Makespan minimization in a job shop with a batch processing machine

A job shop with one batch processing and several discrete machines is analyzed. Given a set of jobs, their process routes, processing requirements, and size, the objective is to schedule the jobs such that the makespan is minimized. The batch processing machine can process a batch of jobs as long as the machine capacity is not violated. The batch processing time is equal to the longest processing job in the batch. The problem under study can be represented as Jm:batch:Cmax. If no batches were formed, the scheduling problem under study reduces to the classical job shop scheduling problem (i.e. Jm:: Cmax), which is known to be NP-hard. This research extends the scheduling literature by combining Jm::Cmax with batch processing. The primary contributions are the mathematical formulation, a new network representation and several solution approaches. The problem under study is observed widely in metal working and other industries, but received limited or no attention due to its complexity. A novel network representation of the problem using disjunctive and conjunctive arcs, and a mathematical formulation are proposed to minimize the makespan. Besides that, several algorithms, like batch forming heuristics, dispatching rules, Modified Shifting Bottleneck, Tabu Search (TS) and Simulated Annealing (SA), were developed and implemented. An experimental study was conducted to evaluate the proposed heuristics, and the results were compared to those from a commercial solver (i.e., CPLEX). TS and SA, with the combination of MWKR-FF as the initial solution, gave the best solutions among all the heuristics proposed. Their results were close to CPLEX; and for some larger instances, with total operations greater than 225, they were competitive in terms of solution quality and runtime. For some larger problem instances, CPLEX was unable to report a feasible solution even after running for several hours. Between SA and the experimental study indicated that SA produced a better average Cmax for all instances. The solution approaches proposed will benefit practitioners to schedule a job shop (with both discrete and batch processing machines) more efficiently. The proposed solution approaches are easier to implement and requires short run times to solve large problem instances.

A high efficient biometrics approach for unconstrained iris segmentation and recognition

This dissertation develops an innovative approach towards less-constrained iris biometrics. Two major contributions are made in this research endeavor: (1) Designed an award-winning segmentation algorithm in the less-constrained environment where image acquisition is made of subjects on the move and taken under visible lighting conditions, and (2) Developed a pioneering iris biometrics method coupling segmentation and recognition of the iris based on video of moving persons under different acquisitions scenarios. The first part of the dissertation introduces a robust and fast segmentation approach using still images contained in the UBIRIS (version 2) noisy iris database. The results show accuracy estimated at 98% when using 500 randomly selected images from the UBIRIS.v2 partial database, and estimated at 97% in a Noisy Iris Challenge Evaluation (NICE.I) in an international competition that involved 97 participants worldwide involving 35 countries, ranking this research group in sixth position. This accuracy is achieved with a processing speed nearing real time. The second part of this dissertation presents an innovative segmentation and recognition approach using video-based iris images. Following the segmentation stage which delineates the iris region through a novel segmentation strategy, some pioneering experiments on the recognition stage of the less-constrained video iris biometrics have been accomplished. In the video-based and less-constrained iris recognition, the test or subject iris videos/images and the enrolled iris images are acquired with different acquisition systems. In the matching step, the verification/identification result was accomplished by comparing the similarity distance of encoded signature from test images with each of the signature dataset from the enrolled iris images. With the improvements gained, the results proved to be highly accurate under the unconstrained environment which is more challenging. This has led to a false acceptance rate (FAR) of 0% and a false rejection rate (FRR) of 17.64% for 85 tested users with 305 test images from the video, which shows great promise and high practical implications for iris biometrics research and system design.

Cooperative routing for collision minimization in wireless sensor networks

Cooperative communication has gained much interest due to its ability to exploit the broadcasting nature of the wireless medium to mitigate multipath fading. There has been considerable amount of research on how cooperative transmission can improve the performance of the network by focusing on the physical layer issues. During the past few years, the researchers have started to take into consideration cooperative transmission in routing and there has been a growing interest in designing and evaluating cooperative routing protocols. Most of the existing cooperative routing algorithms are designed to reduce the energy consumption; however, packet collision minimization using cooperative routing has not been addressed yet. This dissertation presents an optimization framework to minimize collision probability using cooperative routing in wireless sensor networks. More specifically, we develop a mathematical model and formulate the problem as a large-scale Mixed Integer Non-Linear Programming problem. We also propose a solution based on the branch and bound algorithm augmented with reducing the search space (branch and bound space reduction). The proposed strategy builds up the optimal routes from each source to the sink node by providing the best set of hops in each route, the best set of relays, and the optimal power allocation for the cooperative transmission links. To reduce the computational complexity, we propose two near optimal cooperative routing algorithms. In the first near optimal algorithm, we solve the problem by decoupling the optimal power allocation scheme from optimal route selection. Therefore, the problem is formulated by an Integer Non-Linear Programming, which is solved using a branch and bound space reduced method. In the second near optimal algorithm, the cooperative routing problem is solved by decoupling the transmission power and the relay node se- lection from the route selection. After solving the routing problems, the power allocation is applied in the selected route. Simulation results show the algorithms can significantly reduce the collision probability compared with existing cooperative routing schemes.

Minimization of radiation exposure due to computed tomography in inflammatory bowel disease

Patient awareness and concern regarding the potential health risks from ionizing radiation have peaked recently (Coakley et al., 2011) following widespread press and media coverage of the projected cancer risks from the increasing use of computed tomography (CT) (Berrington et al., 2007). The typical young and educated patient with inflammatory bowel disease (IBD) may in particular be conscious of his/her exposure to ionising radiation as a result of diagnostic imaging. Cumulative effective doses (CEDs) in patients with IBD have been reported as being high and are rising, primarily due to the more widespread and repeated use of CT (Desmond et al., 2008). Radiologists, technologists, and referring physicians have a responsibility to firstly counsel their patients accurately regarding the actual risks of ionizing radiation exposure; secondly to limit the use of those imaging modalities which involve ionising radiation to clinical situations where they are likely to change management; thirdly to ensure that a diagnostic quality imaging examination is acquired with lowest possible radiation exposure. In this paper, we synopsize available evidence related to radiation exposure and risk and we report advances in low-dose CT technology and examine the role for alternative imaging modalities such as ultrasonography or magnetic resonance imaging which avoid radiation exposure.

Hierarchical Demand Response for Peak Minimization Using Dantzig-Wolfe Decomposition

Demand response (DR) algorithms manipulate the energy consumption schedules of controllable loads so as to satisfy grid objectives. Implementation of DR algorithms using a centralized agent can be problematic for scalability reasons, and there are issues related to the privacy of data and robustness to communication failures. Thus, it is desirable to use a scalable decentralized algorithm for the implementation of DR. In this paper, a hierarchical DR scheme is proposed for peak minimization based on Dantzig-Wolfe decomposition (DWD). In addition, a time weighted maximization option is included in the cost function, which improves the quality of service for devices seeking to receive their desired energy sooner rather than later. This paper also demonstrates how the DWD algorithm can be implemented more efficiently through the calculation of the upper and lower cost bounds after each DWD iteration.

Using Information on Unconstrained Student Demand to Improve University Course Schedules

We examine how using information on unconstrained demand can improve operational decisions. Specifically, we examine the widespread problem of developing course schedules in not-for-profit university settings. We investigate the potential benefit of incorporating, into the scheduling process, information on the unconstrained demand of students for courses. Prior to this study, the status quo in our college, like that in a large proportion of university settings, was building the course schedule to avoid time conflicts between required courses and to minimize time conflicts between designated groups of courses, such as electives in a particular area. Compared to the status quo approach, we find that, based on three semester's worth of actual data, an approach that explicitly considers students’ course preferences improves a student-based metric of schedule quality on the order of over 4% (which is the equivalent, in our setting, of improving service for over 20% of students).

Allocating reforestation areas for sediment flow minimization: an integer programming formulation and a heuristic solution method

Policy and decision makers dealing with environmental conservation and land use planning often require identifying potential sites for contributing to minimize sediment flow reaching riverbeds. This is the case of reforestation initiatives, which can have sediment flow minimization among their objectives. This paper proposes an Integer Programming (IP) formulation and a Heuristic solution method for selecting a predefined number of locations to be reforested in order to minimize sediment load at a given outlet in a watershed. Although the core structure of both methods can be applied for different sorts of flow, the formulations are targeted to minimization of sediment delivery. The proposed approaches make use of a Single Flow Direction (SFD) raster map covering the watershed in order to construct a tree structure so that the outlet cell corresponds to the root node in the tree. The results obtained with both approaches are in agreement with expert assessments of erosion levels, slopes and distances to the riverbeds, which in turn allows concluding that this approach is suitable for minimizing sediment flow. Since the results obtained with the IP formulation are the same as the ones obtained with the Heuristic approach, an optimality proof is included in the present work. Taking into consideration that the heuristic requires much less computation time, this solution method is more suitable to be applied in large sized problems.

Planar solid oxide fuel cell modeling and optimization targeting the stack's temperature gradient minimization

Minimization of undesirable temperature gradients in all dimensions of a planar solid oxide fuel cell (SOFC) is central to the thermal management and commercialization of this electrochemical reactor. This article explores the effective operating variables on the temperature gradient in a multilayer SOFC stack and presents a trade-off optimization. Three promising approaches are numerically tested via a model-based sensitivity analysis. The numerically efficient thermo-chemical model that had already been developed by the authors for the cell scale investigations (Tang et al. Chem. Eng. J. 2016, 290, 252-262) is integrated and extended in this work to allow further thermal studies at commercial scales. Initially, the most common approach for the minimization of stack's thermal inhomogeneity, i.e., usage of the excess air, is critically assessed. Subsequently, the adjustment of inlet gas temperatures is introduced as a complementary methodology to reduce the efficiency loss due to application of excess air. As another practical approach, regulation of the oxygen fraction in the cathode coolant stream is examined from both technical and economic viewpoints. Finally, a multiobjective optimization calculation is conducted to find an operating condition in which stack's efficiency and temperature gradient are maximum and minimum, respectively.

A Trans-dimensional inversion algorithm to model deformation sources with unconstrained shape in finite element domains

Ground deformation provides valuable insights on subsurface processes with pattens reflecting the characteristics of the source at depth. In active volcanic sites displacements can be observed in unrest phases; therefore, a correct interpretation is essential to assess the hazard potential. Inverse modeling is employed to obtain quantitative estimates of parameters describing the source. However, despite the robustness of the available approaches, a realistic imaging of these reservoirs is still challenging. While analytical models return quick but simplistic results, assuming an isotropic and elastic crust, more sophisticated numerical models, accounting for the effects of topographic loads, crust inelasticity and structural discontinuities, require much higher computational effort and information about the crust rheology may be challenging to infer. All these approaches are based on a-priori source shape constraints, influencing the solution reliability. In this thesis, we present a new approach aimed at overcoming the aforementioned limitations, modeling sources free of a-priori shape constraints with the advantages of FEM simulations, but with a cost-efficient procedure. The source is represented as an assembly of elementary units, consisting in cubic elements of a regular FE mesh loaded with a unitary stress tensors. The surface response due to each of the six stress tensor components is computed and linearly combined to obtain the total displacement field. In this way, the source can assume potentially any shape. Our tests prove the equivalence of the deformation fields due to our assembly and that of corresponding cavities with uniform boundary pressure. Our ability to simulate pressurized cavities in a continuum domain permits to pre-compute surface responses, avoiding remeshing. A Bayesian trans-dimensional inversion algorithm implementing this strategy is developed. 3D Voronoi cells are used to sample the model domain, selecting the elementary units contributing to the source solution and those remaining inactive as part of the crust.

Environmental Controls In The Water Use Patterns Of A Tropical Cloud Forest Tree Species, Drimys Brasiliensis (winteraceae).

Trees from tropical montane cloud forest (TMCF) display very dynamic patterns of water use. They are capable of downwards water transport towards the soil during leaf-wetting events, likely a consequence of foliar water uptake (FWU), as well as high rates of night-time transpiration (Enight) during drier nights. These two processes might represent important sources of water losses and gains to the plant, but little is known about the environmental factors controlling these water fluxes. We evaluated how contrasting atmospheric and soil water conditions control diurnal, nocturnal and seasonal dynamics of sap flow in Drimys brasiliensis (Miers), a common Neotropical cloud forest species. We monitored the seasonal variation of soil water content, micrometeorological conditions and sap flow of D. brasiliensis trees in the field during wet and dry seasons. We also conducted a greenhouse experiment exposing D. brasiliensis saplings under contrasting soil water conditions to deuterium-labelled fog water. We found that during the night D. brasiliensis possesses heightened stomatal sensitivity to soil drought and vapour pressure deficit, which reduces night-time water loss. Leaf-wetting events had a strong suppressive effect on tree transpiration (E). Foliar water uptake increased in magnitude with drier soil and during longer leaf-wetting events. The difference between diurnal and nocturnal stomatal behaviour in D. brasiliensis could be attributed to an optimization of carbon gain when leaves are dry, as well as minimization of nocturnal water loss. The leaf-wetting events on the other hand seem important to D. brasiliensis water balance, especially during soil droughts, both by suppressing tree transpiration (E) and as a small additional water supply through FWU. Our results suggest that decreases in leaf-wetting events in TMCF might increase D. brasiliensis water loss and decrease its water gains, which could compromise its ecophysiological performance and survival during dry periods.

Modelo dinâmico de simulação e otimização da força normal de reação do solo para um mecanismo de corte basal

The physical model was based on the method of Newton-Euler. The model was developed by using the scientific computer program Mathematica®. Several simulations where tried varying the progress speeds (0.69; 1.12; 1.48; 1.82 and 2.12 m s-1); soil profiles (sinoidal, ascending and descending ramp) and height of the profile (0.025 and 0.05 m) to obtain the normal force of soil reaction. After the initial simulations, the mechanism was optimized using the scientific computer program Matlab® having as criterion (function-objective) the minimization of the normal force of reaction of the profile (FN). The project variables were the lengths of the bars (L1y, L2, l3 and L4), height of the operation (L7), the initial length of the spring (Lmo) and the elastic constant of the spring (k t). The lack of robustness of the mechanism in relation to the variable height of the operation was outlined by using a spring with low rigidity and large length. The results demonstrated that the mechanism optimized showed better flotation performance in relation to the initial mechanism.

Atividade fisica e a relação com a qualidade de vida, ansiedade e depressão em pessoas com sequelas de acidente vascular cerebral isquemico (AVCI)/ c Alberto Martins da Costa

Universidade Estadual de Campinas . Faculdade de Educação Física

A positional FEM Formulation for geometrical non-linear analysis of shells

This work presents a fully non-linear finite element formulation for shell analysis comprising linear strain variation along the thickness of the shell and geometrically exact description for curved triangular elements. The developed formulation assumes positions and generalized unconstrained vectors as the variables of the problem, not displacements and finite rotations. The full 3D Saint-Venant-Kirchhoff constitutive relation is adopted and, to avoid locking, the rate of thickness variation enhancement is introduced. As a consequence, the second Piola-Kirchhoff stress tensor and the Green strain measure are employed to derive the specific strain energy potential. Curved triangular elements with cubic approximation are adopted using simple notation. Selected numerical simulations illustrate and confirm the objectivity, accuracy, path independence and applicability of the proposed technique.

Minor and Unsystematic Cortical Topographic Changes of Attention Correlates between Modalities

In this study we analyzed the topography of induced cortical oscillations in 20 healthy individuals performing simple attention tasks. We were interested in qualitatively replicating our recent findings on the localization of attention-induced beta bands during a visual task [1], and verifying whether significant topographic changes would follow the change of attention to the auditory modality. We computed corrected latency averaging of each induced frequency bands, and modeled their generators by current density reconstruction with Lp-norm minimization. We quantified topographic similarity between conditions by an analysis of correlations, whereas the inter-modality significant differences in attention correlates were illustrated in each individual case. We replicated the qualitative result of highly idiosyncratic topography of attention-related activity to individuals, manifested both in the beta bands, and previously studied slow potential distributions [2]. Visual inspection of both scalp potentials and distribution of cortical currents showed minor changes in attention-related bands with respect to modality, as compared to the theta and delta bands, known to be major contributors to the sensory-related potentials. Quantitative results agreed with visual inspection, supporting to the conclusion that attention-related activity does not change much between modalities, and whatever individual changes do occur, they are not systematic in cortical localization across subjects. We discuss our results, combined with results from other studies that present individual data, with respect to the function of cortical association areas.

Estimation of the thickness and the optical parameters of several stacked thin films using optimization

The reverse engineering problem addressed in the present research consists of estimating the thicknesses and the optical constants of two thin films deposited on a transparent substrate using only transmittance data through the whole stack. No functional dispersion relation assumptions are made on the complex refractive index. Instead, minimal physical constraints are employed, as in previous works of some of the authors where only one film was considered in the retrieval algorithm. To our knowledge this is the first report on the retrieval of the optical constants and the thickness of multiple film structures using only transmittance data that does not make use of dispersion relations. The same methodology may be used if the available data correspond to normal reflectance. The software used in this work is freely available through the PUMA Project web page (http://www.ime.usp.br/similar to egbirgin/puma/). (C) 2008 Optical Society of America