Queueing Models with Vacations and Working Vacations

The thesis entitled “Queueing Models with Vacations and Working Vacations" consists of seven chapters including the introductory chapter. In chapters 2 to 7 we analyze different queueing models highlighting the role played by vacations and working vacations. The duration of vacation is exponentially distributed in all these models and multiple vacation policy is followed.In chapter 2 we discuss an M/M/2 queueing system with heterogeneous servers, one of which is always available while the other goes on vacation in the absence of customers waiting for service. Conditional stochastic decomposition of queue length is derived. An illustrative example is provided to study the effect of the input parameters on the system performance measures. Chapter 3 considers a similar setup as chapter 2. The model is analyzed in essentially the same way as in chapter 2 and a numerical example is provided to bring out the qualitative nature of the model. The MAP is a tractable class of point process which is in general nonrenewal. In spite of its versatility it is highly tractable as well. Phase type distributions are ideally suited for applying matrix analytic methods. In all the remaining chapters we assume the arrival process to be MAP and service process to be phase type. In chapter 4 we consider a MAP/PH/1 queue with working vacations. At a departure epoch, the server finding the system empty, takes a vacation. A customer arriving during a vacation will be served but at a lower rate.Chapter 5 discusses a MAP/PH/1 retrial queueing system with working vacations.In chapter 6 the setup of the model is similar to that of chapter 5. The signicant dierence in this model is that there is a nite buer for arrivals.Chapter 7 considers an MMAP(2)/PH/1 queueing model with a nite retrial group

Lead free heterogeneous multilayers with giant magneto electric coupling for microelectronics/microelectromechanical systems applications

Lead free magneto electrics with a strong sub resonant (broad frequency range) magneto electric coupling coefficient (MECC) is the goal of the day which can revolutionise the microelectronics and microelectromechanical systems (MEMS) industry. We report giant resonant MECC in lead free nanograined Barium Titanate–CoFe (Alloy)-Barium Titanate [BTO-CoFe-BTO] sandwiched thin films. The resonant MECC values obtained here are the highest values recorded in thin films/ multilayers. Sub-resonant MECC values are quite comparable to the highest MECC reported in 2-2 layered structures. MECC got enhanced by two orders at a low frequency resonance. The results show the potential of these thin films for transducer, magnetic field assisted energy harvesters, switching devices, and storage applications. Some possible device integration techniques are also discussed

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Computation of locally free class groups

We show that the locally free class group of an order in a semisimple algebra over a number field is isomorphic to a certain ray class group. This description is then used to present an algorithm that computes the locally free class group. The algorithm is implemented in MAGMA for the case where the algebra is a group ring over the rational numbers.

Gender and Space in Tehran

Abstract: This dissertation generally concentrates on the relationships between “gender” and “space” in the present time of urban life in capital city of Tehran. “Gender” as a changing social construct, differentiated within societies and through time, studied this time by investigation on “gender attitude” or “gender identity” means attitudes towards “gender” issues regarding Tehran residences. “Space” as a concept integrated from physical and social constituents investigated through focus on “spatial attitude” means attitudes towards using “living spaces” including private space of “house”, semi private semi public space of neighborhood and finally public spaces of the city. “Activities and practices” in space concentrated instead of “physical” space; this perspective to “space” discussed as the most justified implication of “space” in this debate regarding current situations in city of Tehran. Under a systematic approach, the interactions and interconnections between “gender” and “space” as two constituent variables of social organization investigated by focus on the different associations presented between different “gender identities” and their different “spatial identities”; in fact, “spatial identity” manifests “gender identity” and in opposite direction, “spatial identity” influences to construction of “gender identity”. The hypotheses of case study in Tehran defined as followed: • “Gender identity” is reflected on “spatial identity”. Various “gender identities” in Tehran present different perspectives of “space” or they identify “space” by different values. • As “gender identity” internalizes patriarchal oppression, it internalizes associated “spatial” oppression too. • Within the same social class, different “gender identities” related to men and women, present interconnected qualities, compared with “gender identities” related to men or women of different social classes. This situation could be found in the “spatial” perspectives of different groups of men and women too. • Following the upper hypotheses, “spatial” oppression differs among social classes of Tehran living in different parts of this city. This research undertook a qualitative study in Tehran by interviewing with different parents of both young daughter and son regarding their attitudes towards gender issues from one side and activities and behaviors of their children in different spaces from the other side. Results of case study indicated the parallel changes of parents’ attitudes towards “gender” and “spatial” issues; it means strong connection between “gender” and “space”. It revealed association of “equal” spatial attitudes with “open, neutral” gender attitudes, and also the association of “biased, unequal” spatial identities with “conservative patriarchal” gender identities. It was cleared too that this variable concept – gender space - changes by “sex”; mothers comparing fathers presented more equitable notions towards “gender spatial” issues. It changes too by “social class” and “educational level”, that means “gender spatial” identity getting more open equitable among more educated people of middle and upper classes. “Breadwinning status in the family” also presents its effect on the changes of “gender spatial” identity so participant breadwinners in the family expressed relatively more equitable notions comparing householders and housekeepers. And finally, “gender spatial” identity changes through “place” in the city and regarding South – North line of the city. The illustration of changes of “gender spatial” identity from “open” to “conservative” among society indicated not only vertical variation across social classes, furthermore the horizontal changing among each social class. These results also confirmed hypotheses while made precision on the third one regarding variable of sex. More investigations pointed to some inclusive spatial attitudes throughout society penetrated to different groups of “gender identities”, to “opens” as to “conservatives”, also to groups between them, by two opposite features; first kind, conservative biased spatial practices in favor of patriarchal gender relations and the second, progressive neutral actions in favor of equal gender relations. While the major reason for the inclusive conservative practices was referred to the social insecurity for women, the second neutral ones associated to more formal & safer spaces of the city. In conclusion, while both trends are associated deeply with the important issues of “sex” & “body” in patriarchal thoughts, still strong, they are the consequences of the transitional period of social change in macro level, and the challenges involved regarding interactions between social orders, between old system of patriarchy, the traditional biased “gender spatial” relations and the new one of equal relations. The case study drew an inhomogeneous illustration regarding gender spatial aspects of life in Tehran, the opposite groups of “open” and “conservative”, and the large group of “semi open semi conservative” between them. In macro perspective it presents contradicted social groups according their general life styles; they are the manifestations of challenging trends towards tradition and modernity in Iranian society. This illustration while presents unstable social situations, necessitates probing solutions for social integration; exploring the directions could make heterogeneous social groups close in the way they think and the form they live in spaces. Democratic approaches like participatory development planning might be helpful for the city in its way to more solidarity and sustainability regarding its social spatial – gender as well – development, in macro levels of social spatial planning and in micro levels of physical planning, in private space of house and in public spaces of the city.

Information Exchange and Fusion in Dynamic and Heterogeneous Distributed Environments

Context awareness, dynamic reconfiguration at runtime and heterogeneity are key characteristics of future distributed systems, particularly in ubiquitous and mobile computing scenarios. The main contributions of this dissertation are theoretical as well as architectural concepts facilitating information exchange and fusion in heterogeneous and dynamic distributed environments. Our main focus is on bridging the heterogeneity issues and, at the same time, considering uncertain, imprecise and unreliable sensor information in information fusion and reasoning approaches. A domain ontology is used to establish a common vocabulary for the exchanged information. We thereby explicitly support different representations for the same kind of information and provide Inter-Representation Operations that convert between them. Special account is taken of the conversion of associated meta-data that express uncertainty and impreciseness. The Unscented Transformation, for example, is applied to propagate Gaussian normal distributions across highly non-linear Inter-Representation Operations. Uncertain sensor information is fused using the Dempster-Shafer Theory of Evidence as it allows explicit modelling of partial and complete ignorance. We also show how to incorporate the Dempster-Shafer Theory of Evidence into probabilistic reasoning schemes such as Hidden Markov Models in order to be able to consider the uncertainty of sensor information when deriving high-level information from low-level data. For all these concepts we provide architectural support as a guideline for developers of innovative information exchange and fusion infrastructures that are particularly targeted at heterogeneous dynamic environments. Two case studies serve as proof of concept. The first case study focuses on heterogeneous autonomous robots that have to spontaneously form a cooperative team in order to achieve a common goal. The second case study is concerned with an approach for user activity recognition which serves as baseline for a context-aware adaptive application. Both case studies demonstrate the viability and strengths of the proposed solution and emphasize that the Dempster-Shafer Theory of Evidence should be preferred to pure probability theory in applications involving non-linear Inter-Representation Operations.

Heterogeneous Multi-Robot Cooperation

This report addresses the problem of achieving cooperation within small- to medium- sized teams of heterogeneous mobile robots. I describe a software architecture I have developed, called ALLIANCE, that facilitates robust, fault tolerant, reliable, and adaptive cooperative control. In addition, an extended version of ALLIANCE, called L-ALLIANCE, is described, which incorporates a dynamic parameter update mechanism that allows teams of mobile robots to improve the efficiency of their mission performance through learning. A number of experimental results of implementing these architectures on both physical and simulated mobile robot teams are described. In addition, this report presents the results of studies of a number of issues in mobile robot cooperation, including fault tolerant cooperative control, adaptive action selection, distributed control, robot awareness of team member actions, improving efficiency through learning, inter-robot communication, action recognition, and local versus global control.

Improving Multi-class Text Classification with Naive Bayes

There are numerous text documents available in electronic form. More and more are becoming available every day. Such documents represent a massive amount of information that is easily accessible. Seeking value in this huge collection requires organization; much of the work of organizing documents can be automated through text classification. The accuracy and our understanding of such systems greatly influences their usefulness. In this paper, we seek 1) to advance the understanding of commonly used text classification techniques, and 2) through that understanding, improve the tools that are available for text classification. We begin by clarifying the assumptions made in the derivation of Naive Bayes, noting basic properties and proposing ways for its extension and improvement. Next, we investigate the quality of Naive Bayes parameter estimates and their impact on classification. Our analysis leads to a theorem which gives an explanation for the improvements that can be found in multiclass classification with Naive Bayes using Error-Correcting Output Codes. We use experimental evidence on two commonly-used data sets to exhibit an application of the theorem. Finally, we show fundamental flaws in a commonly-used feature selection algorithm and develop a statistics-based framework for text feature selection. Greater understanding of Naive Bayes and the properties of text allows us to make better use of it in text classification.

Safe Distributed Coordination of Heterogeneous Robots through Dynamic Simple Temporal Networks

Research on autonomous intelligent systems has focused on how robots can robustly carry out missions in uncertain and harsh environments with very little or no human intervention. Robotic execution languages such as RAPs, ESL, and TDL improve robustness by managing functionally redundant procedures for achieving goals. The model-based programming approach extends this by guaranteeing correctness of execution through pre-planning of non-deterministic timed threads of activities. Executing model-based programs effectively on distributed autonomous platforms requires distributing this pre-planning process. This thesis presents a distributed planner for modelbased programs whose planning and execution is distributed among agents with widely varying levels of processor power and memory resources. We make two key contributions. First, we reformulate a model-based program, which describes cooperative activities, into a hierarchical dynamic simple temporal network. This enables efficient distributed coordination of robots and supports deployment on heterogeneous robots. Second, we introduce a distributed temporal planner, called DTP, which solves hierarchical dynamic simple temporal networks with the assistance of the distributed Bellman-Ford shortest path algorithm. The implementation of DTP has been demonstrated successfully on a wide range of randomly generated examples and on a pursuer-evader challenge problem in simulation.

A Note on Object Class Representation and Categorical Perception

We present a novel scheme ("Categorical Basis Functions", CBF) for object class representation in the brain and contrast it to the "Chorus of Prototypes" scheme recently proposed by Edelman. The power and flexibility of CBF is demonstrated in two examples. CBF is then applied to investigate the phenomenon of Categorical Perception, in particular the finding by Bulthoff et al. (1998) of categorization of faces by gender without corresponding Categorical Perception. Here, CBF makes predictions that can be tested in a psychophysical experiment. Finally, experiments are suggested to further test CBF.

The Individual is Nothing, the Class Everything: Psychophysics and Modeling of Recognition in Obect Classes

Most psychophysical studies of object recognition have focussed on the recognition and representation of individual objects subjects had previously explicitely been trained on. Correspondingly, modeling studies have often employed a 'grandmother'-type representation where the objects to be recognized were represented by individual units. However, objects in the natural world are commonly members of a class containing a number of visually similar objects, such as faces, for which physiology studies have provided support for a representation based on a sparse population code, which permits generalization from the learned exemplars to novel objects of that class. In this paper, we present results from psychophysical and modeling studies intended to investigate object recognition in natural ('continuous') object classes. In two experiments, subjects were trained to perform subordinate level discrimination in a continuous object class - images of computer-rendered cars - created using a 3D morphing system. By comparing the recognition performance of trained and untrained subjects we could estimate the effects of viewpoint-specific training and infer properties of the object class-specific representation learned as a result of training. We then compared the experimental findings to simulations, building on our recently presented HMAX model of object recognition in cortex, to investigate the computational properties of a population-based object class representation as outlined above. We find experimental evidence, supported by modeling results, that training builds a viewpoint- and class-specific representation that supplements a pre-existing repre-sentation with lower shape discriminability but possibly greater viewpoint invariance.

Visual Recognition and Categorization on the Basis of Similarities to Multiple Class Prototypes

To recognize a previously seen object, the visual system must overcome the variability in the object's appearance caused by factors such as illumination and pose. Developments in computer vision suggest that it may be possible to counter the influence of these factors, by learning to interpolate between stored views of the target object, taken under representative combinations of viewing conditions. Daily life situations, however, typically require categorization, rather than recognition, of objects. Due to the open-ended character both of natural kinds and of artificial categories, categorization cannot rely on interpolation between stored examples. Nonetheless, knowledge of several representative members, or prototypes, of each of the categories of interest can still provide the necessary computational substrate for the categorization of new instances. The resulting representational scheme based on similarities to prototypes appears to be computationally viable, and is readily mapped onto the mechanisms of biological vision revealed by recent psychophysical and physiological studies.

Context Interchange as a Scalable Solution to Interoperating Amongst Heterogeneous Dynamic Services

Many online services access a large number of autonomous data sources and at the same time need to meet different user requirements. It is essential for these services to achieve semantic interoperability among these information exchange entities. In the presence of an increasing number of proprietary business processes, heterogeneous data standards, and diverse user requirements, it is critical that the services are implemented using adaptable, extensible, and scalable technology. The COntext INterchange (COIN) approach, inspired by similar goals of the Semantic Web, provides a robust solution. In this paper, we describe how COIN can be used to implement dynamic online services where semantic differences are reconciled on the fly. We show that COIN is flexible and scalable by comparing it with several conventional approaches. With a given ontology, the number of conversions in COIN is quadratic to the semantic aspect that has the largest number of distinctions. These semantic aspects are modeled as modifiers in a conceptual ontology; in most cases the number of conversions is linear with the number of modifiers, which is significantly smaller than traditional hard-wiring middleware approach where the number of conversion programs is quadratic to the number of sources and data receivers. In the example scenario in the paper, the COIN approach needs only 5 conversions to be defined while traditional approaches require 20,000 to 100 million. COIN achieves this scalability by automatically composing all the comprehensive conversions from a small number of declaratively defined sub-conversions.