we have identified key assumptions, which are used by the techniques to differentiate between normal and anomalous behavior. When applying a given technique to a particular domain, these assumptions can be used as guidelines to assess the effectiveness of the technique in that domain. For each category, we provide a basic anomaly detection technique, and then show how the different existing techniques in that category are variants of the basic technique. This template provides an easier and more succinct understanding of the techniques belonging to each category. Further, for each category, we identify the advantages and disadvantages of the techniques in that category. We also provide a discussion on the computational complexity of the techniques since it is an important issue in real application domains. We hope that this survey will provide a better understanding of the different directions in which research has been done on this topic, and how techniques developed in one area can be applied in domains for which they were not intended to begin with.

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Anomaly detection: A survey

Data Mining - Concepts and Techniques.

According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

Purpose – Data mining (DM) has been considered to be a tool of business intelligence (BI) for knowledge discovery. Recent discussions in this field state that DM does not contribute to business in a large‐scale. The purpose of this paper is to discuss the importance of business insiders in the process of knowledge development to make DM more relevant to business.Design/methodology/approach – This paper proposes a blog‐based model of knowledge sharing system to support the DM process for effective BI.Findings – Through an illustrative case study, the paper has demonstrated the usefulness of the model of knowledge sharing system for DM in the dynamic transformation of explicit and tacit knowledge for BI. DM can be an effective BI tool only when business insiders are involved and organizational knowledge sharing is implemented.Practical implications – The structure of blog‐based knowledge sharing systems for DM process can be practically applied to enterprises for BI.Originality/value – The paper suggests th...

A knowledge management approach to data mining process for business intelligence

In this paper, we identify a new task for studying the outlying degree (OD) of high-dimensional data, i.e. finding the subspaces (subsets of features) in which the given points are outliers, which are called their outlying subspaces. Since the state-of-the-art outlier detection techniques fail to handle this new problem, we propose a novel detection algorithm, called High-Dimension Outlying subspace Detection (HighDOD), to detect the outlying subspaces of high-dimensional data efficiently. The intuitive idea of HighDOD is that we measure the OD of the point using the sum of distances between this point and itsknearest neighbors. Two heuristic pruning strategies are proposed to realize fast pruning in the subspace search and an efficient dynamic subspace search method with a sample-based learning process has been implemented. Experimental results show that HighDOD is efficient and outperforms other searching alternatives such as the naive top–down, bottom–up and random search methods, and the existing outlier detection methods cannot fulfill this new task effectively.

/pdf/detecting-outlying-subspaces-for-high-dimensional-data-the-36ft7r9rn5.pdf

Detecting outlying subspaces for high-dimensional data: the new task, algorithms, and performance

3D-CNN-based feature extraction of ground-based cloud images for direct normal irradiance prediction

Shared services have been widely spread in the government and private sectors. Unlike outsourcing, shared service is the standardization and consolidation of common functions across the multiple organizations to reduce information process duplication and increase information and knowledge sharing. Shared services should be viewed less as a phenomenon of cost saving and more as a challenge of organization redesign. Five general leading theories of organizational design are examined in the perspective of shared services. A quasi-general organizational design approach is proposed specifically for shared services projects. The proposed approach emphasizes the organizational support for the shared services strategy identification, collabora- tive partnership network design, optimal shared services process design, and policy and regulation system design.

Hai Wang

Papers

A knowledge management approach to data mining process for business intelligence

Detecting outlying subspaces for high-dimensional data: the new task, algorithms, and performance

3D-CNN-based feature extraction of ground-based cloud images for direct normal irradiance prediction

Shared services beyond sourcing the back offices: Organizational design

Detecting anomalies from big network traffic data using an adaptive detection approach