Women at risk: Gender inequality and maternal health.

PubMed

Banda, Pamela C; Odimegwu, Clifford O; Ntoimo, Lorretta F C; Muchiri, Evans

2017-04-01

Gender inequality has been documented as a key driver of negative health outcomes, especially among women. However, studies have not clearly examined the role of gender inequality in maternal health in an African setting. Therefore, the authors of this study examined the role of gender inequality, indicated by lack of female autonomy, in exposing women to maternal health risk. Data were obtained from the 2007 Zambia Demographic and Health Survey on a weighted sample of 3,906 married or partnered women aged 15-49 years. Multivariable analyses revealed that low autonomy in household decision power was associated with maternal health risk (Odds Ratio (OR) = 1.52, p < .001). Autonomy interacted with household wealth showed that respondents who were in the wealthier households and had low autonomy in household decision power (OR = 2.03, p < .05) were more likely to be exposed to maternal health risk than their counterparts who had more autonomy. Efforts to lower women's exposure to maternal mortality and morbidity in Zambia should involve interventions to alter prevailing gender norms that limit women's active participation in decisions about their own health during pregnancy and delivery.

Technical and scale efficiency in the delivery of child health services in Zambia: results from data envelopment analysis.

PubMed

Achoki, Tom; Hovels, Anke; Masiye, Felix; Lesego, Abaleng; Leufkens, Hubert; Kinfu, Yohannes

2017-01-05

Despite tremendous efforts to scale up key maternal and child health interventions in Zambia, progress has not been uniform across the country. This raises fundamental health system performance questions that require further investigation. Our study investigates technical and scale efficiency (SE) in the delivery of maternal and child health services in the country. The study focused on all 72 health districts of Zambia. We compiled a district-level database comprising health outcomes (measured by the probability of survival to 5 years of age), health outputs (measured by coverage of key health interventions) and a set of health system inputs, namely, financial resources and human resources for health, for the year 2010. We used data envelopment analysis to assess the performance of subnational units across Zambia with respect to technical and SE, controlling for environmental factors that are beyond the control of health system decision makers. Nationally, average technical efficiency with respect to improving child survival was 61.5% (95% CI 58.2% to 64.8%), which suggests that there is a huge inefficiency in resource use in the country and the potential to expand services without injecting additional resources into the system. Districts that were more urbanised and had a higher proportion of educated women were more technically efficient. Improved cooking methods and donor funding had no significant effect on efficiency. With the pressing need to accelerate progress in population health, decision makers must seek efficient ways to deliver services to achieve universal health coverage. Understanding the factors that drive performance and seeking ways to enhance efficiency offer a practical pathway through which low-income countries could improve population health without necessarily seeking additional resources. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Two Trees: Migrating Fault Trees to Decision Trees for Real Time Fault Detection on International Space Station

NASA Technical Reports Server (NTRS)

Lee, Charles; Alena, Richard L.; Robinson, Peter

2004-01-01

We started from ISS fault trees example to migrate to decision trees, presented a method to convert fault trees to decision trees. The method shows that the visualizations of root cause of fault are easier and the tree manipulating becomes more programmatic via available decision tree programs. The visualization of decision trees for the diagnostic shows a format of straight forward and easy understands. For ISS real time fault diagnostic, the status of the systems could be shown by mining the signals through the trees and see where it stops at. The other advantage to use decision trees is that the trees can learn the fault patterns and predict the future fault from the historic data. The learning is not only on the static data sets but also can be online, through accumulating the real time data sets, the decision trees can gain and store faults patterns in the trees and recognize them when they come.

The influence of gender and age on choice of flood adaptation strategies: A case study of Zambia and Namibia..

NASA Astrophysics Data System (ADS)

Mabuku, Monde

2017-04-01

It is reported that flood events will increase due to variability and change in climate, thus increasing the number of people exposed to flooding disasters. This exposure negatively impacts rural households' livelihoods. Women, men, young, old has distinctive vulnerability and this shapes the choice of flood adaptation strategies. This calls for a need to adopt group specific interventions to strengthen local adaptive capacity to flooding for the affected population. The purpose of this case study was to determine the adaptation strategies to floods adopted by rural households in the Zambezi region of Namibia and Mwandi district of Zambia. The study further examined how gender and age influenced the choice of different adaptation strategies. Six focus group meetings and a questionnaire survey of 207 randomly sampled households were conducted in the flood prone areas of the study. Descriptive statistics results on the adaptation strategies indicated that a majority of the households in Namibia learnt to live with floods (86%),practiced mafisa cattle trade (86%), flood water harvesting (68%), practiced early and late planting (63%), prayed (55%), practiced conservation agriculture (54%) and fish farming (53%). In Zambia the adaptation strategies were; conservation agriculture (91%), acquiring better skills on preparedness (66%), flood water harvesting (63%), praying (60%), and flood proofing (52%). Logistic regression analysis showed that age positively and significantly influenced the likelihood of taking up adaptation strategies such as tree planting, relocation to higher ground, flood water harvesting, early and late planting. The older the respondents the more likely they were to adopt the strategies mentioned. More young ones were more likely to adopt acquiring better skills on flood preparedness and mafisa cattle trading than the old ones. Gender positively and significantly influenced mafisa cattle trade (p<0.01), male headed households were more likely to adopt mafisa cattle trading than the females. The study concludes that factors such as age and gender influences the choice of any adaptation strategy. For policy purposes, this suggests that relevant stakeholders' interventions should consider gender and age in order to enhance the adaptive capacity of rural households to flooding. This study will inform decision makers and practitioners to consider women and men, young and old in designing programs and projects aimed at strengthening disaster risk reduction and management in the two countries and under similar environments.

Will savannas survive outside the parks? A lesson from Zambia

NASA Astrophysics Data System (ADS)

Kutsch, W.; Merbold, L.; Scholes, B.; Mukelabai, M.

2012-04-01

Miombo woodlands cover the transition zone between dry open savannas and moist forests in Southern Africa. They cover about 2.7 million km2 in southern Africa and provide many ecosystem services that support rural life, including medical products, wild foods, construction timber and fuel. In Zambia, as in many of its neighbouring countries, miombo woodlands are currently experiencing accelerating degradation and clearing, mostly with charcoal production as the initial driver. Domestic energy needs in the growing urban areas are largely satisfied by charcoal, which is less energy-efficient fuel on a tree-to-table basis than the firewood that is used in rural areas, but has a higher energy density and is thus cheaper to transport. This study uses data from inventories and from eddy covariance measurements of carbon exchange to characterize the impact of charcoal production on miombo woodlands. We address the following questions: (i) how much carbon is lost at local as well as at national scale and (ii) does forest degradation result in the loss of a carbon sink? On the basis of our data we (iii) estimate the per capita emissions through deforestation and forest degradation in Zambia and relate it to fossil fuel emissions. Furthermore, (iv) a rough estimate of the energy that is provided by charcoal production to private households at a national level is calculated and (v) options for alternative energy supply to private households are discussed.

A new approach to enhance the performance of decision tree for classifying gene expression data.

PubMed

Hassan, Md; Kotagiri, Ramamohanarao

2013-12-20

Gene expression data classification is a challenging task due to the large dimensionality and very small number of samples. Decision tree is one of the popular machine learning approaches to address such classification problems. However, the existing decision tree algorithms use a single gene feature at each node to split the data into its child nodes and hence might suffer from poor performance specially when classifying gene expression dataset. By using a new decision tree algorithm where, each node of the tree consists of more than one gene, we enhance the classification performance of traditional decision tree classifiers. Our method selects suitable genes that are combined using a linear function to form a derived composite feature. To determine the structure of the tree we use the area under the Receiver Operating Characteristics curve (AUC). Experimental analysis demonstrates higher classification accuracy using the new decision tree compared to the other existing decision trees in literature. We experimentally compare the effect of our scheme against other well known decision tree techniques. Experiments show that our algorithm can substantially boost the classification performance of the decision tree.

Safety validation of decision trees for hepatocellular carcinoma.

PubMed

Wang, Xian-Qiang; Liu, Zhe; Lv, Wen-Ping; Luo, Ying; Yang, Guang-Yun; Li, Chong-Hui; Meng, Xiang-Fei; Liu, Yang; Xu, Ke-Sen; Dong, Jia-Hong

2015-08-21

To evaluate a different decision tree for safe liver resection and verify its efficiency. A total of 2457 patients underwent hepatic resection between January 2004 and December 2010 at the Chinese PLA General Hospital, and 634 hepatocellular carcinoma (HCC) patients were eligible for the final analyses. Post-hepatectomy liver failure (PHLF) was identified by the association of prothrombin time < 50% and serum bilirubin > 50 μmol/L (the "50-50" criteria), which were assessed at day 5 postoperatively or later. The Swiss-Clavien decision tree, Tokyo University-Makuuchi decision tree, and Chinese consensus decision tree were adopted to divide patients into two groups based on those decision trees in sequence, and the PHLF rates were recorded. The overall mortality and PHLF rate were 0.16% and 3.0%. A total of 19 patients experienced PHLF. The numbers of patients to whom the Swiss-Clavien, Tokyo University-Makuuchi, and Chinese consensus decision trees were applied were 581, 573, and 622, and the PHLF rates were 2.75%, 2.62%, and 2.73%, respectively. Significantly more cases satisfied the Chinese consensus decision tree than the Swiss-Clavien decision tree and Tokyo University-Makuuchi decision tree (P < 0.01，P < 0.01); nevertheless, the latter two shared no difference (P = 0.147). The PHLF rate exhibited no significant difference with respect to the three decision trees. The Chinese consensus decision tree expands the indications for hepatic resection for HCC patients and does not increase the PHLF rate compared to the Swiss-Clavien and Tokyo University-Makuuchi decision trees. It would be a safe and effective algorithm for hepatectomy in patients with hepatocellular carcinoma.

The influence of social constructs of hegemonic masculinity and sexual behaviour on acceptability of vaginal microbicides in Zambia.

PubMed

Mweemba, Oliver; Dixey, Rachael; Bond, Virginia; White, Alan

2018-07-01

Vaginal microbicides are heralded as a woman's HIV prevention method. This study, conducted in a microbicide clinical trial setting in Zambia, explored how the social construction of masculinity and sexual behaviour influenced the acceptability of vaginal microbicides. The data were generated from 18 In-depth Interviews and 8 Focus Group Discussions. The data were analysed thematically. The study found that hegemonic masculinity influenced the use of vaginal microbicides positively and negatively, in multiple ways including: decision to initiate gel use, autonomous use of the gel, and consistent use of the gel. Men were seen as heads of households and decision-makers who approved their partners' intentions to initiate gel use. Autonomous gel use by women was not supported because it challenged men's dominant position in sexual matters and at a family level. The socially accepted notion that men engaged in multiple sexual relationships also influenced women's decision to use the gel. Sustained gel use depended on the perceived effect of the gel on men's sexual desires, sexual performance, fertility, and sexual behaviour. This study suggests that acceptability of microbicides partially lies within the realm of men, with use constrained and dictated by cultural constructs and practice of masculinity and gender.

Reasons for home delivery and use of traditional birth attendants in rural Zambia: a qualitative study.

PubMed

Sialubanje, Cephas; Massar, Karlijn; Hamer, Davidson H; Ruiter, Robert A C

2015-09-11

Despite the policy change stopping traditional birth attendants (TBAs) from conducting deliveries at home and encouraging all women to give birth at the clinic under skilled care, many women still give birth at home and TBAs are essential providers of obstetric care in rural Zambia. The main reasons for pregnant women's preference for TBAs are not well understood. This qualitative study aimed to identify reasons motivating women to giving birth at home and seek the help of TBAs. This knowledge is important for the design of public health interventions focusing on promoting facility-based skilled birth attendance in Zambia. We conducted ten focus group discussions (n = 100) with women of reproductive age (15-45 years) in five health centre catchment areas with the lowest institutional delivery rates in the district. In addition, a total of 30 in-depth interviews were conducted comprising 5 TBAs, 4 headmen, 4 husbands, 4 mothers, 4 neighbourhood health committee (NHC) members, 4 community health workers (CHWs) and 5 nurses. Perspectives on TBAs, the decision-making process regarding home delivery and use of TBAs, and reasons for preference of TBAs and their services were explored. Our findings show that women's lack of decision- making autonomy regarding child birth, dependence on the husband and other family members for the final decision, and various physical and socioeconomic barriers including long distances, lack of money for transport and the requirement to bring baby clothes and food while staying at the clinic, prevented them from delivering at a clinic. In addition, socio-cultural norms regarding childbirth, negative attitude towards the quality of services provided at the clinic, made most women deliver at home. Moreover, most women had a positive attitude towards TBAs and perceived them to be respectful, skilled, friendly, trustworthy, and available when they needed them. Our findings suggest a need to empower women with decision-making skills regarding childbirth and to lower barriers that prevent them from going to the health facility in time. There is also need to improve the quality of existing facility-based delivery services and to strengthen linkages between TBAs and the formal health system.

Supporting better decisions across the nexus of water, energy and food through earth observation data: case of the Zambezi basin

NASA Astrophysics Data System (ADS)

Faith Gomo, Fortune; Macleod, Christopher; Rowan, John; Yeluripati, Jagadeesh; Topp, Kairsty

2018-02-01

The water-energy-food (WEF) nexus has been promoted in recent years as an intersectional concept designed to improve planning and regulatory decision-making across the three sectors. The production and consumption of water, energy and food resources are inextricably linked across multiple spatial scales (from the global to the local), but a common feature is competition for land which through different land management practices mediates provisioning ecosystem services. The nexus perspective seeks to understand the interlinkages and use systems-based thinking to frame management options for the present and the future. It aims to highlight advantage and minimise damaging and unsustainable outcomes through informed decisions regarding trade-offs inclusive of economic, ecological and equity considerations. Operationalizing the WEF approach is difficult because of the lack of complete data, knowledge and observability - and the nature of the challenge also depends on the scale of the investigation. Transboundary river basins are particularly challenging because whilst the basin unit defines the hydrological system this is not necessarily coincident with flows of food and energy. There are multiple national jurisdictions and geopolitical relations to consider. Land use changes have a profound influence on hydrological, agricultural, energy provisioning and regulating ecosystem services. Future policy decisions in the water, energy and food sectors could have profound effects, with different demands for land and water resources, intensifying competition for these resources in the future. In this study, we used Google Earth Engine (GEE) to analyse the land cover changes in the Zambezi river basin (1.4 million km2) from 1992 to 2015 using the European Space Agency annual global land cover dataset. Early results indicate transformative processes are underway with significant shifts from tree cover to cropland, with a 4.6 % loss in tree cover and a 16 % gain in cropland during the study period. The changes were found to be occurring mainly in the eastern (Malawi and Mozambique) and southern (Zimbabwe and southern Zambia) parts of the basin. The area under urban land uses was found to have more than doubled during the study period gearing urban centres increasingly as the foci for resource consumption. These preliminary findings are the first step in understanding the spatial and temporal interlinkages of water, energy and food by providing reliable and consistent evidence spanning the local, regional, national and whole transboundary basin scale.

Decision-Tree Formulation With Order-1 Lateral Execution

NASA Technical Reports Server (NTRS)

James, Mark

2007-01-01

A compact symbolic formulation enables mapping of an arbitrarily complex decision tree of a certain type into a highly computationally efficient multidimensional software object. The type of decision trees to which this formulation applies is that known in the art as the Boolean class of balanced decision trees. Parallel lateral slices of an object created by means of this formulation can be executed in constant time considerably less time than would otherwise be required. Decision trees of various forms are incorporated into almost all large software systems. A decision tree is a way of hierarchically solving a problem, proceeding through a set of true/false responses to a conclusion. By definition, a decision tree has a tree-like structure, wherein each internal node denotes a test on an attribute, each branch from an internal node represents an outcome of a test, and leaf nodes represent classes or class distributions that, in turn represent possible conclusions. The drawback of decision trees is that execution of them can be computationally expensive (and, hence, time-consuming) because each non-leaf node must be examined to determine whether to progress deeper into a tree structure or to examine an alternative. The present formulation was conceived as an efficient means of representing a decision tree and executing it in as little time as possible. The formulation involves the use of a set of symbolic algorithms to transform a decision tree into a multi-dimensional object, the rank of which equals the number of lateral non-leaf nodes. The tree can then be executed in constant time by means of an order-one table lookup. The sequence of operations performed by the algorithms is summarized as follows: 1. Determination of whether the tree under consideration can be encoded by means of this formulation. 2. Extraction of decision variables. 3. Symbolic optimization of the decision tree to minimize its form. 4. Expansion and transformation of all nested conjunctive-disjunctive paths to a flattened conjunctive form composed only of equality checks when possible. If each reduced conjunctive form contains only equality checks and all of these forms use the same variables, then the decision tree can be reduced to an order-one operation through a table lookup. The speedup to order one is accomplished by distributing each decision variable over a surface of a multidimensional object by mapping the equality constant to an index

Factors influencing modes of transport and travel time for obstetric care: a mixed methods study in Zambia and Uganda.

PubMed

Sacks, Emma; Vail, Daniel; Austin-Evelyn, Katherine; Greeson, Dana; Atuyambe, Lynn M; Macwan'gi, Mubiana; Kruk, Margaret E; Grépin, Karen A

2016-04-01

Transportation is an important barrier to accessing obstetric care for many pregnant and postpartum women in low-resource settings, particularly in rural areas. However, little is known about how pregnant women travel to health facilities in these settings. We conducted 1633 exit surveys with women who had a recent facility delivery and 48 focus group discussions with women who had either a home or a facility birth in the past year in eight districts in Uganda and Zambia. Quantitative data were analysed using univariate statistics, and qualitative data were analysed using thematic content analysis techniques. On average, women spent 62-68 min travelling to a clinic for delivery. Very different patterns in modes of transport were observed in the two countries: 91% of Ugandan women employed motorized forms of transportation, while only 57% of women in Zambia did. Motorcycle taxis were the most commonly used in Uganda, while cars, trucks and taxis were the most commonly used mode of transportation in Zambia. Lower-income women were less likely to use motorized modes of transportation: in Zambia, women in the poorest quintile took 94 min to travel to a health facility, compared with 34 for the wealthiest quintile; this difference between quintiles was ∼50 min in Uganda. Focus group discussions confirmed that transport is a major challenge due to a number of factors we categorized as the 'three A's:' affordability, accessibility and adequacy of transport options. Women reported that all of these factors had influenced their decision not to deliver in a health facility. The two countries had markedly different patterns of transportation for obstetric care, and modes of transport and travel times varied dramatically by wealth quintile, which policymakers need to take into account when designing obstetric transport interventions. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Decentralization in Zambia: resource allocation and district performance.

PubMed

Bossert, Thomas; Chitah, Mukosha Bona; Bowser, Diana

2003-12-01

Zambia implemented an ambitious process of health sector decentralization in the mid 1990s. This article presents an assessment of the degree of decentralization, called 'decision space', that was allowed to districts in Zambia, and an analysis of data on districts available at the national level to assess allocation choices made by local authorities and some indicators of the performance of the health systems under decentralization. The Zambian officials in health districts had a moderate range of choice over expenditures, user fees, contracting, targeting and governance. Their choices were quite limited over salaries and allowances and they did not have control over additional major sources of revenue, like local taxes. The study found that the formula for allocation of government funding which was based on population size and hospital beds resulted in relatively equal per capita expenditures among districts. Decentralization allowed the districts to make decisions on internal allocation of resources and on user fee levels and expenditures. General guidelines for the allocation of resources established a maximum and minimum percentage to be allocated to district offices, hospitals, health centres and communities. Districts tended to exceed the maximum for district offices, but the large urban districts and those without public district hospitals were not even reaching the minimum for hospital allocations. Wealthier and urban districts were more successful in raising revenue through user fees, although the proportion of total expenditures that came from user fees was low. An analysis of available indicators of performance, such as the utilization of health services, immunization coverage and family planning activities, found little variation during the period 1995-98 except for a decline in immunization coverage, which may have also been affected by changes in donor funding. These findings suggest that decentralization may not have had either a positive or negative impact on services.

Classification and Progression Based on CFS-GA and C5.0 Boost Decision Tree of TCM Zheng in Chronic Hepatitis B.

PubMed

Chen, Xiao Yu; Ma, Li Zhuang; Chu, Na; Zhou, Min; Hu, Yiyang

2013-01-01

Chronic hepatitis B (CHB) is a serious public health problem, and Traditional Chinese Medicine (TCM) plays an important role in the control and treatment for CHB. In the treatment of TCM, zheng discrimination is the most important step. In this paper, an approach based on CFS-GA (Correlation based Feature Selection and Genetic Algorithm) and C5.0 boost decision tree is used for zheng classification and progression in the TCM treatment of CHB. The CFS-GA performs better than the typical method of CFS. By CFS-GA, the acquired attribute subset is classified by C5.0 boost decision tree for TCM zheng classification of CHB, and C5.0 decision tree outperforms two typical decision trees of NBTree and REPTree on CFS-GA, CFS, and nonselection in comparison. Based on the critical indicators from C5.0 decision tree, important lab indicators in zheng progression are obtained by the method of stepwise discriminant analysis for expressing TCM zhengs in CHB, and alterations of the important indicators are also analyzed in zheng progression. In conclusion, all the three decision trees perform better on CFS-GA than on CFS and nonselection, and C5.0 decision tree outperforms the two typical decision trees both on attribute selection and nonselection.

TreePOD: Sensitivity-Aware Selection of Pareto-Optimal Decision Trees.

PubMed

Muhlbacher, Thomas; Linhardt, Lorenz; Moller, Torsten; Piringer, Harald

2018-01-01

Balancing accuracy gains with other objectives such as interpretability is a key challenge when building decision trees. However, this process is difficult to automate because it involves know-how about the domain as well as the purpose of the model. This paper presents TreePOD, a new approach for sensitivity-aware model selection along trade-offs. TreePOD is based on exploring a large set of candidate trees generated by sampling the parameters of tree construction algorithms. Based on this set, visualizations of quantitative and qualitative tree aspects provide a comprehensive overview of possible tree characteristics. Along trade-offs between two objectives, TreePOD provides efficient selection guidance by focusing on Pareto-optimal tree candidates. TreePOD also conveys the sensitivities of tree characteristics on variations of selected parameters by extending the tree generation process with a full-factorial sampling. We demonstrate how TreePOD supports a variety of tasks involved in decision tree selection and describe its integration in a holistic workflow for building and selecting decision trees. For evaluation, we illustrate a case study for predicting critical power grid states, and we report qualitative feedback from domain experts in the energy sector. This feedback suggests that TreePOD enables users with and without statistical background a confident and efficient identification of suitable decision trees.

Information, Knowledge, and Demand for Substitute Health Inputs: Experimental Evidence of Pesticide Use in Zambia

ERIC Educational Resources Information Center

Goeb, Joseph Christopher

2017-01-01

Many goods carry health risks that have important impacts on demand and behavior. However, the risks are rarely transparent and, as a result, consumers often have incomplete knowledge of the health risks associated with many of their consumption decisions. This can lead to inefficient behavior. With that in mind, economists have studied the…

VC-dimension of univariate decision trees.

PubMed

Yildiz, Olcay Taner

2015-02-01

In this paper, we give and prove the lower bounds of the Vapnik-Chervonenkis (VC)-dimension of the univariate decision tree hypothesis class. The VC-dimension of the univariate decision tree depends on the VC-dimension values of its subtrees and the number of inputs. Via a search algorithm that calculates the VC-dimension of univariate decision trees exhaustively, we show that our VC-dimension bounds are tight for simple trees. To verify that the VC-dimension bounds are useful, we also use them to get VC-generalization bounds for complexity control using structural risk minimization in decision trees, i.e., pruning. Our simulation results show that structural risk minimization pruning using the VC-dimension bounds finds trees that are more accurate as those pruned using cross validation.

HMIS and decision-making in Zambia: re-thinking information solutions for district health management in decentralized health systems.

PubMed

Mutemwa, Richard I

2006-01-01

At the onset of health system decentralization as a primary health care strategy, which constituted a key feature of health sector reforms across the developing world, efficient and effective health management information systems (HMIS) were widely acknowledged and adopted as a critical element of district health management strengthening programmes. The focal concern was about the performance and long-term sustainability of decentralized district health systems. The underlying logic was that effective and efficient HMIS would provide district health managers with the information required to make effective strategic decisions that are the vehicle for district performance and sustainability in these decentralized health systems. However, this argument is rooted in normative management and decision theory without significant unequivocal empirical corroboration. Indeed, extensive empirical evidence continues to indicate that managers' decision-making behaviour and the existence of other forms of information outside the HMIS, within the organizational environment, suggest a far more tenuous relationship between the presence of organizational management information systems (such as HMIS) and effective strategic decision-making. This qualitative comparative case-study conducted in two districts of Zambia focused on investigating the presence and behaviour of five formally identified, different information forms, including that from HMIS, in the strategic decision-making process. The aim was to determine the validity of current arguments for HMIS, and establish implications for current HMIS policies. Evidence from the eight strategic decision-making processes traced in the study confirmed the existence of different forms of information in the organizational environment, including that provided by the conventional HMIS. These information forms attach themselves to various organizational management processes and key aspects of organizational routine. The study results point to the need for a radical re-think of district health management information solutions in ways that account for the existence of other information forms outside the formal HMIS in the district health system.

The Decision Tree: A Tool for Achieving Behavioral Change.

ERIC Educational Resources Information Center

Saren, Dru

1999-01-01

Presents a "Decision Tree" process for structuring team decision making and problem solving about specific student behavioral goals. The Decision Tree involves a sequence of questions/decisions that can be answered in "yes/no" terms. Questions address reasonableness of the goal, time factors, importance of the goal, responsibilities, safety,…

Development and acceptability testing of decision trees for self-management of prosthetic socket fit in adults with lower limb amputation.

PubMed

Lee, Daniel Joseph; Veneri, Diana A

2018-05-01

The most common complaint lower limb prosthesis users report is inadequacy of a proper socket fit. Adjustments to the residual limb-socket interface can be made by the prosthesis user without consultation of a clinician in many scenarios through skilled self-management. Decision trees guide prosthesis wearers through the self-management process, empowering them to rectify fit issues, or referring them to a clinician when necessary. This study examines the development and acceptability testing of patient-centered decision trees for lower limb prosthesis users. Decision trees underwent a four-stage process: literature review and expert consultation, designing, two-rounds of expert panel review and revisions, and target audience testing. Fifteen lower limb prosthesis users (average age 61 years) reviewed the decision trees and completed an acceptability questionnaire. Participants reported agreement of 80% or above in five of the eight questions related to acceptability of the decision trees. Disagreement was related to the level of experience of the respondent. Decision trees were found to be easy to use, illustrate correct solutions to common issues, and have terminology consistent with that of a new prosthesis user. Some users with greater than 1.5 years of experience would not use the decision trees based on their own self-management skills. Implications for Rehabilitation Discomfort of the residual limb-prosthetic socket interface is the most common reason for clinician visits. Prosthesis users can use decision trees to guide them through the process of obtaining a proper socket fit independently. Newer users may benefit from using the decision trees more than experienced users.

Minimizing the cost of translocation failure with decision-tree models that predict species' behavioral response in translocation sites.

PubMed

Ebrahimi, Mehregan; Ebrahimie, Esmaeil; Bull, C Michael

2015-08-01

The high number of failures is one reason why translocation is often not recommended. Considering how behavior changes during translocations may improve translocation success. To derive decision-tree models for species' translocation, we used data on the short-term responses of an endangered Australian skink in 5 simulated translocations with different release conditions. We used 4 different decision-tree algorithms (decision tree, decision-tree parallel, decision stump, and random forest) with 4 different criteria (gain ratio, information gain, gini index, and accuracy) to investigate how environmental and behavioral parameters may affect the success of a translocation. We assumed behavioral changes that increased dispersal away from a release site would reduce translocation success. The trees became more complex when we included all behavioral parameters as attributes, but these trees yielded more detailed information about why and how dispersal occurred. According to these complex trees, there were positive associations between some behavioral parameters, such as fight and dispersal, that showed there was a higher chance, for example, of dispersal among lizards that fought than among those that did not fight. Decision trees based on parameters related to release conditions were easier to understand and could be used by managers to make translocation decisions under different circumstances. © 2015 Society for Conservation Biology.

Soft context clustering for F0 modeling in HMM-based speech synthesis

NASA Astrophysics Data System (ADS)

Khorram, Soheil; Sameti, Hossein; King, Simon

2015-12-01

This paper proposes the use of a new binary decision tree, which we call a soft decision tree, to improve generalization performance compared to the conventional `hard' decision tree method that is used to cluster context-dependent model parameters in statistical parametric speech synthesis. We apply the method to improve the modeling of fundamental frequency, which is an important factor in synthesizing natural-sounding high-quality speech. Conventionally, hard decision tree-clustered hidden Markov models (HMMs) are used, in which each model parameter is assigned to a single leaf node. However, this `divide-and-conquer' approach leads to data sparsity, with the consequence that it suffers from poor generalization, meaning that it is unable to accurately predict parameters for models of unseen contexts: the hard decision tree is a weak function approximator. To alleviate this, we propose the soft decision tree, which is a binary decision tree with soft decisions at the internal nodes. In this soft clustering method, internal nodes select both their children with certain membership degrees; therefore, each node can be viewed as a fuzzy set with a context-dependent membership function. The soft decision tree improves model generalization and provides a superior function approximator because it is able to assign each context to several overlapped leaves. In order to use such a soft decision tree to predict the parameters of the HMM output probability distribution, we derive the smoothest (maximum entropy) distribution which captures all partial first-order moments and a global second-order moment of the training samples. Employing such a soft decision tree architecture with maximum entropy distributions, a novel speech synthesis system is trained using maximum likelihood (ML) parameter re-estimation and synthesis is achieved via maximum output probability parameter generation. In addition, a soft decision tree construction algorithm optimizing a log-likelihood measure is developed. Both subjective and objective evaluations were conducted and indicate a considerable improvement over the conventional method.

Decision trees in epidemiological research.

PubMed

Venkatasubramaniam, Ashwini; Wolfson, Julian; Mitchell, Nathan; Barnes, Timothy; JaKa, Meghan; French, Simone

2017-01-01

In many studies, it is of interest to identify population subgroups that are relatively homogeneous with respect to an outcome. The nature of these subgroups can provide insight into effect mechanisms and suggest targets for tailored interventions. However, identifying relevant subgroups can be challenging with standard statistical methods. We review the literature on decision trees, a family of techniques for partitioning the population, on the basis of covariates, into distinct subgroups who share similar values of an outcome variable. We compare two decision tree methods, the popular Classification and Regression tree (CART) technique and the newer Conditional Inference tree (CTree) technique, assessing their performance in a simulation study and using data from the Box Lunch Study, a randomized controlled trial of a portion size intervention. Both CART and CTree identify homogeneous population subgroups and offer improved prediction accuracy relative to regression-based approaches when subgroups are truly present in the data. An important distinction between CART and CTree is that the latter uses a formal statistical hypothesis testing framework in building decision trees, which simplifies the process of identifying and interpreting the final tree model. We also introduce a novel way to visualize the subgroups defined by decision trees. Our novel graphical visualization provides a more scientifically meaningful characterization of the subgroups identified by decision trees. Decision trees are a useful tool for identifying homogeneous subgroups defined by combinations of individual characteristics. While all decision tree techniques generate subgroups, we advocate the use of the newer CTree technique due to its simplicity and ease of interpretation.

Community attitudes towards childbearing and abortion among HIV-positive women in Nigeria and Zambia.

PubMed

Kavanaugh, Megan L; Moore, Ann M; Akinyemi, Odunayo; Adewole, Isaac; Dzekedzeke, Kumbutso; Awolude, Olutosin; Arulogun, Oyedunni

2013-01-01

Although stigma towards HIV-positive women for both continuing and terminating a pregnancy has been documented, to date few studies have examined relative stigma towards one outcome versus the other. This study seeks to describe community attitudes towards each of two possible elective outcomes of an HIV-positive woman's pregnancy - induced abortion or birth - to determine which garners more stigma and document characteristics of community members associated with stigmatising attitudes towards each outcome. Data come from community-based interviews with reproductive-aged men and women, 2401 in Zambia and 2452 in Nigeria. Bivariate and multivariate analyses revealed that respondents from both countries overwhelmingly favoured continued childbearing for HIV-positive pregnant women, but support for induced abortion was slightly higher in scenarios in which anti-retroviral therapy (ART) was unavailable. Zambian respondents held more stigmatising attitudes towards abortion for HIV-positive women than did Nigerian respondents. Women held more stigmatising attitudes towards abortion for HIV-positive women than men, particularly in Zambia. From a sexual and reproductive health and rights perspective, efforts to assist HIV-positive women in preventing unintended pregnancy and to support them in their pregnancy decisions when they do become pregnant should be encouraged in order to combat the social stigma documented in this paper.

An automated approach to the design of decision tree classifiers

NASA Technical Reports Server (NTRS)

Argentiero, P.; Chin, R.; Beaudet, P.

1982-01-01

An automated technique is presented for designing effective decision tree classifiers predicated only on a priori class statistics. The procedure relies on linear feature extractions and Bayes table look-up decision rules. Associated error matrices are computed and utilized to provide an optimal design of the decision tree at each so-called 'node'. A by-product of this procedure is a simple algorithm for computing the global probability of correct classification assuming the statistical independence of the decision rules. Attention is given to a more precise definition of decision tree classification, the mathematical details on the technique for automated decision tree design, and an example of a simple application of the procedure using class statistics acquired from an actual Landsat scene.

Creating ensembles of decision trees through sampling

DOEpatents

Kamath, Chandrika; Cantu-Paz, Erick

2005-08-30

A system for decision tree ensembles that includes a module to read the data, a module to sort the data, a module to evaluate a potential split of the data according to some criterion using a random sample of the data, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method is based on statistical sampling techniques and includes the steps of reading the data; sorting the data; evaluating a potential split according to some criterion using a random sample of the data, splitting the data, and combining multiple decision trees in ensembles.

Bioinformatics in proteomics: application, terminology, and pitfalls.

PubMed

Wiemer, Jan C; Prokudin, Alexander

2004-01-01

Bioinformatics applies data mining, i.e., modern computer-based statistics, to biomedical data. It leverages on machine learning approaches, such as artificial neural networks, decision trees and clustering algorithms, and is ideally suited for handling huge data amounts. In this article, we review the analysis of mass spectrometry data in proteomics, starting with common pre-processing steps and using single decision trees and decision tree ensembles for classification. Special emphasis is put on the pitfall of overfitting, i.e., of generating too complex single decision trees. Finally, we discuss the pros and cons of the two different decision tree usages.

Learning in data-limited multimodal scenarios: Scandent decision forests and tree-based features.

PubMed

Hor, Soheil; Moradi, Mehdi

2016-12-01

Incomplete and inconsistent datasets often pose difficulties in multimodal studies. We introduce the concept of scandent decision trees to tackle these difficulties. Scandent trees are decision trees that optimally mimic the partitioning of the data determined by another decision tree, and crucially, use only a subset of the feature set. We show how scandent trees can be used to enhance the performance of decision forests trained on a small number of multimodal samples when we have access to larger datasets with vastly incomplete feature sets. Additionally, we introduce the concept of tree-based feature transforms in the decision forest paradigm. When combined with scandent trees, the tree-based feature transforms enable us to train a classifier on a rich multimodal dataset, and use it to classify samples with only a subset of features of the training data. Using this methodology, we build a model trained on MRI and PET images of the ADNI dataset, and then test it on cases with only MRI data. We show that this is significantly more effective in staging of cognitive impairments compared to a similar decision forest model trained and tested on MRI only, or one that uses other kinds of feature transform applied to the MRI data. Copyright © 2016. Published by Elsevier B.V.

Predicting membrane protein types using various decision tree classifiers based on various modes of general PseAAC for imbalanced datasets.

PubMed

Sankari, E Siva; Manimegalai, D

2017-12-21

Predicting membrane protein types is an important and challenging research area in bioinformatics and proteomics. Traditional biophysical methods are used to classify membrane protein types. Due to large exploration of uncharacterized protein sequences in databases, traditional methods are very time consuming, expensive and susceptible to errors. Hence, it is highly desirable to develop a robust, reliable, and efficient method to predict membrane protein types. Imbalanced datasets and large datasets are often handled well by decision tree classifiers. Since imbalanced datasets are taken, the performance of various decision tree classifiers such as Decision Tree (DT), Classification And Regression Tree (CART), C4.5, Random tree, REP (Reduced Error Pruning) tree, ensemble methods such as Adaboost, RUS (Random Under Sampling) boost, Rotation forest and Random forest are analysed. Among the various decision tree classifiers Random forest performs well in less time with good accuracy of 96.35%. Another inference is RUS boost decision tree classifier is able to classify one or two samples in the class with very less samples while the other classifiers such as DT, Adaboost, Rotation forest and Random forest are not sensitive for the classes with fewer samples. Also the performance of decision tree classifiers is compared with SVM (Support Vector Machine) and Naive Bayes classifier. Copyright © 2017 Elsevier Ltd. All rights reserved.

Metric Sex Determination of the Human Coxal Bone on a Virtual Sample using Decision Trees.

PubMed

Savall, Frédéric; Faruch-Bilfeld, Marie; Dedouit, Fabrice; Sans, Nicolas; Rousseau, Hervé; Rougé, Daniel; Telmon, Norbert

2015-11-01

Decision trees provide an alternative to multivariate discriminant analysis, which is still the most commonly used in anthropometric studies. Our study analyzed the metric characterization of a recent virtual sample of 113 coxal bones using decision trees for sex determination. From 17 osteometric type I landmarks, a dataset was built with five classic distances traditionally reported in the literature and six new distances selected using the two-step ratio method. A ten-fold cross-validation was performed, and a decision tree was established on two subsamples (training and test sets). The decision tree established on the training set included three nodes and its application to the test set correctly classified 92% of individuals. This percentage was similar to the data of the literature. The usefulness of decision trees has been demonstrated in numerous fields. They have been already used in sex determination, body mass prediction, and ancestry estimation. This study shows another use of decision trees enabling simple and accurate sex determination. © 2015 American Academy of Forensic Sciences.

Multi-test decision tree and its application to microarray data classification.

PubMed

Czajkowski, Marcin; Grześ, Marek; Kretowski, Marek

2014-05-01

The desirable property of tools used to investigate biological data is easy to understand models and predictive decisions. Decision trees are particularly promising in this regard due to their comprehensible nature that resembles the hierarchical process of human decision making. However, existing algorithms for learning decision trees have tendency to underfit gene expression data. The main aim of this work is to improve the performance and stability of decision trees with only a small increase in their complexity. We propose a multi-test decision tree (MTDT); our main contribution is the application of several univariate tests in each non-terminal node of the decision tree. We also search for alternative, lower-ranked features in order to obtain more stable and reliable predictions. Experimental validation was performed on several real-life gene expression datasets. Comparison results with eight classifiers show that MTDT has a statistically significantly higher accuracy than popular decision tree classifiers, and it was highly competitive with ensemble learning algorithms. The proposed solution managed to outperform its baseline algorithm on 14 datasets by an average 6%. A study performed on one of the datasets showed that the discovered genes used in the MTDT classification model are supported by biological evidence in the literature. This paper introduces a new type of decision tree which is more suitable for solving biological problems. MTDTs are relatively easy to analyze and much more powerful in modeling high dimensional microarray data than their popular counterparts. Copyright © 2014 Elsevier B.V. All rights reserved.

Comprehensive decision tree models in bioinformatics.

PubMed

Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter

2012-01-01

Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class attributes and a high number of possibly redundant attributes that are very common in bioinformatics.

Comprehensive Decision Tree Models in Bioinformatics

PubMed Central

Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter

2012-01-01

Purpose Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. Methods This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. Results The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. Conclusions The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class attributes and a high number of possibly redundant attributes that are very common in bioinformatics. PMID:22479449

Using histograms to introduce randomization in the generation of ensembles of decision trees

DOEpatents

Kamath, Chandrika; Cantu-Paz, Erick; Littau, David

2005-02-22

A system for decision tree ensembles that includes a module to read the data, a module to create a histogram, a module to evaluate a potential split according to some criterion using the histogram, a module to select a split point randomly in an interval around the best split, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method includes the steps of reading the data; creating a histogram; evaluating a potential split according to some criterion using the histogram, selecting a split point randomly in an interval around the best split, splitting the data, and combining multiple decision trees in ensembles.

Catholic Schools in Zambia: 1891-1924.

ERIC Educational Resources Information Center

Carmody, Brendan

1999-01-01

Retraces the contribution of the Catholic Church to schooling in Northern Rhodesia (currently Zambia) from 1891-1924. Provides background on the development of the Church in Zambia. Discusses Catholic and government perspectives on schooling and conversion, Catholic schooling in Zambia, and the African response to Catholic schooling. (CMK)

Assessing the capacity of ministries of health to use research in decision-making: conceptual framework and tool.

PubMed

Rodríguez, Daniela C; Hoe, Connie; Dale, Elina M; Rahman, M Hafizur; Akhter, Sadika; Hafeez, Assad; Irava, Wayne; Rajbangshi, Preety; Roman, Tamlyn; Ţîrdea, Marcela; Yamout, Rouham; Peters, David H

2017-08-01

The capacity to demand and use research is critical for governments if they are to develop policies that are informed by evidence. Existing tools designed to assess how government officials use evidence in decision-making have significant limitations for low- and middle-income countries (LMICs); they are rarely tested in LMICs and focus only on individual capacity. This paper introduces an instrument that was developed to assess Ministry of Health (MoH) capacity to demand and use research evidence for decision-making, which was tested for reliability and validity in eight LMICs (Bangladesh, Fiji, India, Lebanon, Moldova, Pakistan, South Africa, Zambia). Instrument development was based on a new conceptual framework that addresses individual, organisational and systems capacities, and items were drawn from existing instruments and a literature review. After initial item development and pre-testing to address face validity and item phrasing, the instrument was reduced to 54 items for further validation and item reduction. In-country study teams interviewed a systematic sample of 203 MoH officials. Exploratory factor analysis was used in addition to standard reliability and validity measures to further assess the items. Thirty items divided between two factors representing organisational and individual capacity constructs were identified. South Africa and Zambia demonstrated the highest level of organisational capacity to use research, whereas Pakistan and Bangladesh were the lowest two. In contrast, individual capacity was highest in Pakistan, followed by South Africa, whereas Bangladesh and Lebanon were the lowest. The framework and related instrument represent a new opportunity for MoHs to identify ways to understand and improve capacities to incorporate research evidence in decision-making, as well as to provide a basis for tracking change.

Using Decision Trees to Detect and Isolate Simulated Leaks in the J-2X Rocket Engine

NASA Technical Reports Server (NTRS)

Schwabacher, Mark A.; Aguilar, Robert; Figueroa, Fernando F.

2009-01-01

The goal of this work was to use data-driven methods to automatically detect and isolate faults in the J-2X rocket engine. It was decided to use decision trees, since they tend to be easier to interpret than other data-driven methods. The decision tree algorithm automatically "learns" a decision tree by performing a search through the space of possible decision trees to find one that fits the training data. The particular decision tree algorithm used is known as C4.5. Simulated J-2X data from a high-fidelity simulator developed at Pratt & Whitney Rocketdyne and known as the Detailed Real-Time Model (DRTM) was used to "train" and test the decision tree. Fifty-six DRTM simulations were performed for this purpose, with different leak sizes, different leak locations, and different times of leak onset. To make the simulations as realistic as possible, they included simulated sensor noise, and included a gradual degradation in both fuel and oxidizer turbine efficiency. A decision tree was trained using 11 of these simulations, and tested using the remaining 45 simulations. In the training phase, the C4.5 algorithm was provided with labeled examples of data from nominal operation and data including leaks in each leak location. From the data, it "learned" a decision tree that can classify unseen data as having no leak or having a leak in one of the five leak locations. In the test phase, the decision tree produced very low false alarm rates and low missed detection rates on the unseen data. It had very good fault isolation rates for three of the five simulated leak locations, but it tended to confuse the remaining two locations, perhaps because a large leak at one of these two locations can look very similar to a small leak at the other location.

Objective consensus from decision trees.

PubMed

Putora, Paul Martin; Panje, Cedric M; Papachristofilou, Alexandros; Dal Pra, Alan; Hundsberger, Thomas; Plasswilm, Ludwig

2014-12-05

Consensus-based approaches provide an alternative to evidence-based decision making, especially in situations where high-level evidence is limited. Our aim was to demonstrate a novel source of information, objective consensus based on recommendations in decision tree format from multiple sources. Based on nine sample recommendations in decision tree format a representative analysis was performed. The most common (mode) recommendations for each eventuality (each permutation of parameters) were determined. The same procedure was applied to real clinical recommendations for primary radiotherapy for prostate cancer. Data was collected from 16 radiation oncology centres, converted into decision tree format and analyzed in order to determine the objective consensus. Based on information from multiple sources in decision tree format, treatment recommendations can be assessed for every parameter combination. An objective consensus can be determined by means of mode recommendations without compromise or confrontation among the parties. In the clinical example involving prostate cancer therapy, three parameters were used with two cut-off values each (Gleason score, PSA, T-stage) resulting in a total of 27 possible combinations per decision tree. Despite significant variations among the recommendations, a mode recommendation could be found for specific combinations of parameters. Recommendations represented as decision trees can serve as a basis for objective consensus among multiple parties.

The decision tree approach to classification

NASA Technical Reports Server (NTRS)

Wu, C.; Landgrebe, D. A.; Swain, P. H.

1975-01-01

A class of multistage decision tree classifiers is proposed and studied relative to the classification of multispectral remotely sensed data. The decision tree classifiers are shown to have the potential for improving both the classification accuracy and the computation efficiency. Dimensionality in pattern recognition is discussed and two theorems on the lower bound of logic computation for multiclass classification are derived. The automatic or optimization approach is emphasized. Experimental results on real data are reported, which clearly demonstrate the usefulness of decision tree classifiers.

Improving medical diagnosis reliability using Boosted C5.0 decision tree empowered by Particle Swarm Optimization.

PubMed

Pashaei, Elnaz; Ozen, Mustafa; Aydin, Nizamettin

2015-08-01

Improving accuracy of supervised classification algorithms in biomedical applications is one of active area of research. In this study, we improve the performance of Particle Swarm Optimization (PSO) combined with C4.5 decision tree (PSO+C4.5) classifier by applying Boosted C5.0 decision tree as the fitness function. To evaluate the effectiveness of our proposed method, it is implemented on 1 microarray dataset and 5 different medical data sets obtained from UCI machine learning databases. Moreover, the results of PSO + Boosted C5.0 implementation are compared to eight well-known benchmark classification methods (PSO+C4.5, support vector machine under the kernel of Radial Basis Function, Classification And Regression Tree (CART), C4.5 decision tree, C5.0 decision tree, Boosted C5.0 decision tree, Naive Bayes and Weighted K-Nearest neighbor). Repeated five-fold cross-validation method was used to justify the performance of classifiers. Experimental results show that our proposed method not only improve the performance of PSO+C4.5 but also obtains higher classification accuracy compared to the other classification methods.

Decision tree and ensemble learning algorithms with their applications in bioinformatics.

PubMed

Che, Dongsheng; Liu, Qi; Rasheed, Khaled; Tao, Xiuping

2011-01-01

Machine learning approaches have wide applications in bioinformatics, and decision tree is one of the successful approaches applied in this field. In this chapter, we briefly review decision tree and related ensemble algorithms and show the successful applications of such approaches on solving biological problems. We hope that by learning the algorithms of decision trees and ensemble classifiers, biologists can get the basic ideas of how machine learning algorithms work. On the other hand, by being exposed to the applications of decision trees and ensemble algorithms in bioinformatics, computer scientists can get better ideas of which bioinformatics topics they may work on in their future research directions. We aim to provide a platform to bridge the gap between biologists and computer scientists.

A Decision Tree for Psychology Majors: Supplying Questions as Well as Answers.

ERIC Educational Resources Information Center

Poe, Retta E.

1988-01-01

Outlines the development of a psychology careers decision tree to help faculty advise students plan their program. States that students using the decision tree may benefit by learning more about their career options and by acquiring better question-asking skills. (GEA)

[Prediction of regional soil quality based on mutual information theory integrated with decision tree algorithm].

PubMed

Lin, Fen-Fang; Wang, Ke; Yang, Ning; Yan, Shi-Guang; Zheng, Xin-Yu

2012-02-01

In this paper, some main factors such as soil type, land use pattern, lithology type, topography, road, and industry type that affect soil quality were used to precisely obtain the spatial distribution characteristics of regional soil quality, mutual information theory was adopted to select the main environmental factors, and decision tree algorithm See 5.0 was applied to predict the grade of regional soil quality. The main factors affecting regional soil quality were soil type, land use, lithology type, distance to town, distance to water area, altitude, distance to road, and distance to industrial land. The prediction accuracy of the decision tree model with the variables selected by mutual information was obviously higher than that of the model with all variables, and, for the former model, whether of decision tree or of decision rule, its prediction accuracy was all higher than 80%. Based on the continuous and categorical data, the method of mutual information theory integrated with decision tree could not only reduce the number of input parameters for decision tree algorithm, but also predict and assess regional soil quality effectively.

The value of decision tree analysis in planning anaesthetic care in obstetrics.

PubMed

Bamber, J H; Evans, S A

2016-08-01

The use of decision tree analysis is discussed in the context of the anaesthetic and obstetric management of a young pregnant woman with joint hypermobility syndrome with a history of insensitivity to local anaesthesia and a previous difficult intubation due to a tongue tumour. The multidisciplinary clinical decision process resulted in the woman being delivered without complication by elective caesarean section under general anaesthesia after an awake fibreoptic intubation. The decision process used is reviewed and compared retrospectively to a decision tree analytical approach. The benefits and limitations of using decision tree analysis are reviewed and its application in obstetric anaesthesia is discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Gender equality and education: Increasing the uptake of HIV testing among married women in Kenya, Zambia and Zimbabwe.

PubMed

Singh, Kavita; Luseno, Winnie; Haney, Erica

2013-01-01

Gender equality and education are being promoted as strategies to combat the HIV epidemic in Africa, but few studies have looked at the role of gender equality and education in the uptake of a vital service - HIV testing. This study looks at the associations between education (a key input needed for gender equality) and key gender equality measures (financial decision making and attitudes toward violence) with ever tested for HIV and tested for HIV in the past year. The study focused on currently married women ages between15-24 and 25-34 in three countries - Kenya, Zambia, and Zimbabwe. The data came from the Demographic and Health Surveys. Logistic regression was used to study the role of gender equality and education on the HIV testing outcomes after controlling for both social and biological factors. Results indicated that education had a consistent positive relationship with testing for both age groups, and the associations were always significant for young women aged 15-24 years (p<0.01). The belief that gender-based violence is unacceptable was positively associated with testing for women aged 25-34 in all the three countries, although the associations were only significant in Kenya (among women reporting ever being tested: OR 1.58, p<0.00; among women reporting being tested in the past year: OR 1.34, p<0.05) and Zambia (among women reporting ever being tested: OR 1.24, p<0.10; among women reporting being tested in the past year: OR 1.29, p<0.05). High financial decision making was associated with testing for women aged 25-34 in Zimbabwe only (among women reporting ever being tested: OR 1.66, p<0.01). Overall, the findings indicate that the education and the promotion of gender equality are important strategies for increasing uptake of a vital HIV service, and thus are important tools for protecting girls and young women against HIV.

Building of fuzzy decision trees using ID3 algorithm

NASA Astrophysics Data System (ADS)

Begenova, S. B.; Avdeenko, T. V.

2018-05-01

Decision trees are widely used in the field of machine learning and artificial intelligence. Such popularity is due to the fact that with the help of decision trees graphic models, text rules can be built and they are easily understood by the final user. Because of the inaccuracy of observations, uncertainties, the data, collected in the environment, often take an unclear form. Therefore, fuzzy decision trees becoming popular in the field of machine learning. This article presents a method that includes the features of the two above-mentioned approaches: a graphical representation of the rules system in the form of a tree and a fuzzy representation of the data. The approach uses such advantages as high comprehensibility of decision trees and the ability to cope with inaccurate and uncertain information in fuzzy representation. The received learning method is suitable for classifying problems with both numerical and symbolic features. In the article, solution illustrations and numerical results are given.

Evolutionary Algorithm Based Automated Reverse Engineering and Defect Discovery

DTIC Science & Technology

2007-09-21

a previous application of a GP as a data mining function to evolve fuzzy decision trees symbolically [3-5], the terminal set consisted of fuzzy...of input and output information is required. In the case of fuzzy decision trees, the database represented a collection of scenarios about which the...fuzzy decision tree to be evolved would make decisions . The database also had entries created by experts representing decisions about the scenarios

Detection of Plasmodium falciparum Infection in Anopheles squamosus (Diptera: Culicidae) in an Area Targeted for Malaria Elimination, Southern Zambia

PubMed Central

Stevenson, Jennifer C.; Simubali, Limonty; Mbambara, Saidon; Musonda, Michael; Mweetwa, Sydney; Mudenda, Twig; Pringle, Julia C.; Jones, Christine M.; Norris, Douglas E.

2016-01-01

Southern Zambia is the focus of strategies to create malaria-free zones. Interventions being rolled out include test and treat strategies and distribution of insecticide-treated bed nets that target vectors that host-seek indoors and late at night. In Macha, Choma District, collections of mosquitoes were made outdoors using barrier screens within homesteads or UV bulb light traps set next to goats, cattle, or chickens during the rainy season of 2015. Anopheline mosquitoes were identified to species using molecular methods and Plasmodium falciparum infectivity was determined by ELISA and real-time qPCR methods. More than 40% of specimens caught were identified as Anopheles squamosus Theobald, 1901 of which six were found harboring malaria parasites. A single sample, morphologically identified as Anopheles coustani Laveran, 1900, was also found to be infectious. All seven specimens were caught outdoors next to goat pens. Parasite-positive specimens as well as a subset of An. squamosus specimens from either the same study or archive collections from the same area underwent sequencing of the mitochondrial cytochrome oxidase subunit I gene. Maximum parsimony trees constructed from the aligned sequences indicated presence of at least two clades of An. squamosus with infectious specimens falling in each clade. The single infectious specimen identified morphologically as An. coustani could not be matched to reference sequences. This is the first report from Zambia of infections in An. squamosus, a species which is described in literature to display exophagic traits. The bionomic characteristics of this species needs to be studied further to fully evaluate the implications for indoor-targeted vector control. PMID:27297214

Creating ensembles of oblique decision trees with evolutionary algorithms and sampling

DOEpatents

Cantu-Paz, Erick [Oakland, CA; Kamath, Chandrika [Tracy, CA

2006-06-13

A decision tree system that is part of a parallel object-oriented pattern recognition system, which in turn is part of an object oriented data mining system. A decision tree process includes the step of reading the data. If necessary, the data is sorted. A potential split of the data is evaluated according to some criterion. An initial split of the data is determined. The final split of the data is determined using evolutionary algorithms and statistical sampling techniques. The data is split. Multiple decision trees are combined in ensembles.

The decision tree classifier - Design and potential. [for Landsat-1 data

NASA Technical Reports Server (NTRS)

Hauska, H.; Swain, P. H.

1975-01-01

A new classifier has been developed for the computerized analysis of remote sensor data. The decision tree classifier is essentially a maximum likelihood classifier using multistage decision logic. It is characterized by the fact that an unknown sample can be classified into a class using one or several decision functions in a successive manner. The classifier is applied to the analysis of data sensed by Landsat-1 over Kenosha Pass, Colorado. The classifier is illustrated by a tree diagram which for processing purposes is encoded as a string of symbols such that there is a unique one-to-one relationship between string and decision tree.

Automated rule-base creation via CLIPS-Induce

NASA Technical Reports Server (NTRS)

Murphy, Patrick M.

1994-01-01

Many CLIPS rule-bases contain one or more rule groups that perform classification. In this paper we describe CLIPS-Induce, an automated system for the creation of a CLIPS classification rule-base from a set of test cases. CLIPS-Induce consists of two components, a decision tree induction component and a CLIPS production extraction component. ID3, a popular decision tree induction algorithm, is used to induce a decision tree from the test cases. CLIPS production extraction is accomplished through a top-down traversal of the decision tree. Nodes of the tree are used to construct query rules, and branches of the tree are used to construct classification rules. The learned CLIPS productions may easily be incorporated into a large CLIPS system that perform tasks such as accessing a database or displaying information.

Decision tree methods: applications for classification and prediction.

PubMed

Song, Yan-Yan; Lu, Ying

2015-04-25

Decision tree methodology is a commonly used data mining method for establishing classification systems based on multiple covariates or for developing prediction algorithms for a target variable. This method classifies a population into branch-like segments that construct an inverted tree with a root node, internal nodes, and leaf nodes. The algorithm is non-parametric and can efficiently deal with large, complicated datasets without imposing a complicated parametric structure. When the sample size is large enough, study data can be divided into training and validation datasets. Using the training dataset to build a decision tree model and a validation dataset to decide on the appropriate tree size needed to achieve the optimal final model. This paper introduces frequently used algorithms used to develop decision trees (including CART, C4.5, CHAID, and QUEST) and describes the SPSS and SAS programs that can be used to visualize tree structure.

Learning from examples - Generation and evaluation of decision trees for software resource analysis

NASA Technical Reports Server (NTRS)

Selby, Richard W.; Porter, Adam A.

1988-01-01

A general solution method for the automatic generation of decision (or classification) trees is investigated. The approach is to provide insights through in-depth empirical characterization and evaluation of decision trees for software resource data analysis. The trees identify classes of objects (software modules) that had high development effort. Sixteen software systems ranging from 3,000 to 112,000 source lines were selected for analysis from a NASA production environment. The collection and analysis of 74 attributes (or metrics), for over 4,700 objects, captured information about the development effort, faults, changes, design style, and implementation style. A total of 9,600 decision trees were automatically generated and evaluated. The trees correctly identified 79.3 percent of the software modules that had high development effort or faults, and the trees generated from the best parameter combinations correctly identified 88.4 percent of the modules on the average.

A case study for a psychographic-behavioral segmentation approach for targeted demand generation in voluntary medical male circumcision.

PubMed

Sgaier, Sema K; Eletskaya, Maria; Engl, Elisabeth; Mugurungi, Owen; Tambatamba, Bushimbwa; Ncube, Gertrude; Xaba, Sinokuthemba; Nanga, Alice; Gogolina, Svetlana; Odawo, Patrick; Gumede-Moyo, Sehlulekile; Kretschmer, Steve

2017-09-13

Public health programs are starting to recognize the need to move beyond a one-size-fits-all approach in demand generation, and instead tailor interventions to the heterogeneity underlying human decision making. Currently, however, there is a lack of methods to enable such targeting. We describe a novel hybrid behavioral-psychographic segmentation approach to segment stakeholders on potential barriers to a target behavior. We then apply the method in a case study of demand generation for voluntary medical male circumcision (VMMC) among 15-29 year-old males in Zambia and Zimbabwe. Canonical correlations and hierarchical clustering techniques were applied on representative samples of men in each country who were differentiated by their underlying reasons for their propensity to get circumcised. We characterized six distinct segments of men in Zimbabwe, and seven segments in Zambia, according to their needs, perceptions, attitudes and behaviors towards VMMC, thus highlighting distinct reasons for a failure to engage in the desired behavior.

A case study for a psychographic-behavioral segmentation approach for targeted demand generation in voluntary medical male circumcision

PubMed Central

Eletskaya, Maria; Engl, Elisabeth; Mugurungi, Owen; Tambatamba, Bushimbwa; Ncube, Gertrude; Xaba, Sinokuthemba; Nanga, Alice; Gogolina, Svetlana; Odawo, Patrick; Gumede-Moyo, Sehlulekile; Kretschmer, Steve

2017-01-01

Public health programs are starting to recognize the need to move beyond a one-size-fits-all approach in demand generation, and instead tailor interventions to the heterogeneity underlying human decision making. Currently, however, there is a lack of methods to enable such targeting. We describe a novel hybrid behavioral-psychographic segmentation approach to segment stakeholders on potential barriers to a target behavior. We then apply the method in a case study of demand generation for voluntary medical male circumcision (VMMC) among 15–29 year-old males in Zambia and Zimbabwe. Canonical correlations and hierarchical clustering techniques were applied on representative samples of men in each country who were differentiated by their underlying reasons for their propensity to get circumcised. We characterized six distinct segments of men in Zimbabwe, and seven segments in Zambia, according to their needs, perceptions, attitudes and behaviors towards VMMC, thus highlighting distinct reasons for a failure to engage in the desired behavior. PMID:28901285

Decision-Tree Models of Categorization Response Times, Choice Proportions, and Typicality Judgments

ERIC Educational Resources Information Center

Lafond, Daniel; Lacouture, Yves; Cohen, Andrew L.

2009-01-01

The authors present 3 decision-tree models of categorization adapted from T. Trabasso, H. Rollins, and E. Shaughnessy (1971) and use them to provide a quantitative account of categorization response times, choice proportions, and typicality judgments at the individual-participant level. In Experiment 1, the decision-tree models were fit to…

Using decision trees to characterize verbal communication during change and stuck episodes in the therapeutic process

PubMed Central

Masías, Víctor H.; Krause, Mariane; Valdés, Nelson; Pérez, J. C.; Laengle, Sigifredo

2015-01-01

Methods are needed for creating models to characterize verbal communication between therapists and their patients that are suitable for teaching purposes without losing analytical potential. A technique meeting these twin requirements is proposed that uses decision trees to identify both change and stuck episodes in therapist-patient communication. Three decision tree algorithms (C4.5, NBTree, and REPTree) are applied to the problem of characterizing verbal responses into change and stuck episodes in the therapeutic process. The data for the problem is derived from a corpus of 8 successful individual therapy sessions with 1760 speaking turns in a psychodynamic context. The decision tree model that performed best was generated by the C4.5 algorithm. It delivered 15 rules characterizing the verbal communication in the two types of episodes. Decision trees are a promising technique for analyzing verbal communication during significant therapy events and have much potential for use in teaching practice on changes in therapeutic communication. The development of pedagogical methods using decision trees can support the transmission of academic knowledge to therapeutic practice. PMID:25914657

Using decision trees to characterize verbal communication during change and stuck episodes in the therapeutic process.

PubMed

Masías, Víctor H; Krause, Mariane; Valdés, Nelson; Pérez, J C; Laengle, Sigifredo

2015-01-01

Methods are needed for creating models to characterize verbal communication between therapists and their patients that are suitable for teaching purposes without losing analytical potential. A technique meeting these twin requirements is proposed that uses decision trees to identify both change and stuck episodes in therapist-patient communication. Three decision tree algorithms (C4.5, NBTree, and REPTree) are applied to the problem of characterizing verbal responses into change and stuck episodes in the therapeutic process. The data for the problem is derived from a corpus of 8 successful individual therapy sessions with 1760 speaking turns in a psychodynamic context. The decision tree model that performed best was generated by the C4.5 algorithm. It delivered 15 rules characterizing the verbal communication in the two types of episodes. Decision trees are a promising technique for analyzing verbal communication during significant therapy events and have much potential for use in teaching practice on changes in therapeutic communication. The development of pedagogical methods using decision trees can support the transmission of academic knowledge to therapeutic practice.

Computerized Adaptive Test vs. decision trees: Development of a support decision system to identify suicidal behavior.

PubMed

Delgado-Gomez, D; Baca-Garcia, E; Aguado, D; Courtet, P; Lopez-Castroman, J

2016-12-01

Several Computerized Adaptive Tests (CATs) have been proposed to facilitate assessments in mental health. These tests are built in a standard way, disregarding useful and usually available information not included in the assessment scales that could increase the precision and utility of CATs, such as the history of suicide attempts. Using the items of a previously developed scale for suicidal risk, we compared the performance of a standard CAT and a decision tree in a support decision system to identify suicidal behavior. We included the history of past suicide attempts as a class for the separation of patients in the decision tree. The decision tree needed an average of four items to achieve a similar accuracy than a standard CAT with nine items. The accuracy of the decision tree, obtained after 25 cross-validations, was 81.4%. A shortened test adapted for the separation of suicidal and non-suicidal patients was developed. CATs can be very useful tools for the assessment of suicidal risk. However, standard CATs do not use all the information that is available. A decision tree can improve the precision of the assessment since they are constructed using a priori information. Copyright © 2016 Elsevier B.V. All rights reserved.

Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets

PubMed Central

Doubravsky, Karel; Dohnal, Mirko

2015-01-01

Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details. PMID:26158662

Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets.

PubMed

Doubravsky, Karel; Dohnal, Mirko

2015-01-01

Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.

Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients.

PubMed

Freitas, Alex A; Limbu, Kriti; Ghafourian, Taravat

2015-01-01

Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied. Decision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models. Graphical AbstractDecision trees for the prediction of tissue partition coefficient and volume of distribution of drugs.

Cambial Growth Season of Brevi-Deciduous Brachystegia spiciformis Trees from South Central Africa Restricted to Less than Four Months

PubMed Central

Trouet, Valérie; Mukelabai, Mukufute; Verheyden, Anouk; Beeckman, Hans

2012-01-01

We investigate cambial growth periodicity in Brachystegia spiciformis, a dominant tree species in the seasonally dry miombo woodland of southern Africa. To better understand how the brevi-deciduous (experiencing a short, drought-induced leaf fall period) leaf phenology of this species can be linked to a distinct period of cambial activity, we applied a bi-weekly pinning to six trees in western Zambia over the course of one year. Our results show that the onset and end of cambial growth was synchronous between trees, but was not concurrent with the onset and end of the rainy season. The relatively short (three to four months maximum) cambial growth season corresponded to the core of the rainy season, when 75% of the annual precipitation fell, and to the period when the trees were at full photosynthetic capacity. Tree-ring studies of this species have found a significant relationship between annual tree growth and precipitation, but we did not observe such a correlation at intra-annual resolution in this study. Furthermore, a substantial rainfall event occurring after the end of the cambial growth season did not induce xylem initiation or false ring formation. Low sample replication should be taken into account when interpreting the results of this study, but our findings can be used to refine the carbon allocation component of process-based terrestrial ecosystem models and can thus contribute to a more detailed estimation of the role of the miombo woodland in the terrestrial carbon cycle. Furthermore, we provide a physiological foundation for the use of Brachystegia spiciformis tree-ring records in paleoclimate research. PMID:23071794

Cloud Detection from Satellite Imagery: A Comparison of Expert-Generated and Automatically-Generated Decision Trees

NASA Technical Reports Server (NTRS)

Shiffman, Smadar

2004-01-01

Automated cloud detection and tracking is an important step in assessing global climate change via remote sensing. Cloud masks, which indicate whether individual pixels depict clouds, are included in many of the data products that are based on data acquired on- board earth satellites. Many cloud-mask algorithms have the form of decision trees, which employ sequential tests that scientists designed based on empirical astrophysics studies and astrophysics simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In this study we explored the potential benefits of automatically-learned decision trees for detecting clouds from images acquired using the Advanced Very High Resolution Radiometer (AVHRR) instrument on board the NOAA-14 weather satellite of the National Oceanic and Atmospheric Administration. We constructed three decision trees for a sample of 8km-daily AVHRR data from 2000 using a decision-tree learning procedure provided within MATLAB(R), and compared the accuracy of the decision trees to the accuracy of the cloud mask. We used ground observations collected by the National Aeronautics and Space Administration Clouds and the Earth s Radiant Energy Systems S COOL project as the gold standard. For the sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks included in the AVHRR data product.

Modifiable risk factors predicting major depressive disorder at four year follow-up: a decision tree approach.

PubMed

Batterham, Philip J; Christensen, Helen; Mackinnon, Andrew J

2009-11-22

Relative to physical health conditions such as cardiovascular disease, little is known about risk factors that predict the prevalence of depression. The present study investigates the expected effects of a reduction of these risks over time, using the decision tree method favoured in assessing cardiovascular disease risk. The PATH through Life cohort was used for the study, comprising 2,105 20-24 year olds, 2,323 40-44 year olds and 2,177 60-64 year olds sampled from the community in the Canberra region, Australia. A decision tree methodology was used to predict the presence of major depressive disorder after four years of follow-up. The decision tree was compared with a logistic regression analysis using ROC curves. The decision tree was found to distinguish and delineate a wide range of risk profiles. Previous depressive symptoms were most highly predictive of depression after four years, however, modifiable risk factors such as substance use and employment status played significant roles in assessing the risk of depression. The decision tree was found to have better sensitivity and specificity than a logistic regression using identical predictors. The decision tree method was useful in assessing the risk of major depressive disorder over four years. Application of the model to the development of a predictive tool for tailored interventions is discussed.

Implementation of Data Mining to Analyze Drug Cases Using C4.5 Decision Tree

NASA Astrophysics Data System (ADS)

Wahyuni, Sri

2018-03-01

Data mining was the process of finding useful information from a large set of databases. One of the existing techniques in data mining was classification. The method used was decision tree method and algorithm used was C4.5 algorithm. The decision tree method was a method that transformed a very large fact into a decision tree which was presenting the rules. Decision tree method was useful for exploring data, as well as finding a hidden relationship between a number of potential input variables with a target variable. The decision tree of the C4.5 algorithm was constructed with several stages including the selection of attributes as roots, created a branch for each value and divided the case into the branch. These stages would be repeated for each branch until all the cases on the branch had the same class. From the solution of the decision tree there would be some rules of a case. In this case the researcher classified the data of prisoners at Labuhan Deli prison to know the factors of detainees committing criminal acts of drugs. By applying this C4.5 algorithm, then the knowledge was obtained as information to minimize the criminal acts of drugs. From the findings of the research, it was found that the most influential factor of the detainee committed the criminal act of drugs was from the address variable.

An Improved Decision Tree for Predicting a Major Product in Competing Reactions

ERIC Educational Resources Information Center

Graham, Kate J.

2014-01-01

When organic chemistry students encounter competing reactions, they are often overwhelmed by the task of evaluating multiple factors that affect the outcome of a reaction. The use of a decision tree is a useful tool to teach students to evaluate a complex situation and propose a likely outcome. Specifically, a decision tree can help students…

Decision Tree Phytoremediation

DTIC Science & Technology

1999-12-01

aromatic hydrocarbons, and landfill leachates . Phytoremediation has been used for point and nonpoint source hazardous waste control. 1.2 Types of... Phytoremediation Prepared by Interstate Technology and Regulatory Cooperation Work Group Phytoremediation Work Team December 1999 Decision Tree...1999 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE Phytoremediation Decision Tree 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c

Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data.

PubMed

Barros, Rodrigo C; Winck, Ana T; Machado, Karina S; Basgalupp, Márcio P; de Carvalho, André C P L F; Ruiz, Duncan D; de Souza, Osmar Norberto

2012-11-21

This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data

PubMed Central

2012-01-01

Background This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor. PMID:23171000

A decision tree for differentiating multiple system atrophy from Parkinson's disease using 3-T MR imaging.

PubMed

Nair, Shalini Rajandran; Tan, Li Kuo; Mohd Ramli, Norlisah; Lim, Shen Yang; Rahmat, Kartini; Mohd Nor, Hazman

2013-06-01

To develop a decision tree based on standard magnetic resonance imaging (MRI) and diffusion tensor imaging to differentiate multiple system atrophy (MSA) from Parkinson's disease (PD). 3-T brain MRI and DTI (diffusion tensor imaging) were performed on 26 PD and 13 MSA patients. Regions of interest (ROIs) were the putamen, substantia nigra, pons, middle cerebellar peduncles (MCP) and cerebellum. Linear, volumetry and DTI (fractional anisotropy and mean diffusivity) were measured. A three-node decision tree was formulated, with design goals being 100 % specificity at node 1, 100 % sensitivity at node 2 and highest combined sensitivity and specificity at node 3. Nine parameters (mean width, fractional anisotropy (FA) and mean diffusivity (MD) of MCP; anteroposterior diameter of pons; cerebellar FA and volume; pons and mean putamen volume; mean FA substantia nigra compacta-rostral) showed statistically significant (P < 0.05) differences between MSA and PD with mean MCP width, anteroposterior diameter of pons and mean FA MCP chosen for the decision tree. Threshold values were 14.6 mm, 21.8 mm and 0.55, respectively. Overall performance of the decision tree was 92 % sensitivity, 96 % specificity, 92 % PPV and 96 % NPV. Twelve out of 13 MSA patients were accurately classified. Formation of the decision tree using these parameters was both descriptive and predictive in differentiating between MSA and PD. • Parkinson's disease and multiple system atrophy can be distinguished on MR imaging. • Combined conventional MRI and diffusion tensor imaging improves the accuracy of diagnosis. • A decision tree is descriptive and predictive in differentiating between clinical entities. • A decision tree can reliably differentiate Parkinson's disease from multiple system atrophy.

Application of preprocessing filtering on Decision Tree C4.5 and rough set theory

NASA Astrophysics Data System (ADS)

Chan, Joseph C. C.; Lin, Tsau Y.

2001-03-01

This paper compares two artificial intelligence methods: the Decision Tree C4.5 and Rough Set Theory on the stock market data. The Decision Tree C4.5 is reviewed with the Rough Set Theory. An enhanced window application is developed to facilitate the pre-processing filtering by introducing the feature (attribute) transformations, which allows users to input formulas and create new attributes. Also, the application produces three varieties of data set with delaying, averaging, and summation. The results prove the improvement of pre-processing by applying feature (attribute) transformations on Decision Tree C4.5. Moreover, the comparison between Decision Tree C4.5 and Rough Set Theory is based on the clarity, automation, accuracy, dimensionality, raw data, and speed, which is supported by the rules sets generated by both algorithms on three different sets of data.

Hydrological Response and Complex Impact Pathways of the 2015/2016 El Niño in Eastern and Southern Africa

NASA Astrophysics Data System (ADS)

Siderius, C.; Gannon, K. E.; Ndiyoi, M.; Opere, A.; Batisani, N.; Olago, D.; Pardoe, J.; Conway, D.

2018-01-01

The 2015/2016 El Niño has been classified as one of the three most severe on record. El Niño teleconnections are commonly associated with droughts in southern Africa and high precipitation in eastern Africa. Despite their relatively frequent occurrence, evidence for their hydrological effects and impacts beyond agriculture is limited. We examine the hydrological response and impact pathways of the 2015/2016 El Niño in eastern and southern Africa, focusing on Botswana, Kenya, and Zambia. We use in situ and remotely sensed time series of precipitation, river flow, and lake levels complemented by qualitative insights from interviews with key organizations in each country about awareness, impacts, and responses. Our results show that drought conditions prevailed in large parts of southern Africa, reducing runoff and contributing to unusually low lake levels in Botswana and Zambia. Key informants characterized this El Niño through record high temperatures and water supply disruption in Botswana and through hydroelectric load shedding in Zambia. Warnings of flood risk in Kenya were pronounced, but the El Niño teleconnection did not materialize as expected in 2015/2016. Extreme precipitation was limited and caused localized impacts. The hydrological impacts in southern Africa were severe and complex, strongly exacerbated by dry antecedent conditions, recent changes in exposure and sensitivity and management decisions. Improved understanding of hydrological responses and the complexity of differing impact pathways can support design of more adaptive, region-specific management strategies.

Multivariate analysis of flow cytometric data using decision trees.

PubMed

Simon, Svenja; Guthke, Reinhard; Kamradt, Thomas; Frey, Oliver

2012-01-01

Characterization of the response of the host immune system is important in understanding the bidirectional interactions between the host and microbial pathogens. For research on the host site, flow cytometry has become one of the major tools in immunology. Advances in technology and reagents allow now the simultaneous assessment of multiple markers on a single cell level generating multidimensional data sets that require multivariate statistical analysis. We explored the explanatory power of the supervised machine learning method called "induction of decision trees" in flow cytometric data. In order to examine whether the production of a certain cytokine is depended on other cytokines, datasets from intracellular staining for six cytokines with complex patterns of co-expression were analyzed by induction of decision trees. After weighting the data according to their class probabilities, we created a total of 13,392 different decision trees for each given cytokine with different parameter settings. For a more realistic estimation of the decision trees' quality, we used stratified fivefold cross validation and chose the "best" tree according to a combination of different quality criteria. While some of the decision trees reflected previously known co-expression patterns, we found that the expression of some cytokines was not only dependent on the co-expression of others per se, but was also dependent on the intensity of expression. Thus, for the first time we successfully used induction of decision trees for the analysis of high dimensional flow cytometric data and demonstrated the feasibility of this method to reveal structural patterns in such data sets.

The Role of Open and Distance Learning in the Implementation of the Right to Education in Zambia

ERIC Educational Resources Information Center

Siaciwena, Richard; Lubinda, Foster

2008-01-01

As a member of the United Nations, Zambia is committed to the observance of human rights enshrined in the Universal Declaration of Human Rights of 1948. This is evidenced, among others, by the fact that Zambia is a signatory to the Convention on the Rights of the Child and the African Charter on the Rights and Welfare of the Child. Zambia has a…

15 CFR Supplement 1 to Part 732 - Decision Tree

Code of Federal Regulations, 2010 CFR

2010-01-01

... 15 Commerce and Foreign Trade 2 2010-01-01 2010-01-01 false Decision Tree 1 Supplement 1 to Part 732 Commerce and Foreign Trade Regulations Relating to Commerce and Foreign Trade (Continued) BUREAU... THE EAR Pt. 732, Supp. 1 Supplement 1 to Part 732—Decision Tree ER06FE04.000 [69 FR 5687, Feb. 6, 2004] ...

15 CFR Supplement No 1 to Part 732 - Decision Tree

Code of Federal Regulations, 2013 CFR

2013-01-01

... 15 Commerce and Foreign Trade 2 2013-01-01 2013-01-01 false Decision Tree No Supplement No 1 to Part 732 Commerce and Foreign Trade Regulations Relating to Commerce and Foreign Trade (Continued... THE EAR Pt. 732, Supp. 1 Supplement No 1 to Part 732—Decision Tree ER06FE04.000 [69 FR 5687, Feb. 6...

15 CFR Supplement No 1 to Part 732 - Decision Tree

Code of Federal Regulations, 2014 CFR

2014-01-01

... 15 Commerce and Foreign Trade 2 2014-01-01 2014-01-01 false Decision Tree No Supplement No 1 to Part 732 Commerce and Foreign Trade Regulations Relating to Commerce and Foreign Trade (Continued... THE EAR Pt. 732, Supp. 1 Supplement No 1 to Part 732—Decision Tree ER06FE04.000 [69 FR 5687, Feb. 6...

15 CFR Supplement 1 to Part 732 - Decision Tree

Code of Federal Regulations, 2012 CFR

2012-01-01

... 15 Commerce and Foreign Trade 2 2012-01-01 2012-01-01 false Decision Tree 1 Supplement 1 to Part 732 Commerce and Foreign Trade Regulations Relating to Commerce and Foreign Trade (Continued) BUREAU... THE EAR Pt. 732, Supp. 1 Supplement 1 to Part 732—Decision Tree ER06FE04.000 [69 FR 5687, Feb. 6, 2004] ...

15 CFR Supplement 1 to Part 732 - Decision Tree

Code of Federal Regulations, 2011 CFR

2011-01-01

... 15 Commerce and Foreign Trade 2 2011-01-01 2011-01-01 false Decision Tree 1 Supplement 1 to Part 732 Commerce and Foreign Trade Regulations Relating to Commerce and Foreign Trade (Continued) BUREAU... THE EAR Pt. 732, Supp. 1 Supplement 1 to Part 732—Decision Tree ER06FE04.000 [69 FR 5687, Feb. 6, 2004] ...

Improved Frame Mode Selection for AMR-WB+ Based on Decision Tree

NASA Astrophysics Data System (ADS)

Kim, Jong Kyu; Kim, Nam Soo

In this letter, we propose a coding mode selection method for the AMR-WB+ audio coder based on a decision tree. In order to reduce computation while maintaining good performance, decision tree classifier is adopted with the closed loop mode selection results as the target classification labels. The size of the decision tree is controlled by pruning, so the proposed method does not increase the memory requirement significantly. Through an evaluation test on a database covering both speech and music materials, the proposed method is found to achieve a much better mode selection accuracy compared with the open loop mode selection module in the AMR-WB+.

Activity classification using realistic data from wearable sensors.

PubMed

Pärkkä, Juha; Ermes, Miikka; Korpipää, Panu; Mäntyjärvi, Jani; Peltola, Johannes; Korhonen, Ilkka

2006-01-01

Automatic classification of everyday activities can be used for promotion of health-enhancing physical activities and a healthier lifestyle. In this paper, methods used for classification of everyday activities like walking, running, and cycling are described. The aim of the study was to find out how to recognize activities, which sensors are useful and what kind of signal processing and classification is required. A large and realistic data library of sensor data was collected. Sixteen test persons took part in the data collection, resulting in approximately 31 h of annotated, 35-channel data recorded in an everyday environment. The test persons carried a set of wearable sensors while performing several activities during the 2-h measurement session. Classification results of three classifiers are shown: custom decision tree, automatically generated decision tree, and artificial neural network. The classification accuracies using leave-one-subject-out cross validation range from 58 to 97% for custom decision tree classifier, from 56 to 97% for automatically generated decision tree, and from 22 to 96% for artificial neural network. Total classification accuracy is 82 % for custom decision tree classifier, 86% for automatically generated decision tree, and 82% for artificial neural network.

A universal hybrid decision tree classifier design for human activity classification.

PubMed

Chien, Chieh; Pottie, Gregory J

2012-01-01

A system that reliably classifies daily life activities can contribute to more effective and economical treatments for patients with chronic conditions or undergoing rehabilitative therapy. We propose a universal hybrid decision tree classifier for this purpose. The tree classifier can flexibly implement different decision rules at its internal nodes, and can be adapted from a population-based model when supplemented by training data for individuals. The system was tested using seven subjects each monitored by 14 triaxial accelerometers. Each subject performed fourteen different activities typical of daily life. Using leave-one-out cross validation, our decision tree produced average classification accuracies of 89.9%. In contrast, the MATLAB personalized tree classifiers using Gini's diversity index as the split criterion followed by optimally tuning the thresholds for each subject yielded 69.2%.

An Isometric Mapping Based Co-Location Decision Tree Algorithm

NASA Astrophysics Data System (ADS)

Zhou, G.; Wei, J.; Zhou, X.; Zhang, R.; Huang, W.; Sha, H.; Chen, J.

2018-05-01

Decision tree (DT) induction has been widely used in different pattern classification. However, most traditional DTs have the disadvantage that they consider only non-spatial attributes (ie, spectral information) as a result of classifying pixels, which can result in objects being misclassified. Therefore, some researchers have proposed a co-location decision tree (Cl-DT) method, which combines co-location and decision tree to solve the above the above-mentioned traditional decision tree problems. Cl-DT overcomes the shortcomings of the existing DT algorithms, which create a node for each value of a given attribute, which has a higher accuracy than the existing decision tree approach. However, for non-linearly distributed data instances, the euclidean distance between instances does not reflect the true positional relationship between them. In order to overcome these shortcomings, this paper proposes an isometric mapping method based on Cl-DT (called, (Isomap-based Cl-DT), which is a method that combines heterogeneous and Cl-DT together. Because isometric mapping methods use geodetic distances instead of Euclidean distances between non-linearly distributed instances, the true distance between instances can be reflected. The experimental results and several comparative analyzes show that: (1) The extraction method of exposed carbonate rocks is of high accuracy. (2) The proposed method has many advantages, because the total number of nodes, the number of leaf nodes and the number of nodes are greatly reduced compared to Cl-DT. Therefore, the Isomap -based Cl-DT algorithm can construct a more accurate and faster decision tree.

Development of a New Decision Tree to Rapidly Screen Chemical Estrogenic Activities of Xenopus laevis.

PubMed

Wang, Ting; Li, Weiying; Zheng, Xiaofeng; Lin, Zhifen; Kong, Deyang

2014-02-01

During the last past decades, there is an increasing number of studies about estrogenic activities of the environmental pollutants on amphibians and many determination methods have been proposed. However, these determination methods are time-consuming and expensive, and a rapid and simple method to screen and test the chemicals for estrogenic activities to amphibians is therefore imperative. Herein is proposed a new decision tree formulated not only with physicochemical parameters but also a biological parameter that was successfully used to screen estrogenic activities of the chemicals on amphibians. The biological parameter, CDOCKER interaction energy (Ebinding ) between chemicals and the target proteins was calculated based on the method of molecular docking, and it was used to revise the decision tree formulated by Hong only with physicochemical parameters for screening estrogenic activity of chemicals in rat. According to the correlation between Ebinding of rat and Xenopus laevis, a new decision tree for estrogenic activities in Xenopus laevis is finally proposed. Then it was validated by using the randomly 8 chemicals which can be frequently exposed to Xenopus laevis, and the agreement between the results from the new decision tree and the ones from experiments is generally satisfactory. Consequently, the new decision tree can be used to screen the estrogenic activities of the chemicals, and combinational use of the Ebinding and classical physicochemical parameters can greatly improves Hong's decision tree. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparing wavefront-optimized, wavefront-guided and topography-guided laser vision correction: clinical outcomes using an objective decision tree.

PubMed

Stonecipher, Karl; Parrish, Joseph; Stonecipher, Megan

2018-05-18

This review is intended to update and educate the reader on the currently available options for laser vision correction, more specifically, laser-assisted in-situ keratomileusis (LASIK). In addition, some related clinical outcomes data from over 1000 cases performed over a 1-year are presented to highlight some differences between the various treatment profiles currently available including the rapidity of visual recovery. The cases in question were performed on the basis of a decision tree to segregate patients on the basis of anatomical, topographic and aberrometry findings; the decision tree was formulated based on the data available in some of the reviewed articles. Numerous recent studies reported in the literature provide data related to the risks and benefits of LASIK; alternatives to a laser refractive procedure are also discussed. The results from these studies have been used to prepare a decision tree to assist the surgeon in choosing the best option for the patient based on the data from several standard preoperative diagnostic tests. The data presented here should aid surgeons in understanding the effects of currently available LASIK treatment profiles. Surgeons should also be able to appreciate how the findings were used to create a decision tree to help choose the most appropriate treatment profile for patients. Finally, the retrospective evaluation of clinical outcomes based on the decision tree should provide surgeons with a realistic expectation for their own outcomes should they adopt such a decision tree in their own practice.

Comparative analysis of tree classification models for detecting fusarium oxysporum f. sp cubense (TR4) based on multi soil sensor parameters

NASA Astrophysics Data System (ADS)

Estuar, Maria Regina Justina; Victorino, John Noel; Coronel, Andrei; Co, Jerelyn; Tiausas, Francis; Señires, Chiara Veronica

2017-09-01

Use of wireless sensor networks and smartphone integration design to monitor environmental parameters surrounding plantations is made possible because of readily available and affordable sensors. Providing low cost monitoring devices would be beneficial, especially to small farm owners, in a developing country like the Philippines, where agriculture covers a significant amount of the labor market. This study discusses the integration of wireless soil sensor devices and smartphones to create an application that will use multidimensional analysis to detect the presence or absence of plant disease. Specifically, soil sensors are designed to collect soil quality parameters in a sink node from which the smartphone collects data from via Bluetooth. Given these, there is a need to develop a classification model on the mobile phone that will report infection status of a soil. Though tree classification is the most appropriate approach for continuous parameter-based datasets, there is a need to determine whether tree models will result to coherent results or not. Soil sensor data that resides on the phone is modeled using several variations of decision tree, namely: decision tree (DT), best-fit (BF) decision tree, functional tree (FT), Naive Bayes (NB) decision tree, J48, J48graft and LAD tree, where decision tree approaches the problem by considering all sensor nodes as one. Results show that there are significant differences among soil sensor parameters indicating that there are variances in scores between the infected and uninfected sites. Furthermore, analysis of variance in accuracy, recall, precision and F1 measure scores from tree classification models homogeneity among NBTree, J48graft and J48 tree classification models.

Aneurysmal subarachnoid hemorrhage prognostic decision-making algorithm using classification and regression tree analysis.

PubMed

Lo, Benjamin W Y; Fukuda, Hitoshi; Angle, Mark; Teitelbaum, Jeanne; Macdonald, R Loch; Farrokhyar, Forough; Thabane, Lehana; Levine, Mitchell A H

2016-01-01

Classification and regression tree analysis involves the creation of a decision tree by recursive partitioning of a dataset into more homogeneous subgroups. Thus far, there is scarce literature on using this technique to create clinical prediction tools for aneurysmal subarachnoid hemorrhage (SAH). The classification and regression tree analysis technique was applied to the multicenter Tirilazad database (3551 patients) in order to create the decision-making algorithm. In order to elucidate prognostic subgroups in aneurysmal SAH, neurologic, systemic, and demographic factors were taken into account. The dependent variable used for analysis was the dichotomized Glasgow Outcome Score at 3 months. Classification and regression tree analysis revealed seven prognostic subgroups. Neurological grade, occurrence of post-admission stroke, occurrence of post-admission fever, and age represented the explanatory nodes of this decision tree. Split sample validation revealed classification accuracy of 79% for the training dataset and 77% for the testing dataset. In addition, the occurrence of fever at 1-week post-aneurysmal SAH is associated with increased odds of post-admission stroke (odds ratio: 1.83, 95% confidence interval: 1.56-2.45, P < 0.01). A clinically useful classification tree was generated, which serves as a prediction tool to guide bedside prognostication and clinical treatment decision making. This prognostic decision-making algorithm also shed light on the complex interactions between a number of risk factors in determining outcome after aneurysmal SAH.

Distribution and phenology of ixodid ticks in southern Zambia.

PubMed

Speybroeck, N; Madder, M; Van Den Bossche, P; Mtambo, J; Berkvens, N; Chaka, G; Mulumba, M; Brandt, J; Tirry, L; Berkvens, D

2002-12-01

Distribution data for epidemiologically important ticks (Acari: Ixodidae) in the Southern Province of Zambia, one of the main cattle areas of the country, are presented. Boophilus microplus (Canestrini) was not recorded in southern Zambia, whereas Boophilus decoloratus (Koch) is present throughout the area. New distribution patterns for less economically important ixodid ticks are also discussed. Southern Zambia is a transition zone because it is the most northern area in Africa where mixed Rhipicephalus appendiculatus Neumann and Rhipicephalus zambeziensis Walker, Norval & Corwin populations were reported. Although a second generation of adult R. appendiculatus/R. zamnbeziensis was encountered, simulations indicated that this phenomenon is very rare in southern Zambia, mainly because of the colder temperatures during the early dry season and lower rainfall. These simulations were supported by a development trial under experimental conditions. Tick body size measurements showed that southern Zambian ticks are larger than eastern Zambian R. appendiculatus. It is hypothesized that body size is related to diapausing intensity in this species. The epidemiological consequences are that a different approach to control Theileria parva (Theiler) (Piroplasmida: Theileriidae) and other tick-borne diseases is needed in southern Zambia, compared to the one adopted in eastern Zambia.

Promotion of exclusive breastfeeding among HIV-positive mothers: an exploratory qualitative study.

PubMed

Hazemba, Alice N; Ncama, Busisiwe P; Sithole, Sello L

2016-01-01

Exclusive breastfeeding has the potential to reduce infant and under-five mortality, but research shows the practice is not widespread in resource-poor settings of sub-Saharan Africa. We explored factors influencing the decision to exclusively breastfeed among HIV-positive mothers accessing interventions for prevention of mother-to-child transmission of HIV in selected sites of Zambia. This exploratory qualitative study was embedded in research conducted on: HIV and infant feeding; choices and decision-outcomes in the context of prevention of mother-to-child transmission among HIV-positive mothers in Zambia. Thirty HIV-positive mothers and six key informants were recruited from two health facilities providing mother-to-child HIV transmission prevention services. A semi-structured guide was used to conduct interviews, which were digitally recorded and simultaneously transcribed. Data coding and analysis was done with the support of QRS Nvivo 10 version software. Despite the known benefits of exclusive breastfeeding, gaps in understanding and potential for behaviour change remained. We found that information promoting exclusive breastfeeding may have been understood by mothers as instructions from the health care workers indicating how to feed their HIV-exposed babies rather than as an option for the mothers' own informed-decision. This understanding influenced a mother's perceptions of breast milk safety while on antiretroviral medicine, of the formula feeding option, and of the baby crying after breastfeeding. The meanings mothers attached to exclusive breastfeeding thus influenced their understanding of breast milk insufficiency, abrupt weaning and mixed feeding in the context of preventing mother-to-child transmission of HIV. In order to enhance feeding practices for HIV-exposed infants, our study suggests a broader health campaign supporting all mothers to exclusively breastfeed.

A survey of decision tree classifier methodology

NASA Technical Reports Server (NTRS)

Safavian, S. R.; Landgrebe, David

1991-01-01

Decision tree classifiers (DTCs) are used successfully in many diverse areas such as radar signal classification, character recognition, remote sensing, medical diagnosis, expert systems, and speech recognition. Perhaps the most important feature of DTCs is their capability to break down a complex decision-making process into a collection of simpler decisions, thus providing a solution which is often easier to interpret. A survey of current methods is presented for DTC designs and the various existing issues. After considering potential advantages of DTCs over single-state classifiers, subjects of tree structure design, feature selection at each internal node, and decision and search strategies are discussed.

A survey of decision tree classifier methodology

NASA Technical Reports Server (NTRS)

Safavian, S. Rasoul; Landgrebe, David

1990-01-01

Decision Tree Classifiers (DTC's) are used successfully in many diverse areas such as radar signal classification, character recognition, remote sensing, medical diagnosis, expert systems, and speech recognition. Perhaps, the most important feature of DTC's is their capability to break down a complex decision-making process into a collection of simpler decisions, thus providing a solution which is often easier to interpret. A survey of current methods is presented for DTC designs and the various existing issue. After considering potential advantages of DTC's over single stage classifiers, subjects of tree structure design, feature selection at each internal node, and decision and search strategies are discussed.

Development of a diagnostic decision tree for obstructive pulmonary diseases based on real-life data

PubMed Central

in ’t Veen, Johannes C.C.M.; Dekhuijzen, P.N. Richard; van Heijst, Ellen; Kocks, Janwillem W.H.; Muilwijk-Kroes, Jacqueline B.; Chavannes, Niels H.; van der Molen, Thys

2016-01-01

The aim of this study was to develop and explore the diagnostic accuracy of a decision tree derived from a large real-life primary care population. Data from 9297 primary care patients (45% male, mean age 53±17 years) with suspicion of an obstructive pulmonary disease was derived from an asthma/chronic obstructive pulmonary disease (COPD) service where patients were assessed using spirometry, the Asthma Control Questionnaire, the Clinical COPD Questionnaire, history data and medication use. All patients were diagnosed through the Internet by a pulmonologist. The Chi-squared Automatic Interaction Detection method was used to build the decision tree. The tree was externally validated in another real-life primary care population (n=3215). Our tree correctly diagnosed 79% of the asthma patients, 85% of the COPD patients and 32% of the asthma–COPD overlap syndrome (ACOS) patients. External validation showed a comparable pattern (correct: asthma 78%, COPD 83%, ACOS 24%). Our decision tree is considered to be promising because it was based on real-life primary care patients with a specialist's diagnosis. In most patients the diagnosis could be correctly predicted. Predicting ACOS, however, remained a challenge. The total decision tree can be implemented in computer-assisted diagnostic systems for individual patients. A simplified version of this tree can be used in daily clinical practice as a desk tool. PMID:27730177

Evolving optimised decision rules for intrusion detection using particle swarm paradigm

NASA Astrophysics Data System (ADS)

Sivatha Sindhu, Siva S.; Geetha, S.; Kannan, A.

2012-12-01

The aim of this article is to construct a practical intrusion detection system (IDS) that properly analyses the statistics of network traffic pattern and classify them as normal or anomalous class. The objective of this article is to prove that the choice of effective network traffic features and a proficient machine-learning paradigm enhances the detection accuracy of IDS. In this article, a rule-based approach with a family of six decision tree classifiers, namely Decision Stump, C4.5, Naive Baye's Tree, Random Forest, Random Tree and Representative Tree model to perform the detection of anomalous network pattern is introduced. In particular, the proposed swarm optimisation-based approach selects instances that compose training set and optimised decision tree operate over this trained set producing classification rules with improved coverage, classification capability and generalisation ability. Experiment with the Knowledge Discovery and Data mining (KDD) data set which have information on traffic pattern, during normal and intrusive behaviour shows that the proposed algorithm produces optimised decision rules and outperforms other machine-learning algorithm.

A Decision Tree for Nonmetric Sex Assessment from the Skull.

PubMed

Langley, Natalie R; Dudzik, Beatrix; Cloutier, Alesia

2018-01-01

This study uses five well-documented cranial nonmetric traits (glabella, mastoid process, mental eminence, supraorbital margin, and nuchal crest) and one additional trait (zygomatic extension) to develop a validated decision tree for sex assessment. The decision tree was built and cross-validated on a sample of 293 U.S. White individuals from the William M. Bass Donated Skeletal Collection. Ordinal scores from the six traits were analyzed using the partition modeling option in JMP Pro 12. A holdout sample of 50 skulls was used to test the model. The most accurate decision tree includes three variables: glabella, zygomatic extension, and mastoid process. This decision tree yielded 93.5% accuracy on the training sample, 94% on the cross-validated sample, and 96% on a holdout validation sample. Linear weighted kappa statistics indicate acceptable agreement among observers for these variables. Mental eminence should be avoided, and definitions and figures should be referenced carefully to score nonmetric traits. © 2017 American Academy of Forensic Sciences.

A framework for sensitivity analysis of decision trees.

PubMed

Kamiński, Bogumił; Jakubczyk, Michał; Szufel, Przemysław

2018-01-01

In the paper, we consider sequential decision problems with uncertainty, represented as decision trees. Sensitivity analysis is always a crucial element of decision making and in decision trees it often focuses on probabilities. In the stochastic model considered, the user often has only limited information about the true values of probabilities. We develop a framework for performing sensitivity analysis of optimal strategies accounting for this distributional uncertainty. We design this robust optimization approach in an intuitive and not overly technical way, to make it simple to apply in daily managerial practice. The proposed framework allows for (1) analysis of the stability of the expected-value-maximizing strategy and (2) identification of strategies which are robust with respect to pessimistic/optimistic/mode-favoring perturbations of probabilities. We verify the properties of our approach in two cases: (a) probabilities in a tree are the primitives of the model and can be modified independently; (b) probabilities in a tree reflect some underlying, structural probabilities, and are interrelated. We provide a free software tool implementing the methods described.

Learning accurate very fast decision trees from uncertain data streams

NASA Astrophysics Data System (ADS)

Liang, Chunquan; Zhang, Yang; Shi, Peng; Hu, Zhengguo

2015-12-01

Most existing works on data stream classification assume the streaming data is precise and definite. Such assumption, however, does not always hold in practice, since data uncertainty is ubiquitous in data stream applications due to imprecise measurement, missing values, privacy protection, etc. The goal of this paper is to learn accurate decision tree models from uncertain data streams for classification analysis. On the basis of very fast decision tree (VFDT) algorithms, we proposed an algorithm for constructing an uncertain VFDT tree with classifiers at tree leaves (uVFDTc). The uVFDTc algorithm can exploit uncertain information effectively and efficiently in both the learning and the classification phases. In the learning phase, it uses Hoeffding bound theory to learn from uncertain data streams and yield fast and reasonable decision trees. In the classification phase, at tree leaves it uses uncertain naive Bayes (UNB) classifiers to improve the classification performance. Experimental results on both synthetic and real-life datasets demonstrate the strong ability of uVFDTc to classify uncertain data streams. The use of UNB at tree leaves has improved the performance of uVFDTc, especially the any-time property, the benefit of exploiting uncertain information, and the robustness against uncertainty.

Real-Time Speech/Music Classification With a Hierarchical Oblique Decision Tree

DTIC Science & Technology

2008-04-01

REAL-TIME SPEECH/ MUSIC CLASSIFICATION WITH A HIERARCHICAL OBLIQUE DECISION TREE Jun Wang, Qiong Wu, Haojiang Deng, Qin Yan Institute of Acoustics...time speech/ music classification with a hierarchical oblique decision tree. A set of discrimination features in frequency domain are selected...handle signals without discrimination and can not work properly in the existence of multimedia signals. This paper proposes a real-time speech/ music

PCA based feature reduction to improve the accuracy of decision tree c4.5 classification

NASA Astrophysics Data System (ADS)

Nasution, M. Z. F.; Sitompul, O. S.; Ramli, M.

2018-03-01

Splitting attribute is a major process in Decision Tree C4.5 classification. However, this process does not give a significant impact on the establishment of the decision tree in terms of removing irrelevant features. It is a major problem in decision tree classification process called over-fitting resulting from noisy data and irrelevant features. In turns, over-fitting creates misclassification and data imbalance. Many algorithms have been proposed to overcome misclassification and overfitting on classifications Decision Tree C4.5. Feature reduction is one of important issues in classification model which is intended to remove irrelevant data in order to improve accuracy. The feature reduction framework is used to simplify high dimensional data to low dimensional data with non-correlated attributes. In this research, we proposed a framework for selecting relevant and non-correlated feature subsets. We consider principal component analysis (PCA) for feature reduction to perform non-correlated feature selection and Decision Tree C4.5 algorithm for the classification. From the experiments conducted using available data sets from UCI Cervical cancer data set repository with 858 instances and 36 attributes, we evaluated the performance of our framework based on accuracy, specificity and precision. Experimental results show that our proposed framework is robust to enhance classification accuracy with 90.70% accuracy rates.

[Comparison of Discriminant Analysis and Decision Trees for the Detection of Subclinical Keratoconus].

PubMed

Kleinhans, Sonja; Herrmann, Eva; Kohnen, Thomas; Bühren, Jens

2017-08-15

Background Iatrogenic keratectasia is one of the most dreaded complications of refractive surgery. In most cases, keratectasia develops after refractive surgery of eyes suffering from subclinical stages of keratoconus with few or no signs. Unfortunately, there has been no reliable procedure for the early detection of keratoconus. In this study, we used binary decision trees (recursive partitioning) to assess their suitability for discrimination between normal eyes and eyes with subclinical keratoconus. Patients and Methods The method of decision tree analysis was compared with discriminant analysis which has shown good results in previous studies. Input data were 32 eyes of 32 patients with newly diagnosed keratoconus in the contralateral eye and preoperative data of 10 eyes of 5 patients with keratectasia after laser in-situ keratomileusis (LASIK). The control group was made up of 245 normal eyes after LASIK and 12-month follow-up without any signs of iatrogenic keratectasia. Results Decision trees gave better accuracy and specificity than did discriminant analysis. The sensitivity of decision trees was lower than the sensitivity of discriminant analysis. Conclusion On the basis of the patient population of this study, decision trees did not prove to be superior to linear discriminant analysis for the detection of subclinical keratoconus. Georg Thieme Verlag KG Stuttgart · New York.

Pruning a decision tree for selecting computer-related assistive devices for people with disabilities.

PubMed

Chi, Chia-Fen; Tseng, Li-Kai; Jang, Yuh

2012-07-01

Many disabled individuals lack extensive knowledge about assistive technology, which could help them use computers. In 1997, Denis Anson developed a decision tree of 49 evaluative questions designed to evaluate the functional capabilities of the disabled user and choose an appropriate combination of assistive devices, from a selection of 26, that enable the individual to use a computer. In general, occupational therapists guide the disabled users through this process. They often have to go over repetitive questions in order to find an appropriate device. A disabled user may require an alphanumeric entry device, a pointing device, an output device, a performance enhancement device, or some combination of these. Therefore, the current research eliminates redundant questions and divides Anson's decision tree into multiple independent subtrees to meet the actual demand of computer users with disabilities. The modified decision tree was tested by six disabled users to prove it can determine a complete set of assistive devices with a smaller number of evaluative questions. The means to insert new categories of computer-related assistive devices was included to ensure the decision tree can be expanded and updated. The current decision tree can help the disabled users and assistive technology practitioners to find appropriate computer-related assistive devices that meet with clients' individual needs in an efficient manner.

Uncertain decision tree inductive inference

NASA Astrophysics Data System (ADS)

Zarban, L.; Jafari, S.; Fakhrahmad, S. M.

2011-10-01

Induction is the process of reasoning in which general rules are formulated based on limited observations of recurring phenomenal patterns. Decision tree learning is one of the most widely used and practical inductive methods, which represents the results in a tree scheme. Various decision tree algorithms have already been proposed such as CLS, ID3, Assistant C4.5, REPTree and Random Tree. These algorithms suffer from some major shortcomings. In this article, after discussing the main limitations of the existing methods, we introduce a new decision tree induction algorithm, which overcomes all the problems existing in its counterparts. The new method uses bit strings and maintains important information on them. This use of bit strings and logical operation on them causes high speed during the induction process. Therefore, it has several important features: it deals with inconsistencies in data, avoids overfitting and handles uncertainty. We also illustrate more advantages and the new features of the proposed method. The experimental results show the effectiveness of the method in comparison with other methods existing in the literature.

77 FR 60966 - Executive-Led Trade Mission to South Africa and Zambia

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-05

... Africa and Zambia AGENCY: International Trade Administration, Department of Commerce. ACTION: Notice...- Led Trade Mission to South Africa and Zambia scheduled for November 26- 30, 2012, to revise the dates... and scheduling constraints permit), interested U.S. agriculture, mining, transportation, water, energy...

Comparative Issues and Methods in Organizational Diagnosis. Report II. The Decision Tree Approach.

DTIC Science & Technology

organizational diagnosis . The advantages and disadvantages of the decision-tree approach generally, and in this study specifically, are examined. A pre-test, using a civilian sample of 174 work groups with Survey of Organizations data, was conducted to assess various decision-tree classification criteria, in terms of their similarity to the distance function used by Bowers and Hausser (1977). The results suggested the use of a large developmental sample, which should result in more distinctly defined boundary lines between classification profiles. Also, the decision matrix

FDT 2.0: Improving scalability of the fuzzy decision tree induction tool - integrating database storage.

PubMed

Durham, Erin-Elizabeth A; Yu, Xiaxia; Harrison, Robert W

2014-12-01

Effective machine-learning handles large datasets efficiently. One key feature of handling large data is the use of databases such as MySQL. The freeware fuzzy decision tree induction tool, FDT, is a scalable supervised-classification software tool implementing fuzzy decision trees. It is based on an optimized fuzzy ID3 (FID3) algorithm. FDT 2.0 improves upon FDT 1.0 by bridging the gap between data science and data engineering: it combines a robust decisioning tool with data retention for future decisions, so that the tool does not need to be recalibrated from scratch every time a new decision is required. In this paper we briefly review the analytical capabilities of the freeware FDT tool and its major features and functionalities; examples of large biological datasets from HIV, microRNAs and sRNAs are included. This work shows how to integrate fuzzy decision algorithms with modern database technology. In addition, we show that integrating the fuzzy decision tree induction tool with database storage allows for optimal user satisfaction in today's Data Analytics world.

Increased fairness in priority setting processes within the health sector: the case of Kapiri-Mposhi District, Zambia

PubMed Central

2014-01-01

Background The challenge of priority setting (PS) in health care within contexts of severe resource limitations has continued to receive attention. Accountability for Reasonableness (AFR) has emerged as a useful framework to guide the implementation of PS processes. In 2006, the AFR approach to enhance legitimate and fair PS was introduced by researchers and decision makers within the health sector in the EU funded research project entitled ‘Response to Accountable priority setting for Trust in health systems’ (REACT). The project aimed to strengthen fairness and accountability in the PS processes of health systems at district level in Zambia, Tanzania and Kenya. This paper focuses on local perceptions and practices of fair PS (baseline study) as well as at the evolution of such perceptions and practices in PS following an AFR based intervention (evaluation study), carried out at district level in Kapiri-Mposhi District in Zambia. Methods Data was collected using in depth interviews (IDIs), focus group discussions (FGDs) and review of documents from national to district level. The study population for this paper consisted of health related stakeholders employed in the district administration, in non-governmental organizations (NGO) and in health facilities. Results During the baseline study, concepts of legitimacy and fairness in PS processes were found to be grounded in local values of equity and impartiality. Government and other organizational strategies strongly supported devolution of PS and decision making procedures. However, important gaps were identified in terms of experiences of stakeholder involvement and fairness in PS processes in practice. The evaluation study revealed that a transformation of the views and methods regarding fairness in PS processes was ongoing in the study district, which was partly attributed to the AFR based intervention. Conclusions The study findings suggest that increased attention was given to fairness in PS processes at district level. The changes were linked to a number of simultaneous factors among them the concepts introduced by the present project with its emphasis on fairness and enhanced participation. A responsive leadership that was increasingly accountable to its operational staff and communities emerged as one of the key elements in driving the processes forward. PMID:24548767

The equity impacts of community financing activities in three African countries.

PubMed

Gilson, L; Kalyalya, D; Kuchler, F; Lake, S; Oranga, H; Ouendo, M

2000-01-01

Although the Bamako Initiative from its very beginning was caught up in wider debates about the potential equity impact of any form of user financing, to date there has been little empirical investigation of this impact. This three-country study, undertaken in Benin, Kenya and Zambia in 1994/95, was initiated to add to the body of relevant evidence. It sought to understand not only what had been the equity impacts of community financing activities in these countries but also how they had been brought about. As a result, it investigated equity primarily through consideration of the design of these financing activities and through the perceptions of different actors, within a limited number of purposively selected geographical areas in each country, about their strengths and weaknesses. Additional data on utilization were either collected during the course of the study (Kenya) or drawn from other available studies (Benin and Zambia). Key issues considered in the studies' assessment of equity were the extent to which both relative and absolute affordability gains were achieved, as well as as an influence over both the distributional and procedural justice of the financing activities, the pattern of decision-making. Across countries there was evidence of relative affordability gains in Benin and Kenya, but Kenyan gains were not sustained over time and no such gains were identified in Zambia. In addition, no country had given attention either to the issue of absolute affordability, through the implementation of effective exemption mechanisms to protect the poorest from the burden of payment, or to the establishment of community decision-making bodies that effectively represented the interests of all groups including the poorest. Overall, therefore, although the Benin Bamako Initiative programme might be judged as successful in terms of what appear to be its own equity objectives, the other two countries' schemes had clear equity problems even in these terms. The experience across countries also highlights the unresolved question of whether equity is concerned with the greatest good for the greatest number or with promoting the interests of the most disadvantaged.

Increased fairness in priority setting processes within the health sector: the case of Kapiri-Mposhi District, Zambia.

PubMed

Zulu, Joseph M; Michelo, Charles; Msoni, Carol; Hurtig, Anna-Karin; Byskov, Jens; Blystad, Astrid

2014-02-18

The challenge of priority setting (PS) in health care within contexts of severe resource limitations has continued to receive attention. Accountability for Reasonableness (AFR) has emerged as a useful framework to guide the implementation of PS processes. In 2006, the AFR approach to enhance legitimate and fair PS was introduced by researchers and decision makers within the health sector in the EU funded research project entitled 'Response to Accountable priority setting for Trust in health systems' (REACT). The project aimed to strengthen fairness and accountability in the PS processes of health systems at district level in Zambia, Tanzania and Kenya. This paper focuses on local perceptions and practices of fair PS (baseline study) as well as at the evolution of such perceptions and practices in PS following an AFR based intervention (evaluation study), carried out at district level in Kapiri-Mposhi District in Zambia. Data was collected using in depth interviews (IDIs), focus group discussions (FGDs) and review of documents from national to district level. The study population for this paper consisted of health related stakeholders employed in the district administration, in non-governmental organizations (NGO) and in health facilities. During the baseline study, concepts of legitimacy and fairness in PS processes were found to be grounded in local values of equity and impartiality. Government and other organizational strategies strongly supported devolution of PS and decision making procedures. However, important gaps were identified in terms of experiences of stakeholder involvement and fairness in PS processes in practice. The evaluation study revealed that a transformation of the views and methods regarding fairness in PS processes was ongoing in the study district, which was partly attributed to the AFR based intervention. The study findings suggest that increased attention was given to fairness in PS processes at district level. The changes were linked to a number of simultaneous factors among them the concepts introduced by the present project with its emphasis on fairness and enhanced participation. A responsive leadership that was increasingly accountable to its operational staff and communities emerged as one of the key elements in driving the processes forward.

The contribution of trees outside forests to national tree biomass and carbon stocks--a comparative study across three continents.

PubMed

Schnell, Sebastian; Altrell, Dan; Ståhl, Göran; Kleinn, Christoph

2015-01-01

In contrast to forest trees, trees outside forests (TOF) often are not included in the national monitoring of tree resources. Consequently, data about this particular resource is rare, and available information is typically fragmented across the different institutions and stakeholders that deal with one or more of the various TOF types. Thus, even if information is available, it is difficult to aggregate data into overall national statistics. However, the National Forest Monitoring and Assessment (NFMA) programme of FAO offers a unique possibility to study TOF resources because TOF are integrated by default into the NFMA inventory design. We have analysed NFMA data from 11 countries across three continents. For six countries, we found that more than 10% of the national above-ground tree biomass was actually accumulated outside forests. The highest value (73%) was observed for Bangladesh (total forest cover 8.1%, average biomass per hectare in forest 33.4 t ha(-1)) and the lowest (3%) was observed for Zambia (total forest cover 63.9%, average biomass per hectare in forest 32 t ha(-1)). Average TOF biomass stocks were estimated to be smaller than 10 t ha(-1). However, given the large extent of non-forest areas, these stocks sum up to considerable quantities in many countries. There are good reasons to overcome sectoral boundaries and to extend national forest monitoring programmes on a more systematic basis that includes TOF. Such an approach, for example, would generate a more complete picture of the national tree biomass. In the context of climate change mitigation and adaptation, international climate mitigation programmes (e.g. Clean Development Mechanism and Reduced Emission from Deforestation and Degradation) focus on forest trees without considering the impact of TOF, a consideration this study finds crucial if accurate measurements of national tree biomass and carbon pools are required.

Autonomy dimensions and care seeking for delivery in Zambia; the prevailing importance of cluster-level measurement.

PubMed

Gabrysch, Sabine; McMahon, Shannon A; Siling, Katja; Kenward, Michael G; Campbell, Oona M R

2016-03-02

It is widely held that decisions whether or when to attend health facilities for childbirth are not only influenced by risk awareness and household wealth, but also by factors such as autonomy or a woman's ability to act upon her own preferences. How autonomy should be constructed and measured - namely, as an individual or cluster-level variable - has been less examined. We drew on household survey data from Zambia to study the effect of several autonomy dimensions (financial, relationship, freedom of movement, health care seeking and violence) on place of delivery for 3200 births across 203 rural clusters (villages). In multilevel logistic regression, two autonomy dimensions (relationship and health care seeking) were strongly associated with facility delivery when measured at the cluster level (OR 1.27 and 1.57, respectively), though not at the individual level. This suggests that power relations and gender norms at the community level may override an individual woman's autonomy, and cluster-level measurement may prove critical to understanding the interplay between autonomy and care seeking in this and similar contexts.

Autonomy dimensions and care seeking for delivery in Zambia; the prevailing importance of cluster-level measurement

PubMed Central

Gabrysch, Sabine; McMahon, Shannon A.; Siling, Katja; Kenward, Michael G.; Campbell, Oona M. R.

2016-01-01

It is widely held that decisions whether or when to attend health facilities for childbirth are not only influenced by risk awareness and household wealth, but also by factors such as autonomy or a woman’s ability to act upon her own preferences. How autonomy should be constructed and measured – namely, as an individual or cluster-level variable – has been less examined. We drew on household survey data from Zambia to study the effect of several autonomy dimensions (financial, relationship, freedom of movement, health care seeking and violence) on place of delivery for 3200 births across 203 rural clusters (villages). In multilevel logistic regression, two autonomy dimensions (relationship and health care seeking) were strongly associated with facility delivery when measured at the cluster level (OR 1.27 and 1.57, respectively), though not at the individual level. This suggests that power relations and gender norms at the community level may override an individual woman’s autonomy, and cluster-level measurement may prove critical to understanding the interplay between autonomy and care seeking in this and similar contexts. PMID:26931301

Balancing risk, interpersonal intimacy and agency: perspectives from marginalised women in Zambia.

PubMed

Davis, Lwendo Moonzwe; Kostick, Kristin Marie

2018-05-15

Women are most exposed to sexual health risks within their marital relationships, primarily due to the sexually risky behaviours of their spouses. Studies show that expanding agency is critical for women to mitigate both physical and sexual health risks and is linked to increased psycho-social well-being and economic independence. Drawing on qualitative and quantitative primary data collected from a peri-urban community in Zambia, this paper explores how women exert agency in a community where few educational and economic opportunities and substantial food insecurity exacerbate women's risk for HIV within their marital relationships. It also examines how expressions of agency within marital unions can reduce HIV risk exposure and lead to socio-economic benefits. However, expressions of agency can also create physical, psycho-social and sexual health risks, particularly when spouses do not support independent decision-making and actions that women consider necessary to support the household and maintain intimacy. Findings highlight the importance of community involvement and addressing harmful socio-cultural norms to foster the realisation of women's agency.

Application of decision tree model for the ground subsidence hazard mapping near abandoned underground coal mines.

PubMed

Lee, Saro; Park, Inhye

2013-09-30

Subsidence of ground caused by underground mines poses hazards to human life and property. This study analyzed the hazard to ground subsidence using factors that can affect ground subsidence and a decision tree approach in a geographic information system (GIS). The study area was Taebaek, Gangwon-do, Korea, where many abandoned underground coal mines exist. Spatial data, topography, geology, and various ground-engineering data for the subsidence area were collected and compiled in a database for mapping ground-subsidence hazard (GSH). The subsidence area was randomly split 50/50 for training and validation of the models. A data-mining classification technique was applied to the GSH mapping, and decision trees were constructed using the chi-squared automatic interaction detector (CHAID) and the quick, unbiased, and efficient statistical tree (QUEST) algorithms. The frequency ratio model was also applied to the GSH mapping for comparing with probabilistic model. The resulting GSH maps were validated using area-under-the-curve (AUC) analysis with the subsidence area data that had not been used for training the model. The highest accuracy was achieved by the decision tree model using CHAID algorithm (94.01%) comparing with QUEST algorithms (90.37%) and frequency ratio model (86.70%). These accuracies are higher than previously reported results for decision tree. Decision tree methods can therefore be used efficiently for GSH analysis and might be widely used for prediction of various spatial events. Copyright © 2013. Published by Elsevier Ltd.

MRI-based decision tree model for diagnosis of biliary atresia.

PubMed

Kim, Yong Hee; Kim, Myung-Joon; Shin, Hyun Joo; Yoon, Haesung; Han, Seok Joo; Koh, Hong; Roh, Yun Ho; Lee, Mi-Jung

2018-02-23

To evaluate MRI findings and to generate a decision tree model for diagnosis of biliary atresia (BA) in infants with jaundice. We retrospectively reviewed features of MRI and ultrasonography (US) performed in infants with jaundice between January 2009 and June 2016 under approval of the institutional review board, including the maximum diameter of periportal signal change on MRI (MR triangular cord thickness, MR-TCT) or US (US-TCT), visibility of common bile duct (CBD) and abnormality of gallbladder (GB). Hepatic subcapsular flow was reviewed on Doppler US. We performed conditional inference tree analysis using MRI findings to generate a decision tree model. A total of 208 infants were included, 112 in the BA group and 96 in the non-BA group. Mean age at the time of MRI was 58.7 ± 36.6 days. Visibility of CBD, abnormality of GB and MR-TCT were good discriminators for the diagnosis of BA and the MRI-based decision tree using these findings with MR-TCT cut-off 5.1 mm showed 97.3 % sensitivity, 94.8 % specificity and 96.2 % accuracy. MRI-based decision tree model reliably differentiates BA in infants with jaundice. MRI can be an objective imaging modality for the diagnosis of BA. • MRI-based decision tree model reliably differentiates biliary atresia in neonatal cholestasis. • Common bile duct, gallbladder and periportal signal changes are the discriminators. • MRI has comparable performance to ultrasonography for diagnosis of biliary atresia.

Predictability of the future development of aggressive behavior of cranial dural arteriovenous fistulas based on decision tree analysis.

PubMed

Satomi, Junichiro; Ghaibeh, A Ammar; Moriguchi, Hiroki; Nagahiro, Shinji

2015-07-01

The severity of clinical signs and symptoms of cranial dural arteriovenous fistulas (DAVFs) are well correlated with their pattern of venous drainage. Although the presence of cortical venous drainage can be considered a potential predictor of aggressive DAVF behaviors, such as intracranial hemorrhage or progressive neurological deficits due to venous congestion, accurate statistical analyses are currently not available. Using a decision tree data mining method, the authors aimed at clarifying the predictability of the future development of aggressive behaviors of DAVF and at identifying the main causative factors. Of 266 DAVF patients, 89 were eligible for analysis. Under observational management, 51 patients presented with intracranial hemorrhage/infarction during the follow-up period. The authors created a decision tree able to assess the risk for the development of aggressive DAVF behavior. Evaluated by 10-fold cross-validation, the decision tree's accuracy, sensitivity, and specificity were 85.28%, 88.33%, and 80.83%, respectively. The tree shows that the main factor in symptomatic patients was the presence of cortical venous drainage. In its absence, the lesion location determined the risk of a DAVF developing aggressive behavior. Decision tree analysis accurately predicts the future development of aggressive DAVF behavior.

[Analysis of the characteristics of the older adults with depression using data mining decision tree analysis].

PubMed

Park, Myonghwa; Choi, Sora; Shin, A Mi; Koo, Chul Hoi

2013-02-01

The purpose of this study was to develop a prediction model for the characteristics of older adults with depression using the decision tree method. A large dataset from the 2008 Korean Elderly Survey was used and data of 14,970 elderly people were analyzed. Target variable was depression and 53 input variables were general characteristics, family & social relationship, economic status, health status, health behavior, functional status, leisure & social activity, quality of life, and living environment. Data were analyzed by decision tree analysis, a data mining technique using SPSS Window 19.0 and Clementine 12.0 programs. The decision trees were classified into five different rules to define the characteristics of older adults with depression. Classification & Regression Tree (C&RT) showed the best prediction with an accuracy of 80.81% among data mining models. Factors in the rules were life satisfaction, nutritional status, daily activity difficulty due to pain, functional limitation for basic or instrumental daily activities, number of chronic diseases and daily activity difficulty due to disease. The different rules classified by the decision tree model in this study should contribute as baseline data for discovering informative knowledge and developing interventions tailored to these individual characteristics.

Acquisition of Scientific Literature in Developing Countries. 4: Zambia.

ERIC Educational Resources Information Center

Lundu, Maurice C.; Lungu, Charles B. M.

1989-01-01

Description of selected science and technical libraries and information services in Zambia focuses on collection development and acquisition policies. The problems of transferring technology through the transfer of information are discussed, the future of information transfer in Zambia is explored, and proposals for future action are presented.…

Applied Swarm-based medicine: collecting decision trees for patterns of algorithms analysis.

PubMed

Panje, Cédric M; Glatzer, Markus; von Rappard, Joscha; Rothermundt, Christian; Hundsberger, Thomas; Zumstein, Valentin; Plasswilm, Ludwig; Putora, Paul Martin

2017-08-16

The objective consensus methodology has recently been applied in consensus finding in several studies on medical decision-making among clinical experts or guidelines. The main advantages of this method are an automated analysis and comparison of treatment algorithms of the participating centers which can be performed anonymously. Based on the experience from completed consensus analyses, the main steps for the successful implementation of the objective consensus methodology were identified and discussed among the main investigators. The following steps for the successful collection and conversion of decision trees were identified and defined in detail: problem definition, population selection, draft input collection, tree conversion, criteria adaptation, problem re-evaluation, results distribution and refinement, tree finalisation, and analysis. This manuscript provides information on the main steps for successful collection of decision trees and summarizes important aspects at each point of the analysis.

Comparison of neurofuzzy logic and decision trees in discovering knowledge from experimental data of an immediate release tablet formulation.

PubMed

Shao, Q; Rowe, R C; York, P

2007-06-01

Understanding of the cause-effect relationships between formulation ingredients, process conditions and product properties is essential for developing a quality product. However, the formulation knowledge is often hidden in experimental data and not easily interpretable. This study compares neurofuzzy logic and decision tree approaches in discovering hidden knowledge from an immediate release tablet formulation database relating formulation ingredients (silica aerogel, magnesium stearate, microcrystalline cellulose and sodium carboxymethylcellulose) and process variables (dwell time and compression force) to tablet properties (tensile strength, disintegration time, friability, capping and drug dissolution at various time intervals). Both approaches successfully generated useful knowledge in the form of either "if then" rules or decision trees. Although different strategies are employed by the two approaches in generating rules/trees, similar knowledge was discovered in most cases. However, as decision trees are not able to deal with continuous dependent variables, data discretisation procedures are generally required.

Parallel object-oriented decision tree system

DOEpatents

Kamath,; Chandrika, Cantu-Paz [Dublin, CA; Erick, [Oakland, CA

2006-02-28

A data mining decision tree system that uncovers patterns, associations, anomalies, and other statistically significant structures in data by reading and displaying data files, extracting relevant features for each of the objects, and using a method of recognizing patterns among the objects based upon object features through a decision tree that reads the data, sorts the data if necessary, determines the best manner to split the data into subsets according to some criterion, and splits the data.

Generation and Termination of Binary Decision Trees for Nonparametric Multiclass Classification.

DTIC Science & Technology

1984-10-01

O M coF=F;; UMBER2. GOVT ACCE5SION NO.1 3 . REC,PINS :A7AL:,G NUMBER ( ’eneration and Terminat_,on :)f Binary D-ecision jC j ik; Trees for Nonnararetrc...1-I . v)IAMO 0~I4 EDvt" O F I 00 . 3 15I OR%.OL.ETL - S-S OCTOBER 1984 LIDS-P-1411 GENERATION AND TERMINATION OF BINARY DECISION TREES FOR...minimizes the Bayes risk. Tree generation and termination are based on the training and test samples, respectively. 0 0 0/ 6 0¢ A 3 I. Introduction We state

EEG feature selection method based on decision tree.

PubMed

Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

The Decision Tree for Teaching Management of Uncertainty

ERIC Educational Resources Information Center

Knaggs, Sara J.; And Others

1974-01-01

A 'decision tree' consists of an outline of the patient's symptoms and a logic for decision and action. It is felt that this approach to the decisionmaking process better facilitates each learner's application of his own level of knowledge and skills. (Author)

Predicting metabolic syndrome using decision tree and support vector machine methods.

PubMed

Karimi-Alavijeh, Farzaneh; Jalili, Saeed; Sadeghi, Masoumeh

2016-05-01

Metabolic syndrome which underlies the increased prevalence of cardiovascular disease and Type 2 diabetes is considered as a group of metabolic abnormalities including central obesity, hypertriglyceridemia, glucose intolerance, hypertension, and dyslipidemia. Recently, artificial intelligence based health-care systems are highly regarded because of its success in diagnosis, prediction, and choice of treatment. This study employs machine learning technics for predict the metabolic syndrome. This study aims to employ decision tree and support vector machine (SVM) to predict the 7-year incidence of metabolic syndrome. This research is a practical one in which data from 2107 participants of Isfahan Cohort Study has been utilized. The subjects without metabolic syndrome according to the ATPIII criteria were selected. The features that have been used in this data set include: gender, age, weight, body mass index, waist circumference, waist-to-hip ratio, hip circumference, physical activity, smoking, hypertension, antihypertensive medication use, systolic blood pressure (BP), diastolic BP, fasting blood sugar, 2-hour blood glucose, triglycerides (TGs), total cholesterol, low-density lipoprotein, high density lipoprotein-cholesterol, mean corpuscular volume, and mean corpuscular hemoglobin. Metabolic syndrome was diagnosed based on ATPIII criteria and two methods of decision tree and SVM were selected to predict the metabolic syndrome. The criteria of sensitivity, specificity and accuracy were used for validation. SVM and decision tree methods were examined according to the criteria of sensitivity, specificity and accuracy. Sensitivity, specificity and accuracy were 0.774 (0.758), 0.74 (0.72) and 0.757 (0.739) in SVM (decision tree) method. The results show that SVM method sensitivity, specificity and accuracy is more efficient than decision tree. The results of decision tree method show that the TG is the most important feature in predicting metabolic syndrome. According to this study, in cases where only the final result of the decision is regarded significant, SVM method can be used with acceptable accuracy in decision making medical issues. This method has not been implemented in the previous research.

Movement Behaviour of Traditionally Managed Cattle in the Eastern Province of Zambia Captured Using Two-Dimensional Motion Sensors.

PubMed

Lubaba, Caesar H; Hidano, Arata; Welburn, Susan C; Revie, Crawford W; Eisler, Mark C

2015-01-01

Two-dimensional motion sensors use electronic accelerometers to record the lying, standing and walking activity of cattle. Movement behaviour data collected automatically using these sensors over prolonged periods of time could be of use to stakeholders making management and disease control decisions in rural sub-Saharan Africa leading to potential improvements in animal health and production. Motion sensors were used in this study with the aim of monitoring and quantifying the movement behaviour of traditionally managed Angoni cattle in Petauke District in the Eastern Province of Zambia. This study was designed to assess whether motion sensors were suitable for use on traditionally managed cattle in two veterinary camps in Petauke District in the Eastern Province of Zambia. In each veterinary camp, twenty cattle were selected for study. Each animal had a motion sensor placed on its hind leg to continuously measure and record its movement behaviour over a two week period. Analysing the sensor data using principal components analysis (PCA) revealed that the majority of variability in behaviour among studied cattle could be attributed to their behaviour at night and in the morning. The behaviour at night was markedly different between veterinary camps; while differences in the morning appeared to reflect varying behaviour across all animals. The study results validate the use of such motion sensors in the chosen setting and highlight the importance of appropriate data summarisation techniques to adequately describe and compare animal movement behaviours if association to other factors, such as location, breed or health status are to be assessed.

Utilization of focused antenatal care in Zambia: examining individual- and community-level factors using a multilevel analysis.

PubMed

Chama-Chiliba, Chitalu M; Koch, Steven F

2015-02-01

We examine the individual- and community-level factors associated with the utilization of antenatal care, following the adoption of the focused antenatal care (FANC) approach in Zambia. Using the 2007 Zambia Demographic and Health Survey, linked with administrative and health facility census data, we specify two multilevel logistic models to assess the factors associated with (1) the inadequate use of antenatal care (ANC) (defined as three or fewer visits) and (2) the non-use of ANC in the first trimester of pregnancy. Although all women in the selected sample had at least one ANC visit, 40% did not have the minimum number required (four), whereas more than 80% of the initial check-ups did not occur in the first trimester. At the individual level, the woman's employment status, quality of ANC received and the husband's educational attainment are negatively associated, while parity, the household childcare burden and wealth are positively associated with inadequate utilization of ANC. Both individual- and community-level characteristics influence inadequate use and non-use of ANC in the first trimester; however, community-level factors are relatively stronger in rural areas. The results suggest that improving the content of care during ANC visits may foster adequate use of ANC and encourage early initiation of ANC visits. Furthermore, health promotion programmes need to further encourage male involvement in pregnant women's decision to seek ANC to encourage adequate use of services. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2013; all rights reserved.

The accountability for reasonableness approach to guide priority setting in health systems within limited resources--findings from action research at district level in Kenya, Tanzania, and Zambia.

PubMed

Byskov, Jens; Marchal, Bruno; Maluka, Stephen; Zulu, Joseph M; Bukachi, Salome A; Hurtig, Anna-Karin; Blystad, Astrid; Kamuzora, Peter; Michelo, Charles; Nyandieka, Lillian N; Ndawi, Benedict; Bloch, Paul; Olsen, Oystein E

2014-08-20

Priority-setting decisions are based on an important, but not sufficient set of values and thus lead to disagreement on priorities. Accountability for Reasonableness (AFR) is an ethics-based approach to a legitimate and fair priority-setting process that builds upon four conditions: relevance, publicity, appeals, and enforcement, which facilitate agreement on priority-setting decisions and gain support for their implementation. This paper focuses on the assessment of AFR within the project REsponse to ACcountable priority setting for Trust in health systems (REACT). This intervention study applied an action research methodology to assess implementation of AFR in one district in Kenya, Tanzania, and Zambia, respectively. The assessments focused on selected disease, program, and managerial areas. An implementing action research team of core health team members and supporting researchers was formed to implement, and continually assess and improve the application of the four conditions. Researchers evaluated the intervention using qualitative and quantitative data collection and analysis methods. The values underlying the AFR approach were in all three districts well-aligned with general values expressed by both service providers and community representatives. There was some variation in the interpretations and actual use of the AFR in the decision-making processes in the three districts, and its effect ranged from an increase in awareness of the importance of fairness to a broadened engagement of health team members and other stakeholders in priority setting and other decision-making processes. District stakeholders were able to take greater charge of closing the gap between nationally set planning and the local realities and demands of the served communities within the limited resources at hand. This study thus indicates that the operationalization of the four broadly defined and linked conditions is both possible and seems to be responding to an actual demand. This provides arguments for the continued application and further assessment of the potential of AFR in supporting priority-setting and other decision-making processes in health systems to achieve better agreed and more sustainable health improvements linked to a mutual democratic learning with potential wider implications.

Improving health information systems for decision making across five sub-Saharan African countries: Implementation strategies from the African Health Initiative.

PubMed

Mutale, Wilbroad; Chintu, Namwinga; Amoroso, Cheryl; Awoonor-Williams, Koku; Phillips, James; Baynes, Colin; Michel, Cathy; Taylor, Angela; Sherr, Kenneth

2013-01-01

Weak health information systems (HIS) are a critical challenge to reaching the health-related Millennium Development Goals because health systems performance cannot be adequately assessed or monitored where HIS data are incomplete, inaccurate, or untimely. The Population Health Implementation and Training (PHIT) Partnerships were established in five sub-Saharan African countries (Ghana, Mozambique, Rwanda, Tanzania, and Zambia) to catalyze advances in strengthening district health systems. Interventions were tailored to the setting in which activities were planned. All five PHIT Partnerships share a common feature in their goal of enhancing HIS and linking data with improved decision-making, specific strategies varied. Mozambique, Ghana, and Tanzania all focus on improving the quality and use of the existing Ministry of Health HIS, while the Zambia and Rwanda partnerships have introduced new information and communication technology systems or tools. All partnerships have adopted a flexible, iterative approach in designing and refining the development of new tools and approaches for HIS enhancement (such as routine data quality audits and automated troubleshooting), as well as improving decision making through timely feedback on health system performance (such as through summary data dashboards or routine data review meetings). The most striking differences between partnership approaches can be found in the level of emphasis of data collection (patient versus health facility), and consequently the level of decision making enhancement (community, facility, district, or provincial leadership). Design differences across PHIT Partnerships reflect differing theories of change, particularly regarding what information is needed, who will use the information to affect change, and how this change is expected to manifest. The iterative process of data use to monitor and assess the health system has been heavily communication dependent, with challenges due to poor feedback loops. Implementation to date has highlighted the importance of engaging frontline staff and managers in improving data collection and its use for informing system improvement. Through rigorous process and impact evaluation, the experience of the PHIT teams hope to contribute to the evidence base in the areas of HIS strengthening, linking HIS with decision making, and its impact on measures of health system outputs and impact.

Improving health information systems for decision making across five sub-Saharan African countries: Implementation strategies from the African Health Initiative

PubMed Central

2013-01-01

Background Weak health information systems (HIS) are a critical challenge to reaching the health-related Millennium Development Goals because health systems performance cannot be adequately assessed or monitored where HIS data are incomplete, inaccurate, or untimely. The Population Health Implementation and Training (PHIT) Partnerships were established in five sub-Saharan African countries (Ghana, Mozambique, Rwanda, Tanzania, and Zambia) to catalyze advances in strengthening district health systems. Interventions were tailored to the setting in which activities were planned. Comparisons across strategies All five PHIT Partnerships share a common feature in their goal of enhancing HIS and linking data with improved decision-making, specific strategies varied. Mozambique, Ghana, and Tanzania all focus on improving the quality and use of the existing Ministry of Health HIS, while the Zambia and Rwanda partnerships have introduced new information and communication technology systems or tools. All partnerships have adopted a flexible, iterative approach in designing and refining the development of new tools and approaches for HIS enhancement (such as routine data quality audits and automated troubleshooting), as well as improving decision making through timely feedback on health system performance (such as through summary data dashboards or routine data review meetings). The most striking differences between partnership approaches can be found in the level of emphasis of data collection (patient versus health facility), and consequently the level of decision making enhancement (community, facility, district, or provincial leadership). Discussion Design differences across PHIT Partnerships reflect differing theories of change, particularly regarding what information is needed, who will use the information to affect change, and how this change is expected to manifest. The iterative process of data use to monitor and assess the health system has been heavily communication dependent, with challenges due to poor feedback loops. Implementation to date has highlighted the importance of engaging frontline staff and managers in improving data collection and its use for informing system improvement. Through rigorous process and impact evaluation, the experience of the PHIT teams hope to contribute to the evidence base in the areas of HIS strengthening, linking HIS with decision making, and its impact on measures of health system outputs and impact. PMID:23819699

The accountability for reasonableness approach to guide priority setting in health systems within limited resources – findings from action research at district level in Kenya, Tanzania, and Zambia

PubMed Central

2014-01-01

Background Priority-setting decisions are based on an important, but not sufficient set of values and thus lead to disagreement on priorities. Accountability for Reasonableness (AFR) is an ethics-based approach to a legitimate and fair priority-setting process that builds upon four conditions: relevance, publicity, appeals, and enforcement, which facilitate agreement on priority-setting decisions and gain support for their implementation. This paper focuses on the assessment of AFR within the project REsponse to ACcountable priority setting for Trust in health systems (REACT). Methods This intervention study applied an action research methodology to assess implementation of AFR in one district in Kenya, Tanzania, and Zambia, respectively. The assessments focused on selected disease, program, and managerial areas. An implementing action research team of core health team members and supporting researchers was formed to implement, and continually assess and improve the application of the four conditions. Researchers evaluated the intervention using qualitative and quantitative data collection and analysis methods. Results The values underlying the AFR approach were in all three districts well-aligned with general values expressed by both service providers and community representatives. There was some variation in the interpretations and actual use of the AFR in the decision-making processes in the three districts, and its effect ranged from an increase in awareness of the importance of fairness to a broadened engagement of health team members and other stakeholders in priority setting and other decision-making processes. Conclusions District stakeholders were able to take greater charge of closing the gap between nationally set planning and the local realities and demands of the served communities within the limited resources at hand. This study thus indicates that the operationalization of the four broadly defined and linked conditions is both possible and seems to be responding to an actual demand. This provides arguments for the continued application and further assessment of the potential of AFR in supporting priority-setting and other decision-making processes in health systems to achieve better agreed and more sustainable health improvements linked to a mutual democratic learning with potential wider implications. PMID:25142148

Cost-effectiveness Analysis with Influence Diagrams.

PubMed

Arias, M; Díez, F J

2015-01-01

Cost-effectiveness analysis (CEA) is used increasingly in medicine to determine whether the health benefit of an intervention is worth the economic cost. Decision trees, the standard decision modeling technique for non-temporal domains, can only perform CEA for very small problems. To develop a method for CEA in problems involving several dozen variables. We explain how to build influence diagrams (IDs) that explicitly represent cost and effectiveness. We propose an algorithm for evaluating cost-effectiveness IDs directly, i.e., without expanding an equivalent decision tree. The evaluation of an ID returns a set of intervals for the willingness to pay - separated by cost-effectiveness thresholds - and, for each interval, the cost, the effectiveness, and the optimal intervention. The algorithm that evaluates the ID directly is in general much more efficient than the brute-force method, which is in turn more efficient than the expansion of an equivalent decision tree. Using OpenMarkov, an open-source software tool that implements this algorithm, we have been able to perform CEAs on several IDs whose equivalent decision trees contain millions of branches. IDs can perform CEA on large problems that cannot be analyzed with decision trees.

Discovering Decision Knowledge from Web Log Portfolio for Managing Classroom Processes by Applying Decision Tree and Data Cube Technology.

ERIC Educational Resources Information Center

Chen, Gwo-Dong; Liu, Chen-Chung; Ou, Kuo-Liang; Liu, Baw-Jhiune

2000-01-01

Discusses the use of Web logs to record student behavior that can assist teachers in assessing performance and making curriculum decisions for distance learning students who are using Web-based learning systems. Adopts decision tree and data cube information processing methodologies for developing more effective pedagogical strategies. (LRW)

Assessing School Readiness for a Practice Arrangement Using Decision Tree Methodology.

ERIC Educational Resources Information Center

Barger, Sara E.

1998-01-01

Questions in a decision-tree address mission, faculty interest, administrative support, and practice plan as a way of assessing arrangements for nursing faculty's clinical practice. Decisions should be based on congruence between the human resource allocation and the reward systems. (SK)

Automated Decision Tree Classification of Corneal Shape

PubMed Central

Twa, Michael D.; Parthasarathy, Srinivasan; Roberts, Cynthia; Mahmoud, Ashraf M.; Raasch, Thomas W.; Bullimore, Mark A.

2011-01-01

Purpose The volume and complexity of data produced during videokeratography examinations present a challenge of interpretation. As a consequence, results are often analyzed qualitatively by subjective pattern recognition or reduced to comparisons of summary indices. We describe the application of decision tree induction, an automated machine learning classification method, to discriminate between normal and keratoconic corneal shapes in an objective and quantitative way. We then compared this method with other known classification methods. Methods The corneal surface was modeled with a seventh-order Zernike polynomial for 132 normal eyes of 92 subjects and 112 eyes of 71 subjects diagnosed with keratoconus. A decision tree classifier was induced using the C4.5 algorithm, and its classification performance was compared with the modified Rabinowitz–McDonnell index, Schwiegerling’s Z3 index (Z3), Keratoconus Prediction Index (KPI), KISA%, and Cone Location and Magnitude Index using recommended classification thresholds for each method. We also evaluated the area under the receiver operator characteristic (ROC) curve for each classification method. Results Our decision tree classifier performed equal to or better than the other classifiers tested: accuracy was 92% and the area under the ROC curve was 0.97. Our decision tree classifier reduced the information needed to distinguish between normal and keratoconus eyes using four of 36 Zernike polynomial coefficients. The four surface features selected as classification attributes by the decision tree method were inferior elevation, greater sagittal depth, oblique toricity, and trefoil. Conclusions Automated decision tree classification of corneal shape through Zernike polynomials is an accurate quantitative method of classification that is interpretable and can be generated from any instrument platform capable of raw elevation data output. This method of pattern classification is extendable to other classification problems. PMID:16357645

Decision Trees Predicting Tumor Shrinkage for Head and Neck Cancer: Implications for Adaptive Radiotherapy.

PubMed

Surucu, Murat; Shah, Karan K; Mescioglu, Ibrahim; Roeske, John C; Small, William; Choi, Mehee; Emami, Bahman

2016-02-01

To develop decision trees predicting for tumor volume reduction in patients with head and neck (H&N) cancer using pretreatment clinical and pathological parameters. Forty-eight patients treated with definitive concurrent chemoradiotherapy for squamous cell carcinoma of the nasopharynx, oropharynx, oral cavity, or hypopharynx were retrospectively analyzed. These patients were rescanned at a median dose of 37.8 Gy and replanned to account for anatomical changes. The percentages of gross tumor volume (GTV) change from initial to rescan computed tomography (CT; %GTVΔ) were calculated. Two decision trees were generated to correlate %GTVΔ in primary and nodal volumes with 14 characteristics including age, gender, Karnofsky performance status (KPS), site, human papilloma virus (HPV) status, tumor grade, primary tumor growth pattern (endophytic/exophytic), tumor/nodal/group stages, chemotherapy regimen, and primary, nodal, and total GTV volumes in the initial CT scan. The C4.5 Decision Tree induction algorithm was implemented. The median %GTVΔ for primary, nodal, and total GTVs was 26.8%, 43.0%, and 31.2%, respectively. Type of chemotherapy, age, primary tumor growth pattern, site, KPS, and HPV status were the most predictive parameters for primary %GTVΔ decision tree, whereas for nodal %GTVΔ, KPS, site, age, primary tumor growth pattern, initial primary GTV, and total GTV volumes were predictive. Both decision trees had an accuracy of 88%. There can be significant changes in primary and nodal tumor volumes during the course of H&N chemoradiotherapy. Considering the proposed decision trees, radiation oncologists can select patients predicted to have high %GTVΔ, who would theoretically gain the most benefit from adaptive radiotherapy, in order to better use limited clinical resources. © The Author(s) 2015.

Peace Corps/Zambia PST 1995 Special Lessons. Nyanja.

ERIC Educational Resources Information Center

Peace Corps (Zambia).

This guide is designed for language teachers training Peace Corps volunteers in Nyanja for service in Zambia, and focuses on daily communication skills in that context. It consists of a language "survival kit" of useful phrases and vocabulary, conjugation of the verb "to be," the Zambia national anthem, extensive notes on verb…

Strategies for Living with the Challenges of HIV and Antiretroviral Use in Zambia

ERIC Educational Resources Information Center

Jones, Deborah; Zulu, Isaac; Mumbi, Miriam; Chitalu, Ndashi; Vamos, Szonja; Gomez, Jacqueline; Weiss, Stephen M.

2009-01-01

This study sought to identify strategies for living with the challenges of HIV and antiretroviral (ARV) use among new medication users in urban Zambia. Participants (n = 160) were recruited from urban Lusaka, Zambia. Qualitative Data was drawn from monthly ARV treatment education intervention groups addressing HIV and antiretroviral use. Themes…

On Parallelism and the Penman Natural Language Generation System.

DTIC Science & Technology

1988-04-01

TagfiniteA Tagsubject L untag ed Figure 2-2: System network with choosers & realization statements 7 decision . We will give a more detailed account of...2: enter the current system. The chooser of the system is in charge of * selection of features. The chooser is itself a decision tree with certain...organization of a chooser is the same as a decision (discrimination) tree, and each branching point in the tree is defined by Ask operation. For example, in

An automated approach to the design of decision tree classifiers

NASA Technical Reports Server (NTRS)

Argentiero, P.; Chin, P.; Beaudet, P.

1980-01-01

The classification of large dimensional data sets arising from the merging of remote sensing data with more traditional forms of ancillary data is considered. Decision tree classification, a popular approach to the problem, is characterized by the property that samples are subjected to a sequence of decision rules before they are assigned to a unique class. An automated technique for effective decision tree design which relies only on apriori statistics is presented. This procedure utilizes a set of two dimensional canonical transforms and Bayes table look-up decision rules. An optimal design at each node is derived based on the associated decision table. A procedure for computing the global probability of correct classfication is also provided. An example is given in which class statistics obtained from an actual LANDSAT scene are used as input to the program. The resulting decision tree design has an associated probability of correct classification of .76 compared to the theoretically optimum .79 probability of correct classification associated with a full dimensional Bayes classifier. Recommendations for future research are included.

Evaluation of Decision Trees for Cloud Detection from AVHRR Data

NASA Technical Reports Server (NTRS)

Shiffman, Smadar; Nemani, Ramakrishna

2005-01-01

Automated cloud detection and tracking is an important step in assessing changes in radiation budgets associated with global climate change via remote sensing. Data products based on satellite imagery are available to the scientific community for studying trends in the Earth's atmosphere. The data products include pixel-based cloud masks that assign cloud-cover classifications to pixels. Many cloud-mask algorithms have the form of decision trees. The decision trees employ sequential tests that scientists designed based on empirical astrophysics studies and simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In a previous study we compared automatically learned decision trees to cloud masks included in Advanced Very High Resolution Radiometer (AVHRR) data products from the year 2000. In this paper we report the replication of the study for five-year data, and for a gold standard based on surface observations performed by scientists at weather stations in the British Islands. For our sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks p < 0.001.

Decision-Tree Analysis for Predicting First-Time Pass/Fail Rates for the NCLEX-RN® in Associate Degree Nursing Students.

PubMed

Chen, Hsiu-Chin; Bennett, Sean

2016-08-01

Little evidence shows the use of decision-tree algorithms in identifying predictors and analyzing their associations with pass rates for the NCLEX-RN(®) in associate degree nursing students. This longitudinal and retrospective cohort study investigated whether a decision-tree algorithm could be used to develop an accurate prediction model for the students' passing or failing the NCLEX-RN. This study used archived data from 453 associate degree nursing students in a selected program. The chi-squared automatic interaction detection analysis of the decision trees module was used to examine the effect of the collected predictors on passing/failing the NCLEX-RN. The actual percentage scores of Assessment Technologies Institute®'s RN Comprehensive Predictor(®) accurately identified students at risk of failing. The classification model correctly classified 92.7% of the students for passing. This study applied the decision-tree model to analyze a sequence database for developing a prediction model for early remediation in preparation for the NCLEXRN. [J Nurs Educ. 2016;55(8):454-457.]. Copyright 2016, SLACK Incorporated.

Sequential decision tree using the analytic hierarchy process for decision support in rectal cancer.

PubMed

Suner, Aslı; Çelikoğlu, Can Cengiz; Dicle, Oğuz; Sökmen, Selman

2012-09-01

The aim of the study is to determine the most appropriate method for construction of a sequential decision tree in the management of rectal cancer, using various patient-specific criteria and treatments such as surgery, chemotherapy, and radiotherapy. An analytic hierarchy process (AHP) was used to determine the priorities of variables. Relevant criteria used in two decision steps and their relative priorities were established by a panel of five general surgeons. Data were collected via a web-based application and analyzed using the "Expert Choice" software specifically developed for the AHP. Consistency ratios in the AHP method were calculated for each set of judgments, and the priorities of sub-criteria were determined. A sequential decision tree was constructed for the best treatment decision process, using priorities determined by the AHP method. Consistency ratios in the AHP method were calculated for each decision step, and the judgments were considered consistent. The tumor-related criterion "presence of perforation" (0.331) and the patient-surgeon-related criterion "surgeon's experience" (0.630) had the highest priority in the first decision step. In the second decision step, the tumor-related criterion "the stage of the disease" (0.230) and the patient-surgeon-related criterion "surgeon's experience" (0.281) were the paramount criteria. The results showed some variation in the ranking of criteria between the decision steps. In the second decision step, for instance, the tumor-related criterion "presence of perforation" was just the fifth. The consistency of decision support systems largely depends on the quality of the underlying decision tree. When several choices and variables have to be considered in a decision, it is very important to determine priorities. The AHP method seems to be effective for this purpose. The decision algorithm developed by this method is more realistic and will improve the quality of the decision tree. Copyright © 2012 Elsevier B.V. All rights reserved.

Comparison of Taxi Time Prediction Performance Using Different Taxi Speed Decision Trees

NASA Technical Reports Server (NTRS)

Lee, Hanbong

2017-01-01

In the STBO modeler and tactical surface scheduler for ATD-2 project, taxi speed decision trees are used to calculate the unimpeded taxi times of flights taxiing on the airport surface. The initial taxi speed values in these decision trees did not show good prediction accuracy of taxi times. Using the more recent, reliable surveillance data, new taxi speed values in ramp area and movement area were computed. Before integrating these values into the STBO system, we performed test runs using live data from Charlotte airport, with different taxi speed settings: 1) initial taxi speed values and 2) new ones. Taxi time prediction performance was evaluated by comparing various metrics. The results show that the new taxi speed decision trees can calculate the unimpeded taxi-out times more accurately.

Co-circulation of multiple genotypes of African swine fever viruses among domestic pigs in Zambia (2013-2015).

PubMed

Simulundu, E; Chambaro, H M; Sinkala, Y; Kajihara, M; Ogawa, H; Mori, A; Ndebe, J; Dautu, G; Mataa, L; Lubaba, C H; Simuntala, C; Fandamu, P; Simuunza, M; Pandey, G S; Samui, K L; Misinzo, G; Takada, A; Mweene, A S

2018-02-01

During 2013-2015, several and severe outbreaks of African swine fever (ASF) affected domestic pigs in six provinces of Zambia. Genetic characterization of ASF viruses (ASFVs) using standardized genotyping procedures revealed that genotypes I, II and XIV were associated with these outbreaks. Molecular and epidemiological data suggest that genotype II ASFV (Georgia 2007/1-like) detected in Northern Province of Zambia may have been introduced from neighbouring Tanzania. Also, a genotype II virus detected in Eastern Province of Zambia showed a p54 phylogenetic relationship that was inconsistent with that of p72, underscoring the genetic variability of ASFVs. While it appears genotype II viruses detected in Zambia arose from a domestic pig cycle, genotypes I and XIV possibly emerged from a sylvatic cycle. Overall, this study demonstrates the co-circulation of multiple genotypes of ASFVs, involvement of both the sylvatic and domestic pig cycle in ASF outbreaks in Zambia and possible trans-boundary spread of the disease in south-eastern Africa. Indeed, while there is need for regional or international concerted efforts in the control of ASF, understanding pig marketing practices, pig population dynamics, pig housing and rearing systems and community engagement will be important considerations when designing future prevention and control strategies of this disease in Zambia. © 2017 Blackwell Verlag GmbH.

Personal and Environmental Predictors of the Intention to Use Maternal Healthcare Services in Kalomo, Zambia

ERIC Educational Resources Information Center

Sialubanje, Cephas; Massar, Karlijn; Hamer, Davidson H.; Ruiter, Robert A. C.

2014-01-01

Low maternal healthcare service utilization contributes to poor maternal and new born health outcomes in rural Zambia. The purpose of this study was to identify important factors influencing women's intention to use these services in Kalomo, Zambia. An interviewer-administered questionnaire was used to collect data from 1007 women of reproductive…

Urbanization in Zambia. An International Urbanization Survey Report to the Ford Foundation.

ERIC Educational Resources Information Center

Simmance, Alan J. F.

This report reviews the "Seers Report," which contained policy guidelines for modern development planning in Zambia, and compares its findings to recent findings during the period 1963-1970. The Seers Report found that Zambia was the most urbanized country in Africa south of the Sahara (excluding South Africa). This report finds that…

Consultancy Report: Assessment of the Zambia College of Distance Education (ZACODE)

ERIC Educational Resources Information Center

Ellis, Justin

2009-01-01

This study was carried out at the request of the Ministry of Education, Zambia. The Commonwealth of Learning contracted Turning Points Consultancy CC, a Namibian company, who provided the services of the author, to "carry out an evaluation of the Zambia College of Distance Education (ZACODE) and submit recommendations to the Ministry of…

A cost-effectiveness analysis of artemether lumefantrine for treatment of uncomplicated malaria in Zambia

PubMed Central

Chanda, Pascalina; Masiye, Felix; Chitah, Bona M; Sipilanyambe, Naawa; Hawela, Moonga; Banda, Patrick; Okorosobo, Tuoyo

2007-01-01

Background Malaria remains a leading cause of morbidity, mortality and non-fatal disability in Zambia, especially among children, pregnant women and the poor. Data gathered by the National Malaria Control Centre has shown that recently observed widespread treatment failure of SP and chloroquine precipitated a surge in malaria-related morbidity and mortality. As a result, the Government has recently replaced chloroquine and SP with combination therapy as first-line treatment for malaria. Despite the acclaimed therapeutic advantages of ACTs over monotherapies with SP and CQ, the cost of ACTs is much greater, raising concerns about affordability in many poor countries such as Zambia. This study evaluates the cost-effectiveness analysis of artemether-lumefantrine, a version of ACTs adopted in Zambia in mid 2004. Methods Using data gathered from patients presenting at public health facilities with suspected malaria, the costs and effects of using ACTs versus SP as first-line treatment for malaria were estimated. The study was conducted in six district sites. Treatment success and reduction in demand for second line treatment constituted the main effectiveness outcomes. The study gathered data on the efficacy of, and compliance to, AL and SP treatment from a random sample of patients. Costs are based on estimated drug, labour, operational and capital inputs. Drug costs were based on dosages and unit prices provided by the Ministry of Health and the manufacturer (Norvatis). Findings The results suggest that AL produces successful treatment at less cost than SP, implying that AL is more cost-effective. While it is acknowledged that implementing national ACT program will require considerable resources, the study demonstrates that the health gains (treatment success) from every dollar spent are significantly greater if AL is used rather than SP. The incremental cost-effectiveness ratio is estimated to be US$4.10. When the costs of second line treatment are considered the ICER of AL becomes negative, indicating that there are greater resource savings associated with AL in terms of reduction of costs of complicated malaria treatment. Conclusion This study suggests the decision to adopt AL is justifiable on both economic and public health grounds. PMID:17313682

Why pigs are free-roaming: Communities' perceptions, knowledge and practices regarding pig management and taeniosis/cysticercosis in a Taenia solium endemic rural area in Eastern Zambia.

PubMed

Thys, Séverine; Mwape, Kabemba E; Lefèvre, Pierre; Dorny, Pierre; Phiri, Andrew M; Marcotty, Tanguy; Phiri, Isaac K; Gabriël, Sarah

2016-07-30

Taenia solium cysticercosis is a neglected parasitic zoonosis in many developing countries including Zambia. Studies in Africa have shown that the underuse of sanitary facilities and the widespread occurrence of free-roaming pigs are the major risk factors for porcine cysticercosis. Socio-cultural determinants related to free range pig management and their implications for control of T. solium remain unclear. The study objective was to assess the communities' perceptions, reported practices and knowledge regarding management of pigs and taeniosis/cysticercosis (including neurocysticercosis) in an endemic rural area in Eastern Zambia, and to identify possible barriers to pig related control measures such as pig confinement. A total of 21 focus group discussions on pig husbandry practices were organized separately with men, women and children, in seven villages from Petauke district. The findings reveal that the perception of pigs and their role in society (financial, agricultural and traditional), the distribution of the management tasks among the family members owning pigs (feeding, building kraal, seeking care) and environmental aspects (feed supply, presence of bush, wood use priorities, rainy season) prevailing in the study area affect pig confinement. People have a fragmented knowledge of the pork tapeworm and its transmission. Even if negative aspects/health risks of free-range pigs keeping are perceived, people are ready to take the risk for socio-economic reasons. Finally, gender plays an important role because women, and also children, seem to have a higher perception of the risks but lack power in terms of economic decision-making compared to men. Currently pig confinement is not seen as an acceptable method to control porcine cysticercosis by many farmers in Eastern Zambia, vaccination and treatment seemed to be more appropriate. Embedded in a One Health approach, disease control programs should therefore ensure a complementary appropriate set of control strategies by engaging new sectors such as agronomy, spatial ecology and finally consider the socio-cultural context, which is likely to enhance the development of control methods that could be accepted by the communities. Copyright © 2016 Elsevier B.V. All rights reserved.

The Republic of Zambia.

PubMed

Hakkert, R; Wieringa, R

1986-05-01

In 1964, at independence, Zambia's economic future looked brighter than that of most other developing countries. Its copper production accounted for 8% of total world production, and only neighboring Zaire outpaced it in the production of cobalt. Its Central Province around Kabwe held rich deposits of both zinc and lead; uranium deposits also had been found, but their projected yield remained undetermined. Since 1974, the decline in the price of copper and the increase in the price of oil have played havoc with Zambia's balance of payments. Copper, which accounted for 40% of the gross national product (GNP) and 98% of all foreign exchange in 1964, shrank to 12% of the GNP in 1978 while still generating most of the foreign exchange. As a result, imports were cut back markedly from $1.5 billion in 1973 to $690 million in 1983. Although this trend is beginning to make a U-turn, Zambia's economic situation is grave. In 1984 the GNP continued to register negative growth and inflation stood at 25%. With its urbanization rate doubling from 21% in 1964 to 43% in 1985, Zambia is now the most urbanized country south of the Sahara. Zambia's 1985 population is estimated to be 6.8 million. Between 1963 and 1969, the average annual population growth rate was 2.5: it was 3.1% between 1969-80. The current birthrate of about 48/1000 is expected to decline only marginally in the next 15 years, but the death rate is declining more rapidly -- from 19/1000 in the late 1960s to 15/1000 in 1985. Life expectancy is expected to rise from the current 51 years to about 58 years. As a result of the high growth rate, Zambia's population is young, with a median age of about 16.3 years. Traditional African values stress the importance of large families. Zambia's total fertility rate was 6.9 in 1985. According to the World Bank, only 1% of married women of childbearing age in 1982 used contraceptives. Although tribal links are weakening, Zambia still counts 73 officially recognized tribes. Together, they speak about 40 different dialects. Zambia now apportions over 15% of its national budget to education. Despite some noticeable progress, the public health structure remains deficient. Principal health problems include malaria, tuberculosis, and, in Northern Province and Luapula Province, sleeping sickness and river blindness. About 2/3 of the labor force, an estimated 2.2 million persons in 1982, still work in agriculture. Female labor force participation is lower in Zambia than in many African nations.

The Charcoal Trap: Miombo Woddlands and the Energy Demands of People

NASA Astrophysics Data System (ADS)

Kutsch, W. L.; Merbold, L.; Mukelabai, M. M.

2012-04-01

Miombo woodlands cover the transition zone between dry open savannas and moist forests in Southern Africa. They cover about 2.7 million km2 in southern Africa and provide many ecosystem services that support rural life, including medical products, wild foods, construction timber and fuel. In Zambia, as in many of its neighbouring countries, miombo woodlands are currently experiencing accelerating degradation and clearing, mostly with charcoal production as the initial driver. Domestic energy needs in the growing urban areas are largely satisfied by charcoal, which is less energy-efficient fuel on a tree-to-table basis than the firewood that is used in rural areas, but has a higher energy density and is thus cheaper to transport. This study uses data from inventories and from eddy covariance measurements of carbon exchange to characterize the impact of charcoal production on miombo woodlands. We address the following questions: (i) how much carbon is lost at local as well as at national scale and (ii) does forest degradation result in the loss of a carbon sink? On the basis of our data we (iii) estimate the per capita emissions through deforestation and forest degradation in Zambia and relate it to fossil fuel emissions. Furthermore, (iv) a rough estimate of the energy that is provided by charcoal production to private households at a national level is calculated and (v) options for alternative energy supply to private households are discussed.

Bayesian additive decision trees of biomarker by treatment interactions for predictive biomarker detection and subgroup identification.

PubMed

Zhao, Yang; Zheng, Wei; Zhuo, Daisy Y; Lu, Yuefeng; Ma, Xiwen; Liu, Hengchang; Zeng, Zhen; Laird, Glen

2017-10-11

Personalized medicine, or tailored therapy, has been an active and important topic in recent medical research. Many methods have been proposed in the literature for predictive biomarker detection and subgroup identification. In this article, we propose a novel decision tree-based approach applicable in randomized clinical trials. We model the prognostic effects of the biomarkers using additive regression trees and the biomarker-by-treatment effect using a single regression tree. Bayesian approach is utilized to periodically revise the split variables and the split rules of the decision trees, which provides a better overall fitting. Gibbs sampler is implemented in the MCMC procedure, which updates the prognostic trees and the interaction tree separately. We use the posterior distribution of the interaction tree to construct the predictive scores of the biomarkers and to identify the subgroup where the treatment is superior to the control. Numerical simulations show that our proposed method performs well under various settings comparing to existing methods. We also demonstrate an application of our method in a real clinical trial.

RE-Powering’s Electronic Decision Tree

EPA Pesticide Factsheets

Developed by US EPA's RE-Powering America's Land Initiative, the RE-Powering Decision Trees tool guides interested parties through a process to screen sites for their suitability for solar photovoltaics or wind installations

Recasting Postcolonial Citizenship through Civic Education: Critical Perspectives on Zambia

ERIC Educational Resources Information Center

Abdi, Ali A.; Shizha, Edward; Bwalya, Ignatio

2006-01-01

Since the early 1990s and, perhaps, as one effect of the emergence of the uni-polar world, there have been a lot of "democratizing" activities in the Sub-Saharan context, with Zambia, a central African country of about 10 million, at the forefront of these processes. While democracy, in one form or another, has come to Zambia,…

Perceptions of and Attitudes towards Ageing in Zambia

ERIC Educational Resources Information Center

Mapoma, Christopher C.; Masaiti, Gift

2012-01-01

This paper reflects part of the wider outlook on ageing in general in Zambia and was intended to investigate perceptions of and attitudes towards the aged and ageing in Zambia by members of the community who, by definition and chronologically are not classified as aged i.e. not yet 60 years and over. Focus Group Discussions (FGD) were used to…

Decision Tree Approach for Soil Liquefaction Assessment

PubMed Central

Gandomi, Amir H.; Fridline, Mark M.; Roke, David A.

2013-01-01

In the current study, the performances of some decision tree (DT) techniques are evaluated for postearthquake soil liquefaction assessment. A database containing 620 records of seismic parameters and soil properties is used in this study. Three decision tree techniques are used here in two different ways, considering statistical and engineering points of view, to develop decision rules. The DT results are compared to the logistic regression (LR) model. The results of this study indicate that the DTs not only successfully predict liquefaction but they can also outperform the LR model. The best DT models are interpreted and evaluated based on an engineering point of view. PMID:24489498

Decision tree approach for soil liquefaction assessment.

PubMed

Gandomi, Amir H; Fridline, Mark M; Roke, David A

2013-01-01

In the current study, the performances of some decision tree (DT) techniques are evaluated for postearthquake soil liquefaction assessment. A database containing 620 records of seismic parameters and soil properties is used in this study. Three decision tree techniques are used here in two different ways, considering statistical and engineering points of view, to develop decision rules. The DT results are compared to the logistic regression (LR) model. The results of this study indicate that the DTs not only successfully predict liquefaction but they can also outperform the LR model. The best DT models are interpreted and evaluated based on an engineering point of view.

Fast Image Texture Classification Using Decision Trees

NASA Technical Reports Server (NTRS)

Thompson, David R.

2011-01-01

Texture analysis would permit improved autonomous, onboard science data interpretation for adaptive navigation, sampling, and downlink decisions. These analyses would assist with terrain analysis and instrument placement in both macroscopic and microscopic image data products. Unfortunately, most state-of-the-art texture analysis demands computationally expensive convolutions of filters involving many floating-point operations. This makes them infeasible for radiation- hardened computers and spaceflight hardware. A new method approximates traditional texture classification of each image pixel with a fast decision-tree classifier. The classifier uses image features derived from simple filtering operations involving integer arithmetic. The texture analysis method is therefore amenable to implementation on FPGA (field-programmable gate array) hardware. Image features based on the "integral image" transform produce descriptive and efficient texture descriptors. Training the decision tree on a set of training data yields a classification scheme that produces reasonable approximations of optimal "texton" analysis at a fraction of the computational cost. A decision-tree learning algorithm employing the traditional k-means criterion of inter-cluster variance is used to learn tree structure from training data. The result is an efficient and accurate summary of surface morphology in images. This work is an evolutionary advance that unites several previous algorithms (k-means clustering, integral images, decision trees) and applies them to a new problem domain (morphology analysis for autonomous science during remote exploration). Advantages include order-of-magnitude improvements in runtime, feasibility for FPGA hardware, and significant improvements in texture classification accuracy.

Determinants of farmers' tree planting investment decision as a degraded landscape management strategy in the central highlands of Ethiopia

NASA Astrophysics Data System (ADS)

Gessesse, B.; Bewket, W.; Bräuning, A.

2015-11-01

Land degradation due to lack of sustainable land management practices are one of the critical challenges in many developing countries including Ethiopia. This study explores the major determinants of farm level tree planting decision as a land management strategy in a typical framing and degraded landscape of the Modjo watershed, Ethiopia. The main data were generated from household surveys and analysed using descriptive statistics and binary logistic regression model. The model significantly predicted farmers' tree planting decision (Chi-square = 37.29, df = 15, P<0.001). Besides, the computed significant value of the model suggests that all the considered predictor variables jointly influenced the farmers' decision to plant trees as a land management strategy. In this regard, the finding of the study show that local land-users' willingness to adopt tree growing decision is a function of a wide range of biophysical, institutional, socioeconomic and household level factors, however, the likelihood of household size, productive labour force availability, the disparity of schooling age, level of perception of the process of deforestation and the current land tenure system have positively and significantly influence on tree growing investment decisions in the study watershed. Eventually, the processes of land use conversion and land degradation are serious which in turn have had adverse effects on agricultural productivity, local food security and poverty trap nexus. Hence, devising sustainable and integrated land management policy options and implementing them would enhance ecological restoration and livelihood sustainability in the study watershed.

Determinants of farmers' tree-planting investment decisions as a degraded landscape management strategy in the central highlands of Ethiopia

NASA Astrophysics Data System (ADS)

Gessesse, Berhan; Bewket, Woldeamlak; Bräuning, Achim

2016-04-01

Land degradation due to lack of sustainable land management practices is one of the critical challenges in many developing countries including Ethiopia. This study explored the major determinants of farm-level tree-planting decisions as a land management strategy in a typical farming and degraded landscape of the Modjo watershed, Ethiopia. The main data were generated from household surveys and analysed using descriptive statistics and a binary logistic regression model. The model significantly predicted farmers' tree-planting decisions (χ2 = 37.29, df = 15, P < 0.001). Besides, the computed significant value of the model revealed that all the considered predictor variables jointly influenced the farmers' decisions to plant trees as a land management strategy. The findings of the study demonstrated that the adoption of tree-growing decisions by local land users was a function of a wide range of biophysical, institutional, socioeconomic and household-level factors. In this regard, the likelihood of household size, productive labour force availability, the disparity of schooling age, level of perception of the process of deforestation and the current land tenure system had a critical influence on tree-growing investment decisions in the study watershed. Eventually, the processes of land-use conversion and land degradation were serious, which in turn have had adverse effects on agricultural productivity, local food security and poverty trap nexus. Hence, the study recommended that devising and implementing sustainable land management policy options would enhance ecological restoration and livelihood sustainability in the study watershed.

Ethnographic Decision Tree Modeling: A Research Method for Counseling Psychology.

ERIC Educational Resources Information Center

Beck, Kirk A.

2005-01-01

This article describes ethnographic decision tree modeling (EDTM; C. H. Gladwin, 1989) as a mixed method design appropriate for counseling psychology research. EDTM is introduced and located within a postpositivist research paradigm. Decision theory that informs EDTM is reviewed, and the 2 phases of EDTM are highlighted. The 1st phase, model…

Mental illness--stigma and discrimination in Zambia.

PubMed

Kapungwe, A; Cooper, S; Mwanza, J; Mwape, L; Sikwese, A; Kakuma, R; Lund, C; Flisher, A J

2010-07-01

The aim of this qualitative study was to explore the presence, causes and means of addressing individual and systemic stigma and discrimination against people with mental illness in Zambia. This is to facilitate the development of tailor-made antistigma initiatives that are culturally sensitive for Zambia and other low-income African countries. This is the first in-depth study on mental illness stigma in Zambia. Fifty semi-structured interviews and 6 focus group discussions were conducted with key stakeholders drawn from 3 districts in Zambia (Lusaka, Kabwe and Sinazongwe). Transcripts were analyzed using a grounded theory approach. Mental illness stigma and discrimination is pervasive across Zambian society, prevailing within the general community, amongst family members, amid general and mental health care providers, and at the level of government. Such stigma appears to be fuelled by misunderstandings of mental illness aetiology; fears of contagion and the perceived dangerousness of people with mental illness; and associations between HIV/AIDS and mental illness. Strategies suggested for reducing stigma and discrimination in Zambia included education campaigns, the transformation of mental health policy and legislation and expanding the social and economic opportunities of the mentally ill. In Zambia, as in many other low-income African countries, very little attention is devoted to addressing the negative beliefs and behaviours surrounding mental illness, despite the devastating costs that ensue. The results from this study underscore the need for greater commitment from governments and policy-makers in African countries to start prioritizing mental illness stigma as a major public health and development issue.

Classification of Parkinsonian syndromes from FDG-PET brain data using decision trees with SSM/PCA features.

PubMed

Mudali, D; Teune, L K; Renken, R J; Leenders, K L; Roerdink, J B T M

2015-01-01

Medical imaging techniques like fluorodeoxyglucose positron emission tomography (FDG-PET) have been used to aid in the differential diagnosis of neurodegenerative brain diseases. In this study, the objective is to classify FDG-PET brain scans of subjects with Parkinsonian syndromes (Parkinson's disease, multiple system atrophy, and progressive supranuclear palsy) compared to healthy controls. The scaled subprofile model/principal component analysis (SSM/PCA) method was applied to FDG-PET brain image data to obtain covariance patterns and corresponding subject scores. The latter were used as features for supervised classification by the C4.5 decision tree method. Leave-one-out cross validation was applied to determine classifier performance. We carried out a comparison with other types of classifiers. The big advantage of decision tree classification is that the results are easy to understand by humans. A visual representation of decision trees strongly supports the interpretation process, which is very important in the context of medical diagnosis. Further improvements are suggested based on enlarging the number of the training data, enhancing the decision tree method by bagging, and adding additional features based on (f)MRI data.

PRIA 3 Fee Determination Decision Tree

EPA Pesticide Factsheets

The PRIA 3 decision tree will help applicants requesting a pesticide registration or certain tolerance action to accurately identify the category of their application and the amount of the required fee before they submit the application.

Solar and Wind Site Screening Decision Trees

EPA Pesticide Factsheets

EPA and NREL created a decision tree to guide state and local governments and other stakeholders through a process for screening sites for their suitability for future redevelopment with solar photovoltaic (PV) energy and wind energy.

Provision and Management of Special Education in Community Schools: A Case of Donata, Malaikha and Shalom Community Schools in Zambia

ERIC Educational Resources Information Center

Mwamba, Mwenya N.

2016-01-01

Community schools appeared in Zambia in 1992 beginning with Lusaka and they quickly spread to other parts of the country. The Ministry of General Education recognizes its obligation to provide education of good quality to all children in response to national and international protocols to which Zambia is a part. The creation of Community Schools…

Bismarck in the Bush: Year 12 Write Zambia's History for Zambian Students

ERIC Educational Resources Information Center

Gray, Peter

2011-01-01

Peter Gray explains how his Year 12 students came to research and write a resource on the history of Zambia, for history teachers "in" Zambia. The construction of the resource stretched the Year 12 students in new ways: the Internet was useless and there were no easy digests in A-Level textbooks to get them started. They would have to…

7 CFR 319.56-43 - Baby corn and baby carrots from Zambia.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 5 2011-01-01 2011-01-01 false Baby corn and baby carrots from Zambia. 319.56-43... § 319.56-43 Baby corn and baby carrots from Zambia. (a) Immature, dehusked “baby” sweet corn (Zea mays L..., which is a field, where the corn has been grown must have been inspected at least once during the...

Provision of Learning and Teaching Materials for Pupils with Visual Impairment: Results from a National Survey in Zambia

ERIC Educational Resources Information Center

Akakandelwa, Akakandelwa; Munsanje, Joseph

2012-01-01

The aim of this study was to determine the provision of learning and teaching materials for pupils with visual impairment in basic and high schools of Zambia. A survey approach utilizing a questionnaire, interviews and a review of the literature was adopted for the study. The findings demonstrated that most schools in Zambia did not provide…

Influence of newborn health messages on care-seeking practices and community health behaviors among participants in the Zambia Chlorhexidine Application Trial.

PubMed

Sivalogan, Kasthuri; Semrau, Katherine E A; Ashigbie, Paul G; Mwangi, Sheila; Herlihy, Julie M; Yeboah-Antwi, Kojo; Banda, Bowen; Grogan, Caroline; Biemba, Godfrey; Hamer, Davidson H

2018-01-01

Identifying and understanding traditional perceptions that influence newborn care practices and care-seeking behavior are crucial to developing sustainable interventions to improve neonatal health. The Zambia Chlorhexidine Application Trial (ZamCAT), a large-scale cluster randomized trial, assessed the impact of 4% chlorhexidine on neonatal mortality and omphalitis in Southern Province, Zambia. The main purpose of this post-ZamCAT qualitative study was to understand the impact of newborn care health messages on care-seeking behavior for neonates and the acceptability, knowledge, and attitudes towards chlorhexidine cord care among community members and health workers in Southern Province. Five focus group discussions and twenty-six in-depth interviews were conducted with mothers and health workers from ten health centers (5 rural and 5 peri-urban/urban). Community perceptions and local realities were identified as fundamental to care-seeking decisions and influenced individual participation in particular health-seeking behaviors. ZamCAT field monitors (data collectors) disseminated health messages at the time of recruitment at the health center and during subsequent home visits. Mothers noted that ZamCAT field monitors were effective in providing lessons and education on newborn care practices and participating mothers were able to share these messages with others in their communities. Although the study found no effect of chlorhexidine cord washes on neonatal mortality, community members had positive views towards chlorhexidine as they perceived that it reduced umbilical cord infections and was a beneficial alternative to traditional cord applications. The acceptability of health initiatives, such as chlorhexidine cord application, in community settings, is dependent on community education, understanding, and engagement. Community-based approaches, such as using community-based cadres of health workers to strengthen referrals, are an acceptable and potentially effective strategy to improve care-seeking behaviors and practices.

Multi-country analysis of treatment costs for HIV/AIDS (MATCH): facility-level ART unit cost analysis in Ethiopia, Malawi, Rwanda, South Africa and Zambia.

PubMed

Tagar, Elya; Sundaram, Maaya; Condliffe, Kate; Matatiyo, Blackson; Chimbwandira, Frank; Chilima, Ben; Mwanamanga, Robert; Moyo, Crispin; Chitah, Bona Mukosha; Nyemazi, Jean Pierre; Assefa, Yibeltal; Pillay, Yogan; Mayer, Sam; Shear, Lauren; Dain, Mary; Hurley, Raphael; Kumar, Ritu; McCarthy, Thomas; Batra, Parul; Gwinnell, Dan; Diamond, Samantha; Over, Mead

2014-01-01

Today's uncertain HIV funding landscape threatens to slow progress towards treatment goals. Understanding the costs of antiretroviral therapy (ART) will be essential for governments to make informed policy decisions about the pace of scale-up under the 2013 WHO HIV Treatment Guidelines, which increase the number of people eligible for treatment from 17.6 million to 28.6 million. The study presented here is one of the largest of its kind and the first to describe the facility-level cost of ART in a random sample of facilities in Ethiopia, Malawi, Rwanda, South Africa and Zambia. In 2010-2011, comprehensive data on one year of facility-level ART costs and patient outcomes were collected from 161 facilities, selected using stratified random sampling. Overall, facility-level ART costs were significantly lower than expected in four of the five countries, with a simple average of $208 per patient-year (ppy) across Ethiopia, Malawi, Rwanda and Zambia. Costs were higher in South Africa, at $682 ppy. This included medications, laboratory services, direct and indirect personnel, patient support, equipment and administrative services. Facilities demonstrated the ability to retain patients alive and on treatment at these costs, although outcomes for established patients (2-8% annual loss to follow-up or death) were better than outcomes for new patients in their first year of ART (77-95% alive and on treatment). This study illustrated that the facility-level costs of ART are lower than previously understood in these five countries. While limitations must be considered, and costs will vary across countries, this suggests that expanded treatment coverage may be affordable. Further research is needed to understand investment costs of treatment scale-up, non-facility costs and opportunities for more efficient resource allocation.

Enhancing global health and education in Malawi, Zambia, and the United States through an interprofessional global health exchange program.

PubMed

Wilson, Lynda Law; Somerall, D'Ann; Theus, Lisa; Rankin, Sally; Ngoma, Catherine; Chimwaza, Angela

2014-05-01

This article describes participant outcomes of an interprofessional collaboration between health professionals and faculty in Malawi, Zambia, and the United States (US). One strategy critical for improving global health and addressing Millennium Development goals is promotion of interprofessional education and collaboration. Program participants included 25 health professionals from Malawi and Zambia, and 19 faculty/health professionals from Alabama and California. African Fellows participated in a 2 week workshop on Interprofessional Education in Alabama followed by 2 weeks working on individual goals with faculty collaborators/mentors. The US Fellows also spent 2 weeks visiting their counterparts in Malawi and Zambia to develop plans for sustainable partnerships. Program evaluations demonstrated participants' satisfaction with the program and indicated that the program promoted interprofessional and cross-cultural understanding; fostered development of long-term sustainable partnerships between health professionals and educators in Zambia and the US; and created increased awareness and use of resources for global health education. © 2014.

Flexible engineering designs for urban water management in Lusaka, Zambia.

PubMed

Tembo, Lucy; Pathirana, Assela; van der Steen, Peter; Zevenbergen, Chris

2015-01-01

Urban water systems are often designed using deterministic single values as design parameters. Subsequently the different design alternatives are compared using a discounted cash flow analysis that assumes that all parameters remain as-predicted for the entire project period. In reality the future is unknown and at best a possible range of values for design parameters can be estimated. A Monte Carlo simulation could then be used to calculate the expected Net Present Value of project alternatives, as well as so-called target curves (cumulative frequency distribution of possible Net Present Values). The same analysis could be done after flexibilities were incorporated in the design, either by using decision rules to decide about the moment of capacity increase, or by buying Real Options (in this case land) to cater for potential capacity increases in the future. This procedure was applied to a sanitation and wastewater treatment case in Lusaka, Zambia. It included various combinations of on-site anaerobic baffled reactors and off-site waste stabilisation ponds. For the case study, it was found that the expected net value of wastewater treatment systems can be increased by 35-60% by designing a small flexible system with Real Options, rather than a large inflexible system.

Applying of Decision Tree Analysis to Risk Factors Associated with Pressure Ulcers in Long-Term Care Facilities.

PubMed

Moon, Mikyung; Lee, Soo-Kyoung

2017-01-01

The purpose of this study was to use decision tree analysis to explore the factors associated with pressure ulcers (PUs) among elderly people admitted to Korean long-term care facilities. The data were extracted from the 2014 National Inpatient Sample (NIS)-data of Health Insurance Review and Assessment Service (HIRA). A MapReduce-based program was implemented to join and filter 5 tables of the NIS. The outcome predicted by the decision tree model was the prevalence of PUs as defined by the Korean Standard Classification of Disease-7 (KCD-7; code L89 * ). Using R 3.3.1, a decision tree was generated with the finalized 15,856 cases and 830 variables. The decision tree displayed 15 subgroups with 8 variables showing 0.804 accuracy, 0.820 sensitivity, and 0.787 specificity. The most significant primary predictor of PUs was length of stay less than 0.5 day. Other predictors were the presence of an infectious wound dressing, followed by having diagnoses numbering less than 3.5 and the presence of a simple dressing. Among diagnoses, "injuries to the hip and thigh" was the top predictor ranking 5th overall. Total hospital cost exceeding 2,200,000 Korean won (US $2,000) rounded out the top 7. These results support previous studies that showed length of stay, comorbidity, and total hospital cost were associated with PUs. Moreover, wound dressings were commonly used to treat PUs. They also show that machine learning, such as a decision tree, could effectively predict PUs using big data.

Predicting the probability of mortality of gastric cancer patients using decision tree.

PubMed

Mohammadzadeh, F; Noorkojuri, H; Pourhoseingholi, M A; Saadat, S; Baghestani, A R

2015-06-01

Gastric cancer is the fourth most common cancer worldwide. This reason motivated us to investigate and introduce gastric cancer risk factors utilizing statistical methods. The aim of this study was to identify the most important factors influencing the mortality of patients who suffer from gastric cancer disease and to introduce a classification approach according to decision tree model for predicting the probability of mortality from this disease. Data on 216 patients with gastric cancer, who were registered in Taleghani hospital in Tehran,Iran, were analyzed. At first, patients were divided into two groups: the dead and alive. Then, to fit decision tree model to our data, we randomly selected 20% of dataset to the test sample and remaining dataset considered as the training sample. Finally, the validity of the model examined with sensitivity, specificity, diagnosis accuracy and the area under the receiver operating characteristic curve. The CART version 6.0 and SPSS version 19.0 softwares were used for the analysis of the data. Diabetes, ethnicity, tobacco, tumor size, surgery, pathologic stage, age at diagnosis, exposure to chemical weapons and alcohol consumption were determined as effective factors on mortality of gastric cancer. The sensitivity, specificity and accuracy of decision tree were 0.72, 0.75 and 0.74 respectively. The indices of sensitivity, specificity and accuracy represented that the decision tree model has acceptable accuracy to prediction the probability of mortality in gastric cancer patients. So a simple decision tree consisted of factors affecting on mortality of gastric cancer may help clinicians as a reliable and practical tool to predict the probability of mortality in these patients.

Moving Towards Inclusive Education Policies and Practices? Basic Education for AIDS Orphans and Other Vulnerable Children in Zambia

ERIC Educational Resources Information Center

Robson, Sue; Kanyanta, Sylvester Bonaventure

2007-01-01

The global spread of HIV and AIDS has presented a major threat to development, affecting the health of the poor and many aspects of social and economic development. The greatest impact of the epidemic has been felt in sub-Saharan Africa, and Zambia ranks among the worst hit countries. The Free Basic Education Policy in Zambia upholds the right of…

Leprosy trends in Zambia 1991-2009.

PubMed

Kapata, Nathan; Chanda-Kapata, Pascalina; Grobusch, Martin Peter; O'Grady, Justin; Bates, Matthew; Mwaba, Peter; Zumla, Alimuddin

2012-10-01

To document leprosy trends in Zambia over the past two decades to ascertain the importance of leprosy as a health problem in Zambia. Retrospective study covering the period 1991-2009 of routine national leprosy surveillance data, published national programme review reports and desk reviews of in-country TB reports. Data reports were available for all the years under study apart from years 2001, 2002 and 2006. The Leprosy case notification rates (CNR) declined from 2.73/10 000 population in 1991 to 0.43/10 000 population in 2009. The general leprosy burden showed a downward trend for both adults and children. Leprosy case burden dropped from approximately 18 000 cases in 1980 to only about 1000 cases in 1996, and by the year 2000, the prevalence rates had fallen to 0.67/10 000 population. There were more multibacillary cases of leprosy than pauci-bacillary cases. Several major gaps in data recording, entry and surveillance were identified. Data on disaggregation by gender, HIV status or geographical origin were not available. Whilst Zambia has achieved WHO targets for leprosy control, leprosy prevalence data from Zambia may not reflect real situation because of poor data recording and surveillance. Greater investment into infrastructure and training are required for more accurate surveillance of leprosy in Zambia. © 2012 Blackwell Publishing Ltd.

The Zambia Children's KS-HHV8 Study: Rationale, Study Design, and Study Methods

PubMed Central

Minhas, Veenu; Crabtree, Kay L.; Chao, Ann; Wojcicki, Janet M.; Sifuniso, Adrian M.; Nkonde, Catherine; Kankasa, Chipepo; Mitchell, Charles D.; Wood, Charles

2011-01-01

The epidemic of human immunodeficiency virus in Zambia has led to a dramatic rise in the incidence of human herpesvirus-8 (HHV-8)–associated Kaposi's sarcoma in both adults and children. However, there is a paucity of knowledge about the routes of HHV-8 transmission to young children. The Zambia Children's KS-HHV8 Study, a large, prospective cohort study in Lusaka, Zambia, was launched in 2004 to investigate the role of household members as a source of HHV-8 infection in young children and social behaviors that may modify the risk of HHV-8 acquisition. This cohort is distinct from other epidemiologic studies designed to investigate HHV-8 incidence and transmission because it recruited and followed complete households in the urban central African context. Between July 2004 and March 2007, 1,600 households were screened; 368 households comprising 464 children and 1,335 caregivers and household members were enrolled. Follow-up of this population continued for 48 months postrecruitment, affording a unique opportunity to study horizontal transmission of HHV-8 and understand the routes and sources of transmission to young children in Zambia. The authors describe the study rationale, design, execution, and characteristics of this cohort, which provides critical data on the epidemiology and transmission of HHV-8 to young children in Zambia. PMID:21447476

Diagnostic classification scheme in Iranian breast cancer patients using a decision tree.

PubMed

Malehi, Amal Saki

2014-01-01

The objective of this study was to determine a diagnostic classification scheme using a decision tree based model. The study was conducted as a retrospective case-control study in Imam Khomeini hospital in Tehran during 2001 to 2009. Data, including demographic and clinical-pathological characteristics, were uniformly collected from 624 females, 312 of them were referred with positive diagnosis of breast cancer (cases) and 312 healthy women (controls). The decision tree was implemented to develop a diagnostic classification scheme using CART 6.0 Software. The AUC (area under curve), was measured as the overall performance of diagnostic classification of the decision tree. Five variables as main risk factors of breast cancer and six subgroups as high risk were identified. The results indicated that increasing age, low age at menarche, single and divorced statues, irregular menarche pattern and family history of breast cancer are the important diagnostic factors in Iranian breast cancer patients. The sensitivity and specificity of the analysis were 66% and 86.9% respectively. The high AUC (0.82) also showed an excellent classification and diagnostic performance of the model. Decision tree based model appears to be suitable for identifying risk factors and high or low risk subgroups. It can also assists clinicians in making a decision, since it can identify underlying prognostic relationships and understanding the model is very explicit.

Ultrasonographic Diagnosis of Biliary Atresia Based on a Decision-Making Tree Model.

PubMed

Lee, So Mi; Cheon, Jung-Eun; Choi, Young Hun; Kim, Woo Sun; Cho, Hyun-Hae; Cho, Hyun-Hye; Kim, In-One; You, Sun Kyoung

2015-01-01

To assess the diagnostic value of various ultrasound (US) findings and to make a decision-tree model for US diagnosis of biliary atresia (BA). From March 2008 to January 2014, the following US findings were retrospectively evaluated in 100 infants with cholestatic jaundice (BA, n = 46; non-BA, n = 54): length and morphology of the gallbladder, triangular cord thickness, hepatic artery and portal vein diameters, and visualization of the common bile duct. Logistic regression analyses were performed to determine the features that would be useful in predicting BA. Conditional inference tree analysis was used to generate a decision-making tree for classifying patients into the BA or non-BA groups. Multivariate logistic regression analysis showed that abnormal gallbladder morphology and greater triangular cord thickness were significant predictors of BA (p = 0.003 and 0.001; adjusted odds ratio: 345.6 and 65.6, respectively). In the decision-making tree using conditional inference tree analysis, gallbladder morphology and triangular cord thickness (optimal cutoff value of triangular cord thickness, 3.4 mm) were also selected as significant discriminators for differential diagnosis of BA, and gallbladder morphology was the first discriminator. The diagnostic performance of the decision-making tree was excellent, with sensitivity of 100% (46/46), specificity of 94.4% (51/54), and overall accuracy of 97% (97/100). Abnormal gallbladder morphology and greater triangular cord thickness (> 3.4 mm) were the most useful predictors of BA on US. We suggest that the gallbladder morphology should be evaluated first and that triangular cord thickness should be evaluated subsequently in cases with normal gallbladder morphology.

Correlation Between the System Capabilities Analytic Process (SCAP) and the Missions and Means Framework (MMF)

DTIC Science & Technology

2013-05-01

specifics of the correlation will be explored followed by discussion of new paradigms— the ordered event list (OEL) and the decision tree — that result from...4.2.1  Brief Overview of the Decision Tree Paradigm ................................................15  4.2.2  OEL Explained...6  Figure 3. A depiction of a notional fault/activation tree . ................................................................7

Personalized Modeling for Prediction with Decision-Path Models

PubMed Central

Visweswaran, Shyam; Ferreira, Antonio; Ribeiro, Guilherme A.; Oliveira, Alexandre C.; Cooper, Gregory F.

2015-01-01

Deriving predictive models in medicine typically relies on a population approach where a single model is developed from a dataset of individuals. In this paper we describe and evaluate a personalized approach in which we construct a new type of decision tree model called decision-path model that takes advantage of the particular features of a given person of interest. We introduce three personalized methods that derive personalized decision-path models. We compared the performance of these methods to that of Classification And Regression Tree (CART) that is a population decision tree to predict seven different outcomes in five medical datasets. Two of the three personalized methods performed statistically significantly better on area under the ROC curve (AUC) and Brier skill score compared to CART. The personalized approach of learning decision path models is a new approach for predictive modeling that can perform better than a population approach. PMID:26098570

Cigarette Price and Other Factors Associated with Brand Choice and Brand Loyalty in Zambia: Findings from the ITC Zambia Survey

PubMed Central

Salloum, Ramzi G.; Goma, Fastone; Chelwa, Grieve; Cheng, Xi; Zulu, Richard; Kaai, Susan C.; Quah, Anne C.K.; Thrasher, James F.; Fong, Geoffrey T.

2015-01-01

Objectives Little is known about cigarette pricing and brand loyalty in sub-Saharan Africa. This study examines these issues in Zambia, analyzing data from the International Tobacco Control (ITC) Zambia Survey. Methods Data from Wave 1 of the ITC Zambia Survey (2012) were analyzed for current smokers of factory-made (FM) cigarettes compared to those who smoked both FM and roll-your-own (RYO) cigarettes, using multivariate logistic regression models to identify the predictors of brand loyalty and reasons for brand choice. Results 75% of FM-only smokers and 64% of FM+RYO smokers reported having a regular brand. Compared with FM-only smokers, FM+RYO smokers were, on average, older (28% vs. 20% ≥ 40 years), low income (64% vs. 43%), and had lower education (76% vs. 44% < secondary). Mean price across FM brands was ZMW0.50 (USD0.08) per stick. Smokers were significantly less likely to be brand-loyal (>1 year) if they were aged 15-17 years (vs. 40-54 years) and if they had moderate (vs. low) income. Brand choice was predicted mostly by friends, taste, and brand popularity. Price was more likely to be a reason for brand loyalty among FM+RYO smokers, among ≥55 year old smokers, and among those who reported being more addicted to cigarettes. Conclusions These results in Zambia document the high levels of brand loyalty in a market where price variation is fairly small across cigarette brands. Future research is needed on longitudinal trends to evaluate the effect of tobacco control policies in Zambia. PMID:25631482

Space/age forestry: Implications of planting density and rotation age in SRIC management decisions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Merriam, R.A.; Phillips, V.D.; Liu, W.

1993-12-31

Short-rotation intensive-culture (SRIC) of promising tree crops is being evaluated worldwide for the production of methanol, ethanol, and electricity from renewable biomass resources. Planting density and rotation age are fundamental management decisions associated with SRIC energy plantations. Most studies of these variables have been conducted without the benefit of a unifying theory of the effects of growing space and rotation age on individual tree growth and stand level productivity. A modeling procedure based on field trials of Eucalyptus spp. is presented that evaluates the growth potential of a tree in the absence and presence of competition of neighboring trees inmore » a stand. The results of this analysis are useful in clarifying economic implications of different growing space and rotation age decisions that tree plantation managers must make. The procedure is readily applicable to other species under consideration for SRIC plantations at any location.« less

A conceptual framework for effectively anticipating water-quality changes resulting from changes in agricultural activities

USGS Publications Warehouse

Capel, Paul D.; Wolock, David M.; Coupe, Richard H.; Roth, Jason L.

2018-01-10

Agricultural activities can affect water quality and the health of aquatic ecosystems; many water-quality issues originate with the movement of water, agricultural chemicals, and eroded soil from agricultural areas to streams and groundwater. Most agricultural activities are designed to sustain or increase crop production, while some are designed to protect soil and water resources. Numerous soil- and water-protection practices are designed to reduce the volume and velocity of runoff and increase infiltration. This report presents a conceptual framework that combines generalized concepts on the movement of water, the environmental behavior of chemicals and eroded soil, and the designed functions of various agricultural activities, as they relate to hydrology, to create attainable expectations for the protection of—with the goal of improving—water quality through changes in an agricultural activity.The framework presented uses two types of decision trees to guide decision making toward attainable expectations regarding the effectiveness of changing agricultural activities to protect and improve water quality in streams. One decision tree organizes decision making by considering the hydrologic setting and chemical behaviors, largely at the field scale. This decision tree can help determine which agricultural activities could effectively protect and improve water quality in a stream from the movement of chemicals, or sediment, from a field. The second decision tree is a chemical fate accounting tree. This decision tree helps set attainable expectations for the permanent removal of sediment, elements, and organic chemicals—such as herbicides and insecticides—through trapping or conservation tillage practices. Collectively, this conceptual framework consolidates diverse hydrologic settings, chemicals, and agricultural activities into a single, broad context that can be used to set attainable expectations for agricultural activities. This framework also enables better decision making for future agricultural activities as a means to reduce current, and prevent new, water-quality issues.

Rapid assessment and mapping of tree cover in southern African savanna woodlands using a new iPhone App and Landsat 8 imagery

NASA Astrophysics Data System (ADS)

Fuller, D. O.

2016-12-01

Tree cover is a key parameter in climate modeling. It strongly influences CO2 exchanges between the land surface and atmosphere and surface energy balance. We measured percent woody canopy cover (PWCC) in the savanna woodlands of eastern Zambia over a 10-day period in May 2016 using a new iPhone App (CanopyApp) and related these field measurements to Landsat 8 (L8) Band 4 (red) imagery acquired approximately the same time. We then used parameters from the band 4 digital numbers (DNs)-PWCC linear regression to derive a new map of PWCC for the entire L8 scene. Consistent with theory and previous empirical studies, we found that the relationship between L8 band 4 DNs- PWCC was negative and linear (r2 = 0.61, p < 0.05). Interestingly, the relationship between PWCC and L8 band 4 surface reflectance was weaker (r2 = 0.46, p < 0.05) than that for DNs. This suggests that the scene model used in L8 atmospheric correction may not account well for within-pixel shadowing effects and other spatial inhomogeneities from variable soil and background reflectance. Our PWCC map agreed qualitatively with similar percent tree-cover maps based on Landsat level 1 products and past field studies in the area conducted using a hemispherical lens. Our results also compared favorably with other remote sensing studies that have used complex multivariate approaches to estimate tree cover, which suggests that use of a single L8 band 4 is sufficient to estimate PWCC when spectral contrast exists between the grass, soil and tree layers during the austral fall period in southern African savannas.

Vlsi implementation of flexible architecture for decision tree classification in data mining

NASA Astrophysics Data System (ADS)

Sharma, K. Venkatesh; Shewandagn, Behailu; Bhukya, Shankar Nayak

2017-07-01

The Data mining algorithms have become vital to researchers in science, engineering, medicine, business, search and security domains. In recent years, there has been a terrific raise in the size of the data being collected and analyzed. Classification is the main difficulty faced in data mining. In a number of the solutions developed for this problem, most accepted one is Decision Tree Classification (DTC) that gives high precision while handling very large amount of data. This paper presents VLSI implementation of flexible architecture for Decision Tree classification in data mining using c4.5 algorithm.

The quest for a framework for sustainable and institutionalised priority-setting for health research in a low-resource setting: the case of Zambia.

PubMed

Kapiriri, Lydia; Chanda-Kapata, Pascalina

2018-02-17

Priority-setting for health research in low-income countries remains a major challenge. While there have been efforts to systematise and improve the processes, most of the initiatives have ended up being a one-off exercise and are yet to be institutionalised. This could, in part, be attributed to the limited capacity for the priority-setting institutions to identify and fund their own research priorities, since most of the priority-setting initiatives are driven by experts. This paper reports findings from a pilot project whose aim was to develop a systematic process to identify components of a locally desirable and feasible health research priority-setting approach and to contribute to capacity strengthening for the Zambia National Health Research Authority. Synthesis of the current literature on the approaches to health research prioritisations. The results of the synthesis were presented and discussed with a sample of Zambian researchers and decision-makers who are involved in health research priority-setting. The ultimate aim was for them to explore the different approaches available for guiding health research priority-setting and to identify an approach that would be relevant and feasible to implement and sustain within the Zambian context. Based on the evidence that was presented, the participants were unable to identify one approach that met the criteria. They identified attributes from the different approaches that they thought would be most appropriate and proposed a process that they deemed feasible within the Zambian context. While it is easier to implement prioritisation based on one approach that the initiator might be interested in, researchers interested in capacity-building for health research priority-setting organisations should expose the low-income country participants to all approaches. Researchers ought to be aware that sometimes one shoe may not fit all, as in the case of Zambia, instead of choosing one approach, the stakeholders may select desirable attributes from the different approaches and piece together an approach that would be feasible and acceptable within their context. An approach that builds on the decision-makers' understanding of their contexts and their input to its development would foster local ownership and has a greater potential for sustainability.

Sub-Saharan Africa Report.

DTIC Science & Technology

1987-01-20

SIGN CONTRACT TO IMPROVE TELECOMMUNICATIONS MB171512 Dakar PANA in English 1431 GMT 17 Dec 86 [Text] Ndola (Zambia), 17 Dec ( ZANA /PANA)—Zambia...rice produc- tion. Sikasula told the official Zambia News Agency ZANA today that he was highly impressed by the work being carried out by the Chinese...rights their almost total reliance on the goodwill of the farmer often leaves them in poor hous- ing, far from medical services and trapped in

Applying Data Mining Techniques to Extract Hidden Patterns about Breast Cancer Survival in an Iranian Cohort Study.

PubMed

Khalkhali, Hamid Reza; Lotfnezhad Afshar, Hadi; Esnaashari, Omid; Jabbari, Nasrollah

2016-01-01

Breast cancer survival has been analyzed by many standard data mining algorithms. A group of these algorithms belonged to the decision tree category. Ability of the decision tree algorithms in terms of visualizing and formulating of hidden patterns among study variables were main reasons to apply an algorithm from the decision tree category in the current study that has not studied already. The classification and regression trees (CART) was applied to a breast cancer database contained information on 569 patients in 2007-2010. The measurement of Gini impurity used for categorical target variables was utilized. The classification error that is a function of tree size was measured by 10-fold cross-validation experiments. The performance of created model was evaluated by the criteria as accuracy, sensitivity and specificity. The CART model produced a decision tree with 17 nodes, 9 of which were associated with a set of rules. The rules were meaningful clinically. They showed in the if-then format that Stage was the most important variable for predicting breast cancer survival. The scores of accuracy, sensitivity and specificity were: 80.3%, 93.5% and 53%, respectively. The current study model as the first one created by the CART was able to extract useful hidden rules from a relatively small size dataset.

Lithostratigraphical correlation of the Neoproterozoic Roan Supergroup from Shaba (Zaire) and Zambia, in the central African copper-cobalt metallogenic province

NASA Astrophysics Data System (ADS)

Cailteux, J.; Binda, P. L.; Katekesha, W. M.; Kampunzu, A. B.; Intiomale, M. M.; Kapenda, D.; Kaunda, C.; Ngongo, K.; Tshiauka, T.; Wendorff, M.

1994-11-01

New data on the lower Katangan sequences in Shaba (Zaire) and Zambia, collected during the 1989 and 1990 UNESCO-sponsored Geotraverses, reveal an important development on friction breccias throughout the Zambian Copperbelt, which still remains poorly documented, and shows that the Zairean and Zambian facies of the Roan Supergroup can be correlated in detail. As in Zaire, the deformation of Katangan terranes during the Lufilian orogeny produced important friction breccias in Zambia. Such breccias occur mostly between the upper part of the Lower Roan Supergroup and the Mwashya Group (R-4): above the shale with grit (RL3) at Konkola and Mindola, or within the Upper Roan Dolomite at Chambishi South, Muliashi and Nchanga. At Mufulira, a typical fragment of Shaba Mines Group was observed within a major heterogeneous tectonic breccia. This situation is similar to that reported at Kipapila (Kimpe) and Lubembe in Zaire, both located on the same tectonic trend as Mufulira. However, a continuous stratigraphical succession can be observed in Zambia from the basal unconformity to the Mwashya Group. Strong lithological similarities were found, formation by formation, between the Roan sequences of Zambia and Zaire. In particular, the complete Mines Group of Zaire (R-2) and the units from the RL6 to the RL4 in Zambia were deposited under comparable conditions of sedimentation and show a similar and correlatable evolution of lithologies. Furthermore, the overlying Dipeta Group (R-3) of Zaire and the RL3, RU2/RU1 of Zambia, are equally comparable. Above the Upper Roan Dolomite, Lower Mwashya dolomitic rocks, identical with the ones of Shaba, have been noted to occur in Zambia in stratigraphical continuity with the typical black shales of the Upper Mwashya. The correlation between the coarse clastics of the Zambian footwall (RL7) and the red dolomitic argillites and sandstones of the Zairean R.A.T. (Roches Argillo Talqueuses: R-1) remains uncertain. However these two sequences show some similarities suggesting a lateral facies change from high-energy siliciclastic sedimentation in Zambia, to quieter, less clastic and more carbonate rich sedimentation in Zaire. In agreement with the proposed lithostratigraphical correlation, volcanic and pyroclastic rocks, occurring both in Zaire and Zambia in the Lower Mwashya, testify to a major period of igneous activity in the region. Intrusive rocks found in the Zambian Roan Group and in the Zairean Dipeta Group can probably be attributed to the same episode of magmatism. Finally it can be shown that several copper-cobalt orebodies are found at the same lithostratigraphical position in Zambia and Zaire: the Zambian ore shale corresponds to the classical Shaba orebodies at the base of the Mines Group (R-2), the Nchanga upper orebody to the lower R-2.3 mineralization and the Zambian RL3 anomalous copper occurrences to those of the R-3.1.2 Dipeta unit.

The Utility of Decision Trees in Oncofertility Care in Japan.

PubMed

Ito, Yuki; Shiraishi, Eriko; Kato, Atsuko; Haino, Takayuki; Sugimoto, Kouhei; Okamoto, Aikou; Suzuki, Nao

2017-03-01

To identify the utility and issues associated with the use of decision trees in oncofertility patient care in Japan. A total of 35 women who had been diagnosed with cancer, but had not begun anticancer treatment, were enrolled. We applied the oncofertility decision tree for women published by Gardino et al. to counsel a consecutive series of women on fertility preservation (FP) options following cancer diagnosis. Percentage of women who decided to undergo oocyte retrieval for embryo cryopreservation and the expected live-birth rate for these patients were calculated using the following equation: expected live-birth rate = pregnancy rate at each age per embryo transfer × (1 - miscarriage rate) × No. of cryopreserved embryos. Oocyte retrieval was performed for 17 patients (48.6%; mean ± standard deviation [SD] age, 36.35 ± 3.82 years). The mean ± SD number of cryopreserved embryos was 5.29 ± 4.63. The expected live-birth rate was 0.66. The expected live-birth rate with FP indicated that one in three oncofertility patients would not expect to have a live birth following oocyte retrieval and embryo cryopreservation. While the decision trees were useful as decision-making tools for women contemplating FP, in the context of the current restrictions on oocyte donation and the extremely small number of adoptions in Japan, the remaining options for fertility after cancer are limited. In order for cancer survivors to feel secure in their decisions, the decision tree may need to be adapted simultaneously with improvements to the social environment, such as greater support for adoption.

Can family planning outreach bridge the urban-rural divide in Zambia?

PubMed

White, Justin S; Speizer, Ilene S

2007-09-05

Zambia experienced declining aggregate fertility and increasing aggregate contraceptive use from 1990 to 2000. Yet, in rural Zambia, progress in family planning has lagged far behind the advances made in Zambia's urban areas. The contraceptive prevalence rate in Lusaka and other urban areas outstripped the rate in rural Zambia by nearly 25 percentage points (41.2 percent versus 16.6 percent) in 2001. The total fertility rate varied between urban and rural areas by 2.5 children (4.3 versus 6.9 children). This paper considers the urban-rural differentials in Zambia and assesses family planning outreach as a tool to narrow this divide. This study uses the Zambia Demographic and Health Survey (DHS) data, collected between 2001 and 2002. Logistic regression techniques were employed to examine factors associated with contraceptive use. The first analysis tested modern contraceptive use versus traditional method use and no use. In addition, separate models were run for samples stratified by type of residence (rural or urban) to determine if different factors were associated with use by residence. A simulation determined the effect of all women receiving at least one household visit from a health worker if all other variables were held constant. Differences in modern contraceptive use between urban and rural areas persist (OR: 1.56, 95 percent CI: 1.24-1.96) even after adjusting for a number of demographic, socioeconomic, cognitive, and attitudinal factors. Household visits by a community health worker significantly increased the likelihood of modern contraceptive use among rural women (OR: 1.83; 95 percent CI: 1.29-2.58). If all rural women received at least one outreach visit per year, the prevalence rate for modern contraceptive methods would be expected to increase for this group by 5.9 percentage points, a marked increase but less than one-quarter of the total urban-rural differential. Outreach in the form of health worker visits can improve access to family planning services, but it does not eliminate barriers to access or address continued high-fertility desires in Zambia. Until policymakers consider strategies that address both family planning demand creation and supply of services, progress in Zambia and the rest of sub-Saharan Africa will continue to lag behind the rest of the world.

Aspergillus section Flavi community structure in Zambia influences aflatoxin contamination of maize and groundnut.

PubMed

Kachapulula, Paul W; Akello, Juliet; Bandyopadhyay, Ranajit; Cotty, Peter J

2017-11-16

Aflatoxins are cancer-causing, immuno-suppressive mycotoxins that frequently contaminate important staples in Zambia including maize and groundnut. Several species within Aspergillus section Flavi have been implicated as causal agents of aflatoxin contamination in Africa. However, Aspergillus populations associated with aflatoxin contamination in Zambia have not been adequately detailed. Most of Zambia's arable land is non-cultivated and Aspergillus communities in crops may originate in non-cultivated soil. However, relationships between Aspergillus populations on crops and those resident in non-cultivated soils have not been explored. Because characterization of similar fungal populations outside of Zambia have resulted in strategies to prevent aflatoxins, the current study sought to improve understanding of fungal communities in cultivated and non-cultivated soils and in crops. Crops (n=412) and soils from cultivated (n=160) and non-cultivated land (n=60) were assayed for Aspergillus section Flavi from 2012 to 2016. The L-strain morphotype of Aspergillus flavus and A. parasiticus were dominant on maize and groundnut (60% and 42% of Aspergillus section Flavi, respectively). Incidences of A. flavus L-morphotype were negatively correlated with aflatoxin in groundnut (log y=2.4990935-0.09966x, R 2 =0.79, P=0.001) but not in maize. Incidences of A. parasiticus partially explained groundnut aflatoxin concentrations in all agroecologies and maize aflatoxin in agroecology III (log y=0.1956034+0.510379x, R 2 =0.57, P<0.001) supporting A. parasiticus as the dominant etiologic agent of aflatoxin contamination in Zambia. Communities in both non-cultivated and cultivated soils were dominated by A. parasiticus (69% and 58%, respectively). Aspergillus parasiticus from cultivated and non-cultivated land produced statistically similar concentrations of aflatoxins. Aflatoxin-producers causing contamination of crops in Zambia may be native and, originate from non-cultivated areas, and not be introduced with non-native crops such as maize and groundnut. Non-cultivated land may be an important reservoir from which aflatoxin-producers are repeatedly introduced to cultivated areas. The potential of atoxigenic members of the A. flavus-L morphotype for management of aflatoxin in Zambia is also suggested. Characterization of the causal agents of aflatoxin contamination in agroecologies across Zambia gives support for modifying fungal community structure to reduce the aflatoxin-producing potential. Published by Elsevier B.V.

Comparison of Naive Bayes and Decision Tree on Feature Selection Using Genetic Algorithm for Classification Problem

NASA Astrophysics Data System (ADS)

Rahmadani, S.; Dongoran, A.; Zarlis, M.; Zakarias

2018-03-01

This paper discusses the problem of feature selection using genetic algorithms on a dataset for classification problems. The classification model used is the decicion tree (DT), and Naive Bayes. In this paper we will discuss how the Naive Bayes and Decision Tree models to overcome the classification problem in the dataset, where the dataset feature is selectively selected using GA. Then both models compared their performance, whether there is an increase in accuracy or not. From the results obtained shows an increase in accuracy if the feature selection using GA. The proposed model is referred to as GADT (GA-Decision Tree) and GANB (GA-Naive Bayes). The data sets tested in this paper are taken from the UCI Machine Learning repository.

The institutional context of tobacco production in Zambia.

PubMed

Labonté, Ronald; Lencucha, Raphael; Drope, Jeffrey; Packer, Corinne; Goma, Fastone M; Zulu, Richard

2018-01-16

Tobacco production is said to be an important contributor to Zambia's economy in terms of labour and revenue generation. In light of Zambia's obligations under the WHO Framework Convention of Tobacco Control (FCTC) we examined the institutional actors in Zambia's tobacco sector to better understand their roles and determine the institutional context that supports tobacco production in Zambia. Findings from 26 qualitative, semi-structured individual or small-group interviews with key informants from governmental, intergovernmental and non-governmental organisations were analysed, along with data and information from published literature. Although Zambia is obligated under the FCTC to take steps to reduce tobacco production, the country's weak economy and strong tobacco interests make it difficult to achieve this goal. Respondents uniformly acknowledged that growing the country's economy and ensuring employment for its citizens are the government's top priorities. Lacklustre coordination and collaboration between the institutional actors, both within and outside government, contributes to an environment that helps sustain tobacco production in the country. A Tobacco Products Control Bill has been under review for a number of years, but with no supply measures included, and with no indication of when or whether it will be passed. As with other low-income countries involved in tobacco production, there is inconsistency between Zambia's economic policy to strengthen the country's economy and its FCTC commitment to regulate and control tobacco production. The absence of a whole-of-government approach towards tobacco control has created an institutional context of duelling objectives, with some government ministries working at cross-purposes and tobacco interests left unchecked. With no ultimate coordinating authority, this industry risks being run according to the desire and demands of multinational tobacco companies, with few, if any, checks against them.

Cigarette price and other factors associated with brand choice and brand loyalty in Zambia: findings from the ITC Zambia Survey.

PubMed

Salloum, Ramzi G; Goma, Fastone; Chelwa, Grieve; Cheng, Xi; Zulu, Richard; Kaai, Susan C; Quah, Anne C K; Thrasher, James F; Fong, Geoffrey T

2015-07-01

Little is known about cigarette pricing and brand loyalty in sub-Saharan Africa. This study examines these issues in Zambia, analysing data from the International Tobacco Control (ITC) Zambia Survey. Data from Wave 1 of the ITC Zambia Survey (2012) were analysed for current smokers of factory-made (FM) cigarettes compared with those who smoked both FM and roll-your-own (RYO) cigarettes, using multivariate logistic regression models to identify the predictors of brand loyalty and reasons for brand choice. 75% of FM-only smokers and 64% of FM+RYO smokers reported having a regular brand. Compared with FM-only smokers, FM+RYO smokers were, on average, older (28% vs 20% ≥40 years), low income (64% vs 43%) and had lower education (76% vs 44% < secondary). Mean price across FM brands was ZMW0.50 (US$0.08) per stick. Smokers were significantly less likely to be brand loyal (>1 year) if they were aged 15-17 years (vs 40-54 years) and if they had moderate (vs low) income. Brand choice was predicted mostly by friends, taste and brand popularity. Price was more likely to be a reason for brand loyalty among FM+RYO smokers, among ≥55-year-old smokers and among those who reported being more addicted to cigarettes. These results in Zambia document the high levels of brand loyalty in a market where price variation is fairly small across cigarette brands. Future research is needed on longitudinal trends to evaluate the effect of tobacco control policies in Zambia. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Predictive models for subtypes of autism spectrum disorder based on single-nucleotide polymorphisms and magnetic resonance imaging.

PubMed

Jiao, Y; Chen, R; Ke, X; Cheng, L; Chu, K; Lu, Z; Herskovits, E H

2011-01-01

Autism spectrum disorder (ASD) is a neurodevelopmental disorder, of which Asperger syndrome and high-functioning autism are subtypes. Our goal is: 1) to determine whether a diagnostic model based on single-nucleotide polymorphisms (SNPs), brain regional thickness measurements, or brain regional volume measurements can distinguish Asperger syndrome from high-functioning autism; and 2) to compare the SNP, thickness, and volume-based diagnostic models. Our study included 18 children with ASD: 13 subjects with high-functioning autism and 5 subjects with Asperger syndrome. For each child, we obtained 25 SNPs for 8 ASD-related genes; we also computed regional cortical thicknesses and volumes for 66 brain structures, based on structural magnetic resonance (MR) examination. To generate diagnostic models, we employed five machine-learning techniques: decision stump, alternating decision trees, multi-class alternating decision trees, logistic model trees, and support vector machines. For SNP-based classification, three decision-tree-based models performed better than the other two machine-learning models. The performance metrics for three decision-tree-based models were similar: decision stump was modestly better than the other two methods, with accuracy = 90%, sensitivity = 0.95 and specificity = 0.75. All thickness and volume-based diagnostic models performed poorly. The SNP-based diagnostic models were superior to those based on thickness and volume. For SNP-based classification, rs878960 in GABRB3 (gamma-aminobutyric acid A receptor, beta 3) was selected by all tree-based models. Our analysis demonstrated that SNP-based classification was more accurate than morphometry-based classification in ASD subtype classification. Also, we found that one SNP--rs878960 in GABRB3--distinguishes Asperger syndrome from high-functioning autism.

The application of a decision tree to establish the parameters associated with hypertension.

PubMed

Tayefi, Maryam; Esmaeili, Habibollah; Saberi Karimian, Maryam; Amirabadi Zadeh, Alireza; Ebrahimi, Mahmoud; Safarian, Mohammad; Nematy, Mohsen; Parizadeh, Seyed Mohammad Reza; Ferns, Gordon A; Ghayour-Mobarhan, Majid

2017-02-01

Hypertension is an important risk factor for cardiovascular disease (CVD). The goal of this study was to establish the factors associated with hypertension by using a decision-tree algorithm as a supervised classification method of data mining. Data from a cross-sectional study were used in this study. A total of 9078 subjects who met the inclusion criteria were recruited. 70% of these subjects (6358 cases) were randomly allocated to the training dataset for the constructing of the decision-tree. The remaining 30% (2720 cases) were used as the testing dataset to evaluate the performance of decision-tree. Two models were evaluated in this study. In model I, age, gender, body mass index, marital status, level of education, occupation status, depression and anxiety status, physical activity level, smoking status, LDL, TG, TC, FBG, uric acid and hs-CRP were considered as input variables and in model II, age, gender, WBC, RBC, HGB, HCT MCV, MCH, PLT, RDW and PDW were considered as input variables. The validation of the model was assessed by constructing a receiver operating characteristic (ROC) curve. The prevalence rates of hypertension were 32% in our population. For the decision-tree model I, the accuracy, sensitivity, specificity and area under the ROC curve (AUC) value for identifying the related risk factors of hypertension were 73%, 63%, 77% and 0.72, respectively. The corresponding values for model II were 70%, 61%, 74% and 0.68, respectively. We have developed a decision tree model to identify the risk factors associated with hypertension that maybe used to develop programs for hypertension management. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Identifying the performance characteristics of a winning outcome in elite mixed martial arts competition.

PubMed

James, Lachlan P; Robertson, Sam; Haff, G Gregory; Beckman, Emma M; Kelly, Vincent G

2017-03-01

To determine those performance indicators that have the greatest influence on classifying outcome at the elite level of mixed martial arts (MMA). A secondary objective was to establish the efficacy of decision tree analysis in explaining the characteristics of victory when compared to alternate statistical methods. Cross-sectional observational. Eleven raw performance indicators from male Ultimate Fighting Championship bouts (n=234) from July 2014 to December 2014 were screened for analysis. Each raw performance indicator was also converted to a rate-dependent measure to be scaled to fight duration. Further, three additional performance indicators were calculated from the dataset and included in the analysis. Cohen's d effect sizes were employed to determine the magnitude of the differences between Wins and Losses, while decision tree (chi-square automatic interaction detector (CHAID)) and discriminant function analyses (DFA) were used to classify outcome (Win and Loss). Effect size comparisons revealed differences between Wins and Losses across a number of performance indicators. Decision tree (raw: 71.8%; rate-scaled: 76.3%) and DFA (raw: 71.4%; rate-scaled 71.2%) achieved similar classification accuracies. Grappling and accuracy performance indicators were the most influential in explaining outcome. The decision tree models also revealed multiple combinations of performance indicators leading to victory. The decision tree analyses suggest that grappling activity and technique accuracy are of particular importance in achieving victory in elite-level MMA competition. The DFA results supported the importance of these performance indicators. Decision tree induction represents an intuitive and slightly more accurate approach to explaining bout outcome in this sport when compared to DFA. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Decision tree analysis in subarachnoid hemorrhage: prediction of outcome parameters during the course of aneurysmal subarachnoid hemorrhage using decision tree analysis.

PubMed

Hostettler, Isabel Charlotte; Muroi, Carl; Richter, Johannes Konstantin; Schmid, Josef; Neidert, Marian Christoph; Seule, Martin; Boss, Oliver; Pangalu, Athina; Germans, Menno Robbert; Keller, Emanuela

2018-01-19

OBJECTIVE The aim of this study was to create prediction models for outcome parameters by decision tree analysis based on clinical and laboratory data in patients with aneurysmal subarachnoid hemorrhage (aSAH). METHODS The database consisted of clinical and laboratory parameters of 548 patients with aSAH who were admitted to the Neurocritical Care Unit, University Hospital Zurich. To examine the model performance, the cohort was randomly divided into a derivation cohort (60% [n = 329]; training data set) and a validation cohort (40% [n = 219]; test data set). The classification and regression tree prediction algorithm was applied to predict death, functional outcome, and ventriculoperitoneal (VP) shunt dependency. Chi-square automatic interaction detection was applied to predict delayed cerebral infarction on days 1, 3, and 7. RESULTS The overall mortality was 18.4%. The accuracy of the decision tree models was good for survival on day 1 and favorable functional outcome at all time points, with a difference between the training and test data sets of < 5%. Prediction accuracy for survival on day 1 was 75.2%. The most important differentiating factor was the interleukin-6 (IL-6) level on day 1. Favorable functional outcome, defined as Glasgow Outcome Scale scores of 4 and 5, was observed in 68.6% of patients. Favorable functional outcome at all time points had a prediction accuracy of 71.1% in the training data set, with procalcitonin on day 1 being the most important differentiating factor at all time points. A total of 148 patients (27%) developed VP shunt dependency. The most important differentiating factor was hyperglycemia on admission. CONCLUSIONS The multiple variable analysis capability of decision trees enables exploration of dependent variables in the context of multiple changing influences over the course of an illness. The decision tree currently generated increases awareness of the early systemic stress response, which is seemingly pertinent for prognostication.

Faults Discovery By Using Mined Data

NASA Technical Reports Server (NTRS)

Lee, Charles

2005-01-01

Fault discovery in the complex systems consist of model based reasoning, fault tree analysis, rule based inference methods, and other approaches. Model based reasoning builds models for the systems either by mathematic formulations or by experiment model. Fault Tree Analysis shows the possible causes of a system malfunction by enumerating the suspect components and their respective failure modes that may have induced the problem. The rule based inference build the model based on the expert knowledge. Those models and methods have one thing in common; they have presumed some prior-conditions. Complex systems often use fault trees to analyze the faults. Fault diagnosis, when error occurs, is performed by engineers and analysts performing extensive examination of all data gathered during the mission. International Space Station (ISS) control center operates on the data feedback from the system and decisions are made based on threshold values by using fault trees. Since those decision-making tasks are safety critical and must be done promptly, the engineers who manually analyze the data are facing time challenge. To automate this process, this paper present an approach that uses decision trees to discover fault from data in real-time and capture the contents of fault trees as the initial state of the trees.

Evaluation with Decision Trees of Efficacy and Safety of Semirigid Ureteroscopy in the Treatment of Proximal Ureteral Calculi.

PubMed

Sancak, Eyup Burak; Kılınç, Muhammet Fatih; Yücebaş, Sait Can

2017-01-01

The decision on the choice of proximal ureteral stone therapy depends on many factors, and sometimes urologists have difficulty in choosing the treatment option. This study is aimed at evaluating the factors affecting the success of semirigid ureterorenoscopy (URS) using the "decision tree" method. From January 2005 to November 2015, the data of consecutive patients treated for proximal ureteral stone were retrospectively analyzed. A total of 920 patients with proximal ureteral stone treated with semirigid URS were included in the study. All statistically significant attributes were tested using the decision tree method. The model created using decision tree had a sensitivity of 0.993 and an accuracy of 0.857. While URS treatment was successful in 752 patients (81.7%), it was unsuccessful in 168 patients (18.3%). According to the decision tree method, the most important factor affecting the success of URS is whether the stone is impacted to the ureteral wall. The second most important factor affecting treatment was intramural stricture requiring dilatation if the stone is impacted, and the size of the stone if not impacted. Our study suggests that the impacted stone, intramural stricture requiring dilatation and stone size may have a significant effect on the success rate of semirigid URS for proximal ureteral stone. Further studies with population-based and longitudinal design should be conducted to confirm this finding. © 2017 S. Karger AG, Basel.

Addressing HIV in Zambia through traditional games.

PubMed

Njelesani, Janet; Njelesani, Donald

2018-05-18

There has been a proliferation of organizations in Zambia touting the mobilization of traditional games as a tool to prevent HIV. However, there is a dearth of evidence on how culturally important activities like traditional games are being incorporated into programing. The purpose of this study was to explore how traditional games are used as a strategy to prevent HIV in Zambia. This qualitative study generated data from 17 case studies of HIV programs operating in Lusaka, Zambia. Observations of the programs were conducted and 44 interviews with program staff were completed. Participants believed that traditional games can engage youth while helping them learn about HIV. However, when traditional games were implemented, they were oversimplified and taught via regimented practices that did not foster critical thinking. This kind of implementation comes at the expense of the development of skills needed to retain and act on information essential for HIV prevention. The results of the study also reveal that due to the increase in cultural pride that has welcomed the revival of traditional games, there are opportunities to encourage government and political support for their systematic integration to address HIV in Zambia.

C-fuzzy variable-branch decision tree with storage and classification error rate constraints

NASA Astrophysics Data System (ADS)

Yang, Shiueng-Bien

2009-10-01

The C-fuzzy decision tree (CFDT), which is based on the fuzzy C-means algorithm, has recently been proposed. The CFDT is grown by selecting the nodes to be split according to its classification error rate. However, the CFDT design does not consider the classification time taken to classify the input vector. Thus, the CFDT can be improved. We propose a new C-fuzzy variable-branch decision tree (CFVBDT) with storage and classification error rate constraints. The design of the CFVBDT consists of two phases-growing and pruning. The CFVBDT is grown by selecting the nodes to be split according to the classification error rate and the classification time in the decision tree. Additionally, the pruning method selects the nodes to prune based on the storage requirement and the classification time of the CFVBDT. Furthermore, the number of branches of each internal node is variable in the CFVBDT. Experimental results indicate that the proposed CFVBDT outperforms the CFDT and other methods.

A Modified Decision Tree Algorithm Based on Genetic Algorithm for Mobile User Classification Problem

PubMed Central

Liu, Dong-sheng; Fan, Shu-jiang

2014-01-01

In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity. PMID:24688389

Planning effectiveness may grow on fault trees.

PubMed

Chow, C W; Haddad, K; Mannino, B

1991-10-01

The first step of a strategic planning process--identifying and analyzing threats and opportunities--requires subjective judgments. By using an analytical tool known as a fault tree, healthcare administrators can reduce the unreliability of subjective decision making by creating a logical structure for problem solving and decision making. A case study of 11 healthcare administrators showed that an analysis technique called prospective hindsight can add to a fault tree's ability to improve a strategic planning process.

Mapping Disparities in Access to Safe, Timely, and Essential Surgical Care in Zambia.

PubMed

Esquivel, Micaela M; Uribe-Leitz, Tarsicio; Makasa, Emmanuel; Lishimpi, Kennedy; Mwaba, Peter; Bowman, Kendra; Weiser, Thomas G

2016-11-01

Surgical care is widely unavailable in developing countries; advocates recommend that countries evaluate and report on access to surgical care to improve availability and aid health planners in decision making. To analyze the infrastructure, capacity, and availability of surgical care in Zambia to inform health policy priorities. In this observational study, all hospitals providing surgical care were identified in cooperation with the Zambian Ministry of Health. On-site data collection was conducted from February 1 through August 30, 2011, with an adapted World Health Organization Global Initiative for Emergency and Essential Surgical Care survey. Data collection at each facility included interviews with hospital personnel and assessment of material resources. Data were geocoded and analyzed in a data visualization platform from March 1 to December 1, 2015. We analyzed time and distance to surgical services, as well as the proportion of the population living within 2 hours from a facility providing surgical care. Surgical capacity, supplies, human resources, and infrastructure at each surgical facility, as well as the population living within 2 hours from a hospital providing surgical care. Data were collected from all 103 surgical facilities identified as providing surgical care. When including all surgical facilities (regardless of human resources and supplies), 14.9% of the population (2 166 460 of 14 500 000 people) lived more than 2 hours from surgical care. However, only 17 hospitals (16.5%) met the World Health Organization minimum standards of surgical safety; when limiting the analysis to these hospitals, 65.9% of the population (9 552 780 people) lived in an area that was more than 2 hours from a surgical facility. Geographic analysis of emergency and essential surgical care, defined as access to trauma care, obstetric care, and care of common abdominal emergencies, found that 80.7% of the population (11 704 700 people) lived in an area that was more than 2 hours from these surgical facilities. A large proportion of the population in Zambia does not have access to safe and timely surgical care; this percentage would change substantially if all surgical hospitals were adequately resourced. Geospatial visualization tools assist in the evaluation of surgical infrastructure in Zambia and can identify key areas for improvement.

Task sharing in Zambia: HIV service scale-up compounds the human resource crisis.

PubMed

Walsh, Aisling; Ndubani, Phillimon; Simbaya, Joseph; Dicker, Patrick; Brugha, Ruairí

2010-09-17

Considerable attention has been given by policy makers and researchers to the human resources for health crisis in Africa. However, little attention has been paid to quantifying health facility-level trends in health worker numbers, distribution and workload, despite growing demands on health workers due to the availability of new funds for HIV/AIDS control scale-up. This study analyses and reports trends in HIV and non-HIV ambulatory service workloads on clinical staff in urban and rural district level facilities. Structured surveys of health facility managers, and health services covering 2005-07 were conducted in three districts of Zambia in 2008 (two urban and one rural), to fill this evidence gap. Intra-facility analyses were conducted, comparing trends in HIV and non-HIV service utilisation with staff trends. Clinical staff (doctors, nurses and nurse-midwives, and clinical officers) numbers and staff population densities fell slightly, with lower ratios of staff to population in the rural district. The ratios of antenatal care and family planning registrants to nurses/nurse-midwives were highest at baseline and increased further at the rural facilities over the three years, while daily outpatient department (OPD) workload in urban facilities fell below that in rural facilities. HIV workload, as measured by numbers of clients receiving antiretroviral treatment (ART) and prevention of mother to child transmission (PMTCT) per facility staff member, was highest in the capital city, but increased rapidly in all three districts. The analysis suggests evidence of task sharing, in that staff designated by managers as ART and PMTCT workers made up a higher proportion of frontline service providers by 2007. This analysis of workforce patterns across 30 facilities in three districts of Zambia illustrates that the remarkable achievements in scaling-up HIV/AIDS service delivery has been on the back of sustained non-HIV workload levels, increasing HIV workload and stagnant health worker numbers. The findings are based on an analysis of routine data that are available to district and national managers. Mixed methods research is needed, combining quantitative analyses of routine health information with follow-up qualitative interviews, to explore and explain workload changes, and to identify and measure where problems are most acute, so that decision makers can respond appropriately. This study provides quantitative evidence of a human resource crisis in health facilities in Zambia, which may be more acute in rural areas.

Prescriptive models to support decision making in genetics.

PubMed

Pauker, S G; Pauker, S P

1987-01-01

Formal prescriptive models can help patients and clinicians better understand the risks and uncertainties they face and better formulate well-reasoned decisions. Using Bayes rule, the clinician can interpret pedigrees, historical data, physical findings and laboratory data, providing individualized probabilities of various diagnoses and outcomes of pregnancy. With the advent of screening programs for genetic disease, it becomes increasingly important to consider the prior probabilities of disease when interpreting an abnormal screening test result. Decision trees provide a convenient formalism for structuring diagnostic, therapeutic and reproductive decisions; such trees can also enhance communication between clinicians and patients. Utility theory provides a mechanism for patients to understand the choices they face and to communicate their attitudes about potential reproductive outcomes in a manner which encourages the integration of those attitudes into appropriate decisions. Using a decision tree, the relevant probabilities and the patients' utilities, physicians can estimate the relative worth of various medical and reproductive options by calculating the expected utility of each. By performing relevant sensitivity analyses, clinicians and patients can understand the impact of various soft data, including the patients' attitudes toward various health outcomes, on the decision making process. Formal clinical decision analytic models can provide deeper understanding and improved decision making in clinical genetics.

Applications of urban tree canopy assessment and prioritization tools: supporting collaborative decision making to achieve urban sustainability goals

Treesearch

Dexter H. Locke; J. Morgan Grove; Michael Galvin; Jarlath P.M. ONeil-Dunne; Charles Murphy

2013-01-01

Urban Tree Canopy (UTC) Prioritizations can be both a set of geographic analysis tools and a planning process for collaborative decision-making. In this paper, we describe how UTC Prioritizations can be used as a planning process to provide decision support to multiple government agencies, civic groups and private businesses to aid in reaching a canopy target. Linkages...

Combining binary decision tree and geostatistical methods to estimate snow distribution in a mountain watershed

USGS Publications Warehouse

Balk, Benjamin; Elder, Kelly

2000-01-01

We model the spatial distribution of snow across a mountain basin using an approach that combines binary decision tree and geostatistical techniques. In April 1997 and 1998, intensive snow surveys were conducted in the 6.9‐km2 Loch Vale watershed (LVWS), Rocky Mountain National Park, Colorado. Binary decision trees were used to model the large‐scale variations in snow depth, while the small‐scale variations were modeled through kriging interpolation methods. Binary decision trees related depth to the physically based independent variables of net solar radiation, elevation, slope, and vegetation cover type. These decision tree models explained 54–65% of the observed variance in the depth measurements. The tree‐based modeled depths were then subtracted from the measured depths, and the resulting residuals were spatially distributed across LVWS through kriging techniques. The kriged estimates of the residuals were added to the tree‐based modeled depths to produce a combined depth model. The combined depth estimates explained 60–85% of the variance in the measured depths. Snow densities were mapped across LVWS using regression analysis. Snow‐covered area was determined from high‐resolution aerial photographs. Combining the modeled depths and densities with a snow cover map produced estimates of the spatial distribution of snow water equivalence (SWE). This modeling approach offers improvement over previous methods of estimating SWE distribution in mountain basins.

New Splitting Criteria for Decision Trees in Stationary Data Streams.

PubMed

Jaworski, Maciej; Duda, Piotr; Rutkowski, Leszek; Jaworski, Maciej; Duda, Piotr; Rutkowski, Leszek; Rutkowski, Leszek; Duda, Piotr; Jaworski, Maciej

2018-06-01

The most popular tools for stream data mining are based on decision trees. In previous 15 years, all designed methods, headed by the very fast decision tree algorithm, relayed on Hoeffding's inequality and hundreds of researchers followed this scheme. Recently, we have demonstrated that although the Hoeffding decision trees are an effective tool for dealing with stream data, they are a purely heuristic procedure; for example, classical decision trees such as ID3 or CART cannot be adopted to data stream mining using Hoeffding's inequality. Therefore, there is an urgent need to develop new algorithms, which are both mathematically justified and characterized by good performance. In this paper, we address this problem by developing a family of new splitting criteria for classification in stationary data streams and investigating their probabilistic properties. The new criteria, derived using appropriate statistical tools, are based on the misclassification error and the Gini index impurity measures. The general division of splitting criteria into two types is proposed. Attributes chosen based on type- splitting criteria guarantee, with high probability, the highest expected value of split measure. Type- criteria ensure that the chosen attribute is the same, with high probability, as it would be chosen based on the whole infinite data stream. Moreover, in this paper, two hybrid splitting criteria are proposed, which are the combinations of single criteria based on the misclassification error and Gini index.

Decision tree analysis to stratify risk of de novo non-melanoma skin cancer following liver transplantation.

PubMed

Tanaka, Tomohiro; Voigt, Michael D

2018-03-01

Non-melanoma skin cancer (NMSC) is the most common de novo malignancy in liver transplant (LT) recipients; it behaves more aggressively and it increases mortality. We used decision tree analysis to develop a tool to stratify and quantify risk of NMSC in LT recipients. We performed Cox regression analysis to identify which predictive variables to enter into the decision tree analysis. Data were from the Organ Procurement Transplant Network (OPTN) STAR files of September 2016 (n = 102984). NMSC developed in 4556 of the 105984 recipients, a mean of 5.6 years after transplant. The 5/10/20-year rates of NMSC were 2.9/6.3/13.5%, respectively. Cox regression identified male gender, Caucasian race, age, body mass index (BMI) at LT, and sirolimus use as key predictive or protective factors for NMSC. These factors were entered into a decision tree analysis. The final tree stratified non-Caucasians as low risk (0.8%), and Caucasian males > 47 years, BMI < 40 who did not receive sirolimus, as high risk (7.3% cumulative incidence of NMSC). The predictions in the derivation set were almost identical to those in the validation set (r 2  = 0.971, p < 0.0001). Cumulative incidence of NMSC in low, moderate and high risk groups at 5/10/20 year was 0.5/1.2/3.3, 2.1/4.8/11.7 and 5.6/11.6/23.1% (p < 0.0001). The decision tree model accurately stratifies the risk of developing NMSC in the long-term after LT.

Interpretation of diagnostic data: 6. How to do it with more complex maths.

PubMed

1983-11-15

We have now shown you how to use decision analysis in making those rare, tough diagnostic decisions that are not soluble through other, easier routes. In summary, to "use more complex maths" the following steps will be useful: Create a decision tree or map of all the pertinent courses of action and their consequences. Assign probabilities to the branches of each chance node. Assign utilities to each of the potential outcomes shown on the decision tree. Combine the probabilities and utilities for each node on the decision tree. Pick the decision that leads to the highest expected utility. Test your decision for its sensitivity to clinically sensible changes in probabilities and utilities. That concludes this series of clinical epidemiology rounds. You've come a long way from "doing it with pictures" and are now able to extract most of the diagnostic information that can be provided from signs, symptoms and laboratory investigations. We would appreciate learning whether you have found this series useful and how we can do a better job of presenting these and other elements of "the science of the art of medicine".

Policy Route Map for Academic Libraries' Digital Content

ERIC Educational Resources Information Center

Koulouris, Alexandros; Kapidakis, Sarantos

2012-01-01

This paper presents a policy decision tree for digital information management in academic libraries. The decision tree is a policy guide, which offers alternative access and reproduction policy solutions according to the prevailing circumstances (for example acquisition method, copyright ownership). It refers to the digital information life cycle,…

Decision-Tree, Rule-Based, and Random Forest Classification of High-Resolution Multispectral Imagery for Wetland Mapping and Inventory

EPA Science Inventory

Efforts are increasingly being made to classify the world’s wetland resources, an important ecosystem and habitat that is diminishing in abundance. There are multiple remote sensing classification methods, including a suite of nonparametric classifiers such as decision-tree...

Siting a municipal solid waste disposal facility, part II: the effects of external criteria on the final decision.

PubMed

Korucu, M Kemal; Karademir, Aykan

2014-02-01

The procedure of a multi-criteria decision analysis supported by the geographic information systems was applied to the site selection process of a planning municipal solid waste management practice based on twelve different scenarios. The scenarios included two different decision tree modes and two different weighting models for three different area requirements. The suitability rankings of the suitable sites obtained from the application of the decision procedure for the scenarios were assessed by a factorial experimental design concerning the effect of some external criteria on the final decision of the site selection process. The external criteria used in the factorial experimental design were defined as "Risk perception and approval of stakeholders" and "Visibility". The effects of the presence of these criteria in the decision trees were evaluated in detail. For a quantitative expression of the differentiations observed in the suitability rankings, the ranking data were subjected to ANOVA test after a normalization process. Then the results of these tests were evaluated by Tukey test to measure the effects of external criteria on the final decision. The results of Tukey tests indicated that the involvement of the external criteria into the decision trees produced statistically meaningful differentiations in the suitability rankings. Since the external criteria could cause considerable external costs during the operation of the disposal facilities, the presence of these criteria in the decision tree in addition to the other criteria related to environmental and legislative requisites could prevent subsequent external costs in the first place.

Health professional feedback on HPV vaccination roll-out in a developing country.

PubMed

Venturas, Collette; Umeh, Kanayo

2017-04-04

Worldwide, Zambia has the highest cervical cancer incidence rates (58.4/100,000 per year) and mortality rates (36.2/100,000 per year). The human papilloma virus (HPV) vaccine is considered a vital preventative measure against cervical cancer, particularly in sub-Saharan countries, such as Zambia. Past research suggests health professionals' experiences with HPV vaccination rollout can have practical implications for effective delivery. To explore health professionals' perspectives on the HPV vaccination programme in Zambia. Researcher travelled to Zambia and conducted semi-structured interviews with fifteen health professionals working in private, government, and missionary clinics/hospitals. Observation was conducted for triangulation purposes. Thematic analysis was used to analyse the data. Five main themes emerged; medical misconceptions about the HPV vaccination, particularly with regards to infertility; fear of the unknown, including possible side effects and inadequate empirical research; need for prior desensitisation to resolve cultural barriers prior to vaccination rollout; a rural-urban divide in health awareness, particularly in relation to cancer vaccines; and economic concerns associated with access to the HPV vaccination for most of the Zambian population. Overall, the findings indicate that an essential avenue for facilitating HPV vaccination rollout in Zambia is by implementing a pre-rollout community effort that removes or softens cultural barriers, particularly in rural areas. It is also essential to correct erroneous HPV presumptions health professionals may have around infertility. Affordability remains a seemingly intractable hindrance that hampers HPV vaccination rollout in Zambia. Copyright © 2017 Elsevier Ltd. All rights reserved.

Decision support for mitigating the risk of tree induced transmission line failure in utility rights-of-way.

PubMed

Poulos, H M; Camp, A E

2010-02-01

Vegetation management is a critical component of rights-of-way (ROW) maintenance for preventing electrical outages and safety hazards resulting from tree contact with conductors during storms. Northeast Utility's (NU) transmission lines are a critical element of the nation's power grid; NU is therefore under scrutiny from federal agencies charged with protecting the electrical transmission infrastructure of the United States. We developed a decision support system to focus right-of-way maintenance and minimize the potential for a tree fall episode that disables transmission capacity across the state of Connecticut. We used field data on tree characteristics to develop a system for identifying hazard trees (HTs) in the field using limited equipment to manage Connecticut power line ROW. Results from this study indicated that the tree height-to-diameter ratio, total tree height, and live crown ratio were the key characteristics that differentiated potential risk trees (danger trees) from trees with a high probability of tree fall (HTs). Products from this research can be transferred to adaptive right-of-way management, and the methods we used have great potential for future application to other regions of the United States and elsewhere where tree failure can disrupt electrical power.

Priorities for Antiretroviral Therapy Research in Sub-Saharan Africa: A 2002 Consensus Conference in Zambia

PubMed Central

Zulu, Isaac; Schuman, Paula; Musonda, Rosemary; Chomba, Elwyn; Mwinga, Kasonde; Sinkala, Moses; Chisembele, Maureen; Mwaba, Peter; Kasonde, Dorothy; Vermund, Sten H.

2009-01-01

Background A consensus conference was held to discuss priorities for antiretroviral therapy (ART) research in Zambia, one of the world’s most heavily HIV-afflicted nations. Zambia, like other resource-limited settings, has increasing access to highly active antiretroviral therapy (HAART) because of declining drug costs, use of government-purchased generic medications, and increased global donations. For sustained delivery of care with HAART in a resource-constrained medical and public health context, operational research is required and clinical trials are desirable. The priority areas for research are most relevant today given the increasing availability of HAART. Methods A conference was held in Lusaka, Zambia, in January 2002 to discuss priority areas for ART research in Zambia, with participants drawn from a broad cross section of Zambian society. State-of-the-art reviews and 6 intensive small group discussions helped to formulate a suggested research agenda. Results Conference participants believed that the most urgent research priorities were to assess how therapeutic resources could be applied for the greatest overall benefit and to minimize the impact of nonadherence and viral resistance. Identified research priorities were as follows: To determine when to initiate HAART in relation to CD4+ cell count To assess whether HIV/AIDS can be managed well without the use of costly frequent viral load measurements and CD4+ cell count monitoring To assess whether HIV/AIDS can be managed in the same fashion in patients coinfected with opportunistic infections such as tuberculosis and HIV-related chronic diarrhea, taking into consideration complications that may occur in tuberculosis such as immune reconstitution syndrome and medication malabsorption in the presence of diarrhea To carefully assess and characterize toxicities, adverse effects, and viral resistance patterns in Zambia, including studies of mothers exposed to prepartum single-dose nevirapine To conduct operational research to assess clinical and field-based strategies to maximize adherence for better outcomes of ART in Zambia To assess ART approaches most valuable for pediatric and adolescent patients in Zambia Conference participants recommended that HIV-related clinical care and research be integrated within home-based care services and operated within the existing health delivery structures to ensure sustainability, reduce costs, and strengthen the structures. Conclusion Our consensus was that antiretroviral clinical trials and operational research are essential for Zambia to address the new challenges arising from increasing ART availability. There is global consensus that antiretroviral clinical trials in resource-constrained countries are possible, and the capacity for such trials should be developed further in Africa. PMID:15213567

Decision tree modeling using R.

PubMed

Zhang, Zhongheng

2016-08-01

In machine learning field, decision tree learner is powerful and easy to interpret. It employs recursive binary partitioning algorithm that splits the sample in partitioning variable with the strongest association with the response variable. The process continues until some stopping criteria are met. In the example I focus on conditional inference tree, which incorporates tree-structured regression models into conditional inference procedures. While growing a single tree is subject to small changes in the training data, random forests procedure is introduced to address this problem. The sources of diversity for random forests come from the random sampling and restricted set of input variables to be selected. Finally, I introduce R functions to perform model based recursive partitioning. This method incorporates recursive partitioning into conventional parametric model building.

A Qualitative Study of Migrant-related Stressors, Psychosocial Outcomes and HIV Risk Behavior among Truck Drivers in Zambia

PubMed Central

Ncube, Nomagugu; Simona, Simona J.; Kansankala, Brian; Sinkala, Emmanuel; Raidoo, Jasmin

2017-01-01

Truck drivers are part of mobile populations which have been noted as a key population at risk of HIV in Zambia. This study was aimed at 1) determining Potentially Traumatic Events (PTEs), labor migrant-related stressors, psychosocial problems and HIV risk behaviors among truck drivers in Zambia and 2) examining the relationship between PTEs, migrant-related stressors, psychosocial outcomes and HIV sexual risk behavior among truck drivers in Zambia. We conducted fifteen semi-structured interviews with purposively sampled male truck drivers at trucking companies in Lusaka, Zambia. Findings indicate that truck drivers experience multiple stressors and potentially traumatic incidences, including delays and long waiting hours at borders, exposure to crime and violence, poverty, stress related to resisting temptation of sexual interactions with sex workers or migrant women, and job-related safety concerns. Multiple psychosocial problems such as intimate partner violence, loneliness, anxiety and depression-like symptoms were noted. Transactional sex, coupled with inconsistent condom use were identified as HIV sexual risk behaviors. Findings suggest the critical need to develop HIV prevention interventions which account for mobility, potentially traumatic events, psychosocial problems, and the extreme fear of HIV testing among this key population. PMID:27681145

Cost of abortions in Zambia: A comparison of safe abortion and post abortion care.

PubMed

Parmar, Divya; Leone, Tiziana; Coast, Ernestina; Murray, Susan Fairley; Hukin, Eleanor; Vwalika, Bellington

2017-02-01

Unsafe abortion is a significant but preventable cause of maternal mortality. Although induced abortion has been legal in Zambia since 1972, many women still face logistical, financial, social, and legal obstacles to access safe abortion services, and undergo unsafe abortion instead. This study provides the first estimates of costs of post abortion care (PAC) after an unsafe abortion and the cost of safe abortion in Zambia. In the absence of routinely collected data on abortions, we used multiple data sources: key informant interviews, medical records and hospital logbooks. We estimated the costs of providing safe abortion and PAC services at the University Teaching Hospital, Lusaka and then projected these costs to generate indicative cost estimates for Zambia. Due to unavailability of data on the actual number of safe abortions and PAC cases in Zambia, we used estimates from previous studies and from other similar countries, and checked the robustness of our estimates with sensitivity analyses. We found that PAC following an unsafe abortion can cost 2.5 times more than safe abortion care. The Zambian health system could save as much as US$0.4 million annually if those women currently treated for an unsafe abortion instead had a safe abortion.

Increased Economic Relations Between China and Zambia in the Last Decade: Implications on Zambia’s Existing Bilateral Relations with the United States

DTIC Science & Technology

2013-12-13

Pacific region, but also the world at large. China and the U.S. have agreed to a new model of relations, based on practical cooperation and...as a significant model to determine whether the increase in China and Zambia relations lead to a change in the nature of bilateral relations between...a model in countries with similar features and given the circumstances. The last decade has seen China step up its economic activities on the

Prediction of the compression ratio for municipal solid waste using decision tree.

PubMed

Heshmati R, Ali Akbar; Mokhtari, Maryam; Shakiba Rad, Saeed

2014-01-01

The compression ratio of municipal solid waste (MSW) is an essential parameter for evaluation of waste settlement and landfill design. However, no appropriate model has been proposed to estimate the waste compression ratio so far. In this study, a decision tree method was utilized to predict the waste compression ratio (C'c). The tree was constructed using Quinlan's M5 algorithm. A reliable database retrieved from the literature was used to develop a practical model that relates C'c to waste composition and properties, including dry density, dry weight water content, and percentage of biodegradable organic waste using the decision tree method. The performance of the developed model was examined in terms of different statistical criteria, including correlation coefficient, root mean squared error, mean absolute error and mean bias error, recommended by researchers. The obtained results demonstrate that the suggested model is able to evaluate the compression ratio of MSW effectively.

What Satisfies Students?: Mining Student-Opinion Data with Regression and Decision Tree Analysis

ERIC Educational Resources Information Center

Thomas, Emily H.; Galambos, Nora

2004-01-01

To investigate how students' characteristics and experiences affect satisfaction, this study uses regression and decision tree analysis with the CHAID algorithm to analyze student-opinion data. A data mining approach identifies the specific aspects of students' university experience that most influence three measures of general satisfaction. The…

Identification of pests and diseases of Dalbergia hainanensis based on EVI time series and classification of decision tree

NASA Astrophysics Data System (ADS)

Luo, Qiu; Xin, Wu; Qiming, Xiong

2017-06-01

In the process of vegetation remote sensing information extraction, the problem of phenological features and low performance of remote sensing analysis algorithm is not considered. To solve this problem, the method of remote sensing vegetation information based on EVI time-series and the classification of decision-tree of multi-source branch similarity is promoted. Firstly, to improve the time-series stability of recognition accuracy, the seasonal feature of vegetation is extracted based on the fitting span range of time-series. Secondly, the decision-tree similarity is distinguished by adaptive selection path or probability parameter of component prediction. As an index, it is to evaluate the degree of task association, decide whether to perform migration of multi-source decision tree, and ensure the speed of migration. Finally, the accuracy of classification and recognition of pests and diseases can reach 87%--98% of commercial forest in Dalbergia hainanensis, which is significantly better than that of MODIS coverage accuracy of 80%--96% in this area. Therefore, the validity of the proposed method can be verified.

East Coast fever and multiple El Niño Southern oscillation ranks.

PubMed

Fandamu, P; Duchateau, L; Speybroeck, N; Mulumba, M; Berkvens, D

2006-01-30

East Coast fever (ECF), a tick-borne disease of cattle, is a major constraint to livestock development in Africa in general and southern Zambia in particular. Understanding the transmission patterns of this disease complex is very difficult as shown by previous studies in southern and eastern Zambia due to the interplay of risk factors. In this long-term study, we investigated whether global weather changes had any influence on disease transmission in traditionally kept cattle in southern Zambia. The results from this study show a strong association between increased Theileria parva contacts in cattle and the presence of El Niño, clearly linking a simple climatic index to disease outbreaks. We therefore propose that in southern Zambia, the simple and readily available multiple El Niño Southern oscillation index (MEI) ranks be used in planning ECF control programmes and early warning.

Examining the Role of Couples' Characteristics in Contraceptive use in Nigeria and Zambia.

PubMed

Ntoimo, Lorretta Favour C; Chirwa-Banda, Pamela

2017-12-01

Relationship-related characteristics influence diverse health and demographic outcomes. This study examined the role of couples' characteristics in contraceptive use. Data were obtained from 2013 Nigeria and 2013-14 Zambia Demographic and Health Surveys. The study population consisted of couples in monogamous union (married or living together) who had at least one live birth and the wife was not pregnant at the time of the survey. Prevalence of contraceptive use among couples in Nigeria was 27% and 63% in Zambia. Couples' educational attainment, religious affiliation, the frequency of listening to the radio, reported number of children, fertility preference, region of residence and household wealth index were significant predictors of contraceptive use among couples in Nigeria and Zambia. Given the significant role of couples' characteristics in the uptake of contraceptives, there is the need to encourage interventions that target couples, particularly those of poor socioeconomic status.

A decision tree model for predicting mediastinal lymph node metastasis in non-small cell lung cancer with F-18 FDG PET/CT.

PubMed

Pak, Kyoungjune; Kim, Keunyoung; Kim, Mi-Hyun; Eom, Jung Seop; Lee, Min Ki; Cho, Jeong Su; Kim, Yun Seong; Kim, Bum Soo; Kim, Seong Jang; Kim, In Joo

2018-01-01

We aimed to develop a decision tree model to improve diagnostic performance of positron emission tomography/computed tomography (PET/CT) to detect metastatic lymph nodes (LN) in non-small cell lung cancer (NSCLC). 115 patients with NSCLC were included in this study. The training dataset included 66 patients. A decision tree model was developed with 9 variables, and validated with 49 patients: short and long diameters of LNs, ratio of short and long diameters, maximum standardized uptake value (SUVmax) of LN, mean hounsfield unit, ratio of LN SUVmax and ascending aorta SUVmax (LN/AA), and ratio of LN SUVmax and superior vena cava SUVmax. A total of 301 LNs of 115 patients were evaluated in this study. Nodular calcification was applied as the initial imaging parameter, and LN SUVmax (≥3.95) was assessed as the second. LN/AA (≥2.92) was required to high LN SUVmax. Sensitivity was 50% for training dataset, and 40% for validation dataset. However, specificity was 99.28% for training dataset, and 96.23% for validation dataset. In conclusion, we have developed a new decision tree model for interpreting mediastinal LNs. All LNs with nodular calcification were benign, and LNs with high LN SUVmax and high LN/AA were metastatic Further studies are needed to incorporate subjective parameters and pathologic evaluations into a decision tree model to improve the test performance of PET/CT.

Identifying Risk Factors for Drug Use in an Iranian Treatment Sample: A Prediction Approach Using Decision Trees.

PubMed

Amirabadizadeh, Alireza; Nezami, Hossein; Vaughn, Michael G; Nakhaee, Samaneh; Mehrpour, Omid

2018-05-12

Substance abuse exacts considerable social and health care burdens throughout the world. The aim of this study was to create a prediction model to better identify risk factors for drug use. A prospective cross-sectional study was conducted in South Khorasan Province, Iran. Of the total of 678 eligible subjects, 70% (n: 474) were randomly selected to provide a training set for constructing decision tree and multiple logistic regression (MLR) models. The remaining 30% (n: 204) were employed in a holdout sample to test the performance of the decision tree and MLR models. Predictive performance of different models was analyzed by the receiver operating characteristic (ROC) curve using the testing set. Independent variables were selected from demographic characteristics and history of drug use. For the decision tree model, the sensitivity and specificity for identifying people at risk for drug abuse were 66% and 75%, respectively, while the MLR model was somewhat less effective at 60% and 73%. Key independent variables in the analyses included first substance experience, age at first drug use, age, place of residence, history of cigarette use, and occupational and marital status. While study findings are exploratory and lack generalizability they do suggest that the decision tree model holds promise as an effective classification approach for identifying risk factors for drug use. Convergent with prior research in Western contexts is that age of drug use initiation was a critical factor predicting a substance use disorder.

Exploratory Use of Decision Tree Analysis in Classification of Outcome in Hypoxic-Ischemic Brain Injury.

PubMed

Phan, Thanh G; Chen, Jian; Singhal, Shaloo; Ma, Henry; Clissold, Benjamin B; Ly, John; Beare, Richard

2018-01-01

Prognostication following hypoxic ischemic encephalopathy (brain injury) is important for clinical management. The aim of this exploratory study is to use a decision tree model to find clinical and MRI associates of severe disability and death in this condition. We evaluate clinical model and then the added value of MRI data. The inclusion criteria were as follows: age ≥17 years, cardio-respiratory arrest, and coma on admission (2003-2011). Decision tree analysis was used to find clinical [Glasgow Coma Score (GCS), features about cardiac arrest, therapeutic hypothermia, age, and sex] and MRI (infarct volume) associates of severe disability and death. We used the area under the ROC (auROC) to determine accuracy of model. There were 41 (63.7% males) patients having MRI imaging with the average age 51.5 ± 18.9 years old. The decision trees showed that infarct volume and age were important factors for discrimination between mild to moderate disability and severe disability and death at day 0 and day 2. The auROC for this model was 0.94 (95% CI 0.82-1.00). At day 7, GCS value was the only predictor; the auROC was 0.96 (95% CI 0.86-1.00). Our findings provide proof of concept for further exploration of the role of MR imaging and decision tree analysis in the early prognostication of hypoxic ischemic brain injury.

Fish to meat intake ratio and cooking oils are associated with hepatitis C virus carriers with persistently normal alanine aminotransferase levels.

PubMed

Otsuka, Momoka; Uchida, Yuki; Kawaguchi, Takumi; Taniguchi, Eitaro; Kawaguchi, Atsushi; Kitani, Shingo; Itou, Minoru; Oriishi, Tetsuharu; Kakuma, Tatsuyuki; Tanaka, Suiko; Yagi, Minoru; Sata, Michio

2012-10-01

  Dietary habits are involved in the development of chronic inflammation; however, the impact of dietary profiles of hepatitis C virus carriers with persistently normal alanine transaminase levels (HCV-PNALT) remains unclear. The decision-tree algorithm is a data-mining statistical technique, which uncovers meaningful profiles of factors from a data collection. We aimed to investigate dietary profiles associated with HCV-PNALT using a decision-tree algorithm.   Twenty-seven HCV-PNALT and 41 patients with chronic hepatitis C were enrolled in this study. Dietary habit was assessed using a validated semiquantitative food frequency questionnaire. A decision-tree algorithm was created by dietary variables, and was evaluated by area under the receiver operating characteristic curve analysis (AUROC).   In multivariate analysis, fish to meat ratio, dairy product and cooking oils were identified as independent variables associated with HCV-PNALT. The decision-tree algorithm was created with two variables: a fish to meat ratio and cooking oils/ideal bodyweight. When subjects showed a fish to meat ratio of 1.24 or more, 68.8% of the subjects were HCV-PNALT. On the other hand, 11.5% of the subjects were HCV-PNALT when subjects showed a fish to meat ratio of less than 1.24 and cooking oil/ideal bodyweight of less than 0.23 g/kg. The difference in the proportion of HCV-PNALT between these groups are significant (odds ratio 16.87, 95% CI 3.40-83.67, P = 0.0005). Fivefold cross-validation of the decision-tree algorithm showed an AUROC of 0.6947 (95% CI 0.5656-0.8238, P = 0.0067).   The decision-tree algorithm disclosed that fish to meat ratio and cooking oil/ideal bodyweight were associated with HCV-PNALT. © 2012 The Japan Society of Hepatology.

Data Clustering and Evolving Fuzzy Decision Tree for Data Base Classification Problems

NASA Astrophysics Data System (ADS)

Chang, Pei-Chann; Fan, Chin-Yuan; Wang, Yen-Wen

Data base classification suffers from two well known difficulties, i.e., the high dimensionality and non-stationary variations within the large historic data. This paper presents a hybrid classification model by integrating a case based reasoning technique, a Fuzzy Decision Tree (FDT), and Genetic Algorithms (GA) to construct a decision-making system for data classification in various data base applications. The model is major based on the idea that the historic data base can be transformed into a smaller case-base together with a group of fuzzy decision rules. As a result, the model can be more accurately respond to the current data under classifying from the inductions by these smaller cases based fuzzy decision trees. Hit rate is applied as a performance measure and the effectiveness of our proposed model is demonstrated by experimentally compared with other approaches on different data base classification applications. The average hit rate of our proposed model is the highest among others.

Computerization of guidelines: a knowledge specification method to convert text to detailed decision tree for electronic implementation.

PubMed

Aguirre-Junco, Angel-Ricardo; Colombet, Isabelle; Zunino, Sylvain; Jaulent, Marie-Christine; Leneveut, Laurence; Chatellier, Gilles

2004-01-01

The initial step for the computerization of guidelines is the knowledge specification from the prose text of guidelines. We describe a method of knowledge specification based on a structured and systematic analysis of text allowing detailed specification of a decision tree. We use decision tables to validate the decision algorithm and decision trees to specify and represent this algorithm, along with elementary messages of recommendation. Edition tools are also necessary to facilitate the process of validation and workflow between expert physicians who will validate the specified knowledge and computer scientist who will encode the specified knowledge in a guide-line model. Applied to eleven different guidelines issued by an official agency, the method allows a quick and valid computerization and integration in a larger decision support system called EsPeR (Personalized Estimate of Risks). The quality of the text guidelines is however still to be developed further. The method used for computerization could help to define a framework usable at the initial step of guideline development in order to produce guidelines ready for electronic implementation.

Tobacco Use and Secondhand Smoke Exposure During Pregnancy in Two African Countries: Zambia and the Democratic Republic of the Congo

PubMed Central

Chomba, Elwyn; Tshefu, Antoinette; Onyamboko, Marie; Kaseba - Sata, Christine; Moore, Janet; McClure, Elizabeth M; Moss, Nancy; Goco, Norman; Bloch, Michele; Goldenberg, Robert L

2013-01-01

Objective To study pregnant women’s knowledge, attitudes and behaviors towards tobacco use and secondhand smoke (SHS) exposure, and exposure to advertising for and against tobacco products in Zambia and the Democratic Republic of the Congo (DRC). Design Prospective cross-sectional survey between November 2004 and September 2005. Setting Antenatal care clinics in Lusaka, Zambia and Kinshasa, DRC. Population Pregnant women in Zambia (909) and the DRC (847). Methods Research staff administered a structured questionnaire to pregnant women attending antenatal care clinics. Main Outcome Measures Pregnant women’s use of tobacco, exposure to SHS, knowledge of the harms of tobacco, and exposure to advertising for and against tobacco products. Results Only about 10% of pregnant women reported having ever tried cigarettes (6.6% Zambia; 14.1% DRC). However, in the DRC, 41.8% of pregnant women had ever tried other forms of tobacco, primarily snuff. About 10% of pregnant women and young children were frequently or always exposed to SHS. Pregnant women’s knowledge of the hazards of smoking and SHS exposure was extremely limited. About 13% of pregnant women had seen or heard advertising for tobacco products in the last 30 days. Conclusions Tobacco use and SHS exposure pose serious threats to the health of women, infants, and children. In many African countries, maternal and infant health outcomes are often poor and will likely worsen if maternal tobacco use increases. Our findings suggest that a “window of opportunity” exists to prevent increased tobacco use and SHS exposure of pregnant women in Zambia and the DRC. PMID:20230310

Changes in sexual behaviour and practice and HIV prevalence indicators among young people aged 15–24 years in Zambia: An in-depth analysis of the 2001–2002 and 2007 Zambia Demographic and Health Surveys

PubMed Central

Kembo, Joshua

2014-01-01

HIV and AIDS still pose a major public health problem to most countries in sub-Saharan Africa, Zambia included. The objective of the paper is to determine changes in selected sexual behaviour and practice and HIV prevalence indicators between 2001–2002 and 2007. We used the Demographic and Health Survey Indicators Database for the computation of the selected indicators. We further used STATA 10.0 to compute significance tests to test for statistical difference in the indicators. The results indicate some changes in sexual behaviour, as indicated by an increase in abstinence, use of condoms and the decrease in multiple partnerships. The overall percentage of abstinence among never-married young men and women aged 15–24 years in Zambia increased significantly by 15.2% (p = .000) and 5.9% (p = .001) respectively, between 2001–2002 and 2007. A statistically significant increase of 6.6% (p = .029) was observed in the percentage of young women who reported having used a condom during the last time they had had premarital sex. A statistically significant decrease of 11.0% (p = .000) and 1.4% (p = .000) was observed among young men and women, respectively, who reported having multiple partners in the preceding 12 months. The factorial decomposition using multivariate analysis reveals that the indicators which contributed to the statistically significant 2.6% decline in HIV prevalence among young women aged 15–24 years in Zambia include proportion reporting condom use during premarital sex (+6.6%), abstinence (+5.9%), sex before age 15 (– 4.5%), premarital sex (– 2.6%), sex before age 18 (– 2.4%) and proportion reporting multiple partnerships (– 1.4%). Remarkable strides have been achieved towards promoting responsible sexual behaviour and practice among young people in Zambia. Further research focusing on factors that predispose young women in Zambia to higher risk of infection from HIV is required. The results from this paper should be useful in the design of programmes to control the spread of HIV and AIDS, particularly among young people in Zambia and other sub-Saharan countries. PMID:24702245

Zambia.

PubMed

1988-08-01

Attention in this discussion of Zambia is directed to the following: geography; the people; history; government; the economy; foreign relations; defense; and relations between Zambia and the US. In 1986, the population totaled 7 million with an annual growth rate of 3.7%. The infant mortality rate is 87/1000 with a life expectancy of 51 years. Zambia, located in south-central Africa, is bordered by Zaire, Tanzania, Malawi, Mozambique, Zimbabwe, Botswana, Angola, and Namibia. The population is made up of over 70 Bantu-speaking tribes. Expatriates, mostly British (15,000 in 1986) or South African, live primarily in Lusaka where they are employed in mines and related activities. Some ancestors of present-day Zambians most likely arrived about 2000 years ago and eventually displaced or absorbed indigenous stone age hunters and gatherers. The major waves of Bantu-speaking immigrants began in the 15th century; the greatest influx occurred in the late 17th to the early 19th centuries. After the mid-19th century, the area was penetrated by Western explorers. In 1888, Northern and Southern Rhodesia (now Zambia and Zimbabwe) were proclaimed a British sphere of influence. Southern Rhodesia was annexed formally and granted self-government in 1923. Independence was realized on October 24, 1964. Zambia was the 1st British territory to become a republic immediately upon realizing independence. The constitution promulgated on August 25, 1973, abrogated the original 1964 constitution, and this new constitution and the national elections that followed in December 1973 were the final steps in achieving what is termed a "1-party participatory democracy." President Kenneth Kaunda is the major figure in the country's politics. He has wide popular support and traditionally has bridged the rivalries among the country's various regions and ethnic groups. The economy of Zambia is based primarily on its majority state-owned copper industry, which is the only significant source of foreign exchange. Copper production has dropped to less than 500,000 metric tons/year from a high of 720,000 in 1976. Beginning in late 1982, Zambian government leaders took several important steps to deal with the country's economic plight, including restricting public spending, reducing government subsidies, raising farm producer incentives, and devaluing the currency. The US maintains a substantial foreign assistance program in Zambia.

Prices and mark-ups on antimalarials: evidence from nationally representative studies in six malaria-endemic countries

PubMed Central

Palafox, Benjamin; Patouillard, Edith; Tougher, Sarah; Goodman, Catherine; Hanson, Kara; Kleinschmidt, Immo; Torres Rueda, Sergio; Kiefer, Sabine; O’Connell, Kate; Zinsou, Cyprien; Phok, Sochea; Akulayi, Louis; Arogundade, Ekundayo; Buyungo, Peter; Mpasela, Felton; Poyer, Stephen; Chavasse, Desmond

2016-01-01

The private for-profit sector is an important source of treatment for malaria. However, private patients face high prices for the recommended treatment for uncomplicated malaria, artemisinin combination therapies (ACTs), which makes them more likely to receive cheaper, less effective non-artemisinin therapies (nATs). This study seeks to better understand consumer antimalarial prices by documenting and exploring the pricing behaviour of retailers and wholesalers. Using data collected in 2009–10, we present survey estimates of antimalarial retail prices, and wholesale- and retail-level price mark-ups from six countries (Benin, Cambodia, the Democratic Republic of Congo, Nigeria, Uganda and Zambia), along with qualitative findings on factors affecting pricing decisions. Retail prices were lowest for nATs, followed by ACTs and artemisinin monotherapies (AMTs). Retailers applied the highest percentage mark-ups on nATs (range: 40% in Nigeria to 100% in Cambodia and Zambia), whereas mark-ups on ACTs (range: 22% in Nigeria to 71% in Zambia) and AMTs (range: 22% in Nigeria to 50% in Uganda) were similar in magnitude, but lower than those applied to nATs. Wholesale mark-ups were generally lower than those at retail level, and were similar across antimalarial categories in most countries. When setting prices wholesalers and retailers commonly considered supplier prices, prevailing market prices, product availability, product characteristics and the costs related to transporting goods, staff salaries and maintaining a property. Price discounts were regularly used to encourage sales and were sometimes used by wholesalers to reward long-term customers. Pricing constraints existed only in Benin where wholesaler and retailer mark-ups are regulated; however, unlicensed drug vendors based in open-air markets did not adhere to the pricing regime. These findings indicate that mark-ups on antimalarials are reasonable. Therefore, improving ACT affordability would be most readily achieved by interventions that reduce commodity prices for retailers, such as ACT subsidies, pooled purchasing mechanisms and cost-effective strategies to increase the distribution coverage area of wholesalers. PMID:25944705

The Zambian wildlife ranching industry: scale, associated benefits, and limitations affecting its development.

PubMed

Lindsey, Peter A; Barnes, Jonathan; Nyirenda, Vincent; Pumfrett, Belinda; Tambling, Craig J; Taylor, W Andrew; t'Sas Rolfes, Michael

2013-01-01

The number and area of wildlife ranches in Zambia increased from 30 and 1,420 km(2) in 1997 to 177 and ∼6,000 km(2) by 2012. Wild ungulate populations on wildlife ranches increased from 21,000 individuals in 1997 to ∼91,000 in 2012, while those in state protected areas declined steeply. Wildlife ranching and crocodile farming have a turnover of ∼USD15.7 million per annum, compared to USD16 million from the public game management areas which encompass an area 29 times larger. The wildlife ranching industry employs 1,200 people (excluding jobs created in support industries), with a further ∼1,000 individuals employed through crocodile farming. Wildlife ranches generate significant quantities of meat (295,000 kg/annum), of which 30,000 kg of meat accrues to local communities and 36,000 kg to staff. Projected economic returns from wildlife ranching ventures are high, with an estimated 20-year economic rate of return of 28%, indicating a strong case for government support for the sector. There is enormous scope for wildlife ranching in Zambia due to the availability of land, high diversity of wildlife and low potential for commercial livestock production. However, the Zambian wildlife ranching industry is small and following completion of field work for this study, there was evidence of a significant proportion of ranchers dropping out. The industry is performing poorly, due to inter alia: rampant commercial bushmeat poaching; failure of government to allocate outright ownership of wildlife to landowners; bureaucratic hurdles; perceived historical lack of support from the Zambia Wildlife Authority and government; a lack of a clear policy on wildlife ranching; and a ban on hunting on unfenced lands including game ranches. For the wildlife ranching industry to develop, these limitations need to be addressed decisively. These findings are likely to apply to other savanna countries with large areas of marginal land potentially suited to wildlife ranching.

Benchmarking health system performance across districts in Zambia: a systematic analysis of levels and trends in key maternal and child health interventions from 1990 to 2010.

PubMed

Colson, Katherine Ellicott; Dwyer-Lindgren, Laura; Achoki, Tom; Fullman, Nancy; Schneider, Matthew; Mulenga, Peter; Hangoma, Peter; Ng, Marie; Masiye, Felix; Gakidou, Emmanuela

2015-04-02

Achieving universal health coverage and reducing health inequalities are primary goals for an increasing number of health systems worldwide. Timely and accurate measurements of levels and trends in key health indicators at local levels are crucial to assess progress and identify drivers of success and areas that may be lagging behind. We generated estimates of 17 key maternal and child health indicators for Zambia's 72 districts from 1990 to 2010 using surveys, censuses, and administrative data. We used a three-step statistical model involving spatial-temporal smoothing and Gaussian process regression. We generated estimates at the national level for each indicator by calculating the population-weighted mean of the district values and calculated composite coverage as the average of 10 priority interventions. National estimates masked substantial variation across districts in the levels and trends of all indicators. Overall, composite coverage increased from 46% in 1990 to 73% in 2010, and most of this gain was attributable to the scale-up of malaria control interventions, pentavalent immunization, and exclusive breastfeeding. The scale-up of these interventions was relatively equitable across districts. In contrast, progress in routine services, including polio immunization, antenatal care, and skilled birth attendance, stagnated or declined and exhibited large disparities across districts. The absolute difference in composite coverage between the highest-performing and lowest-performing districts declined from 37 to 26 percentage points between 1990 and 2010, although considerable variation in composite coverage across districts persisted. Zambia has made marked progress in delivering maternal and child health interventions between 1990 and 2010; nevertheless, substantial variations across districts and interventions remained. Subnational benchmarking is important to identify these disparities, allowing policymakers to prioritize areas of greatest need. Analyses such as this one should be conducted regularly and feed directly into policy decisions in order to increase accountability at the local, regional, and national levels.

Health Outcomes and Cost Impact of the New WHO 2013 Guidelines on Prevention of Mother-to-Child Transmission of HIV in Zambia

PubMed Central

Ishikawa, Naoko; Shimbo, Takuro; Miyano, Shinsuke; Sikazwe, Izukanji; Mwango, Albert; Ghidinelli, Massimo N.; Syakantu, Gardner

2014-01-01

Background Countries are currently progressing towards the elimination of new paediatric HIV infections by 2015. WHO published new consolidated guidelines in June 2013, which now recommend either ‘Antiretroviral drugs (ARVs) for women living with HIV during pregnancy and breastfeeding (Option B)’ or ‘Lifelong antiretroviral therapy (ART) for all pregnant and breastfeeding women living with HIV (Option B+)’, while de facto phasing out Option A. This study examined health outcomes and cost impact of the shift to WHO 2013 recommendations in Zambia. Methods A decision analytic model was developed based on the national health system perspective. Estimated risk and number of cases of HIV transmission to infants and to serodiscordant partners, and proportions of HIV-infected pregnant women with CD4 count of ≤350 cells/mm3 to initiate ART were compared between 2010 Option A and the 2013 recommendations. Total costs of prevention of mother-to-child transmission of HIV (PMTCT) services per annual cohort of pregnant women, incremental cost-effectiveness ratio (ICER) per infection averted and quality-adjusted life-year (QALY) gained were examined. Results Our analysis suggested that the shift from 2010 Option A to the 2013 guidelines would result in a 33% reduction of the risk of HIV transmission among exposed infants. The risk of transmission to serodiscordant partners for a period of 24 months would be reduced by 72% with ‘ARVs during pregnancy and breastfeeding’ and further reduced by 15% with ‘Lifelong ART’. The probability of HIV-infected pregnant women to initiate ART would increase by 80%. It was also suggested that while the shift would generate higher PMTCT costs, it would be cost-saving in the long term as it spares future treatment costs by preventing infections in infants and partners. Conclusion The shift to the WHO 2013 guidelines in Zambia would positively impact health of family and save future costs related to care and treatment. PMID:24604067

The Zambian Wildlife Ranching Industry: Scale, Associated Benefits, and Limitations Affecting Its Development

PubMed Central

Lindsey, Peter A.; Barnes, Jonathan; Nyirenda, Vincent; Pumfrett, Belinda; Tambling, Craig J.; Taylor, W. Andrew; Rolfes, Michael t’Sas

2013-01-01

The number and area of wildlife ranches in Zambia increased from 30 and 1,420 km2 in 1997 to 177 and ∼6,000 km2 by 2012. Wild ungulate populations on wildlife ranches increased from 21,000 individuals in 1997 to ∼91,000 in 2012, while those in state protected areas declined steeply. Wildlife ranching and crocodile farming have a turnover of ∼USD15.7 million per annum, compared to USD16 million from the public game management areas which encompass an area 29 times larger. The wildlife ranching industry employs 1,200 people (excluding jobs created in support industries), with a further ∼1,000 individuals employed through crocodile farming. Wildlife ranches generate significant quantities of meat (295,000 kg/annum), of which 30,000 kg of meat accrues to local communities and 36,000 kg to staff. Projected economic returns from wildlife ranching ventures are high, with an estimated 20-year economic rate of return of 28%, indicating a strong case for government support for the sector. There is enormous scope for wildlife ranching in Zambia due to the availability of land, high diversity of wildlife and low potential for commercial livestock production. However, the Zambian wildlife ranching industry is small and following completion of field work for this study, there was evidence of a significant proportion of ranchers dropping out. The industry is performing poorly, due to inter alia: rampant commercial bushmeat poaching; failure of government to allocate outright ownership of wildlife to landowners; bureaucratic hurdles; perceived historical lack of support from the Zambia Wildlife Authority and government; a lack of a clear policy on wildlife ranching; and a ban on hunting on unfenced lands including game ranches. For the wildlife ranching industry to develop, these limitations need to be addressed decisively. These findings are likely to apply to other savanna countries with large areas of marginal land potentially suited to wildlife ranching. PMID:24367493

Multi-Country Analysis of Treatment Costs for HIV/AIDS (MATCH): Facility-Level ART Unit Cost Analysis in Ethiopia, Malawi, Rwanda, South Africa and Zambia

PubMed Central

Tagar, Elya; Sundaram, Maaya; Condliffe, Kate; Matatiyo, Blackson; Chimbwandira, Frank; Chilima, Ben; Mwanamanga, Robert; Moyo, Crispin; Chitah, Bona Mukosha; Nyemazi, Jean Pierre; Assefa, Yibeltal; Pillay, Yogan; Mayer, Sam; Shear, Lauren; Dain, Mary; Hurley, Raphael; Kumar, Ritu; McCarthy, Thomas; Batra, Parul; Gwinnell, Dan; Diamond, Samantha; Over, Mead

2014-01-01

Background Today's uncertain HIV funding landscape threatens to slow progress towards treatment goals. Understanding the costs of antiretroviral therapy (ART) will be essential for governments to make informed policy decisions about the pace of scale-up under the 2013 WHO HIV Treatment Guidelines, which increase the number of people eligible for treatment from 17.6 million to 28.6 million. The study presented here is one of the largest of its kind and the first to describe the facility-level cost of ART in a random sample of facilities in Ethiopia, Malawi, Rwanda, South Africa and Zambia. Methods & Findings In 2010–2011, comprehensive data on one year of facility-level ART costs and patient outcomes were collected from 161 facilities, selected using stratified random sampling. Overall, facility-level ART costs were significantly lower than expected in four of the five countries, with a simple average of $208 per patient-year (ppy) across Ethiopia, Malawi, Rwanda and Zambia. Costs were higher in South Africa, at $682 ppy. This included medications, laboratory services, direct and indirect personnel, patient support, equipment and administrative services. Facilities demonstrated the ability to retain patients alive and on treatment at these costs, although outcomes for established patients (2–8% annual loss to follow-up or death) were better than outcomes for new patients in their first year of ART (77–95% alive and on treatment). Conclusions This study illustrated that the facility-level costs of ART are lower than previously understood in these five countries. While limitations must be considered, and costs will vary across countries, this suggests that expanded treatment coverage may be affordable. Further research is needed to understand investment costs of treatment scale-up, non-facility costs and opportunities for more efficient resource allocation. PMID:25389777

Validating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care.

PubMed

Verbakel, Jan Y; Lemiengre, Marieke B; De Burghgraeve, Tine; De Sutter, An; Aertgeerts, Bert; Bullens, Dominique M A; Shinkins, Bethany; Van den Bruel, Ann; Buntinx, Frank

2015-08-07

Acute infection is the most common presentation of children in primary care with only few having a serious infection (eg, sepsis, meningitis, pneumonia). To avoid complications or death, early recognition and adequate referral are essential. Clinical prediction rules have the potential to improve diagnostic decision-making for rare but serious conditions. In this study, we aimed to validate a recently developed decision tree in a new but similar population. Diagnostic accuracy study validating a clinical prediction rule. Acutely ill children presenting to ambulatory care in Flanders, Belgium, consisting of general practice and paediatric assessment in outpatient clinics or the emergency department. Physicians were asked to score the decision tree in every child. The outcome of interest was hospital admission for at least 24 h with a serious infection within 5 days after initial presentation. We report the diagnostic accuracy of the decision tree in sensitivity, specificity, likelihood ratios and predictive values. In total, 8962 acute illness episodes were included, of which 283 lead to admission to hospital with a serious infection. Sensitivity of the decision tree was 100% (95% CI 71.5% to 100%) at a specificity of 83.6% (95% CI 82.3% to 84.9%) in the general practitioner setting with 17% of children testing positive. In the paediatric outpatient and emergency department setting, sensitivities were below 92%, with specificities below 44.8%. In an independent validation cohort, this clinical prediction rule has shown to be extremely sensitive to identify children at risk of hospital admission for a serious infection in general practice, making it suitable for ruling out. NCT02024282. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Decay fungi of oaks and associated hardwoods for western arborists

Treesearch

Jessie A. Glaeser; Kevin T. Smith

2010-01-01

Examination of trees for the presence and extent of decay should be part of any hazard tree assessment. Identification of the fungi responsible for the decay improves prediction of tree performance and the quality of management decisions, including tree pruning or removal. Scouting for Sudden Oak Death (SOD) in the West has drawn attention to hardwood tree species,...

Climate change impacts on tree ranges: model intercomparison facilitates understanding and quantification of uncertainty.

PubMed

Cheaib, Alissar; Badeau, Vincent; Boe, Julien; Chuine, Isabelle; Delire, Christine; Dufrêne, Eric; François, Christophe; Gritti, Emmanuel S; Legay, Myriam; Pagé, Christian; Thuiller, Wilfried; Viovy, Nicolas; Leadley, Paul

2012-06-01

Model-based projections of shifts in tree species range due to climate change are becoming an important decision support tool for forest management. However, poorly evaluated sources of uncertainty require more scrutiny before relying heavily on models for decision-making. We evaluated uncertainty arising from differences in model formulations of tree response to climate change based on a rigorous intercomparison of projections of tree distributions in France. We compared eight models ranging from niche-based to process-based models. On average, models project large range contractions of temperate tree species in lowlands due to climate change. There was substantial disagreement between models for temperate broadleaf deciduous tree species, but differences in the capacity of models to account for rising CO(2) impacts explained much of the disagreement. There was good quantitative agreement among models concerning the range contractions for Scots pine. For the dominant Mediterranean tree species, Holm oak, all models foresee substantial range expansion. © 2012 Blackwell Publishing Ltd/CNRS.

A multivariate decision tree analysis of biophysical factors in tropical forest fire occurrence

Treesearch

Rey S. Ofren; Edward Harvey

2000-01-01

A multivariate decision tree model was used to quantify the relative importance of complex hierarchical relationships between biophysical variables and the occurrence of tropical forest fires. The study site is the Huai Kha Kbaeng wildlife sanctuary, a World Heritage Site in northwestern Thailand where annual fires are common and particularly destructive. Thematic...

Which Types of Leadership Styles Do Followers Prefer? A Decision Tree Approach

ERIC Educational Resources Information Center

Salehzadeh, Reza

2017-01-01

Purpose: The purpose of this paper is to propose a new method to find the appropriate leadership styles based on the followers' preferences using the decision tree technique. Design/methodology/approach: Statistical population includes the students of the University of Isfahan. In total, 750 questionnaires were distributed; out of which, 680…

The Americans with Disabilities Act: A Decision Tree for Social Services Administrators

ERIC Educational Resources Information Center

O'Brien, Gerald V.; Ellegood, Christina

2005-01-01

The 1990 Americans with Disabilities Act has had a profound influence on social workers and social services administrators in virtually all work settings. Because of the multiple elements of the act, however, assessing the validity of claims can be a somewhat arduous and complicated task. This article provides a "decision tree" for…

A Decision-Tree-Oriented Guidance Mechanism for Conducting Nature Science Observation Activities in a Context-Aware Ubiquitous Learning

ERIC Educational Resources Information Center

Hwang, Gwo-Jen; Chu, Hui-Chun; Shih, Ju-Ling; Huang, Shu-Hsien; Tsai, Chin-Chung

2010-01-01

A context-aware ubiquitous learning environment is an authentic learning environment with personalized digital supports. While showing the potential of applying such a learning environment, researchers have also indicated the challenges of providing adaptive and dynamic support to individual students. In this paper, a decision-tree-oriented…

A decision tree approach using silvics to guide planning for forest restoration

Treesearch

Sharon M. Hermann; John S. Kush; John C. Gilbert

2013-01-01

We created a decision tree based on silvics of longleaf pine (Pinus palustris) and historical descriptions to develop approaches for restoration management at Horseshoe Bend National Military Park located in central Alabama. A National Park Service goal is to promote structure and composition of a forest that likely surrounded the 1814 battlefield....

What Satisfies Students? Mining Student-Opinion Data with Regression and Decision-Tree Analysis. AIR 2002 Forum Paper.

ERIC Educational Resources Information Center

Thomas, Emily H.; Galambos, Nora

To investigate how students' characteristics and experiences affect satisfaction, this study used regression and decision-tree analysis with the CHAID algorithm to analyze student opinion data from a sample of 1,783 college students. A data-mining approach identifies the specific aspects of students' university experience that most influence three…

Foraging Behaviour in Magellanic Woodpeckers Is Consistent with a Multi-Scale Assessment of Tree Quality

PubMed Central

Vergara, Pablo M.; Soto, Gerardo E.; Rodewald, Amanda D.; Meneses, Luis O.; Pérez-Hernández, Christian G.

2016-01-01

Theoretical models predict that animals should make foraging decisions after assessing the quality of available habitat, but most models fail to consider the spatio-temporal scales at which animals perceive habitat availability. We tested three foraging strategies that explain how Magellanic woodpeckers (Campephilus magellanicus) assess the relative quality of trees: 1) Woodpeckers with local knowledge select trees based on the available trees in the immediate vicinity. 2) Woodpeckers lacking local knowledge select trees based on their availability at previously visited locations. 3) Woodpeckers using information from long-term memory select trees based on knowledge about trees available within the entire landscape. We observed foraging woodpeckers and used a Brownian Bridge Movement Model to identify trees available to woodpeckers along foraging routes. Woodpeckers selected trees with a later decay stage than available trees. Selection models indicated that preferences of Magellanic woodpeckers were based on clusters of trees near the most recently visited trees, thus suggesting that woodpeckers use visual cues from neighboring trees. In a second analysis, Cox’s proportional hazards models showed that woodpeckers used information consolidated across broader spatial scales to adjust tree residence times. Specifically, woodpeckers spent more time at trees with larger diameters and in a more advanced stage of decay than trees available along their routes. These results suggest that Magellanic woodpeckers make foraging decisions based on the relative quality of trees that they perceive and memorize information at different spatio-temporal scales. PMID:27416115

Foraging Behaviour in Magellanic Woodpeckers Is Consistent with a Multi-Scale Assessment of Tree Quality.

PubMed

Vergara, Pablo M; Soto, Gerardo E; Moreira-Arce, Darío; Rodewald, Amanda D; Meneses, Luis O; Pérez-Hernández, Christian G

2016-01-01

Theoretical models predict that animals should make foraging decisions after assessing the quality of available habitat, but most models fail to consider the spatio-temporal scales at which animals perceive habitat availability. We tested three foraging strategies that explain how Magellanic woodpeckers (Campephilus magellanicus) assess the relative quality of trees: 1) Woodpeckers with local knowledge select trees based on the available trees in the immediate vicinity. 2) Woodpeckers lacking local knowledge select trees based on their availability at previously visited locations. 3) Woodpeckers using information from long-term memory select trees based on knowledge about trees available within the entire landscape. We observed foraging woodpeckers and used a Brownian Bridge Movement Model to identify trees available to woodpeckers along foraging routes. Woodpeckers selected trees with a later decay stage than available trees. Selection models indicated that preferences of Magellanic woodpeckers were based on clusters of trees near the most recently visited trees, thus suggesting that woodpeckers use visual cues from neighboring trees. In a second analysis, Cox's proportional hazards models showed that woodpeckers used information consolidated across broader spatial scales to adjust tree residence times. Specifically, woodpeckers spent more time at trees with larger diameters and in a more advanced stage of decay than trees available along their routes. These results suggest that Magellanic woodpeckers make foraging decisions based on the relative quality of trees that they perceive and memorize information at different spatio-temporal scales.

A method of building of decision trees based on data from wearable device during a rehabilitation of patients with tibia fractures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kupriyanov, M. S., E-mail: mikhail.kupriyanov@gmail.com; Shukeilo, E. Y., E-mail: eyshukeylo@gmail.com; Shichkina, J. A., E-mail: strange.y@mail.ru

2015-11-17

Nowadays technologies which are used in traumatology are a combination of mechanical, electronic, calculating and programming tools. Relevance of development of mobile applications for an expeditious data processing which are received from medical devices (in particular, wearable devices), and formulation of management decisions increases. Using of a mathematical method of building of decision trees for an assessment of a patient’s health condition using data from a wearable device considers in this article.

A method of building of decision trees based on data from wearable device during a rehabilitation of patients with tibia fractures

NASA Astrophysics Data System (ADS)

Kupriyanov, M. S.; Shukeilo, E. Y.; Shichkina, J. A.

2015-11-01

Nowadays technologies which are used in traumatology are a combination of mechanical, electronic, calculating and programming tools. Relevance of development of mobile applications for an expeditious data processing which are received from medical devices (in particular, wearable devices), and formulation of management decisions increases. Using of a mathematical method of building of decision trees for an assessment of a patient's health condition using data from a wearable device considers in this article.

Protein attributes contribute to halo-stability, bioinformatics approach

PubMed Central

2011-01-01

Halophile proteins can tolerate high salt concentrations. Understanding halophilicity features is the first step toward engineering halostable crops. To this end, we examined protein features contributing to the halo-toleration of halophilic organisms. We compared more than 850 features for halophilic and non-halophilic proteins with various screening, clustering, decision tree, and generalized rule induction models to search for patterns that code for halo-toleration. Up to 251 protein attributes selected by various attribute weighting algorithms as important features contribute to halo-stability; from them 14 attributes selected by 90% of models and the count of hydrogen gained the highest value (1.0) in 70% of attribute weighting models, showing the importance of this attribute in feature selection modeling. The other attributes mostly were the frequencies of di-peptides. No changes were found in the numbers of groups when K-Means and TwoStep clustering modeling were performed on datasets with or without feature selection filtering. Although the depths of induced trees were not high, the accuracies of trees were higher than 94% and the frequency of hydrophobic residues pointed as the most important feature to build trees. The performance evaluation of decision tree models had the same values and the best correctness percentage recorded with the Exhaustive CHAID and CHAID models. We did not find any significant difference in the percent of correctness, performance evaluation, and mean correctness of various decision tree models with or without feature selection. For the first time, we analyzed the performance of different screening, clustering, and decision tree algorithms for discriminating halophilic and non-halophilic proteins and the results showed that amino acid composition can be used to discriminate between halo-tolerant and halo-sensitive proteins. PMID:21592393

A Rural Implementation of a 52 Node Mixed Wireless Mesh Network in Macha, Zambia

NASA Astrophysics Data System (ADS)

Backens, Jonathan; Mweemba, Gregory; van Stam, Gertjan

In spite of increasing international and academic attention, there remains many challenges facing real world implementations of developing technologies. There has been considerable hype behind Wireless Mesh Networking as the ubiquitous solution for rural ICT in the developing world. In this paper, we present the real world rural mesh network implementation in the village of Macha, Zambia and draw both performance conclusions as well as overall experiential conclusions. The purpose of this paper is to introduce and analyze our low cost solution and extrapolate future trends for rural ICT implementations in Zambia.

Observation of the total solar eclipse on 21 June 2001 in Zambia

NASA Astrophysics Data System (ADS)

Takahashi, Noritsugu; Yumoto, Kiyohumi; Ichimoto, Kiyoshi

2002-04-01

On 21 June 2001, path of totality in Angola, Zambia, Zimbabwe, Mozambique, and Madagascar in Africa. The Japan Scientific Observation Team, consisting primarily of the members of the Solar Eclipse Subcommittee of the Committee for International Collaboration in Astronomy of the Science Council of JAPAN, visited Lusaka in Zambia to observe the total solar eclipse. Blessed with fine weather, the observation was successful. The outline of the influence of solar eclipse on the terrestrial magnetism, polarization of the flash spectrum, and other observation data, as well as the way educational activities were carried out, are reported.

Adherence to Point-of-Use Water Treatment over Short-Term Implementation: Parallel Crossover Trials of Flocculation-Disinfection Sachets in Pakistan and Zambia.

PubMed

Shaheed, A; Rathore, S; Bastable, A; Bruce, J; Cairncross, S; Brown, J

2018-06-05

The health benefits of point-of-use (POU) water treatment can only be realized through high adherence: correct, consistent, and sustained use. We conducted parallel randomized, longitudinal crossover trials measuring short-term adherence to two single-use flocculant-disinfectant sachets in Pakistan and Zambia. In both trials, adherence declined sharply for both products over the eight week surveillance periods, with overall lower adherence to both products in Zambia. There was no significant difference in adherence between the two products. Estimated median daily production of treated water dropped over the crossover period from 2.5 to 1.4 L person -1 day -1 (46% decline) in Pakistan and from 1.4 to 1.1 L person -1 day -1 (21% decline) in Zambia. The percentage of surveillance points with detectable total chlorine in household drinking water declined from 70% to 49% in Pakistan and rose marginally from 28% to 30% in Zambia. The relatively low and decreasing adherence observed in this study suggests that these products would have provided little protection from waterborne disease risk in these settings. Our findings underscore the challenge of achieving high adherence to POU water treatment, even under conditions of short-term adoption with intensive follow-up.

Socio-cultural factors surrounding mental distress during the perinatal period in Zambia: a qualitative investigation

PubMed Central

2012-01-01

Background The presence of mental distress during pregnancy and after childbirth imposes detrimental developmental and health consequences for families in all nations. In Zambia, the Ministry of Health (MoH) has proposed a more comprehensive approach towards mental health care, recognizing the importance of the mental health of women during the perinatal period. Aim The study explores factors contributing to mental distress during the perinatal period of motherhood in Zambia. Methods A qualitative study was conducted in Lusaka, Zambia with nineteen focus groups comprising 149 women and men from primary health facilities and schools respectively. Findings There are high levels of mental distress in four domains: worry about HIV status and testing; uncertainty about survival from childbirth; lack of social support; and vulnerability/oppression. Conclusion Identifying mental distress and prompt referral for interventions is critical to improving the mental health of the mother and prevent the effects of mental distress on the baby. Recommendation Strategies should be put in place to ensure pregnant women are screened for possible perinatal mental health problems during their visit to antenatal clinic and referral made to qualified mental health professionals. In addition further research is recommended in order to facilitate evidence based mental health policy formulation and implementation in Zambia. PMID:22954173

Theileriosis in Zambia: etiology, epidemiology and control measures.

PubMed

Nambota, A; Samui, K; Sugimoto, C; Kakuta, T; Onuma, M

1994-06-01

In Zambia, theileriosis manifests itself in the form of Corridor disease (CD), caused by Theileria parva lawrencei, and East Coast fever (ECF), caused by T. parva parva. Of the approximately 3 million cattle in Zambia, 1.4 million are at risk to theileriosis. ECF is found in the Northern and Eastern provinces of the country, while CD appears in Southern, Central, Lusaka and Copperbelt provinces. Theileriosis is a major constraint to the development of the livestock industry in Zambia, with losses of about 10,000 cattle per annum. The disease is spreading at a very fast rate, over-flowing its original borders. The epidemiology is complicated by, among other factors, the wide distribution of the tick vector, Rhipicephalus appendiculatus, which is found all over the country. The current strategy of relying on tick control and therapeutic drugs as a way of controlling the disease is becoming increasingly difficult for Zambia. This is because both curative drugs and acaricides are very costly. Immunization against theileriosis using the infection and treatment method as a way of controlling the disease is becoming increasingly accepted, provided local Theileria stocks are used. This paper reviews the incidence of theileriosis in the last 2 years, 1991 and 1992. It also gives a historical perspective of the disease, epidemiology and control measures presently in use.

Classification tree for the assessment of sedentary lifestyle among hypertensive.

PubMed

Castelo Guedes Martins, Larissa; Venícios de Oliveira Lopes, Marcos; Gomes Guedes, Nirla; Paixão de Menezes, Angélica; de Oliveira Farias, Odaleia; Alves Dos Santos, Naftale

2016-04-01

To develop a classification tree of clinical indicators for the correct prediction of the nursing diagnosis "Sedentary lifestyle" (SL) in people with high blood pressure (HTN). A cross-sectional study conducted in an outpatient care center specializing in high blood pressure and Mellitus diabetes located in northeastern Brazil. The sample consisted of 285 people between 19 and 59 years old diagnosed with high blood pressure and was applied an interview and physical examination, obtaining socio-demographic information, related factors and signs and symptoms that made the defining characteristics for the diagnosis under study. The tree was generated using the CHAID algorithm (Chi-square Automatic Interaction Detection). The construction of the decision tree allowed establishing the interactions between clinical indicators that facilitate a probabilistic analysis of multiple situations allowing quantify the probability of an individual presenting a sedentary lifestyle. The tree included the clinical indicator Choose daily routine without exercise as the first node. People with this indicator showed a probability of 0.88 of presenting the SL. The second node was composed of the indicator Does not perform physical activity during leisure, with 0.99 probability of presenting the SL with these two indicators. The predictive capacity of the tree was established at 69.5%. Decision trees help nurses who care HTN people in decision-making in assessing the characteristics that increase the probability of SL nursing diagnosis, optimizing the time for diagnostic inference.

An improved classification tree analysis of high cost modules based upon an axiomatic definition of complexity

NASA Technical Reports Server (NTRS)

Tian, Jianhui; Porter, Adam; Zelkowitz, Marvin V.

1992-01-01

Identification of high cost modules has been viewed as one mechanism to improve overall system reliability, since such modules tend to produce more than their share of problems. A decision tree model was used to identify such modules. In this current paper, a previously developed axiomatic model of program complexity is merged with the previously developed decision tree process for an improvement in the ability to identify such modules. This improvement was tested using data from the NASA Software Engineering Laboratory.

A key for the Forest Service hardwood tree grades

Treesearch

Gary W. Miller; Leland F. Hanks; Harry V., Jr. Wiant

1986-01-01

A dichotomous key organizes the USDA Forest Service hardwood tree grade specifications into a stepwise procedure for those learning to grade hardwood sawtimber. The key addresses the major grade factors, tree size, surface characteristics, and allowable cull deductions in a series of paried choices that lead the user to a decision regarding tree grade.

Inferences from growing trees backwards

Treesearch

David W. Green; Kent A. McDonald

1997-01-01

The objective of this paper is to illustrate how longitudinal stress wave techniques can be useful in tracking the future quality of a growing tree. Monitoring the quality of selected trees in a plantation forest could provide early input to decisions on the effectiveness of management practices, or future utilization options, for trees in a plantation. There will...

Acute Mental Discomfort Associated with Suicide Behavior in a Clinical Sample of Patients with Affective Disorders: Ascertaining Critical Variables Using Artificial Intelligence Tools.

PubMed

Morales, Susana; Barros, Jorge; Echávarri, Orietta; García, Fabián; Osses, Alex; Moya, Claudia; Maino, María Paz; Fischman, Ronit; Núñez, Catalina; Szmulewicz, Tita; Tomicic, Alemka

2017-01-01

In efforts to develop reliable methods to detect the likelihood of impending suicidal behaviors, we have proposed the following. To gain a deeper understanding of the state of suicide risk by determining the combination of variables that distinguishes between groups with and without suicide risk. A study involving 707 patients consulting for mental health issues in three health centers in Greater Santiago, Chile. Using 345 variables, an analysis was carried out with artificial intelligence tools, Cross Industry Standard Process for Data Mining processes, and decision tree techniques. The basic algorithm was top-down, and the most suitable division produced by the tree was selected by using the lowest Gini index as a criterion and by looping it until the condition of belonging to the group with suicidal behavior was fulfilled. Four trees distinguishing the groups were obtained, of which the elements of one were analyzed in greater detail, since this tree included both clinical and personality variables. This specific tree consists of six nodes without suicide risk and eight nodes with suicide risk (tree decision 01, accuracy 0.674, precision 0.652, recall 0.678, specificity 0.670, F measure 0.665, receiver operating characteristic (ROC) area under the curve (AUC) 73.35%; tree decision 02, accuracy 0.669, precision 0.642, recall 0.694, specificity 0.647, F measure 0.667, ROC AUC 68.91%; tree decision 03, accuracy 0.681, precision 0.675, recall 0.638, specificity 0.721, F measure, 0.656, ROC AUC 65.86%; tree decision 04, accuracy 0.714, precision 0.734, recall 0.628, specificity 0.792, F measure 0.677, ROC AUC 58.85%). This study defines the interactions among a group of variables associated with suicidal ideation and behavior. By using these variables, it may be possible to create a quick and easy-to-use tool. As such, psychotherapeutic interventions could be designed to mitigate the impact of these variables on the emotional state of individuals, thereby reducing eventual risk of suicide. Such interventions may reinforce psychological well-being, feelings of self-worth, and reasons for living, for each individual in certain groups of patients.

Analytical and CASE study on Limited Search, ID3, CHAID, C4.5, Improved C4.5 and OVA Decision Tree Algorithms to design Decision Support System

NASA Astrophysics Data System (ADS)

Kaur, Parneet; Singh, Sukhwinder; Garg, Sushil; Harmanpreet

2010-11-01

In this paper we study about classification algorithms for farm DSS. By applying classification algorithms i.e. Limited search, ID3, CHAID, C4.5, Improved C4.5 and One VS all Decision Tree on common data set of crop with specified class, results are obtained. The tool used to derive results is SPINA. The graphical results obtained from tool are compared to suggest best technique to develop farm Decision Support System. This analysis would help to researchers to design effective and fast DSS for farmer to take decision for enhancing their yield.

7 CFR 319.56-43 - Baby corn and baby carrots from Zambia.

Code of Federal Regulations, 2010 CFR

2010-01-01

... § 319.56-43 Baby corn and baby carrots from Zambia. (a) Immature, dehusked “baby” sweet corn (Zea mays L... consignments only. (b) Immature “baby” carrots (Daucus carota L. ssp. sativus) for consumption measuring 10 to...

Uninjured trees - a meaningful guide to white-pine weevil control decisions

Treesearch

William E. Waters

1962-01-01

The white-pine weevil, Pissodes strobi, is a particularly insidious forest pest that can render a stand of host trees virtually worthless. It rarely, if ever, kills a tree; but the crooks, forks, and internal defects that develop in attacked trees over a period of years may reduce the merchantable volume and value of the tree at harvest age to zero. Dollar losses are...

Compensatory value of urban trees in the United States

Treesearch

David J. Nowak; Daniel E. Crane; John F. Dwyer

2002-01-01

Understanding the value of an urban forest can give decision makers a better foundation for urban tree namagement. Based on tree-valuation methods of the Council of Tree and Landscape Appraisers and field data from eight cities, total compensatory value of tree populations in U.S. cities ranges from $101 million in Jersey City, New Jersey, to $6.2 billion in New York,...

A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks.

PubMed

Alauthaman, Mohammad; Aslam, Nauman; Zhang, Li; Alasem, Rafe; Hossain, M A

2018-01-01

In recent years, Botnets have been adopted as a popular method to carry and spread many malicious codes on the Internet. These malicious codes pave the way to execute many fraudulent activities including spam mail, distributed denial-of-service attacks and click fraud. While many Botnets are set up using centralized communication architecture, the peer-to-peer (P2P) Botnets can adopt a decentralized architecture using an overlay network for exchanging command and control data making their detection even more difficult. This work presents a method of P2P Bot detection based on an adaptive multilayer feed-forward neural network in cooperation with decision trees. A classification and regression tree is applied as a feature selection technique to select relevant features. With these features, a multilayer feed-forward neural network training model is created using a resilient back-propagation learning algorithm. A comparison of feature set selection based on the decision tree, principal component analysis and the ReliefF algorithm indicated that the neural network model with features selection based on decision tree has a better identification accuracy along with lower rates of false positives. The usefulness of the proposed approach is demonstrated by conducting experiments on real network traffic datasets. In these experiments, an average detection rate of 99.08 % with false positive rate of 0.75 % was observed.

Investment incentives and the implementation of the Framework Convention on Tobacco Control: evidence from Zambia.

PubMed

Lencucha, Raphael; Drope, Jeffrey; Labonte, Ronald; Zulu, Richard; Goma, Fastone

2016-07-01

Policy misalignment across different sectors of government serves as one of the pivotal barriers to WHO Framework Convention on Tobacco Control (FCTC) implementation. This paper examines the logic used by government officials to justify investment incentives to increase tobacco processing and manufacturing in the context of FCTC implementation in Zambia. We conducted qualitative semistructured interviews with key informants from government, civil society and intergovernmental economic organisations (n=23). We supplemented the interview data with an analysis of public documents pertaining to the policy of economic development in Zambia. We found gross misalignments between the policies of the economic sector and efforts to implement the provisions of the FCTC. Our interviews uncovered the rationale used by officials in the economic sector to justify providing economic incentives to bolster tobacco processing and manufacturing in Zambia: (1) tobacco is not consumed by Zambians/tobacco is an export commodity, (2) economic benefits outweigh health costs and (3) tobacco consumption is a personal choice. Much of the struggle Zambia has experienced in implementing the FCTC can be attributed to misalignments between the economic and health sectors. Zambia's development agenda seeks to bolster agricultural processing and manufacturing. Tobacco control proponents must recognise and work within this context in order to foster productive strategies with those working on tobacco supply issues. These findings are broadly applicable to the global context. It is important that the Ministry of Health monitors the tobacco policy of and engages with these sectors to find ways of harmonising FCTC implementation. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

The reach and impact of social marketing and reproductive health communication campaigns in Zambia.

PubMed

Van Rossem, Ronan; Meekers, Dominique

2007-12-18

Like many sub-Saharan African countries, Zambia is dealing with major health issues, including HIV/AIDS, family planning, and reproductive health. To address reproductive health problems and the HIV/AIDS epidemic in Zambia, several social marketing and health communication programs focusing on reproductive and HIV/AIDS prevention programs are being implemented. This paper describes the reach of these programs and assesses their impact on condom use. This paper assesses the reach of selected radio and television programs about family planning and HIV/AIDS and of communications about the socially marketed Maximum condoms in Zambia, as well as their impact on condom use, using data from the 2001-2002 Zambia Demographic and Health Survey. To control for self-selection and endogeneity, we use a two-stage regression model to estimate the effect of program exposure on the behavioural outcomes. Those who were exposed to radio and television programs about family planning and HIV/AIDS were more likely to have ever used a condom (OR = 1.16 for men and 1.06 for women). Men highly exposed to Maximum condoms social marketing communication were more likely than those with low exposure to the program to have ever used a condom (OR = 1.48), and to have used a condom at their last sexual intercourse (OR = 1.23). Findings suggest that the reproductive health and social marketing campaigns in Zambia reached a large portion of the population and had a significant impact on condom use. The results suggest that future reproductive health communication campaigns that invest in radio programming may be more effective than those investing in television programming, and that future campaigns should seek to increase their impact among women, perhaps by focusing on the specific constrains that prevent females from using condoms.

Aflatoxin contamination of groundnut and maize in Zambia: observed and potential concentrations.

PubMed

Kachapulula, P W; Akello, J; Bandyopadhyay, R; Cotty, P J

2017-06-01

The aims of the study were to quantify aflatoxins, the potent carcinogens associated with stunting and immune suppression, in maize and groundnut across Zambia's three agroecologies and to determine the vulnerability to aflatoxin increases after purchase. Aflatoxin concentrations were determined for 334 maize and groundnut samples from 27 districts using lateral-flow immunochromatography. Seventeen per cent of crops from markets contained aflatoxin concentrations above allowable levels in Zambia (10 μg kg -1 ). Proportions of crops unsafe for human consumption differed significantly (P < 0·001) among agroecologies with more contamination (38%) in the warmest (Agroecology I) and the least (8%) in cool, wet Agroecology III. Aflatoxin in groundnut (39 μg kg -1 ) and maize (16 μg kg -1 ) differed (P = 0·032). Poor storage (31°C, 100% RH, 1 week) increased aflatoxin in safe crops by over 1000-fold in both maize and groundnut. The L morphotype of Aspergillus flavus was negatively correlated with postharvest increases in groundnut. Aflatoxins are common in Zambia's food staples with proportions of unsafe crops dependent on agroecology. Fungal community structure influences contamination suggesting Zambia would benefit from biocontrol with atoxigenic A. flavus. Aflatoxin contamination across the three agroecologies of Zambia is detailed and the case for aflatoxin management with atoxigenic biocontrol agents provided. The first method for evaluating the potential for aflatoxin increase after purchase is presented. Published 2017. This article is a U.S. Government work and is in the public domain in the USA. Journal of Applied Microbiology published by John Wiley & Sons Ltd on behalf of The Society for Applied Microbiology.

Liver fibrosis in treatment-naïve HIV-infected and HIV/HBV co-infected patients: Zambia and Switzerland compared.

PubMed

Wandeler, Gilles; Mulenga, Lloyd; Vinikoor, Michael J; Kovari, Helen; Battegay, Manuel; Calmy, Alexandra; Cavassini, Matthias; Bernasconi, Enos; Schmid, Patrick; Bolton-Moore, Carolyn; Sinkala, Edford; Chi, Benjamin H; Egger, Matthias; Rauch, Andri

2016-10-01

To examine the association between hepatitis B virus (HBV) infection and liver fibrosis in HIV-infected patients in Zambia and Switzerland. HIV-infected adults starting antiretroviral therapy in two clinics in Zambia and Switzerland were included. Liver fibrosis was evaluated using the aspartate aminotransferase-to-platelet-ratio index (APRI), with a ratio >1.5 defining significant fibrosis and a ratio >2.0 indicating cirrhosis. The association between hepatitis B surface antigen (HBsAg) positivity, HBV replication, and liver fibrosis was examined using logistic regression. In Zambia, 96 (13.0%) of 739 patients were HBsAg-positive compared to 93 (4.5%) of 2058 in Switzerland. HBsAg-positive patients were more likely to have significant liver fibrosis than HBsAg-negative ones: the adjusted odds ratio (aOR) was 3.25 (95% confidence interval (CI) 1.44-7.33) in Zambia and 2.50 (95% CI 1.19-5.25) in Switzerland. Patients with a high HBV viral load (≥20000 IU/ml) were more likely to have significant liver fibrosis compared to HBsAg-negative patients or patients with an undetectable viral load: aOR 3.85 (95% CI 1.29-11.44) in Zambia and 4.20 (95% CI 1.64-10.76) in Switzerland. In both settings, male sex was a strong risk factor for significant liver fibrosis. Despite the differences in HBV natural history between Sub-Saharan Africa and Europe, the degree of liver fibrosis and the association with important risk factors were similar. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Prognostic Factors and Decision Tree for Long-term Survival in Metastatic Uveal Melanoma.

PubMed

Lorenzo, Daniel; Ochoa, María; Piulats, Josep Maria; Gutiérrez, Cristina; Arias, Luis; Català, Jaum; Grau, María; Peñafiel, Judith; Cobos, Estefanía; Garcia-Bru, Pere; Rubio, Marcos Javier; Padrón-Pérez, Noel; Dias, Bruno; Pera, Joan; Caminal, Josep Maria

2017-12-04

The purpose of this study was to demonstrate the existence of a bimodal survival pattern in metastatic uveal melanoma. Secondary aims were to identify the characteristics and prognostic factors associated with long-term survival and to develop a clinical decision tree. The medical records of 99 metastatic uveal melanoma patients were retrospectively reviewed. Patients were classified as either short (≤ 12 months) or long-term survivors (> 12 months) based on a graphical interpretation of the survival curve after diagnosis of the first metastatic lesion. Ophthalmic and oncological characteristics were assessed in both groups. Of the 99 patients, 62 (62.6%) were classified as short-term survivors, and 37 (37.4%) as long-term survivors. The multivariate analysis identified the following predictors of long-term survival: age ≤ 65 years (p=0.012) and unaltered serum lactate dehydrogenase levels (p=0.018); additionally, the size (smaller vs. larger) of the largest liver metastasis showed a trend towards significance (p=0.063). Based on the variables significantly associated with long-term survival, we developed a decision tree to facilitate clinical decision-making. The findings of this study demonstrate the existence of a bimodal survival pattern in patients with metastatic uveal melanoma. The presence of certain clinical characteristics at diagnosis of distant disease is associated with long-term survival. A decision tree was developed to facilitate clinical decision-making and to counsel patients about the expected course of disease.

Test Reviews: Euler, B. L. (2007). "Emotional Disturbance Decision Tree". Lutz, FL: Psychological Assessment Resources

ERIC Educational Resources Information Center

Tansy, Michael

2009-01-01

The Emotional Disturbance Decision Tree (EDDT) is a teacher-completed norm-referenced rating scale published by Psychological Assessment Resources, Inc., in Lutz, Florida. The 156-item EDDT was developed for use as part of a broader assessment process to screen and assist in the identification of 5- to 18-year-old children for the special…

Phytotechnology Technical and Regulatory Guidance Document

DTIC Science & Technology

2001-04-01

contaminated media is rather new. Throughout the development process of this document, we referred to the science as “ phytoremediation .” Recently...the media containing contaminants, we now refer to “phytotechnologies” as the overarching terminology, while using “ phytoremediation ” more...publication of the ITRC document, Phytoremediation Decision Tree. The decision tree was designed to allow potential users to take basic information

Classifying dysmorphic syndromes by using artificial neural network based hierarchical decision tree.

PubMed

Özdemir, Merve Erkınay; Telatar, Ziya; Eroğul, Osman; Tunca, Yusuf

2018-05-01

Dysmorphic syndromes have different facial malformations. These malformations are significant to an early diagnosis of dysmorphic syndromes and contain distinctive information for face recognition. In this study we define the certain features of each syndrome by considering facial malformations and classify Fragile X, Hurler, Prader Willi, Down, Wolf Hirschhorn syndromes and healthy groups automatically. The reference points are marked on the face images and ratios between the points' distances are taken into consideration as features. We suggest a neural network based hierarchical decision tree structure in order to classify the syndrome types. We also implement k-nearest neighbor (k-NN) and artificial neural network (ANN) classifiers to compare classification accuracy with our hierarchical decision tree. The classification accuracy is 50, 73 and 86.7% with k-NN, ANN and hierarchical decision tree methods, respectively. Then, the same images are shown to a clinical expert who achieve a recognition rate of 46.7%. We develop an efficient system to recognize different syndrome types automatically in a simple, non-invasive imaging data, which is independent from the patient's age, sex and race at high accuracy. The promising results indicate that our method can be used for pre-diagnosis of the dysmorphic syndromes by clinical experts.

Applying decision tree for identification of a low risk population for type 2 diabetes. Tehran Lipid and Glucose Study.

PubMed

Ramezankhani, Azra; Pournik, Omid; Shahrabi, Jamal; Khalili, Davood; Azizi, Fereidoun; Hadaegh, Farzad

2014-09-01

The aim of this study was to create a prediction model using data mining approach to identify low risk individuals for incidence of type 2 diabetes, using the Tehran Lipid and Glucose Study (TLGS) database. For a 6647 population without diabetes, aged ≥20 years, followed for 12 years, a prediction model was developed using classification by the decision tree technique. Seven hundred and twenty-nine (11%) diabetes cases occurred during the follow-up. Predictor variables were selected from demographic characteristics, smoking status, medical and drug history and laboratory measures. We developed the predictive models by decision tree using 60 input variables and one output variable. The overall classification accuracy was 90.5%, with 31.1% sensitivity, 97.9% specificity; and for the subjects without diabetes, precision and f-measure were 92% and 0.95, respectively. The identified variables included fasting plasma glucose, body mass index, triglycerides, mean arterial blood pressure, family history of diabetes, educational level and job status. In conclusion, decision tree analysis, using routine demographic, clinical, anthropometric and laboratory measurements, created a simple tool to predict individuals at low risk for type 2 diabetes. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Intelligent Diagnostic Assistant for Complicated Skin Diseases through C5's Algorithm.

PubMed

Jeddi, Fatemeh Rangraz; Arabfard, Masoud; Kermany, Zahra Arab

2017-09-01

Intelligent Diagnostic Assistant can be used for complicated diagnosis of skin diseases, which are among the most common causes of disability. The aim of this study was to design and implement a computerized intelligent diagnostic assistant for complicated skin diseases through C5's Algorithm. An applied-developmental study was done in 2015. Knowledge base was developed based on interviews with dermatologists through questionnaires and checklists. Knowledge representation was obtained from the train data in the database using Excel Microsoft Office. Clementine Software and C5's Algorithms were applied to draw the decision tree. Analysis of test accuracy was performed based on rules extracted using inference chains. The rules extracted from the decision tree were entered into the CLIPS programming environment and the intelligent diagnostic assistant was designed then. The rules were defined using forward chaining inference technique and were entered into Clips programming environment as RULE. The accuracy and error rates obtained in the training phase from the decision tree were 99.56% and 0.44%, respectively. The accuracy of the decision tree was 98% and the error was 2% in the test phase. Intelligent diagnostic assistant can be used as a reliable system with high accuracy, sensitivity, specificity, and agreement.

Data mining for multiagent rules, strategies, and fuzzy decision tree structure

NASA Astrophysics Data System (ADS)

Smith, James F., III; Rhyne, Robert D., II; Fisher, Kristin

2002-03-01

A fuzzy logic based resource manager (RM) has been developed that automatically allocates electronic attack resources in real-time over many dissimilar platforms. Two different data mining algorithms have been developed to determine rules, strategies, and fuzzy decision tree structure. The first data mining algorithm uses a genetic algorithm as a data mining function and is called from an electronic game. The game allows a human expert to play against the resource manager in a simulated battlespace with each of the defending platforms being exclusively directed by the fuzzy resource manager and the attacking platforms being controlled by the human expert or operating autonomously under their own logic. This approach automates the data mining problem. The game automatically creates a database reflecting the domain expert's knowledge. It calls a data mining function, a genetic algorithm, for data mining of the database as required and allows easy evaluation of the information mined in the second step. The criterion for re- optimization is discussed as well as experimental results. Then a second data mining algorithm that uses a genetic program as a data mining function is introduced to automatically discover fuzzy decision tree structures. Finally, a fuzzy decision tree generated through this process is discussed.

Prevalence and Determinants of Preterm Birth in Tehran, Iran: A Comparison between Logistic Regression and Decision Tree Methods.

PubMed

Amini, Payam; Maroufizadeh, Saman; Samani, Reza Omani; Hamidi, Omid; Sepidarkish, Mahdi

2017-06-01

Preterm birth (PTB) is a leading cause of neonatal death and the second biggest cause of death in children under five years of age. The objective of this study was to determine the prevalence of PTB and its associated factors using logistic regression and decision tree classification methods. This cross-sectional study was conducted on 4,415 pregnant women in Tehran, Iran, from July 6-21, 2015. Data were collected by a researcher-developed questionnaire through interviews with mothers and review of their medical records. To evaluate the accuracy of the logistic regression and decision tree methods, several indices such as sensitivity, specificity, and the area under the curve were used. The PTB rate was 5.5% in this study. The logistic regression outperformed the decision tree for the classification of PTB based on risk factors. Logistic regression showed that multiple pregnancies, mothers with preeclampsia, and those who conceived with assisted reproductive technology had an increased risk for PTB ( p < 0.05). Identifying and training mothers at risk as well as improving prenatal care may reduce the PTB rate. We also recommend that statisticians utilize the logistic regression model for the classification of risk groups for PTB.

Decision tree and PCA-based fault diagnosis of rotating machinery

NASA Astrophysics Data System (ADS)

Sun, Weixiang; Chen, Jin; Li, Jiaqing

2007-04-01

After analysing the flaws of conventional fault diagnosis methods, data mining technology is introduced to fault diagnosis field, and a new method based on C4.5 decision tree and principal component analysis (PCA) is proposed. In this method, PCA is used to reduce features after data collection, preprocessing and feature extraction. Then, C4.5 is trained by using the samples to generate a decision tree model with diagnosis knowledge. At last the tree model is used to make diagnosis analysis. To validate the method proposed, six kinds of running states (normal or without any defect, unbalance, rotor radial rub, oil whirl, shaft crack and a simultaneous state of unbalance and radial rub), are simulated on Bently Rotor Kit RK4 to test C4.5 and PCA-based method and back-propagation neural network (BPNN). The result shows that C4.5 and PCA-based diagnosis method has higher accuracy and needs less training time than BPNN.

Decision Tree based Prediction and Rule Induction for Groundwater Trichloroethene (TCE) Pollution Vulnerability

NASA Astrophysics Data System (ADS)

Park, J.; Yoo, K.

2013-12-01

For groundwater resource conservation, it is important to accurately assess groundwater pollution sensitivity or vulnerability. In this work, we attempted to use data mining approach to assess groundwater pollution vulnerability in a TCE (trichloroethylene) contaminated Korean industrial site. The conventional DRASTIC method failed to describe TCE sensitivity data with a poor correlation with hydrogeological properties. Among the different data mining methods such as Artificial Neural Network (ANN), Multiple Logistic Regression (MLR), Case Base Reasoning (CBR), and Decision Tree (DT), the accuracy and consistency of Decision Tree (DT) was the best. According to the following tree analyses with the optimal DT model, the failure of the conventional DRASTIC method in fitting with TCE sensitivity data may be due to the use of inaccurate weight values of hydrogeological parameters for the study site. These findings provide a proof of concept that DT based data mining approach can be used in predicting and rule induction of groundwater TCE sensitivity without pre-existing information on weights of hydrogeological properties.

The application of data mining techniques to oral cancer prognosis.

PubMed

Tseng, Wan-Ting; Chiang, Wei-Fan; Liu, Shyun-Yeu; Roan, Jinsheng; Lin, Chun-Nan

2015-05-01

This study adopted an integrated procedure that combines the clustering and classification features of data mining technology to determine the differences between the symptoms shown in past cases where patients died from or survived oral cancer. Two data mining tools, namely decision tree and artificial neural network, were used to analyze the historical cases of oral cancer, and their performance was compared with that of logistic regression, the popular statistical analysis tool. Both decision tree and artificial neural network models showed superiority to the traditional statistical model. However, as to clinician, the trees created by the decision tree models are relatively easier to interpret compared to that of the artificial neural network models. Cluster analysis also discovers that those stage 4 patients whose also possess the following four characteristics are having an extremely low survival rate: pN is N2b, level of RLNM is level I-III, AJCC-T is T4, and cells mutate situation (G) is moderate.

Aflatoxin contamination of groundnut and maize in Zambia: observed and potential concentrations

USDA-ARS?s Scientific Manuscript database

Maize and groundnut, important staples in Zambia, are susceptible to aflatoxin-producing fungi. Aflatoxins are potent human carcinogens also associated with stunting and immunosuppression. Although health and economic burdens of aflatoxins are well known, patterns of contamination in maize and grou...

Aspergillus section Flavi community structure in Zambia influences aflatoxin contamination of Maize and Groundnut

USDA-ARS?s Scientific Manuscript database

Aflatoxins are cancer-causing, immuno-suppressive mycotoxins that frequently contaminate important staples in Zambia including maize and groundnut. Several species within Aspergillus section Flavi have been implicated as causal agents of aflatoxin contamination in Africa. However, Aspergillus popula...

Non-prescription sale and dispensing of antibiotics in community pharmacies in Zambia.

PubMed

Kalungia, Aubrey Chichonyi; Burger, Johanita; Godman, Brian; Costa, Juliana de Oliveira; Simuwelu, Chimwemwe

2016-12-01

In Zambia, antibiotics are categorized as prescription-only medicines. Antibiotics dispensed without a prescription pose a public health threat, which is a concern. Consequently, the aim is to ascertain the extent of non-prescription sales and dispensing of antibiotics in community pharmacies in Zambia. The practice of non-prescription sale and dispensing were assessed in 73 randomly selected community retail pharmacies, using a structured interviewer-administered questionnaire with simulated case scenarios. Majority (97%) stated that clients frequently requested non-prescribed antibiotics. Interviewees usually asked clients' indications (94%), counselled on dosing (96%) and suggested changes to antibiotic choices (97%). All (100%) dispensed non-prescribed antibiotics. Commonly dispensed antibiotics included amoxicillin (52%), cotrimoxazole (25%) and metronidazole (23%). Non-prescription sale and dispensing of antibiotics was significantly associated with interviewees' professional qualification in four out of five simulations. Non-prescription sale and dispensing of antibiotics is widespread in Zambia. Concerted public and professional interventions are needed coupled with stronger regulatory enforcement to reduce this.

Lusaka, Zambia, during SAFARI-2000: Convergence of local and imported ozone pollution

NASA Astrophysics Data System (ADS)

Thompson, Anne M.; Witte, Jacquelyn C.; Freiman, M. Tal; Phahlane, N. Agnes; Coetzee, Gert J. R.

2002-10-01

In August and September, throughout south central Africa, seasonal clearing of dry vegetation and other fire-related activities lead to intense smoke haze and ozone formation. The first ozone soundings in the heart of the southern African burning region were taken at Lusaka, Zambia (15.5S, 28E) in early September 2000. Maximum surface ozone was over 90 ppbv and column tropospheric ozone exceeded 50 DU. These values are higher than concurrent measurements over Nairobi (1S, 38E) and Irene (25S, 28E, near Pretoria). At least 30% of Lusaka surface ozone appears to be from local sources. A layer at 800-500 hPa has ozone >120 ppbv and originates from trans-boundary recirculation. Starting out over Zambia, Angola, and Namibia, ozone-rich air travels east to the Indian Ocean, before heading back toward Mozambique, Zimbabwe and Zambia. Thus, Lusaka collects local and imported pollution, consistent with its location within the southern African gyre.

"Lazy men", time-use, and rural development in Zambia.

PubMed

Whitehead, A

1999-11-01

This paper examines how work and the labor in agriculture in rural sub-Saharan Africa is measured. Section 1 presents a historical example of colonial discourses of the "lazy" African (the Lamba in Zambia). Section 2 analyzes a study carried out in rural Zambia to illustrate the relationship between stereotypes held by many Europeans, particular aspects of the colonial project, and the social relations brought about by colonialism. Section 3 examines the ways in which present work and labor approaches in sub-Saharan Africa embody value judgements which leads to distorted documentation of the division of labor between opposite genders. Sections 4 through 7 look at a time-use study conducted in Zambia and argue that studies of such nature create value judgement on what comprises work, and about how researchers and planners classify this. Overall, this article has demonstrated that time-use surveys may provide inadequate understanding of women and men's work in the absence of an understanding of the local context in which the work is undertaken, and of labor markets.

Preliminary Investigation of Trypanosomosis in Exotic Dog Breeds from Zambia's Luangwa and Zambezi Valleys Using LAMP

PubMed Central

Namangala, Boniface; Oparaocha, Elizabeth; Kajino, Kiichi; Hayashida, Kyoko; Moonga, Ladslav; Inoue, Noboru; Suzuki, Yasuhiko; Sugimoto, Chihiro

2013-01-01

Canine African trypanosomosis (CAT) is rarely reported in the literature. In this preliminary study, we evaluated the performance of loop-mediated isothermal amplification (LAMP) against microscopy to detect CAT in six exotic dog breeds naturally infected with trypanosomes from Zambia's South Luangwa National Park and Chiawa Game Management Area. To our knowledge, this is the first report of CAT in Zambia. The patients exhibited a variety of aspecific clinical signs. The LAMP did not only confirm all six parasitologically positive CAT cases detected passively between April 2010 and January 2012, but was also critical in trypanosome speciation. According to LAMP, the majority of the dogs had monolytic infections with either Trypanosoma congolense or Trypanosoma brucei rhodesiense. The LAMP is thus a potential simple and cost-effective tool for trypanosome diagnosis in endemic regions. The rare report of zoonotic trypanosomes in dogs in Zambia has public health implications and justifies further investigations of CAT. PMID:23716412

Insecticide-treated nets mass distribution campaign: benefits and lessons in Zambia.

PubMed

Masaninga, Freddie; Mukumbuta, Nawa; Ndhlovu, Ketty; Hamainza, Busiku; Wamulume, Pauline; Chanda, Emmanuel; Banda, John; Mwanza-Ingwe, Mercy; Miller, John M; Ameneshewa, Birkinesh; Mnzava, Abraham; Kawesha-Chizema, Elizabeth

2018-04-24

Zambia was an early adopter of insecticide-treated nets strategy in 2001, and policy for mass distribution with long-lasting insecticidal nets (LLINs) in 2005. Since then, the country has implemented mass distribution supplemented with routine delivery through antenatal care and under five clinics in health facilities. The national targets of universal (100%) coverage and 80% utilization of LLINs have not been attained. Free mass LLIN distribution campaign in Zambia offers important lessons to inform future campaigns in the African region. This study reviewed LLIN free mass distribution campaign information derived from Zambia's national and World Health Organization Global Malaria Programme annual reports and strategic plans published between 2001 and 2016. In 2014, a nationwide mass distribution campaign in Zambia delivered all the 6.0 million LLINs in 6 out of 10 provinces in 4 months between June and September before the onset of the rainy season. Compared with 235,800 LLINs and 2.9 million LLINs distributed on a rolling basis in 2008 and 2013, respectively, the 2014 mass campaign, which distributed 6 million LLINs represented the largest one-time-nationwide LLIN distribution in Zambia. The province (Luapula) with highest malaria transmission, mostly with rural settings recorded 98-100% sleeping spaces in homes covered with LLINs. The percentage of households owning at least 1 LLIN increased from 50.9% in 2006 to 77.7% in 2015. The 2014 mass campaign involved a coordinated response with substantial investments into macro (central) and micro (district) level planning, capacity building, tracking and logistics management supported by a new non-health sector partnership landscape. Coordination of LLIN distribution and logistics benefited from the mobile phone technology to transmit "real time" data on commodity tracking that facilitated timely delivery to districts. Free mass distribution of LLINs policy was adopted in 2005 in Zambia. Consistently implemented, has not only contributed to increased coverage of LLINs, but has also produced the added value and lessons of strengthening joint planning, strategic coordination, partnerships with non-health sector institutions and community engagement with traditional leaders at community. Furthermore, the mass distribution, through improving coverage has indirect added (spin-off) value or impact on other arthropod-borne diseases, in addition to malaria.

Estimating Loss to Follow-Up in HIV-Infected Patients on Antiretroviral Therapy: The Effect of the Competing Risk of Death in Zambia and Switzerland

PubMed Central

Mwango, Albert; Stringer, Jeffrey; Ledergerber, Bruno; Mulenga, Lloyd; Bucher, Heiner C.; Westfall, Andrew O.; Calmy, Alexandra; Boulle, Andrew; Chintu, Namwinga; Egger, Matthias; Chi, Benjamin H.

2011-01-01

Background Loss to follow-up (LTFU) is common in antiretroviral therapy (ART) programmes. Mortality is a competing risk (CR) for LTFU; however, it is often overlooked in cohort analyses. We examined how the CR of death affected LTFU estimates in Zambia and Switzerland. Methods and Findings HIV-infected patients aged ≥18 years who started ART 2004–2008 in observational cohorts in Zambia and Switzerland were included. We compared standard Kaplan-Meier curves with CR cumulative incidence. We calculated hazard ratios for LTFU across CD4 cell count strata using cause-specific Cox models, or Fine and Gray subdistribution models, adjusting for age, gender, body mass index and clinical stage. 89,339 patients from Zambia and 1,860 patients from Switzerland were included. 12,237 patients (13.7%) in Zambia and 129 patients (6.9%) in Switzerland were LTFU and 8,498 (9.5%) and 29 patients (1.6%), respectively, died. In Zambia, the probability of LTFU was overestimated in Kaplan-Meier curves: estimates at 3.5 years were 29.3% for patients starting ART with CD4 cells <100 cells/µl and 15.4% among patients starting with ≥350 cells/µL. The estimates from CR cumulative incidence were 22.9% and 13.6%, respectively. Little difference was found between naïve and CR analyses in Switzerland since only few patients died. The results from Cox and Fine and Gray models were similar: in Zambia the risk of loss to follow-up and death increased with decreasing CD4 counts at the start of ART, whereas in Switzerland there was a trend in the opposite direction, with patients with higher CD4 cell counts more likely to be lost to follow-up. Conclusions In ART programmes in low-income settings the competing risk of death can substantially bias standard analyses of LTFU. The CD4 cell count and other prognostic factors may be differentially associated with LTFU in low-income and high-income settings. PMID:22205933

Machine Learning Through Signature Trees. Applications to Human Speech.

ERIC Educational Resources Information Center

White, George M.

A signature tree is a binary decision tree used to classify unknown patterns. An attempt was made to develop a computer program for manipulating signature trees as a general research tool for exploring machine learning and pattern recognition. The program was applied to the problem of speech recognition to test its effectiveness for a specific…

Modeling individual tree survial

Treesearch

Quang V. Cao

2016-01-01

Information provided by growth and yield models is the basis for forest managers to make decisions on how to manage their forests. Among different types of growth models, whole-stand models offer predictions at stand level, whereas individual-tree models give detailed information at tree level. The well-known logistic regression is commonly used to predict tree...

Predicting Tillage Patterns in the Tiffin River Watershed Using Remote Sensing Methods

NASA Astrophysics Data System (ADS)

Brooks, C.; McCarty, J. L.; Dean, D. B.; Mann, B. F.

2012-12-01

Previous research in tillage mapping has focused primarily on utilizing low to no-cost, moderate (30 m to 15 m) resolution satellite data. Successful data processing techniques published in the scientific literature have focused on extracting and/or classifying tillage patterns through manipulation of spectral bands. For instance, Daughtry et al. (2005) evaluated several spectral indices for crop residue cover using satellite multispectral and hyperspectral data and to categorize soil tillage intensity in agricultural fields. A weak to moderate relationship between Landsat Thematic Mapper (TM) indices and crop residue cover was found; similar results were reported in Minnesota. Building on the findings from the scientific literature and previous work done by MTRI in the heavily agricultural Tiffin watershed of northwest Ohio and southeast Michigan, a decision tree classifier approach (also referred to as a classification tree) was used, linking several satellite data to on-the-ground tillage information in order to boost classification results. This approach included five tillage indices and derived products. A decision tree methodology enabled the development of statistically optimized (i.e., minimizing misclassification rates) classification algorithms at various desired time steps: monthly, seasonally, and annual over the 2006-2010 time period. Due to their flexibility, processing speed, and availability within all major remote sensing and statistical software packages, decision trees can ingest several data inputs from multiple sensors and satellite products, selecting only the bands, band ratios, indices, and products that further reduce misclassification errors. The project team created crop-specific tillage pattern classification trees whereby a training data set (~ 50% of available ground data) was created for production of the actual decision tree and a validation data set was set aside (~ 50% of available ground data) in order to assess the accuracy of the classification. A seasonal time step was used, optimizing a decision tree based on seasonal ground data for tillage patterns and satellite data and products for years 2006 through 2010. Annual crop type maps derived by the project team and the USDA Cropland Data Layer project was used an input to understand locations of corn, soybeans, wheat, etc. on a yearly basis. As previously stated, the robustness of the decision tree approach is the ability to implement various satellite data and products across temporal, spectral, and spatial resolutions, thereby improving the resulting classification and providing a reliable method that is not sensor-dependent. Tillage pattern classification from satellite imagery is not a simple task and has proven a challenge to previous researchers investigating this remote sensing topic. The team's decision tree method produced a practical, usable output within a focused project time period. Daughtry, C.S.T., Hunt Jr., E.R., Doraiswamy, P.C., McMurtrey III, J.E. 2005. Remote sensing the spatial distribution of crop residues. Agron. J. 97, 864-871.

Using decision tree models to depict primary care physicians CRC screening decision heuristics.

PubMed

Wackerbarth, Sarah B; Tarasenko, Yelena N; Curtis, Laurel A; Joyce, Jennifer M; Haist, Steven A

2007-10-01

The purpose of this study was to identify decision heuristics utilized by primary care physicians in formulating colorectal cancer screening recommendations. Qualitative research using in-depth semi-structured interviews. We interviewed 66 primary care internists and family physicians evenly drawn from academic and community practices. A majority of physicians were male, and almost all were white, non-Hispanic. Three researchers independently reviewed each transcript to determine the physician's decision criteria and developed decision trees. Final trees were developed by consensus. The constant comparative methodology was used to define the categories. Physicians were found to use 1 of 4 heuristics ("age 50," "age 50, if family history, then earlier," "age 50, if family history, then screen at age 40," or "age 50, if family history, then adjust relative to reference case") for the timing recommendation and 5 heuristics ["fecal occult blood test" (FOBT), "colonoscopy," "if not colonoscopy, then...," "FOBT and another test," and "a choice between options"] for the type decision. No connection was found between timing and screening type heuristics. We found evidence of heuristic use. Further research is needed to determine the potential impact on quality of care.

Semi-Automated Approach for Mapping Urban Trees from Integrated Aerial LiDAR Point Cloud and Digital Imagery Datasets

NASA Astrophysics Data System (ADS)

Dogon-Yaro, M. A.; Kumar, P.; Rahman, A. Abdul; Buyuksalih, G.

2016-09-01

Mapping of trees plays an important role in modern urban spatial data management, as many benefits and applications inherit from this detailed up-to-date data sources. Timely and accurate acquisition of information on the condition of urban trees serves as a tool for decision makers to better appreciate urban ecosystems and their numerous values which are critical to building up strategies for sustainable development. The conventional techniques used for extracting trees include ground surveying and interpretation of the aerial photography. However, these techniques are associated with some constraints, such as labour intensive field work and a lot of financial requirement which can be overcome by means of integrated LiDAR and digital image datasets. Compared to predominant studies on trees extraction mainly in purely forested areas, this study concentrates on urban areas, which have a high structural complexity with a multitude of different objects. This paper presented a workflow about semi-automated approach for extracting urban trees from integrated processing of airborne based LiDAR point cloud and multispectral digital image datasets over Istanbul city of Turkey. The paper reveals that the integrated datasets is a suitable technology and viable source of information for urban trees management. As a conclusion, therefore, the extracted information provides a snapshot about location, composition and extent of trees in the study area useful to city planners and other decision makers in order to understand how much canopy cover exists, identify new planting, removal, or reforestation opportunities and what locations have the greatest need or potential to maximize benefits of return on investment. It can also help track trends or changes to the urban trees over time and inform future management decisions.

Decision-Tree Program

NASA Technical Reports Server (NTRS)

Buntine, Wray

1994-01-01

IND computer program introduces Bayesian and Markov/maximum-likelihood (MML) methods and more-sophisticated methods of searching in growing trees. Produces more-accurate class-probability estimates important in applications like diagnosis. Provides range of features and styles with convenience for casual user, fine-tuning for advanced user or for those interested in research. Consists of four basic kinds of routines: data-manipulation, tree-generation, tree-testing, and tree-display. Written in C language.

Interpretable Categorization of Heterogeneous Time Series Data

NASA Technical Reports Server (NTRS)

Lee, Ritchie; Kochenderfer, Mykel J.; Mengshoel, Ole J.; Silbermann, Joshua

2017-01-01

We analyze data from simulated aircraft encounters to validate and inform the development of a prototype aircraft collision avoidance system. The high-dimensional and heterogeneous time series dataset is analyzed to discover properties of near mid-air collisions (NMACs) and categorize the NMAC encounters. Domain experts use these properties to better organize and understand NMAC occurrences. Existing solutions either are not capable of handling high-dimensional and heterogeneous time series datasets or do not provide explanations that are interpretable by a domain expert. The latter is critical to the acceptance and deployment of safety-critical systems. To address this gap, we propose grammar-based decision trees along with a learning algorithm. Our approach extends decision trees with a grammar framework for classifying heterogeneous time series data. A context-free grammar is used to derive decision expressions that are interpretable, application-specific, and support heterogeneous data types. In addition to classification, we show how grammar-based decision trees can also be used for categorization, which is a combination of clustering and generating interpretable explanations for each cluster. We apply grammar-based decision trees to a simulated aircraft encounter dataset and evaluate the performance of four variants of our learning algorithm. The best algorithm is used to analyze and categorize near mid-air collisions in the aircraft encounter dataset. We describe each discovered category in detail and discuss its relevance to aircraft collision avoidance.

Application of data mining techniques to explore predictors of upper urinary tract damage in patients with neurogenic bladder.

PubMed

Fang, H; Lu, B; Wang, X; Zheng, L; Sun, K; Cai, W

2017-08-17

This study proposed a decision tree model to screen upper urinary tract damage (UUTD) for patients with neurogenic bladder (NGB). Thirty-four NGB patients with UUTD were recruited in the case group, while 78 without UUTD were included in the control group. A decision tree method, classification and regression tree (CART), was then applied to develop the model in which UUTD was used as a dependent variable and history of urinary tract infections, bladder management, conservative treatment, and urodynamic findings were used as independent variables. The urethra function factor was found to be the primary screening information of patients and treated as the root node of the tree; Pabd max (maximum abdominal pressure, >14 cmH2O), Pves max (maximum intravesical pressure, ≤89 cmH2O), and gender (female) were also variables associated with UUTD. The accuracy of the proposed model was 84.8%, and the area under curve was 0.901 (95%CI=0.844-0.958), suggesting that the decision tree model might provide a new and convenient way to screen UUTD for NGB patients in both undeveloped and developing areas.

Graphic Representations as Tools for Decision Making.

ERIC Educational Resources Information Center

Howard, Judith

2001-01-01

Focuses on the use of graphic representations to enable students to improve their decision making skills in the social studies. Explores three visual aids used in assisting students with decision making: (1) the force field; (2) the decision tree; and (3) the decision making grid. (CMK)

Assessment of coalbed gas resources of the Kalahari Basin Province of Botswana, Zimbabwe, and Zambia, Africa, 2016

USGS Publications Warehouse

Brownfield, Michael E.; Schenk, Christopher J.; Klett, Timothy R.; Tennyson, Marilyn E.; Mercier, Tracey J.; Gaswirth, Stephanie B.; Marra, Kristen R.; Hawkins, Sarah J.; Finn, Thomas M.; Le, Phuong A.; Leathers-Miller, Heidi M.

2017-02-24

Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 4.5 trillion cubic feet of coalbed gas in the Kalahari Basin Province of Botswana, Zambia, and Zimbabwe, Africa.

Costing commodity and human resource needs for integrated community case management in thie differing community health strategies of Ethiopia, Kenya and Zambia.

PubMed

Nefdt, Rory; Ribaira, Eric; Diallo, Khassoum

2014-10-01

To ensure correct and appropriate funding is available, there is a need to estimate resource needs for improved planning and implementation of integrated Community Case Management (iCCM). To compare and estimate costs for commodity and human resource needs for iCCM, based on treatment coverage rates, bottlenecks and national targets in Ethiopia, Kenya and Zambia from 2014 to 2016. Resource needs were estimated using Ministry of Health (MoH) targets fronm 2014 to 2016 for implementation of case management of pneumonia, diarrhea and malaria through iCCM based on epidemiological, demographic, economic, intervention coverage and other health system parameters. Bottleneck analysis adjusted cost estimates against system barriers. Ethiopia, Kenya and Zambia were chosen to compare differences in iCCM costs in different programmatic implementation landscapes. Coverage treatment rates through iCCM are lowest in Ethiopia, followed by Kenya and Zambia, but Ethiopia had the greatest increases between 2009 and 2012. Deployment of health extension workers (HEWs) in Ethiopia is more advanced compared to Kenya and Zambia, which have fewer equivalent cadres (called commu- nity health workers (CHWs)) covering a smaller proportion of the population. Between 2014 and 2016, the propor- tion of treatments through iCCM compared to health centres are set to increase from 30% to 81% in Ethiopia, 1% to 18% in Kenya and 3% to 22% in Zambia. The total estimated cost of iCCM for these three years are USD 75,531,376 for Ethiopia, USD 19,839,780 for Kenya and USD 33,667,742 for Zambia. Projected per capita expen- diture for 2016 is USD 0.28 for Ethiopia, USD 0.20 in Kenya and USD 0.98 in Zambia. Commodity costs for pneumonia and diarrhea were a small fraction of the total iCCM budget for all three countries (less than 3%), while around 80% of the costs related to human resources. Analysis of coverage, demography and epidemiology data improves estimates of fimding requirements for iCCM. Bottleneck analysis adjusts cost estimates by including system barriers, thus reflecting a more accurate estimate of potential resource utilization. Adding pneumonia and diarrhea interventions to existing large scale community-based malaria case management programs is likely to require relatively small and nationally affordable investments. iCCM can be implemented for USD 0.09 to 0.98 per capita per annum, depending on the stage of scale-up and targets set by the MoH.

The Effect of Defense R&D Expenditures on Military Capability and Technological Spillover

DTIC Science & Technology

2013-03-01

ix List of Figures Page Figure 1. Decision Tree for Sectoring R&D Units...approach, often called sectoring , categorizes R&D activities by funding source, and the functional approach categorizes R&D activities by their objective...economic objectives (defense, and control and care of environment) (OECD, 2002). Figure 1 shows the decision tree for sectoring R&D units and

Modeling flash floods in ungauged mountain catchments of China: A decision tree learning approach for parameter regionalization

NASA Astrophysics Data System (ADS)

Ragettli, S.; Zhou, J.; Wang, H.; Liu, C.

2017-12-01

Flash floods in small mountain catchments are one of the most frequent causes of loss of life and property from natural hazards in China. Hydrological models can be a useful tool for the anticipation of these events and the issuing of timely warnings. Since sub-daily streamflow information is unavailable for most small basins in China, one of the main challenges is finding appropriate parameter values for simulating flash floods in ungauged catchments. In this study, we use decision tree learning to explore parameter set transferability between different catchments. For this purpose, the physically-based, semi-distributed rainfall-runoff model PRMS-OMS is set up for 35 catchments in ten Chinese provinces. Hourly data from more than 800 storm runoff events are used to calibrate the model and evaluate the performance of parameter set transfers between catchments. For each catchment, 58 catchment attributes are extracted from several data sets available for whole China. We then use a data mining technique (decision tree learning) to identify catchment similarities that can be related to good transfer performance. Finally, we use the splitting rules of decision trees for finding suitable donor catchments for ungauged target catchments. We show that decision tree learning allows to optimally utilize the information content of available catchment descriptors and outperforms regionalization based on a conventional measure of physiographic-climatic similarity by 15%-20%. Similar performance can be achieved with a regionalization method based on spatial proximity, but decision trees offer flexible rules for selecting suitable donor catchments, not relying on the vicinity of gauged catchments. This flexibility makes the method particularly suitable for implementation in sparsely gauged environments. We evaluate the probability to detect flood events exceeding a given return period, considering measured discharge and PRMS-OMS simulated flows with regionalized parameters. Overall, the probability of detection of an event with a return period of 10 years is 62%. 44% of all 10-year flood peaks can be detected with a timing error of 2 hours or less. These results indicate that the modeling system can provide useful information about the timing and magnitude of flood events at ungauged sites.

Blood oxygen level dependent magnetic resonance imaging for detecting pathological patterns in lupus nephritis patients: a preliminary study using a decision tree model.

PubMed

Shi, Huilan; Jia, Junya; Li, Dong; Wei, Li; Shang, Wenya; Zheng, Zhenfeng

2018-02-09

Precise renal histopathological diagnosis will guide therapy strategy in patients with lupus nephritis. Blood oxygen level dependent (BOLD) magnetic resonance imaging (MRI) has been applicable noninvasive technique in renal disease. This current study was performed to explore whether BOLD MRI could contribute to diagnose renal pathological pattern. Adult patients with lupus nephritis renal pathological diagnosis were recruited for this study. Renal biopsy tissues were assessed based on the lupus nephritis ISN/RPS 2003 classification. The Blood oxygen level dependent magnetic resonance imaging (BOLD-MRI) was used to obtain functional magnetic resonance parameter, R2* values. Several functions of R2* values were calculated and used to construct algorithmic models for renal pathological patterns. In addition, the algorithmic models were compared as to their diagnostic capability. Both Histopathology and BOLD MRI were used to examine a total of twelve patients. Renal pathological patterns included five classes III (including 3 as class III + V) and seven classes IV (including 4 as class IV + V). Three algorithmic models, including decision tree, line discriminant, and logistic regression, were constructed to distinguish the renal pathological pattern of class III and class IV. The sensitivity of the decision tree model was better than that of the line discriminant model (71.87% vs 59.48%, P < 0.001) and inferior to that of the Logistic regression model (71.87% vs 78.71%, P < 0.001). The specificity of decision tree model was equivalent to that of the line discriminant model (63.87% vs 63.73%, P = 0.939) and higher than that of the logistic regression model (63.87% vs 38.0%, P < 0.001). The Area under the ROC curve (AUROCC) of the decision tree model was greater than that of the line discriminant model (0.765 vs 0.629, P < 0.001) and logistic regression model (0.765 vs 0.662, P < 0.001). BOLD MRI is a useful non-invasive imaging technique for the evaluation of lupus nephritis. Decision tree models constructed using functions of R2* values may facilitate the prediction of renal pathological patterns.

A Clinical Decision Tree to Predict Whether a Bacteremic Patient Is Infected With an Extended-Spectrum β-Lactamase-Producing Organism.

PubMed

Goodman, Katherine E; Lessler, Justin; Cosgrove, Sara E; Harris, Anthony D; Lautenbach, Ebbing; Han, Jennifer H; Milstone, Aaron M; Massey, Colin J; Tamma, Pranita D

2016-10-01

Timely identification of extended-spectrum β-lactamase (ESBL) bacteremia can improve clinical outcomes while minimizing unnecessary use of broad-spectrum antibiotics, including carbapenems. However, most clinical microbiology laboratories currently require at least 24 additional hours from the time of microbial genus and species identification to confirm ESBL production. Our objective was to develop a user-friendly decision tree to predict which organisms are ESBL producing, to guide appropriate antibiotic therapy. We included patients ≥18 years of age with bacteremia due to Escherichia coli or Klebsiella species from October 2008 to March 2015 at Johns Hopkins Hospital. Isolates with ceftriaxone minimum inhibitory concentrations ≥2 µg/mL underwent ESBL confirmatory testing. Recursive partitioning was used to generate a decision tree to determine the likelihood that a bacteremic patient was infected with an ESBL producer. Discrimination of the original and cross-validated models was evaluated using receiver operating characteristic curves and by calculation of C-statistics. A total of 1288 patients with bacteremia met eligibility criteria. For 194 patients (15%), bacteremia was due to a confirmed ESBL producer. The final classification tree for predicting ESBL-positive bacteremia included 5 predictors: history of ESBL colonization/infection, chronic indwelling vascular hardware, age ≥43 years, recent hospitalization in an ESBL high-burden region, and ≥6 days of antibiotic exposure in the prior 6 months. The decision tree's positive and negative predictive values were 90.8% and 91.9%, respectively. Our findings suggest that a clinical decision tree can be used to estimate a bacteremic patient's likelihood of infection with ESBL-producing bacteria. Recursive partitioning offers a practical, user-friendly approach for addressing important diagnostic questions. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

Moving beyond the "male perpetrator, female victim" discourse in addressing sex and relationships for HIV prevention: peer research in Eastern Zambia.

PubMed

Heslop, Jo; Banda, Rabecca

2013-05-01

Despite the resources put into HIV education programmes with young people in sub-Saharan Africa in the past two decades, there is little clear evidence of impact. Many programmes continue to be oriented towards individual behaviour change (and in reality, often sexual abstinence) with insufficient focus on understanding how societies constrain or enable individual agency in sexual decision-making and how this is affected by social norms. If education programmes do address gender they often reinforce a "male perpetrator, female victim" discourse, where girls and women are held responsible for boys' and men's sexuality as well as their own. This paper discusses the discourses around gender, sexuality and HIV constructed by young women and men (aged 16-29) in a rural Eastern Zambia village. Data on young women's and men's narratives were gathered using a participatory peer approach. Research uncovered numerous and sometimes conflicting discourses (cultural, moral, economic, and sexual) influencing young women's and men's thinking about sexuality and sexual behaviour, in particular the limited possibilities for safe consensual sex, and thus their vulnerability to HIV. The research suggests that the realities young people face are much more complex than HIV prevention strategies address. We recommend a more nuanced approach, tailored to the community contexts involved. Copyright © 2013 Reproductive Health Matters. Published by Elsevier Ltd. All rights reserved.

North-South Corridor Demonstration Project: Ethical and Logistical Challenges in the Design of a Demonstration Study of Early Antiretroviral Treatment for Long Distance Truck Drivers along a Transport Corridor through South Africa, Zimbabwe, and Zambia

PubMed Central

Gomez, G. B.; Venter, W. D. F.; Lange, J. M. A.; Rees, H.; Hankins, C.

2013-01-01

Background. Long-distance truck drivers are at risk of acquiring and transmitting HIV and have suboptimal access to care. New HIV prevention strategies using antiretroviral drugs to reduce transmission risk (early antiretroviral therapy (ART) at CD4 count >350 cells/μL) have shown efficacy in clinical trials. Demonstration projects are needed to evaluate “real world” programme effectiveness. We present the protocol for a demonstration study to evaluate the feasibility, acceptability, and cost of an early ART intervention for HIV-positive truck drivers along a transport corridor across South Africa, Zimbabwe, and Zambia, as part of an enhanced strategy to improve treatment adherence and retention in care. Methods and Analysis. This demonstration study would follow an observational cohort of truck drivers receiving early treatment. Our mixed methods approach includes quantitative, qualitative, and economic analyses. Key ethical and logistical issues are discussed (i.e., choice of drug regimen, recruitment of participants, and monitoring of adherence, behavioural changes, and adverse events). Conclusion. Questions specific to the design of tailored early ART programmes are amenable to operational research approaches but present substantial ethical and logistical challenges. Addressing these in demonstration projects can inform policy decisions regarding strategies to reduce health inequalities in access to HIV prevention and treatment programmes. PMID:23606977

Fire management assessment of Eastern Province, Zambia

Treesearch

L. T. Hollingsworth; D. Johnson; G. Sikaundi; S. Siame

2015-01-01

The mission that produced this assessment was prompted by requests from Forestry Department personnel in Zambia to the United States Agency for International Development (USAID) for formal fire management training. USAID contacted the United States Forest Service's (USFS) International Programs (IP) with the training request. Together, USFS, USAID, and Zambian...

Cost Sharing in Zambia's Public Universities: Prospects and Challenges

ERIC Educational Resources Information Center

Masaiti, Gift; Shen, Hong

2013-01-01

This research paper explores the concept of "cost sharing" which became more prominent in Zambia education with the advent of democratic form of governance in 1991. As a way of responding to the ever diminishing tax revenues, government through the education policy of 1996, allowed higher education institutions including public…

OUTLINE OF VOCATIONAL TRAINING IN ZAMBIA.

ERIC Educational Resources Information Center

Australian Dept. of Labour and National Service, Perth.

THE 1963 POPULATION OF ZAMBIA WAS APPROXIMATELY 3.5 MILLION. THE 8-YEAR PRIMARY EDUCATION PROGRAM IS FOLLOWED BY SECONDARY, SECONDARY TECHNICAL, AND TRADE SCHOOL OPTIONS. THERE IS AN INCREASE IN ADULT EDUCATION AT THE PRIMARY AND SECONDARY LEVELS. CRAFT AND TECHNICIAN LEVEL PROGRAMS ARE CONDUCTED AT NORTHERN TECHNICAL COLLEGE AND ITS ANCILLARY…

Linguistic Landscapes and the Sociolinguistics of Language Vitality in Multilingual Contexts of Zambia

ERIC Educational Resources Information Center

Banda, Felix; Jimaima, Hambaba

2017-01-01

The article illustrates a sociolinguistics of language vitality that accounts for "minority" and unofficial languages across multiple localities in dispersed communities of multilingual speakers of Zambia where only seven out of seventy-three indigenous languages have been designated official and "zoned" for use in specified…

Zambia: Multi-Faith Religious Education?

ERIC Educational Resources Information Center

Carmody, Brendan

2006-01-01

As countries' populations become more religiously diverse, a need to review the religious education syllabus that operates is often perceived. One such country is Zambia, which was not only traditionally religiously diverse but has become even more so with the advent of Christianity, Islam and Hinduism and other non-African faiths. This article…

Ensemble stump classifiers and gene expression signatures in lung cancer.

PubMed

Frey, Lewis; Edgerton, Mary; Fisher, Douglas; Levy, Shawn

2007-01-01

Microarray data sets for cancer tumor tissue generally have very few samples, each sample having thousands of probes (i.e., continuous variables). The sparsity of samples makes it difficult for machine learning techniques to discover probes relevant to the classification of tumor tissue. By combining data from different platforms (i.e., data sources), data sparsity is reduced, but this typically requires normalizing data from the different platforms, which can be non-trivial. This paper proposes a variant on the idea of ensemble learners to circumvent the need for normalization. To facilitate comprehension we build ensembles of very simple classifiers known as decision stumps--decision trees of one test each. The Ensemble Stump Classifier (ESC) identifies an mRNA signature having three probes and high accuracy for distinguishing between adenocarcinoma and squamous cell carcinoma of the lung across four data sets. In terms of accuracy, ESC outperforms a decision tree classifier on all four data sets, outperforms ensemble decision trees on three data sets, and simple stump classifiers on two data sets.

Study and Ranking of Determinants of Taenia solium Infections by Classification Tree Models

PubMed Central

Mwape, Kabemba E.; Phiri, Isaac K.; Praet, Nicolas; Dorny, Pierre; Muma, John B.; Zulu, Gideon; Speybroeck, Niko; Gabriël, Sarah

2015-01-01

Taenia solium taeniasis/cysticercosis is an important public health problem occurring mainly in developing countries. This work aimed to study the determinants of human T. solium infections in the Eastern province of Zambia and rank them in order of importance. A household (HH)-level questionnaire was administered to 680 HHs from 53 villages in two rural districts and the taeniasis and cysticercosis status determined. A classification tree model (CART) was used to define the relative importance and interactions between different predictor variables in their effect on taeniasis and cysticercosis. The Katete study area had a significantly higher taeniasis and cysticercosis prevalence than the Petauke area. The CART analysis for Katete showed that the most important determinant for cysticercosis infections was the number of HH inhabitants (6 to 10) and for taeniasis was the number of HH inhabitants > 6. The most important determinant in Petauke for cysticercosis was the age of head of household > 32 years and for taeniasis it was age < 55 years. The CART analysis showed that the most important determinant for both taeniasis and cysticercosis infections was the number of HH inhabitants (6 to 10) in Katete district and age in Petauke. The results suggest that control measures should target HHs with a high number of inhabitants and older individuals. PMID:25404073

Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China

PubMed Central

Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

2016-01-01

Background: In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. Methods: As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6–12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. Results: The prevalence of anemia was 12.60% with a range of 3.47%–40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. Conclusions: The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities. PMID:27174328

ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography.

PubMed

Berthon, Beatrice; Marshall, Christopher; Evans, Mererid; Spezi, Emiliano

2016-07-07

Accurate and reliable tumour delineation on positron emission tomography (PET) is crucial for radiotherapy treatment planning. PET automatic segmentation (PET-AS) eliminates intra- and interobserver variability, but there is currently no consensus on the optimal method to use, as different algorithms appear to perform better for different types of tumours. This work aimed to develop a predictive segmentation model, trained to automatically select and apply the best PET-AS method, according to the tumour characteristics. ATLAAS, the automatic decision tree-based learning algorithm for advanced segmentation is based on supervised machine learning using decision trees. The model includes nine PET-AS methods and was trained on a 100 PET scans with known true contour. A decision tree was built for each PET-AS algorithm to predict its accuracy, quantified using the Dice similarity coefficient (DSC), according to the tumour volume, tumour peak to background SUV ratio and a regional texture metric. The performance of ATLAAS was evaluated for 85 PET scans obtained from fillable and printed subresolution sandwich phantoms. ATLAAS showed excellent accuracy across a wide range of phantom data and predicted the best or near-best segmentation algorithm in 93% of cases. ATLAAS outperformed all single PET-AS methods on fillable phantom data with a DSC of 0.881, while the DSC for H&N phantom data was 0.819. DSCs higher than 0.650 were achieved in all cases. ATLAAS is an advanced automatic image segmentation algorithm based on decision tree predictive modelling, which can be trained on images with known true contour, to predict the best PET-AS method when the true contour is unknown. ATLAAS provides robust and accurate image segmentation with potential applications to radiation oncology.

The risk of disabling, surgery and reoperation in Crohn's disease - A decision tree-based approach to prognosis.

PubMed

Dias, Cláudia Camila; Pereira Rodrigues, Pedro; Fernandes, Samuel; Portela, Francisco; Ministro, Paula; Martins, Diana; Sousa, Paula; Lago, Paula; Rosa, Isadora; Correia, Luis; Moura Santos, Paula; Magro, Fernando

2017-01-01

Crohn's disease (CD) is a chronic inflammatory bowel disease known to carry a high risk of disabling and many times requiring surgical interventions. This article describes a decision-tree based approach that defines the CD patients' risk or undergoing disabling events, surgical interventions and reoperations, based on clinical and demographic variables. This multicentric study involved 1547 CD patients retrospectively enrolled and divided into two cohorts: a derivation one (80%) and a validation one (20%). Decision trees were built upon applying the CHAIRT algorithm for the selection of variables. Three-level decision trees were built for the risk of disabling and reoperation, whereas the risk of surgery was described in a two-level one. A receiver operating characteristic (ROC) analysis was performed, and the area under the curves (AUC) Was higher than 70% for all outcomes. The defined risk cut-off values show usefulness for the assessed outcomes: risk levels above 75% for disabling had an odds test positivity of 4.06 [3.50-4.71], whereas risk levels below 34% and 19% excluded surgery and reoperation with an odds test negativity of 0.15 [0.09-0.25] and 0.50 [0.24-1.01], respectively. Overall, patients with B2 or B3 phenotype had a higher proportion of disabling disease and surgery, while patients with later introduction of pharmacological therapeutic (1 months after initial surgery) had a higher proportion of reoperation. The decision-tree based approach used in this study, with demographic and clinical variables, has shown to be a valid and useful approach to depict such risks of disabling, surgery and reoperation.

Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China.

PubMed

Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

2016-05-20

In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6-12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. The prevalence of anemia was 12.60% with a range of 3.47%-40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities.

ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography

NASA Astrophysics Data System (ADS)

Berthon, Beatrice; Marshall, Christopher; Evans, Mererid; Spezi, Emiliano

2016-07-01

Accurate and reliable tumour delineation on positron emission tomography (PET) is crucial for radiotherapy treatment planning. PET automatic segmentation (PET-AS) eliminates intra- and interobserver variability, but there is currently no consensus on the optimal method to use, as different algorithms appear to perform better for different types of tumours. This work aimed to develop a predictive segmentation model, trained to automatically select and apply the best PET-AS method, according to the tumour characteristics. ATLAAS, the automatic decision tree-based learning algorithm for advanced segmentation is based on supervised machine learning using decision trees. The model includes nine PET-AS methods and was trained on a 100 PET scans with known true contour. A decision tree was built for each PET-AS algorithm to predict its accuracy, quantified using the Dice similarity coefficient (DSC), according to the tumour volume, tumour peak to background SUV ratio and a regional texture metric. The performance of ATLAAS was evaluated for 85 PET scans obtained from fillable and printed subresolution sandwich phantoms. ATLAAS showed excellent accuracy across a wide range of phantom data and predicted the best or near-best segmentation algorithm in 93% of cases. ATLAAS outperformed all single PET-AS methods on fillable phantom data with a DSC of 0.881, while the DSC for H&N phantom data was 0.819. DSCs higher than 0.650 were achieved in all cases. ATLAAS is an advanced automatic image segmentation algorithm based on decision tree predictive modelling, which can be trained on images with known true contour, to predict the best PET-AS method when the true contour is unknown. ATLAAS provides robust and accurate image segmentation with potential applications to radiation oncology.

Trees Are Terrific!

ERIC Educational Resources Information Center

Braus, Judy, Ed.

1992-01-01

Ranger Rick's NatureScope is a creative education series dedicated to inspiring in children an understanding and appreciation of the natural world while developing the skills they will need to make responsible decisions about the environment. Contents are organized into the following sections: (1) "What Makes a Tree a Tree?," including…

A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran.

PubMed

Khosravi, Khabat; Pham, Binh Thai; Chapi, Kamran; Shirzadi, Ataollah; Shahabi, Himan; Revhaug, Inge; Prakash, Indra; Tien Bui, Dieu

2018-06-15

Floods are one of the most damaging natural hazards causing huge loss of property, infrastructure and lives. Prediction of occurrence of flash flood locations is very difficult due to sudden change in climatic condition and manmade factors. However, prior identification of flood susceptible areas can be done with the help of machine learning techniques for proper timely management of flood hazards. In this study, we tested four decision trees based machine learning models namely Logistic Model Trees (LMT), Reduced Error Pruning Trees (REPT), Naïve Bayes Trees (NBT), and Alternating Decision Trees (ADT) for flash flood susceptibility mapping at the Haraz Watershed in the northern part of Iran. For this, a spatial database was constructed with 201 present and past flood locations and eleven flood-influencing factors namely ground slope, altitude, curvature, Stream Power Index (SPI), Topographic Wetness Index (TWI), land use, rainfall, river density, distance from river, lithology, and Normalized Difference Vegetation Index (NDVI). Statistical evaluation measures, the Receiver Operating Characteristic (ROC) curve, and Freidman and Wilcoxon signed-rank tests were used to validate and compare the prediction capability of the models. Results show that the ADT model has the highest prediction capability for flash flood susceptibility assessment, followed by the NBT, the LMT, and the REPT, respectively. These techniques have proven successful in quickly determining flood susceptible areas. Copyright © 2018 Elsevier B.V. All rights reserved.

Finding structure in data using multivariate tree boosting

PubMed Central

Miller, Patrick J.; Lubke, Gitta H.; McArtor, Daniel B.; Bergeman, C. S.

2016-01-01

Technology and collaboration enable dramatic increases in the size of psychological and psychiatric data collections, but finding structure in these large data sets with many collected variables is challenging. Decision tree ensembles such as random forests (Strobl, Malley, & Tutz, 2009) are a useful tool for finding structure, but are difficult to interpret with multiple outcome variables which are often of interest in psychology. To find and interpret structure in data sets with multiple outcomes and many predictors (possibly exceeding the sample size), we introduce a multivariate extension to a decision tree ensemble method called gradient boosted regression trees (Friedman, 2001). Our extension, multivariate tree boosting, is a method for nonparametric regression that is useful for identifying important predictors, detecting predictors with nonlinear effects and interactions without specification of such effects, and for identifying predictors that cause two or more outcome variables to covary. We provide the R package ‘mvtboost’ to estimate, tune, and interpret the resulting model, which extends the implementation of univariate boosting in the R package ‘gbm’ (Ridgeway et al., 2015) to continuous, multivariate outcomes. To illustrate the approach, we analyze predictors of psychological well-being (Ryff & Keyes, 1995). Simulations verify that our approach identifies predictors with nonlinear effects and achieves high prediction accuracy, exceeding or matching the performance of (penalized) multivariate multiple regression and multivariate decision trees over a wide range of conditions. PMID:27918183

Tools of the Future: How Decision Tree Analysis Will Impact Mission Planning

NASA Technical Reports Server (NTRS)

Otterstatter, Matthew R.

2005-01-01

The universe is infinitely complex; however, the human mind has a finite capacity. The multitude of possible variables, metrics, and procedures in mission planning are far too many to address exhaustively. This is unfortunate because, in general, considering more possibilities leads to more accurate and more powerful results. To compensate, we can get more insightful results by employing our greatest tool, the computer. The power of the computer will be utilized through a technology that considers every possibility, decision tree analysis. Although decision trees have been used in many other fields, this is innovative for space mission planning. Because this is a new strategy, no existing software is able to completely accommodate all of the requirements. This was determined through extensive research and testing of current technologies. It was necessary to create original software, for which a short-term model was finished this summer. The model was built into Microsoft Excel to take advantage of the familiar graphical interface for user input, computation, and viewing output. Macros were written to automate the process of tree construction, optimization, and presentation. The results are useful and promising. If this tool is successfully implemented in mission planning, our reliance on old-fashioned heuristics, an error-prone shortcut for handling complexity, will be reduced. The computer algorithms involved in decision trees will revolutionize mission planning. The planning will be faster and smarter, leading to optimized missions with the potential for more valuable data.

The use of decision trees and naïve Bayes algorithms and trace element patterns for controlling the authenticity of free-range-pastured hens' eggs.

PubMed

Barbosa, Rommel Melgaço; Nacano, Letícia Ramos; Freitas, Rodolfo; Batista, Bruno Lemos; Barbosa, Fernando

2014-09-01

This article aims to evaluate 2 machine learning algorithms, decision trees and naïve Bayes (NB), for egg classification (free-range eggs compared with battery eggs). The database used for the study consisted of 15 chemical elements (As, Ba, Cd, Co, Cs, Cu, Fe, Mg, Mn, Mo, Pb, Se, Sr, V, and Zn) determined in 52 eggs samples (20 free-range and 32 battery eggs) by inductively coupled plasma mass spectrometry. Our results demonstrated that decision trees and NB associated with the mineral contents of eggs provide a high level of accuracy (above 80% and 90%, respectively) for classification between free-range and battery eggs and can be used as an alternative method for adulteration evaluation. © 2014 Institute of Food Technologists®

Pollution mitigation and carbon sequestration by an urban forest.

PubMed

Brack, C L

2002-01-01

At the beginning of the 1900s, the Canberra plain was largely treeless. Graziers had carried out extensive clearing of the original trees since the 1820s leaving only scattered remnants and some plantings near homesteads. With the selection of Canberra as the site for the new capital of Australia, extensive tree plantings began in 1911. These trees have delivered a number of benefits, including aesthetic values and the amelioration of climatic extremes. Recently, however, it was considered that the benefits might extend to pollution mitigation and the sequestration of carbon. This paper outlines a case study of the value of the Canberra urban forest with particular reference to pollution mitigation. This study uses a tree inventory, modelling and decision support system developed to collect and use data about trees for tree asset management. The decision support system (DISMUT) was developed to assist in the management of about 400,000 trees planted in Canberra. The size of trees during the 5-year Kyoto Commitment Period was estimated using DISMUT and multiplied by estimates of value per square meter of canopy derived from available literature. The planted trees are estimated to have a combined energy reduction, pollution mitigation and carbon sequestration value of US$20-67 million during the period 2008-2012.

Using real options analysis to support strategic management decisions

NASA Astrophysics Data System (ADS)

Kabaivanov, Stanimir; Markovska, Veneta; Milev, Mariyan

2013-12-01

Decision making is a complex process that requires taking into consideration multiple heterogeneous sources of uncertainty. Standard valuation and financial analysis techniques often fail to properly account for all these sources of risk as well as for all sources of additional flexibility. In this paper we explore applications of a modified binomial tree method for real options analysis (ROA) in an effort to improve decision making process. Usual cases of use of real options are analyzed with elaborate study on the applications and advantages that company management can derive from their application. A numeric results based on extending simple binomial tree approach for multiple sources of uncertainty are provided to demonstrate the improvement effects on management decisions.

Attitudes toward abortion in Zambia.

PubMed

Geary, Cynthia Waszak; Gebreselassie, Hailemichael; Awah, Paschal; Pearson, Erin

2012-09-01

Despite Zambia's relatively progressive abortion law, women continue to seek unsafe, illegal abortions. Four domains of abortion attitudes - support for legalization, immorality, rights, and access to services - were measured in 4 communities. A total of 668 people were interviewed. Associations among the 4 domains were inconsistent with expectations. The belief that abortion is immoral was widespread, but was not associated with lack of support for legalization. Instead, it was associated with belief that women need access to safe services. These findings suggest that increasing awareness about abortion law in Zambia may be important for encouraging more favorable attitudes. Copyright © 2012 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

Health worker shortages in Zambia: an assessment of government responses.

PubMed

Gow, Jeff; George, Gavin; Mutinta, Given; Mwamba, Sylvia; Ingombe, Lutungu

2011-11-01

A dire health worker shortage in Zambia's national health programs is adversely impacting the quantity and quality of health care and posing a serious barrier to achieving Millennium Development Goals to improve population health. In 2005, Zambia's Ministry of Health developed a 10-year strategic plan for human resources for health to address the crisis through improved training, hiring, and retention. The plan has neither arrested nor reduced the shortage. We review the causes of the shortage, present results from a health worker survey showing that safe work conditions, manageable workloads, and career advancement opportunities matter more to respondents than financial compensation. We comment on the adequacy of government efforts to address the health worker shortage.

Improving ensemble decision tree performance using Adaboost and Bagging

NASA Astrophysics Data System (ADS)

Hasan, Md. Rajib; Siraj, Fadzilah; Sainin, Mohd Shamrie

2015-12-01

Ensemble classifier systems are considered as one of the most promising in medical data classification and the performance of deceision tree classifier can be increased by the ensemble method as it is proven to be better than single classifiers. However, in a ensemble settings the performance depends on the selection of suitable base classifier. This research employed two prominent esemble s namely Adaboost and Bagging with base classifiers such as Random Forest, Random Tree, j48, j48grafts and Logistic Model Regression (LMT) that have been selected independently. The empirical study shows that the performance varries when different base classifiers are selected and even some places overfitting issue also been noted. The evidence shows that ensemble decision tree classfiers using Adaboost and Bagging improves the performance of selected medical data sets.

Knowledge Quality Functions for Rule Discovery

DTIC Science & Technology

1994-09-01

Managers in many organizations finding themselves in the possession of large and rapidly growing databases are beginning to suspect the information in their...missing values (Smyth and Goodman, 1992, p. 303). Decision trees "tend to grow very large for realistic applications and are thus difficult to interpret...by humans" (Holsheimer, 1994, p. 42). Decision trees also grow excessively complicated in the presence of noisy databases (Dhar and Tuzhilin, 1993, p

Structural Equation Model Trees

ERIC Educational Resources Information Center

Brandmaier, Andreas M.; von Oertzen, Timo; McArdle, John J.; Lindenberger, Ulman

2013-01-01

In the behavioral and social sciences, structural equation models (SEMs) have become widely accepted as a modeling tool for the relation between latent and observed variables. SEMs can be seen as a unification of several multivariate analysis techniques. SEM Trees combine the strengths of SEMs and the decision tree paradigm by building tree…

a Rough Set Decision Tree Based Mlp-Cnn for Very High Resolution Remotely Sensed Image Classification

NASA Astrophysics Data System (ADS)

Zhang, C.; Pan, X.; Zhang, S. Q.; Li, H. P.; Atkinson, P. M.

2017-09-01

Recent advances in remote sensing have witnessed a great amount of very high resolution (VHR) images acquired at sub-metre spatial resolution. These VHR remotely sensed data has post enormous challenges in processing, analysing and classifying them effectively due to the high spatial complexity and heterogeneity. Although many computer-aid classification methods that based on machine learning approaches have been developed over the past decades, most of them are developed toward pixel level spectral differentiation, e.g. Multi-Layer Perceptron (MLP), which are unable to exploit abundant spatial details within VHR images. This paper introduced a rough set model as a general framework to objectively characterize the uncertainty in CNN classification results, and further partition them into correctness and incorrectness on the map. The correct classification regions of CNN were trusted and maintained, whereas the misclassification areas were reclassified using a decision tree with both CNN and MLP. The effectiveness of the proposed rough set decision tree based MLP-CNN was tested using an urban area at Bournemouth, United Kingdom. The MLP-CNN, well capturing the complementarity between CNN and MLP through the rough set based decision tree, achieved the best classification performance both visually and numerically. Therefore, this research paves the way to achieve fully automatic and effective VHR image classification.

A retrospective analysis to identify the factors affecting infection in patients undergoing chemotherapy.

PubMed

Park, Ji Hyun; Kim, Hyeon-Young; Lee, Hanna; Yun, Eun Kyoung

2015-12-01

This study compares the performance of the logistic regression and decision tree analysis methods for assessing the risk factors for infection in cancer patients undergoing chemotherapy. The subjects were 732 cancer patients who were receiving chemotherapy at K university hospital in Seoul, Korea. The data were collected between March 2011 and February 2013 and were processed for descriptive analysis, logistic regression and decision tree analysis using the IBM SPSS Statistics 19 and Modeler 15.1 programs. The most common risk factors for infection in cancer patients receiving chemotherapy were identified as alkylating agents, vinca alkaloid and underlying diabetes mellitus. The logistic regression explained 66.7% of the variation in the data in terms of sensitivity and 88.9% in terms of specificity. The decision tree analysis accounted for 55.0% of the variation in the data in terms of sensitivity and 89.0% in terms of specificity. As for the overall classification accuracy, the logistic regression explained 88.0% and the decision tree analysis explained 87.2%. The logistic regression analysis showed a higher degree of sensitivity and classification accuracy. Therefore, logistic regression analysis is concluded to be the more effective and useful method for establishing an infection prediction model for patients undergoing chemotherapy. Copyright © 2015 Elsevier Ltd. All rights reserved.

MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

NASA Technical Reports Server (NTRS)

Riggs, George A.; Hall, Dorothy K.

2010-01-01

Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

hs-CRP is strongly associated with coronary heart disease (CHD): A data mining approach using decision tree algorithm.

PubMed

Tayefi, Maryam; Tajfard, Mohammad; Saffar, Sara; Hanachi, Parichehr; Amirabadizadeh, Ali Reza; Esmaeily, Habibollah; Taghipour, Ali; Ferns, Gordon A; Moohebati, Mohsen; Ghayour-Mobarhan, Majid

2017-04-01

Coronary heart disease (CHD) is an important public health problem globally. Algorithms incorporating the assessment of clinical biomarkers together with several established traditional risk factors can help clinicians to predict CHD and support clinical decision making with respect to interventions. Decision tree (DT) is a data mining model for extracting hidden knowledge from large databases. We aimed to establish a predictive model for coronary heart disease using a decision tree algorithm. Here we used a dataset of 2346 individuals including 1159 healthy participants and 1187 participant who had undergone coronary angiography (405 participants with negative angiography and 782 participants with positive angiography). We entered 10 variables of a total 12 variables into the DT algorithm (including age, sex, FBG, TG, hs-CRP, TC, HDL, LDL, SBP and DBP). Our model could identify the associated risk factors of CHD with sensitivity, specificity, accuracy of 96%, 87%, 94% and respectively. Serum hs-CRP levels was at top of the tree in our model, following by FBG, gender and age. Our model appears to be an accurate, specific and sensitive model for identifying the presence of CHD, but will require validation in prospective studies. Copyright © 2017 Elsevier B.V. All rights reserved.

A Comparison between Decision Tree and Random Forest in Determining the Risk Factors Associated with Type 2 Diabetes.

PubMed

Esmaily, Habibollah; Tayefi, Maryam; Doosti, Hassan; Ghayour-Mobarhan, Majid; Nezami, Hossein; Amirabadizadeh, Alireza

2018-04-24

We aimed to identify the associated risk factors of type 2 diabetes mellitus (T2DM) using data mining approach, decision tree and random forest techniques using the Mashhad Stroke and Heart Atherosclerotic Disorders (MASHAD) Study program. A cross-sectional study. The MASHAD study started in 2010 and will continue until 2020. Two data mining tools, namely decision trees, and random forests, are used for predicting T2DM when some other characteristics are observed on 9528 subjects recruited from MASHAD database. This paper makes a comparison between these two models in terms of accuracy, sensitivity, specificity and the area under ROC curve. The prevalence rate of T2DM was 14% among these subjects. The decision tree model has 64.9% accuracy, 64.5% sensitivity, 66.8% specificity, and area under the ROC curve measuring 68.6%, while the random forest model has 71.1% accuracy, 71.3% sensitivity, 69.9% specificity, and area under the ROC curve measuring 77.3% respectively. The random forest model, when used with demographic, clinical, and anthropometric and biochemical measurements, can provide a simple tool to identify associated risk factors for type 2 diabetes. Such identification can substantially use for managing the health policy to reduce the number of subjects with T2DM .

Distance Learners' Perspective on User-Friendly Instructional Materials at the University of Zambia

ERIC Educational Resources Information Center

Simui, F.; Thompson, L. C.; Mundende, K.; Mwewa, G.; Kakana, F.; Chishiba, A.; Namangala, B.

2017-01-01

This case study focuses on print-based instructional materials available to distance education learners at the University of Zambia. Using the Visual Paradigm Software, we model distance education learners' voices into sociograms to make a contribution to the ongoing discourse on quality distance learning in poorly resourced communities. Emerging…

Deschooling Language Study in East Africa: The Zambia Plan.

ERIC Educational Resources Information Center

Roberts, David Harrill

The second language learning methods of Southern Baptist missionaries in Zambia are described. Instead of studying the new language in a school setting, the student receives a week of orientation and is then placed in the community and expected to practice communicating with the native speakers at every opportunity. The student follows a course…

Information Provision in Emergency Settings: The Experience of Refugee Communities in Zambia

ERIC Educational Resources Information Center

Kanyengo, Brendah Kakulwa; Kanyengo, Christine Wamunyima

2011-01-01

This article identifies information provision services in emergency settings using Zambia as a case study by identifying innovative ways of providing library and information services. The thrust of the article is to analyze information management practices of organizations that work within refugee camps and how they take specific cognizance of the…

Organization of Distance Education at the University of Zambia: An Analysis of the Practice.

ERIC Educational Resources Information Center

Nyirenda, Juma E.

1989-01-01

Discussion of two basic organizational models for distance education systems or institutions focuses on the mixed-mode organization at the University of Zambia. Highlights include the development, production, storage, and distribution of teaching materials; communication channels between students and teachers; and the record-keeping system. (11…

Early Childhood Care and Education in Zambia: An Integral Part of Educational Provision?

ERIC Educational Resources Information Center

Thomas, Carolyn M.; Thomas, Matthew A. M.

2009-01-01

The field of international development has recently been consumed by a shift in contemporary educational discourse, one that moves Early Childhood Care and Education (ECCE) closer to the forefront of what is considered progressive policy formation. In Zambia, the current educational environment seems to indicate that the creation and continued…

Zambian Pre-Service Teachers' Voices about Successful Inclusive Education

ERIC Educational Resources Information Center

Muwana, Florence C.; Ostrosky, Michaelene M.

2014-01-01

While inclusion has been studied in many parts of the world, there is a dearth of research on this topic in Zambia. This study investigated the perceptions of pre-service teachers about the benefits of inclusion and the resources needed to successfully include students with disabilities in general education settings in Zambia. Participants…

Inquiry-Based Science Education: A Scenario on Zambia's High School Science Curriculum

ERIC Educational Resources Information Center

Chabalengula, Vivien M.; Mumba, Frackson

2012-01-01

This paper is aimed at elucidating the current state of inquiry-based science education (IBSE) in Zambia's high school science curriculum. Therefore, we investigated Zambian teachers' conceptions of inquiry; determined inquiry levels in the national high school science curriculum materials, which include syllabi, textbooks and practical exams; and…

Conceptualising Education Quality in Zambia: A Comparative Analysis across the Local, National and Global Discourses

ERIC Educational Resources Information Center

Lee, Jeongmin; Zuilkowski, Stephanie Simmons

2017-01-01

Building on the Education for All movement, the 2030 Agenda for Sustainable Development re-emphasises quality education as a discrete goal. Contextualising the discussion surrounding this goal in Zambia, this study examines how education quality is conceptualised by educational stakeholders at local, national, and global levels. Triangulating…

Mycobacterium bovis infection at the interface between domestic and wild animals in Zambia.

PubMed

Hang'ombe, Mudenda B; Munyeme, Musso; Nakajima, Chie; Fukushima, Yukari; Suzuki, Haruka; Matandiko, Wigganson; Ishii, Akihiro; Mweene, Aaron S; Suzuki, Yasuhiko

2012-11-14

In Zambia, the presence of bovine tuberculosis in both wild and domestic animals has long been acknowledged and mutual transmission between them has been predicted without any direct evidence. Elucidation of the circulating Mycobacterium bovis strains at wild and domestic animals interphase area in Zambia, where bovine tuberculosis was diagnosed in wildlife seemed to be important. A PCR identified 15 and 37 M. bovis isolates from lechwe and cattle, respectively. Spoligotype analysis revealed that M. bovis strains from lechwe and cattle in Kafue basin clustered into a major node SB0120, where isolates outside the Kafue basin clustered into different nodes of SB0131 and SB0948. The comparatively higher variety of strains in cattle compared to lechwe elucidated by Mycobacterial Interspersed Repetitive Units-Variable Number Tandem Repeats analyses are consistent with cattle being the probable source of M. bovis in wild and domestic animals interphase area in Zambia. These results provide strong evidence of M. bovis strains transfer between cattle and lechwe, with the latter having developed into a sylvatic reservoir host.

Mycobacterium bovis infection at the interface between domestic and wild animals in Zambia

PubMed Central

2012-01-01

Background In Zambia, the presence of bovine tuberculosis in both wild and domestic animals has long been acknowledged and mutual transmission between them has been predicted without any direct evidence. Elucidation of the circulating Mycobacterium bovis strains at wild and domestic animals interphase area in Zambia, where bovine tuberculosis was diagnosed in wildlife seemed to be important. Results A PCR identified 15 and 37 M. bovis isolates from lechwe and cattle, respectively. Spoligotype analysis revealed that M. bovis strains from lechwe and cattle in Kafue basin clustered into a major node SB0120, where isolates outside the Kafue basin clustered into different nodes of SB0131 and SB0948. The comparatively higher variety of strains in cattle compared to lechwe elucidated by Mycobacterial Interspersed Repetitive Units–Variable Number Tandem Repeats analyses are consistent with cattle being the probable source of M. bovis in wild and domestic animals interphase area in Zambia. Conclusions These results provide strong evidence of M. bovis strains transfer between cattle and lechwe, with the latter having developed into a sylvatic reservoir host. PMID:23151267

Diagnosis and genotyping of African swine fever viruses from 2015 outbreaks in Zambia.

PubMed

Thoromo, Jonas; Simulundu, Edgar; Chambaro, Herman M; Mataa, Liywalii; Lubaba, Caesar H; Pandey, Girja S; Takada, Ayato; Misinzo, Gerald; Mweene, Aaron S

2016-04-29

In early 2015, a highly fatal haemorrhagic disease of domestic pigs resembling African swine fever (ASF) occurred in North Western, Copperbelt, and Lusaka provinces of Zambia. Molecular diagnosis by polymerase chain reaction targeting specific amplification of p72 (B646L) gene of ASF virus (ASFV) was conducted. Fourteen out of 16 domestic pigs from the affected provinces were found to be positive for ASFV. Phylogenetic analyses based on part of the p72 and the complete p54 (E183L) genes revealed that all the ASFVs detected belonged to genotypes I and Id, respectively. Additionally, epidemiological data suggest that the same ASFV spread from Lusaka to other provinces possibly through uncontrolled and/or illegal pig movements. Although the origin of the ASFV that caused outbreaks in domestic pigs in Zambia could not be ascertained, it appears likely that the virus may have emerged from within the country or region, probably from a sylvatic cycle. It is recommended that surveillance of ASF, strict biosecurity, and quarantine measures be imposed in order to prevent further spread and emergence of new ASF outbreaks in Zambia.

Environmental justice and factors that influence participation in tree planting programs in Portland, Oregon, U.S

Treesearch

Geoffrey H. Donovan; John Mills

2014-01-01

Many cities have policies encouraging homeowners to plant trees. For these policies to be effective, it is important to understand what motivates a homeowner’s tree-planting decision. Researchers address this question by identifying variables that influence participation in a tree-planting program in Portland, Oregon, U.S. According to the study, homeowners with street...

Decision Tree Algorithm-Generated Single-Nucleotide Polymorphism Barcodes of rbcL Genes for 38 Brassicaceae Species Tagging.

PubMed

Yang, Cheng-Hong; Wu, Kuo-Chuan; Chuang, Li-Yeh; Chang, Hsueh-Wei

2018-01-01

DNA barcode sequences are accumulating in large data sets. A barcode is generally a sequence larger than 1000 base pairs and generates a computational burden. Although the DNA barcode was originally envisioned as straightforward species tags, the identification usage of barcode sequences is rarely emphasized currently. Single-nucleotide polymorphism (SNP) association studies provide us an idea that the SNPs may be the ideal target of feature selection to discriminate between different species. We hypothesize that SNP-based barcodes may be more effective than the full length of DNA barcode sequences for species discrimination. To address this issue, we tested a r ibulose diphosphate carboxylase ( rbcL ) S NP b arcoding (RSB) strategy using a decision tree algorithm. After alignment and trimming, 31 SNPs were discovered in the rbcL sequences from 38 Brassicaceae plant species. In the decision tree construction, these SNPs were computed to set up the decision rule to assign the sequences into 2 groups level by level. After algorithm processing, 37 nodes and 31 loci were required for discriminating 38 species. Finally, the sequence tags consisting of 31 rbcL SNP barcodes were identified for discriminating 38 Brassicaceae species based on the decision tree-selected SNP pattern using RSB method. Taken together, this study provides the rational that the SNP aspect of DNA barcode for rbcL gene is a useful and effective sequence for tagging 38 Brassicaceae species.

Kernel and divergence techniques in high energy physics separations

NASA Astrophysics Data System (ADS)

Bouř, Petr; Kůs, Václav; Franc, Jiří

2017-10-01

Binary decision trees under the Bayesian decision technique are used for supervised classification of high-dimensional data. We present a great potential of adaptive kernel density estimation as the nested separation method of the supervised binary divergence decision tree. Also, we provide a proof of alternative computing approach for kernel estimates utilizing Fourier transform. Further, we apply our method to Monte Carlo data set from the particle accelerator Tevatron at DØ experiment in Fermilab and provide final top-antitop signal separation results. We have achieved up to 82 % AUC while using the restricted feature selection entering the signal separation procedure.

Disease constraints for utilization of the African buffalo (Syncerus caffer) on game ranches in Zambia.

PubMed

Munang'andu, Hetron M; Munag'andu, Hetron M; Siamudaala, Victor M; Nambota, Andrew; Bwalya, John M; Munyeme, Musso; Mweene, Aaron S; Takada, Ayato; Kida, Hiroshi

2006-05-01

Eco-tourism depending on wildlife is becoming increasingly profitable and landowners are beginning to favor game farming and ecotourism. In these areas, large-scale translocation of wildlife involves a diversity of species and large populations. The African buffalo (Syncerus caffer) is one of the major tourist attractions in Zambia. It accounts for 8.7% and 12.4% of the total animal species hunted in the Game Management Areas and the total hunting revenue earned in Zambia, respectively. It is ecologically an important animal species essential for the purpose of habitat control and facilitating the provision of suitable grazing pastures. However, the rearing of the African buffalo on game ranches has been hampered by its carrier state of the Southern Africa Terroritory (SAT) serotypes of foot and mouth disease virus (FMD). The African buffalo is also known to be a carrier of Theileria parva lawrencei, the causative agent of corridor disease (CD) that continues to have devastating effects on the livestock industry in Zambia. In addition, the importation of buffaloes from countries with populations endemic to bovine tuberculosis is highly restricted. Veterinary regulations in Zambia, strongly advocate against the translocation of buffaloes from protected areas to private ranches for disease control purposes thereby mounting a considerable constraint on the economic and ecological viability of the industry. It is hoped that this review will motivate the relevant government authorities in exploiting ways in which this animal species play a central role in eco-tourism.

Ethnoveterinary treatments for common cattle diseases in four districts of the Southern Province, Zambia.

PubMed

Syakalima, Michelo; Simuunza, Martin; Zulu, Victor Chisha

2018-02-01

Ethno veterinary knowledge has rarely been recorded, and no or limited effort has been made to exploit this knowledge despite its widespread use in Zambia. This study documented the types of plants used to treat important animal diseases in rural Zambia as a way of initiating their sustained documentation and scientific validation. The study was done in selected districts of the Southern Zambia, Africa. The research was a participatory epidemiological study conducted in two phases. The first phase was a pre-study exploratory rapid rural appraisal conducted to familiarize the researchers with the study areas, and the second phase was a participatory rural appraisal to help gather the data. The frequency index was used to rank the commonly mentioned treatments. A number of diseases and traditional treatments were listed with the help of local veterinarians. Diseases included: Corridor disease (Theileriosis), foot and mouth disease, blackleg, bloody diarrhea, lumpy skin disease, fainting, mange, blindness, coughing, bloat, worms, cobra snakebite, hemorrhagic septicemia, and transmissible venereal tumors. The plant preparations were in most diseases given to the livestock orally (as a drench). Leaves, barks, and roots were generally used depending on the plant type. Ethno veterinary medicine is still widespread among the rural farmers in the province and in Zambia in general. Some medicines are commonly used across diseases probably because they have a wide spectrum of action. These medicines should, therefore, be validated for use in conventional livestock healthcare systems in the country to reduce the cost of treatments.

A divide and conquer approach to cope with uncertainty, human health risk, and decision making in contaminant hydrology

NASA Astrophysics Data System (ADS)

de Barros, Felipe P. J.; Bolster, Diogo; Sanchez-Vila, Xavier; Nowak, Wolfgang

2011-05-01

Assessing health risk in hydrological systems is an interdisciplinary field. It relies on the expertise in the fields of hydrology and public health and needs powerful translation concepts to provide decision support and policy making. Reliable health risk estimates need to account for the uncertainties and variabilities present in hydrological, physiological, and human behavioral parameters. Despite significant theoretical advancements in stochastic hydrology, there is still a dire need to further propagate these concepts to practical problems and to society in general. Following a recent line of work, we use fault trees to address the task of probabilistic risk analysis and to support related decision and management problems. Fault trees allow us to decompose the assessment of health risk into individual manageable modules, thus tackling a complex system by a structural divide and conquer approach. The complexity within each module can be chosen individually according to data availability, parsimony, relative importance, and stage of analysis. Three differences are highlighted in this paper when compared to previous works: (1) The fault tree proposed here accounts for the uncertainty in both hydrological and health components, (2) system failure within the fault tree is defined in terms of risk being above a threshold value, whereas previous studies that used fault trees used auxiliary events such as exceedance of critical concentration levels, and (3) we introduce a new form of stochastic fault tree that allows us to weaken the assumption of independent subsystems that is required by a classical fault tree approach. We illustrate our concept in a simple groundwater-related setting.

The reach and impact of social marketing and reproductive health communication campaigns in Zambia

PubMed Central

Van Rossem, Ronan; Meekers, Dominique

2007-01-01

Background Like many sub-Saharan African countries, Zambia is dealing with major health issues, including HIV/AIDS, family planning, and reproductive health. To address reproductive health problems and the HIV/AIDS epidemic in Zambia, several social marketing and health communication programs focusing on reproductive and HIV/AIDS prevention programs are being implemented. This paper describes the reach of these programs and assesses their impact on condom use. Methods This paper assesses the reach of selected radio and television programs about family planning and HIV/AIDS and of communications about the socially marketed Maximum condoms in Zambia, as well as their impact on condom use, using data from the 2001–2002 Zambia Demographic and Health Survey. To control for self-selection and endogeneity, we use a two-stage regression model to estimate the effect of program exposure on the behavioural outcomes. Results Those who were exposed to radio and television programs about family planning and HIV/AIDS were more likely to have ever used a condom (OR = 1.16 for men and 1.06 for women). Men highly exposed to Maximum condoms social marketing communication were more likely than those with low exposure to the program to have ever used a condom (OR = 1.48), and to have used a condom at their last sexual intercourse (OR = 1.23). Conclusion Findings suggest that the reproductive health and social marketing campaigns in Zambia reached a large portion of the population and had a significant impact on condom use. The results suggest that future reproductive health communication campaigns that invest in radio programming may be more effective than those investing in television programming, and that future campaigns should seek to increase their impact among women, perhaps by focusing on the specific constrains that prevent females from using condoms. PMID:18088437

Underutilisation of routinely collected data in the HIV programme in Zambia: a review of quantitatively analysed peer-reviewed articles.

PubMed

Munthali, Tendai; Musonda, Patrick; Mee, Paul; Gumede, Sehlulekile; Schaap, Ab; Mwinga, Alwyn; Phiri, Caroline; Kapata, Nathan; Michelo, Charles; Todd, Jim

2017-06-13

The extent to which routinely collected HIV data from Zambia has been used in peer-reviewed published articles remains unexplored. This paper is an analysis of peer-reviewed articles that utilised routinely collected HIV data from Zambia within six programme areas from 2004 to 2014. Articles on HIV, published in English, listed in the Directory of open access journals, African Journals Online, Google scholar, and PubMed were reviewed. Only articles from peer-reviewed journals, that utilised routinely collected data and included quantitative data analysis methods were included. Multi-country studies involving Zambia and another country, where the specific results for Zambia were not reported, as well as clinical trials and intervention studies that did not take place under routine care conditions were excluded, although community trials which referred patients to the routine clinics were included. Independent extraction was conducted using a predesigned data collection form. Pooled analysis was not possible due to diversity in topics reviewed. A total of 69 articles were extracted for review. Of these, 7 were excluded. From the 62 articles reviewed, 39 focused on HIV treatment and retention in care, 15 addressed prevention of mother-to-child transmission, 4 assessed social behavioural change, and 4 reported on voluntary counselling and testing. In our search, no articles were found on condom programming or voluntary male medical circumcision. The most common outcome measures reported were CD4+ count, clinical failure or mortality. The population analysed was children in 13 articles, women in 16 articles, and both adult men and women in 33 articles. During the 10 year period of review, only 62 articles were published analysing routinely collected HIV data in Zambia. Serious consideration needs to be made to maximise the utility of routinely collected data, and to benefit from the funds and efforts to collect these data. This could be achieved with government support of operational research and publication of findings based on routinely collected Zambian HIV data.

Developing a community driven sustainable model of maternity waiting homes for rural Zambia.

PubMed

Lori, Jody R; Munro-Kramer, Michelle L; Mdluli, Eden Ahmed; Musonda Mrs, Gertrude K; Boyd, Carol J

2016-10-01

maternity waiting homes (MWHs) are residential dwellings located near health facilities where women in the late stages of pregnancy stay to await childbirth and receive immediate postpartum services. These shelters help overcome distance and transportation barriers that prevent women from receiving timely skilled obstetric care. the purpose of this study was to explore Zambian stakeholders' beliefs regarding the acceptability, feasibility, and sustainability of maternity waiting homes (MWHs) to inform a model for rural Zambia. a qualitative design using a semi-structured interview guide for data collection was used. two rural districts in the Eastern province of Zambia. individual interviews were conducted with community leaders (n=46). Focus groups were held with Safe Motherhood Action Groups, husbands, and women of childbearing age in two rural districts in Zambia (n=500). latent content analysis was used to analyze the data. participants were overwhelmingly in support of MWHs as a way to improve access to facility-based childbirth and address the barrier of distance. Data suggest that participants can describe features of high quality care, and the type of care they expect from a MWH. Stakeholders acknowledged the need to contribute to the maintenance of the MWH, and that community involvement was crucial to MWH sustainability. access to facility childbirth remains particularly challenging in rural Zambia and delays in seeking care exist. Maternity waiting homes offer a feasible and acceptable intervention to reduce delays in seeking care, thereby holding the potential to improve maternal outcomes. this study joins a growing literature on the acceptability, feasibility, and sustainability of MWHs. It is believed that MWHs, by addressing the distance and transportation barriers, will increase the use of skilled birth attendants, thereby reducing maternal and neonatal morbidity and mortality in rural, low resource areas of Zambia. We recommend that any initiative, such as MWHs, seeking to increase facility-based births with a skilled birth attendant also concurrently addresses any local deficiencies in quality of care. Copyright © 2016 Elsevier Ltd. All rights reserved.

Automated diagnosis of coronary artery disease based on data mining and fuzzy modeling.

PubMed

Tsipouras, Markos G; Exarchos, Themis P; Fotiadis, Dimitrios I; Kotsia, Anna P; Vakalis, Konstantinos V; Naka, Katerina K; Michalis, Lampros K

2008-07-01

A fuzzy rule-based decision support system (DSS) is presented for the diagnosis of coronary artery disease (CAD). The system is automatically generated from an initial annotated dataset, using a four stage methodology: 1) induction of a decision tree from the data; 2) extraction of a set of rules from the decision tree, in disjunctive normal form and formulation of a crisp model; 3) transformation of the crisp set of rules into a fuzzy model; and 4) optimization of the parameters of the fuzzy model. The dataset used for the DSS generation and evaluation consists of 199 subjects, each one characterized by 19 features, including demographic and history data, as well as laboratory examinations. Tenfold cross validation is employed, and the average sensitivity and specificity obtained is 62% and 54%, respectively, using the set of rules extracted from the decision tree (first and second stages), while the average sensitivity and specificity increase to 80% and 65%, respectively, when the fuzzification and optimization stages are used. The system offers several advantages since it is automatically generated, it provides CAD diagnosis based on easily and noninvasively acquired features, and is able to provide interpretation for the decisions made.

Re-Construction of Reference Population and Generating Weights by Decision Tree

DTIC Science & Technology

2017-07-21

2017 Claflin University Orangeburg, SC 29115 DEFENSE EQUAL OPPORTUNITY MANAGEMENT INSTITUTE RESEARCH, DEVELOPMENT, AND STRATEGIC...Original Dataset 32 List of Figures in Appendix B Figure 1: Flow and Components of Project 20 Figure 2: Decision Tree 31 Figure 3: Effects of Weight...can compare the sample data. The dataset of this project has the reference population on unit level for group and gender, which is in red-dotted box

An Approach for Implementing a Microcomputer Based Report Origination System in the Ada Programming Language

DTIC Science & Technology

1983-03-01

Decision Tree -------------------- 62 4-E. PACKAGE unitrep Action/Area Selection flow Chart 82 4-7. PACKAGE unitrep Control Flow Chart...the originetor wculd manually draft simple, readable, formatted iressages using "-i predef.ined forms and decision logic trees . This alternative was...Study Analysis DATA CCNTENT ERRORS PERCENT OF ERRORS Character Type 2.1 Calcvlations/Associations 14.3 Message Identification 4.? Value Pisiratch 22.E

Method and apparatus for detecting a desired behavior in digital image data

DOEpatents

Kegelmeyer, Jr., W. Philip

1997-01-01

A method for detecting stellate lesions in digitized mammographic image data includes the steps of prestoring a plurality of reference images, calculating a plurality of features for each of the pixels of the reference images, and creating a binary decision tree from features of randomly sampled pixels from each of the reference images. Once the binary decision tree has been created, a plurality of features, preferably including an ALOE feature (analysis of local oriented edges), are calculated for each of the pixels of the digitized mammographic data. Each of these plurality of features of each pixel are input into the binary decision tree and a probability is determined, for each of the pixels, corresponding to the likelihood of the presence of a stellate lesion, to create a probability image. Finally, the probability image is spatially filtered to enforce local consensus among neighboring pixels and the spatially filtered image is output.

Method and apparatus for detecting a desired behavior in digital image data

DOEpatents

Kegelmeyer, Jr., W. Philip

1997-01-01

A method for detecting stellate lesions in digitized mammographic image data includes the steps of prestoring a plurality of reference images, calculating a plurality of features for each of the pixels of the reference images, and creating a binary decision tree from features of randomly sampled pixels from each of the reference images. Once the binary decision tree has been created, a plurality of features, preferably including an ALOE feature (analysis of local oriented edges), are calculated for each of the pixels of the digitized mammographic data. Each of these plurality of features of each pixel are input into the binary decision tree and a probability is determined, for each of the pixels, corresponding to the likelihood of the presence of a stellate lesion, to create a probability image. Finally, the probability image is spacially filtered to enforce local consensus among neighboring pixels and the spacially filtered image is output.

Identification of Potential Sources of Mercury (Hg) in Farmland Soil Using a Decision Tree Method in China.

PubMed

Zhong, Taiyang; Chen, Dongmei; Zhang, Xiuying

2016-11-09

Identification of the sources of soil mercury (Hg) on the provincial scale is helpful for enacting effective policies to prevent further contamination and take reclamation measurements. The natural and anthropogenic sources and their contributions of Hg in Chinese farmland soil were identified based on a decision tree method. The results showed that the concentrations of Hg in parent materials were most strongly associated with the general spatial distribution pattern of Hg concentration on a provincial scale. The decision tree analysis gained an 89.70% total accuracy in simulating the influence of human activities on the additions of Hg in farmland soil. Human activities-for example, the production of coke, application of fertilizers, discharge of wastewater, discharge of solid waste, and the production of non-ferrous metals-were the main external sources of a large amount of Hg in the farmland soil.

A Hybrid Approach of Stepwise Regression, Logistic Regression, Support Vector Machine, and Decision Tree for Forecasting Fraudulent Financial Statements

PubMed Central

Goo, Yeong-Jia James; Shen, Zone-De

2014-01-01

As the fraudulent financial statement of an enterprise is increasingly serious with each passing day, establishing a valid forecasting fraudulent financial statement model of an enterprise has become an important question for academic research and financial practice. After screening the important variables using the stepwise regression, the study also matches the logistic regression, support vector machine, and decision tree to construct the classification models to make a comparison. The study adopts financial and nonfinancial variables to assist in establishment of the forecasting fraudulent financial statement model. Research objects are the companies to which the fraudulent and nonfraudulent financial statement happened between years 1998 to 2012. The findings are that financial and nonfinancial information are effectively used to distinguish the fraudulent financial statement, and decision tree C5.0 has the best classification effect 85.71%. PMID:25302338

Identifying Risk and Protective Factors in Recidivist Juvenile Offenders: A Decision Tree Approach

PubMed Central

Ortega-Campos, Elena; García-García, Juan; Gil-Fenoy, Maria José; Zaldívar-Basurto, Flor

2016-01-01

Research on juvenile justice aims to identify profiles of risk and protective factors in juvenile offenders. This paper presents a study of profiles of risk factors that influence young offenders toward committing sanctionable antisocial behavior (S-ASB). Decision tree analysis is used as a multivariate approach to the phenomenon of repeated sanctionable antisocial behavior in juvenile offenders in Spain. The study sample was made up of the set of juveniles who were charged in a court case in the Juvenile Court of Almeria (Spain). The period of study of recidivism was two years from the baseline. The object of study is presented, through the implementation of a decision tree. Two profiles of risk and protective factors are found. Risk factors associated with higher rates of recidivism are antisocial peers, age at baseline S-ASB, problems in school and criminality in family members. PMID:27611313

Circum-Arctic petroleum systems identified using decision-tree chemometrics

USGS Publications Warehouse

Peters, K.E.; Ramos, L.S.; Zumberge, J.E.; Valin, Z.C.; Scotese, C.R.; Gautier, D.L.

2007-01-01

Source- and age-related biomarker and isotopic data were measured for more than 1000 crude oil samples from wells and seeps collected above approximately 55??N latitude. A unique, multitiered chemometric (multivariate statistical) decision tree was created that allowed automated classification of 31 genetically distinct circumArctic oil families based on a training set of 622 oil samples. The method, which we call decision-tree chemometrics, uses principal components analysis and multiple tiers of K-nearest neighbor and SIMCA (soft independent modeling of class analogy) models to classify and assign confidence limits for newly acquired oil samples and source rock extracts. Geochemical data for each oil sample were also used to infer the age, lithology, organic matter input, depositional environment, and identity of its source rock. These results demonstrate the value of large petroleum databases where all samples were analyzed using the same procedures and instrumentation. Copyright ?? 2007. The American Association of Petroleum Geologists. All rights reserved.

Three-dimensional object recognition using similar triangles and decision trees

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly

1993-01-01

A system, TRIDEC, that is capable of distinguishing between a set of objects despite changes in the objects' positions in the input field, their size, or their rotational orientation in 3D space is described. TRIDEC combines very simple yet effective features with the classification capabilities of inductive decision tree methods. The feature vector is a list of all similar triangles defined by connecting all combinations of three pixels in a coarse coded 127 x 127 pixel input field. The classification is accomplished by building a decision tree using the information provided from a limited number of translated, scaled, and rotated samples. Simulation results are presented which show that TRIDEC achieves 94 percent recognition accuracy in the 2D invariant object recognition domain and 98 percent recognition accuracy in the 3D invariant object recognition domain after training on only a small sample of transformed views of the objects.

Identification of Potential Sources of Mercury (Hg) in Farmland Soil Using a Decision Tree Method in China

PubMed Central

Zhong, Taiyang; Chen, Dongmei; Zhang, Xiuying

2016-01-01

Identification of the sources of soil mercury (Hg) on the provincial scale is helpful for enacting effective policies to prevent further contamination and take reclamation measurements. The natural and anthropogenic sources and their contributions of Hg in Chinese farmland soil were identified based on a decision tree method. The results showed that the concentrations of Hg in parent materials were most strongly associated with the general spatial distribution pattern of Hg concentration on a provincial scale. The decision tree analysis gained an 89.70% total accuracy in simulating the influence of human activities on the additions of Hg in farmland soil. Human activities—for example, the production of coke, application of fertilizers, discharge of wastewater, discharge of solid waste, and the production of non-ferrous metals—were the main external sources of a large amount of Hg in the farmland soil. PMID:27834884

A hybrid approach of stepwise regression, logistic regression, support vector machine, and decision tree for forecasting fraudulent financial statements.

PubMed

Chen, Suduan; Goo, Yeong-Jia James; Shen, Zone-De

2014-01-01

As the fraudulent financial statement of an enterprise is increasingly serious with each passing day, establishing a valid forecasting fraudulent financial statement model of an enterprise has become an important question for academic research and financial practice. After screening the important variables using the stepwise regression, the study also matches the logistic regression, support vector machine, and decision tree to construct the classification models to make a comparison. The study adopts financial and nonfinancial variables to assist in establishment of the forecasting fraudulent financial statement model. Research objects are the companies to which the fraudulent and nonfraudulent financial statement happened between years 1998 to 2012. The findings are that financial and nonfinancial information are effectively used to distinguish the fraudulent financial statement, and decision tree C5.0 has the best classification effect 85.71%.

Tree value system: users guide.

Treesearch

J.K. Ayer Sachet; D.G. Briggs; R.D. Fight

1989-01-01

This paper instructs resource analysts on use of the Tree Value System (TREEVAL). TREEVAL is a microcomputer system of programs for calculating tree or stand values and volumes based on predicted product recovery. Designed for analyzing silvicultural decisions, the system can also be used for appraisals and for evaluating log bucking. The system calculates results...

A decision support tool for identifying abuse of controlled substances by ForwardHealth Medicaid members.

PubMed

Mailloux, Allan T; Cummings, Stephen W; Mugdh, Mrinal

2010-01-01

Our objective was to use Wisconsin's Medicaid Evaluation and Decision Support (MEDS) data warehouse to develop and validate a decision support tool (DST) that (1) identifies Wisconsin Medicaid fee-for-service recipients who are abusing controlled substances, (2) effectively replicates clinical pharmacist recommendations for interventions intended to curb abuse of physician and pharmacy services, and (3) automates data extraction, profile generation and tracking of recommendations and interventions. From pharmacist manual reviews of medication profiles, seven measures of overutilization of controlled substances were developed, including (1-2) 6-month and 2-month "shopping" scores, (3-4) 6-month and 2-month forgery scores, (5) duplicate/same day prescriptions, (6) count of controlled substance claims, and the (7) shopping 6-month score for the individual therapeutic class with the highest score. The pattern analysis logic for the measures was encoded into SQL and applied to the medication profiles of 190 recipients who had already undergone manual review. The scores for each measure and numbers of providers were analyzed by exhaustive chi-squared automatic interaction detection (CHAID) to determine significant thresholds and combinations of predictors of pharmacist recommendations, resulting in a decision tree to classify recipients by pharmacist recommendations. The overall correct classification rate of the decision tree was 95.3%, with a 2.4% false positive rate and 4.0% false negative rate for lock-in versus prescriber-alert letter recommendations. Measures used by the decision tree include the 2-month and 6-month shopping scores, and the number of pharmacies and prescribers. The number of pharmacies was the best predictor of abuse of controlled substances. When a Medicaid recipient receives prescriptions for controlled substances at 8 or more pharmacies, the likelihood of a lock-in recommendation is 90%. The availability of the Wisconsin MEDS data warehouse has enabled development and application of a decision tree for detecting recipient fraud and abuse of controlled substance medications. Using standard pharmacy claims data, the decision tree effectively replicates pharmacist manual review recommendations. The DST has automated extraction and evaluation of pharmacy claims data for creating recommendations for guiding pharmacists in the selection of profiles for manual review. The DST is now the primary method used by the Wisconsin Medicaid program to detect fraud and abuse of physician and pharmacy services committed by recipients.

Globalising Accessibility: Drawing on the Experiences of Developed Countries to Enable the Participation of Disabled People in Zambia

ERIC Educational Resources Information Center

Banda-Chalwe, Martha; Nitz, Jennifer C.; de Jonge, Desleigh

2012-01-01

This paper explores the accessibility situation in a developing country such as Zambia. The global view of accessibility for disabled people is provided to examine the accessibility situation in developed and developing countries, highlighting the role of the environment in achieving rights for disabled people. Recognition of disability rights…

Developing a Nutrition and Health Education Program for Primary Schools in Zambia

ERIC Educational Resources Information Center

Sherman, Jane; Muehlhoff, Ellen

2007-01-01

School-based health and nutrition interventions in developing countries aim at improving children's nutrition and learning ability. In addition to the food and health inputs, children need access to education that is relevant to their lives, of good quality, and effective in its approach. Based on evidence from the Zambia Nutrition Education in…

Situation Reports--Austria, Belgium, Bolivia, Botswana, Finland, German Federal Republic, Italy, Luxembourg, Mauritania, Netherlands, Norway, Portugal, Puerto Rico, Sweden, Tanzania, Yugoslavia, and Zambia.

ERIC Educational Resources Information Center

International Planned Parenthood Federation, London (England).

Data pertaining to population and family planning in seventeen foreign countries are presented in these situation reports. Countries included are Austria, Belgium, Bolivia, Botswana, Finland, German Federal Republic, Italy, Luxembourg, Mauritania, Netherlands, Norway, Portugal, Puerto Rico, Sweden, Tanzania, Yugoslavia, and Zambia. Information is…

Factors Contributing to the Failure to Use Condoms among Students in Zambia

ERIC Educational Resources Information Center

Mbulo, Lazarous; Newman, Ian M.; Shell, Duane F.

2007-01-01

This study explored factors that may predict condom use among college and high school students in Zambia. Using the Social Cognitive Theory, this study examined the relationship of drinking behaviors, alcohol-sexual expectations, education level, and religion to condom use among 961 students. The results of the study show that condom use was low…

Un/Doing Gender? A Case Study of School Policy and Practice in Zambia

ERIC Educational Resources Information Center

Bajaj, Monisha

2009-01-01

This article explores an attempt to disrupt gender inequality in a unique, low-cost private school in Ndola, Zambia. It examines deliberate school policies aimed at "undoing gender" or fostering greater gender equity. These include efforts to maintain gender parity at all levels of the school and the requirement that both young men and…

The Impact of an Unconditional Cash Transfer on Early Child Development: The Zambia Child Grant Program

ERIC Educational Resources Information Center

Seidenfeld, David; Prencipe, Leah; Handa, Sudhanshu; Hawkinson, Laura

2015-01-01

Little research has been conducted on unconditional cash transfers (UCTs) despite their growing prevalence in Africa, including South Africa, Zambia, Zimbabwe, Kenya, Malawi, Lesotho, and Uganda. In this study, researchers implemented a randomized control trial with over 2,500 households to investigate the impact of Africa's child grant program on…

HIV Testing among Adolescents in Ndola, Zambia: How Individual, Relational, and Environmental Factors Relate to Demand

ERIC Educational Resources Information Center

Denison, Julie A.; McCauley, Ann P.; Dunnett-Dagg, Wendy A.; Lungu, Nalakwanji; Sweat, Michael D.

2009-01-01

This study examined how individual, relational and environmental factors related to adolescent demand for HIV voluntary counseling and testing (VCT). A cross-sectional survey among randomly selected 16-19-year-olds in Ndola, Zambia, covered individual (e.g., HIV knowledge), environmental (e.g., distance), and relational factors (e.g., discussed…

Report from the Field: Education under Structural Adjustment in Nigeria and Zambia.

ERIC Educational Resources Information Center

Babalola, Joel B.; Lungwangwa, Geoffrey; Adeyinka, Augustus A.

1999-01-01

Investigates the effects of the Structural Adjustment Program (SAP) on the educational systems in Nigeria and Zambia. Reports that SAP impacted the public expenditure on education, the purchasing power of the incomes earned by both learning institutions and their staff, and on access, equity, and quality indicators in education at all levels. (CMK)

Education and Zambia's Democratic Development: Reconstituting "Something" from the Predatory Project of Neoliberal Globalization

ERIC Educational Resources Information Center

Abdi, Ali A.; Ellis, Lee

2007-01-01

Zambia, a central African country of about 10 million people, is currently exposed to the nonsubjective forces of globalization, including institutional weaknesses such as high unemployment rated and chronic levels of poverty that ipso facto problematize its governance and social development priorities. The first part of the article focuses on an…

76 FR 37055 - Notice of Request for Extension of Approval of an Information Collection; Importation of Baby...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-24

...] Notice of Request for Extension of Approval of an Information Collection; Importation of Baby Squash and Baby Courgettes From Zambia AGENCY: Animal and Plant Health Inspection Service, USDA. ACTION: Extension... importation of baby squash and baby courgettes from Zambia. DATES: We will consider all comments that we...

Catholic Education in Zambia: Mission Integrity and Politics

ERIC Educational Resources Information Center

Carmody, Brendan

2016-01-01

This article provides the history of Catholic state-aided schooling in Zambia for over a century. It notes how the Catholic Church came to view its school to be a pivotal means of church development. By cooperation with the state it entered more fully into the nation's future by offering high-quality state-sponsored schooling. This proved to…

Embers to Bonfires: An Analysis of Early Childhood Teacher Training in Zambia

ERIC Educational Resources Information Center

Evans-Palmer, Teri E.; Shen, Mei-Yi

2017-01-01

This study examined a five-year project initiated by the Women's Global Connection (WGC) to train pre-primary teachers in schools serving HIV/AIDS orphans in Zambia. The researchers evaluated the contextual factors of the training initiative to clarify why some teachers possess high self-efficacy, while others do not. The article analyses the…

Challenges of the African Military in Peacekeeping Missions in Africa

DTIC Science & Technology

2012-03-20

the potential it required the African defense industry cooperation and governments’ commitment to development and economic growth . Lack of such...Challenges of the African Military in Peacekeeping Missions in Africa by Brigadier General James N Mazimba Zambia Army...AFRICAN MILITARY IN PEACEKEEPING MISSIONS IN AFRICA by Brigadier General James N Mazimba Zambia Army William J Flavin

Access, Quality, and Opportunity: A Case Study of Zambia Open Community Schools (ZOCS)

ERIC Educational Resources Information Center

Mwalimu, Michelle

2011-01-01

Community schools and other approaches to Alternative Primary Education or APE have increased access to primary education for underserved populations in Africa, Asia, and Latin America as a major goal of the Education for All (EFA) movement. In Zambia, a country where an estimated 20 percent of the basic education enrollment now attends community…

Factors Related to Pre-Service Teachers' Attitudes towards Inclusion: A Case for Zambia

ERIC Educational Resources Information Center

Muwana, Florence Chuzu; Ostrosky, Michaelene M.

2014-01-01

Inclusive education has become a global trend in the provision of services for students with disabilities. In Zambia and other developing nations, international initiatives from UNESCO and other nongovernmental organisations have contributed to the consensus that all children have a right to a free and appropriate education and that all students…

Mwabu: Interactive Education in Zambia

ERIC Educational Resources Information Center

Gordon, Jenny; Postlewhite, Kerry

2017-01-01

Africa has more people younger than 20 years old than anywhere in the world, and the continent's population is set to double to two billion by 2050. Asking whether that is a challenge or an opportunity isn't really the right question because it is both. For Mwabu, an education technology company born and bred in Zambia, the more important question…

Patterns of Rift Valley fever activity in Zambia.

PubMed Central

Davies, F. G.; Kilelu, E.; Linthicum, K. J.; Pegram, R. G.

1992-01-01

An hypothesis that there was an annual emergence of Rift Valley fever virus in Zambia, during or after the seasonal rains, was examined with the aid of sentinel cattle. Serum samples taken during 1974 and 1978 showed evidence of epizootic Rift Valley fever in Zambia, with more than 80% positive. A sentinel herd exposed from 1982 to 1986 showed that some Rift Valley fever occurred each year. This was usually at a low level, with 3-8% of the susceptible cattle seroconverting. In 1985-6 more than 20% of the animals seroconverted, and this greater activity was associated with vegetational changes--which could be detected by remote-sensing satellite imagery--which have also been associated with greater virus activity in Kenya. PMID:1547835

A decision support system using combined-classifier for high-speed data stream in smart grid

NASA Astrophysics Data System (ADS)

Yang, Hang; Li, Peng; He, Zhian; Guo, Xiaobin; Fong, Simon; Chen, Huajun

2016-11-01

Large volume of high-speed streaming data is generated by big power grids continuously. In order to detect and avoid power grid failure, decision support systems (DSSs) are commonly adopted in power grid enterprises. Among all the decision-making algorithms, incremental decision tree is the most widely used one. In this paper, we propose a combined classifier that is a composite of a cache-based classifier (CBC) and a main tree classifier (MTC). We integrate this classifier into a stream processing engine on top of the DSS such that high-speed steaming data can be transformed into operational intelligence efficiently. Experimental results show that our proposed classifier can return more accurate answers than other existing ones.

'No sister, the breast alone is not enough for my baby' a qualitative assessment of potentials and barriers in the promotion of exclusive breastfeeding in southern Zambia.

PubMed

Fjeld, Eli; Siziya, Seter; Katepa-Bwalya, Mary; Kankasa, Chipepo; Moland, Karen Marie; Tylleskär, Thorkild

2008-11-05

Appropriate feeding practices are of fundamental importance for the survival, growth, development and health of infants and young children. The aim of the present study was to collect baseline information on current infant and young child feeding practices, attitudes and knowledge in Mazabuka, Zambia, using a qualitative approach. The study was conducted in Mazabuka, 130 km south of Lusaka in Zambia in January and February in 2005. Nine focus group discussions with mothers and a total of 18 in-depth interviews with fathers, grandmothers, health staff and traditional birth attendants were performed in both rural and urban areas. Breastfeeding was reported to be universal, the use of pre-lacteal feeds appeared to be low, colostrum was rarely discarded, and attitudes to and knowledge about exclusive breastfeeding were generally good. However, few practised exclusive breastfeeding. The barriers revealed were: (1) the perception of insufficient milk, (2) the fear of dying or becoming too sick to be able to breastfeed, (3) convention, (4) the perception of 'bad milk' and (5) lack of knowledge on the subject. The health staff and traditional birth attendants were the most important actors in transmitting knowledge about infant feeding to the mothers. Both categories appeared to have updated knowledge on child health and were well respected in the society. Fathers and grandmothers tended to be less knowledgeable on novel subjects such as exclusive breastfeeding and often showed a negative attitude towards it. At the same time they had considerable authority over mothers and children and infant feeding decisions. The rural population was in general less educated and more prone to conventional non-exclusive feeding practices. The message that exclusive breastfeeding (EBF) is beneficial for child health had reached the health workers and was taught to mothers. However, conventions and expectations from family members in this Zambian community were important barriers in preventing the message of EBF from being translated into practice. The deep-rooted beliefs that prohibit EBF need to be addressed in projects and campaigns promoting EBF.

Prices and mark-ups on antimalarials: evidence from nationally representative studies in six malaria-endemic countries.

PubMed

Palafox, Benjamin; Patouillard, Edith; Tougher, Sarah; Goodman, Catherine; Hanson, Kara; Kleinschmidt, Immo; Torres Rueda, Sergio; Kiefer, Sabine; O'Connell, Kate; Zinsou, Cyprien; Phok, Sochea; Akulayi, Louis; Arogundade, Ekundayo; Buyungo, Peter; Mpasela, Felton; Poyer, Stephen; Chavasse, Desmond

2016-03-01

The private for-profit sector is an important source of treatment for malaria. However, private patients face high prices for the recommended treatment for uncomplicated malaria, artemisinin combination therapies (ACTs), which makes them more likely to receive cheaper, less effective non-artemisinin therapies (nATs). This study seeks to better understand consumer antimalarial prices by documenting and exploring the pricing behaviour of retailers and wholesalers. Using data collected in 2009-10, we present survey estimates of antimalarial retail prices, and wholesale- and retail-level price mark-ups from six countries (Benin, Cambodia, the Democratic Republic of Congo, Nigeria, Uganda and Zambia), along with qualitative findings on factors affecting pricing decisions. Retail prices were lowest for nATs, followed by ACTs and artemisinin monotherapies (AMTs). Retailers applied the highest percentage mark-ups on nATs (range: 40% in Nigeria to 100% in Cambodia and Zambia), whereas mark-ups on ACTs (range: 22% in Nigeria to 71% in Zambia) and AMTs (range: 22% in Nigeria to 50% in Uganda) were similar in magnitude, but lower than those applied to nATs. Wholesale mark-ups were generally lower than those at retail level, and were similar across antimalarial categories in most countries. When setting prices wholesalers and retailers commonly considered supplier prices, prevailing market prices, product availability, product characteristics and the costs related to transporting goods, staff salaries and maintaining a property. Price discounts were regularly used to encourage sales and were sometimes used by wholesalers to reward long-term customers. Pricing constraints existed only in Benin where wholesaler and retailer mark-ups are regulated; however, unlicensed drug vendors based in open-air markets did not adhere to the pricing regime. These findings indicate that mark-ups on antimalarials are reasonable. Therefore, improving ACT affordability would be most readily achieved by interventions that reduce commodity prices for retailers, such as ACT subsidies, pooled purchasing mechanisms and cost-effective strategies to increase the distribution coverage area of wholesalers. © The Author 2015. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.

Advanced Subspace Techniques for Modeling Channel and Session Variability in a Speaker Recognition System

DTIC Science & Technology

2012-03-01

with each SVM discriminating between a pair of the N total speakers in the data set. The (( + 1))/2 classifiers then vote on the final...classification of a test sample. The Random Forest classifier is an ensemble classifier that votes amongst decision trees generated with each node using...Forest vote , and the effects of overtraining will be mitigated by the fact that each decision tree is overtrained differently (due to the random

The development and evaluation of content validity of the Zambia Spina Bifida Functional Measure: Preliminary studies

PubMed Central

Amosun, Seyi L.; Shilalukey-Ngoma, Mary P.; Kafaar, Zuhayr

2017-01-01

Background Very little is known on outcome measures for children with spina bifida (SB) in Zambia. If rehabilitation professionals managing children with SB in Zambia and other parts of sub-Saharan Africa are to instigate measuring outcomes routinely, a tool has to be made available. The main objective of this study was to develop an appropriate and culturally sensitive instrument for evaluating the impact of the interventions on children with SB in Zambia. Methods A mixed design method was used for the study. Domains were identified retrospectively and confirmation was done through a systematic review study. Items were generated through semi-structured interviews and focus group discussions. Qualitative data were downloaded, translated into English, transcribed verbatim and presented. These were then placed into categories of the main domains of care deductively through the process of manifest content analysis. Descriptive statistics, alpha coefficient and index of content validity were calculated using SPSS. Results Self-care, mobility and social function were identified as main domains, while participation and communication were sub-domains. A total of 100 statements were generated and 78 items were selected deductively. An alpha coefficient of 0.98 was computed and experts judged the items. Conclusions The new functional measure with an acceptable level of content validity titled Zambia Spina Bifida Functional Measure (ZSBFM) was developed. It was designed to evaluate effectiveness of interventions given to children with SB from the age of 6 months to 5 years. Psychometric properties of reliability and construct validity were tested and are reported in another study. PMID:28951850

Antimicrobial Resistant Enteropathogenic Escherichia coli and Salmonella spp. in Houseflies Infesting Fish in Food Markets in Zambia.

PubMed

Songe, Mwansa M; Hang'ombe, Bernard M; Knight-Jones, Theodore J D; Grace, Delia

2016-12-28

Diarrhea is one of the most common diseases and is a leading cause of death in developing countries. This is often caused by contaminated food. Poor food hygiene standards are exacerbated by the presence of flies which can transmit a variety of infectious microorganisms, particularly through animal source foods. This fact becomes especially important in developing countries like Zambia, where fish is a highly valued source of protein. Our interest in this study was to identify if the flies that beset food markets in Zambia carry important pathogenic bacteria on their bodies, and subsequently if these bacteria carry resistance genes to commonly used antibiotics, which would indicate problems in eradicating these pathogens. The present study took into account fish vendors' and consumers' perception of flies and interest in interventions to reduce their numbers. We conducted semi-structured interviews with (1) traders (comprised of randomly selected males and females) and (2) consumers (including randomly selected males and females). Thereafter, we collected flies found on fish in markets in Mongu and Lusaka districts of Zambia. For the entire study, a total of 418 fly samples were analyzed in the laboratory and Salmonella spp. and enteropathogenic Escherichia coli were isolated from the flies. Further laboratory screening revealed that overall, 17.2% (72/418) (95% CI; 43.2%-65.5%) of total samples analyzed contained Extended-Spectrum Beta-Lactamase (ESBL)-producing E. coli . These significant findings call for a strengthening of the antibiotic administering policy in Zambia and the development of sustainable interventions to reduce fly numbers in food markets and improve food safety and hygiene.

Mitochondrial Haplotype Diversity in Zambian Lions: Bridging a Gap in the Biogeography of an Iconic Species

PubMed Central

Curry, Caitlin J.; White, Paula A.; Derr, James N.

2015-01-01

Analysis of DNA sequence diversity at the 12S to 16S mitochondrial genes of 165 African lions (Panthera leo) from five main areas in Zambia has uncovered haplotypes which link Southern Africa with East Africa. Phylogenetic analysis suggests Zambia may serve as a bridge connecting the lion populations in southern Africa to eastern Africa, supporting earlier hypotheses that eastern-southern Africa may represent the evolutionary cradle for the species. Overall gene diversity throughout the Zambian lion population was 0.7319 +/- 0.0174 with eight haplotypes found; three haplotypes previously described and the remaining five novel. The addition of these five novel haplotypes, so far only found within Zambia, nearly doubles the number of haplotypes previously reported for any given geographic location of wild lions. However, based on an AMOVA analysis of these haplotypes, there is little to no matrilineal gene flow (Fst = 0.47) when the eastern and western regions of Zambia are considered as two regional sub-populations. Crossover haplotypes (H9, H11, and Z1) appear in both populations as rare in one but common in the other. This pattern is a possible result of the lion mating system in which predominately males disperse, as all individuals with crossover haplotypes were male. The determination and characterization of lion sub-populations, such as done in this study for Zambia, represent a higher-resolution of knowledge regarding both the genetic health and connectivity of lion populations, which can serve to inform conservation and management of this iconic species. PMID:26674533

Trends of selected cattle diseases in eastern Zambia between 1988 and 2008.

PubMed

Mubamba, Chrisborn; Sitali, Joseph; Gummow, Bruce

2011-09-01

Livestock diseases have long been a challenge to livestock production and public health in sub-Saharan Africa and Zambia in particular. The Eastern Province of Zambia is one area in Zambia that is not spared by this challenge. Among various livestock diseases affecting cattle in this region, the most prominent are East Coast Fever (ECF) and African Animal Trypanasomiasis (AAT). Since little has been published on the epidemiological trends of these diseases in eastern Zambia, a retrospective epidemiological study was carried out using reports that were submitted to the provincial veterinary office over the past 20 years. This paper assists in evaluating the impact of some of these aid programmes. Data was analysed using Excel(©), SPSS(®), Epi Info(©), and Epi Map(©) software. Apparent prevalence of AAT in cattle had decreased in the study period from estimates as high as 50% in Katete and Petauke district in 1990 and 1992 respectively to just below 3% (Petauke and Katete) in 2008, thereby, reducing the provincial apparent prevalence from 20% in 1992 to just below 3% in 2008. AAT apparent prevalence dropped from estimates as high as 17% in Chadiza district and 6% in Chipata district in 1990 to just below 1% in 2008 thereby reducing the provincial mean prevalence of East Coast Fever from 6% (1990) to 1% (2008). The inclusion of donor assistance in disease control programmes for both AAT and ECF appeared to have a significant impact on the prevalence of both diseases. Copyright © 2011 Elsevier B.V. All rights reserved.

Ethnoveterinary treatments for common cattle diseases in four districts of the Southern Province, Zambia

PubMed Central

Syakalima, Michelo; Simuunza, Martin; Zulu, Victor Chisha

2018-01-01

Aim: Ethno veterinary knowledge has rarely been recorded, and no or limited effort has been made to exploit this knowledge despite its widespread use in Zambia. This study documented the types of plants used to treat important animal diseases in rural Zambia as a way of initiating their sustained documentation and scientific validation. Materials and Methods: The study was done in selected districts of the Southern Zambia, Africa. The research was a participatory epidemiological study conducted in two phases. The first phase was a pre-study exploratory rapid rural appraisal conducted to familiarize the researchers with the study areas, and the second phase was a participatory rural appraisal to help gather the data. The frequency index was used to rank the commonly mentioned treatments. Results: A number of diseases and traditional treatments were listed with the help of local veterinarians. Diseases included: Corridor disease (Theileriosis), foot and mouth disease, blackleg, bloody diarrhea, lumpy skin disease, fainting, mange, blindness, coughing, bloat, worms, cobra snakebite, hemorrhagic septicemia, and transmissible venereal tumors. The plant preparations were in most diseases given to the livestock orally (as a drench). Leaves, barks, and roots were generally used depending on the plant type. Conclusion: Ethno veterinary medicine is still widespread among the rural farmers in the province and in Zambia in general. Some medicines are commonly used across diseases probably because they have a wide spectrum of action. These medicines should, therefore, be validated for use in conventional livestock healthcare systems in the country to reduce the cost of treatments. PMID:29657394

Mitochondrial Haplotype Diversity in Zambian Lions: Bridging a Gap in the Biogeography of an Iconic Species.

PubMed

Curry, Caitlin J; White, Paula A; Derr, James N

2015-01-01

Analysis of DNA sequence diversity at the 12S to 16S mitochondrial genes of 165 African lions (Panthera leo) from five main areas in Zambia has uncovered haplotypes which link Southern Africa with East Africa. Phylogenetic analysis suggests Zambia may serve as a bridge connecting the lion populations in southern Africa to eastern Africa, supporting earlier hypotheses that eastern-southern Africa may represent the evolutionary cradle for the species. Overall gene diversity throughout the Zambian lion population was 0.7319 +/- 0.0174 with eight haplotypes found; three haplotypes previously described and the remaining five novel. The addition of these five novel haplotypes, so far only found within Zambia, nearly doubles the number of haplotypes previously reported for any given geographic location of wild lions. However, based on an AMOVA analysis of these haplotypes, there is little to no matrilineal gene flow (Fst = 0.47) when the eastern and western regions of Zambia are considered as two regional sub-populations. Crossover haplotypes (H9, H11, and Z1) appear in both populations as rare in one but common in the other. This pattern is a possible result of the lion mating system in which predominately males disperse, as all individuals with crossover haplotypes were male. The determination and characterization of lion sub-populations, such as done in this study for Zambia, represent a higher-resolution of knowledge regarding both the genetic health and connectivity of lion populations, which can serve to inform conservation and management of this iconic species.

Using Decision Trees for Estimating Mode Choice of Trips in Buca-Izmir

NASA Astrophysics Data System (ADS)

Oral, L. O.; Tecim, V.

2013-05-01

Decision makers develop transportation plans and models for providing sustainable transport systems in urban areas. Mode Choice is one of the stages in transportation modelling. Data mining techniques can discover factors affecting the mode choice. These techniques can be applied with knowledge process approach. In this study a data mining process model is applied to determine the factors affecting the mode choice with decision trees techniques by considering individual trip behaviours from household survey data collected within Izmir Transportation Master Plan. From this perspective transport mode choice problem is solved on a case in district of Buca-Izmir, Turkey with CRISP-DM knowledge process model.

Interacting with mobile devices by fusion eye and hand gestures recognition systems based on decision tree approach

NASA Astrophysics Data System (ADS)

Elleuch, Hanene; Wali, Ali; Samet, Anis; Alimi, Adel M.

2017-03-01

Two systems of eyes and hand gestures recognition are used to control mobile devices. Based on a real-time video streaming captured from the device's camera, the first system recognizes the motion of user's eyes and the second one detects the static hand gestures. To avoid any confusion between natural and intentional movements we developed a system to fuse the decision coming from eyes and hands gesture recognition systems. The phase of fusion was based on decision tree approach. We conducted a study on 5 volunteers and the results that our system is robust and competitive.

A dynamic fault tree model of a propulsion system

NASA Technical Reports Server (NTRS)

Xu, Hong; Dugan, Joanne Bechta; Meshkat, Leila

2006-01-01

We present a dynamic fault tree model of the benchmark propulsion system, and solve it using Galileo. Dynamic fault trees (DFT) extend traditional static fault trees with special gates to model spares and other sequence dependencies. Galileo solves DFT models using a judicious combination of automatically generated Markov and Binary Decision Diagram models. Galileo easily handles the complexities exhibited by the benchmark problem. In particular, Galileo is designed to model phased mission systems.

Including public-health benefits of trees in urban-forestry decision making

Treesearch

Geoffrey H. Donovan

2017-01-01

Research demonstrating the biophysical benefits of urban trees are often used to justify investments in urban forestry. Far less emphasis, however, is placed on the non-bio-physical benefits such as improvements in public health. Indeed, the public-health benefits of trees may be significantly larger than the biophysical benefits, and, therefore, failure to account for...

Goal Programming: A New Tool for the Christmas Tree Industry

Treesearch

Bruce G. Hansen

1977-01-01

Goal programing (GP) can be useful for decision making in the natural Christmas tree industry. Its usefulness is demonstrated through an analysis of a hypothetical problem in which two potential growers decide how to use 10 acres in growing Christmas trees. Though the physical settings are identical, distinct differences between their goals significantly influence the...

Lessons learned from Applications of a Decision Tree for Confronting Climate Change Uncertainty - the Short Term and the Long Term

NASA Astrophysics Data System (ADS)

Ray, P. A.; Wi, S.; Bonzanigo, L.; Taner, M. U.; Rodriguez, D.; Garcia, L.; Brown, C.

2016-12-01

The Decision Tree for Confronting Climate Change Uncertainty is a hierarchical, staged framework for accomplishing climate change risk management in water resources system investments. Since its development for the World Bank Water Group two years ago, the framework has been applied to pilot demonstration projects in Nepal (hydropower generation), Mexico (water supply), Kenya (multipurpose reservoir operation), and Indonesia (flood risks to dam infrastructure). An important finding of the Decision Tree demonstration projects has been the need to present the risks/opportunities of climate change to stakeholders and investors in proportion to risks/opportunities and hazards of other kinds. This presentation will provide an overview of tools and techniques used to quantify risks/opportunities to each of the project types listed above, with special attention to those found most useful for exploration of the risk space. Careful exploration of the risk/opportunity space shows that some interventions would be better taken now, whereas risks/opportunities of other types would be better instituted incrementally in order to maintain reversibility and flexibility. A number of factors contribute to the robustness/flexibility tradeoff: available capital, magnitude and imminence of potential risk/opportunity, modular (or not) character of investment, and risk aversion of the decision maker, among others. Finally, in each case, nuance was required in the translation of Decision Tree findings into actionable policy recommendations. Though the narrative of stakeholder solicitation, engagement, and ultimate partnership is unique to each case, summary lessons are available from the portfolio that can serve as a guideline to the community of climate change risk managers.

Decision tree analysis of treatment strategies for mild and moderate cases of clinical mastitis occurring in early lactation.

PubMed

Pinzón-Sánchez, C; Cabrera, V E; Ruegg, P L

2011-04-01

The objective of this study was to develop a decision tree to evaluate the economic impact of different durations of intramammary treatment for the first case of mild or moderate clinical mastitis (CM) occurring in early lactation with various scenarios of pathogen distributions and use of on-farm culture. The tree included 2 decision and 3 probability events. The first decision evaluated use of on-farm culture (OFC; 2 programs using OFC and 1 not using OFC) and the second decision evaluated treatment strategies (no intramammary antimicrobials or antimicrobials administered for 2, 5, or 8 d). The tree included probabilities for the distribution of etiologies (gram-positive, gram-negative, or no growth), bacteriological cure, and recurrence. The economic consequences of mastitis included costs of diagnosis and initial treatment, additional treatments, labor, discarded milk, milk production losses due to clinical and subclinical mastitis, culling, and transmission of infection to other cows (only for CM caused by Staphylococcus aureus). Pathogen-specific estimates for bacteriological cure and milk losses were used. The economically optimal path for several scenarios was determined by comparison of expected monetary values. For most scenarios, the optimal economic strategy was to treat CM caused by gram-positive pathogens for 2 d and to avoid antimicrobials for CM cases caused by gram-negative pathogens or when no pathogen was recovered. Use of extended intramammary antimicrobial therapy (5 or 8 d) resulted in the least expected monetary values. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Binary Decision Trees for Preoperative Periapical Cyst Screening Using Cone-beam Computed Tomography.

PubMed

Pitcher, Brandon; Alaqla, Ali; Noujeim, Marcel; Wealleans, James A; Kotsakis, Georgios; Chrepa, Vanessa

2017-03-01

Cone-beam computed tomographic (CBCT) analysis allows for 3-dimensional assessment of periradicular lesions and may facilitate preoperative periapical cyst screening. The purpose of this study was to develop and assess the predictive validity of a cyst screening method based on CBCT volumetric analysis alone or combined with designated radiologic criteria. Three independent examiners evaluated 118 presurgical CBCT scans from cases that underwent apicoectomies and had an accompanying gold standard histopathological diagnosis of either a cyst or granuloma. Lesion volume, density, and specific radiologic characteristics were assessed using specialized software. Logistic regression models with histopathological diagnosis as the dependent variable were constructed for cyst prediction, and receiver operating characteristic curves were used to assess the predictive validity of the models. A conditional inference binary decision tree based on a recursive partitioning algorithm was constructed to facilitate preoperative screening. Interobserver agreement was excellent for volume and density, but it varied from poor to good for the radiologic criteria. Volume and root displacement were strong predictors for cyst screening in all analyses. The binary decision tree classifier determined that if the volume of the lesion was >247 mm 3 , there was 80% probability of a cyst. If volume was <247 mm 3 and root displacement was present, cyst probability was 60% (78% accuracy). The good accuracy and high specificity of the decision tree classifier renders it a useful preoperative cyst screening tool that can aid in clinical decision making but not a substitute for definitive histopathological diagnosis after biopsy. Confirmatory studies are required to validate the present findings. Published by Elsevier Inc.

Rapid decision support tool based on novel ecosystem service variables for retrofitting of permeable pavement systems in the presence of trees.

PubMed

Scholz, Miklas; Uzomah, Vincent C

2013-08-01

The retrofitting of sustainable drainage systems (SuDS) such as permeable pavements is currently undertaken ad hoc using expert experience supported by minimal guidance based predominantly on hard engineering variables. There is a lack of practical decision support tools useful for a rapid assessment of the potential of ecosystem services when retrofitting permeable pavements in urban areas that either feature existing trees or should be planted with trees in the near future. Thus the aim of this paper is to develop an innovative rapid decision support tool based on novel ecosystem service variables for retrofitting of permeable pavement systems close to trees. This unique tool proposes the retrofitting of permeable pavements that obtained the highest ecosystem service score for a specific urban site enhanced by the presence of trees. This approach is based on a novel ecosystem service philosophy adapted to permeable pavements rather than on traditional engineering judgement associated with variables based on quick community and environment assessments. For an example case study area such as Greater Manchester, which was dominated by Sycamore and Common Lime, a comparison with the traditional approach of determining community and environment variables indicates that permeable pavements are generally a preferred SuDS option. Permeable pavements combined with urban trees received relatively high scores, because of their great potential impact in terms of water and air quality improvement, and flood control, respectively. The outcomes of this paper are likely to lead to more combined permeable pavement and tree systems in the urban landscape, which are beneficial for humans and the environment. Copyright © 2013 Elsevier B.V. All rights reserved.

Redressing Gender Inequalities in Education. A Review of Constraints and Priorities in Malawi, Zambia, and Zimbabwe.

ERIC Educational Resources Information Center

Swainson, Nicola

The causes and manifestations of gender inequalities in education in Malawi, Zambia, and Zimbabwe and policy options for redressing them were examined through a review of literature on the causes, nature, and extent of gender disparities in education in the study region and information on efforts to eliminate gender inequality. Special attention…

"Distance Learning" or "Learning at a Distance"? Case Study of an Education Initiative to Deliver an In-Service Bachelors Degree in Zambia

ERIC Educational Resources Information Center

Smith, Christopher J.

2010-01-01

In 1998, as part of what was then Zambia's Department of Technical Education and Vocational Training's (DTEVT) human resources capacity building initiative, under the Ministry of Science, Technology and Vocational Training (MSTVT), donor funding was secured to provide degree-level training for key teachers and managers within the technical…

Understanding the Psychosocial and Environmental Factors and Barriers Affecting Utilization of Maternal Healthcare Services in Kalomo, Zambia: A Qualitative Study

ERIC Educational Resources Information Center

Sialubanje, Cephas; Massar, Karlijn; Hamer, Davidson H.; Ruiter, Robert A. C.

2014-01-01

This qualitative study aimed to identify psychosocial and environmental factors contributing to low utilization of maternal healthcare services in Kalomo, Zambia. Twelve focus group discussions (n = 141) and 35 in-depth interviews were conducted in six health centre catchment areas. Focus group discussions comprised women of reproductive age…

Assessment of Integrated Environmental Management in Public and Private Schools in the Copperbelt Province of Zambia

ERIC Educational Resources Information Center

Makisa, Kaponda

2016-01-01

Copperbelt Province is one of the ten provinces of Zambia. It has public and private schools which have been faced with escalating levels of environmental problems due to growth in human population and economic growth. The environmental problems which are matters of concern in the schools include, unsound waste management, loss of vegetation…

The Catholic School in Zambia 1964-2014: Catholic and Catholic?

ERIC Educational Resources Information Center

Carmody, Brendan

2015-01-01

This article sketches the history of the Catholic school in Zambia over a 50-year period noting how for reasons of political acceptability it increasingly became less at home with its religious mission thereby finding itself with an unclear sense of purpose. In order to redeem its identity, this article argues that there is need for the school to…

Exploring Understandings of Inclusion in Schools in Zambia and Tanzania Using Reflective Writing and Photography

ERIC Educational Resources Information Center

Miles, Susie

2011-01-01

In this article I explore insights gained from participating in an exploratory, small-scale study led by the Enabling Education Network (EENET) in 17 schools in northern Zambia and five schools in Tanzania. Facilitating South-based research, while based in a Northern university, raises complex ethical issues about voice and control which are…

A Library Response to the Massification of Higher Education: The Case of the University of Zambia Library

ERIC Educational Resources Information Center

Kanyengo, Christine Wamunyima

2009-01-01

This paper looks at the challenges that libraries in Africa face in responding to massification of higher education by discussing the University of Zambia library's response in library and information resources provision. As a result of massification of higher education, libraries have been forced not only to employ new and different strategies to…

Callings, Work Role Fit, Psychological Meaningfulness and Work Engagement among Teachers in Zambia

ERIC Educational Resources Information Center

Rothmann, Sebastiaan; Hamukang'andu, Lukondo

2013-01-01

Our aim in this study was to investigate the relationships among a calling orientation, work role fit, psychological meaningfulness and work engagement of teachers in Zambia. A quantitative approach was followed and a cross-sectional survey was used. The sample (n = 150) included 75 basic and 75 secondary school teachers in the Choma district of…

Beyond a Learning Society? It Is All to Be Done Again: Zambia and Zimbabwe

ERIC Educational Resources Information Center

Alexander, David

2006-01-01

This article considers the ways in which educators and learning societies in Zambia and Zimbabwe have had to struggle to create independent, democratic and critical curricula in difficult circumstances over the last 50 years in the context of historical shifts in power, a declining British Empire and the re-emergence of reactionary forces at a…

Distance Education Examination Management in a Lowly Resourced North-Eastern Region of Zambia: a Phenomenological Approach

ERIC Educational Resources Information Center

Simui, Francis; Chibale, Henry; Namangala, Boniface

2017-01-01

This paper focuses on the management of distance education examination in a lowly resourced North-Eastern region of Zambia. The study applies Hermeneutic Phenomenology approach to generate and make sense of the data. It is the lived experiences of 2 invigilators and 66 students purposively selected that the study draws its insights from. Meaning…

Predictors of Attitudes toward Intimate Partner Violence: A Comparative Study of Men in Zambia and Kenya

ERIC Educational Resources Information Center

Lawoko, Stephen

2008-01-01

Attitudes toward intimate partner violence (IPV) were compared between Zambian and Kenyan men on sociodemographic, attitudinal, and structural predictors of such attitudes. Data were retrieved from the latest Demographic and Health Surveys in each country. The results showed that many men in Zambia (71%) and Kenya (68%) justified IPV to punish a…

Grassroot Soccer Resiliency Pilot Program: Building Resiliency through Sport-Based Education in Zambia and South Africa

ERIC Educational Resources Information Center

Peacock-Villada, Paola; DeCelles, Jeff; Banda, Peter S.

2007-01-01

Grassroot Soccer (GRS), a U.S.-based nonprofit organization, designed a curriculum and sport-based teaching model to build resiliency, targeting boys and girls in Lusaka, Zambia, and Johannesburg, South Africa, where most children are reminded daily of the devastation caused by AIDS and where many face chronic and acute hardship. Collaborating…

An Audit of Skills and Qualifications in Preservation and Conservation Techniques: The Case of the University of Zambia Libraries

ERIC Educational Resources Information Center

Shameenda, Kimbo Lemmy; Kanyengo, Christine Wamunyima

2012-01-01

This article establishes the level of skills and experience in preservation and conservation management using a case study methodological approach conducted in the 3 university libraries at the University of Zambia. The findings revealed that 20 (57%) of the library staff had not received formal training in preservation and conservation of library…

The Nature and Role of Religious Studies at the University of Zambia: 1985-2005

ERIC Educational Resources Information Center

Carmody, Brendan

2008-01-01

The place of religion in higher education has been and remains a complex issue internationally. This article aims to outline the nature and development of Religious Studies at the University of Zambia in Lusaka (UNZA) as an instance of how religion entered higher education in an African setting. In doing so, it will also provide perspectives on…

Targeting indoor residual spraying for malaria using epidemiological data: a case study of the Zambia experience.

PubMed

Pinchoff, Jessie; Larsen, David A; Renn, Silvia; Pollard, Derek; Fornadel, Christen; Maire, Mark; Sikaala, Chadwick; Sinyangwe, Chomba; Winters, Benjamin; Bridges, Daniel J; Winters, Anna M

2016-01-06

In Zambia and other sub-Saharan African countries affected by ongoing malaria transmission, indoor residual spraying (IRS) for malaria prevention has typically been implemented over large areas, e.g., district-wide, and targeted to peri-urban areas. However, there is a recent shift in some countries, including Zambia, towards the adoption of a more strategic and targeted IRS approach, in coordination with increased emphasis on universal coverage of long-lasting insecticidal nets (LLINs) and effective insecticide resistance management. A true targeted approach would deliver IRS to sub-district areas identified as high-risk, with the goal of maximizing the prevention of malaria cases and deaths. Together with the Government of the Republic of Zambia, a new methodology was developed applying geographic information systems and satellite imagery to support a targeted IRS campaign during the 2014 spray season using health management information system data. This case study focuses on the developed methodology while also highlighting the significant research gaps which must be filled to guide countries on the most effective strategy for IRS targeting in the context of universal LLIN coverage and evolving insecticide resistance.

Evaluation of a TB infection control implementation initiative in out-patient HIV clinics in Zambia and Botswana.

PubMed

Emerson, C; Lipke, V; Kapata, N; Mwananyambe, N; Mwinga, A; Garekwe, M; Lanje, S; Moshe, Y; Pals, S L; Nakashima, A K; Miller, B

2016-07-01

Out-patient human immunodeficiency virus (HIV) care and treatment clinics in Zambia and Botswana, countries with a high burden of HIV and TB infection. To develop a tuberculosis infection control (TB IC) training and implementation package and evaluate the implementation of TB IC activities in facilities implementing the package. Prospective program evaluation of a TB IC training and implementation package using a standardized facility risk assessment tool, qualitative interviews with facility health care workers and measures of pre- and post-test performance. A composite measure of facility performance in TB IC improved from 32% at baseline to 50% at 1 year among eight facilities in Zambia, and from 27% to 80% at 6 months among 10 facilities in Botswana. Although there was marked improvement in indicators of managerial, administrative and environmental controls, key ongoing challenges remained in ensuring access to personal protective equipment and implementing TB screening in health care workers. TB IC activities at out-patient HIV clinics in Zambia and Botswana improved after training using the implementation package. Continued infrastructure support, as well as monitoring and evaluation, are needed to support the scale-up and sustainability of TB IC programs in facilities in low-resource countries.

Barriers and Facilitators to HIV Testing Among Zambian Female Sex Workers in Three Transit Hubs.

PubMed

Chanda, Michael M; Perez-Brumer, Amaya G; Ortblad, Katrina F; Mwale, Magdalene; Chongo, Steven; Kamungoma, Nyambe; Kanchele, Catherine; Fullem, Andrew; Barresi, Leah; Bärnighausen, Till; Oldenburg, Catherine E

2017-07-01

Zambia has a generalized HIV epidemic, and HIV is concentrated along transit routes. Female sex workers (FSWs) are disproportionately affected by the epidemic. HIV testing is the crucial first step for engagement in HIV care and HIV prevention activities. However, to date little work has been done with FSWs in Zambia, and little is known about barriers and facilitators to HIV testing in this population. FSW peer educators were recruited through existing sex worker organizations for participation in a trial related to HIV testing among FSWs. We conducted five focus groups with FSW peer educators (N = 40) in three transit towns in Zambia (Livingstone, Chirundu, and Kapiri Mposhi) to elicit community norms related to HIV testing. Emerging themes demonstrated barriers and facilitators to HIV testing occurring at multiple levels, including individual, social network, and structural. Stigma and discrimination, including healthcare provider stigma, were a particularly salient barrier. Improving knowledge, social support, and acknowledgment of FSWs and women's role in society emerged as facilitators to testing. Interventions to improve HIV testing among FSWs in Zambia will need to address barriers and facilitators at multiple levels to be maximally effective.

The prediction of breast cancer biopsy outcomes using two CAD approaches that both emphasize an intelligible decision process

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elter, M.; Schulz-Wendtland, R.; Wittenberg, T.

2007-11-15

Mammography is the most effective method for breast cancer screening available today. However, the low positive predictive value of breast biopsy resulting from mammogram interpretation leads to approximately 70% unnecessary biopsies with benign outcomes. To reduce the high number of unnecessary breast biopsies, several computer-aided diagnosis (CAD) systems have been proposed in the last several years. These systems help physicians in their decision to perform a breast biopsy on a suspicious lesion seen in a mammogram or to perform a short term follow-up examination instead. We present two novel CAD approaches that both emphasize an intelligible decision process to predictmore » breast biopsy outcomes from BI-RADS findings. An intelligible reasoning process is an important requirement for the acceptance of CAD systems by physicians. The first approach induces a global model based on decison-tree learning. The second approach is based on case-based reasoning and applies an entropic similarity measure. We have evaluated the performance of both CAD approaches on two large publicly available mammography reference databases using receiver operating characteristic (ROC) analysis, bootstrap sampling, and the ANOVA statistical significance test. Both approaches outperform the diagnosis decisions of the physicians. Hence, both systems have the potential to reduce the number of unnecessary breast biopsies in clinical practice. A comparison of the performance of the proposed decision tree and CBR approaches with a state of the art approach based on artificial neural networks (ANN) shows that the CBR approach performs slightly better than the ANN approach, which in turn results in slightly better performance than the decision-tree approach. The differences are statistically significant (p value <0.001). On 2100 masses extracted from the DDSM database, the CRB approach for example resulted in an area under the ROC curve of A(z)=0.89{+-}0.01, the decision-tree approach in A(z)=0.87{+-}0.01, and the ANN approach in A(z)=0.88{+-}0.01.« less

Underpinning Sustainable Vector Control through Informed Insecticide Resistance Management

PubMed Central

Hemmings, Kay; Hughes, Angela J.; Chanda, Emmanuel; Musapa, Mulenga; Kamuliwo, Mulakwa; Phiri, Faustina N.; Muzia, Lucy; Chanda, Javan; Kandyata, Alister; Chirwa, Brian; Poer, Kathleen; Hemingway, Janet; Wondji, Charles S.; Ranson, Hilary; Coleman, Michael

2014-01-01

Background There has been rapid scale-up of malaria vector control in the last ten years. Both of the primary control strategies, long-lasting pyrethroid treated nets and indoor residual spraying, rely on the use of a limited number of insecticides. Insecticide resistance, as measured by bioassay, has rapidly increased in prevalence and has come to the forefront as an issue that needs to be addressed to maintain the sustainability of malaria control and the drive to elimination. Zambia's programme reported high levels of resistance to the insecticides it used in 2010, and, as a result, increased its investment in resistance monitoring to support informed resistance management decisions. Methodology/Principal Findings A country-wide survey on insecticide resistance in Zambian malaria vectors was performed using WHO bioassays to detect resistant phenotypes. Molecular techniques were used to detect target-site mutations and microarray to detect metabolic resistance mechanisms. Anopheles gambiae s.s. was resistant to pyrethroids, DDT and carbamates, with potential organophosphate resistance in one population. The resistant phenotypes were conferred by both target-site and metabolic mechanisms. Anopheles funestus s.s. was largely resistant to pyrethroids and carbamates, with potential resistance to DDT in two locations. The resistant phenotypes were conferred by elevated levels of cytochrome p450s. Conclusions/Significance Currently, the Zambia National Malaria Control Centre is using these results to inform their vector control strategy. The methods employed here can serve as a template to all malaria-endemic countries striving to create a sustainable insecticide resistance management plan. PMID:24932861

Stages of Change for Voluntary Medical Male Circumcision and Sexual Risk Behavior in Uncircumcised Zambian Men: The Spear and Shield Project.

PubMed

Redding, Colleen A; Jones, Deborah; Zulu, Robert; Chitalu, Ndashi; Cook, Ryan; Weiss, Stephen M

2015-12-01

Dissemination and scale up of voluntary medical male circumcision (VMMC) programs is well supported by evidence that VMMC reduces HIV risk in populations with high HIV prevalence and low rates of circumcision, as is the case in Zambia. At both individual and population levels, it is important to understand what stages of change for VMMC are associated with, especially across cultures. This study evaluated VMMC knowledge, misinformation, and stages of change for VMMC of uncircumcised men and boys (over 18 years), as well as the concurrent relationship between VMMC stages of change and sexual risk behaviors. Uncircumcised (N = 800) adult men and boys (over 18) were screened and recruited from urban community health centers in Lusaka, Zambia, where they then completed baseline surveys assessing knowledge, attitudes, HIV risk behaviors, and stages of change for VMMC. A series of analyses explored cross-sectional relationships among these variables. VMMC was culturally acceptable in half of the sample; younger, unmarried, and more educated men were more ready to undergo VMMC. Stage of change for VMMC was also related to knowledge, and those at greater HIV risk reported greater readiness to undergo VMMC. Efforts to increase VMMC uptake should address the role of perceived HIV risk, risk behaviors, readiness, accurate knowledge, cultural acceptance, and understanding of the significant degree of HIV protection conferred as part of the VMMC decision making process. These results support incorporating comprehensive HIV risk reduction in VMMC promotion programs.

Economic Justification Of Robust Or Adaptive Planning And Design Of Resilient Water Resources Systems Under Deep Uncertainty: A Case Study In The Iolanda Water Treatment Plant Of Lusaka, Zambia

NASA Astrophysics Data System (ADS)

Mendoza, G.; Tkach, M.; Kucharski, J.; Chaudhry, R.

2017-12-01

This discussion is focused around the application of a bottom-up vulnerability assessment procedure for planning of climate resilience to a water treament plant for teh city of Iolanda, Zambia. This project is a Millennium Challenge Corporation (MCC) innitiaive with technical support by the UNESCO category II, International Center for Integrated Water Resources Management (ICIWaRM) with secretariat at the US Army Corps of Engineers Institute for Water Resources. The MCC is an innovative and independent U.S. foreign aid agency that is helping lead the fight against global poverty. The bottom-up vulnerability assessmentt framework examines critical performance thresholds, examines the external drivers that would lead to failure, establishes plausibility and analytical uncertainty that would lead to failure, and provides the economic justification for robustness or adaptability. This presentation will showcase the experiences in the application of the bottom-up framework to a region that is very vulnerable to climate variability, has poor instituional capacities, and has very limited data. It will illustrate the technical analysis and a decision process that led to a non-obvious climate robust solution. Most importantly it will highlight the challenges of utilizing discounted cash flow analysis (DCFA), such as net present value, in justifying robust or adaptive solutions, i.e. comparing solution under different future risks. We highlight a solution to manage the potential biases these DCFA procedures can incur.

Application of Decision Tree to Obtain Optimal Operation Rules for Reservoir Flood Control Considering Sediment Desilting-Case Study of Tseng Wen Reservoir

NASA Astrophysics Data System (ADS)

ShiouWei, L.

2014-12-01

Reservoirs are the most important water resources facilities in Taiwan.However,due to the steep slope and fragile geological conditions in the mountain area,storm events usually cause serious debris flow and flood,and the flood then will flush large amount of sediment into reservoirs.The sedimentation caused by flood has great impact on the reservoirs life.Hence,how to operate a reservoir during flood events to increase the efficiency of sediment desilting without risk the reservoir safety and impact the water supply afterward is a crucial issue in Taiwan. 　Therefore,this study developed a novel optimization planning model for reservoir flood operation considering flood control and sediment desilting,and proposed easy to use operating rules represented by decision trees.The decision trees rules have considered flood mitigation,water supply and sediment desilting.The optimal planning model computes the optimal reservoir release for each flood event that minimum water supply impact and maximum sediment desilting without risk the reservoir safety.Beside the optimal flood operation planning model,this study also proposed decision tree based flood operating rules that were trained by the multiple optimal reservoir releases to synthesis flood scenarios.The synthesis flood scenarios consists of various synthesis storm events,reservoir's initial storage and target storages at the end of flood operating. 　Comparing the results operated by the decision tree operation rules(DTOR) with that by historical operation for Krosa Typhoon in 2007,the DTOR removed sediment 15.4% more than that of historical operation with reservoir storage only8.38×106m3 less than that of historical operation.For Jangmi Typhoon in 2008,the DTOR removed sediment 24.4% more than that of historical operation with reservoir storage only 7.58×106m3 less than that of historical operation.The results show that the proposed DTOR model can increase the sediment desilting efficiency and extend the reservoir life.

Propensity score estimation: neural networks, support vector machines, decision trees (CART), and meta-classifiers as alternatives to logistic regression.

PubMed

Westreich, Daniel; Lessler, Justin; Funk, Michele Jonsson

2010-08-01

Propensity scores for the analysis of observational data are typically estimated using logistic regression. Our objective in this review was to assess machine learning alternatives to logistic regression, which may accomplish the same goals but with fewer assumptions or greater accuracy. We identified alternative methods for propensity score estimation and/or classification from the public health, biostatistics, discrete mathematics, and computer science literature, and evaluated these algorithms for applicability to the problem of propensity score estimation, potential advantages over logistic regression, and ease of use. We identified four techniques as alternatives to logistic regression: neural networks, support vector machines, decision trees (classification and regression trees [CART]), and meta-classifiers (in particular, boosting). Although the assumptions of logistic regression are well understood, those assumptions are frequently ignored. All four alternatives have advantages and disadvantages compared with logistic regression. Boosting (meta-classifiers) and, to a lesser extent, decision trees (particularly CART), appear to be most promising for use in the context of propensity score analysis, but extensive simulation studies are needed to establish their utility in practice. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Type 2 Diabetes Mellitus Screening and Risk Factors Using Decision Tree: Results of Data Mining.

PubMed

Habibi, Shafi; Ahmadi, Maryam; Alizadeh, Somayeh

2015-03-18

The aim of this study was to examine a predictive model using features related to the diabetes type 2 risk factors. The data were obtained from a database in a diabetes control system in Tabriz, Iran. The data included all people referred for diabetes screening between 2009 and 2011. The features considered as "Inputs" were: age, sex, systolic and diastolic blood pressure, family history of diabetes, and body mass index (BMI). Moreover, we used diagnosis as "Class". We applied the "Decision Tree" technique and "J48" algorithm in the WEKA (3.6.10 version) software to develop the model. After data preprocessing and preparation, we used 22,398 records for data mining. The model precision to identify patients was 0.717. The age factor was placed in the root node of the tree as a result of higher information gain. The ROC curve indicates the model function in identification of patients and those individuals who are healthy. The curve indicates high capability of the model, especially in identification of the healthy persons. We developed a model using the decision tree for screening T2DM which did not require laboratory tests for T2DM diagnosis.

Structural adjustment and drought in Zambia.

PubMed

Mulwanda, M

1995-06-01

While drought is not uncommon in Zambia, the country is now facing the worst drought in history. The monetary and social costs will be enormous. Although it is too early to measure the economic and social costs of the drought on Zambia, it is obvious that the impact is catastrophic on a country whose economy is under pressure. The drought will affect the structural adjustment programme (SAP) unveiled by the new government which has embraced the market economy. The country has imported, and will continue to import, large quantities of maize and other foodstuffs, a situation likely to strain the balance of payments. Earlier targets with regard to export earnings, reductions in the budget deficit, and GDP growth as contained in the Policy Framework Paper (PFP) are no longer attainable due to the effects of the drought.

Predicting the disease of Alzheimer with SNP biomarkers and clinical data using data mining classification approach: decision tree.

PubMed

Erdoğan, Onur; Aydin Son, Yeşim

2014-01-01

Single Nucleotide Polymorphisms (SNPs) are the most common genomic variations where only a single nucleotide differs between individuals. Individual SNPs and SNP profiles associated with diseases can be utilized as biological markers. But there is a need to determine the SNP subsets and patients' clinical data which is informative for the diagnosis. Data mining approaches have the highest potential for extracting the knowledge from genomic datasets and selecting the representative SNPs as well as most effective and informative clinical features for the clinical diagnosis of the diseases. In this study, we have applied one of the widely used data mining classification methodology: "decision tree" for associating the SNP biomarkers and significant clinical data with the Alzheimer's disease (AD), which is the most common form of "dementia". Different tree construction parameters have been compared for the optimization, and the most accurate tree for predicting the AD is presented.

Pricing and reimbursement frameworks in Central Eastern Europe: a decision tool to support choices.

PubMed

Kolasa, Katarzyna; Kalo, Zoltan; Hornby, Edward

2015-02-01

Given limited financial resources in the Central Eastern European (CEE) region, challenges in obtaining access to innovative medical technologies are formidable. The objective of this research was to develop a decision tree that supports decision makers and drug manufacturers from CEE region in their search for optimal innovative pricing and reimbursement scheme (IPRSs). A systematic literature review was performed to search for published IPRSs, and then ten experts from the CEE region were interviewed to ascertain their opinions on these schemes. In total, 33 articles representing 46 unique IPRSs were analyzed. Based on our literature review and subsequent expert input, key decision nodes and branches of the decision tree were developed. The results indicate that outcome-based schemes are better suited to deal with uncertainties surrounding cost effectiveness, while non-outcome-based schemes are more appropriate for pricing and budget impact challenges.

Development and Validation of a Primary Care-Based Family Health History and Decision Support Program (MeTree)

PubMed Central

Orlando, Lori A.; Buchanan, Adam H.; Hahn, Susan E.; Christianson, Carol A.; Powell, Karen P.; Skinner, Celette Sugg; Chesnut, Blair; Blach, Colette; Due, Barbara; Ginsburg, Geoffrey S.; Henrich, Vincent C.

2016-01-01

INTRODUCTION Family health history is a strong predictor of disease risk. To reduce the morbidity and mortality of many chronic diseases, risk-stratified evidence-based guidelines strongly encourage the collection and synthesis of family health history to guide selection of primary prevention strategies. However, the collection and synthesis of such information is not well integrated into clinical practice. To address barriers to collection and use of family health histories, the Genomedical Connection developed and validated MeTree, a Web-based, patient-facing family health history collection and clinical decision support tool. MeTree is designed for integration into primary care practices as part of the genomic medicine model for primary care. METHODS We describe the guiding principles, operational characteristics, algorithm development, and coding used to develop MeTree. Validation was performed through stakeholder cognitive interviewing, a genetic counseling pilot program, and clinical practice pilot programs in 2 community-based primary care clinics. RESULTS Stakeholder feedback resulted in changes to MeTree’s interface and changes to the phrasing of clinical decision support documents. The pilot studies resulted in the identification and correction of coding errors and the reformatting of clinical decision support documents. MeTree’s strengths in comparison with other tools are its seamless integration into clinical practice and its provision of action-oriented recommendations guided by providers’ needs. LIMITATIONS The tool was validated in a small cohort. CONCLUSION MeTree can be integrated into primary care practices to help providers collect and synthesize family health history information from patients with the goal of improving adherence to risk-stratified evidence-based guidelines. PMID:24044145

Detection of clinical mastitis with sensor data from automatic milking systems is improved by using decision-tree induction.

PubMed

Kamphuis, C; Mollenhorst, H; Heesterbeek, J A P; Hogeveen, H

2010-08-01

The objective was to develop and validate a clinical mastitis (CM) detection model by means of decision-tree induction. For farmers milking with an automatic milking system (AMS), it is desirable that the detection model has a high level of sensitivity (Se), especially for more severe cases of CM, at a very high specificity (Sp). In addition, an alert for CM should be generated preferably at the quarter milking (QM) at which the CM infection is visible for the first time. Data were collected from 9 Dutch dairy herds milking automatically during a 2.5-yr period. Data included sensor data (electrical conductivity, color, and yield) at the QM level and visual observations of quarters with CM recorded by the farmers. Visual observations of quarters with CM were combined with sensor data of the most recent automatic milking recorded for that same quarter, within a 24-h time window before the visual assessment time. Sensor data of 3.5 million QM were collected, of which 348 QM were combined with a CM observation. Data were divided into a training set, including two-thirds of all data, and a test set. Cows in the training set were not included in the test set and vice versa. A decision-tree model was trained using only clear examples of healthy (n=24,717) or diseased (n=243) QM. The model was tested on 105 QM with CM and a random sample of 50,000 QM without CM. While keeping the Se at a level comparable to that of models currently used by AMS, the decision-tree model was able to decrease the number of false-positive alerts by more than 50%. At an Sp of 99%, 40% of the CM cases were detected. Sixty-four percent of the severe CM cases were detected and only 12.5% of the CM that were scored as watery milk. The Se increased considerably from 40% to 66.7% when the time window increased from less than 24h before the CM observation, to a time window from 24h before to 24h after the CM observation. Even at very wide time windows, however, it was impossible to reach an Se of 100%. This indicates the inability to detect all CM cases based on sensor data alone. Sensitivity levels varied largely when the decision tree was validated per herd. This trend was confirmed when decision trees were trained using data from 8 herds and tested on data from the ninth herd. This indicates that when using the decision tree as a generic CM detection model in practice, some herds will continue having difficulties in detecting CM using mastitis alert lists, whereas others will perform well. Copyright (c) 2010 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Predicting post-fire tree mortality for 12 western US conifers using the First-Order Fire Effects Model (FOFEM)

Treesearch

Sharon Hood; Duncan Lutes

2017-01-01

Accurate prediction of fire-caused tree mortality is critical for making sound land management decisions such as developing burning prescriptions and post-fire management guidelines. To improve efforts to predict post-fire tree mortality, we developed 3-year post-fire mortality models for 12 Western conifer species - white fir (Abies concolor [Gord. &...

Context-Sensitive Ethics in School Psychology

ERIC Educational Resources Information Center

Lasser, Jon; Klose, Laurie McGarry; Robillard, Rachel

2013-01-01

Ethical codes and licensing rules provide foundational guidance for practicing school psychologists, but these sources fall short in their capacity to facilitate effective decision-making. When faced with ethical dilemmas, school psychologists can turn to decision-making models, but step-wise decision trees frequently lack the situation…

Study and ranking of determinants of Taenia solium infections by classification tree models.

PubMed

Mwape, Kabemba E; Phiri, Isaac K; Praet, Nicolas; Dorny, Pierre; Muma, John B; Zulu, Gideon; Speybroeck, Niko; Gabriël, Sarah

2015-01-01

Taenia solium taeniasis/cysticercosis is an important public health problem occurring mainly in developing countries. This work aimed to study the determinants of human T. solium infections in the Eastern province of Zambia and rank them in order of importance. A household (HH)-level questionnaire was administered to 680 HHs from 53 villages in two rural districts and the taeniasis and cysticercosis status determined. A classification tree model (CART) was used to define the relative importance and interactions between different predictor variables in their effect on taeniasis and cysticercosis. The Katete study area had a significantly higher taeniasis and cysticercosis prevalence than the Petauke area. The CART analysis for Katete showed that the most important determinant for cysticercosis infections was the number of HH inhabitants (6 to 10) and for taeniasis was the number of HH inhabitants > 6. The most important determinant in Petauke for cysticercosis was the age of head of household > 32 years and for taeniasis it was age < 55 years. The CART analysis showed that the most important determinant for both taeniasis and cysticercosis infections was the number of HH inhabitants (6 to 10) in Katete district and age in Petauke. The results suggest that control measures should target HHs with a high number of inhabitants and older individuals. © The American Society of Tropical Medicine and Hygiene.

Gender, British Administration and Mission Management of Education in Zambia 1900-1939

ERIC Educational Resources Information Center

Allen, Julia

2010-01-01

This article discusses the impact of including gender in the analytical framework in a study of the management and provision of education in Zambia from 1900 to 1939. It shows that a focus on gender allows females to enter the historical narrative and the leadership of women such as Mabel Shaw, Hannah Frances Davidson and Julia Smith can be given…

Beyond Time: Temporal and Extra-Temporal Functions of Tense and Aspect Marking in Totela, a Bantu Language of Zambia

ERIC Educational Resources Information Center

Crane, Thera Marie

2011-01-01

This dissertation aims to characterize the relationship between the temporal and information-structuring functions of tense and aspect marking in Totela, an endangered Bantu language of Zambia and Namibia. To that end, I investigate and describe in detail the semantics and pragmatics of selected tense and aspect markers, showing for each that a…

Two new planthopper species (Hemiptera, Fulgoroidea, Caliscelidae) collected in pitfall traps in Zambia.

PubMed

Chmurova, Lucia; Webb, Michael D

2016-08-22

Two new species of planthoppers in the family Caliscelidae (Hemiptera: Fulgoroidea) are described from Zambia, i.e., Afronaso spinosa sp. n. and Calampocus zambiaensis sp. n. All specimens are flightless males and nearly all were collected from baited pitfall traps (except for one specimen collected from a yellow pan trap), suggesting that they live near to or on the ground.

An Investigation into Challenges Faced by Secondary School Teachers and Pupils in Algebraic Linear Equations: A Case of Mufulira District, Zambia

ERIC Educational Resources Information Center

Samuel, Koji; Mulenga, H. M.; Angel, Mukuka

2016-01-01

This paper investigates the challenges faced by secondary school teachers and pupils in the teaching and learning of algebraic linear equations. The study involved 80 grade 11 pupils and 15 teachers of mathematics, drawn from 4 selected secondary schools in Mufulira district, Zambia in Central Africa. A descriptive survey method was employed to…

Factors Associated with School Teachers' Perceived Needs and Level of Adoption of HIV Prevention Education in Lusaka, Zambia

ERIC Educational Resources Information Center

Henning, Margaret; Chi, Chunheui; Khanna, Sunil K.

2011-01-01

Objective: The purpose of this study was to evaluate the socio-cultural variables that may influence teachers' adoption of classroom-based HIV/AIDS education within the school setting and among school types in Zambia's Lusaka Province. Method: Mixed methods were used to collect original data. Using semi-structured interviews (n=11) and a survey…

Network Models of Entrepreneurial Ecosystems in Developing Economies

DTIC Science & Technology

2014-01-01

Department of Mathematical Sciences, U.S. Military Academy Candice Price , Ph.D. , Department of Mathematical Sciences, U.S. Military Academy NOTICES...methodology. “Youth unemployment is a ticking time bomb,” –Alexander Chikwanda, Finance Minister, Zambia Protesters in Tahrir Square, Cairo...with the recent political and social changes in the region, only contributes to this high unemployment rate. As the Finance Minister of Zambia stated

Adherence to antiretroviral therapy (ART) during the early months of treatment in rural Zambia: influence of demographic characteristics and social surroundings of patients

PubMed Central

2012-01-01

Background Around 70% of those living with HIV in need of treatment accessed antiretroviral therapy (ART) in Zambia by 2009. However, sustaining high levels of adherence to ART is a challenge. This study aimed to identify the predictive factors associated with ART adherence during the early months of treatment in rural Zambia. Methods This is a field based observational longitudinal study in Mumbwa district, which is located 150 km west of Lusaka, the capital of Zambia. Treatment naive patients aged over 15 years, who initiated treatment during September-November 2010, were enrolled. Patients were interviewed at the initiation and six weeks later. The treatment adherence was measured according to self-reporting by the patients. Multiple logistic regression analysis was performed to identify the predictive factors associated with the adherence. Results Of 157 patients, 59.9% were fully adherent to the treatment six weeks after starting ART. According to the multivariable analysis, full adherence was associated with being female [Adjusted Odds Ratio (AOR), 3.3; 95% Confidence interval (CI), 1.2-8.9], having a spouse who were also on ART (AOR, 4.4; 95% CI, 1.5-13.1), and experience of food insufficiency in the previous 30 days (AOR, 5.0; 95% CI, 1.8-13.8). Some of the most common reasons for missed doses were long distance to health facilities (n = 21, 53.8%), food insufficiency (n = 20, 51.3%), and being busy with other activities such as work (n = 15, 38.5%). Conclusions The treatment adherence continues to be a significant challenge in rural Zambia. Social supports from spouses and people on ART could facilitate their treatment adherence. This is likely to require attention by ART services in the future, focusing on different social influences on male and female in rural Zambia. In addition, poverty reduction strategies may help to reinforce adherence to ART and could mitigate the influence of HIV infection for poor patients and those who fall into poverty after starting ART. PMID:23270312

Agriculture expansion, wood energy and woody encroachment in the Miombo woodlands: striving towards sustainability in Zambia.

NASA Astrophysics Data System (ADS)

Pelletier, J.

2017-12-01

Agricultural expansion is mostly done at the expense of forests and woodlands in the tropics. In Sub-Saharan Africa, forests are also critical as providers of wood energy for domestic consumption with a clear majority of households depending on firewood and charcoal as primary source of energy. Using Zambia as a case study, we look at the link between agricultural expansion, wood energy and the sustainability of forest resources. Zambia has been identified as having one of the highest rates of deforestation in the world, but there is large uncertainty in these estimates. The government of Zambia has identified charcoal production as one of the main of drivers of forest cover loss and is targeting this practice in their national strategy for reducing emissions from deforestation and forest degradation (REDD+). Other assessment however indicate that agricultural expansion is by far the main driver of deforestation and charcoal production is sustainable in Zambia. These competing evaluations call for a better understanding of the drivers of change. Using two national-scale vegetation surveys and remote sensing data, we compare and validate historical forest cover loss estimates to improve their accuracy. We attribute the change and their associated emissions to specific drivers of deforestation. The ecological properties of areas under change are compared to stable areas over time. Our results from national permanent plots indicate a woody encroachment process in Zambia, a potential ecological response to rising CO2 levels. We found that despite large emissions from deforestation, forests and woodlands have been acting as a carbon sink. This research addresses directly the potential feedbacks and responses to competing demands on forests coming from different sectors, including for agriculture and energy, to set the baseline on which to evaluate forest sustainability now and in the future given potentially new ecological conditions. It provides policy relevant information on drivers of deforestation for orienting the policy response for transitioning towards a low-carbon development pathway, ensuring food security and securing livelihood needs in sustainable wood energy.

Branch: an interactive, web-based tool for testing hypotheses and developing predictive models.

PubMed

Gangavarapu, Karthik; Babji, Vyshakh; Meißner, Tobias; Su, Andrew I; Good, Benjamin M

2016-07-01

Branch is a web application that provides users with the ability to interact directly with large biomedical datasets. The interaction is mediated through a collaborative graphical user interface for building and evaluating decision trees. These trees can be used to compose and test sophisticated hypotheses and to develop predictive models. Decision trees are built and evaluated based on a library of imported datasets and can be stored in a collective area for sharing and re-use. Branch is hosted at http://biobranch.org/ and the open source code is available at http://bitbucket.org/sulab/biobranch/ asu@scripps.edu or bgood@scripps.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Block-Based Connected-Component Labeling Algorithm Using Binary Decision Trees

PubMed Central

Chang, Wan-Yu; Chiu, Chung-Cheng; Yang, Jia-Horng

2015-01-01

In this paper, we propose a fast labeling algorithm based on block-based concepts. Because the number of memory access points directly affects the time consumption of the labeling algorithms, the aim of the proposed algorithm is to minimize neighborhood operations. Our algorithm utilizes a block-based view and correlates a raster scan to select the necessary pixels generated by a block-based scan mask. We analyze the advantages of a sequential raster scan for the block-based scan mask, and integrate the block-connected relationships using two different procedures with binary decision trees to reduce unnecessary memory access. This greatly simplifies the pixel locations of the block-based scan mask. Furthermore, our algorithm significantly reduces the number of leaf nodes and depth levels required in the binary decision tree. We analyze the labeling performance of the proposed algorithm alongside that of other labeling algorithms using high-resolution images and foreground images. The experimental results from synthetic and real image datasets demonstrate that the proposed algorithm is faster than other methods. PMID:26393597

Event Classification and Identification Based on the Characteristic Ellipsoid of Phasor Measurement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, Jian; Diao, Ruisheng; Makarov, Yuri V.

2011-09-23

In this paper, a method to classify and identify power system events based on the characteristic ellipsoid of phasor measurement is presented. The decision tree technique is used to perform the event classification and identification. Event types, event locations and clearance times are identified by decision trees based on the indices of the characteristic ellipsoid. A sufficiently large number of transient events were simulated on the New England 10-machine 39-bus system based on different system configurations. Transient simulations taking into account different event types, clearance times and various locations are conducted to simulate phasor measurement. Bus voltage magnitudes and recordedmore » reactive and active power flows are used to build the characteristic ellipsoid. The volume, eccentricity, center and projection of the longest axis in the parameter space coordinates of the characteristic ellipsoids are used to classify and identify events. Results demonstrate that the characteristic ellipsoid and the decision tree are capable to detect the event type, location, and clearance time with very high accuracy.« less

Online adaptive decision trees: pattern classification and function approximation.

PubMed

Basak, Jayanta

2006-09-01

Recently we have shown that decision trees can be trained in the online adaptive (OADT) mode (Basak, 2004), leading to better generalization score. OADTs were bottlenecked by the fact that they are able to handle only two-class classification tasks with a given structure. In this article, we provide an architecture based on OADT, ExOADT, which can handle multiclass classification tasks and is able to perform function approximation. ExOADT is structurally similar to OADT extended with a regression layer. We also show that ExOADT is capable not only of adapting the local decision hyperplanes in the nonterminal nodes but also has the potential of smoothly changing the structure of the tree depending on the data samples. We provide the learning rules based on steepest gradient descent for the new model ExOADT. Experimentally we demonstrate the effectiveness of ExOADT in the pattern classification and function approximation tasks. Finally, we briefly discuss the relationship of ExOADT with other classification models.

A hybrid method for classifying cognitive states from fMRI data.

PubMed

Parida, S; Dehuri, S; Cho, S-B; Cacha, L A; Poznanski, R R

2015-09-01

Functional magnetic resonance imaging (fMRI) makes it possible to detect brain activities in order to elucidate cognitive-states. The complex nature of fMRI data requires under-standing of the analyses applied to produce possible avenues for developing models of cognitive state classification and improving brain activity prediction. While many models of classification task of fMRI data analysis have been developed, in this paper, we present a novel hybrid technique through combining the best attributes of genetic algorithms (GAs) and ensemble decision tree technique that consistently outperforms all other methods which are being used for cognitive-state classification. Specifically, this paper illustrates the combined effort of decision-trees ensemble and GAs for feature selection through an extensive simulation study and discusses the classification performance with respect to fMRI data. We have shown that our proposed method exhibits significant reduction of the number of features with clear edge classification accuracy over ensemble of decision-trees.

Application of the pessimistic pruning to increase the accuracy of C4.5 algorithm in diagnosing chronic kidney disease

NASA Astrophysics Data System (ADS)

Muslim, M. A.; Herowati, A. J.; Sugiharti, E.; Prasetiyo, B.

2018-03-01

A technique to dig valuable information buried or hidden in data collection which is so big to be found an interesting patterns that was previously unknown is called data mining. Data mining has been applied in the healthcare industry. One technique used data mining is classification. The decision tree included in the classification of data mining and algorithm developed by decision tree is C4.5 algorithm. A classifier is designed using applying pessimistic pruning in C4.5 algorithm in diagnosing chronic kidney disease. Pessimistic pruning use to identify and remove branches that are not needed, this is done to avoid overfitting the decision tree generated by the C4.5 algorithm. In this paper, the result obtained using these classifiers are presented and discussed. Using pessimistic pruning shows increase accuracy of C4.5 algorithm of 1.5% from 95% to 96.5% in diagnosing of chronic kidney disease.

The economic impact of pig-associated parasitic zoonosis in Northern Lao PDR.

PubMed

Choudhury, Adnan Ali Khan; Conlan, James V; Racloz, Vanessa Nadine; Reid, Simon Andrew; Blacksell, Stuart D; Fenwick, Stanley G; Thompson, Andrew R C; Khamlome, Boualam; Vongxay, Khamphouth; Whittaker, Maxine

2013-03-01

The parasitic zoonoses human cysticercosis (Taenia solium), taeniasis (other Taenia species) and trichinellosis (Trichinella species) are endemic in the Lao People's Democratic Republic (Lao PDR). This study was designed to quantify the economic burden pig-associated zoonotic disease pose in Lao PDR. In particular, the analysis included estimation of the losses in the pork industry as well as losses due to human illness and lost productivity. A Markov-probability based decision-tree model was chosen to form the basis of the calculations to estimate the economic and public health impacts of taeniasis, trichinellosis and cysticercosis. Two different decision trees were run simultaneously on the model's human cohort. A third decision tree simulated the potential impacts on pig production. The human capital method was used to estimate productivity loss. The results found varied significantly depending on the rate of hospitalisation due to neurocysticerosis. This study is the first systematic estimate of the economic impact of pig-associated zoonotic diseases in Lao PDR that demonstrates the significance of the diseases in that country.

Antimicrobial Resistant Enteropathogenic Escherichia coli and Salmonella spp. in Houseflies Infesting Fish in Food Markets in Zambia

PubMed Central

Songe, Mwansa M.; Hang’ombe, Bernard M.; Knight-Jones, Theodore J. D.; Grace, Delia

2016-01-01

Diarrhea is one of the most common diseases and is a leading cause of death in developing countries. This is often caused by contaminated food. Poor food hygiene standards are exacerbated by the presence of flies which can transmit a variety of infectious microorganisms, particularly through animal source foods. This fact becomes especially important in developing countries like Zambia, where fish is a highly valued source of protein. Our interest in this study was to identify if the flies that beset food markets in Zambia carry important pathogenic bacteria on their bodies, and subsequently if these bacteria carry resistance genes to commonly used antibiotics, which would indicate problems in eradicating these pathogens. The present study took into account fish vendors’ and consumers’ perception of flies and interest in interventions to reduce their numbers. We conducted semi-structured interviews with (1) traders (comprised of randomly selected males and females) and (2) consumers (including randomly selected males and females). Thereafter, we collected flies found on fish in markets in Mongu and Lusaka districts of Zambia. For the entire study, a total of 418 fly samples were analyzed in the laboratory and Salmonella spp. and enteropathogenic Escherichia coli were isolated from the flies. Further laboratory screening revealed that overall, 17.2% (72/418) (95% CI; 43.2%–65.5%) of total samples analyzed contained Extended-Spectrum Beta-Lactamase (ESBL)-producing E. coli. These significant findings call for a strengthening of the antibiotic administering policy in Zambia and the development of sustainable interventions to reduce fly numbers in food markets and improve food safety and hygiene. PMID:28036049

AIDS education for a low literate audience in Zambia.

PubMed

Msimuko, A K

1988-04-01

A workshop funded by the USA Program for Appropriate Technology in Health (PATH) was an effort by Zambia toward prevention and control of AIDS. The lack of educational materials about AIDS for a low-literate audience was the major problem addressed by the workshop. Other problems include the lack of collaborative effort in the development of materials on AIDS, and the lack of skills needed in the development of such materials in Zambia. 1 of the objectives of the workshop was to launch the Planned Parenthood Association of Zambia's (PPAZ) materials development project. The scope of this project includes the production of educational materials on AIDS for low-literate audiences and a counseling handbook for family planning workers. Print materials should be simply written, using words, idioms, and graphics that are familiar to the target audience. Other workshop objectives included the establishment of collaborative relationships between organizations involved in existing AIDS educational activities in Zambia, and the development of practical skills needed to produce print materials. Education was identified as the most important strategy for the prevention and control of AIDS, and PPAZ should be the executing agency of the print materials project. Audience research, using focus group techniques, focus group discussions, behavioral messages, and pretesting of messages, should be the most effective means of reaching targeted audiences. PPAZ is contracted by PATH to begin development of educational materials, and 2 committees have formed to implement the project and to establish interagency collaboration. Audience research was begun between January and March of 1988, focusing on people's beliefs, practices, and ideas about AIDS. The final phase of the project will be the printing, distribution, and use of the AIDS materials and the training of family planning field workers in the proper use of these materials.

Investment Incentives and the Implementation of the Framework Convention on Tobacco Control: Evidence from Zambia

PubMed Central

Drope, Jeffrey; Labonte, Ronald; Zulu, Richard; Goma, Fastone

2016-01-01

Purpose Policy misalignment across different sectors of government serves as one of the pivotal barriers to WHO Framework convention on Tobacco Control (FCTC) implementation. This paper examines the logic used by government officials to justify providing investment incentives to increase tobacco processing and manufacturing in the context of FCTC implementation in Zambia. Methods We conducted qualitative semi-structured interviews with key informants from government, civil society and intergovernmental economic organizations (n=23). We supplemented the interview data with an analysis of public documents pertaining to economic development policy in Zambia. Results We found gross misalignments between the policies of the economic sector and efforts to implement the provisions of the FCTC. Our interviews uncovered the rationale used by officials in the economic sector to justify providing economic incentives to bolster tobacco processing and manufacturing in Zambia: 1) tobacco is not consumed by Zambians/tobacco is an export commodity, 2) economic benefits outweigh health costs, and 3) tobacco consumption is a personal choice. Conclusions Much of the struggle Zambia has experienced implementing the FCTC can be attributed to misalignments between the economic and health sectors. Zambia’s development agenda seeks to bolster agricultural processing and manufacturing. Tobacco control proponents must understand and work within this context of economic development in order to foster productive strategies with those working on tobacco supply issues. These findings are broadly applicable to the global analysis on the barriers and facilitators of FCTC implementation. It is important that the Ministry of Health monitors the tobacco policy of other sectors and engages with these sectors to find ways of harmonizing FCTC implementation across sectors. PMID:26135987

Outbreak of Plague in a High Malaria Endemic Region - Nyimba District, Zambia, March-May 2015.

PubMed

Sinyange, Nyambe; Kumar, Ramya; Inambao, Akatama; Moonde, Loveness; Chama, Jonathan; Banda, Mapopa; Tembo, Elliot; Nsonga, Beron; Mwaba, John; Fwoloshi, Sombo; Musokotwane, Kebby; Chizema, Elizabeth; Kapin'a, Muzala; Hang'ombe, Benard Mudenda; Baggett, Henry C; Hachaambwa, Lottie

2016-08-12

Outbreaks of plague have been recognized in Zambia since 1917 (1). On April 10, 2015, Zambia's Ministry of Health was notified by the Eastern Provincial Medical Office of possible bubonic plague cases in Nyimba District. Eleven patients with acute fever and cervical lymphadenopathy had been evaluated at two rural health centers during March 28-April 9, 2015; three patients died. To confirm the outbreak and develop control measures, the Zambia Ministry of Health's Field Epidemiology Training Program (ZFETP) conducted epidemiologic and laboratory investigations in partnership with the University of Zambia's schools of Medicine and Veterinary Medicine and the provincial and district medical offices. Twenty-one patients with clinically compatible plague were identified, with symptom onset during March 26-May 5, 2015. The median age was 8 years, and all patients were from the same village. Blood specimens or lymph node aspirates from six (29%) patients tested positive for Yersinia pestis by polymerase chain reaction (PCR). There is an urgent need to improve early identification and treatment of plague cases. PCR is a potential complementary tool for identifying plague, especially in areas with limited microbiologic capacity. Twelve (57%) patients, including all six with PCR-positive plague and all three who died, also tested positive for malaria by rapid diagnostic test (RDT). Plague patients coinfected with malaria might be misdiagnosed as solely having malaria, and appropriate antibacterial treatment to combat plague might not be given, increasing risk for mortality. Because patients with malaria might be coinfected with other pathogens, broad spectrum antibiotic treatment to cover other pathogens is recommended for all children with severe malaria, until a bacterial infection is excluded.

Prevalence and predictors of squamous intraepithelial lesions of the cervix in HIV-infected women in Lusaka, Zambia

PubMed Central

Parham, Groesbeck P.; Sahasrabuddhe, Vikrant V.; Mwanahamuntu, Mulindi H.; Shepherd, Bryan E.; Hicks, Michael L.; Stringer, Elizabeth M.; Vermund, Sten H.

2009-01-01

Objectives HIV-infected women living in resource-constrained nations like Zambia are now accessing antiretroviral therapy and thus may live long enough for HPV-induced cervical cancer to manifest and progress. We evaluated the prevalence and predictors of cervical squamous intraepithelial lesions (SIL) among HIV-infected women in Zambia. Methods We screened 150 consecutive, non-pregnant HIV-infected women accessing HIV/AIDS care services in Lusaka, Zambia. We collected cervical specimens for cytological analysis by liquid-based monolayer cytology (ThinPrep Pap Test®) and HPV typing using the Roche Linear Array® PCR assay. Results The median age of study participants was 36 years (range 23-49 years) and their median CD4+ count was 165/μL (range 7-942). The prevalence of SIL on cytology was 76% (114/150), of which 23.3% (35/150) women had low-grade SIL, 32.6% (49/150) had high-grade SIL, and 20% (30/150) had lesions suspicious for squamous cell carcinoma (SCC). High-risk HPV types were present in 85.3% (128/150) women. On univariate analyses, age of the participant, CD4+ cell count, and presence of any high-risk HPV type were significantly associated with the presence of severely abnormal cytological lesions (i.e., high-grade SIL and lesions suspicious for SCC). Multivariable logistic regression modeling suggested the presence of any high-risk HPV type as an independent predictor of severely abnormal cytology (adjusted OR: 12.4, 95% CI 2.62-58.1, p=0.02). Conclusions The high prevalence of abnormal squamous cytology in our study is one of the highest reported in any population worldwide. Screening of HIV-infected women in resource-constrained settings like Zambia should be implemented to prevent development of HPV-induced SCC. PMID:16875716

Taenia solium from a community perspective: Preliminary costing data in the Katete and Sinda districts in Eastern Zambia.

PubMed

Hobbs, Emma C; Mwape, Kabemba E; Devleesschauwer, Brecht; Gabriël, Sarah; Chembensofu, Mwelwa; Mambwe, Moses; Phiri, Isaac K; Masuku, Maxwell; Zulu, Gideon; Colston, Angela; Willingham, Arve Lee; Berkvens, Dirk; Dorny, Pierre; Bottieau, Emmanuel; Speybroeck, Niko

2018-02-15

The tapeworm Taenia solium is endemic in Zambia, however its socioeconomic cost is unknown. During a large-scale interventional study conducted in Zambia, baseline economic costs of human and porcine T. solium infections were measured. Questionnaire surveys were conducted within three neighbourhoods in Zambia's Eastern province in 2015 and 2016. A human health questionnaire, capturing costs of clinical symptoms commonly attributable to human cysticercosis and taeniasis, was conducted in randomly selected households (n = 267). All pig-keeping households were administered a pig socioeconomic questionnaire (n = 271) that captured pig demographic data, costs of pig-keeping, and economic losses from porcine cysticercosis. Of all respondents 62% had reportedly experienced at least one of the surveyed symptoms. Seizure-like episodes were reported by 12%, severe chronic headaches by 36%, and vision problems by 23% of respondents. These complaints resulted in 147 health care consultations and 17 hospitalizations in the five years preceding the study, and an estimated productivity loss of 608 working days per year. Of all pigs 69% were bought within villages. Nearly all adult pigs were sold to local traders, and tongue palpation for detection of cysticerci was commonly performed. Reportedly, 95% of pig owners could not sell tongue-positive pigs, while infected pigs fetched only 45% of the normal sale value. These preliminary costing data indicate that human and porcine T. solium infections substantially impact endemic areas of Eastern Zambia. A full socioeconomic burden assessment may enable improved T. solium management in sub-Saharan Africa. Copyright © 2018 Ross University School of Veterinary Medicine. Published by Elsevier B.V. All rights reserved.

Schistosomiasis in Zambia: a systematic review of past and present experiences.

PubMed

Kalinda, Chester; Chimbari, Moses J; Mukaratirwa, Samson

2018-04-30

The speedy rate of change in the environmental and socio-economics factors may increase the incidence, prevalence and risk of schistosomiasis infections in Zambia. However, available information does not provide a comprehensive understanding of the biogeography and distribution of the disease, ecology and population dynamics of intermediate host snails. The current study used an information-theoretical approach to understand the biogeography and prevalence schistosomiasis and identified knowledge gaps that would be useful to improve policy towards surveillance and eradication of intermediate hosts snails in Zambia. To summarise the existing knowledge and build on past and present experiences of schistosomiasis epidemiology for effective disease control in Zambia, a systematic search of literature for the period 2000-2017 was done on PubMed, Google Scholar and EBSCOhost. Using the key words: 'Schistosomiasis', 'Biomphalaria', 'Bulinus', 'Schistosoma mansoni', 'Schistosoma haematobium', and 'Zambia', in combination with Booleans terms 'AND' and 'OR', published reports/papers were obtained and reviewed independently for inclusion. Thirteen papers published in English that fulfilled the inclusion criteria were selected for the final review. The papers suggest that the risk of infection has increased over the years and this has been attributed to environmental, socio-economic and demographic factors. Furthermore, schistosomiasis is endemic in many parts of the country with infection due to Schistosoma haematobium being more prevalent than that due to S. mansoni. This review also found that S. haematobium was linked to genital lesions, thus increasing risks of contracting other diseases such as HIV and cervical cancer. For both S. haematobium and S. mansoni, environmental, socio-economic, and demographic factors were influential in the transmission and prevalence of the disease and highlight the need for detailed knowledge on ecological modelling and mapping the distribution of the disease and intermediate host snails for effective implementation of control strategies.

Provisioning of Game Meat to Rural Communities as a Benefit of Sport Hunting in Zambia

PubMed Central

White, Paula A.; Belant, Jerrold L.

2015-01-01

Sport hunting has reportedly multiple benefits to economies and local communities; however, few of these benefits have been quantified. As part of their lease agreements with the Zambia Wildlife Authority, sport hunting operators in Zambia are required to provide annually to local communities free of charge i.e., provision a percentage of the meat obtained through sport hunting. We characterized provisioning of game meat to rural communities by the sport hunting industry in Zambia for three game management areas (GMAs) during 2004–2011. Rural communities located within GMAs where sport hunting occurred received on average > 6,000 kgs per GMA of fresh game meat annually from hunting operators. To assess hunting industry compliance, we also compared the amount of meat expected as per the lease agreements versus observed amounts of meat provisioned from three GMAs during 2007–2009. In seven of eight annual comparisons of these GMAs, provisioning of meat exceeded what was required in the lease agreements. Provisioning occurred throughout the hunting season and peaked during the end of the dry season (September–October) coincident with when rural Zambians are most likely to encounter food shortages. We extrapolated our results across all GMAs and estimated 129,771 kgs of fresh game meat provisioned annually by the sport hunting industry to rural communities in Zambia at an approximate value for the meat alone of >US$600,000 exclusive of distribution costs. During the hunting moratorium (2013–2014), this supply of meat has halted, likely adversely affecting rural communities previously reliant on this food source. Proposed alternatives to sport hunting should consider protein provisioning in addition to other benefits (e.g., employment, community pledges, anti-poaching funds) that rural Zambian communities receive from the sport hunting industry. PMID:25693191

Provisioning of game meat to rural communities as a benefit of sport hunting in Zambia.

PubMed

White, Paula A; Belant, Jerrold L

2015-01-01

Sport hunting has reportedly multiple benefits to economies and local communities; however, few of these benefits have been quantified. As part of their lease agreements with the Zambia Wildlife Authority, sport hunting operators in Zambia are required to provide annually to local communities free of charge i.e., provision a percentage of the meat obtained through sport hunting. We characterized provisioning of game meat to rural communities by the sport hunting industry in Zambia for three game management areas (GMAs) during 2004-2011. Rural communities located within GMAs where sport hunting occurred received on average > 6,000 kgs per GMA of fresh game meat annually from hunting operators. To assess hunting industry compliance, we also compared the amount of meat expected as per the lease agreements versus observed amounts of meat provisioned from three GMAs during 2007-2009. In seven of eight annual comparisons of these GMAs, provisioning of meat exceeded what was required in the lease agreements. Provisioning occurred throughout the hunting season and peaked during the end of the dry season (September-October) coincident with when rural Zambians are most likely to encounter food shortages. We extrapolated our results across all GMAs and estimated 129,771 kgs of fresh game meat provisioned annually by the sport hunting industry to rural communities in Zambia at an approximate value for the meat alone of >US$600,000 exclusive of distribution costs. During the hunting moratorium (2013-2014), this supply of meat has halted, likely adversely affecting rural communities previously reliant on this food source. Proposed alternatives to sport hunting should consider protein provisioning in addition to other benefits (e.g., employment, community pledges, anti-poaching funds) that rural Zambian communities receive from the sport hunting industry.

An Integrated Hydro-Economic Model for Economy-Wide Climate Change Impact Assessment for Zambia

NASA Astrophysics Data System (ADS)

Zhu, T.; Thurlow, J.; Diao, X.

2008-12-01

Zambia is a landlocked country in Southern Africa, with a total population of about 11 million and a total area of about 752 thousand square kilometers. Agriculture in the country depends heavily on rainfall as the majority of cultivated land is rain-fed. Significant rainfall variability has been a huge challenge for the country to keep a sustainable agricultural growth, which is an important condition for the country to meet the United Nations Millennium Development Goals. The situation is expected to become even more complex as climate change would impose additional impacts on rainwater availability and crop water requirements, among other changes. To understand the impacts of climate variability and change on agricultural production and national economy, a soil hydrology model and a crop water production model are developed to simulate actual crop water uses and yield losses under water stress which provide annual shocks for a recursive dynamic computational general equilibrium (CGE) model developed for Zambia. Observed meteorological data of the past three decades are used in the integrated hydro-economic model for climate variability impact analysis, and as baseline climatology for climate change impact assessment together with several GCM-based climate change scenarios that cover a broad range of climate projections. We found that climate variability can explain a significant portion of the annual variations of agricultural production and GDP of Zambia in the past. Hidden beneath climate variability, climate change is found to have modest impacts on agriculture and national economy of Zambia around 2025 but the impacts would be pronounced in the far future if appropriate adaptations are not implemented. Policy recommendations are provided based on scenario analysis.

Industrial and occupational ergonomics in the petrochemical process industry: a regression trees approach.

PubMed

Bevilacqua, M; Ciarapica, F E; Giacchetta, G

2008-07-01

This work is an attempt to apply classification tree methods to data regarding accidents in a medium-sized refinery, so as to identify the important relationships between the variables, which can be considered as decision-making rules when adopting any measures for improvement. The results obtained using the CART (Classification And Regression Trees) method proved to be the most precise and, in general, they are encouraging concerning the use of tree diagrams as preliminary explorative techniques for the assessment of the ergonomic, management and operational parameters which influence high accident risk situations. The Occupational Injury analysis carried out in this paper was planned as a dynamic process and can be repeated systematically. The CART technique, which considers a very wide set of objective and predictive variables, shows new cause-effect correlations in occupational safety which had never been previously described, highlighting possible injury risk groups and supporting decision-making in these areas. The use of classification trees must not, however, be seen as an attempt to supplant other techniques, but as a complementary method which can be integrated into traditional types of analysis.

A research of selected textural features for detection of asbestos-cement roofing sheets using orthoimages

NASA Astrophysics Data System (ADS)

Książek, Judyta

2015-10-01

At present, there has been a great interest in the development of texture based image classification methods in many different areas. This study presents the results of research carried out to assess the usefulness of selected textural features for detection of asbestos-cement roofs in orthophotomap classification. Two different orthophotomaps of southern Poland (with ground resolution: 5 cm and 25 cm) were used. On both orthoimages representative samples for two classes: asbestos-cement roofing sheets and other roofing materials were selected. Estimation of texture analysis usefulness was conducted using machine learning methods based on decision trees (C5.0 algorithm). For this purpose, various sets of texture parameters were calculated in MaZda software. During the calculation of decision trees different numbers of texture parameters groups were considered. In order to obtain the best settings for decision trees models cross-validation was performed. Decision trees models with the lowest mean classification error were selected. The accuracy of the classification was held based on validation data sets, which were not used for the classification learning. For 5 cm ground resolution samples, the lowest mean classification error was 15.6%. The lowest mean classification error in the case of 25 cm ground resolution was 20.0%. The obtained results confirm potential usefulness of the texture parameter image processing for detection of asbestos-cement roofing sheets. In order to improve the accuracy another extended study should be considered in which additional textural features as well as spectral characteristics should be analyzed.

Comparison of two data mining techniques in labeling diagnosis to Iranian pharmacy claim dataset: artificial neural network (ANN) versus decision tree model.

PubMed

Rezaei-Darzi, Ehsan; Farzadfar, Farshad; Hashemi-Meshkini, Amir; Navidi, Iman; Mahmoudi, Mahmoud; Varmaghani, Mehdi; Mehdipour, Parinaz; Soudi Alamdari, Mahsa; Tayefi, Batool; Naderimagham, Shohreh; Soleymani, Fatemeh; Mesdaghinia, Alireza; Delavari, Alireza; Mohammad, Kazem

2014-12-01

This study aimed to evaluate and compare the prediction accuracy of two data mining techniques, including decision tree and neural network models in labeling diagnosis to gastrointestinal prescriptions in Iran. This study was conducted in three phases: data preparation, training phase, and testing phase. A sample from a database consisting of 23 million pharmacy insurance claim records, from 2004 to 2011 was used, in which a total of 330 prescriptions were assessed and used to train and test the models simultaneously. In the training phase, the selected prescriptions were assessed by both a physician and a pharmacist separately and assigned a diagnosis. To test the performance of each model, a k-fold stratified cross validation was conducted in addition to measuring their sensitivity and specificity. Generally, two methods had very similar accuracies. Considering the weighted average of true positive rate (sensitivity) and true negative rate (specificity), the decision tree had slightly higher accuracy in its ability for correct classification (83.3% and 96% versus 80.3% and 95.1%, respectively). However, when the weighted average of ROC area (AUC between each class and all other classes) was measured, the ANN displayed higher accuracies in predicting the diagnosis (93.8% compared with 90.6%). According to the result of this study, artificial neural network and decision tree model represent similar accuracy in labeling diagnosis to GI prescription.

Unexpected anthropophily in the potential secondary malaria vectors Anopheles coustani s.l. and Anopheles squamosus in Macha, Zambia.

PubMed

Fornadel, Christen M; Norris, Laura C; Franco, Veronica; Norris, Douglas E

2011-08-01

Anopheles coustani s.l. and Anopheles squamosus are sub-Saharan mosquito species that have been implicated in malaria transmission. Although generally believed to be of negligible importance due to their overwhelmingly zoophilic behavior, An. coustani s.l. and An. squamosus made up a large proportion of the anophelines collected by human landing catches during the 2007-2008 and 2008-2009 rainy seasons in Macha, Zambia. Further, polymerase chain reaction-based blood meal identification showed that the majority of blood meals from these mosquito species caught in human-baited Centers for Disease Control light traps were from human hosts. Although no An. coustani s.l. or An. squamosus were found to be positive for Plasmodium, the demonstrated anthropophilic tendencies of these mosquitoes in southern Zambia suggest their potential as secondary malaria vectors.

Multifunctional imaging signature for V-KI-RAS2 Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations in colorectal cancer.

PubMed

Miles, Kenneth A; Ganeshan, Balaji; Rodriguez-Justo, Manuel; Goh, Vicky J; Ziauddin, Zia; Engledow, Alec; Meagher, Marie; Endozo, Raymondo; Taylor, Stuart A; Halligan, Stephen; Ell, Peter J; Groves, Ashley M

2014-03-01

This study explores the potential for multifunctional imaging to provide a signature for V-KI-RAS2 Kirsten rat sarcoma viral oncogene homolog (KRAS) gene mutations in colorectal cancer. This prospective study approved by the institutional review board comprised 33 patients undergoing PET/CT before surgery for proven primary colorectal cancer. Tumor tissue was examined histologically for presence of the KRAS mutations and for expression of hypoxia-inducible factor-1 (HIF-1) and minichromosome maintenance protein 2 (mcm2). The following imaging parameters were derived for each tumor: (18)F-FDG uptake ((18)F-FDG maximum standardized uptake value [SUVmax]), CT texture (expressed as mean of positive pixels [MPP]), and blood flow measured by dynamic contrast-enhanced CT. A recursive decision tree was developed in which the imaging investigations were applied sequentially to identify tumors with KRAS mutations. Monte Carlo analysis provided mean values and 95% confidence intervals for sensitivity, specificity, and accuracy. The final decision tree comprised 4 decision nodes and 5 terminal nodes, 2 of which identified KRAS mutants. The true-positive rate, false-positive rate, and accuracy (95% confidence intervals) of the decision tree were 82.4% (63.9%-93.9%), 0% (0%-10.4%), and 90.1% (79.2%-96.0%), respectively. KRAS mutants with high (18)F-FDG SUVmax and low MPP showed greater frequency of HIF-1 expression (P = 0.032). KRAS mutants with low (18)F-FDG SUV(max), high MPP, and high blood flow expressed mcm2 (P = 0.036). Multifunctional imaging with PET/CT and recursive decision-tree analysis to combine measurements of tumor (18)F-FDG uptake, CT texture, and perfusion has the potential to identify imaging signatures for colorectal cancers with KRAS mutations exhibiting hypoxic or proliferative phenotypes.

Insurance Contract Analysis for Company Decision Support in Acquisition Management

NASA Astrophysics Data System (ADS)

Chernovita, H. P.; Manongga, D.; Iriani, A.

2017-01-01

One of company activities to retain their business is marketing the products which include in acquisition management to get new customers. Insurance contract analysis using ID3 to produce decision tree and rules to be decision support for the insurance company. The decision tree shows 13 rules that lead to contract termination claim. This could be a guide for the insurance company in acquisition management to prevent contract binding with these contract condition because it has a big chance for the customer to terminate their insurance contract before its expired date. As the result, there are several strong points that could be the determinant of contract termination such as: 1) customer age whether too young or too old, 2) long insurance period (above 10 years), 3) big insurance amount, 4) big amount of premium charges, and 5) payment method.

An Examination of Professionalism in the Zambia Army

DTIC Science & Technology

2014-12-12

corporateness . According to Huntington’s definition, professional officers should never intervene in politics, because officers would lose their...colonial Masters. Therefore, they depicted the African worker as powerless and devoid of self -awareness. This study seeks to put an officer in an African...the Zambia National Broadcasting Corporation radio station that he had taken over the reign of the country in a military coup. The coup was thwarted

Report to UNESCO on Eleven Weeks as Consultant to the Governments of Kenya, Tanzania, Zambia and Malawi on Aspects of Biology Teaching, February to April, 1971.

ERIC Educational Resources Information Center

Meyer, Rex

This report describes the activities of a UNESCO consultant who visited Kenya, Tanzania, Zambia and Malawi for the purpose of assisting local education agencies in the Biology Teaching Pilot Project. The consultant's report briefly summarizes the status of the School Science Project (SSP) in these East African countries. Also listed are the…

New Agricultural Settlement, Meheba River, Zambia, Africa

NASA Technical Reports Server (NTRS)

1990-01-01

This infra-red view of a new settlement along the Meheba River, Zambia, Africa (12.5S, 26.0E) resembles the resettlement clusters in the Amazon basin of Brazil. However, this settlement is on savanna land not a tropical forest region, so relatively little land clearing was required. The familiar pattern of small single family plots, no large commercial fields, along the branches of a herringbone road network is evident.

Expanding contraceptive choice in the developing world: lessons from the Lao People's Democratic Republic and the Republic of Zambia.

PubMed

d'Arcangues, Catherine M; Ba-Thike, Katherine; Say, Lale

2013-12-01

Women need different forms of contraception over their lifetime. In the developed world, they have access to some 20 different methods. In developing countries, only a few options are available. This paper focuses on four under-used methods: intrauterine devices, implants, emergency contraception and female condoms. It examines reasons for their low uptake, strategies used for their adoption, and challenges in sustaining these efforts, in two countries: Laos and Zambia. In-country documentation and reports from international partners were reviewed; questionnaires were sent and interviews carried out with ministry officials, senior providers, and local representatives of international organisations and international non-governmental organisations. In Laos, the family planning programme is relatively young; its challenges include ensuring the sustainability of services and supplies, improving the quality of IEC to dispel misconceptions surrounding contraception, and developing novel distribution systems to reach rural populations. Zambia has a much older programme, which lost ground in the face of competing health priorities. Its challenges include strengthening the supply chain management, coordinating the multiple groups of providers and ensuring the sustainability of services in rural areas. The contrast offered by Laos and Zambia illustrates the importance of regular evaluation to identify priority areas for improving contraceptive delivery.