The Estimation of Flows on Regional Labour Markets By Using the ADETON Procedure

An in-depth analysis of regional labour markets requires information not only on stocks but also on flows. As a tool for detailed flow analysis the Multi Account System (MAS) has been developed at the Institute for Employment Research (IAB) which uses fine grained transition matrices as basic information. To estimate these transition matrices from possibly incomplete and inconsistent statistical data the ADETON procedure has been worked out to compute matrices which are struc-turally similar to given reference matrix and at the same time satisfy certain linear con-straints. As main advantage of ADETON in comparison to conventional methods soft constraints may be specified which allow information of inherently fuzzy character about transition flows to be taken into account. By using soft constraints of this kind it is possible to in-clude data affected by sampling errors or are distorted by some kind of “noiseâ€. To obtain structural similarity to a reference matrix two different distance measures can be used: relative entropy and the chi-square distance function. They have been proven to give approximately identical results. Up to now ADETON has shown to be an efficient computation method even for complex problems with thousands of matrix elements and constraints. ADETON has been applied to estimate matrices of the Multi Account System. The results are used for the guidance of regional labour market policy.

Hybrid Optimization Based Mathematical Procedure for Dimensional Synthesis of Slider-Crank Linkage

In this paper, an optimization procedure for path generation synthesis of the slider-crank mechanism will be presented. The proposed approach is based on a hybrid strategy, mixing local and global optimization techniques. Regarding the local optimization scheme, based on the null gradient condition, a novel methodology to solve the resulting non-linear equations is developed. The solving procedure consists of decoupling two subsystems of equations which can be solved separately and following an iterative process. In relation to the global technique, a multi-start method based on a genetic algorithm is implemented. The fitness function incorporated in the genetic algorithm will take as arguments the set of dimensional parameters of the slider-crank mechanism. Several illustrative examples will prove the validity of the proposed optimization methodology, in some cases achieving an even better result compared to mechanisms with a higher number of dimensional parameters, such as the four-bar mechanism or the Watt’s mechanism.The authors wish to acknowledge financial support received from the Spanish government through the Ministerio de Economía y Competitividad (Project DPI2015−67626-P (MINECO/FEDER, UE)), the support for the research group through Project Ref. IT949−16, provided by the Departamento de Educación, Política Lingüística y Cultura from the regional Basque Government, and the Program BIKAINTEK 2020 (Ref. 012-B2/2020) provided by the Departamento de Desarrollo Económico, Sostenibilidad y Medio Ambiente from the regional Basque Government

Position Tracking Of Slider Crank Mechanism Using Pid Controller Optimized By Ziegler Nichol’s Method

This paper presents a study on the position tracking response of a Propotional-Integral-Derivative (PID) controlled- slider crank mechanism, which is driven by a two phase stepper motor. In this study, the rod and crank are assumed to be rigid where the Newton second law is applied to formulate the equation of motion. A position tracking control of the slider crank mechanism is then developed by using PID controller. Several tests such as saw tooth, step function and square function are used in order to examine the performance of the proposed control structure. The results show that, the proposed control structure is able to tracking the desired position with a good response. The slider crank mechanism rig is then developed to investigate experimentally the ability of the proposed controller structure. The results show that the proposed control structure is able to track the desired displacements with accepTABLE error

Optimal synthesis of planar adjustable mechanisms

Adjustable mechanisms provide degrees of flexibility while retaining desirable features of one degree of freedom close-loop mechanisms, such as simplicity, stability, and high speed capabilities. By adjusting linkage parameters, additional phases of motions can be achieved using the same hardware. However, an adjustment to the mechanism adds only one or two additional design positions and divides desired positions into phases , each of which contains only a few positions usually insufficient for industrial applications. In order to extend the design position limitation of adjustable mechanisms, an optimal synthesis method based on link length structural error is developed and applied to kinematic synthesis of adjustable planar mechanisms in this research. Designed with this method, adjustable mechanisms can achieve phases of many design positions with a minimized error. The conveniently-calculated link length structural error effectively reflects the overall difference between generated and desired motions without directly comparing them; and its compact fourth-order polynomial form facilitates the gradient- based optimization process. Link length structural error based optimal synthesis methods are developed for adjustable planar four-bar mechanisms for three typical synthesis tasks. For multi-phase approximate motion generation, standard optimization model is established based on adjustable optimal dyads considering all types of adjustments. For multi-phase continuous path generation, a proper driving dyad is firstly found by an optimization procedure using the full rotation requirement. The driven dyad is then found using the optimization technique for motion generation after calculating all coupler angles. For multi-phase function generation, the coupler length is chosen to carry the structural error and adjustments to the coupler and the side-link lengths are considered. Numerical synthesis examples have demonstrated that the developed method is effective and efficient for multi-phase motion, path, and function generation of planar four-bar linkages with a large number of specified positions in each phase

Optimization for Urban Mobility Systems

In the recent decades, new modes of transportation have been developed due to urbanization, highly dense population, and technological advancement. As a result, design and operation of urban transportation have become increasingly important to better utilize the resources and efficiently meet demand. This dissertation was motivated by two problems on optimizing design and control of urban transportation. In the first one, we consider a problem of dynamically matching heterogeneous market parcitipants so as to maximize the total number of matching, which was motivated by practices of ride-sharing platforms. In the other problem, we study efficient design of elevator zoning system in high-rises with uncertainty in customer batching.In Chapter 1, we consider a multiperiod stochastic optimization of a market that matches heterogeneous and impatient agents. The model was mainly motivated from carpooling products run by ride-sharing platforms such as Uber and Lyft, and kidney exchange market, where market participants are heterogeneous in terms of how likely they can be matched with others. In the case of a ride-sharing platform, one of the key operational decisions for carpooling is to efficiently match riders and clear the market in a timely manner. In doing so, the platform needs to take into account the heterogeneity of riders in terms of their trip types(e.g origin-destination pair) and different matching compatibility. For example, some customers may request rides within San Francisco, while others may request rides from San Francisco to outside the city. Since picking up and dropping off a customer within the city can be done within relatively short amount of time, those who want to travel within the city can be matched with any other riders for carpooling. However, the destinations of those who want to travel to outside the city may be very different, and in order to maintain customers' additional transit time due to carpooling, it is likely that they can be only matched with those who want to travel within the city. In the case of kidney exchange where market participants arrive in the form of patient-donor pair, pairs with donor who can donate her kidney to most of patients (for example, blood type O) and patient who can get kidney from most of donors (for example, blood type AB) can be easily matched to other pairs. The opposite case would be hard-to-match pair that is incompatible for matching with most of other pairs. Our model is an abstraction of these two motivating examples, and considers two types of agents: easy-to-match agents that can be matched with either type of agents, and hard-to-match agents that can be only matched with easy-to-match ones. We first formulate a dynamic program to solve for optimal matching decisions over infinite time horizon in a discrete time setting, and characterize structure of optimal stationary policies. Inspired by practices in kidney exchange where the market is cleared for every fixed time interval, we connect the discrete time model to a continuous time setting by investigating the effect of the length of matching intervals on the matching performance. Results from numerical experiments indicate certain patterns in the relationship between the length of matching intervals and the maximum number of matching achieved, and provides valuable insights for future direction of research. In Chapter 2, we consider a zoning problem for elevator dispatching systems in high-rises. In practice, zoning is frequently used to improve efficiency of elevator systems. The idea of zoning is to prevent different elevators from stopping at common floors, which may result in long service times of elevators and thus long waiting times of customers. Our goal is to provide a mathematical framework that can help a system planner decide optimal zoning design with some performance guarantee. To this end, we focus on uppeak traffic situation during morning rush hour, which is in general the heaviest traffic during the day. The performance in the uppeak traffic situation can be considered as the system's capacity, because if the system can handle uppeak traffic well, it can also serve other types of traffic with good performance. Thus, the performance measure in the uppeak traffic situation can be used as a metric to choose the optimal zoning configuration. One of the components that complicate the problem is customer batching, on which the system may not have a control. In view of this, we formulate an adversarial optimization problem that can measure the system performance of different zoning decisions. By considering the heaviest traffic situation of the day and using the adversarial framework, we provide a model that can be used for capacity planning of elevator systems. We formulate mixed-integer linear program(MILP)s to find the optimal zoning configuration. To solve the MILPs, we show that we can use simple greedy algorithms and solve smaller linear programs. We also provide a few illustrative examples as well as numerical experiments to verify the theoretical results and obtain insights for further analysis

Predictably Incoherent Judgments

When people make moral or legal judgments in isolation, they produce a pattern of outcomes that they would themselves reject, if only they could see that pattern as a whole. A major reason is that human thinking is category-bound. When people see a case in isolation, they spontaneously compare it to other cases that are mainly drawn from the same category of harms. When people are required to compare cases that involve different kinds of harms, judgments that appear sensible when the problems are considered separately often appear incoherent and arbitrary in the broader context. Another major source of incoherence is what we call the translation problem: The translation of moral judgments into the relevant metrics of dollars and years is not grounded in either principle or intuition, and produces large differences among people.. The incoherence produced by category-bound thinking is illustrated by an experimental study of punitive damages and contingent valuation. We also show how category-bound thinking and the translation problem combine to produce anomalies in administrative penalties. The underlying phenomena have large implications for many topics in law, including jury behavior, the valuation of public goods, punitive damages, criminal sentencing, and civil fines. We consider institutional reforms that might overcome the problem of predictably incoherent judgments. Connections are also drawn to several issues in legal theory, including valuation of life, incommensurability, and the aspiration to global coherence in adjudication

Eating and repeating : mimesis in food rhetorics

textThere is emerging, in the discipline of rhetoric and composition, a rhetoric of food. In this dissertation, I map the various approaches to food rhetorics, and I look at three different foods: burritos, kale, and kombucha. Using these foods as commonplaces, I explore the social and rhetorical discourse around them. I use “a cultural biography of things” methodology to describe the history of the burrito and use that history to contextualize Chipotle Mexican Grill’s new media strategies. Throughout the cultural biography of the burrito and the analysis of Chipotle’s marketing, I highlight a theatrical mimesis that blurs the lines between imitation and reality. I suggest that kale can be associated the books of Michael Pollan, whose work, I argue, constitutes a genre that establishes a set of conventions for how we think and communicate about food. I begin by looking at how Chipotle builds its corporate ethos by citing Michael Pollan’s books on its website. Then I approach Pollan’s body of work as a genre, showing how it establishes certain conventions in food discourse. We see transmissions of these conventions throughout food networks. I look at how fermented foods, like kombucha, travel through alternative food networks, like groups of “fermentos” led by Sandor Katz, until they have proliferated to the point of becoming mainstream. I show how Michael Pollan engages with the world of countercultural food movements like fermentos and argue that Pollan’s engagement with fermentos signals a move into posthuman rhetorics. Building on the idea of micropolitics, I posit a compostmodern micro(be)politics that re-articulates the human not as an agentive individual governed by autonomy, but as an ecology itself, situated within other ecologies. I conclude by reading “nobody cares what you ate for lunch” memes as a response to and provocation to an abundance of online food talk. We can read these memes as evidence of the significance of online food discourse. Instead of taking the memes at face value, we can ask, “who does care about food in online networks?”Englis

Face recognition/clustering - performance improvements, 2007

This thesis will introduce Face Recognition as an important and crucially needed type of biometrics. The existing and most widely used Face Recognition algorithms have been tested and the results will be presented. Additionally, the limitations of the existing FF methods will be discussed, focusing chiefly on the future of Face Recognition and the reasons such relatively poor results were achieved in comparison with results from other Biometrics. Finally, a novel system that enhances the performance of the face matching for existing FF algorithms (High-speed k-means Image Clustering using the Discrete Cosine Transform and its comparison with existing methods) will be discussed. Appendix A focuses on the results obtained from the Haar face detection algorithm, utilizing different face databases. Appendix B is dedicated to the Matlab code