Comments on “A New Model of Two Directional Jc Distributions for Bi 2Sr2CaCu2O 8 Materials”

The authors comments on the claim of Takahashi et al. that the distribution model, utilizing the mixture of Gaussian distributions, for the local critical current density of superconducting materials they proposed is a new idea. The authors points out the the method have been known since 1886.     

On the recent papers by Nagode et al.

The recent work Professor Nagode and colleagues is discussed with respect to the use of mixture Weibull models.     

Tumor size and prognosis in aggressively treated osteosarcoma

PURPOSE: The aim of this retrospective analysis was to investigate the prognostic significance and optimal measures of tumor size in osteosarcoma treated with intensive neoadjuvant chemotherapy. PATIENTS AND METHODS: Initial anterior-posterior (AP) and lateral x-ray films of 128 patients treated within the trials Cooperative Osteosarcoma Study (COSS)-80, -82, and -86, were evaluated for the following three tumor diameters: length, width, and depth. Metastasis-free survival (MFS) analyses were performed in univariate and multivariate models with one, two, and three dimensions of the tumor as absolute or relative measures (tumor length, referred to bone length, plane and volume to body-surface area). RESULTS: Univariate analyses of MFS showed a high prognostic significance of all absolute measures. Relative measures, at best, showed a comparable predictive value. Cox regression analysis indicated the high prognostic significance of absolute tumor volume (ATV; P < .0001) and histologic response (P < .0001). None of 19 patients with an ATV < or = 70 cm3 and only four of 53 with an ATV < or = 150 cm3 relapsed, while in patients with an ATV more than 150 cm3, the relapse rate remained 40% to 60%, irrespective of further increase in volume. CONCLUSION: Initial tumor size is an important and easily obtainable prognostic factor in osteosarcoma and may serve as a basis for risk-adapted therapy. It is best represented by the absolute three-dimensional measure ATV. There is a cut-off point regarding the incidence of metastases at a tumor volume of approximately 150 cm3 as calculated from two-plane x-ray films.     

Mesh-Mon: A multi-radio mesh monitoring and management system

Mesh networks are a potential solution for providing communication infrastructure in an emergency. They can be rapidly deployed by first responders in the wake of a major disaster to augment an existing wireless or wired network. We imagine a mesh node with multiple radios embedded in each emergency vehicle arriving at the site to form the backbone of a mobile wireless mesh. The ability of such a mesh network to monitor itself, diagnose faults and anticipate problems are essential features for its sustainable operation. Typical SNMP-based centralized solutions introduce a single point of failure and are unsuitable for managing such a network. Mesh-Mon is a decentralized monitoring and management system designed for such a mobile, rapidly deployed, unplanned mesh network and works independently of the underlying mesh routing protocol. Mesh-Mon nodes are designed to actively cooperate and use localized algorithms to predict, detect, diagnose and resolve network problems in a scalable manner. Mesh-Mon is independent of the underlying routing protocol and can operate even if the mesh routing protocol completely fails. One novel aspect of our approach is that we employ mobile users of the mesh, running software called Mesh-Mon-Ami, to ferry management packets between physically-disconnected partitions in a delay-tolerant-network manner. The main contributions of this paper are the design, implementation and evaluation of a comprehensive monitoring and management architecture that helps a network administrator proactively identify, diagnose and resolve a range of issues that can occur in a dynamic mesh network. In experiments on Dart-Mesh, our 16-node indoor mesh testbed, we found Mesh-Mon to be effective in quickly diagnosing and resolving a variety of problems with high accuracy, without adding significant management overhead.     

Free-living inferential modeling of blood glucose level using only noninvasive inputs

The goal of this work is to present a causation modeling methodology with the ability to accurately infer blood glucose levels using a large set of highly correlated noninvasive input variables over an extended period of time. These models can provide insight to improve glucose monitoring, and glucose regulation through advanced model-based control technologies. The efficacy of this approach is demonstrated using real data from a type 2 diabetic (T2D) subject collected under free-living conditions over a period of 25 consecutive days. The model was identified and tested using eleven variables that included three food variables as well as several activity and stress variables. The model was trained using 20 days of data and validated using 5 days of data. This gave a fitted correlation coefficient of 0.70 and an average absolute error (AAE) (i.e., the average of the absolute values for the measured glucose concentration minus modeled glucose concentration) of 13.3 mg/dL for the validation data. This AAE result was significantly better than the subject’s personal glucose meter AAE of 15.3 mg/dL for replicated measurements.     

The beta exponential distribution

The exponential distribution is perhaps the most widely applied statistical distribution for problems in reliability. In this note, we introduce a generalization—referred to as the beta exponential distribution—generated from the logit of a beta random variable. We provide a comprehensive treatment of the mathematical properties of the beta exponential distribution. We derive expressions for the moment generating function, characteristic function, the first four moments, variance, skewness, kurtosis, mean deviation about the mean, mean deviation about the median, Rényi entropy, Shannon entropy, the distribution of sums and ratios, and the asymptotic distribution of the extreme order statistics. We also discuss simulation issues, estimation by the methods of moments and maximum likelihood and provide an expression for the Fisher information matrix. We hope that this generalization will attract wider applicability in reliability.     

Hide-n-Sense: Preserving Privacy Efficiently in Wireless mHealth

As healthcare in many countries faces an aging population and rising costs, mobile sensing technologies promise a new opportunity. Using mobile health (mHealth) sensing, which uses medical sensors to collect data about the patients, and mobile phones to act as a gateway between sensors and electronic health record systems, caregivers can continuously monitor the patients and deliver better care. Furthermore, individuals can become better engaged in monitoring and managing their own health. Although some work on mHealth sensing has addressed security, achieving strong privacy for low-power sensors remains a challenge. We make three contributions. First, we propose an mHealth sensing protocol that provides strong security and privacy properties at the link layer, with low energy overhead, suitable for low-power sensors. The protocol uses three novel techniques: adaptive security, to dynamically modify transmission overhead; MAC striping, to make forgery difficult even for small-sized Message Authentication Codes; and asymmetric resource requirements, in recognition of the limited resources in tiny mHealth sensors. Second, we demonstrate its feasibility by implementing a prototype on a Chronos wrist device, and evaluating it experimentally. Third, we provide a security, privacy, and energy analysis of our system.     

On the /spl eta/-/spl kappa/ distribution

For original paper by Yacoub et al., see IEEE Trans. Broadcasting., vol.51, p.504-11 (2005 December).     

File-access characteristics of parallel scientific workloads

Phenomenal improvements in the computational performance of multiprocessors have not been matched by comparable gains in I/O system performance. This imbalance has resulted in I/O becoming a significant bottleneck for many scientific applications. One key to overcoming this bottleneck is improving the performance of multiprocessor file systems. The design of a high-performance multiprocessor file system requires a comprehensive understanding of the expected workload. Unfortunately, until recently, no general workload studies of multiprocessor file systems have been conducted. The goal of the CHARISMA project was to remedy this problem by characterizing the behavior of several production workloads, on different machines, at the level of individual reads and writes. The first set of results from the CHARISMA project describe the workloads observed on an Intel iPSC/860 and a Thinking Machines CM-5. This paper is intended to compare and contrast these two workloads for an understanding of their essential similarities and differences, isolating common trends and platform-dependent variances. Using this comparison, we are able to gain more insight into the general principles that should guide multiprocessor file-system design