Studies of Group Fused Lasso and Probit Model for Right-Censored Data

This document is composed of three main chapters. In the first chapter, we study the mixture of experts, a powerful machine learning model in which each expert handles a different region of the covariate space. However, it is crucial to choose an appropriate number of experts to avoid overfitting or underfitting. A group fused lasso (GFL) term is added to the model with the goal of making the coefficients of the experts and the gating network closer together. An algorithm to optimize the problem is also developed using block-wise coordinate descent in the dual counterpart. Numerical results on simulated and real world datasets show that the penalized model outperforms the unpenalized one and performs on par with many well-known models. The second chapter studies GFL on its own and methods to solve it efficiently. In GFL, the response and the coefficient of each observation are not scalars but vectors. Thus, many fast solvers of the fused lasso cannot be applied to the GFL. Two algorithms are proposed to solve the GFL, namely Alternating Minimization and Dual Path. Results from speed trial show that our algorithms are competitive compared to other existing methods. The third chapter proposes a better alternative to the Box-Cox transformation, a popular method to transform the response variable to have an approximately normal distribution in many cases. The Box-Cox transformation is widely applied in regression, ANOVA and machine learning for both complete and censored data. However, since it is parametric, it can be too restrictive in many cases. Our proposed method is nonparametric, more flexible and can be fitted efficiently by our novel EM algorithms which accommodate both complete and right-censored data

Droplet ejection by electrowetting actuation

Fast contact-line motion of a droplet spreading on a solid substrate under the electrowetting effect generates strong capillary waves on the droplet's surface. The capillary waves may be strong enough to induce ejection of a satellite droplet from the primary one. In this study, we show that the size of the satellite droplet and the ejection time are not only dependent on the contact-line velocity, which directly relates to the applied voltage enabling the electrowetting effect, but also affected by the ejection dynamics. We derive a theoretical model of the criteria for droplet ejection and experimentally verify the proposed criteria for wide ranges of viscosity, droplet size and the applied voltage

高強度鋼柱の高温時におけるクリープ挙動解析

東京理科大学2022年

Opportunistic secure transmission for wireless relay networks with modify-and-forward protocol

This paper investigates the security at the physical layer in cooperative wireless networks (CWNs) where the data transmission between nodes can be realised via either direct transmission (DT) or relaying transmission (RT) schemes. Inspired by the concept of physical-layer network coding (PNC), a secure PNC-based modify-and-forward (SPMF) is developed to cope with the imperfect shared knowledge of the message modification between relay and destination in the conventional modify-and-forward (MF). In this paper, we first derive the secrecy outage probability (SOP) of the SPMF scheme, which is shown to be a general expression for deriving the SOP of any MF schemes. By comparing the SOPs of various schemes, the usage of the relay is shown to be not always necessary and even causes a poorer performance depending on target secrecy rate and quality of channel links. To this extent, we then propose an opportunistic secure transmission protocol to minimise the SOP of the CWNs. In particular, an optimisation problem is developed in which secrecy rate thresholds (SRTs) are determined to find an optimal scheme among various DT and RT schemes for achieving the lowest SOP. Furthermore, the conditions for the existence of SRTs are derived with respect to various channel conditions to determine if the relay could be relied on in practice

An efficient constructive e-alignment for onsite-online learning

This paper aims at proposing an efficient constructive electronic-based alignment (CeA) to promote self-learning amongst the students via e-learning environment where e-lectures/e-tutorials are developed followed by e-assessments. The CeA is developed based on behaviourism, cognitivism, humanism and constructivism to ensure the students’ learning does take place in the e-learning environment. Considering engineering related courses at higher education, it has been shown that the decline in mathematical background of the students causes difficulties in accomplishing the quantitative curricula. A well-designed constructive alignment is thus necessary to support active learning of the students having different background. Onsite tutorials and seminars may be helpful; however, they may not be very effective, especially in a large-sized and/or high-diversity class. Therefore, in this paper, the proposed CeA not only helps the onsite students strengthen their knowledge but also provides the offsite students with various kinds of learning supplement. Particularly, a case study is presented to show the potential impact of the CeA on both onsite and online learning of mathematics for postgraduate students in both telecommunications engineering and computer networks