Suboptimal Multistage Nonparametric Hypotheses Test

2000 Mathematics Subject Classification: 62L10, 62L15.

Nonparametric versus Parametric Statistical Approaches for Genetic Anticipation: The Pancreatic Cancer Case

2000 Mathematics Subject Classi cation: 62N01, 62N05, 62P10, 92D10, 92D30.

A Test of Association between Qualitative Trait and a Set of SNPs

2000 Mathematics Subject Classification: 62P10, 92D10, 92D30, 62F03

Comparing Several Methods of Discriminant Analysis on the Case of Wine Data

2000 Mathematics Subject Classification: 62H30, 62J20, 62P12, 68T99

Fractal Analysis for Cancer Research: Case Study and Simulation of Fractals

2010 Mathematics Subject Classification: 65D18.

First-Order Conditions for Optimization Problems with Quasiconvex Inequality Constraints

2000 Mathematics Subject Classification: 90C46, 90C26, 26B25, 49J52.

Optimal combination of energy crops under different policy scenarios:the case of Northern Greece

Energy crops production is considered as environmentally benign and socially acceptable, offering ecological benefits over fossil fuels through their contribution to the reduction of greenhouse gases and acidifying emissions. Energy crops are subjected to persistent policy support by the EU, despite their limited or even marginally negative impact on the greenhouse effect. The present study endeavors to optimize the agricultural income generated by energy crops in a remote and disadvantageous region, with the assistance of linear programming. The optimization concerns the income created from soybean, sunflower (proxy for energy crop), and corn. Different policy scenarios imposed restrictions on the value of the subsidies as a proxy for EU policy tools, the value of inputs (costs of capital and labor) and different irrigation conditions. The results indicate that the area and the imports per energy crop remain unchanged, independently of the policy scenario enacted. Furthermore, corn cultivation contributes the most to iFncome maximization, whereas the implemented CAP policy plays an incremental role in uptaking an energy crop. A key implication is that alternative forms of motivation should be provided to the farmers beyond the financial ones in order the extensive use of energy crops to be achieved.

A lean kultúra értelmezése és mérése egy egészségügyi szolgáltatónál (The interpretation and measurement of the lean culture – in case of a healthcare service provider)

A lean menedzsment egészségügyi szolgáltatásokra való alkalmazásával elérhető eredmények egyre inkább nyilvánvalóvá válnak. Ennek köszönhetően a szektorban dinamikus növekedés tapasztalható ezen a téren. A kutatások azonban arra hívják fel a figyelmet, hogy a lean menedzsment alkalmazásával elért eredmények csak akkor lesznek fenntarthatóak, ha az eszközök alkalmazását a kultúra átalakulása is követi. A kultúra változásának követéséhez annak folyamatos értékelésére van szükség. A szervezeti kultúra lean-specifikus méréséhez azonban – a szerzők tudomása szerint – még nincs kidolgozott eszköz. Ezért cikkükben a kapcsolódó szakirodalom áttekintése után kidolgoztak egy lean kultúra kérdőívet, majd bemutatják a kérdőív tesztelését és annak eredményeit. Összegzésként elmondható, hogy az itt bemutatott kérdőív az első tesztelés alapján további fejlesztésre szorul. / === / The results that can be obtained by applying lean management in healthcare services become more and more clear. This generates a dynamic increase of lean applications in healthcare. However, researches are warning that the res ults obtained by lean applications can only be sustained, if next to the use of the lean tools cultural change will also take place. In order to track changes in culture its constant evaluation is necessary. According to the authors’ knowledge today does not exist any lean-specific culture evaluation tool. In this paper they elaborate a lean culture questionnaire based on the review of relevant literature. Than they describe its test and the results of the test. The authors conclude that the questionnaire as introduced here needs further improvement.

Improved stochastic optimization of railway timetables

We present a general model to find the best allocation of a limited amount of supplements (extra minutes added to a timetable in order to reduce delays) on a set of interfering railway lines. By the best allocation, we mean the solution under which the weighted sum of expected delays is minimal. Our aim is to finely adjust an already existing and well-functioning timetable. We model this inherently stochastic optimization problem by using two-stage recourse models from stochastic programming, building upon earlier research from the literature. We present an improved formulation, allowing for an efficient solution using a standard algorithm for recourse models. We show that our model may be solved using any of the following theoretical frameworks: linear programming, stochastic programming and convex non-linear programming, and present a comparison of these approaches based on a real-life case study. Finally, we introduce stochastic dependency into the model, and present a statistical technique to estimate the model parameters from empirical data.

An asymptotic test for the Conditional Value-at-Risk

Conditional Value-at-Risk (equivalent to the Expected Shortfall, Tail Value-at-Risk and Tail Conditional Expectation in the case of continuous probability distributions) is an increasingly popular risk measure in the fields of actuarial science, banking and finance, and arguably a more suitable alternative to the currently widespread Value-at-Risk. In my paper, I present a brief literature survey, and propose a statistical test of the location of the CVaR, which may be applied by practising actuaries to test whether CVaR-based capital levels are in line with observed data. Finally, I conclude with numerical experiments and some questions for future research.

Defining failure in the nonprofit organization: The case of four human service agencies

Private nonprofit human service organizations provide a spectrum of services that aim to resolve societal problems. Their failure may leave needed and desired services unprovided or not provided sufficiently to meet public demand. However, the concept of organizational failure has not been examined for the nonprofit organization. This research addresses the deficiency in the literatures of organization failure and nonprofit organizations.^ An eight category typology, developed from a review of the current literature and findings from expert interviews, is initially presented to define nonprofit organization failure. A multiple case study design is used to test the typology in four nonprofit human service delivery agencies. The case analysis reduces the typology to five types salient to nonprofit organization failure: input failure, legitimacy failure, adaptive failure, management failure and leadership failure.^ The resulting five category typology is useful to both theory builders and nonprofit practitioners. For theory development, the interaction of the failure types extends the literature and lays a foundation for a theory of nonprofit organization failure that diffuses management and leadership across all of the failure types, highlights management and leadership failure as collective functions shared by paid staff and the volunteer board of directors, and emphasizes the importance of organization legitimacy.^ From a practical perspective, the typology provides a tool for diagnosing failure in the nonprofit organization. Using the management indicators developed for the typology, a checklist of the warning signals of potential failure, emphasizing the key types of management and leadership, offers nonprofit decision makers a priori examination of an organization's propensity for failure. ^

Planning and evaluation of Business English course in compliance with internationalization in Taiwan: A case study of Tainan Women's College of Arts & Technology

In compliance with the economic internationalization movement and the development of Asia-Pacific Regional Operation Center (APROC) in Taiwan, international business has become more and more important. To sustain favorable trade balances every year and the promotion of APROC in Taiwan, more and more talent with knowledge and skills of Business English are needed. As a consequence, it is necessary to make Business English curriculum appropriate to meet the emerging needs.^ Two groups, experimental and control, received the revised or traditional Business English course to answer the question, "Does the Business English curriculum at Tainan Woman's College of Arts & Technology (TWCAT) meet the needs of students?" Ninety-five subjects were randomly selected from the commercial departments at TWCAT and then randomly assigned to the two groups. In addition, the Business English scores of the subjects' previous semester were collected and analyzed to justify the random selection and assignment. The finding was that their initial equivalence was proved.^ A questionnaire for students and another one for the business community were administered to facilitate data collection and analysis. The results of the questionnaires were used to modify the curriculum content of Business English.^ A final-term examination was given to the subjects at the end of the pilot study of Business English in early May of 1998. The resulting scores of the examination were used to determine if there was a significant difference in learning achievement between the students of the two groups.^ Using Independent Samples Test, significant results indicated that the experimental group had higher level of learning Business English than the control group. The finding supports the hypothesis of this study.^ Recommendations based on these results are that the revised curriculum be adapted and used by TWCAT because it better meets student needs. ^

Optimization of pavement maintenance and rehabilitation programming using shuffled complex evolution algorithm

The major barrier to practical optimization of pavement preservation programming has always been that for formulations where the identity of individual projects is preserved, the solution space grows exponentially with the problem size to an extent where it can become unmanageable by the traditional analytical optimization techniques within reasonable limit. This has been attributed to the problem of combinatorial explosion that is, exponential growth of the number of combinations. The relatively large number of constraints often presents in a real-life pavement preservation programming problems and the trade-off considerations required between preventive maintenance, rehabilitation and reconstruction, present yet another factor that contributes to the solution complexity. In this research study, a new integrated multi-year optimization procedure was developed to solve network level pavement preservation programming problems, through cost-effectiveness based evolutionary programming analysis, using the Shuffled Complex Evolution (SCE) algorithm.^ A case study problem was analyzed to illustrate the robustness and consistency of the SCE technique in solving network level pavement preservation problems. The output from this program is a list of maintenance and rehabilitation treatment (M&R) strategies for each identified segment of the network in each programming year, and the impact on the overall performance of the network, in terms of the performance levels of the recommended optimal M&R strategy. ^ The results show that the SCE is very efficient and consistent in the simultaneous consideration of the trade-off between various pavement preservation strategies, while preserving the identity of the individual network segments. The flexibility of the technique is also demonstrated, in the sense that, by suitably coding the problem parameters, it can be used to solve several forms of pavement management programming problems. It is recommended that for large networks, some sort of decomposition technique should be applied to aggregate sections, which exhibit similar performance characteristics into links, such that whatever M&R alternative is recommended for a link can be applied to all the sections connected to it. In this way the problem size, and hence the solution time, can be greatly reduced to a more manageable solution space. ^ The study concludes that the robust search characteristics of SCE are well suited for solving the combinatorial problems in long-term network level pavement M&R programming and provides a rich area for future research. ^

Optimization of adaptive traffic signal control with transit signal priority at isolated intersections using parallel genetic algorithms

Optimization of adaptive traffic signal timing is one of the most complex problems in traffic control systems. This dissertation presents a new method that applies the parallel genetic algorithm (PGA) to optimize adaptive traffic signal control in the presence of transit signal priority (TSP). The method can optimize the phase plan, cycle length, and green splits at isolated intersections with consideration for the performance of both the transit and the general vehicles. Unlike the simple genetic algorithm (GA), PGA can provide better and faster solutions needed for real-time optimization of adaptive traffic signal control. ^ An important component in the proposed method involves the development of a microscopic delay estimation model that was designed specifically to optimize adaptive traffic signal with TSP. Macroscopic delay models such as the Highway Capacity Manual (HCM) delay model are unable to accurately consider the effect of phase combination and phase sequence in delay calculations. In addition, because the number of phases and the phase sequence of adaptive traffic signal may vary from cycle to cycle, the phase splits cannot be optimized when the phase sequence is also a decision variable. A "flex-phase" concept was introduced in the proposed microscopic delay estimation model to overcome these limitations. ^ The performance of PGA was first evaluated against the simple GA. The results show that PGA achieved both faster convergence and lower delay for both under- or over-saturated traffic conditions. A VISSIM simulation testbed was then developed to evaluate the performance of the proposed PGA-based adaptive traffic signal control with TSP. The simulation results show that the PGA-based optimizer for adaptive TSP outperformed the fully actuated NEMA control in all test cases. The results also show that the PGA-based optimizer was able to produce TSP timing plans that benefit the transit vehicles while minimizing the impact of TSP on the general vehicles. The VISSIM testbed developed in this research provides a powerful tool to design and evaluate different TSP strategies under both actuated and adaptive signal control. ^

Optimization models for selecting bus stops for accessibility improvements for people with disabilities

Bus stops are key links in the journeys of transit patrons with disabilities. Inaccessible bus stops prevent people with disabilities from using fixed-route bus services, thus limiting their mobility. The Americans with Disabilities Act (ADA) of 1990 prescribes the minimum requirements for bus stop accessibility by riders with disabilities. Due to limited budgets, transit agencies can only select a limited number of bus stop locations for ADA improvements annually. These locations should preferably be selected such that they maximize the overall benefits to patrons with disabilities. In addition, transit agencies may also choose to implement the universal design paradigm, which involves higher design standards than current ADA requirements and can provide amenities that are useful for all riders, like shelters and lighting. Many factors can affect the decision to improve a bus stop, including rider-based aspects like the number of riders with disabilities, total ridership, customer complaints, accidents, deployment costs, as well as locational aspects like the location of employment centers, schools, shopping areas, and so on. These interlacing factors make it difficult to identify optimum improvement locations without the aid of an optimization model. This dissertation proposes two integer programming models to help identify a priority list of bus stops for accessibility improvements. The first is a binary integer programming model designed to identify bus stops that need improvements to meet the minimum ADA requirements. The second involves a multi-objective nonlinear mixed integer programming model that attempts to achieve an optimal compromise among the two accessibility design standards. Geographic Information System (GIS) techniques were used extensively to both prepare the model input and examine the model output. An analytic hierarchy process (AHP) was applied to combine all of the factors affecting the benefits to patrons with disabilities. An extensive sensitivity analysis was performed to assess the reasonableness of the model outputs in response to changes in model constraints. Based on a case study using data from Broward County Transit (BCT) in Florida, the models were found to produce a list of bus stops that upon close examination were determined to be highly logical. Compared to traditional approaches using staff experience, requests from elected officials, customer complaints, etc., these optimization models offer a more objective and efficient platform on which to make bus stop improvement suggestions.