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Using Multivariate Statistics

Data Mining Practical Machine Learning Tools and Techniques

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

The present report is submitted in response to General Assembly resolution 61/106, by which the Assembly adopted the Convention on the Rights of Persons with Disabilities and the Optional Protocol thereto. As requested by the Assembly, a brief overview of the status of the Convention as at 3 August 2007 is presented. The report also contains a brief description of technical arrangements on staff and facilities made necessary for the effective performance of the functions of the Conference of States Parties and the Committee under the Convention and the Optional Protocol, and a description on the progressive implementation of standards and guidelines for the accessibility of facilities and services of the United Nations system. Recent efforts of the United Nations and agencies to disseminate information on the Convention and the Optional Protocol are also described.

わかりやすい障害者の権利条約 : 知的障害のある人の権利のために = Convention on the rights of persons with disabilities

The Object Management Group's (OMG) Model Driven Architecture (MDA) strategy envisages a world where models play a more direct role in software production, being amenable to manipulation and transformation by machine. Model Driven Engineering (MDE) is wider in scope than MDA. MDE combines process and analysis with architecture. This article sets out a framework for model driven engineering, which can be used as a point of reference for activity in this area. It proposes an organisation of the modelling 'space' and how to locate models in that space. It discusses different kinds of mappings between models. It explains why process and architecture are tightly connected. It discusses the importance and nature of tools. It identifies the need for defining families of languages and transformations, and for developing techniques for generating/configuring tools from such definitions. It concludes with a call to align metamodelling with formal language engineering techniques.

Model Driven Engineering

Review: A meta-analysis of e-learning technology acceptance: The role of user types and e-learning technology types

ContextSoftware metrics may be used in fault prediction models to improve software quality by predicting fault location. ObjectiveThis paper aims to identify software metrics and to assess their applicability in software fault prediction. We investigated the influence of context on metrics' selection and performance. MethodThis systematic literature review includes 106 papers published between 1991 and 2011. The selected papers are classified according to metrics and context properties. ResultsObject-oriented metrics (49%) were used nearly twice as often compared to traditional source code metrics (27%) or process metrics (24%). Chidamber and Kemerer's (CK) object-oriented metrics were most frequently used. According to the selected studies there are significant differences between the metrics used in fault prediction performance. Object-oriented and process metrics have been reported to be more successful in finding faults compared to traditional size and complexity metrics. Process metrics seem to be better at predicting post-release faults compared to any static code metrics. ConclusionMore studies should be performed on large industrial software systems to find metrics more relevant for the industry and to answer the question as to which metrics should be used in a given context.

http://romisatriawahono.net/lecture/rm/survey/software%20engineering/Software%20Fault%20Defect%20Prediction/Radjenovic%20-%20Software%20fault%20prediction%20metrics%20-%202013.pdf

Software fault prediction metrics

Blockchain technology enables the creation of a decentralized environment, where transactions and data are not under the control of any third party organization. Any transaction ever completed is recorded in a public ledger in a verifiable and permanent way. Based on the blockchain technology, we propose a global higher education credit platform, named EduCTX. This platform is based on the concept of the European Credit Transfer and Accumulation System (ECTS). It constitutes a globally trusted, decentralized higher education credit, and grading system that can offer a globally unified viewpoint for students and higher education institutions (HEIs), as well as for other potential stakeholders, such as companies, institutions, and organizations. As a proof of concept, we present a prototype implementation of the environment, based on the open-source Ark Blockchain Platform. Based on a globally distributed peer-to-peer network, EduCTX will process, manage, and control ECTX tokens, which represent credits that students gain for completed courses, such as ECTS. HEIs are the peers of the blockchain network. The platform is a first step toward a more transparent and technologically advanced form of higher education systems. The EduCTX platform represents the basis of the EduCTX initiative, which anticipates that various HEIs would join forces in order to create a globally efficient, simplified, and ubiquitous environment in order to avoid language and administrative barriers. Therefore, we invite and encourage HEIs to join the EduCTX initiative and the EduCTX blockchain network.

EduCTX: A Blockchain-Based Higher Education Credit Platform

When users are presented with a new technology or service, a number of factors influence their decision about how and when they will use it. To measure how students and teachers are going to accept and use a specific e-learning technology or service, an appropriate instrument is needed. In this paper common theories that can be used for measuring students' acceptance of e-learning technologies and services are presented. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was used to develop the measurement instrument. The measurement items have been adapted to Moodle, an open source web-based Virtual Learning Environment (VLE). Empirical data was conducted using an online survey with undergraduate students (n=235). To understand students’ perceptions about using Moodle, the UTAUT research model and hypothesized relationships between UTAUT constructs were empirically tested using the structural equation modeling (SEM) approach. The results indicate that performance expectancy and social influence have a significant impact on students’ attitudes towards using Moodle. Social influence and attitudes toward using are significant determinants of students' behavioral intention. Students’ behavioural intentions were shown to be strong and significant determinant of actual use of Moodle. The implications and limitations of the present study are also discussed.

Marjan Hericko

Papers

Review: A meta-analysis of e-learning technology acceptance: The role of user types and e-learning technology types

Software fault prediction metrics

EduCTX: A Blockchain-Based Higher Education Credit Platform

An Empirical Study of Virtual Learning Environment Adoption Using UTAUT

Privacy antecedents for SNS self-disclosure