Miracle-dz/UniFAR-FTUs huggingface dataset:
Indexing for Xml Types Abstract Indexing for Xml Types

Indexing for XML Types Karima Echihabi Master of Science Graduate Department of Computer Science University of Toronto 2002 XML is increasingly gaining ground as a standard for data representation and exchange over the web. XML data most often has some embedded structure; therefore, it is interesting to exploit this structure whenever present. The structure of an XML document can be modeled by DTDs, XML Schema, or XQuery types. Both XML Schema and XQuery have a type system that supports a subtyping relation between types. The purpose of this thesis is to develop an indexing mechanism, called Tindex, that e ciently retrieves supertypes of an XML type. We consider XQuery types and DTDs, and our indexing mechanism can be extended to XML Schema. The main research challenge for indexing XML types is the complex nature of terms to index, i.e. terms are regular expressions. Tindex can be used in query optimization, storage optimization, data integration, and XML data repositories. ii Acknowledgements I was rst inspired to pursue my graduate studies when I was working at Microsoft Corp. Redmond, Washington as a Software Engineer. So, I enrolled as a part-time student at the University of Washington. After taking a database course, I decided that I wanted to spend more time learning about the database eld speci cally XML data management. So, when the opportunity came to study full-time at the University of Toronto, I decided to seize it. Going back to school was full of challenges, but also full of reward. I am happy I went through this endeavor. I am thankful to my Supervisor Prof. Alberto Mendelzon for his guidance, advice and patience during my research. I would also like to extend my thanks to my second reader Prof. Ken Sevcik for his valuable time and comments. My sincere thanks also go to my o cemates for their support during stressful times, and my mentors Susan Sim from UofT, and Ann Gruhn from IBM for their advice on how to succeed in graduate school. Finally, my deepest gratitude goes to my mother Zainab, my father Lahoussaine, my sister So a, my brothers Abdelhamid and Ali, and my ance Younes for their emotional support and encouragement. I dedicate this thesis to all of them with all my love. iii
Effects of phase leg reactor, submodule capacitor, number of submodules and switching frequency on harmonics in modular multilevel converters

The modular multilevel converter (M2C) will play an important role in the future especially for high-voltage and high-power applications where controllability is a key factor. Although a lot of research has been carried out on this topic, little has been done to understand how different system parameters, like the arm reactor, the submodule capacitor, number of submodules and switching frequency, influence the performance of the converter. In this study, a robust model of a M2C was presented and used to perform an extensive parametric sweep versus the variables mentioned above. It has been shown that by implementing an anti-windup scheme, the model remains stable over a large range of parameters. It has also been shown that an optimum knee point exists in all total harmonic distortion (THD) graphs versus inductance, capacitance, number of submodules and switching frequency. Finally, it has been shown that to decrease THD, the number of submodules can be increased while making sure the effective arm capacitance is maintained constant.
Implementation and analysis of the histograms of oriented Gradients algorithm on a heterogeneous multicore CPU/GPU architecture

Due to the integration of multiple heterogeneous processing units on a single die, programmers can make use of processors with various features. For instance, the Samsung Exynos 5 Octa mobile processor features two ARM CPU clusters (Cortex-A7/A15), a mobile Mali GPU, and a dedicated image processor (codec). However, data transfer delays and missing data coherencies between clusters complicate heterogeneous programming. Programs should not only scale over multiple cores, but also distribute the work over heterogeneous processing units. Depending on the algorithm and platform characteristics, the selection of a proper partitioning scheme appears as a challenging task. In this work, we present a heterogeneous implementation of the Histograms of Oriented Gradients algorithm as a case study, which is a key algorithm in the field of driver assistance systems. The implementation is targeted on the CPU-clusters and the GPU of the Samsung Exynos 5 Octa 5422. In order to generate the best partitioning scheme, we specifically discuss different strategies. Therefore, we analyze the computational capabilities as well as the power consumption of the individual processing units using different algorithmic processing stages. We show that a GPU-only execution slows down the computation compared with the CPU-only version, while mapping to both devices (CPU and GPU) achieves a speedup of 1.68.
A simulation approach to structure-based software reliability analysis

Structure-based techniques enable an analysis of the influence of individual components on the application reliability. In an effort to ensure analytical tractability, prevalent structure-based analysis techniques are based on assumptions which preclude the use of these techniques for reliability analysis during the testing and operational phases. In this paper, we develop simulation procedures to assess the impact of individual components on the reliability of an application in the presence of fault detection and repair strategies that may be employed during testing. We also develop simulation procedures to analyze the application reliability for various operational configurations. We illustrate the potential of simulation procedures using several examples. Based on the results of these examples, we provide novel insights into how testing and repair strategies can be tailored depending on the application structure to achieve the desired reliability in a cost-effective manner. We also discuss how the results could be used to explore alternative operational configurations of a software application taking into consideration the application structure so as to cause minimal interruption in the field.
Playing ‘games’ with human health the role of game theory in optimizing reliability in wireless health networks

Current advances in wireless sensor networks have contributed to the development of multi-hop wireless body sensor networks (WBSNs). These networks, which are primarily comprised of low-power sensor nodes, provide long term health and physiological monitoring of patients without obstructing their normal activities. However, the time-varying nature of network resources poses a significant challenge to the high reliability of operations required of a body sensor network. In this paper, we address the problem of reliability optimization in multi-hop WBSNs, where the nodes co-operate with each other in maximizing system performance. We model our problem as a co-operative game which inherently induces a distributed mechanism that optimizes the reliability of network operations in a multi-hop WBSN supporting concurrent applications. By the term ‘reliability’, we imply the system utility generated when each sensor node (user) services its specific application. We denote the system utility as an instance of the vector of utilities of individual users, where each user's utility is a function of its allocated bandwidth. Our mechanism jointly accounts for the dynamistic nature of the wireless medium, application quality of service, user fairness in achieving the resources to service applications, and results in an optimal operating point (utility vector) at which the WBSN should operate. We arrive at the result that the Nash bargaining solution of the co-operative game gives us the optimal system operating point, i.e., the Nash bargaining solution optimizes the overall system reliability.
Applied Data Mining Approach in Ubiquitous World of Air Transportation

Noise is a big problem for people living near airports, therefore the public, airport authorities and pilots are looking for ways to reduce the noise in the vicinity of populated areas. Optimal solution would be flight paths that are farthest from those areas, and worst paths are those, that just go above them. There are two classes of paths, namely optimal and non-optimal ones. This paper is going to use one of successfully used data mining techniques, namely neural network, which is capable of recognizing patterns. We used some coordinates of various flight paths as input for learning purposes of Neural Network, and defined two classes representing the optimal and non-optimal flight paths. The results have shown that this technique is well capable of recognizing the optimal and non-optimal flight paths. This technique can be used to reduce the noise.
Satisfying multiple constraints in real-time database systems

Real-time database systems, such as military command, control and communication, avionics, radar tracking, and managing automated factories, have timing constraints and temporal consistency constraints. The timing constraint requires a transaction to be completed by a specified deadline. The temporal consistency constraints require that data read by a transaction be up-to-date. In such environments, multiple users share the same database, and some of the users may have restricted access to information from the database. Hence, in addition to maintaining timing and temporal consistency constraints, it is also necessary to provide security for real-time databases. Satisfying more than one constraint in a real-time database system is challenging because maintaining one constraint often means the sacrifice of another. For example, in order to meet a deadline, a transaction may have to read some out-of-date data and as a result, may become temporally inconsistent. Similarly, maintenance of security may require some transactions be blocked or restarted. As a result, those transactions may miss their deadlines. Most research on real-time database systems has addressed timing constraints only and not security or temporal constraints. In this work, we propose to examine multiple constraints in real-time database systems, specifically, maintaining security and temporal consistency in real-time database systems. The objective of this work is twofold. Our first goal is to incorporate security constraints in real-time database systems in such a way that not only is security achieved, but achieving security does not degrade real-time performance significantly. We present new concurrency control algorithms for maintaining security in a real-time database system. These algorithms specially aim at closing or removing covert channels, which facilitate an indirect flow of information between users at two different security levels. We identify the properties of secure real-time database systems. We propose metrics to measure the consequences of introducing a covert channel. We also propose strategies to trade-off between timeliness and security. We present and implement a simulation model for a real-time database system. We implement our new algorithms based these strategies and algorithms and study their performance using a real-time database system simulation. For our second goal, we propose novel strategies for maintaining temporal consistency. A real-time temporal database system mainly consists of two types of data objects, sensor objects and derived objects. A sensor object is obtained directly from sensors monitoring the real world. The value of a derived object is computed from a set of other objects, known as the read-set …
University ’ s repository of research publications and other research outputs SMEs and banks : investigating the link between trust and the pledging of personal collateral Conference Item

Research on relationship lending focuses attention on economic factors which influence the relationships between SMEs’ owners/managers and banks but no previous work has focused on the role of trust. Trust is expected to reduce agency costs, the perceived credit risk and, thus, influence credit availability and credit terms. Trustworthiness is associated with three attributes of SME owner managers’ namely; ability, benevolence and integrity. It is hypothesised that lending managers’ assessment of the trustworthiness of SME owner managers affects the request of personal collateral from bank when credit is provided. Trustworthiness is hypothesised as negatively associated with personal collateral in the form of personal guarantees and personal assets. Using the data obtained from a survey of lending managers from banks in North East Italy we test this relationship. Research methods include construction of control variables and a vector of trustworthiness factors based on the data collected on a random sample of 535 borrowing firms. Results from the regression analysis show some evidence that the line of credit of firms enjoying high level of trust are less collateralised with entrepreneurs’ personal assets even if the significance of both the specification and trust is low. Our findings support the view found in earlier literature on trust that personal collateral pledging is decided at the beginning of the relationship and then such a decision is not changed by the bank. Some implications of these results and future research are discussed.
An interpreter for framework-specific modeling languages

Framework-specific modeling languages (FSMLs) are specifications of framework concepts and their intended usages. Interpreting an FSML over a set of applications enables a user to detect framework concepts in source code through reverse-engineering. We describe our FSML interpreter written using Prolog. The interpreter itself consists of two main components: a parser that is responsible for reading an FSML specification and an engine, responsible for interpreting the constraints of the FSML and reverseengineering an FSML instance from a set of program facts. We discuss the purpose of each component and further highlight the advantages, as well as disadvantages of our implementation.
Enhancement of speech recognition using a variable-length frame overlapping method

This paper proposes a method of determining a variable-length frame overlap between two consecutive frames for speech recognition. Compared with the conventional fixed-length frame overlapping method, the proposed method can improve the performance of speech signal processing when performing the front-end processing procedure of speech recognition. By varying the length of frame overlaps using the proposed method, a more accurate feature vector of speech signals will be extracted. Experiment results show that the proposed variable-length frame overlapping approach is apparently superior to the conventional fixed-length one in recognition performance.
Effects of Laissez-Faire Leadership on Commitment to Service Quality

This study aims to examine the validity of Laissez-Faire leadership style among the medical practitioners. This leadership style has been criticized in the literature as the destructive style of leadership. However, laissez-faire leadership style has been responsive for numerous positive behaviors and outcomes at the workplace. Laissez-faire leadership style has remained permissive with other leadership style types. Nonetheless, in comparison with other leadership styles, its significance has been unexplored especially in domains like commitment and service organization. In this study, the authors analyzed how Laissez-Faire leadership relates to the commitment of service quality. While using self-administered approach, the current study sampled doctors from public hospitals of Pakistan. The Partial Least Square Path Modeling results via Smart PLS 2.0 with 182 retained responses. The results indicated that laissez-faire type of leadership persists, and paramount in the services sector and also showed a significant effect on doctor’s commitment. The current research found a significant impact of laissez-faire leadership on doctors’ commitment. Therefore, from the findings, it is referred that this study holds theoretical and practical implications also suggest future directions.
Introduction to String Theory and Gauge/Gravity duality for students in QCD and QGP phenomenology

String theory has been initially derived from motivations coming from strong interaction phenomenology,but its application faced deep conceptual and practical difficulties. The strong interactions found their theoretical foundation elsewhere, namely on QCD, the quantum gauge field theory of quarks and gluons. Recently, the Gauge/Gravity correspondence allowed to initiate a reformulation of the connection between strings and gauge field theories, avoiding some of the initial drawbacks and opening the way to new insights on the gauge theory at strong coupling and eventually QCD. Among others, the recent applications of the Gauge/Gravity correspondence to the formation of the QGP, the quark-gluon plasma, in heavy-ion reactions seem to provide a physically interesting insight on phenomenological features of the reactions. In these lectures we will give a simplified introduction to those aspects of string theory which, at the origin and in the recent developments, are connected to strong interactions, for those students which are starting to learn QCD and QGP physics from an experimental or phenomenological point of view.
A fast clustering algorithm based on grid and density

The efficiency of data mining algorithms is a very important issue as data becoming larger and larger. Density-based clustering analysis can discover clusters with arbitrary shape and is insensitive to noise data. The advantage of grid-based clustering method is linear time complexity. In this paper, we present a new clustering algorithm CLUGD relying on grid and density. We first construct a grid of relevant portion. Then the algorithm finds references by grid and classifies these references to core references and bound references. Then it attaches the data of the bound references to the nearest core references and aggregation the core references in neighboring portions. At last, in-direct graph is used to classify these core references and maps cluster to original data. We performed an experimental evaluation of effectiveness and efficiency of CLUGD using synthetic data and the data of the SEQUOIA 2000 Benchmark. Both theory analysis and experimental results confirm that CLUGD can discover clusters with arbitrary shape and is insensitive to noise data. In the meanwhile, its executing efficiency is much higher than DBSCAN algorithm based on R*-tree
lac Repressor Is an Antivirulence Factor of Salmonella enterica: Its Role in the Evolution of Virulence in Salmonella

The genus Salmonella includes many pathogens of great medical and veterinary importance. Bacteria belonging to this genus are very closely related to those belonging to the genus Escherichia. lacZYA operon and lacI are present in Escherichia coli, but not in Salmonella enterica. It has been proposed that Salmonella has lost lacZYA operon and lacI during evolution. In this study, we have investigated the physiological and evolutionary significance of the absence of lacI in Salmonella enterica. Using murine model of typhoid fever, we show that the expression of LacI causes a remarkable reduction in the virulence of Salmonella enterica. LacI also suppresses the ability of Salmonella enterica to proliferate inside murine macrophages. Microarray analysis revealed that LacI interferes with the expression of virulence genes of Salmonella pathogenicity island 2. This effect was confirmed by RT-PCR and Western blot analysis. Interestingly, we found that SBG0326 of Salmonella bongori is homologous to lacI of Escherichia coli. Salmonella bongori is the only other species of the genus Salmonella and it lacks the virulence genes of Salmonella pathogenicity island 2. Overall, our results demonstrate that LacI is an antivirulence factor of Salmonella enterica and suggest that absence of lacI has facilitated the acquisition of virulence genes of Salmonella pathogenicity island 2 in Salmonella enterica making it a successful systemic pathogen.
Child and Parent Predictors of Perceptions of Parent—Child Relationship Quality

Objective/Method: Predictors of perceptions of parent—child relationship quality were examined for 175 children with ADHD, 119 comparison children, and parents of these children, drawn from the follow-up phase of the Multimodal Treatment Study of Children with ADHD. Results/Conclusion: Children with ADHD perceived their mothers and fathers as more power assertive than comparison children. Children higher on depressive symptomatology also perceived their mothers and fathers as less warm and more power assertive. Mothers perceived themselves as more power assertive and fathers perceived themselves as less warm if they were higher on depressive symptomatology themselves or had children with ADHD or higher levels of depressive symptomatology. Several interactions indicated that the association between child factors and parental perceptions of warmth and power assertion often depended on parental depressive symptomatology. The findings resolve a previous contradiction in the literature regarding the relationship between child depressive symptoms and parental perceptions of parent—child relationship quality. (J. of Att. Dis. 2007;11(1) 37-48)
Calculation of CPU performance, power and cost using Hadoop

Technology is progressing at a fast pace, and it is the need of the hour to scrutinize big data workloads on cloud computing. The requisite of working with large data sets and more secure platforms gives rise to the necessity of analyzing techniques and tools regarding performance and power consumption. One of the most frequently used big data cloud computing framework is Hadoop. Hadoop — an open source implementation of MapReduce — is employed for processing big data, while handling extensive workload applications for several purposes. The performance, cost and power estimations of underlying processors on Hadoop can be done by characterizing different workloads on Hadoop framework. A comprehensive study is carried out to calculate CPU performance, cost and power consumption regarding different workloads, so as to facilitate efficient usage of different processors to deal with various workloads according to the user requirements.
MATCHUP: Memory Abstractions for Heap Manipulating Programs

Memory-intensive implementations often require access to an external, off-chip memory which can substantially slow down an FPGA accelerator due to memory bandwidth limitations. Buffering frequently reused data on chip is a common approach to address this problem and the optimization of the cache architecture introduces yet another complex design space. This paper presents a high-level synthesis (HLS) design aid that generates parallel application-specific multi-scratchpad architectures including on-chip caches. Our program analysis identifies non-overlapping memory regions, supported by private scratchpads, and regions which are shared by parallel units after parallelization and which are supported by coherent scratchpads and synchronization primitives. It also decides whether the parallelization is legal with respect to data dependencies. The novelty of this work is the focus on programs using dynamic, pointer-based data structures and dynamic memory allocation which, while common in software engineering, remain difficult to analyze and are beyond the scope of the overwhelming majority of HLS techniques to date. We demonstrate our technique with three case studies of applications using dynamically allocated data structures and use Xilinx Vivado HLS as an exemplary HLS tool. We show up to 10x speed-up after parallelization of the HLS implementations and the insertion of the application-specific distributed hybrid scratchpad architecture.