Factors affecting e-Learning effectiveness in a higher learning institution in Malaysia

The purpose of this research was to investigate factors that influence the effectiveness of the e-learning system in a higher learning institution. The participants were students randomly selected from diploma and degree programs. The main instrument was a questionnaire that was distributed to the students. The researchers collected 205 completed questionnaires out of a total of 300. Four factors were chosen as independent variables namely: reaction and satisfaction,learning outcome and achievement, familiarity with online learning technology, and participation and interaction. It was found that the effectiveness of the e-learning system was significantly affected by reaction and satisfaction, learning outcome and achievement, and familiarity with online learning technology. The participation and interaction factor had no apparent effect on the effectiveness of the e-learning system. Therefore, it is recommended that higher learning institutions interested in introducing e-learning should focus on students’ reaction and satisfaction towards the system.E-learning should focus on learning outcomes and achievement. It is also recommended that institutions first look into the issue of familiarity with online learning technology among students before introducing the e-learning system so as to determine whether students are comfortable with the online learning tools

Standing out from the affordable luxury brands: Can Coach be the next LVMH?

This exploratory research intends to study the improvement procedure for Coach and provide justification why and how Coach could be further developed

Fashion technology forecasting: From now to future

The purposes of this research were to further investigate how fashion has been driven by technology and to provide how fashion technology will be moving forward in the future

PointAtrousGraph: Deep Hierarchical Encoder-Decoder with Point Atrous Convolution for Unorganized 3D Points

Motivated by the success of encoding multi-scale contextual information for image analysis, we propose our PointAtrousGraph (PAG) - a deep permutation-invariant hierarchical encoder-decoder for efficiently exploiting multi-scale edge features in point clouds. Our PAG is constructed by several novel modules, such as Point Atrous Convolution (PAC), Edge-preserved Pooling (EP) and Edge-preserved Unpooling (EU). Similar with atrous convolution, our PAC can effectively enlarge receptive fields of filters and thus densely learn multi-scale point features. Following the idea of non-overlapping max-pooling operations, we propose our EP to preserve critical edge features during subsampling. Correspondingly, our EU modules gradually recover spatial information for edge features. In addition, we introduce chained skip subsampling/upsampling modules that directly propagate edge features to the final stage. Particularly, our proposed auxiliary loss functions can further improve our performance. Experimental results show that our PAG outperform previous state-of-the-art methods on various 3D semantic perception applications.Comment: 11 pages, 10 figure

Robust 6D Object Pose Estimation by Learning RGB-D Features

Accurate 6D object pose estimation is fundamental to robotic manipulation and grasping. Previous methods follow a local optimization approach which minimizes the distance between closest point pairs to handle the rotation ambiguity of symmetric objects. In this work, we propose a novel discrete-continuous formulation for rotation regression to resolve this local-optimum problem. We uniformly sample rotation anchors in SO(3), and predict a constrained deviation from each anchor to the target, as well as uncertainty scores for selecting the best prediction. Additionally, the object location is detected by aggregating point-wise vectors pointing to the 3D center. Experiments on two benchmarks: LINEMOD and YCB-Video, show that the proposed method outperforms state-of-the-art approaches. Our code is available at https://github.com/mentian/object-posenet.Comment: Accepted at ICRA 202

Cerebral small vessel disease burden is associated with poststroke depressive symptoms: A 15-month prospective study

Objective: All types of cerebral small vessel disease (SVD) markers including lacune, white matter hyperintensities (WMH), cerebral microbleeds, and perivascular spaces were found to be associated with poststroke depressive symptoms (PDS). This study explored whether the combination of the four markers constituting an overall SVD burden was associated with PDS. Methods: A cohort of 563 patients with acute ischemic stroke were followed over a 15-month period after the index stroke. A score of _7 on the 15-item Geriatric Depression Scale was defined as clinically significant PDS. Scores of the four SVD markers ascertained on magnetic resonance imaging were summed up to represent total SVD burden. The association between SVD burden and PDS was assessed with generalized estimating equation models. Results: The study sample had a mean age of 67.0 _ 10.2 years and mild-moderate stroke [National Institutes of Health Stroke Scale score: 3, interquartile, 1–5]. PDS were found in 18.3%, 11.6%, and 12.3% of the sample at 3, 9, and 15 months after stroke, respectively. After adjusting for demographic characteristics, vascular risk factors, social support, stroke severity, physical and cognitive functions, and size and locations of stroke, the SVD burden was associated with an increased risk of PDS [odds ratio = 1.30; 95% confidence interval = 1.07–1.58; p = 0.010]. Other significant predictors of PDS were time of assessment, female sex, smoking, number of acute infarcts, functional independence, and social support. Conclusion: SVD burden was associated with PDS examined over a 15-month follow-up in patients with mild to moderate acute ischemic stroke

2-Bromo-p-terphen­yl

In the title compound, C18H13Br, the dihedral angles between the mean planes of the central benzene ring and the mean planes of the outer phenyl and bromo­phenyl rings are 33.47 (8) and 66.35 (8)°, respectively. In the crystal, weak C—H⋯π and inter­molecular Br⋯Br [3.5503 (15) Å] inter­actions contribute to the stabilization of the packing

Phase transition between quantum and classical regimes for the escape rate of a biaxial spin system

Employing the method of mapping the spin problem onto a particle one, we have derived the particle Hamiltonian for a biaxial spin system with a transverse or longitudinal magnetic field. Using the Hamiltonian and introducing the parameter $p (\equiv (U_{max}-E)/(U_{max}-U_{min}))$ where $U_{max}$ (U_{min}) corresponds to the top (bottom) of the potential and $E$ is the energy of the particle, we have studied the first- or second-order transition around the crossover temperature between thermal and quantum regimes for the escape rate, depending on the anisotropy constant and the external magnetic field. It is shown that the phase boundary separating the first- and second-order transition and its crossover temperature are greatly influenced by the transverse anisotropy constant as well as the transverse or longitudinal magnetic field.Comment: 5 pages + 3 figures, to be published in Phys. Rev.