Sustainability has become a major concern of contemporary product design. Whether it's furniture, appliances, apparel, or technology designers of every field must now consider the ecological impact of the products that they create. Sustainability of material resources, impact and by products of manufacturing processes, energy using in production, product lifespan, and disposal are all things that must be carefully considered to maximize product sustainability. Strategies for reducing negative environmental impact include maximizing material usage, using recycled and or biodegradable materials, minimizing product weight and transportation, reducing energy consumption, and dematerialization. In more recent years the idea of increasing product lifespan has received a lot of attention from design theorists. This doesn't just mean making goods that can physically last a lifetime and have superior performance. The consumer must have an attachment to the object. This attachment comes from an emotional connection. Contemporary designers must find innovative ways of creating an emotional bond between product and consumer. How can mass produced goods achieve this goal? I believe the answer is involving the consumer in the design process in order to personalize and customize the products they buy. Made to order goods offer the customer the opportunity to co-design the products that they desire so that they suit particular needs and wants. Instead of selecting pre-manufactured goods from a store or website consumers can now personalize and customize an increasing number and range of products. Companies like Longchamp, Nike, Levis, Addidas, and Ralph Lauren are capitalizing on the fact that consumers want to personalize and customize the products they consume without having to lift a finger. By allowing customers to choose colors, sizes, styles, and even adding personalized logos these companies are capitalizing on the fact that consumers want customization. People become more invested and more attached to objects that they have spent effort in creating, allow for self-expression, and that are unique to the user. The consumer is allowed to be creative but this is only from a limited amount of choices available to them. My research involves taking the concept of customization further to make products that are completely unique to an individual. Nothing is more personal and individualized than the human fingerprint. I am exploring how the fingerprint can be abstracted and used as texture on the surface of furniture. By making objects that are personalized to the user it is my goal to deepen the connection between owner and object to increase product lifespan.

Fingerprints have been an invaluable tool for law enforcement and forensics for over a century, motivating research into automated fingerprint based identification in the early 1960's. More recently, fingerprints have found an application in the emerging industry of biometric systems. Biometrics is the automatic identification of an individual based on physiological or behavioral characteristics. Due to its security related applications and the current world political climate, biometrics is presently the subject of intense research by private and academic institutions. Fingerprints are emerging as the most common and trusted biometric for personal identification. However, despite decades of intense research there are still significant challenges for the developers of automated fingerprint verification systems. This thesis includes an examination of all major stages of the fingerprint verification process, with contributions made at each step. The primary focus is upon fingerprint registration, which is the challenging problem of aligning two prints in order to compare their corresponding features for verification. A hierarchical approach is proposed consisting of three stages, each of which employs novel features and techniques for alignment. Experimental results show that the hierarchical approach is robust and outperforms competing state-of-the-art registration methods from the literature. However, despite its power, like most algorithms it has limitations. Therefore, a novel method of information fusion at the registration level has been developed. The technique dynamically selects registration parameters from a set of competing algorithms using a statistical framework. This allows for the relative advantages of different approaches to be exploited. The results show a significant improvement in alignment accuracy for a wide variety of fingerprint databases. Given a robust alignment of two fingerprints, it still remains to be verified whether or not they have originated from the same finger. This is a non-trivial problem, and a close examination of fingerprint features available for this task is conducted with extensive experimental results.

The objective of the study was to investigate the air pollution of working place and the fence of aluminum plants. Four sites were selected for conducting the sampling of particulate matter¡]PM¡^to establish the fingerprints of PM in aluminum plants. Moreover, the receptor model was used to apportion the major contributing sources of particulate matter. The results of the study showed that PM concentrations in the working places were high, which might be emitted from manufacturing or mechanical operating process in the melting furnace, the continuous casting, and etc. The total suspended solid concentrations from non-combustion pollution source ¡]such as hot rolling , cold rolling, and plate industry¡^ were usually below 200 µg /m3. Moreover, the size distributions of PM in working places were usually bi-modal type. The particle sizes with the highest concentration in five and coarse fractions were 0.18~0.56 µm respectively. As for the combustion sources, the particle sizes with the highest concentration were 0.56~1.0 µm and 11.5~24.7 µm, respectively. The particle emitted from zinc casting source were mostly in the fine particle fraction¡]1.0~3.2 µm¡^. The fingerprint profiles of PM from the working places showed that the major metal content of the hot rolling were Al, Zn, K, Cr. Among then, Cr might be source of from the using of chromate acid. The most abundant water-soluble ions were sulfate ion and chlorine and chloride. The carbon content accounted for about 22% of the PM mass. The ratio of organic carbon to elemental carbon were 2.54 and 2.80. The major metal content of melting process was Al, the minor metals were Zn, k, Ca, Fe. The ratio of anion to cation¡]A/C¡^ was about 0.80. The most abundant ion sulfate, while the chloride, the fluoride, potassium, and the ammonium ions were minor ones. The carbon content accounted about 19.2% and 27.3% of PM mass respectively. The ratio of organic carbon to elemental carbon were 1.21 and 1.07. Moreover, the major metals were k, Ca, Fe. The major ion was chloride, while the nitrate calcium and potassium ions were minor ones. The A/C was 0.7. The carbon content accounted for 54.8% and 51.0% of PM2.5 and PM10, respectively. The ratio of organic carbon to elemental carbon was about 2.9. The results obtained from receptor modeling showed that the contribution percentage of fugitive PM from the aluminum plant (including hot rolling, melting furnace, and low-wave furnace) was between 5.9 and 13.2%, Another major source was traffic refracted pollution with a contribution percentage between 17.0% and 23.0%, Fur then more, in the surrounding PM, was between 11.2% and 20.7%, while the contribution from the steel plant and Moreover, the municipal incineration was 2.5~6.5% and 2.3~5.0%,respectively. The sea salt contributed 4.3~7.1% of PM mass. The unsolved percentage was 7.0~11.8%.

The thesis explores the extent to which interpretive techniques can improve our understanding of the impacts of information systems. Two themes are explored: the capacity of interpretive techniques to evaluate information systems' impacts from within the work context, and the extent to which the process emphasis of the interpretive approach can facilitate learning about information systems and their impacts. The thesis proposes that the impacts of information systems comprise a combination of known or anticipated phenomena and emergent phenomena that cannot be wholly predicted in advance and argues that the value of an information system lies in its effective use, which in turn depends upon its being understood by its users and assimilated into their work. Support for this proposal is provided from the literature and through evaluation of the impacts of the National Automated Fingerprint Identification System (NAFIS) on fingerprint work in England and Wales. Deep insight into NAFIS and fingerprint work are provided by the use of Repertory Grid Analysis (RGA) as a content-free data gathering technique, used within the interpretive framework proposed by Walsham (1993). The data generated by RGA are analysed using the protocols proposed by Thomas and Harri-Augstein (1985) which support what they call "self-organised learning". In this way, RGA is used to facilitate learning through evaluation, enabling participants to learn to benefit from information systems. The RGA process and outcomes are described in detail. The contribution of the RGA data to the interpretive approach is discussed and the results compared with those arising from a more orthodox evaluation ofNAFIS. The results demonstrate that orthodox evaluation techniques underestimate the value of an information system by failing to assess the significance of many of the issues and concerns that emerge as it is assimilated into the work setting. The research is shown to have contributed to the evaluation of NAFIS, directly impacting the work of a wide range of users and managers in the fingerprint, police and wider criminal justice communities. The results are also shown to be generalisable to other organisational settings and therefore having implications for both the information systems and wider evaluation communities.

Universiẗat, Diss., 2002--Jena.

In an attempt to develop a statistical model for fingerprint analysis, the Minutiae:Ridge-Length Ratio (MRLR) was used to examine differences between the different sexes, hands, fingers, ridge patterns, and racial groups. In regards to sex, statistically significant MRLR differences (α=0.05) were found between males and females when analyzing both individual prints (p<0.001) and entire ten-print cards (p=0.025). Further examination of the data revealed more specific differences within separate subcategories. The MRLR was significantly different (p<0.001) between males and females with both right and left hands. With respect to sex and individual finger differences, the thumb (p<0.001), index finger (p<0.001), and middle finger (p=0.015) were statistically significant. For ridge pattern, whorls (p<0.001) and ulnar loops (p<0.001) had significant differences between the sexes. Racially, males and females had statistically significant differences from one another within the Caucasian (p<0.001) and African American (p<0.001) racial groups. Further investigation of variables independent of sex highlighted other statistically significant MRLR relationships. Within the fingers, the thumb was found to be significantly different than the middle (p<0.001), ring (p<0.001), and little fingers (p<0.001); the index finger also differed from the little finger significantly (p=0.001). Comparison of level one detail demonstrated the whorl pattern was statistically different than the arch (p<0.001), radial loop (p=0.002), and ulnar loop patterns (p<0.001). No statistically significant difference was found between the right and left hands of the sample population (p=0.160). The racial subdivisions produced more complex relationships. Caucasians had statistically significant MRLR differences to African Americans (p=0.036), Hispanics (p=0.003), and Asians (p=0.046). African Americans had additional significant differences from Hispanics (p<0.001), Asians (p<0.001), and Native Americans (p=0.036). Finally, Native Americans and Hispanics shared a significant difference as well (p<0.036). However, due to the uncertainty of racial demographic data, the extrapolation of these findings to the general population may not be appropriate for forensic investigation purposes.

abstract: Deoxyribonucleic Acid (DNA) evidence has been shown to have a strong effect on juror decision-making when presented in court. While DNA evidence has been shown to be extremely reliable, fingerprint evidence, and the way it is presented in court, has come under much scrutiny. Forensic fingerprint experts have been working on a uniformed way to present fingerprint evidence in court. The most promising has been the Probabilistic Based Fingerprint Evidence (PBFE) created by Forensic Science Services (FSS) (G. Langenburg, personal communication, April 16, 2011). The current study examined how the presence and strength of DNA evidence influenced jurors' interpretation of probabilistic fingerprint evidence. Mock jurors read a summary of a murder case that included fingerprint evidence and testimony from a fingerprint expert and, in some conditions, DNA evidence and testimony from a DNA expert. Results showed that when DNA evidence was found at the crime scene and matched the defendant other evidence and the overall case was rated as stronger than when no DNA was present. Fingerprint evidence did not cause a stronger rating of other evidence and the overall case. Fingerprint evidence was underrated in some cases, and jurors generally weighed all the different strengths of fingerprint testimony to the same degree. / Dissertation/Thesis / M.S. Psychology 2012

Dissertation (LLM)--University of Pretoria, 2014. / gm2015 / Centre for Human Rights / LLM / Unrestricted

One of the oldest biometrics that has been used to uniquely identify a person is their fingerprint. Recent developments in research on fingerprint collection have made it possible to collect fingerprint data from a stand-off digital image. Each of the techniques developed so far have relied on either a very controlled capture environment to ensure only a single fingertip is collected or manual cropping of the image down to the fingertip. The main body of the research focuses on extracting the fingerprint itself. If fingerprint collection via digital image is ever to be fielded in the real world on such devices as smart phones or tablets it will be necessary for the software to automatically detect a single or multiple fingertips in an image and isolate them for extracting the fingerprint. We introduce an automatic fingertip detection algorithm that couples image processing techniques with a machine learning capability to successfully identify varying numbers of fingertips in digital images. Our algorithm proves that while it is difficult to remove all constraints from the capture environment it is achievable with the method we have developed and we can achieve a recall of 69.77% at a precision of 78.95%. This gives us the important capability to detect varying numbers of fingertips in an image and provide a crucial piece in what could be a complete automated fingerprint recognition system.

Location-based services have experienced substantial growth in the last decade. However, despite extensive research efforts, sub-meter location accuracy with low-cost infrastructure continues to be elusive. Comparing with infrastructure-based solutions, infrastructure-free indoor localization has the major advantage of avoiding extra cost for infrastructure deployment. There are two typical types of infrastructure-free indoor localization solutions, i.e., Pedestrian Dead Reckoning (PDR)-based and fingerprint-based. PDR-based solutions rely on inertial measurement units to estimate the user's relative location. Despite the effort, many issues still remain in PDR systems. For example, any deployed smartphone-based PDR system needs to cope with the changing orientation of smartphone that the phone might be putting in a pocket, or being taken out to use, etc. In addition, the outputs of Micro Electro-Mechanical Systems (MEMS) sensors on smart devices vary over time which results in rapidly accumulated localization errors without external references. Fingerprint-based solutions utilize different types of location dependent parameters to estimate user's absolute location. Although fingerprint-based solutions are usually more practical than PDR-based, they suffer from laborious site survey process. In this dissertation, we aim to mitigate these challenges. First of all, illumination intensity is introduced as a new type of fingerprints to provide location references for PDR-based indoor localization. We propose IDyLL -- an indoor localization system using inertial measurement units (IMU) and photodiode sensors on smartphones. Using a novel illumination peak detection algorithm, IDyLL augments IMU-based pedestrian dead reckoning with location fixes. Moreover, we devise a burned-out detection algorithm for simultaneous luminary-assisted IPS and burned-out luminary detection. Experimental study using data collected from smartphones shows that IDyLL is able to achieve high localization accuracy at low costs. As for fingerprint collection, several frameworks are proposed to ease the laborious site survey process, without compromising fingerprint quality. We propose TuRF, a path-based fingerprint collection mechanism for site survey. MobiBee, a treasure hunt game, is further designed to take advantage of gamification and incentive models for fast fingerprint collection. Motivated by applying mobile crowdsensing for fingerprint collection, we propose ALSense, a distributed active learning framework, for budgeted mobile crowdsensing applications. Novel stream-based active learning strategies are developed to orchestrate queries of annotation data and the upload of unlabeled data from mobile devices. Extensive experiments demonstrate that ALSense can indeed achieve higher classification accuracy given fixed data acquisition budgets. Facing malicious behaviors, three types of location-related attacks and their corresponding detection algorithms are investigated. Experiments on both crowdsensed and emulated dataset show that the proposed algorithms can detect all three types of attacks with high accuracy. / Thesis / Doctor of Philosophy (PhD)