Beyond Economy: Impact of National Cultural Values on Nationwide Broadband Difffusion.

This study examines how the non-conventional factors of national cultural values and government involvement affect the diffusion of broadband Internet technologies in various nations around the world. An innovative element of the study was the examination of the influence patterns at different stages of diffusion, which was measured by the number of years taken to pass a certain threshold level of diffusion. Hierarchical multiple regression analysis was conducted on data from 64 countries that was collected from 1996 to 2006. Prominent national cultural value variables were constructed using survey data from Hofstede and Inglehart’s cross-national surveys. The overall findings of this study indicate that non-conventional factors are significantly correlated with both broadband Internet diffusion level and broadband Internet diffusion speed at each diffusion stage. Furthermore, analysis of broadband Internet diffusion level confirmed that the models explaining nationwide broadband Internet diffusion for developing and developing countries are markedly different. The analysis concludes with implications for further research and public policy in the realm of information and communication technology.Ph.D.CommunicationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/75956/1/sjoo_1.pd

Utilizing ECG Waveform Features as New Biometric Authentication Method

In this study, we are proposing a practical way for human identification based on a new biometric method. The new method is built on the use of the electrocardiogram (ECG) signal waveform features, which are produced from the process of acquiring electrical activities of the heart by using electrodes placed on the body. This process is launched over a period of time by using a recording device to read and store the ECG signal. On the contrary of other biometrics method like voice, fingerprint and iris scan, ECG signal cannot be copied or manipulated. The first operation for our system is to record a portion of 30 seconds out of whole ECG signal of a certain user in order to register it as user template in the system. Then the system will take 7 to 9 seconds in authenticating the template using template matching techniques. 44 subjects‟ raw ECG data were downloaded from Physionet website repository. We used a template matching technique for the authentication process and Linear SVM algorithm for the classification task. The accuracy rate was 97.2% for the authentication process and 98.6% for the classification task; with false acceptance rate 1.21%

The Seven Deadly Sins of Communication Research

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74955/1/j.1460-2466.2008.00382.x.pd

Real-Time Depth-Based Hand Detection and Tracking

This paper illustrates the hand detection and tracking method that operates in real time on depth data. To detect a hand region, we propose the classifier that combines a boosting and a cascade structure. The classifier uses the features of depth-difference at the stage of detection as well as learning. The features of each candidate segment are to be computed by subtracting the averages of depth values of subblocks from the central depth value of the segment. The features are selectively employed according to their discriminating power when constructing the classifier. To predict a hand region in a successive frame, a seed point in the next frame is to be determined. Starting from the seed point, a region growing scheme is applied to obtain a hand region. To determine the central point of a hand, we propose the so-called Depth Adaptive Mean Shift algorithm. DAM-Shift is a variant of CAM-Shift (Bradski, 1998), where the size of the search disk varies according to the depth of a hand. We have evaluated the proposed hand detection and tracking algorithm by comparing it against the existing AdaBoost (Friedman et al., 2000) qualitatively and quantitatively. We have analyzed the tracking accuracy through performance tests in various situations

Insulin Secretion and Incretin Hormone Concentration in Women with Previous Gestational Diabetes Mellitus

BackgroundWe examined the change in the levels of incretin hormone and effects of glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide 1 (GLP-1) on insulin secretion in women with previous gestational diabetes (pGDM).MethodsA 75-g oral glucose tolerance test (OGTT) was conducted on 34 women with pGDM. In addition, 11 women with normal glucose tolerance, matched for age, height and weight, were also tested. The insulin, GIP, GLP-1, and glucagon concentrations were measured, and their anthropometric and biochemical markers were also measured.ResultsAmong 34 women with pGDM, 18 had normal glucose tolerance, 13 had impaired glucose tolerance (IGT) and 1 had diabetes. No significant differences were found in GLP-1 concentration between the pGDM and control group. However, a significantly high level of glucagon was present in the pGDM group at 30 minutes into the OGTT. The GIP concentration was elevated at 30 minutes and 60 minutes in the pGDM group. With the exception of the 30-minute timepoint, women with IGT had significantly high blood glucose from 0 to 120 minutes. However, there was no significant difference in insulin or GLP-1 concentration. The GIP level was significantly high from 0 to 90 minutes in patients diagnosed with IGT.ConclusionGLP-1 secretion does not differ between pGDM patients and normal women. GIP was elevated, but that does not seem to induce in increase in insulin secretion. Therefore, we conclude that other factors such as heredity and environment play important roles in the development of type 2 diabetes