Thesis advisor: Jean M. Bartunek / Whereas some organizations effectively vanish when they die, others have robust legacies grounded in ongoing, post-death organizing that preserves valued organizational elements after an organization dies. Through post-death organizing, former members perpetuate an organization's legacy, or a shared understanding of its historical contributions. Post-death organizing may be best understood as an expression of the endurance of former members' identification with a defunct organization. This dissertation develops and tests a model of the role of organizational identification endurance in members' propensity to participate in post-death organizing and the consequent effects on organizational identity. The model identified the cognitive, evaluative, and affective processes underlying organizational identification and its individual and situational antecedents. Data for this study were drawn from a survey of 2,192 former employees of Digital Equipment Corporation (DEC) in 28 countries around the world. The analysis of these data was conducted using confirmatory factor analysis and structural equation modeling procedures. The resulting model demonstrated strong fit with the data according to several goodness-of-fit indices. The model provides support for a positive relationship between organizational identification endurance and four antecedent factors, including need for organizational identification, positive affectivity, length of service, and perceived relational organizational identity orientation. As expected, organizational identification endurance was positively related to participation in post-death organizing and perceived strength of a defunct organization's identity. Participation in post-death organizing was also positively related with perceived organizational identity strength. Contrary to expectations, the extent to which individuals' employment coincided with years of growth was negatively related to the endurance of organizational identification. Further investigation of this relationship through post-hoc analyses provided inconclusive support for a relationship in either direction between these variables. This research on post-death organizing elaborates scholarly and managerial understanding about former organizational members' motives for participating in post-death organizing. Rather than simply moving to new organizational settings, individuals who are strongly identified with their defunct organizations will be drawn towards opportunities to preserve the organizational characteristics on which their identification is based. This research also has important implications for identification research. This research sheds light on the processes that enable the endurance of organizational identification, which may be more long lasting than the organizations from which it is derived. This research elaborates theories of identification by illuminating the intertwined effects of cognition, evaluation and affect on identification and its implications for individuals' behavior during and after experiences of organizational death. / Thesis (PhD) — Boston College, 2009. / Submitted to: Boston College. Carroll School of Management. / Discipline: Organization Studies.

本文旨在探討《馬太福音》中的主角耶穌人性化的形象。我們發現這位角色在馬太筆下的故事世界中充滿挫折、掙扎、失望，然而，他仍然堅守他所相信的神旨意，直至生命的終結。然而，耶穌的故事並未因其死亡而終結，馬太以信仰的角度將之重新述說：(1) 在十字架斷氣的一刻，耶穌被確認為神兒子(太27:50-54)；(2) 詳細描述耶穌的復活及顯現(太28:1-20；對比可16:1-8)。耶穌成為了傳奇。 / 運用心理的視角分析《馬太福音》的敘事情節，我們探討耶穌在其傳道過程裏如何面對種種挫折事件。耶穌所遇到的外在挫折事件，包括不斷被質疑挑戰、甚至背叛出賣。與此同時，我們亦刻劃出馬太如何描述耶穌內在所持的兩個信念的破滅──人子快來及神兒子身份。 / 我們認為上述種種事件極有可能引致馬太筆下的耶穌對自己的身份有所疑惑，所以在凱撒利亞腓立比向門徒問「我是誰？」。本文透過「角色心理-敘事分析」的研究角度，呈現出《馬太福音》的敘事亦是一個描述耶穌「身份轉化」的過程。 / The present study aims at investigating the image of Jesus’ humanity as crafted in the Gospel of Matthew. We discover that this character Jesus in Matthew’s narrative is full of frustrations, struggles and disappointments in his ministry; however, he believes in God until he dies. Nevertheless, Jesus’ death is not the end. Matthew re-shapes Jesus’ story further from the perspective of faith, (1) affirming his sonship of God even right after his last breath on the cross (Mt 27:50-54); (2) clarifying details about the resurrection and Jesus appearance (Mt 28:1-20; cf. Mk 16:1-8). Jesus becomes legend up till now! / Focusing on the plot of the Matthean narrative, we shall see how the character Jesus faces critics, challenges, denials and even betrayals through out his whole ministry, which belongs to the external aspect of the narrative plot. At the same time, we also articulate that Matthew sophisticatedly paths the internal aspect of this Jesus, whose dual beliefs of the ‘imminent coming of Son of Man’ and ‘his identity of Son of God’ become vanished. / We suggest that all this contributes him to doubt about his own belief and identity. And therefore it is Jesus’ question, "Who am I?" at Caesarea Philippi. With this perspective, perhaps we may call it ‘the psycho-narrative analysis of character’; we further suggest that Matthew’s narrative is the process of the identity transformation of Jesus. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / 周東妮. / Thesis (Ph.D.) Chinese University of Hong Kong, 2014. / Includes bibliographical references (leaves 360-377). / Abstracts also in English. / Zhou Dongni.

La réutilisation est l’un des principaux objectifs de l’ingénierie logicielle. De nombreux concepts et mécanismes associés ont été proposés pour promouvoir la réutilisation des fonctionnalités offertes par le logiciel. L’ingénierie logicielle à base de composants (CBSE) est l’une des plus importantes approches qui ont été proposées pour augmenter la réutilisation des logiciels.Ainsi, plusieurs travaux ont été réalisés afin de restructurer les systèmes existants en systèmes à base de composants. Néanmoins, presque toutes les approches proposées visent plus l’identification des composants que l’identification des parties ré-utilisables. Ainsi, elles sont limitées à identifier des composants, correspondant à des ensembles de classes, permettantl’extraction d’une vue architecturale de l’ancien système. Mais, les composants identifiés ne peuvent pas être implantés avec un modèle concret de composants.Dans cette thèse, nous proposons deux approches pour améliorer la réutilisation des composants extraits, mais aussi faciliter la compréhension de l’architecture sous-jacente. Ainsi, la première approche vise l’identification des interfaces du composant extrait en fonction de ses interactions avec les autres composants. La seconde a pour objectif de rendre possible l’implantation des composants extraits avec un modèle concret de composants. Ceci est fait en utilisant des instances de classes (objets) qui composent les composants extraits pour déduire des instances possibles de composant.L’évaluation des approches proposées par une étude empirique montre que i) l’ensemble des interfaces identifiées correspondent aux différents aspects fonctionnels des composants extraits. ii) et, qu’il est possible d’implanter, dans un modèle concret de composants, les composants extraits sans modifier le comportement de l’application. / Reuse is one of the main goals of software engineering. Many concepts and associated mechanisms were proposed to promote the reuse of features offered by the software. Component based software engineering (CBSE) is one of the important approaches which was proposed to increase the software reuse. Thus, several works were conducted in order to restructure legacy systems into component-based ones. Nevertheless, almost all proposed approaches are more targeted for component identification than for the identification of reusable parts. Thus, they are limited to identify components, corresponding to sets of classes, allowing an extraction of the architectural view of the legacy system. But, the identified components can not be easily implemented in a concrete component model.In this thesis, we propose two approaches to improve the reusability of the extracted components and by the way facilitate the comprehension of the underlying architecture. Thus, the first approach aims the identification of the extracted component’s interfaces according to its interactions with the other components. The second one aims to make extracted components implementable within a concrete component model. This is done by using class instances (objects) that compose the extracted components to infer possible component instances.The evaluation of the proposed approaches via an empirical study showed that i) overall the identified interfaces correspond to the different functional aspects of the extracted components. ii) and, that is possible to implement, within a concrete component model, the extracted components without altering the behavior of the application.

This thesis is divided into four Phases. The aim of each phase is to identify facial creases useful in human identification.In Phase 1, creases were analysed on peri- and post-embalmed cadavers in CAHID to establish whether or not there is any change to crease with facial bloating. Embalming was chosen to simulate effects seen on a bloated face during decomposition. The results suggested that creases are quite resilient and changes were only detected relating to creases located on the periphery of the face, particularly at areas where the skin is thick, such as at the cheek region. Two new creases not classified in literature were identified on the face; these creases were called vertical superciliary arch lines and the lateral nose crease. Manifestations of these creases were also seen on faces in Phase 2 and 3 of the research. Phase 2 focused on the application of facial creases for the identification of living individuals. Volunteers were obtained from the University of Aberdeen and University of Dundee. Phase 2 was divided further into Phase 2a and Phase 2b. Phase 2a focused on matching creases from video and photograph sources while Phase 2b focused on matching creases from 3D surface scans to face photographs. A higher match rate was obtained for Phase 2a, where the shadows of the creases on two different sources were similar, as compared to the 3D to 2D analysis in Phase 2b. A Bayesian conclusion scale was utilised to categorise the conclusion.Research in Phase 3 focused on establishing facial crease correlation with skull morphology. Material for the research was obtained from William Bass skeletal collection at the University of Tennessee which provided ante-mortem face photographs with related 3D skull surface scans. Superimposition of the creases on the face photographs with the skulls was conducted to enable the visual analysis of the crease location. The qualitative analysis indicated that the infraorbital crease follows the outline of the orbits in 52% of the total subjects. No correlation was obtained between the nasolabial fold (NLF) and the bony surface inferior to the location of the crease. However, the depth of the selected skeletal region indicated the NLF was detected in 95% of the subjects. Quantitative analysis was carried out with the aid of geometric morphometrics (GMM) to analyse the maxilla morphology to establish whether the morphology indicated crease morphology. Geometric morphometric analysis indicated that people with a strong NLF had a long and narrow maxillary region.The conclusions obtained in Phase 3 were tested through a blind study in Phase 4. Analyses of the NLF and infraorbital crease were conducted on the Helmer skull collection available in CAHID. Ten skulls were provided to the researcher for analysis without related ante-mortem photographs. Once analyses were completed, the ante-mortem photographs were supplied and conclusions were obtained by comparing the crease reconstruction to the face photograph. Correct reconstruction was obtained in six of the ten specimens (60%). One case was inconclusive due to poor photograph quality though the location of the crease region appeared to be correct. The three inaccurate results showed an overestimation of the NLF strength, though the location of the crease manifestation was correct.

Along with academically focused benefits such as vocabulary and literacy, fiction reading has social-emotional benefits. Readers of fiction can identify with characters, and be transported into the fictional world, to differing degrees. Fiction, specifically, can help foster empathy. It has been well established that lifelong fiction readers have higher levels of cognitive empathy than those who have had limited experience with fiction. This relationship between transportation and empathy is well-researched, but the effect of identification on transportation and empathy is less well-defined. The relationship between identification with characters and transportation has mixed findings, and has been studied mostly with films. The current study focuses on the relationship between identification and cognitive empathy, with transportation as a possible mediator. Participants (n=148, age 18-60) read the story The Necklace by Guy de Maupassant, with explicit directions: either to read as if they were the main character (high identification), or read objectively (low identification). Participants then rated their identification (as a manipulation check) and transportation using self-report scales. Cognitive empathy was measured by the reading the Mind in the Eyes test, where participants saw a picture of eyes, and selected which emotion was being expressed. Results showed no difference between groups, indicating a failed manipulation. Further tests showed no significant correlation between condition and transportation; or condition and cognitive empathy; or transportation in cognitive empathy. There was also no significant regression equation. Future research is needed to understand the underlying mechanisms, and more potential benefits of fiction.

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Abstract: In this thesis, we give a general construction of a conditional model through embedding that concept into the concept of unconditional model. Formally, the conditional model is considered as a statistical model bearing on all the variables, i.e. on the "endogenous variables" Y and the conditioning, or "exogenous", variables Z such that j, the parameter characterizing the marginal distribution of Z, is a nuisance parameter that is identified and "well-separated” from q, the parameter of interest characterizing the Z-conditional distribution. Therefore, a family of marginal distributions on the exogenous variables and a family of “well specified” transitions of probabilities, playing a role of conditional probabilities in a global model, characterize a conditional model. Typically, but not always, j takes values in a "thick" subset F, of all the probability distributions of Z. From this construction, we analyze the identification of a conditional model in the framework of the identification of a function of the parameters in unconditional model. We propose a definition of identification in conditional models called weak identification, derived from the usual concept of identification in unconditional models. We show, under a separability condition, that weak identification may be considered as a generalization of definitions usually met in the statistical literature; in particular those in Manski (1988) and Matzkin (1993). However, an undesirable property of weak identification is shown, namely that under rather general conditions, the weak identification does not depend on the sample size. As an alternative, three other levels of identification are given, stressing the proper role of the randomness of the conditioning variables. Similar distinctions are also shown to be relevant for properties of estimators, such as unbiasedness or consistency. The relationships between these different levels of identification, unbiasedness and consistency are given. Another aspect analyzed in this thesis is the concept of partial sufficiency. Our contribution to this area is to give some further properties of S-sufficiency. In particular, we establish the connection between S-sufficiency and the identification concept for unconditional models and also for conditional models with partially observable endogenous variables. We show that when we reduce the structural (latent) model by marginalizing w.r.t an S-sufficient statistic, we do not lose the identification of the parameter of interest in the statistical (reduced) model. Furthermore, we study the properties and the conditions of applicability of S-sufficiency, with a view to compare the properties of the standard concept of sufficiency and of S-sufficiency respectively. As an application, we analyze the identification of the conditional binary response models from the semi-parametric point of view.

Industrirobotar är idag en väsentlig del i tillverkningsindustrin där de bland annat används för att minska kostnader, öka produktivitet och kvalitet och ersätta människor i farliga eller slitsamma uppgifter. Höga krav på noggrannhet och snabbhet hos robotens rörelser innebär också höga krav på de matematiska modeller som ligger till grund för robotens styrsystem. Modellerna används där för att beskriva det komplicerade sambandet mellan robotarmens rörelser och de motorer som orsakar rörelsen. Tillförlitliga modeller är också nödvändiga för exempelvis mekanisk design, simulering av prestanda, diagnos och övervakning. En trend idag är att bygga lättviktsrobotar, vilket innebär att robotens vikt minskas men att den fortfarande kan hantera en lika tung last. Orsaken till detta är främst att minska kostnaden, men också säkerhetsaspekter spelar in. En lättare robotarm ger dock en vekare struktur där elastiska effekter inte längre kan försummas i modellen om man kräver hög prestanda. De elastiska effekterna beskrivs i den matematiska modellen med hjälp av fjädrar och dämpare. Denna avhandling handlar om hur dessa matematiska modeller kan tas fram genom systemidentifiering, vilket är ett viktigt verktyg där mätningar från robotens rörelser används för att bestämma okända parametrar i modellen. Det som mäts är position och moment hos robotens alla motorer. Identifiering av industrirobotar är ett utmanande problem bland annat eftersom robotens beteende varierar beroende på armens position. Den metod som föreslås i avhandlingen innebär att man först identifierar lokala modeller i ett antal positioner. Var och en av dessa beskriver robotens beteende kring en viss arbetspunkt. Sedan anpassas parametrarna i en global modell, som är giltig för alla positioner, så att den så väl som möjligt beskriver det lokala beteendet i de olika positionerna. I avhandlingen analyseras olika metoder för att ta fram lokala modeller. För att få bra resultat krävs att experimenten är omsorgsfullt utformade. För att minska osäkerheten i den globala modellens identifierade parametrar ingår också valet av optimala positioner för experimenten. Olika metoder för att identifiera parametrarna jämförs i avhandlingen och experimentella resultat visar användbarheten av den föreslagna metoden. Den identifierade robotmodellen ger en bra global beskrivning av robotens beteende. Resultatet av forskningen har även gjorts tillgängligt i ett datorverktyg för att noggrant kunna ta fram lokala modeller och identifiera parametrar i dynamiska robotmodeller. / Industrial robots are today essential components in the manufacturing industry where they are used to save costs, increase productivity and quality, and eliminate dangerous and laborious work. High demands on accuracy and speed of the robot motion require that the mathematical models, used in the motion control system, are accurate. The models are used to describe the complicated nonlinear relation between the robot motion and the motors that cause the motion. Accurate dynamic robot models are needed in many areas, such as mechanical design, performance simulation, control, diagnosis, and supervision. A trend in industrial robots is toward lightweight robot structures, where the weight is reduced but with a preserved payload capacity. This is motivated by cost reduction as well as safety issues, but results in a weaker (more compliant) mechanical structure with enhanced elastic effects. For high performance, it is therefore necessary to have models describing these elastic effects. This thesis deals with identification of dynamic robot models, which means that measurements from the robot motion are used to estimate unknown parameters in the models. The measured signals are angular position and torque of the motors. Identifying robot models is a challenging task since an industrial robot is a multivariable, nonlinear, unstable, and resonant system. In this thesis, the unknown parameters (typically spring-damper pairs) in a physically parameterized nonlinear dynamic model are identified, mainly in the frequency domain, using estimates of the nonparametric frequency response function (FRF) in different robot configurations/positions. Each nonparametric FRF then describe the local behavior around an operating point. The nonlinear parametric robot model is linearized in the same operating points and the optimal parameters are obtained by minimizing the discrepancy between the nonparametric FRFs and the parametric FRFs (the FRFs of the linearized parametric robot model). Methods for estimating the nonparametric FRF from experimental data are analyzed with respect to bias, variance, and nonlinearities. In order to accurately estimate the nonparametric FRF, the experiments must be carefully designed. To minimize the uncertainty in the estimated parameters, the selection of optimal robot configurations/positions for the experiments is also part of the design. Different parameter estimators are compared in the thesis and experimental results show the usefulness of the proposed identification procedure. The identified nonlinear robot model gives a good global description of the dynamics in the frequency range of interest. The research work is also implemented and made easily available in a software tool for accurate estimation of nonparametric FRFs as well as parametric robot models.

Virtual manufacturing has gained considerable importance in the last decade. To obtain reliable predictions in a virtual environment, the factors that influence the outcome of a manufacturing operation need to be carefully modeled and integrated in a simulation platform. The dynamic behavior of the Computer Numerical Control (CNC) system, which has a profound influence on the final part geometry and tolerance integrity, is among these factors. Classical CNC drive identification techniques are usually time consuming and need to be performed by an engineer qualified in dynamics and control theory. These techniques require the servo loop or the trajectory interpolator to be disconnected in order to inject the necessary identification signals, causing downtime to the machine. Hence, these techniques are usually not practical for constructing virtual models of existing CNC machine tools in a manufacturing environment. This thesis presents an alternative strategy for constructing virtual drive models with minimal intervention and downtime to the machinery. The proposed technique, named “rapid identification”, consists of executing a short G-code experiment and collecting input/output data using the motion capture feature available on most CNC controllers. The data is then processed to reverse engineer the equivalent tracking and disturbance transfer functions and friction characteristics of the machine. It is shown that virtual drive models constructed this way can be used to predict the real machine’s contouring performance for large class of drive systems, controlled with different control techniques. In the proposed scheme, the excitation is delivered by smoothly interpolated motion commands. Hence, convergence of parameters to their true values is not guaranteed. When the real system contains pole-zero cancellations, namely due to feedforward control action, this also results in a loss of identifiability. In order to guarantee the stability of the identified drive models, the pole locations are constrained with frequency and damping ratio limits. Hence, the rapid identification task is cast as a constrained minimization problem. Two solution strategies have been developed. In the first approach, Lagrange Multipliers (LM) technique is applied, which yields successful estimation results. However, implementation of LM is computationally intensive and requires the use of a dedicated symbolic solver. This limits the portability for industrial implementation. In the second approach, a Genetic Algorithm (GA) search technique is developed, which is a more practical but slightly approximate alternative. The GA allows parameter bounds to be incorporated in a natural manner and converges to 2-3% vicinity of the LM solution in one-tenth of the computation time. The GA solution can be easily ported to different computation platforms. Both LM and GA identification techniques were validated in simulations and experiments conducted on virtual and real machine tool drives. It is shown that although the parameters estimated using the rapid identification scheme do not always match their true values, the key tracking and disturbance rejection characteristics of the drives are successfully captured in the frequency range of the CNC motion commands. Therefore, the drive models constructed with rapid identification can be used to predict the contouring accuracy of real machine tools in a virtual process planning environment. This thesis presents an alternative strategy for constructing virtual drive models with minimal intervention and downtime to the machinery. The proposed technique, named “rapid identification”, consists of executing a short G-code experiment and collecting input/output data using the motion capture feature available on most CNC controllers. The data is then processed to reverse engineer the equivalent tracking and disturbance transfer functions and friction characteristics of the machine. It is shown that virtual drive models constructed this way can be used to predict the real machine’s contouring performance for large class of drive systems, controlled with different control techniques. In the proposed scheme, the excitation is delivered by smoothly interpolated motion commands. Hence, convergence of parameters to their true values is not guaranteed. When the real system contains pole-zero cancellations, namely due to feedforward control action, this also results in a loss of identifiability. In order to guarantee the stability of the identified drive models, the pole locations are constrained with frequency and damping ratio limits. Hence, the rapid identification task is cast as a constrained minimization problem. Two solution strategies have been developed. In the first approach, Lagrange Multipliers (LM) technique is applied, which yields successful estimation results. However, implementation of LM is computationally intensive and requires the use of a dedicated symbolic solver. This limits the portability for industrial implementation. In the second approach, a Genetic Algorithm (GA) search technique is developed, which is a more practical but slightly approximate alternative. The GA allows parameter bounds to be incorporated in a natural manner and converges to 2-3% vicinity of the LM solution in one-tenth of the computation time. The GA solution can be easily ported to different computation platforms. Both LM and GA identification techniques were validated in simulations and experiments conducted on virtual and real machine tool drives. It is shown that although the parameters estimated using the rapid identification scheme do not always match their true values, the key tracking and disturbance rejection characteristics of the drives are successfully captured in the frequency range of the CNC motion commands. Therefore, the drive models constructed with rapid identification can be used to predict the contouring accuracy of real machine tools in a virtual process planning environment.

No description available.