Learning to Select Pre-Trained Deep Representations with Bayesian Evidence Framework

We propose a Bayesian evidence framework to facilitate transfer learning from pre-trained deep convolutional neural networks (CNNs). Our framework is formulated on top of a least squares SVM (LS-SVM) classifier, which is simple and fast in both training and testing, and achieves competitive performance in practice. The regularization parameters in LS-SVM is estimated automatically without grid search and cross-validation by maximizing evidence, which is a useful measure to select the best performing CNN out of multiple candidates for transfer learning; the evidence is optimized efficiently by employing Aitken's delta-squared process, which accelerates convergence of fixed point update. The proposed Bayesian evidence framework also provides a good solution to identify the best ensemble of heterogeneous CNNs through a greedy algorithm. Our Bayesian evidence framework for transfer learning is tested on 12 visual recognition datasets and illustrates the state-of-the-art performance consistently in terms of prediction accuracy and modeling efficiency.Comment: Appearing in CVPR-2016 (oral presentation

“ME NO MORE COME”: PERSISTENCE AND QUITTING AMONG ADULT SPANISH-SPEAKING ENGLISH LEARNERS

The purpose of this qualitative case study was to explore what makes adult Spanish-speaking English learners (ELs) stay or drop out of English class in a non-profit English literacy center in a city in a southwestern state in the United States. Findings reveal that adult English learners’ decisions towards staying or dropping out are complex, multifaceted, and dynamic. Superacion (Spanish word meaning self-improvement, self-actualization) was central to adult English learners’ decisions in investing for English learning. ELs’ multifaceted socio-cultural backgrounds, needs, and motivational factors are dynamic and fluid, consisting of both cognitive and affective aspects. When adult ELs dropped out, the data show that affective aspects play a strong role. When adult ELs stayed in the program, cognitive aspects played a strong role. The feelings of being cared about, learning something new, and having a good teacher that contributed to Superacion influenced ELs to stay. Teacher apathy and feeling oppressed influenced ELs to drop out

Occurrence and Characterization of Paraffin Wax Formed in Developing Wells and Pipelines

Deposition and precipitation of paraffin wax in pipelines are major problems in the production, transfer, storage, and processing of crude oil. To prevent complete clogging, it is necessary to minimize and remove deposited wax in pipelines and tubing. Significant research has been done addressing the mechanisms of wax formation and its composition. In this review, the status of research and perspectives on the occurrence and characterization of the paraffin wax that forms in crude oil developing wells and pipelines has been critically reviewed. Several approaches for detecting paraffin wax and managing wax formation damage during oil recovery were discussed. This review also highlighted the effects of temperature and crude oil type on wax formation. Document type: Articl

리눅스 환경에서 solid-state disk 성능 최적화를 위한 디스크 입출력 요구 변환 계층

2

광학 저장 매체상에 LDPC 코드를 이용한 데이터의 분산 기록 방법.

2

KULEX: An ADL power-assistance demonstration

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Prioritizing Soft Real-Time Tasks to Improve End-to-End Response Time in Distributed Control Systems

Abstract. In distributed control systems, real-time tasks may be classi ed into local tasks and global tasks. Local tasks are usually bound to a speci c node and responsible for hard real-time functions to control I/O devices whereas global tasks perform soft real-time functions such asdata logging, status reporting, and statistical analysis. Such a global task is divided into several subtasks each of which is allocated to a node and has precedence relation with other subtasks. To schedule local tasks and subtasks in a node, we must determine their priorities in the xed-priority system. In this paper, we present an algorithm to assign priorities to tasks to guarantee the deadlines of local tasks and improve the end-to-end response time of a global task which amounts to the sum of response time of its subtasks. The proposed algorithm has no run-time overhead such as slack calculation and its performance is comparable to that of slack stealing algorithm under various workloads.

1998a, 'Bandwidth Allocation for Transmission of Real-Time Messages

Abstract: In IEEE 802.12 network, a repeater arbitrates the network access contentions among the nodes on round robin basis. The node having received a grant from the repeater, can transmit a frame. The burst mode, a newly approved feature in IEEE 802.12 network, allows a node to transmit multiple frames per grant. This paper proposes a bandwidth allocation scheme based on the burst mode to guarantee the deadlines of periodic real-time messages. Once the bandwidth of each node is derived from the lengths and deadlines of periodic messages, a node can transmit the frames up to the allocated bandwidth per grant. Simulation study shows that the proposed scheme provides much higher guarantee ratio and graceful degradation for high network load, compared with the existing approaches