EFEKTIVITAS MODEL PEMBELAJARAN MIND MAPPING TERHADAP HASIL BELAJAR SISWA PADA MATA PELAJARAN GEOGRAFI SMA

This study aims to determine differences in learning outcomes of the control class and the experimental class using the mind mapping learning model with the imindmap application. The type of research used is a quasi experimental. Design type nonequivalent control group design. Data collection techniques used are observations and measurement. The data collection instruments in this study were test sheets and observation sheets. The results of this study indicate that there are differences in the learning outcomes of students who are taught using mind mapping learning model with the imindmap application and students who are not taught using mind mapping learning model with the imindmap application

Realizing live sequence charts in SystemVerilog.

The design of an embedded control system starts with an investigation of properties and behaviors of the process evolving within its environment, and an analysis of the requirement for its safety performance. In early stages, system requirements are often specified as scenarios of behavior using sequence charts for different use cases. This specification must be precise, intuitive and expressive enough to capture different aspects of embedded control systems. As a rather rich and useful extension to the classical message sequence charts, live sequence charts (LSC), which provide a rich collection of constructs for specifying both possible and mandatory behaviors, are very suitable for designing an embedded control system. However, it is not a trivial task to realize a high-level design model in executable program codes effectively and correctly. This paper tackles the challenging task by providing a mapping algorithm to automatically synthesize SystemVerilog programs from given LSC specifications

ICface: Interpretable and Controllable Face Reenactment Using GANs

This paper presents a generic face animator that is able to control the pose and expressions of a given face image. The animation is driven by human interpretable control signals consisting of head pose angles and the Action Unit (AU) values. The control information can be obtained from multiple sources including external driving videos and manual controls. Due to the interpretable nature of the driving signal, one can easily mix the information between multiple sources (e.g. pose from one image and expression from another) and apply selective post-production editing. The proposed face animator is implemented as a two-stage neural network model that is learned in a self-supervised manner using a large video collection. The proposed Interpretable and Controllable face reenactment network (ICface) is compared to the state-of-the-art neural network-based face animation techniques in multiple tasks. The results indicate that ICface produces better visual quality while being more versatile than most of the comparison methods. The introduced model could provide a lightweight and easy to use tool for a multitude of advanced image and video editing tasks.Comment: Accepted in WACV-202

A Framework to Control Functional Connectivity in the Human Brain

In this paper, we propose a framework to control brain-wide functional connectivity by selectively acting on the brain's structure and parameters. Functional connectivity, which measures the degree of correlation between neural activities in different brain regions, can be used to distinguish between healthy and certain diseased brain dynamics and, possibly, as a control parameter to restore healthy functions. In this work, we use a collection of interconnected Kuramoto oscillators to model oscillatory neural activity, and show that functional connectivity is essentially regulated by the degree of synchronization between different clusters of oscillators. Then, we propose a minimally invasive method to correct the oscillators' interconnections and frequencies to enforce arbitrary and stable synchronization patterns among the oscillators and, consequently, a desired pattern of functional connectivity. Additionally, we show that our synchronization-based framework is robust to parameter mismatches and numerical inaccuracies, and validate it using a realistic neurovascular model to simulate neural activity and functional connectivity in the human brain.Comment: To appear in the proceedings of the 58th IEEE Conference on Decision and Contro

An investigation into the use of quality management techniques in NZ IT projects : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Information Systems at Massey University

The risks in an IT project are very high both because of its complexity and also because the context of rapidly-developing technology leads to a high degree of uncertainty. IT projects should have comprehensive formal quality management fully integrated within all aspects of project management. A review of the quality management in IT project literature suggests, customer-focused TQM is now synonymous with good management. TQM combines the use of computerised data collection and statistical experimentation with a focus on teamwork, group participation and a culture of continuous improvement in operating systems (Robert. 1993). Using the survey methodology and through two case studies, qualitative data was gathered to develop a model of quality management implementation process in New Zealand. Key words: Quality. Total Quality Management (TQM), Quality Control (QC), Quality Assurance (QA), Quality Model