The influence of national culture on the attitude towards mobile recommender systems

This is the post-print version of the final paper published in Technological Forecasting and Social Change. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.This study aimed to identify factors that influence user attitudes towards mobile recommender systems and to examine how these factors interact with cultural values to affect attitudes towards this technology. Based on the theory of reasoned action, belief factors for mobile recommender systems are identified in three dimensions: functional, contextual, and social. Hypotheses explaining different impacts of cultural values on the factors affecting attitudes were also proposed. The research model was tested based on data collected in China, South Korea, and the United Kingdom. Findings indicate that functional and social factors have significant impacts on user attitudes towards mobile recommender systems. The relationships between belief factors and attitudes are moderated by two cultural values: collectivism and uncertainty avoidance. The theoretical and practical implications of applying theory of reasoned action and innovation diffusion theory to explain the adoption of new technologies in societies with different cultures are also discussed.National Research Foundation of Korea Grant funded by the Korean governmen

Linkless octree using multi-level perfect hashing

The standard C/C++ implementation of a spatial partitioning data structure, such as octree and quadtree, is often inefficient in terms of storage requirements particularly when the memory overhead for maintaining parent-to-child pointers is significant with respect to the amount of actual data in each tree node. In this work, we present a novel data structure that implements uniform spatial partitioning without storing explicit parent-to-child pointer links. Our linkless tree encodes the storage locations of subdivided nodes using perfect hashing while retaining important properties of uniform spatial partitioning trees, such as coarse-to-fine hierarchical representation, efficient storage usage, and efficient random accessibility. We demonstrate the performance of our linkless trees using image compression and path planning examples.postprin

Continuous collision detection for ellipsoids

We present an accurate and efficient algorithm for continuous collision detection between two moving ellipsoids. We start with a highly optimized implementation of interference testing between two stationary ellipsoids based on an algebraic condition described in terms of the signs of roots of the characteristic equation of two ellipsoids. Then we derive a time-dependent characteristic equation for two moving ellipsoids, which enables us to develop a real-time algorithm for computing the time intervals in which two moving ellipsoids collide. The effectiveness of our approach is demonstrated with several practical examples. © 2006 IEEE.published_or_final_versio

Investigation of inter-slice magnetization transfer effects as a new method for MTR imaging of the human brain

We present a new method for magnetization transfer (MT) ratio imaging in the brain that requires no separate saturation pulse. Interslice MT effects that are inherent to multi-slice balanced steady-state free precession (bSSFP) imaging were controlled via an interslice delay time to generate MT-weighted (0 s delay) and reference images (5-8 s delay) for MT ratio (MTR) imaging of the brain. The effects of varying flip angle and phase encoding (PE) order were investigated experimentally in normal, healthy subjects. Values of up to ∼ 50% and ∼ 40% were observed for white and gray matter MTR. Centric PE showed larger MTR, higher SNR, and better contrast between white and gray matter than linear PE. Simulations of a two-pool model of MT agreed well with in vivo MTR values. Simulations were also used to investigate the effects of varying acquisition parameters, and the effects of varying flip angle, PE steps, and interslice delay are discussed. Lastly, we demonstrated reduced banding with a non-balanced SSFP-FID sequence and showed preliminary results of interslice MTR imaging of meningioma

Evaluation of Directive-Based GPU Programming Models on a Block Eigensolver with Consideration of Large Sparse Matrices

Achieving high performance and performance portability for large-scale scientific applications is a major challenge on heterogeneous computing systems such as many-core CPUs and accelerators like GPUs. In this work, we implement a widely used block eigensolver, Locally Optimal Block Preconditioned Conjugate Gradient (LOBPCG), using two popular directive based programming models (OpenMP and OpenACC) for GPU-accelerated systems. Our work differs from existing work in that it adopts a holistic approach that optimizes the full solver performance rather than narrowing the problem into small kernels (e.g., SpMM, SpMV). Our LOPBCG GPU implementation achieves a 2.8$${\times }$$–4.3$${\times }$$ speedup over an optimized CPU implementation when tested with four different input matrices. The evaluated configuration compared one Skylake CPU to one Skylake CPU and one NVIDIA V100 GPU. Our OpenMP and OpenACC LOBPCG GPU implementations gave nearly identical performance. We also consider how to create an efficient LOBPCG solver that can solve problems larger than GPU memory capacity. To this end, we create microbenchmarks representing the two dominant kernels (inner product and SpMM kernel) in LOBPCG and then evaluate performance when using two different programming approaches: tiling the kernels, and using Unified Memory with the original kernels. Our tiled SpMM implementation achieves a 2.9$${\times }$$ and 48.2$${\times }$$ speedup over the Unified Memory implementation on supercomputers with PCIe Gen3 and NVLink 2.0 CPU to GPU interconnects, respectively

Task-Specific Sensor Planning for Robotic Assembly Tasks

When performing multi-robot tasks, sensory feedback is crucial in reducing uncertainty for correct execution. Yet the utilization of sensors should be planned as an integral part of the task planning, taken into account several factors such as the tolerance of different inferred properties of the scene and interaction with different agents. In this paper we handle this complex problem in a principled, yet efficient way. We use surrogate predictors based on open-loop simulation to estimate and bound the probability of success for specific tasks. We reason about such task-specific uncertainty approximants and their effectiveness. We show how they can be incorporated into a multi-robot planner, and demonstrate results with a team of robots performing assembly tasks

Consecutive treatment with phytase and arazyme influence protein hydrolysis of soybean meal

Soybean meal (SBM) is the main protein supplement used in animal feed worldwide. The degree of hydrolysis (DH) of SBM treated with two enzymes viz. phytase and arazyme was investigated for the first time in this study. The DH of SBM in the treatment with arazyme increased significantly as compared to the control without enzyme application. About 1.5-times and 10-fold higher DH were observed in phytase treatment when compared to the control treatments containing no enzyme. At the end of 24 h, enzymatic hydrolysis was done through consecutive treatment with 0.5% (w/v) phytase and 0.02% (w/v) arazyme, and the protein in the hydrolysate were mostly degraded free amino acids and peptides (<6 KDa) when SDS-PAGE and fast protein liquid chromatography (FPLC) techniques used. Free amino acids contents of the soybean meal treated with phytase-arazyme increased by 2 to 14 fold as compared to products without enzyme. These results suggested that soybean meal proteins continuously treated with phytase and arazyme can be used as commercial feed additive for accelerated livestock growth.Key words: Soybean meal, phytase, arazyme, hydrolysis