889 resultados para continuous and discrete variables


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This thesis is concerned with the inventory control of items that can be considered independent of one another. The decisions when to order and in what quantity, are the controllable or independent variables in cost expressions which are minimised. The four systems considered are referred to as (Q, R), (nQ,R,T), (M,T) and (M,R,T). Wiith ((Q,R) a fixed quantity Q is ordered each time the order cover (i.e. stock in hand plus on order ) equals or falls below R, the re-order level. With the other three systems reviews are made only at intervals of T. With (nQ,R,T) an order for nQ is placed if on review the inventory cover is less than or equal to R, where n, which is an integer, is chosen at the time so that the new order cover just exceeds R. In (M, T) each order increases the order cover to M. Fnally in (M, R, T) when on review, order cover does not exceed R, enough is ordered to increase it to M. The (Q, R) system is examined at several levels of complexity, so that the theoretical savings in inventory costs obtained with more exact models could be compared with the increases in computational costs. Since the exact model was preferable for the (Q,R) system only exact models were derived for theoretical systems for the other three. Several methods of optimization were tried, but most were found inappropriate for the exact models because of non-convergence. However one method did work for each of the exact models. Demand is considered continuous, and with one exception, the distribution assumed is the normal distribution truncated so that demand is never less than zero. Shortages are assumed to result in backorders, not lost sales. However, the shortage cost is a function of three items, one of which, the backorder cost, may be either a linear, quadratic or an exponential function of the length of time of a backorder, with or without period of grace. Lead times are assumed constant or gamma distributed. Lastly, the actual supply quantity is allowed to be distributed. All the sets of equations were programmed for a KDF 9 computer and the computed performances of the four inventory control procedures are compared under each assurnption.

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Sensorimotor synchronization is hypothesized to arise through two different processes, associated with continuous or discontinuous rhythmic movements. This study investigated synchronization of continuous and discontinuous movements to different pacing signals (auditory or visual), pacing interval (500, 650, 800, 950 ms) and across effectors (non-dominant vs. non-dominant hand). The results showed that mean and variability of asynchronization errors were consistently smaller for discontinuous movements compared to continuous movements. Furthermore, both movement types were timed more accurately with auditory pacing compared to visual pacing and were more accurate with the dominant hand. Shortening the pacing interval also improved sensorimotor synchronization accuracy in both continuous and discontinuous movements. These results show the dependency of temporal control of movements on the nature of the motor task, the type and rate of extrinsic sensory information as well as the efficiency of the motor actuators for sensory integration.

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Theory development on the relationship between strategic planning and organizational performance has focussed on largely discrete examinations of dependent and independent variables. While the literature has examined the impact of organizational learning on strategic planning, no holistic empirical approaches have been employed in order to fully explore the inter-play between these important constructs. This paper addresses the cited limitations in both the strategic planning and organizational performance literatures by creating profiles of organizational learning and strategic planning capacity using a configuration theory-based approach. The organizational learning orientation profiles (OLOPs) created of prospector, disseminator, interpretative and memory, contribute to theory development regarding the relationship of strategic planning and organizational learning. The theory developed provides insights that have not been previously reported.

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This research aims at a study of the hybrid flow shop problem which has parallel batch-processing machines in one stage and discrete-processing machines in other stages to process jobs of arbitrary sizes. The objective is to minimize the makespan for a set of jobs. The problem is denoted as: FF: batch1,sj:Cmax. The problem is formulated as a mixed-integer linear program. The commercial solver, AMPL/CPLEX, is used to solve problem instances to their optimality. Experimental results show that AMPL/CPLEX requires considerable time to find the optimal solution for even a small size problem, i.e., a 6-job instance requires 2 hours in average. A bottleneck-first-decomposition heuristic (BFD) is proposed in this study to overcome the computational (time) problem encountered while using the commercial solver. The proposed BFD heuristic is inspired by the shifting bottleneck heuristic. It decomposes the entire problem into three sub-problems, and schedules the sub-problems one by one. The proposed BFD heuristic consists of four major steps: formulating sub-problems, prioritizing sub-problems, solving sub-problems and re-scheduling. For solving the sub-problems, two heuristic algorithms are proposed; one for scheduling a hybrid flow shop with discrete processing machines, and the other for scheduling parallel batching machines (single stage). Both consider job arrival and delivery times. An experiment design is conducted to evaluate the effectiveness of the proposed BFD, which is further evaluated against a set of common heuristics including a randomized greedy heuristic and five dispatching rules. The results show that the proposed BFD heuristic outperforms all these algorithms. To evaluate the quality of the heuristic solution, a procedure is developed to calculate a lower bound of makespan for the problem under study. The lower bound obtained is tighter than other bounds developed for related problems in literature. A meta-search approach based on the Genetic Algorithm concept is developed to evaluate the significance of further improving the solution obtained from the proposed BFD heuristic. The experiment indicates that it reduces the makespan by 1.93 % in average within a negligible time when problem size is less than 50 jobs.

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Bankruptcy prediction has been a fruitful area of research. Univariate analysis and discriminant analysis were the first methodologies used. While they perform relatively well at correctly classifying bankrupt and nonbankrupt firms, their predictive ability has come into question over time. Univariate analysis lacks the big picture that financial distress entails. Multivariate discriminant analysis requires stringent assumptions that are violated when dealing with accounting ratios and market variables. This has led to the use of more complex models such as neural networks. While the accuracy of the predictions has improved with the use of more technical models, there is still an important point missing. Accounting ratios are the usual discriminating variables used in bankruptcy prediction. However, accounting ratios are backward-looking variables. At best, they are a current snapshot of the firm. Market variables are forward-looking variables. They are determined by discounting future outcomes. Microstructure variables, such as the bid-ask spread, also contain important information. Insiders are privy to more information that the retail investor, so if any financial distress is looming, the insiders should know before the general public. Therefore, any model in bankruptcy prediction should include market and microstructure variables. That is the focus of this dissertation. The traditional models and the newer, more technical models were tested and compared to the previous literature by employing accounting ratios, market variables, and microstructure variables. Our findings suggest that the more technical models are preferable, and that a mix of accounting and market variables are best at correctly classifying and predicting bankrupt firms. Multi-layer perceptron appears to be the most accurate model following the results. The set of best discriminating variables includes price, standard deviation of price, the bid-ask spread, net income to sale, working capital to total assets, and current liabilities to total assets.

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This dissertation analyzed and compared variables affecting interest rate and yield of certificates of participation, tax-exempt revenue bonds and tax-exempt general obligation bonds. The study employed qualitative and quantitative analysis methods. ^ Qualitative research methods included surveys, interviews and focus groups. The survey solicited debt load information from 67 Florida school districts (21 responded) and addressed the question which districts used certificates of participation and why. Eight individuals with experience dealing with all three debt instruments were interviewed. A follow-up focus group of six school district financial officers gathered additional data. Results from the qualitative methods revealed school districts used certificates of participation based on millage authority amount available relative to overall tax base. Also identified was the belief of a significant difference in certificates of participation costs and the other two debt instrument types. ^ The study's quantitative methods analyzed 1998 and 1999 initial issues of Moody's AAA rated certificates of participation, tax-exempt revenue bonds and tax-exempt general obligation bonds. Through an analysis of covariance (ANCOVA), the study examined interest rates and yields while controlling for the covariates of credit enhancement, issue size, and maturity date. The analysis identified no significant difference between interest rates of certificates of participation and tax-exempt general obligation bonds (p < 0.05). There was a significant difference between interest rates of tax-exempt revenue bonds and tax-exempt general obligation bonds. This study discerned no significant difference between yield on certificates of participation and tax-exempt general obligation bonds. It identified a difference in yield between both certificates of participation and tax-exempt general obligation bonds compared with tax-exempt revenue bonds. ^ The study found COPs to have lesser overall costs than RV bonds. COPs also have a quicker entry into the market resulting in construction cost savings. The study found policy implications such as investment portfolio limitations and public choice issues about using COPs as a mechanism to grow government. ^

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Background Self-harm places an individual at increased risk of future self-harm and suicide, and indicates distress and maladaptive coping. Those who present to hospital with self-cutting form a significant minority of self-harm patients who are at increased risk of prospective repetition of self-harm and suicide compared with those presenting with intentional overdose. In addition to increased risk, there is emerging evidence of demographic, psychological, clinical, and social differences between those presenting with self-cutting and those presenting with overdose. Aim and Key Objectives The aim of the current doctoral work was to examine in detail the association between presenting with self-cutting and risk of prospective repetition. The objectives were: to identify evidence-based risk factors for repetition of self-harm among those presenting to emergency departments with self-harm; to compare demographic and presentation characteristics and prospective repetition across presentations of self-cutting only, self-cutting plus intentional overdose, and intentional overdose only; to compare prospective repetition and other characteristics within self-cutting presentations based on the type of treatment received; to compare self-cutting and intentional overdose patients on psychological risk and protective factors for repetition; and to examine the lived experience of engaging in repeated overdose and self-cutting. Methods The current doctoral work used a mixed-methods approach and is comprised of one systematic review and four empirical studies. The empirical studies were two registry-based prospective studies of Irish hospital presentations of self-harm, one prospective structured interview study, and one qualitative study using Interpretative Phenomenological Analysis. Results The systematic review identified several consistent and emerging risk factors for repetition of self-harm, compared to which self-cutting had a medium-sized effect. The registry studies demonstrated that the involvement of self-cutting, particularly less medically severe selfcutting, confers an increased risk of 1-month and 12-month repetition among Irish index selfharm presentations. The structured psychological study detected higher hopelessness and lower non-reactivity to inner experience among those presenting with self-cutting, and higher depression among those who repeated self-harm. Repeaters had lower baseline levels of protective psychological factors than non-repeaters and continued to have higher depression and hopelessness at follow-up. Finally, the qualitative study indicated that self-harm is a purposeful action taken in response to an overwhelming situation and is evaluated afterwards in terms of personal and social effects. Chosen method of self-harm seemed to be influenced by the desired outcome of the self-harm act, capability, accessibility and previous experience. Conclusion Despite limitations in terms of recruitment rates, the work presented in this thesis is innovative in examining the issue of the association between self-cutting and repetition from multiple perspectives. No one factor can reliably predict all repetition but self-cutting represents one consistent and easily detected risk factor for repetition. Those who present with self-cutting exhibit significant differences on demographic, clinical, and psychological variables compared with those presenting with intentional overdose, and seem to exhibit a more vulnerable profile. However, those who present with self-cutting do not form a discrete or homogenous group, and self-harm methods and levels of suicidal intent are liable to fluctuate over time.

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Bayesian nonparametric models, such as the Gaussian process and the Dirichlet process, have been extensively applied for target kinematics modeling in various applications including environmental monitoring, traffic planning, endangered species tracking, dynamic scene analysis, autonomous robot navigation, and human motion modeling. As shown by these successful applications, Bayesian nonparametric models are able to adjust their complexities adaptively from data as necessary, and are resistant to overfitting or underfitting. However, most existing works assume that the sensor measurements used to learn the Bayesian nonparametric target kinematics models are obtained a priori or that the target kinematics can be measured by the sensor at any given time throughout the task. Little work has been done for controlling the sensor with bounded field of view to obtain measurements of mobile targets that are most informative for reducing the uncertainty of the Bayesian nonparametric models. To present the systematic sensor planning approach to leaning Bayesian nonparametric models, the Gaussian process target kinematics model is introduced at first, which is capable of describing time-invariant spatial phenomena, such as ocean currents, temperature distributions and wind velocity fields. The Dirichlet process-Gaussian process target kinematics model is subsequently discussed for modeling mixture of mobile targets, such as pedestrian motion patterns.

Novel information theoretic functions are developed for these introduced Bayesian nonparametric target kinematics models to represent the expected utility of measurements as a function of sensor control inputs and random environmental variables. A Gaussian process expected Kullback Leibler divergence is developed as the expectation of the KL divergence between the current (prior) and posterior Gaussian process target kinematics models with respect to the future measurements. Then, this approach is extended to develop a new information value function that can be used to estimate target kinematics described by a Dirichlet process-Gaussian process mixture model. A theorem is proposed that shows the novel information theoretic functions are bounded. Based on this theorem, efficient estimators of the new information theoretic functions are designed, which are proved to be unbiased with the variance of the resultant approximation error decreasing linearly as the number of samples increases. Computational complexities for optimizing the novel information theoretic functions under sensor dynamics constraints are studied, and are proved to be NP-hard. A cumulative lower bound is then proposed to reduce the computational complexity to polynomial time.

Three sensor planning algorithms are developed according to the assumptions on the target kinematics and the sensor dynamics. For problems where the control space of the sensor is discrete, a greedy algorithm is proposed. The efficiency of the greedy algorithm is demonstrated by a numerical experiment with data of ocean currents obtained by moored buoys. A sweep line algorithm is developed for applications where the sensor control space is continuous and unconstrained. Synthetic simulations as well as physical experiments with ground robots and a surveillance camera are conducted to evaluate the performance of the sweep line algorithm. Moreover, a lexicographic algorithm is designed based on the cumulative lower bound of the novel information theoretic functions, for the scenario where the sensor dynamics are constrained. Numerical experiments with real data collected from indoor pedestrians by a commercial pan-tilt camera are performed to examine the lexicographic algorithm. Results from both the numerical simulations and the physical experiments show that the three sensor planning algorithms proposed in this dissertation based on the novel information theoretic functions are superior at learning the target kinematics with

little or no prior knowledge

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Background: Interventions to increase cooking skills (CS) and food skills (FS) as a route to improving overall diet are popular within public health. This study tested a comprehensive model of diet quality by assessing the influence of socio-demographic, knowledge- and psychological-related variables alongside perceived CS and FS abilities. The correspondence of two measures of diet quality further validated the Eating Choices Index (ECI) for use in quantitative research.
Methods: A cross-sectional survey was conducted in a quota-controlled nationally representative sample of 1049 adults aged 20–60 years drawn from the Island of Ireland. Surveys were administered in participants’ homes via computer-assisted personal interviewing (CAPI) assessing a range of socio-demographic, knowledge- and psychological-related variables alongside perceived CS and FS abilities. Regression models were used to model factors influencing diet quality. Correspondence between 2 measures of diet quality was assessed using chi-square and Pearson correlations.
Results: ECI score was significantly negatively correlated with DINE Fat intake (r = -0.24, p < 0.001), and ECI score was significantly positively correlated with DINE Fibre intake (r = 0.38, p < 0.001), demonstrating a high agreement. Findings indicated that males, younger respondents and those with no/few educational qualifications scored significantly lower on both CS and FS abilities. The relative influence of socio-demographic, knowledge, psychological variables and CS and FS abilities on dietary outcomes varied, with regression models explaining 10–20 % of diet quality variance. CS ability exerted the strongest relationship with saturated fat intake (β = -0.296, p < 0.001) and was a significant predictor of fibre intake (β = -0.113, p < 0.05), although not for healthy food choices (ECI) (β = 0.04, p > 0.05).
Conclusion: Greater CS and FS abilities may not lead directly to healthier dietary choices given the myriad of other factors implicated; however, CS appear to have differential influences on aspects of the diet, most notably in relation to lowering saturated fat intake. Findings suggest that CS and FS should not be singular targets of interventions designed to improve diet; but targeting specific sub-groups of the population e.g. males, younger adults, those with limited education might be more fruitful. A greater understanding of the interaction of factors influencing cooking and food practices within the home is needed.

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[EN] Background: Plasma biochemical and hematologic variables are important in the management of endangered sea turtles, such as loggerheads. However, studies on blood biochemistry and hematology of loggerheads are limited, and different concentrations according to variable criteria have been reported. Objective: The purpose of this study was to establish and compare baseline plasma chemistry and hematology values in Eastern Atlantic juvenile and adult nesting loggerhead sea turtles (Caretta caretta).

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This study investigated cow characteristics, farm facilities, and herd management strategies during the dry period to examine their joint influence on somatic cell counts (SCC) in early lactation. Data from 52 commercial dairy farms throughout England and Wales were collected over a 2-yr period. For the purpose of analysis, cows were separated into those housed for the dry period (6,419 cow-dry periods) and those at pasture (7,425 cow-dry periods). Bayesian multilevel models were specified with 2 response variables: ln SCC (continuous) and SCC >199,000 cells/mL (binary), both within 30 d of calving. Cow factors associated with an increased SCC after calving were parity, an SCC >199,000 cells/mL in the 60 d before drying off, increasing milk yield 0 to 30 d before drying off, and reduced DIM after calving at the time of SCC estimation. Herd management factors associated with an increased SCC after calving included procedures at drying off, aspects of bedding management, stocking density, and method of pasture grazing. Posterior predictions were used for model assessment, and these indicated that model fit was generally good. The research demonstrated that specific dry-period management strategies have an important influence on SCC in early lactation.

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Introduzione Nel 2014 è stato proposto un protocollo di studio riguardante la sorveglianza delle lesioni cistiche del pancreas (intese come IPMN) e denominato PACYFIC Study. Obiettivi Obiettivo primario era di stabilire l’impatto di un programma di sorveglianza in termini di pazienti arruolati e pazienti con indicazione chirurgica. Obiettivi secondari erano: 1) stabilire l’impatto dei fattori demografici, clinici, radiologici e della strategia di sorveglianza sull’indicazione chirurgica, sulla capacità individuare le lesioni maligne, sulla sopravvivenza. Materiali e Metodi Lo studio su cui si è basata la raccolta dei dati è uno studio di tipo prospettico, di coorte, multicentrico, internazionale. Lo studio ha incluso gli individui con una IPMN, di nuova o pregressa diagnosi, che giustifichi una sorveglianza o il trattamento chirurgico. I dati clinici, demografici, radiologici e chirurgici sono stati raccolti in un database prospettico. Le variabili discrete sono state espresse come frequenza e percentuale. Le continue come medie e deviazioni standard o mediane e range interquartile (IQR). Per l’analisi statistica sono stati utilizzati il test di Fischer, il test del Chi quadro, il test di Spearman, il test di Student. L’analisi multivariata è stata eseguita utilizzando la regressione logistica espressa come Odds Ratio e intervallo di confidenza al 95 %. Per la sopravvivenza è stato utilizzato il metodo di Kaplan-Meier. L’analisi multivariata sulle sopravvivenze è stata eseguita mediante la regressione di Cox. Risultati Il protocollo di sorveglianza ha permesso l'arruolamento di 516 pazienti. 53 pazienti hanno raggiunto l'indicazione chirurgica. La sopravvivenza globale della coorte è stata di 326.8± 9.1 mesi. I fattori predittivi la sopravvivenza sono risultati età (OR 1.07, P-value<0.001), sesso (OR 1.82, P-value=0.006), ittero, noduli murali (OR 4.84, P-value=0.018 e OR 2.19, P-value=0.016), chirurgia (OR 0.46, P-value 0.038). Conclusioni L'introduzione del protocollo di sorveglianza ha portato ad un aumento di identificazione di lesioni e ha avuto impatto sulla sopravvivenza

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As people spend a third of their lives at work and, in most cases, indoors, the work environment assumes crucial importance. The continuous and dynamic interaction between people and the working environment surrounding them produces physiological and psychological effects on operators. Recognizing the substantial impact of comfort and well-being on employee satisfaction and job performance, the literature underscores the need for industries to implement indoor environment control strategies to ensure long-term success and profitability. However, managing physical risks (i.e., ergonomic and microclimate) in industrial environments is often constrained by production and energy requirements. In the food processing industry, for example, the safety of perishable products dictates storage temperatures that do not allow for operator comfort. Conversely, warehouses dedicated to non-perishable products often lack cooling systems to limit energy expenditure, reaching high temperatures in the summer period. Moreover, exceptional events, like the COVID-19 pandemic, introduce new constraints, with recommendations impacting thermal stress and respiratory health. Furthermore, the thesis highlights how workers' variables, particularly the aging process, reduce tolerance to environmental stresses. Consequently, prolonged exposure to environmental stress conditions at work results in cardiovascular disease and musculoskeletal disorders. In response to the global trend of an aging workforce, the thesis bridges a literature gap by proposing methods and models that integrate the age factor into comfort assessment. It aims to present technical and technological solutions to mitigate microclimate risks in industrial environments, ultimately seeking innovative ways to enhance the aging workforce's comfort, performance, experience, and skills. The research outlines a logical-conceptual scheme with three main areas of focus: analyzing factors influencing the work environment, recognizing constraints to worker comfort, and designing solutions. The results significantly contribute to science by laying the foundation for new research in worker health and safety in an ageing working population's extremely current industrial context.

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This article seeks to investigate associations between satisfaction with life and sociodemographic variables, health conditions, functionality, social involvement and social support among elderly caregivers and non-caregivers, as well as between satisfaction and the intensity of stress in the caregiver group. A sample of 338 caregivers was selected according to two items of the Brazilian version of the Elders Life Stress Inventory. A comparison-group of elderly non-caregivers was selected at random, with a similar gender, age and income profile. Data were derived from self-reported questionnaires and scales. Elderly caregivers with low levels of satisfaction and high levels of stress revealed more symptoms of insomnia, fatigue, diseases and worse IADL performance. Those with greater satisfaction and less stress revealed a good level of social support. Insomnia, depression and fatigue were associated with low satisfaction among caregivers, and with fatigue, depression and low social support among non-caregivers. It was considered relevant that instrumental, psychological and informative support can improve the quality of life and the quality of care provided by elderly caregivers, especially if they are affected by unfavorable health and psychosocial conditions and low satisfaction with life.

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THE PURPOSE OF THIS STUDY WAS TO PROPOSE A SPECIFIC LACTATE MINIMUM TEST FOR ELITE BASKETBALL PLAYERS CONSIDERING THE: Running Anaerobic Sprint Test (RAST) as a hyperlactatemia inductor, short distances (specific distance, 20 m) during progressive intensity and mathematical analysis to interpret aerobic and anaerobic variables. The basketball players were assigned to four groups: All positions (n=26), Guard (n= 7), Forward (n=11) and Center (n=8). The hyperlactatemia elevation (RAST) method consisted of 6 maximum sprints over 35 m separated by 10 s of recovery. The progressive phase of the lactate minimum test consisted of 5 stages controlled by an electronic metronome (8.0, 9.0, 10.0, 11.0 and 12.0 km/h) over a 20 m distance. The RAST variables and the lactate values were analyzed using visual and mathematical models. The intensity of the lactate minimum test, determined by a visual method, reduced in relation to polynomial fits (2nd degree) for the Small Forward positions and General groups. The Power and Fatigue Index values, determined by both methods, visual and 3rd degree polynomial, were not significantly different between the groups. In conclusion, the RAST is an excellent hyperlactatemia inductor and the progressive intensity of lactate minimum test using short distances (20 m) can be specifically used to evaluate the aerobic capacity of basketball players. In addition, no differences were observed between the visual and polynomial methods for RAST variables, but lactate minimum intensity was influenced by the method of analysis.