More intrinsic parameters should be used in assessing degeneration of articular cartilage with quantitative ultrasound

During the last decade, the quantitative ultrasound technique has been widely employed as a versatile modality to investigate a thin but crucial tissue layer – the articular cartilage. Previous studies provide information about the morphology and mechanical and acoustic properties of the tissue derived from ultrasound measurements and correlate them with cartilage degeneration. In a previous issue of Arthritis Research & Therapy, Kuroki and colleagues presented a study about the relationship between International Cartilage Repair Society grading and ultrasound echo magnitude, duration, and interval in human knee cartilage. We think indirect measurements of the intrinsic physical characteristics of cartilage, as reported in this study, should be interpreted more carefully as they can be affected by many experimental and physical factors. In this editorial, we offer our opinion that more intrinsic material parameters should be selected for the assessment of degeneration states of cartilage using quantitative ultrasound

A Practical Case Study of the Interactive TV Service as a Time-Critical Product

In this paper, we conducted a case study of time-critical goods - NG goods. We expected the study to integrate the field of information management and the TV broadcasting field, thereby creating a new wave of potential for the information management field after e-commerce. We suggest two perspectives germane to industry development: the development of the whole industry, and, the operation of the individual companie

Targeted online password guessing:an underestimated threat

While trawling online/offline password guessing has been intensively studied, only a few studies have examined targeted online guessing, where an attacker guesses a specific victim's password for a service, by exploiting the victim's personal information such as one sister password leaked from her another account and some personally identifiable information (PII). A key challenge for targeted online guessing is to choose the most effective password candidates, while the number of guess attempts allowed by a server's lockout or throttling mechanisms is typically very small. We propose TarGuess, a framework that systematically characterizes typical targeted guessing scenarios with seven sound mathematical models, each of which is based on varied kinds of data available to an attacker. These models allow us to design novel and efficient guessing algorithms. Extensive experiments on 10 large real-world password datasets show the effectiveness of TarGuess. Particularly, TarGuess I~IV capture the four most representative scenarios and within 100 guesses: (1) TarGuess-I outperforms its foremost counterpart by 142% against security-savvy users and by 46% against normal users; (2) TarGuess-II outperforms its foremost counterpart by 169% on security-savvy users and by 72% against normal users; and (3) Both TarGuess-III and IV gain success rates over 73% against normal users and over 32% against security-savvy users. TarGuess-III and IV, for the first time, address the issue of cross-site online guessing when given the victim's one sister password and some PII