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The aim of this study was to investigate if a mechanical recruitment process could be a useful tool for employers to avoid discrimination. National and international law protect jobseekers from discrimination during the recruiting process. Despite this individuals frequently report that they are treated unfairly when they apply for a job. In line with this research shows that some individuals do not have the same opportunities in the labour market as the rest of the population. This study focus on discrimination based on ethnicity, age, gender or disability. Today most of the hiring decisions are based on employers professional judgement. This constitute a potential risk for discrimination since the judgement can be influenced by prejudices and stereotypes. The research shows that employers tend to measure variables which are not relevant for individuals future job performance when they make decisions in selection processes. A mechanical approach for the recruitment can broadly correct for this since it is based on standardized procedures that eliminates human judgement. The data collection of candidates strictly relate to a defined job profile which only contains criterions that are of importance for the employment. Pre-specified algorithms are later on used for combining each candidates data into an overall assessment. This regulates that the same criteria is measured for all individuals. In order to analyse the material a legal dogmatic method has been combined with a legal sociology method.

A wireless sensor network is a collection of numerous sensors distributed on an area of interest to collect and process data from the environment. One particular threat in wireless sensor networks is node compromise attacks, that is, attacks where the adversary gets physical access to a node and to the programs and keying material stored on it. Only authorized queries should be allowed in the network and the integrity and confidentiality of the data that is being collected should be protected. We propose a layered key distribution scheme together with two protocols for query authentication and confidential data aggregation. The layered key distribution is more robust to node and communication failures than a predefined tree structure. The protocols are secure under the assumption that less than n sensor nodes are compromised. n is a design parameter that allows us to trade off security for overhead. When more than n sensor nodes are compromised, our simulations show that the attacker can only introduce unauthorized queries into a limited part of the network and can only get access to a small part of the data that is aggregated in the network. Considering the data collection protocol we also contribute with strategies to reduce the energy consumption of an integrity preserving in-network aggregation scheme to a level below the energy consumption of a non-aggregation scheme. Our improvements reduce node congestion by a factor of three and the total communication load by 30%. Location privacy of the users carrying mobile devices is another aspect considered in this thesis. Considering a mobile sink that collects data from the network, we propose a strategy for data collection that requires no information about the location and movement pattern of the sink. We show that it is possible to provide data collection services, while protecting the location privacy of the sink. When mobile phones with built-in sensors are used as sensor nodes, location information about where the data has been sensed can be used to trace users and infer other personal information about them, like state of health or personal preferences. Therefore, location privacy preserving mechanisms have been proposed to provide location privacy to the users. We investigate how a location privacy preserving mechanism influences the quality of the collected data and consider strategies to reconstruct the data distribution without compromising location privacy. / WISENET

Despite the significant advances that have been made in traffic sensor technologies, there are only a few systems that provide measurements at the trip level and fewer yet that can do so for all travel modes. On the other hand, traditional methods of collecting individual travel behavior (i.e. manual or web-based travel diaries) are resource intensive and prone to a wide range of errors. Moreover, although dedicated GPS loggers provide the ability to collect detailed travel behavior data with less effort, their use still faces several challenges including the need to distribute and retrieve the logger; the potential need to have the survey participants upload data from the logger to a server; and the need for survey participants to carry another device with them on all their trips. The widespread adoption of smart phones provides an opportunity to acquire travel behavior data from individuals without the need for participants to record trips in a travel diary or to carry dedicated recording devices with them on their travels. The collected travel data can then be used by municipalities and regions for forecasting the travel demand or for analyzing the travel behavior of individuals. In the current research, a smart phone based travel behavior surveying system is designed, developed, and pilot tested. The custom software written for this study is capable of recording the travel characteristics of individuals over the course of any period of time (e.g. days or weeks) and across all travel modes. In this system, a custom application on the smart phone records the GPS data (using the onboard GPS unit) at a prescribed frequency and then automatically transmits the data to a dedicated server. In the server, the data are stored in a dedicated database to be then processed using trip characteristics inference algorithms. The main challenge with the implemented system is the need to reduce the amount of energy consumed by the device to calculate and transmit the GPS fixes. In order to reduce the power consumption from the travel behavior data acquisition software, several techniques are proposed in the current study. Finally, in order to evaluate the performance of the developed system, first the accuracy of the position information obtained from the data acquisition software is analyzed, and then the impact of the proposed methods for reducing the battery consumption is examined. As a conclusion, the results of implemented system shows that collecting individual travel behavior data through the use of GPS enabled smart phones is technically feasible and would address most of the limitations associated with other survey techniques. According to the results, the accuracy of the GPS positions and speed collected through the implemented system is comparable to GPS loggers. Moreover, proposed battery reduction techniques are able to reduce the battery consumption rate from 13.3% per hour to 5.75% per hour (i.e. 57% reduction) when the trip maker is non-stationary and from 5.75% per hour to 1.41% per hour (i.e. 75.5% reduction) when the trip maker is stationary.

Behavioral research involves the study of the behaviors of one or more agents (often animals) in order to better understand the agents' thoughts and actions. Identifying subject movements and behaviors based upon those movements is a critical, time-consuming step in behavioral research. To successfully perform behavior analysis, three goals must be met. First, the agents of interest are observed, and their movements recorded. Second, each individual must be uniquely identified. Finally, behaviors must be identified and recognized. I explore a system that can uniquely identify and track agents, then use these tracks to automatically build behavioral models and recognize similar behaviors in the future. I address the tracking and identification problems using a combination of laser range finders, active RFID sensors, and probabilistic models for real-time tracking. The laser range component adds environmental flexibility over vision based systems, while the RFID tags help disambiguate individual agents. The probabilistic models are important to target identification during the complex interactions with other agents of similar appearance. In addition to tracking, I present work on automatic methods for generating behavioral models based on supervised learning techniques using the agents' tracked data. These models can be used to classify new tracked data and identify the behavior exhibited by the agent, which can then be used to help automate behavior analysis.

Modern civil structures as well as loads on them are still too complex to be accurately modeled or simulated. Therefore, structural failures and structural defects are NOT uncommon! More and more full-scale structural monitoring systems have been deployed in order to monitor how structures behave under various loading conditions. This research focuses on how to maximise benefits from such full-scale measurements by employing advanced digital signal processing techniques. This study is based on accelerometer and GPS data collected on three very different structures, namely, the steel tower in Tokyo, the long and slender suspension bridge in Hong Kong, and the tall office tower in Sydney, under a range of loading conditions, i.e., typhoon, earthquake, heavy traffic, and small scale wind. Systematic analysis of accelerometer and GPS data has demonstrated that the two sensors complement each other in monitoring the static, quasi-static and dynamic movements of the structures. It has also been confirmed that the Finite Element Model could under-estimate the natural frequencies of structures by more than 40% in some case. The effectiveness of using wavelet to de-noise GPS measurement has been demonstrated. The weakness and strengths of accelerometer and GPS have been identified and framework has been developed on how to integrate the two as well as how to optimize the integration. The three-dimensional spectral analysis framework has been developed which can track the temporal evolution of all the frequency components and effectively represents the result in the 3D spectrogram of frequency, time and magnitude. The dominant frequency can also be tracked on the 3D mesh to vividly illustrate the damping signature of the structure. The frequency domain coherent analysis based on this 3D analysis framework can further enhance the detection of common signals between sensors. The developed framework can significantly improve the visualized performance of the integrated system without increasing hardware costs. Indoor experiments have shown the excellent characteristics of the optical fibre Bragg gratings (FBGs) for deformation monitoring. Innovative and low-cost approach has been developed to measure the shift of FBG???s central wavelength. Furthermore, a schematic design has been completed to multiplex FBGs in order to enable distributed monitoring. In collaboration with the University of Sydney, the first Australian full-scale structural monitoring system of GPS and accelerometer has been deployed on the Latitude Tower in Sydney to support current and future research.

Extensive research has been undertaken to improve the robustness of runoff quantity predictions for urban catchments. However, equally robust predictions for runoff quality have yet to be attained. Past studies addressing this issue have typically been confined to the use of simple conceptual or empirical models which forgo the tedious steps of providing a physical representation of the actual system to be modelled. Consequently, even if the modelling results for the test catchments are satisfactory, the reliability and applicability of these models for other catchments remain uncertain. It is deemed that by employing process-based, deterministic models, many of these uncertainties can be eliminated. A lack of understanding of the hydrological processes occurring during storm events and the absence of good calibration data, however, hamper the advancement of such models and limit their use in the field. This research proposes that the development of a hydrologic model based on the kinematic wave equations linked to an advection-dispersion model that simulates pollutant detachment and transport will improve both runoff quantity and quality simulations and enhance the robustness of the predictions. At the very worst, a model of this type could still highlight the underlying issues that inhibit models from reproducing the recorded historical hydrographs and pollutographs. In actual fact, this approach has already been applied by various modellers to simulate the entrainment of pollutants from urban catchments. Also, the paradigm shift to using the Water Sensitive Urban Design (WSUD) approach in designing urban stormwater systems has prompted the need to differentiate the various sources of pollutants in urban catchments such as roads, roofs and other impervious surfaces. The primary objective of the study reported herein is to model runoff quantity and quality from small urban catchments, facilitated by the procurement of the necessary field data to calibrate and validate the model via implementation of a comprehensive field exercise based in Sydney. From a water quality perspective, trace metals were selected as the foci. The study outcomes include the formulation of a linkage of models capable of providing accurate and reliable runoff quantity and quality predictions for the study catchments by taking into consideration: - The different availability of pollutants from urban catchments, i.e. roads vs. roofs; - The build-up characteristics of pollutants on the distinct urban surfaces and their spatial distribution; - The contribution of rainwater to urban runoff pollution; - The partitioning of pollutants according to particulate bound and dissolved phases; - The respective role of rainfall and runoff in the detachment and entrainment of pollutants; - The influence of particle properties such as particle size distribution and density on pollutant transport; and - The relationship associating particulate bound metals to suspended solids. The simulation results obtained using the proposed model were found to be suitable for modelling the detachment and transport of pollutants for small urban catchments. Interpretation of these results reveals several key findings which could help to rectify shortcomings of existing modelling approaches. Even though the robustness of the model presented here may not translate into a significant improvement in the overall robustness of model predictions, the physical basis on which this process-based model was developed nevertheless provides the flexibility necessary for implementation at alternative sites. It is also shown that the availability of reliable runoff data is essential for implementation of the model for other similar urban catchments. In conclusion, the proposed model in this study will serve as a worthy tool in future urban catchment management studies.

Diss. (sammanfattning) Umeå : Sveriges lantbruksuniv., 2007. / Härtill 6 uppsatser.

Thesis (Ph. D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2008. / Committee Chair: Michaels, Jennifer; Committee Member: Habetler, Thomas; Committee Member: Jacobs, Laurence; Committee Member: Michaels, Thomas; Committee Member: Vachtsevanos, George.

Thesis (M.S.)--University of Missouri-Columbia, 2007. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. "May 2007" Includes bibliographical references.