Control theoretic models of pointing

This article presents an empirical comparison of four models from manual control theory on their ability to model targeting behaviour by human users using a mouse: McRuer’s Crossover, Costello’s Surge, second-order lag (2OL), and the Bang-bang model. Such dynamic models are generative, estimating not only movement time, but also pointer position, velocity, and acceleration on a moment-to-moment basis. We describe an experimental framework for acquiring pointing actions and automatically fitting the parameters of mathematical models to the empirical data. We present the use of time-series, phase space, and Hooke plot visualisations of the experimental data, to gain insight into human pointing dynamics. We find that the identified control models can generate a range of dynamic behaviours that captures aspects of human pointing behaviour to varying degrees. Conditions with a low index of difficulty (ID) showed poorer fit because their unconstrained nature leads naturally to more behavioural variability. We report on characteristics of human surge behaviour (the initial, ballistic sub-movement) in pointing, as well as differences in a number of controller performance measures, including overshoot, settling time, peak time, and rise time. We describe trade-offs among the models. We conclude that control theory offers a promising complement to Fitts’ law based approaches in HCI, with models providing representations and predictions of human pointing dynamics, which can improve our understanding of pointing and inform design

Advanced Algorithms for Satellite Communication Signal Processing

Dizertační práce je zaměřena na softwarově definované přijímače určené k úzkopásmové družicové komunikaci. Komunikační kanály družicových spojů zahrnujících komunikaci s hlubokým vesmírem jsou zatíženy vysokými úrovněmi šumu, typicky modelovaného AWGN, a silným Dopplerovým posuvem signálu způsobeným mimořádnou rychlostí pohybu objektu. Dizertační práce představuje možné postupy řešení výpočetně efektivní digitální downkonverze úzkopásmových signálů a systému odhadu kmitočtu nosné úzkopásmových signálů zatížených Dopplerovým posuvem v řádu násobků šířky pásma signálu. Popis navrhovaných algoritmů zahrnuje analytický postup jejich vývoje a tam, kde je to možné, i analytické hodnocení jejich chování. Algoritmy jsou modelovány v prostředí MATLAB Simulink a tyto modely jsou využity pro ověření vlastností simulacemi. Modely byly také využity k experimentálním testům na reálném signálu přijatém z družice PSAT v laboratoři experimentálních družic na ústavu radioelektroniky.The dissertation is focused on software defined receivers intended for narrowband satellite communication. The satellite communication channel including deep space communication suffers from a high level of noise, typically modeled by AWGN, and from a strong Doppler shift of a signal caused by the unprecedented speed of an object in motion. The dissertation shows possible approaches to the issues of computationally efficient digital downconversion of narrowband signals and the carrier frequency estimation of narrowband signals distorted by the Doppler shift in the order of multiples of the signal bandwidth. The description of the proposed algorithms includes an analytical approach of its development and, if possible, the analytical performance assessment. The algorithms are modeled in MATLAB Simulink and the models are used for validating the performance by the simulation. The models were also used for experimental tests on the real signal received from the PSAT satellite at the laboratory of experimental satellites at the department of radio electronics.

A modulation property of time-frequency derivatives of filtered phase and its application to aperiodicity and fo estimation

We introduce a simple and linear SNR (strictly speaking, periodic to random power ratio) estimator (0dB to 80dB without additional calibration/linearization) for providing reliable descriptions of aperiodicity in speech corpus. The main idea of this method is to estimate the background random noise level without directly extracting the background noise. The proposed method is applicable to a wide variety of time windowing functions with very low sidelobe levels. The estimate combines the frequency derivative and the time-frequency derivative of the mapping from filter center frequency to the output instantaneous frequency. This procedure can replace the periodicity detection and aperiodicity estimation subsystems of recently introduced open source vocoder, YANG vocoder. Source code of MATLAB implementation of this method will also be open sourced.Comment: 8 pages 9 figures, Submitted and accepted in Interspeech201

Characteristics of boards of directors and board effectiveness: a study of Malaysian Public listed companies

Boards of directors are integral to modem corporations and, consequently, receive much attention from regulators, researchers and stakeholders. Although this domain is receiving increased scrutiny, most studies have been based on relating various dimensions of board structure and composition to fum financial performance. However, such studies have failed to draw an unambiguous conclusion about the impact of board structure and composition on firm performance. Considering the importance of board dynamics on the effectiveness of the board, this study examines the characteristics of members of boards of directors and determines the contribution that these characteristics make to the effectiveness of boards of directors in Malaysian Public Listed Companies (PLCs). Furthermore, there is limited study in this area from emerging-economy countries with relatively less developed capital markets. The underlying theme throughout this study is that characteristics of members of boards of directors are important components of board effectiveness. Based on extensive literature, this study develops a theoretical framework and six research questions. The characteristics of boards of director members considered in this study include demographic characteristics, personality characteristics and values, and competencies. Concerning the characteristics of effective boards, this study used a range of boards of directors' attributes including board roles, structure, composition, board membership and board dynamics. However, as this study utilised a qualitative approach, board effectiveness was assessed by reference to the pahcipants' points of view of their overall boards. In other words, what is being assessed in this study is not the relationship between board characteristics and fum financial performance but rather the participants perception of their boards. Data inthis study relied on two key sources: in-depth interviews and publicly available data from 2007 annual reports of the top 100 Malaysia PLCs. In-depth interviews were conducted with 33 directors of the top 100 Malaysian PLCs and 8 representatives of Malaysian corporate governance organisations. They were chosen because of their knowledge and experience in Malaysian corporate governance. The results of this study show that board members' demographic characteristics (age, tenure, multiple directorships), their personality characteristics and values (commitment, integrity, open mindedness, relationships with others) and their competencies (experience in corporate management, relevant knowledge and skills and relevant types of educational qualifications), as well as good networking with the government, are integral components of the effectiveness of Malaysian PLC boards. In addition, four components that have been found to be important for the effectiveness of Malayslan PLC boards include competence and diverse backgrounds of board members, a good culture, clear roles and responsibilities, and well-defined board strncturcs. More importantly, the results indicate that board membership is the most important component influencing board effectiveness for Malaysian PLCs. Although the relationship between board characteristics and fm performance has not been addressed directly, this study contributes to the understanding of the important characteristics of board members and board effectiveness. This thesis makes a number of contributions. The results add to the knowledge base for countries with developing economies. Further, it contributes to theory by proposing an integrated model of board effectiveness, which provides a basis for future hypothesis testing and theory building to identify more consistent relationships between the characteristics of boards of director members and fum performance. Testing the framework against f m s ' financial performance provides an avenue for future research that can contribute to closing the gap in the knowledge that exists concerning the relationship between board members' characteristics and firms' financial performance. In conclusion, the results from this thesis may have some implications for Malaysian regulators and others concerned with the establishment of guidelines pertaining to the selection of effective board members and effective boards

EEG-Based User Reaction Time Estimation Using Riemannian Geometry Features

Riemannian geometry has been successfully used in many brain-computer interface (BCI) classification problems and demonstrated superior performance. In this paper, for the first time, it is applied to BCI regression problems, an important category of BCI applications. More specifically, we propose a new feature extraction approach for Electroencephalogram (EEG) based BCI regression problems: a spatial filter is first used to increase the signal quality of the EEG trials and also to reduce the dimensionality of the covariance matrices, and then Riemannian tangent space features are extracted. We validate the performance of the proposed approach in reaction time estimation from EEG signals measured in a large-scale sustained-attention psychomotor vigilance task, and show that compared with the traditional powerband features, the tangent space features can reduce the root mean square estimation error by 4.30-8.30%, and increase the estimation correlation coefficient by 6.59-11.13%.Comment: arXiv admin note: text overlap with arXiv:1702.0291

Motion clouds: model-based stimulus synthesis of natural-like random textures for the study of motion perception

Choosing an appropriate set of stimuli is essential to characterize the response of a sensory system to a particular functional dimension, such as the eye movement following the motion of a visual scene. Here, we describe a framework to generate random texture movies with controlled information content, i.e., Motion Clouds. These stimuli are defined using a generative model that is based on controlled experimental parametrization. We show that Motion Clouds correspond to dense mixing of localized moving gratings with random positions. Their global envelope is similar to natural-like stimulation with an approximate full-field translation corresponding to a retinal slip. We describe the construction of these stimuli mathematically and propose an open-source Python-based implementation. Examples of the use of this framework are shown. We also propose extensions to other modalities such as color vision, touch, and audition