Estimating and reducing the memory requirements of signal processing codes for embedded systems

Most embedded systems have limited amount of memory. In contrast, the memory requirements of the digital signal processing (DSP) and video processing codes (in nested loops, in particular) running on embedded systems is significant. This paper addresses the problem of estimating and reducing the amount of memory needed for transfers of data in embedded systems. First, the problem of estimating the region associated with a statement or the set of elements referenced by a statement during the execution of nested loops is analyzed. For a fixed execution ordering, a quantitative analysis of the number of elements referenced is presented; exact expressions for uniformly generated references and a close upper and lower bound for nonuniformly generated references are derived. Second, in addition to presenting an algorithm that computes the total memory required, this paper also discusses the effect of transformations (that change the execution ordering) on the lifetimes of array variables, i.e., the time between the first and last accesses to a given array location. The term maximum window size is introduced, and quantitative expressions are derived to compute the maximum window size. A detailed analysis of the effect of unimodular transformations on data locality, including the calculation of the maximum window size, is presented.     

A case-mix classification system for medical rehabilitation

Dissatisfaction with Medicare's current system of paying for rehabilitation care has led to proposals for a rehabilitation prospective payment system, but first a classification system for rehabilitation patients must be created. Data for 36,980 patients admitted to and discharged from 125 rehabilitation facilities between January 1, 1990, and April 19, 1991, were provided by the Uniform Data System for Medical Rehabilitation. Classification rules were formed using clinical judgment and a recursive partitioning algorithm. The Functional Independence Measure version of the Function Related Groups (FIM-FRGs) uses four predictor variables: diagnosis leading to disability, admission scores for motor and cognitive functional status subscales as measured by the Functional Independence Measure, and patient age. The system contains 53 FRGs and explains 31.3% of the variance in the natural logarithm length of stay for patients in a validation sample. The FIM-FRG classification system is conceptually simple and stable when tested on a validation sample. The classification system contains a manageable number of groups, and may represent a solution to the problem of classifying medical rehabilitation patients for payment, facility planning, and research on the outcomes, quality, and cost of rehabilitation.     

Vitek system antimicrobial susceptibility testing of O1, O139, and non-O1 Vibrio cholerae

Vibrio cholerae causes epidemic diarrhea throughout the world. Fluid replacement is the primary therapy for cholera; however, high mortality rates often necessitate the use of antibiotics. V. cholerae, like most bacteria, has developed resistance to some antibiotics. In the early 1990s a new serotype strain, Bengal 0139, began a new wave of cholera epidemics. Bengal isolates showed unique trends in antimicrobial resistance. Many clinical laboratories use automated antibiotic susceptibility testing for V. cholerae. It is important to know if automated susceptibility test results for V. cholerae coincide with reported trends in antibiotic susceptibility. In the present study, we used the Vitek automated susceptibility system to determine the susceptibilities of 79 V. cholerae O1 isolates, 100 O139 isolates, and 112 non-O1 isolates. Vitek susceptibilities for V. cholerae showed a good correlation with preestablished epidemiological data. Although the new O139 serogroup showed a trend of increased resistance to trimethoprim-sulfamethoxazole and nitrofurantoin, it was more susceptible to ampicillin than previous serogroup O1 and non-O1 strains. Regardless of serogroup, > or = 98% of the V. cholerae isolates tested were susceptible to most antibiotics tested by us. It is important to continue susceptibility testing of all new isolates of V. cholerae because of emerging resistant strains. However, V. cholerae remains susceptible to most of the available antibiotics.     

Pharmacokinetics of hyperimmune anti-human immunodeficiency virus immunoglobulin in persons with AIDS

Hyperimmune anti-human immunodeficiency virus immunoglobulin (HIVIG) is an intravenous immunoglobulin prepared from HIV-infected asymptomatic donors with a CD4 cell count greater than 400 cells/microl and a high titer of antibody to HIV-1 p24 protein. Twelve persons with AIDS received four doses of HMG (two at 50 mg/kg of body weight and then two at 200 mg/kg) every 28 days. Pharmacokinetics were evaluated by measurement of anti-p24 antibody. HIVIG was well tolerated, and all participants completed the study. Three subjects who were not receiving Pneumocystis carinii pneumonia (PCP) prophylaxis developed PCP. The mean value for HIVIG clearance was 3.02 ml/kg/day at 50 mg/kg and 3.65 ml/kg/day at 200 mg/kg (P = 0.027); the mean trough antibody titers (reciprocal units) were 1,442 and 4,428, respectively. This study indicates that high titers of anti-p24 antibody can be maintained with a monthly administration schedule of HIVIG and that short-term safety is acceptable. Comparisons to evaluate the therapeutic potential of HIVIG are justified.     

Reliability models for computer systems: An overview including dataflow graphs

The reliability of a system is the probability that the system will perform its intended mission under given conditions. This paper provides an overview of the approaches to reliability modelling and identifies their strengths and weaknesses. The models discussed include structure models, simple stochastic models and decomposable stochastic models. Ignoring time-dependence, structure models give reliability as a function of the topological structure of the system. Simple stochastic models make direct use of the properties of underlying stochastic processes, while decomposable models consider more complex systems and analyse them through subsystems. Petri nets and dataflow graphs facilitate the analysis of complex systems by providing a convenient framework for reliability analysis.