The effect of vision congruence on employee empowerment, commitment, satisfaction, and performance

Five models delineating the person-situation fit controversy were developed and tested. Hypotheses were tested to determine the linkages between vision congruence, empowerment, locus of control, job satisfaction, organizational commitment, and employee performance. Vision was defined as a mental image of a possible and desirable future state of the organization.^ Data were collected from 213 employees in a major flower import company. Participants were from various organizational levels and ethnic backgrounds. The data collection procedure consisted of three parts. First, a profile analysis instrument was used which was developed employing a Q-sort based technique, to measure the vision congruence between the CEO and each employee. Second, employees completed a survey instrument which included scales measuring empowerment, locus of control, job satisfaction, organizational commitment, and social desirability. Third, supervisor performance ratings were gathered from employee files. Data analysis consisted of using Kendall's tau to measure the correlation between CEO's and each employee's vision. Path analyses were conducted using the EQS structural equation program to test five theoretical models for goodness-of-fit. Regression analysis was employed to test whether locus of control acted as a moderator variable.^ The results showed that vision congruence is significantly related to job satisfaction and employee commitment, and perceived empowerment acts as an intervening variable affecting employee outcomes. The study also found that people with an internal locus of control were more likely to feel empowered than were those with external beliefs. Implications of these findings for both researchers and practitioners are discussed and suggestions for future research directions are provided. ^

Enabling adaptability in service aggregates using transparent shaping techniques

Distributed applications are exposed as reusable components that are dynamically discovered and integrated to create new applications. These new applications, in the form of aggregate services, are vulnerable to failure due to the autonomous and distributed nature of their integrated components. This vulnerability creates the need for adaptability in aggregate services. The need for adaptation is accentuated for complex long-running applications as is found in scientific Grid computing, where distributed computing nodes may participate to solve computation and data-intensive problems. Such applications integrate services for coordinated problem solving in areas such as Bioinformatics. For such applications, when a constituent service fails, the application fails, even though there are other nodes that can substitute for the failed service. This concern is not addressed in the specification of high-level composition languages such as that of the Business Process Execution Language (BPEL). We propose an approach to transparently autonomizing existing BPEL processes in order to make them modifiable at runtime and more resilient to the failures in their execution environment. By transparent introduction of adaptive behavior, adaptation preserves the original business logic of the aggregate service and does not tangle the code for adaptive behavior with that of the aggregate service. The major contributions of this dissertation are: first, we assessed the effectiveness of BPEL language support in developing adaptive mechanisms. As a result, we identified the strengths and limitations of BPEL and came up with strategies to address those limitations. Second, we developed a technique to enhance existing BPEL processes transparently in order to support dynamic adaptation. We proposed a framework which uses transparent shaping and generative programming to make BPEL processes adaptive. Third, we developed a technique to dynamically discover and bind to substitute services. Our technique was evaluated and the result showed that dynamic utilization of components improves the flexibility of adaptive BPEL processes. Fourth, we developed an extensible policy-based technique to specify how to handle exceptional behavior. We developed a generic component that introduces adaptive behavior for multiple BPEL processes. Fifth, we identify ways to apply our work to facilitate adaptability in composite Grid services.

Novel online data cleaning protocols for data streams in trajectory, Wireless Sensor Networks

The promise of Wireless Sensor Networks (WSNs) is the autonomous collaboration of a collection of sensors to accomplish some specific goals which a single sensor cannot offer. Basically, sensor networking serves a range of applications by providing the raw data as fundamentals for further analyses and actions. The imprecision of the collected data could tremendously mislead the decision-making process of sensor-based applications, resulting in an ineffectiveness or failure of the application objectives. Due to inherent WSN characteristics normally spoiling the raw sensor readings, many research efforts attempt to improve the accuracy of the corrupted or "dirty" sensor data. The dirty data need to be cleaned or corrected. However, the developed data cleaning solutions restrict themselves to the scope of static WSNs where deployed sensors would rarely move during the operation. Nowadays, many emerging applications relying on WSNs need the sensor mobility to enhance the application efficiency and usage flexibility. The location of deployed sensors needs to be dynamic. Also, each sensor would independently function and contribute its resources. Sensors equipped with vehicles for monitoring the traffic condition could be depicted as one of the prospective examples. The sensor mobility causes a transient in network topology and correlation among sensor streams. Based on static relationships among sensors, the existing methods for cleaning sensor data in static WSNs are invalid in such mobile scenarios. Therefore, a solution of data cleaning that considers the sensor movements is actively needed. This dissertation aims to improve the quality of sensor data by considering the consequences of various trajectory relationships of autonomous mobile sensors in the system. First of all, we address the dynamic network topology due to sensor mobility. The concept of virtual sensor is presented and used for spatio-temporal selection of neighboring sensors to help in cleaning sensor data streams. This method is one of the first methods to clean data in mobile sensor environments. We also study the mobility pattern of moving sensors relative to boundaries of sub-areas of interest. We developed a belief-based analysis to determine the reliable sets of neighboring sensors to improve the cleaning performance, especially when node density is relatively low. Finally, we design a novel sketch-based technique to clean data from internal sensors where spatio-temporal relationships among sensors cannot lead to the data correlations among sensor streams.

Customization of the design of antenna using genetic algorithm and finite-difference time-domain technique

Antenna design is an iterative process in which structures are analyzed and changed to comply with certain performance parameters required. The classic approach starts with analyzing a "known" structure, obtaining the value of its performance parameter and changing this structure until the "target" value is achieved. This process relies on having an initial structure, which follows some known or "intuitive" patterns already familiar to the designer. The purpose of this research was to develop a method of designing UWB antennas. What is new in this proposal is that the design process is reversed: the designer will start with the target performance parameter and obtain a structure as the result of the design process. This method provided a new way to replicate and optimize existing performance parameters. The base of the method was the use of a Genetic Algorithm (GA) adapted to the format of the chromosome that will be evaluated by the Electromagnetic (EM) solver. For the electromagnetic study we used XFDTD™ program, based in the Finite-Difference Time-Domain technique. The programming portion of the method was created under the MatLab environment, which serves as the interface for converting chromosomes, file formats and transferring of data between the XFDTD™ and GA. A high level of customization had to be written into the code to work with the specific files generated by the XFDTD™ program. Two types of cost functions were evaluated; the first one seeking broadband performance within the UWB band, and the second one searching for curve replication of a reference geometry. The performance of the method was evaluated considering the speed provided by the computer resources used. Balance between accuracy, data file size and speed of execution was achieved by defining parameters in the GA code as well as changing the internal parameters of the XFDTD™ projects. The results showed that the GA produced geometries that were analyzed by the XFDTD™ program and changed following the search criteria until reaching the target value of the cost function. Results also showed how the parameters can change the search criteria and influence the running of the code to provide a variety of geometries.

A generalized multidimensional index structure for multimedia data to support content-based similarity searches in a collaborative search environment

Since multimedia data, such as images and videos, are way more expressive and informative than ordinary text-based data, people find it more attractive to communicate and express with them. Additionally, with the rising popularity of social networking tools such as Facebook and Twitter, multimedia information retrieval can no longer be considered a solitary task. Rather, people constantly collaborate with one another while searching and retrieving information. But the very cause of the popularity of multimedia data, the huge and different types of information a single data object can carry, makes their management a challenging task. Multimedia data is commonly represented as multidimensional feature vectors and carry high-level semantic information. These two characteristics make them very different from traditional alpha-numeric data. Thus, to try to manage them with frameworks and rationales designed for primitive alpha-numeric data, will be inefficient. An index structure is the backbone of any database management system. It has been seen that index structures present in existing relational database management frameworks cannot handle multimedia data effectively. Thus, in this dissertation, a generalized multidimensional index structure is proposed which accommodates the atypical multidimensional representation and the semantic information carried by different multimedia data seamlessly from within one single framework. Additionally, the dissertation investigates the evolving relationships among multimedia data in a collaborative environment and how such information can help to customize the design of the proposed index structure, when it is used to manage multimedia data in a shared environment. Extensive experiments were conducted to present the usability and better performance of the proposed framework over current state-of-art approaches.

Tin oxide based composites derived using electrostatic spray deposition technique as anodes for lithium-ion batteries

Recent advances in the electric & hybrid electric vehicles and rapid developments in the electronic devices have increased the demand for high power and high energy density lithium ion batteries. Graphite (theoretical specific capacity: 372 mAh/g) used in commercial anodes cannot meet these demands. Amorphous SnO2 anodes (theoretical specific capacity: 781 mAh/g) have been proposed as alternative anode materials. But these materials have poor conductivity, undergo a large volume change during charging and discharging, large irreversible capacity loss leading to poor cycle performances. To solve the issues related to SnO2 anodes, we propose to synthesize porous SnO2 composites using electrostatic spray deposition technique. First, porous SnO2/CNT composites were fabricated and the effects of the deposition temperature (200, 250, 300 °C) & CNT content (10, 20, 30, 40 wt %) on the electrochemical performance of the anodes were studied. Compared to pure SnO2 and pure CNT, the composite materials as anodes showed better discharge capacity and cyclability. 30 wt% CNT content and 250 °C deposition temperature were found to be the optimal conditions with regard to energy capacity whereas the sample with 20% CNT deposited at 250 °C exhibited good capacity retention. This can be ascribed to the porous nature of the anodes and the improvement in the conductivity by the addition of CNT. Electrochemical impedance spectroscopy studies were carried out to study in detail the change in the surface film resistance with cycling. By fitting EIS data to an equivalent circuit model, the values of the circuit components, which represent surface film resistance, were obtained. The higher the CNT content in the composite, lower the change in surface film resistance at certain voltage upon cycling. The surface resistance increased with the depth of discharge and decreased slightly at fully lithiated state. Graphene was also added to improve the performance of pure SnO2 anodes. The composites heated at 280 °C showed better energy capacity and energy density. The specific capacities of as deposited and post heat-treated samples were 534 and 737 mAh/g after 70 cycles. At the 70th cycle, the energy density of the composites at 195 °C and 280 °C were 1240 and 1760 Wh/kg, respectively, which are much higher than the commercially used graphite electrodes (37.2–74.4 Wh/kg). Both SnO2/CNTand SnO2/grapheme based composites with improved energy densities and capacities than pure SnO2 can make a significant impact on the development of new batteries for electric vehicles and portable electronics applications.

Enhanced skip -list search algorithm in 3-layer mediator framework

The Three-Layer distributed mediation architecture, designed by Secure System Architecture laboratory, employed a layered framework of presence, integration, and homogenization mediators. The architecture does not have any central component that may affect the system reliability. A distributed search technique was adapted in the system to increase its reliability. An Enhanced Chord-like algorithm (E-Chord) was designed and deployed in the integration layer. The E-Chord is a skip-list algorithm based on Distributed Hash Table (DHT) which is a distributed but structured architecture. DHT is distributed in the sense that no central unit is required to maintain indexes, and it is structured in the sense that indexes are distributed over the nodes in a systematic manner. Each node maintains three kind of routing information: a frequency list, a successor/predecessor list, and a finger table. None of the nodes in the system maintains all indexes, and each node knows about some other nodes in the system. These nodes, also called composer mediators, were connected in a P2P fashion. ^ A special composer mediator called a global mediator initiates the keyword-based matching decomposition of the request using the E-Chord. It generates an Integrated Data Structure Graph (IDSG) on the fly, creates association and dependency relations between nodes in the IDSG, and then generates a Global IDSG (GIDSG). The GIDSG graph is a plan which guides the global mediator how to integrate data. It is also used to stream data from the mediators in the homogenization layer which connected to the data sources. The connectors start sending the data to the global mediator just after the global mediator creates the GIDSG and just before the global mediator sends the answer to the presence mediator. Using the E-Chord and GIDSG made the mediation system more scalable than using a central global schema repository since all the composers in the integration layer are capable of handling and routing requests. Also, when a composer fails, it would only minimally affect the entire mediation system. ^

Tin Oxide Based Composites Derived Using Electrostatic Spray Deposition Technique as Anodes for Li-Ion Batteries

Recent advances in the electric & hybrid electric vehicles and rapid developments in the electronic devices have increased the demand for high power and high energy density lithium ion batteries. Graphite (theoretical specific capacity: 372 mAh/g) used in commercial anodes cannot meet these demands. Amorphous SnO2 anodes (theoretical specific capacity: 781 mAh/g) have been proposed as alternative anode materials. But these materials have poor conductivity, undergo a large volume change during charging and discharging, large irreversible capacity loss leading to poor cycle performances. To solve the issues related to SnO2 anodes, we propose to synthesize porous SnO2 composites using electrostatic spray deposition technique. First, porous SnO2/CNT composites were fabricated and the effects of the deposition temperature (200,250, 300 oC) & CNT content (10, 20, 30, 40 wt %) on the electrochemical performance of the anodes were studied. Compared to pure SnO2 and pure CNT, the composite materials as anodes showed better discharge capacity and cyclability. 30 wt% CNT content and 250 oC deposition temperature were found to be the optimal conditions with regard to energy capacity whereas the sample with 20% CNT deposited at 250 oC exhibited good capacity retention. This can be ascribed to the porous nature of the anodes and the improvement in the conductivity by the addition of CNT. Electrochemical impedance spectroscopy studies were carried out to study in detail the change in the surface film resistance with cycling. By fitting EIS data to an equivalent circuit model, the values of the circuit components, which represent surface film resistance, were obtained. The higher the CNT content in the composite, lower the change in surface film resistance at certain voltage upon cycling. The surface resistance increased with the depth of discharge and decreased slightly at fully lithiated state. Graphene was also added to improve the performance of pure SnO2 anodes. The composites heated at 280 oC showed better energy capacity and energy density. The specific capacities of as deposited and post heat-treated samples were 534 and 737 mAh/g after 70 cycles. At the 70th cycle, the energy density of the composites at 195 °C and 280 °C were 1240 and 1760 Wh/kg, respectively, which are much higher than the commercially used graphite electrodes (37.2-74.4 Wh/kg). Both SnO2/CNTand SnO2/grapheme based composites with improved energy densities and capacities than pure SnO2 can make a significant impact on the development of new batteries for electric vehicles and portable electronics applications.