Solution of the Least Squares Method problem of pairwise comparison matrices

The aim of the paper is to present a new global optimization method for determining all the optima of the Least Squares Method (LSM) problem of pairwise comparison matrices. Such matrices are used, e.g., in the Analytic Hierarchy Process (AHP). Unlike some other distance minimizing methods, LSM is usually hard to solve because of the corresponding nonlinear and non-convex objective function. It is found that the optimization problem can be reduced to solve a system of polynomial equations. Homotopy method is applied which is an efficient technique for solving nonlinear systems. The paper ends by two numerical example having multiple global and local minima.

A non-linear discrete stochastic optimization model for Advanced Access patient appointment scheduling

Access to healthcare is a major problem in which patients are deprived of receiving timely admission to healthcare. Poor access has resulted in significant but avoidable healthcare cost, poor quality of healthcare, and deterioration in the general public health. Advanced Access is a simple and direct approach to appointment scheduling in which the majority of a clinic's appointments slots are kept open in order to provide access for immediate or same day healthcare needs and therefore, alleviate the problem of poor access the healthcare. This research formulates a non-linear discrete stochastic mathematical model of the Advanced Access appointment scheduling policy. The model objective is to maximize the expected profit of the clinic subject to constraints on minimum access to healthcare provided. Patient behavior is characterized with probabilities for no-show, balking, and related patient choices. Structural properties of the model are analyzed to determine whether Advanced Access patient scheduling is feasible. To solve the complex combinatorial optimization problem, a heuristic that combines greedy construction algorithm and neighborhood improvement search was developed. The model and the heuristic were used to evaluate the Advanced Access patient appointment policy compared to existing policies. Trade-off between profit and access to healthcare are established, and parameter analysis of input parameters was performed. The trade-off curve is a characteristic curve and was observed to be concave. This implies that there exists an access level at which at which the clinic can be operated at optimal profit that can be realized. The results also show that, in many scenarios by switching from existing scheduling policy to Advanced Access policy clinics can improve access without any decrease in profit. Further, the success of Advanced Access policy in providing improved access and/or profit depends on the expected value of demand, variation in demand, and the ratio of demand for same day and advanced appointments. The contributions of the dissertation are a model of Advanced Access patient scheduling, a heuristic to solve the model, and the use of the model to understand the scheduling policy trade-offs which healthcare clinic managers must make. ^

Algorithms for scheduling parallel batch processing machines with non-identical job ready times

This research is motivated by a practical application observed at a printed circuit board (PCB) manufacturing facility. After assembly, the PCBs (or jobs) are tested in environmental stress screening (ESS) chambers (or batch processing machines) to detect early failures. Several PCBs can be simultaneously tested as long as the total size of all the PCBs in the batch does not violate the chamber capacity. PCBs from different production lines arrive dynamically to a queue in front of a set of identical ESS chambers, where they are grouped into batches for testing. Each line delivers PCBs that vary in size and require different testing (or processing) times. Once a batch is formed, its processing time is the longest processing time among the PCBs in the batch, and its ready time is given by the PCB arriving last to the batch. ESS chambers are expensive and a bottleneck. Consequently, its makespan has to be minimized. ^ A mixed-integer formulation is proposed for the problem under study and compared to a formulation recently published. The proposed formulation is better in terms of the number of decision variables, linear constraints and run time. A procedure to compute the lower bound is proposed. For sparse problems (i.e. when job ready times are dispersed widely), the lower bounds are close to optimum. ^ The problem under study is NP-hard. Consequently, five heuristics, two metaheuristics (i.e. simulated annealing (SA) and greedy randomized adaptive search procedure (GRASP)), and a decomposition approach (i.e. column generation) are proposed—especially to solve problem instances which require prohibitively long run times when a commercial solver is used. Extensive experimental study was conducted to evaluate the different solution approaches based on the solution quality and run time. ^ The decomposition approach improved the lower bounds (or linear relaxation solution) of the mixed-integer formulation. At least one of the proposed heuristic outperforms the Modified Delay heuristic from the literature. For sparse problems, almost all the heuristics report a solution close to optimum. GRASP outperforms SA at a higher computational cost. The proposed approaches are viable to implement as the run time is very short. ^

Correlates of Non-Institutional Food Service Turnover

The high rate of restaurant employee turnover, particularly of the non-supervisory employee, is a continuing problem. The authors assess the possible correlates of this turnover and their relative strengths, ranking and comparing working hours, quality of supervision, chance for promotion, on-the-job training, pay, work of others, employees' attitudes, and management's interest in employees to present possible solutions for the high rate of turnover.

Learning Data-Driven Models of Non-Verbal Behaviors for Building Rapport Using an Intelligent Virtual Agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness. Evidence-based patient-centered Brief Motivational Interviewing (BMI) interven- tions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary. Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems. To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].

Renormalization group flows between non-unitary conformal models

Recentemente sono stati valutati come fisicamente consistenti diversi modelli non-hermitiani sia in meccanica quantistica che in teoria dei campi. La classe dei modelli pseudo-hermitiani, infatti, si adatta ad essere usata per la descrizione di sistemi fisici dal momento che, attraverso un opportuno operatore metrico, risulta possibile ristabilire una struttura hermitiana ed unitaria. I sistemi PT-simmetrici, poi, sono una categoria particolarmente studiata in letteratura. Gli esempi riportati sembrano suggerire che anche le cosiddette teorie conformi non-unitarie appartengano alla categoria dei modelli PT-simmetrici, e possano pertanto adattarsi alla descrizione di fenomeni fisici. In particolare, si tenta qui la costruzione di determinate lagrangiane Ginzburg-Landau per alcuni modelli minimali non-unitari, sulla base delle identificazioni esistenti per quanto riguarda i modelli minimali unitari. Infine, si suggerisce di estendere il dominio del noto teorema c alla classe delle teorie di campo PT-simmetriche, e si propongono alcune linee per una possibile dimostrazione dell'ipotizzato teorema c_{eff}.

Can a Broader Education Narrow the Gap? Evidence on Non-Academic Features of Schooling

Empirical studies of education programs and systems, by nature, rely upon use of student outcomes that are measurable. Often, these come in the form of test scores. However, in light of growing evidence about the long-run importance of other student skills and behaviors, the time has come for a broader approach to evaluating education. This dissertation undertakes experimental, quasi-experimental, and descriptive analyses to examine social, behavioral, and health-related mechanisms of the educational process. My overarching research question is simply, which inside- and outside-the-classroom features of schools and educational interventions are most beneficial to students in the long term? Furthermore, how can we apply this evidence toward informing policy that could effectively reduce stark social, educational, and economic inequalities?

The first study of three assesses mechanisms by which the Fast Track project, a randomized intervention in the early 1990s for high-risk children in four communities (Durham, NC; Nashville, TN; rural PA; and Seattle, WA), reduced delinquency, arrests, and health and mental health service utilization in adolescence through young adulthood (ages 12-20). A decomposition of treatment effects indicates that about a third of Fast Track’s impact on later crime outcomes can be accounted for by improvements in social and self-regulation skills during childhood (ages 6-11), such as prosocial behavior, emotion regulation and problem solving. These skills proved less valuable for the prevention of mental and physical health problems.

The second study contributes new evidence on how non-instructional investments – such as increased spending on school social workers, guidance counselors, and health services – affect multiple aspects of student performance and well-being. Merging several administrative data sources spanning the 1996-2013 school years in North Carolina, I use an instrumental variables approach to estimate the extent to which local expenditure shifts affect students’ academic and behavioral outcomes. My findings indicate that exogenous increases in spending on non-instructional services not only reduce student absenteeism and disciplinary problems (important predictors of long-term outcomes) but also significantly raise student achievement, in similar magnitude to corresponding increases in instructional spending. Furthermore, subgroup analyses suggest that investments in student support personnel such as social workers, health services, and guidance counselors, in schools with concentrated low-income student populations could go a long way toward closing socioeconomic achievement gaps.

The third study examines individual pathways that lead to high school graduation or dropout. It employs a variety of machine learning techniques, including decision trees, random forests with bagging and boosting, and support vector machines, to predict student dropout using longitudinal administrative data from North Carolina. I consider a large set of predictor measures from grades three through eight including academic achievement, behavioral indicators, and background characteristics. My findings indicate that the most important predictors include eighth grade absences, math scores, and age-for-grade as well as early reading scores. Support vector classification (with a high cost parameter and low gamma parameter) predicts high school dropout with the highest overall validity in the testing dataset at 90.1 percent followed by decision trees with boosting and interaction terms at 89.5 percent.

Best Practices: Lessons Learned by a South Florida Non-Profit Community Based Organization while Designing and Implementing a Career Exploration Evidence Informed Framework in Urban Communities

All A’s was designed to support of the agency’s family strengthening initiatives in South Florida. All A’s uses evidence informed strategies poised to be an inclusive curriculum that teaches self-determination and adaptive behavior skills. The framework incorporates problem based learning and adult learning theory and follows the Universal Design for Learning. Since 2012, the agency has served over 8500 youth and 4,000 adults using the framework. The framework addresses educational underachievement and career readiness in at risk populations. It is used to enhance participants AWARENESS of setting SMART goals to achieve future goals and career aspirations. Participants are provided with ACCESS to resources and opportunities for creating and implementing an ACTION plan as they pursue and ACHIEVE their goals. All A’s promotes protective factors and expose youth to career pathways in Science, Technology, Engineering and Math (STEM) related fields. Youth participate in college tours, job site visits, job shadowing, high school visits, online college and career preparation assistance, service learning projects, STEM projects, and the Winning Futures© mentoring program. Adults are assisted with résumé development; learn job search strategies, interview techniques, job shadowing experiences, computer and financial literacy programs. Adults and youth are also given the opportunity to complete industry-recognized certifications in high demand industries (food service, general labor, and construction), and test preparation for the General Educational Development Test.

THE EFFECT OF PURPOSEFUL MATHEMATICS DISCOURSE IN THE CLASSROOM ON STUDENTS’ MATHEMATICS LANGUAGE IN THE CONTEXT OF PROBLEM SOLVING

This study examines how one secondary school teacher’s use of purposeful oral mathematics language impacted her students’ language use and overall communication in written solutions while working with word problems in a grade nine academic mathematics class. Mathematics is often described as a distinct language. As with all languages, students must develop a sense for oral language before developing social practices such as listening, respecting others ideas, and writing. Effective writing is often seen by students that have strong oral language skills. Classroom observations, teacher and student interviews, and collected student work served as evidence to demonstrate the nature of both the teacher’s and the students’ use of oral mathematical language in the classroom, as well as the effect the discourse and language use had on students’ individual written solutions while working on word problems. Inductive coding for themes revealed that the teacher’s purposeful use of oral mathematical language had a positive impact on students’ written solutions. The teacher’s development of a mathematical discourse community created a space for the students to explore mathematical language and concepts that facilitated a deeper level of conceptual understanding of the learned material. The teacher’s oral language appeared to transfer into students written work albeit not with the same complexity of use of the teacher’s oral expression of the mathematical register. Students that learn mathematical language and concepts better appear to have a growth mindset, feel they have ownership over their learning, use reorganizational strategies, and help develop a discourse community.

Hegel’s Non-Metaphysical Idea of Freedom

the article explores the putatively non-metaphysical – non-voluntarist, and even non-causal – concept of freedom outlined in Hegel’s work and discusses its influential interpretation by robert Pippin as an ‘essentially practical’ concept. I argue that Hegel’s affirmation of freedom must be distinguished from that of Kant and Fichte, since it does not rely on a prior understanding of self-consciousness as an originally teleological relation and it has not the nature of a claim ‘from a practical point of view’.

Rabbits, stoats and the predator problem: Why a strong animal rights position need not call for human intervention to protect prey from predators

Animal rights positions face the ‘predator problem’: the suggestion that if the rights of nonhuman animals are to be protected, then we are obliged to interfere in natural ecosystems to protect prey from predators. Generally, rather than embracing this conclusion, animal ethicists have rejected it, basing this objection on a number of different arguments. This paper considers but challenges three such arguments, before defending a fourth possibility. Rejected are Peter Singer’s suggestion that interference will lead to more harm than good, Sue Donaldson and Will Kymlicka’s suggestion that respect for nonhuman sovereignty necessitates non-interference in normal circumstances, and Alasdair Cochrane’s solution based on the claim that predators cannot survive without killing prey. The possibility defended builds upon Tom Regan’s suggestion that predators, as moral patients but not moral agents, cannot violate the rights of their prey, and so the rights of the prey, while they do exist, do not call for intervention. This idea is developed by a consideration of how moral agents can be more or less responsible for a given event, and defended against criticisms offered by thinkers including Alasdair Cochrane and Dale Jamieson.

Women into Non-Traditional Sectors: Addressing Gender Segregation in the Northern Ireland Workforce

The horizontal segregation of the workforce along gender lines tends to assign women to lower paid, lower status employment. Consequently, schemes to address segregation have focused on preparing women to enter non‐traditional occupations through training and development processes. This article examines models to encourage women into non‐traditional employment, focusing on the Women into Non‐Traditional Sectors (WINS) project in Belfast, Northern Ireland. However, changing women to suit a hostile work environment assumes women to be the problem, whereas it is the barriers that women face in undertaking non‐traditional jobs that need to be changed. It is concluded, therefore, that while models such as WINS can be successful in assisting women into non‐traditional sectors, change processes to make workplaces more accessible are a more pressing and appropriate approach to de‐segregating the workforce.

Complete framework for efficient characterisation of non-Markovian processes

A non-Markovian process is one that retains `memory' of its past. A systematic understanding of these processes is necessary to fully describe and harness a vast range of complex phenomena; however, no such general characterisation currently exists. This long-standing problem has hindered advances in understanding physical, chemical and biological processes, where often dubious theoretical assumptions are made to render a dynamical description tractable. Moreover, the methods currently available to treat non-Markovian quantum dynamics are plagued with unphysical results, like non-positive dynamics. Here we develop an operational framework to characterise arbitrary non-Markovian quantum processes. We demonstrate the universality of our framework and how the characterisation can be rendered efficient, before formulating a necessary and sufficient condition for quantum Markov processes. Finally, we stress how our framework enables the actual systematic analysis of non-Markovian processes, the understanding of their typicality, and the development of new master equations for the effective description of memory-bearing open-system evolution.

Asymmetric hydrogen flame in a heated micro-channel: role of Darrieus-Landau and thermal-diffusive instabilities

Present work examines numerically the asymmetric behavior of hydrogen/air flame in a micro-channel subjected to a non-uniform wall temperature distribution. A high resolution (with cell size of 25 μm × 25 μm) of two-dimensional transient Navier–Stokes simulation is conducted in the low-Mach number formulation using detailed chemistry evolving 9 chemical species and 21 elementary reactions. Firstly, effects of hydrodynamic and diffusive-thermal instabilities are studied by performing the computations for different Lewis numbers. Then, the effects of preferential diffusion of heat and mass transfer on the asymmetric behavior of the hydrogen flame are analyzed for different inlet velocities and equivalence ratios. Results show that for the flames in micro-channels, interactions between thermal diffusion and molecular diffusion play major role in evolution of a symmetric flame into an asymmetric one. Furthermore, the role of Darrieus–Landau instability found to be minor. It is also found that in symmetric flames, the Lewis number decreases behind the flame front. This is related to the curvature of flame which leads to the inclination of thermal and mass fluxes. The mass diffusion vectors point toward the walls and the thermal diffusion vectors point toward the centerline. Asymmetric flame is observed when the length of flame front is about 1.1–1.15 times of the channel width.

Temperature fields in a channel partially filled with a porous material under local thermal non-equilibrium condition-an exact solution

This work examines analytically the forced convection in a channel partially filled with a porous material and subjected to constant wall heat flux. The Darcy–Brinkman–Forchheimer model is used to represent the fluid transport through the porous material. The local thermal non-equilibrium, two-equation model is further employed as the solid and fluid heat transport equations. Two fundamental models (models A and B) represent the thermal boundary conditions at the interface between the porous medium and the clear region. The governing equations of the problem are manipulated, and for each interface model, exact solutions, for the solid and fluid temperature fields, are developed. These solutions incorporate the porous material thickness, Biot number, fluid to solid thermal conductivity ratio and Darcy number as parameters. The results can be readily used to validate numerical simulations. They are, further, applicable to the analysis of enhanced heat transfer, using porous materials, in heat exchangers.