4,472 research outputs found
A Synthetical Approach for Blog Recommendation Mechanism: Trust, Social Relation, and Semantic Analysis
Weblog is a good paradigm of online social network which constitutes web-based regularly updated journals with reverse chronological sequences of dated entries, usually with blogrolls on the sidebars, allowing bloggers link to favorite site which they are frequently visited. In this study we propose an elaborate blog recommendation mechanism that combines trust model, social relation and semantic analysis and illustrate how it can be applied to a prestigious online blogging system – Wretch in Taiwan. By preliminary results of experimental study, we found some implications and empirically prove some theories in domain of social networking, and the example reveals that the proposed recommendation mechanism is quite feasible and promising
Investigating the Possibility of Intervertebral Disc Regeneration Induced by Granulocyte Colony Stimulating Factor-Stimulated Stem Cells in Rats
Intervertebral disc (IVD) degeneration is a multifactorial process that is influenced by contributions from genetic predisposition, the aging phenomenon, lifestyle conditions, biomechanical loading and activities, and other health factors (such as diabetes). Attempts to decelerate disc degeneration using various techniques have been reported. However, to date, there has been no proven technique effective for broad clinical application. Granulocyte colony-stimulating factor (GCSF) is a growth factor cytokine that has been shown to enhance the availability of circulating hematopoietic stem cells to the brain and heart as well as their capacity for mobilization of mesenchymal bone marrow stem cells. GCSF also exerts significant increases in circulating neutrophils as well as potent anti-inflammatory effects. In our study, we hypothesize that GCSF can induce bone marrow stem cells differentiation and mobilization to regenerate the degenerated IVD. We found that GCSF had no contribution in disc regeneration or maintenance; however, there were cell proliferation within end plates. The effects of GCSF treatment on end plates might deserve further investigation
A STUDY OF THE INFLUENCE FROM DIFFERENT RUNNING SLOPE ON THE ANGLES OF LIMB JOINTS
This study focuses on an analysis and comparison of the hip, knee, and ankle joint angle changes and differences during the stance and swing phase of the running gait cycle while running on the same uphill or downhill gradient as well as the lower joint angle changes while running on different uphill or downhill inclines or on level ground. This study should also provide insight into whether or not there is a significant difference between the lower joint angle patterns while running on slopes of different steepness, which in turn can serve as a reference for runners and coaches for uphill or downhill running training or workout exercises. For this study we employed a high-speed camera, which allows us to capture the running motion cycles of the sagittal plane of test subjects while running on different uphill or downhill gradients. Motion analysis software was employed for data compilation, while a comparative analysis was conducted by utilizing statistical software. After extensive discussions and analysis, we reached the following conclusions: 1. Slope gradient changes have a significant impact on hip joint angles during the stance phase. The steeper the incline is, the greater is the difference between the hip joint angles. 2. Slope gradient changes have a significant effect on joint angle changes during the swing phase. The steeper the uphill gradient, the smaller are the hip, knee, and ankle joint angles, while steeper downhill gradients lead to larger hip and knee joint angles. 3. A comparison of the changes of all joint angles during uphill, downhill, and level ground running reveals that angle changes during uphill running are greater than during downhill running. It can be inferred that this phenomenon is caused by the fact that the number of muscle groups involved in uphill running is larger than in downhill running
How the Design Leadership and Strategic Design Drive New Value in Enterprises and Organizations
Today's design has shifted from the original primary pursuit of appearance and function to processes and systems, creating new meanings for corporate strategies, products and services. Nowadays, enterprises are increasingly paying attention to the power of design, and regard design as the main innovation method and incorporate it into the organizations. Design began to be considered a key role at the top of large organizations. Although people recognize that design can bring good effects to enterprises and organizations, and there is growing interest in cultivating design thinking, what are the leaders who can lead enterprises, organizations and have design thinking? Their characteristics and how to formulate and plan strategic design still not fully elucidated. Therefore, this research uses related theories to understand the way of thinking and characteristics of design leaders, only in this way we formulate good strategic design for enterprises and organizations, and become an indispensable and important help in today rapidly changing world
SPEECH ENHANCEMENT BASED ON SPARSE THEORY UNDER NOISY ENVIRONMENT
[[abstract]]Recently, the sparse algorithm for sparse enhancement is more and more popular issues. In this paper, we classify the process of the sparse theory to enhance speech signal into two parts, one is for dictionary training part and the other is signal reconstruction part. We focus on the White Gaussian Noise. Clean speech dictionary D is trained by K-SVD algorithm. The orthogonal matching pursuit(OMP) algorithm is used to obtain the sparse coefficients X of clean speech dictionary D. Denoising performance of the experiments shows that our proposed method is superior than other methods in SNR, LLR, SNRseg and PESQ.[[sponsorship]]National Taipei University[[conferencetype]]國際[[conferencedate]]20150718~20150719[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Tokyo, Japa
3D FACE MODEL CONSTRUCTION BASED ON KINECT FOR FACE RECOGNITION
[[abstract]]We propose a simpler and faster method to recognize face. First, we use Kinect
to detect frontal face and get depth image information with face, then we portrayed
face in OpenGL to construct a three-dimensional face model based on the depth
information. The face model also retains texture information of the original face
images, and to create a complete change depth of face. It has a good result of
repairing the distortion in side face. We can get a set face images with different angles
by the method proposed, In recognition part, we use PCA(Principal Component
Analysis) to reduce the dimensions, and classified with SVM(Support Vector
Machine). The experiments show that the side face recognition can have good results.[[sponsorship]]National Taipei University[[conferencetype]]國際[[conferencedate]]20150718~20150719[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Tokyo, Japa
LLM4TS: Two-Stage Fine-Tuning for Time-Series Forecasting with Pre-Trained LLMs
In this work, we leverage pre-trained Large Language Models (LLMs) to enhance
time-series forecasting. Mirroring the growing interest in unifying models for
Natural Language Processing and Computer Vision, we envision creating an
analogous model for long-term time-series forecasting. Due to limited
large-scale time-series data for building robust foundation models, our
approach LLM4TS focuses on leveraging the strengths of pre-trained LLMs. By
combining time-series patching with temporal encoding, we have enhanced the
capability of LLMs to handle time-series data effectively. Inspired by the
supervised fine-tuning in chatbot domains, we prioritize a two-stage
fine-tuning process: first conducting supervised fine-tuning to orient the LLM
towards time-series data, followed by task-specific downstream fine-tuning.
Furthermore, to unlock the flexibility of pre-trained LLMs without extensive
parameter adjustments, we adopt several Parameter-Efficient Fine-Tuning (PEFT)
techniques. Drawing on these innovations, LLM4TS has yielded state-of-the-art
results in long-term forecasting. Our model has also shown exceptional
capabilities as both a robust representation learner and an effective few-shot
learner, thanks to the knowledge transferred from the pre-trained LLM
A Real Time Hand Gesture Recognition System Based on DFT and SVM
[[abstract]]Vision based band gesture recognition provides a more nature and powerful means for human-computer interaction. A fast detection process of hand gesture and an effective feature extraction process are presented. The proposed a hand gesture recognition algorithm comprises four main steps. First use Cam-shift algorithm to track skin color after closing process. Second, in order to extract feature, we use BEA to extract the boundary of the hand. Third, the benefits of Fourier descriptor are invariance to the starting point of the boundary, deformation, and rotation, and therefore transform the starting point of the boundary by Fourier transformation. Finally, outline feature for the nonlinear non-separable type of data was classified by using SVM. Experimental results showed the accuracy is 93.4% in average and demonstrated the feasibility of proposed system.[[incitationindex]]EI[[booktype]]電子版[[booktype]]紙
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