Study of Cost Overrun and Delays of Department of Defense (DoD)\u27s Space Acquisition Program

Defense and Aerospace Systems Acquisition projects, just like any other Large-Scale Complex Engineered Systems (LSCES) experience delays and cost overrun during the acquisition process. Cost overrun and delays in LSCES are due, in part, to high complexity, size of the project, involvement of various stakeholders, organizations, political disruptions, changes in requirements and scope. These uncertainties, due to the exogenous factors, have cost the federal government billions of dollars and delays in completion of the programs. Cost estimation of federal programs is usually based on previous generations of systems produced and almost all the time the costs are underestimated. Underestimation of the cost of the programs is an endogenous factor, which results in cost overrun for any program, the behavior of the cost escalation is pre-forecasted to be normally distributed, but due to the cost overrun, the cost escalation curve may be skewed. In this paper, the authors will be studying the cost escalation and time delays of the Advanced Extremely High Frequency (AEHF), a DoD\u27s space acquisition program. The distribution of the cost and time can aid in understanding the effects of endogenous factors influencing the cost overrun and the effect of change in requirements during the acquisition process. This data will serve as a foundation for further research to create a framework, which will be used, in better forecasting of the cost of the acquisition of the programs

An Agent-Based Approach to Artificial Stock Market Modeling

Consumer stock markets have long been a target of modeling efforts for the economic gains anticipatorily enabled by well-performing models. Aimed at identifying strategies capable of achieving desired returns, many modeling approaches have attempted to capture the innumerable and intricate complexities present within these adaptive socio-technical systems. Decreasingly constrained by available computation power, contemporary models have grown in sophistication to include several of the features present in de facto market systems. However, these models require extensive effort to dictate the variety of states, behaviors, and adaptations that entities of the system may exhibit. Mandating the development of complex formulas and an incredible number of situational considerations, traditional approaches to stock market modeling are intensive to architect and applicable to a limited range of scenarios. Further, these models commonly fail to incorporate external influences on the actions of investing parties. Employing an agent-based approach, independent and externally influenced entities are modeled to simulate market activity. Under the jurisdiction of assigned simple rules, agents of the system interact in complex and emergent ways without requiring macroscopic guiding equations. Successive trails are conducted using varying initialization values, enabling the determination of robust investment strategies performing well across a range of market scenarios

Analysis of Autonomous Unmanned Aerial Systems based on Operational Scenarios using Value Modelling

In recent years, the use of UAS (Unmanned Aerial Systems) has moved beyond the realm of military operations and has made its way into the hands of consumers and commercial industries. Although the applications of UAS in commercial industries are virtually endless, there are many issues regarding their operations that need to be considered before these valuable pieces of equipment are allowed for widespread civil use. Currently, UAS operations in the public domain are guided and controlled by the FAA Part 107 rules after overwhelming public pressure caused by the earlier 333 exemption. In order to approach such larger issues, this paper will exploit the use of value models, which will help to quantify how the different environmental and operational scenarios play a role in UAS operations based on the task being performed. The primary aim of this research is to use the attributes from key factors of the UAS such as the autonomy levels (AL) and technology readiness levels (TRL) along with their operating scenario factors, such as the environmental complexity and task complexity, based on the operating environment in which a UAS performs its task. To analyze the performance of autonomous UAS in different operational scenarios, the physical characteristics and class of a UAS may be linked to its AL and TRL. Using these parameters, the risks faced by the UAS in a particular mission are quantified and a value is assigned to the abstract entities involved. Although there are many critical questions with respect to good practices to be followed by UAS operators in order to obtain valuable data and information on the structures being scanned and monitored, there are many other challenges with regards to large scale operations of UAS such as the ethical, legal and societal implications that have to be addressed

Rethinking the Design of Low-Cost Point-of-Care Diagnostic Devices

Reducing the global diseases burden requires effective diagnosis and treatment. In the developing world, accurate diagnosis can be the most expensive and time-consuming aspect of health care. Healthcare cost can, however, be reduced by use of affordable rapid diagnostic tests (RDTs). In the developed world, low-cost RDTs are being developed in many research laboratories; however, they are not being equally adopted in the developing countries. This disconnect points to a gap in the design philosophy, where parameterization of design variables ignores the most critical component of the system, the point-of-use stakeholders (e.g., doctors, nurses and patients). Herein, we demonstrated that a general focus on reducing cost (i.e., “low-cost”), rather than efficiency and reliability is misguided by the assumption that poverty reduces the value individuals place on their well-being. A case study of clinicians in Kenya showed that “zero-cost” is a low-weight parameter for point-of-use stakeholders, while reliability and standardization are crucial. We therefore argue that a user-driven, value-addition systems-engineering approach is needed for the design of RDTs to enhance adoption and translation into the field

Comparison of demographic and clinical characteristics between pulmonary and extra-pulmonary tuberculosis patients in Kiambu County, 2012-2015

Background: Tuberculosis (TB) continues to be a public health challenge globally. The most common organ to be involved is the lung although it can affect any organ in the body. The diagnosis of extra-pulmonary TB (EPTB) has faced many challenges mainly due to inadequate expertise to diagnose or lack of equipment for diagnosis.Objective: To compare the demographic and clinical characteristics between pulmonary and extrapulmonary tuberculosis in Kiambu CountyDesign: Retrospective cross-sectional studySetting: Kiambu County, KenyaSubjects: Tuberculosis patients notified in TIBU surveillance systemResults: Of the 15, 833 patients analyzed, 2,704 (17%) had extra-pulmonary tuberculosis. Male to female ratio was 1:1.7 in PTB and 1:1.3 in EPTB patients. There was declining trend of TB cases notified over the years for both PTB and EPTB. Pleural TB accounted for 38% with TB lymphadenitis accounting for 14% of the EPTB subtypes. TB-HIV co-infection was higher among EPTB (36%) compared to PTB (30%). The treatment success rate was 85% and 86% among PTB and EPTB cases respectively. The mortality was 10% among EPTB and 5% in PTB cases. The 5-14 age category were more likely to developing EPTB compared to PTB (AOR 4.67 95% CI (1.5-13.99). Kabete zone was most affected with EPTB (AOR 2.11(1.19-2.74) while a protective factor was observed among the HIV positive clients (AOR 0.58 (0.43 - 0.78)Conclusion: There was a general decline in cases for both EPTB and PTB. However, the age category most affected was 5-14 years. The co-infectivity rate was higher among the EPTB patients compared to the PTB patients. High index of suspicion and appropriate diagnostic tools are needed in evaluation particularly in EPTB which will assist in early management of the patients. ART uptake could play a big role in protecting HIV positive clients from getting EPTB

Hunger, waiting time and transport costs: Time to confront challenges to ART adherence in Africa

International audienceAdherence levels in Africa have been found to be better than those in the US. However around one out of four ART users fail to achieve optimal adherence, risking drug resistance and negative treatment outcomes. A high demand for 2nd line treatments (currently ten times more expensive than 1st line ART) undermines the sustainability of African ART programs. There is an urgent need to identify context-specific constraints to adherence and implement interventions to address them. We used rapid appraisals (involving mainly qualitative methods) to find out why and when people do not adhere to ART in Uganda, Tanzania and Botswana. Multidisciplinary teams of researchers and local health professionals conducted the studies, involving a total of 54 semi-structured interviews with health workers, 73 semi-structured interviews with ART users and other key informants, 34 focus group discussions, and 218 exit interviews with ART users. All the facilities studied in Botswana, Tanzania and Uganda provide ARVs free of charge, but ART users report other related costs (e.g. transport expenditures, registration and user fees at the private health facilities, and lost wages due to long waiting times) as main obstacles to optimal adherence. Side effects and hunger in the initial treatment phase are an added concern. We further found that ART users find it hard to take their drugs when they are among people to whom they have not disclosed their HIV status, such as co-workers and friends. The research teams recommend that (i) health care workers inform patients better about adverse effects; (ii) ART programmes provide transport and food support to patients who are too poor to pay; (iii) recurrent costs to users be reduced by providing three-months, rather than the one-month refills once optimal adherence levels have been achieved; and (iv) pharmacists play an important role in this follow-up care

The inverted cup device for blood transfer on malaria RDTs: ease of use, acceptability and safety in routine use by health workers in Nigeria

Abstract Background Malaria rapid diagnostic tests (RDTs) are becoming widely adopted for case management at community level. However, reports and anecdotal observations indicate that the blood transfer step poses a significant challenge to many users. This study sought to evaluate the inverted cup device in the hands of health workers in everyday clinical practice, in comparison with the plastic pipette, and to determine the volume accuracy of the device made of a lower-cost plastic. Methods The volume accuracy of inverted cup devices made of two plastics, PMMA and SBC, was compared by transferring blood 150 times onto filter paper and comparing the blood spot areas with those produced by 20 reference transfers with a calibrated micropipette. The ease of use, safety and acceptability of the inverted cup device and the pipette were evaluated by 50 health workers in Nigeria. Observations were recorded on pre-designed questionnaires, by the health workers themselves and by trained observers. Focus group discussions were also conducted. Results The volume accuracy assessment showed that the device made from the low-cost material (SBC) delivered a more accurate volume (mean 5.4 μL, SD 0.48 μL, range 4.5–7.0 μL) than the PMMA device (mean 5.9 μL, SD 0.48 μL, range 4.9–7.2 μL). The observational evaluation demonstrated that the inverted cup device performed better than the pipette in all aspects, e.g. higher proportions of health workers achieved successful blood collection (96%, vs. 66%), transfer of the required blood volume (90%, vs. 58%), and blood deposit without any loss (95%, vs. 50%). Majority of health workers also considered it’ very easy’ to use (81%),’very appropriate’ for everyday use (78%), and 50% of them reported that it was their preferred BTD. Conclusions The good volume accuracy and high acceptability of the inverted cup device shown in this study, along with observed ease of use and safety in hands of health workers, further strengthens prior findings which demonstrated its higher accuracy as compared with other BTDs in a laboratory setting. Altogether, these studies suggest that the inverted cup device should replace other types of devices for use in day-to-day malaria diagnosis with RDTs.https://deepblue.lib.umich.edu/bitstream/2027.42/140763/1/12936_2018_Article_2173.pd

Development and validation of a diagnostic aid for convulsive epilepsy in sub-Saharan Africa: a retrospective case-control study

Background: Identification of convulsive epilepsy in sub-Saharan Africa relies on access to resources that are often unavailable. Infrastructure and resource requirements can further complicate case verification. Using machine-learning techniques, we have developed and tested a region-specific questionnaire panel and predictive model to identify people who have had a convulsive seizure. These findings have been implemented into a free app for health-care workers in Kenya, Uganda, Ghana, Tanzania, and South Africa. Methods: In this retrospective case-control study, we used data from the Studies of the Epidemiology of Epilepsy in Demographic Sites in Kenya, Uganda, Ghana, Tanzania, and South Africa. We randomly split these individuals using a 7:3 ratio into a training dataset and a validation dataset. We used information gain and correlation-based feature selection to identify eight binary features to predict convulsive seizures. We then assessed several machine-learning algorithms to create a multivariate prediction model. We validated the best-performing model with the internal dataset and a prospectively collected external-validation dataset. We additionally evaluated a leave-one-site-out model (LOSO), in which the model was trained on data from all sites except one that, in turn, formed the validation dataset. We used these features to develop a questionnaire-based predictive panel that we implemented into a multilingual app (the Epilepsy Diagnostic Companion) for health-care workers in each geographical region. Findings: We analysed epilepsy-specific data from 4097 people, of whom 1985 (48·5%) had convulsive epilepsy, and 2112 were controls. From 170 clinical variables, we initially identified 20 candidate predictor features. Eight features were removed, six because of negligible information gain and two following review by a panel of qualified neurologists. Correlation-based feature selection identified eight variables that demonstrated predictive value; all were associated with an increased risk of an epileptic convulsion except one. The logistic regression, support vector, and naive Bayes models performed similarly, outperforming the decision-tree model. We chose the logistic regression model for its interpretability and implementability. The area under the receiver operator curve (AUC) was 0·92 (95% CI 0·91–0·94, sensitivity 85·0%, specificity 93·7%) in the internal-validation dataset and 0·95 (0·92–0·98, sensitivity 97·5%, specificity 82·4%) in the external-validation dataset. Similar results were observed for the LOSO model (AUC 0·94, 0·93–0·96, sensitivity 88·2%, specificity 95·3%). Interpretation: On the basis of these findings, we developed the Epilepsy Diagnostic Companion as a predictive model and app offering a validated culture-specific and region-specific solution to confirm the diagnosis of a convulsive epileptic seizure in people with suspected epilepsy. The questionnaire panel is simple and accessible for health-care workers without specialist knowledge to administer. This tool can be iteratively updated and could lead to earlier, more accurate diagnosis of seizures and improve care for people with epilepsy

Lessons Learned Developing a Diagnostic Tool for HIV-Associated Dementia Feasible to Implement in Resource-Limited Settings: Pilot Testing in Kenya

Objective: To conduct a preliminary evaluation of the utility and reliability of a diagnostic tool for HIV-associated dementia (HAD) for use by primary health care workers (HCW) which would be feasible to implement in resource-limited settings. Background: In resource-limited settings, HAD is an indication for anti-retroviral therapy regardless of CD4 T-cell count. Anti-retroviral therapy, the treatment for HAD, is now increasingly available in resource-limited settings. Nonetheless, HAD remains under-diagnosed likely because of limited clinical expertise and availability of diagnostic tests. Thus, a simple diagnostic tool which is practical to implement in resource-limited settings is an urgent need. Methods: A convenience sample of 30 HIV-infected outpatients was enrolled in Western Kenya. We assessed the sensitivity and specificity of a diagnostic tool for HAD as administered by a primary HCW. This was compared to an expert clinical assessment which included examination by a physician, neuropsychological testing, and in selected cases, brain imaging. Agreement between HCW and an expert examiner on certain tool components was measured using Kappa statistic. Results: The sample was 57 % male, mean age was 38.6 years, mean CD4 T-cell count was 323 cells/mL, and 54 % had less than a secondary school education. Six (20%) of the subjects were diagnosed with HAD by expert clinical assessment. The diagnostic tool was 63 % sensitive and 67 % specific for HAD. Agreement between HCW and expert examiners was poor for many individual items of the diagnostic tool (K =.03–.65). This diagnostic tool had moderate sensitivity and specificity fo