Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

物件導向軟體之架構(Object-Oriented Software Construction)探討

Globalisation of supply chains makes their management and control more difficult. Blockchain technology, as a distributed digital ledger technology which ensures transparency, traceability, and sec...

Blockchain technology and its relationships to sustainable supply chain management

Normal accidents. Living with high-risk technologies

A systematic literature review of blockchain-based applications: Current status, classification and open issues

Blockchain is a decentralized transaction and data management technology developed first for Bitcoin cryptocurrency. The interest in Blockchain technology has been increasing since the idea was coined in 2008. The reason for the interest in Blockchain is its central attributes that provide security, anonymity and data integrity without any third party organization in control of the transactions, and therefore it creates interesting research areas, especially from the perspective of technical challenges and limitations. In this research, we have conducted a systematic mapping study with the goal of collecting all relevant research on Blockchain technology. Our objective is to understand the current research topics, challenges and future directions regarding Blockchain technology from the technical perspective. We have extracted 41 primary papers from scientific databases. The results show that focus in over 80% of the papers is on Bitcoin system and less than 20% deals with other Blockchain applications including e.g. smart contracts and licensing. The majority of research is focusing on revealing and improving limitations of Blockchain from privacy and security perspectives, but many of the proposed solutions lack concrete evaluation on their effectiveness. Many other Blockchain scalability related challenges including throughput and latency have been left unstudied. On the basis of this study, recommendations on future research directions are provided for researchers.

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Where Is Current Research on Blockchain Technology?-A Systematic Review.

The goal of this roadmap paper is to summarize the state-of-the-art and to identify critical challenges for the systematic software engineering of self-adaptive systems. The paper is partitioned into four parts, one for each of the identified essential views of self-adaptation: modelling dimensions, requirements, engineering, and assurances. For each view, we present the state-of-the-art and the challenges that our community must address. This roadmap paper is a result of the Dagstuhl Seminar 08031 on "Software Engineering for Self-Adaptive Systems," which took place in January 2008.

/pdf/software-engineering-for-self-adaptive-systems-a-research-3vvz0zex5m.pdf

Software Engineering for Self-Adaptive Systems: A Research Roadmap

The Software Engineering Institute (SEI) defines an SPL as a set of software-intensive systems that share a common, managed set of features satisfying the specific needs of a particular market segment or mission. A fundamental principle of SPLs is variability management, which involves separating the product line into three parts - common components, parts common to some but not all products, and individual products with their own specific requirements - and managing these throughout development. Using SPLs seeks to maximize reusable variation and eliminate wasteful generic development of components used only once. Although traditional SPL engineering recognizes that variation points are bound at different stages of development, and possibly also at runtime, it typically binds variation points before delivery of the software. In contrast, DSPL engineers typically aren't concerned with pre-runtime variation points. However, they recognize that in practice mixed approaches might be viable, where some variation points related to the environment's static properties are bound before runtime and others related to the dynamic properties are bound at runtime.

Dynamic Software Product Lines

Dynamic software product lines extend existing product line engineering approaches by moving their capabilities to runtime, helping to ensure that system adaptations lead to desirable properties.

Sooyong Park

Papers

Where Is Current Research on Blockchain Technology?-A Systematic Review.

Software Engineering for Self-Adaptive Systems: A Research Roadmap

Dynamic Software Product Lines

Dynamic Software Product Lines

Building Dynamic Software Product Lines