Cai K.-Y.,Beihang University |
Cao P.,CAS Beijing Institute of Applied Physics And Computational Mathematics |
Dong Z.,Data Applied |
Liu K.,CAS Beijing Institute of Applied Physics And Computational Mathematics
Computers and Mathematics with Applications | Year: 2010
Software reliability testing is concerned with the quantitative relationship between software testing and software reliability. Our previous work develops a mathematically rigorous modeling framework for software reliability testing. However the modeling framework is confined to the case of perfect debugging, where detected defects are removed without introducing new defects. In this paper the modeling framework is extended to the case of imperfect debugging and two models are proposed. In the first model it is assumed that debugging is imperfect and may make the number of remaining defects reduce by one, remain intact, or increase by one. In the second model it is assumed that when the number of remaining defects reaches the upper bound, the probability that the number of remaining defects is increased by one by debugging is zero. The expected behaviors of the cumulative number of observed failures and the number of remaining defects in the first model show that the software testing process may induce a linear or nonlinear dynamic system, depending on the relationship between the probability of debugging introducing a new defect and that of debugging removing a detected defect. The second-order behaviors of the first model also show that in the case of imperfect debugging, although there may be unbiased estimator for the initial number of defects remaining in the software under test, the cumulative number of observed failures and the current number of remaining defects are not sufficient for precisely estimating the initial number of remaining defects. This is because the variance of the unbiased estimator approaches a non-zero constant as the software testing process proceeds. This may be treated as an intrinsic principle of uncertainty for software testing. The expected behaviors of the cumulative number of observed failures and the number of remaining defects in the second model show that the software testing process may induce a nonlinear dynamic system. However theoretical analysis and simulation results show that, if defects are more often removed from than introduced into the software under test, the expected behaviors of the two models tend to coincide with each other as the upper bound of the number of remaining defects approaches infinity. © 2010 Elsevier Ltd. All rights reserved.
News Article | February 21, 2017
Industry Participants Seek a New Level of Operational Control According to Applied Market Data Managers at commercial vehicle fleets understand the phrase ‘Be Careful What You Wish For.’ Striving to compete effectively in an industry sector with increasing customer expectations, rising fuel costs and intense competition, fleets have been collecting and analyzing data from engine and vehicle sensors and electronic modules and combining it with inputs from cab-mounted electronics, expecting that by measuring vehicle and driver performance, improved operating efficiency would follow – and it has. This information has been used to increase fleet performance, primarily in the areas of fuel costs, driver performance, and asset utilization and to meet the increasingly stringent shipper and consignee demands for tight gate-in/gate-out pick-up and delivery windows. But as the level of vehicle digitization and data collection continues, fleet managers are finding themselves data-rich and analysis-poor. They’ve entered a new phase, seeking to find better ways to collate and manage the information contained in the data that onboard sensors and modules capture. Increasingly, fleet decision makers are turning to analytics programs to merge, blend, analyze and visualize their trove of data points in ways that will help managers identify trends, risks and opportunities and take steps to optimize performance and improve operating results as part of their daily operational routine. Because commercial fleets acquire data from a range of sources including OEM vehicle sensors, aftermarket devices, fueling stations, and maintenance terminals, issues related to data quality (scrubbing) and data integration (blending) will need to be defined and addressed early in any analytics program acquisition process. This requirement will become increasingly important as new initiatives such as the ITS vehicle-to-vehicle communication program moves closer to full implementation, adding data from disparate roadway sensors to the mix. An area with significant promise involves the structured analysis of engine and vehicle data for enhanced preventive maintenance using predictive analytics, a powerful decision support tool being developed and implemented by several asset-based companies, most notably GE. Because of the wide spectrum of data available to fleets, defining the specific operational questions that need to be answered will be a key input to IT teams and system integrators. Creating visualizations and dashboards that address the functional demands of decision makers is a key step toward realizing the value of analytics and is the best way to avoid ‘data whiteout.’ As commercial vehicle fleets adopt analytics capabilities, the operational envelope will tighten for all commercial carriers. Many fleets not actively pursuing or considering the use of analytics will find themselves seeking a strategy to respond to this dynamic in order to stay competitive. The findings of a recent survey are detailed in a new report prepared by Applied Market Data. Fleet Management Analytics: Solutions, Strategies and Opportunities has been researched and written to be of optimal value to over-the-road logistics market sector participants. It consists of in-depth analyses, descriptions and evaluations of technology selection factors and implementation issues, opportunity assessments, business factors and market sector profiles. More information is available at www.appliedmarketdata.com Applied Market Data is a transportation and logistics technology consulting firm focused on the areas of technology strategy, product commercialization, venture development, and market research. We assist technology companies in achieving their business objectives through the creation of detailed development strategies, product commercialization programs, and comprehensive market and technology research and analysis. Our market research publications are designed, researched and written to provide timely and insightful information and data on focused market segments, with the aim of providing market participants with the essential knowledge to refine and execute their marketing plans and attain their financial targets.
Carlton R.,Global Health Economics and Outcomes Research |
Lunacsek O.,Data Applied |
Regan T.,Xcenda |
American Health and Drug Benefits | Year: 2014
Background: Excessive daytime sleepiness affects nearly 20% of the general population and is associated with many medical conditions, including shift work disorder (SWD), obstructive sleep apnea (OSA), and narcolepsy. Excessive sleepiness imposes a significant clinical, quality-of-life, safety, and economic burden on society.Objective: To compare healthcare costs for patients receiving initial therapy with armodafinil or with modafinil for the treatment of excessive sleepiness associated with OSA, SWD, or narcolepsy.Methods: A retrospective cohort analysis of medical and pharmacy claims was conducted using the IMS LifeLink Health Plan Claims Database. Patients aged ≥18 years who had a pharmacy claim for armodafinil or for modafinil between June 1, 2009, and February 28, 2012, and had 6 months of continuous eligibility before the index prescription date, as well as International Classification of Diseases, Ninth Revision diagnosis for either OSA (327.23), SWD (327.36), or narcolepsy (347.0×) were included i n the study. Patients were placed into 1 of 2 treatment cohorts based on their index prescription and followed for 1 month minimum and 34 months maximum. The annualized all-cause costs were calculated by multiplying the average per-month medical and pharmacy costs for each patient by 12 months. The daily average consumption (DACON) for armodafinil or for modafinil was calculated by dividing the total units dispensed of either drug by the prescription days supply.Results: A total of 5693 patients receiving armodafinil and 9212 patients receiving modafinil were included in this study. A lower DACON was observed for armodafinil (1.04) compared with modafinil (1.47). The postindex mean medical costs were significantly lower for the armodafinil cohort compared with the modafinil cohort after adjusting for baseline differences ($11,363 vs $13,775, respectively; P = .005). The mean monthly drug-specific pharmacy costs were lower for the armodafinil cohort compared with the modafinil cohort ($166 vs $326, respective ly; P <.001). In addition, lower total healthcare costs were observed for the armodafinil cohort compared with the modafinil cohort after correcting for baseline differences ($18,309 vs $23,530, respectively; P <.001).Conclusion: As shown in this analysis, armodafinil may have real-world DACON advantages and may be associated with lower overall healthcare costs compared with modafinil. © 2014 Engage Healthcare Communications, LLC. All rights reserved.
News Article | February 24, 2017
Safety and Tactile Features Address the Needs of Older and Compromised Patients According to Applied Market Data The aging global population and special-needs patients are two patient groups that represent a growing healthcare segment. Recognizing this, a small but growing number of pharmaceutical sector participants and their product development partners have created injection devices that address several of the feature and functional needs of at-risk patients. The administration of injectables is moving increasingly from practitioner offices and healthcare facilities to patient homes. Decisions regarding as-supplied packaging that were once considered boilerplate have moved to the early stages of the development process. Drug developers and their device partners are increasing their emphasis on device features and functionality, attempting to create injectable products that are more user-friendly while promoting patient adherence and safety. These features address a wide spectrum of device attributes, including form factor, device-patient interaction, security and safety, dosing, activation, off-device communication, and drug formulation factors. By creating devices that address patient limitations and family concerns, this class of devices is tapping into a growing theme among the aging and their loved ones. Pre-event audible patient instructions and post-event feedback provide a measure of assurance that the medication was indeed injected properly. Wireless connectivity allows caregivers to remotely monitor dosing and event performance. Dose reminders and failsafe injection event activation increase patient confidence in the self-administration process. Small form factor injectors and ergonomic device designs are aimed at expanding the number of patients with compromised dexterity that can self-medicate. For the remainder of the decade, pipeline drugs and shifting demographics will drive sector growth as an aging population of baby boomers (23% of U.S. population) provides stimulus for industry demand. Currently, the over 65 segment accounts for approximately 13% of the U.S. population, with an estimated 40% of total healthcare expenditures, but by 2020, this segment is expected to grow to 17% of the population. Applied Market Data has researched this evolving market and incorporated survey findings in a new report. Injection Devices for At-Risk Populations is a comprehensive assessment of this emerging drug delivery segment. As the drug delivery market transitions from standard protocols to a patient needs-based approach in lockstep with personalized medicine, we expect competition in this segment to intensify. More information is available at www.appliedmarketdata.com Applied Market Data is a management consulting firm focused on the areas of technology strategy, product commercialization, venture development, and market research. We assist technology companies in achieving their business objectives through the creation of detailed development strategies, product commercialization programs, and comprehensive market and technology research and analysis. Our market research publications are designed, researched and written to provide timely and insightful information and data on focused market segments, with the aim of providing market participants with the essential knowledge to refine and execute their marketing plans and attain their financial targets.
Rajbhandary S.,Data Applied |
Basu K.,Data Applied
Health Policy | Year: 2010
Objective: This paper investigates the relationship between the working conditions and illness- and injury-related absenteeism of full-time Registered Nurses (RNs) and Licensed Practical Nurses (LPNs). Method: We used 2005 National Survey of the Work and Health of Nurses, which was designed to be representative of nurses employed in nursing in Canada in the fall of 2005. We estimated Negative Binomial regression models separately for RNs and LPNs with health related absenteeism as the dependent variable. The regressors include working conditions, work settings, and shift type/length along with socio-demographic variables. Results: Depression is a significant determinant of absenteeism for both RNs and LPNs. However, workload and lack of respect are significant determinant of absenteeism for LPNs but not for RNs. Both RNs and LPNs working in other setting (physician offices, private nursing educations, educational institutions, governments and associations) will have less absenteeism than those working in hospitals. For LPNs, those working in long-term facility will also have less absenteeism than those working in hospitals. The length and type of shift also has significant effect on absenteeism. Discussion: Improving working conditions with a resulting reduction in absenteeism might be an economic way to increase the labour supply of nurses without increasing new admissions or new recruits. © 2010.
Data Applied | Date: 2016-04-05
Computer software, namely, software development tools for the creation of mobile internet applications and client interfaces; Downloadable mobile applications for creating sales and marketing presentations.
Data Applied | Date: 2012-11-01
Computer application software for mobile phones, namely, software for analyzing data; Computer hardware and software systems for analyzing data.
Data Applied | Date: 2015-02-17
News Article | February 21, 2017
NASHUA, N.H., Feb. 21, 2017 /PRNewswire/ -- Managers at commercial vehicle fleets understand the phrase 'Be Careful What You Wish For.' Striving to compete effectively in an industry sector with increasing customer expectations, rising fuel costs and intense competition, fleets have been...