Warranty prediction during product development: Developing an event generation engine in an engineer-to-order environment

In order for manufacturing companies to stay competitive, it is necessary to drive warranty system improvements in terms of improved product reliability, improved service delivery efficiency and properly designed warranty policies. However, traditional methods for assessing warranty performance are not always sufficient to alert product development teams of the impending warranty issues. Furthermore, improved assessment methods are needed to aid product development teams make decisions related to the warranty performance of the product. The focus of this research was to develop a framework to integrate statistical inference methods and data mining techniques to create a warranty event generation framework. This was done on the context of an engineer-to-order product development environment. The objectives of this work were: (1) to develop an inference model for the integration of disparate data sources; (2) to demonstrate that multiple data streams can be conditioned for input into the above inference model; (3) to develop the above model and process in light of actual data. This thesis will report on the progress and challenges that have been made toward fulfilling these objectives. The thesis closes by outlining the future research agenda for developing a warranty event generation engine that can integrate data from disparate data sources

Computational methods for augmenting association-based gene mapping

The context and motivation for this thesis is gene mapping, the discovery of genetic variants that affect susceptibility to disease. The goals of gene mapping research include understanding of disease mechanisms, evaluating individual disease risks and ultimately developing new medicines and treatments. Traditional genetic association mapping methods test each measured genetic variant independently for association with the disease. One way to improve the power of detecting disease-affecting variants is to base the tests on haplotypes, strings of adjacent variants that are inherited together, instead of individual variants. To enable haplotype analyses in large-scale association studies, this thesis introduces two novel statistical models and gives an efficient algorithm for haplotype reconstruction, jointly called HaloRec. HaploRec is based on modeling local regularities of variable length in the haplotypes of the studied population and using the obtained model to statistically reconstruct the most probable haplotypes for each studied individual. Our experiments demonstrate that HaploRec is especially well suited to data sets with a large number or markers and subjects, such as those typically used in currently popular genome-wide association studies. Public biological databases contain large amounts of data that can help in determining the relevance of putative associations. In this thesis, we introduce Biomine, a database and search engine that integrates data from several such databases under a uniform graph representation. The graph database is used to derive a general proximity measure for biological entities represented as graph nodes, based on a novel scheme of weighting individual graph edges based on their informativeness and type. The resulting proximity measure can be used as a basis for various data analysis tasks, such as ranking putative disease genes and visualization of gene relationships. Our experiments show that relevant disease genes can be identified from among the putative ones with a reasonable accuracy using Biomine. Best accuracy is obtained when a pre-known reference set of disease genes is available, but experiments using a novel clustering-based method demonstrate that putative disease genes can also be ranked without a reference set under suitable conditions. An important complementary use of Biomine is the search and visualization of indirect relationships between graph nodes, which can be used e.g. to characterize the relationship of putative disease genes to already known disease genes. We provide two methods for selecting subgraphs to be visualized: one based on weights of the edges on the paths connecting query nodes, and one based on using context free grammars to define the types of paths to be displayed. Both of these query interfaces to Biomine are available online.Tämän väitöskirjan aihealue on geenikartoitus, tautialttiuteen vaikuttavien perinnöllisten muunnosten paikantaminen. Geenikartoituksen käytännöllisiä päämääriä ovat tautimekanismien ymmärtäminen, yksilöllisten tautiriskien arviointi sekä uusien lääkitysten kehittäminen. Tässä työssä on kehitetty laskennallisia menetelmiä joita voidaan käyttää parantamaan olemassaolevien geenikartoitusmenetelmien tehoa sekä analysoimaan niiden antamia alustavia tuloksia. Geenikartoitusmenetelmät perustuvat ns. markereihin, jotka ovat yksilöllistä vaihtelua sisältäviä kohtia perimässä. Tyypillisesti käytetyt menetelmät mittaavat kussakin markerissa esiintyvien muunnosten yhteyttä tautiin erikseen, huomioimatta muita markereita. Kartoituksen tarkkuutta voidaan parantaa käyttämällä testaamisen yksikkönä yksittäisten markerien sijaan haplotyyppejä, lähekkäisissä markereissa esiintyvien muunnosten muodostamia säännönmukaisia jaksoja jotka periytyvät yhdessä. Laboratoriomenelmät eivät suoraan tuota tietoa siitä, miten kunkin yksilön perimästä mitatut muunnokset jakautuvat tämän kahdelta vanhemmalta perimiin haplotyyppeihin. Tämän väitöskirjan alkupuolella esitetään laskennallinen menetelmä, joilla haplotyypit voidaan rekonstruoida tilastollisesti, perustuen niiden paikallisiin säännönmukaisuuksiin. Kehitetty menetelmä on laskennallisesti tehokas ja soveltuu erityisesti genominlaajuisiin tutkimuksiin, joissa sekä tutkittujen yksilöiden että markereiden määrät ovat suuria, ja markerit sijaitsevat kohtuullisen etäällä toisistaan. Yksittäisten muunnosten vaikutukset tauteihin ovat usein suhteellisen heikkoja, ja kun testataan suuri joukko markereita, tuloksiin tulee yleensä sattumalta mukaan myös muunnoksia joilla ei ole todellista vaikutusta tautiin. Julkiset biologiset tietokannat sisältävät paljon tietoa joka voi auttaa alustavien geenikartoitustulosten merkityksen arvioimista. Työn toisessa osassa esitellään Biomine, tietokanta jossa on yhdistetty tietoa joukosta tällaisia tietokantoja käyttäen painotettua verkkomallia joka kuvaa mm. geenien, proteiinien ja tautien välisiä tunnettuja yhteyksiä. Verkon solmujen välisten epäsuorien yhteyksien voimakkuuden mittaamiseen esitetään uusi menetelmä. Tätä menetelmää voidaan hyödyntää mm. geenikartoituksella löydettyjen kandidaattigeenien priorisointiin, perustuen siihen että mitataan kandidaattigeenien ja entuudestaan tunnettujen tautigeenien välisten yhteyksien voimakkuutta, tai kandidaattigeenien keskinäisten yhteyksien voimakkuutta. Työssä esitetään myös menetelmiä verkkotietokannan solmujen välisten epäsuorien yhteyksien visualisointiin, perustuen kulloinkin kiinnostuksen kohteena olevien solmujen yhteyttä parhaiten kuvaavan pienen aliverkon eristämiseen tietokannasta. Aliverkon valintaan esitetään kaksi laskennallisesti tehokasta menetelmää: toinen perustuen yhteyksien voimakkuuden arvioimiseen, ja toinen perustuen yhdistävien polkujen sisältämien linkkien tyyppeihin. Nämä visualisointimenetelmät ovat myös käytettävissä julkisessa verkkopalvelussa jossa voi tehdä kyselyjä Biomine-tietokantaan

Computational Approaches to Drug Profiling and Drug-Protein Interactions

Despite substantial increases in R&D spending within the pharmaceutical industry, denovo drug design has become a time-consuming endeavour. High attrition rates led to a long period of stagnation in drug approvals. Due to the extreme costs associated with introducing a drug to the market, locating and understanding the reasons for clinical failure is key to future productivity. As part of this PhD, three main contributions were made in this respect. First, the web platform, LigNFam enables users to interactively explore similarity relationships between ‘drug like’ molecules and the proteins they bind. Secondly, two deep-learning-based binding site comparison tools were developed, competing with the state-of-the-art over benchmark datasets. The models have the ability to predict offtarget interactions and potential candidates for target-based drug repurposing. Finally, the open-source ScaffoldGraph software was presented for the analysis of hierarchical scaffold relationships and has already been used in multiple projects, including integration into a virtual screening pipeline to increase the tractability of ultra-large screening experiments. Together, and with existing tools, the contributions made will aid in the understanding of drug-protein relationships, particularly in the fields of off-target prediction and drug repurposing, helping to design better drugs faster

Analysis of Layered Social Networks

Prevention of near-term terrorist attacks requires an understanding of current terrorist organizations to include their composition, the actors involved, and how they operate to achieve their objectives. To aid this understanding, operations research, sociological, and behavioral theory relevant to the study of social networks are applied, thereby providing theoretical foundations for new methodologies to analyze non-cooperative organizations, defined as those trying to hide their structure or are unwilling to provide information regarding their operations. Techniques applying information regarding multiple dimensions of interpersonal relationships, inferring from them the strengths of interpersonal ties, are explored. A layered network construct is offered that provides new analytic opportunities and insights generally unaccounted for in traditional social network analyses. These provide decision makers improved courses of action designed to impute influence upon an adversarial network, thereby achieving a desired influence, perception, or outcome to one or more actors within the target network. This knowledge may also be used to identify key individuals, relationships, and organizational practices. Subsequently, such analysis may lead to the identification of exploitable weaknesses to either eliminate the network as a whole, cause it to become operationally ineffective, or influence it to directly or indirectly support National Security Strategy

Pacific Symposium on Biocomputing 2023

The Pacific Symposium on Biocomputing (PSB) 2023 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2023 will be held on January 3-7, 2023 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2023 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field

The Impact of internet social networking websites on the gay community: Behavior and identity

The hypothesis of this thesis is that social networking website design can exert a mediating influence upon the culture of a site by supporting certain behaviors more than others; this influence can be analyzed in an active and structured way that takes into account the culture of the community it addresses. Evidence will be offered by case study, demonstration of specific mediations, and analysis. This hypothesis will be tested with specific reference to the gay male community. The scope of this paper will be limited to the analysis of gay-oriented social networking websites as new media, in general and through specific examples. I will present frameworks for categorizing and analyzing these websites that consider the mediating influences associated with site design. In the last chapter, I will propose community-enhancing design. The method of analysis first takes into account the nature of new media. It then discusses the concepts of cultural mediums and mediators in terms of site-wide typology and specific forms of mediation. It then identifies common elements of gay social networking sites and their associated usage as well as the design decisions that are related to them. Next user goals and site goals are correlated to these design decisions. Virtual personas and real communities are discusses as a concept. Using the proposed methodology, gay.com and other sites are analyzed and compared. Conclusions are drawn from the results of this analysis and evidence presented. The impact of social networking websites upon sexual activity is discussed. Finally, conclusions are summarized and recommendations are cited related to what these sites could be

Doctor of Physical Therapy Students’ Perspectives on Leadership Development in the Context of the Proposed Leadership Competencies Framework for Physical Therapists

Leadership is an emerging field in physical therapy professional research. Research efforts have concentrated on identifying the most desirable leadership skills and behaviors for practicing physical therapists, or on curricular interventions implemented in specific educational programs. This study utilized a qualitative phenomenological design to investigate the perspectives of 21 current and former student leaders from Marshall University School of Physical Therapy, specifically investigating the scope and effectiveness of available opportunities in developing leadership skills and behaviors. Participants were also probed regarding their motivation for pursuing pre-professional leadership development opportunities. Findings from this study suggest the available opportunities are effective to engage an increasing number of students in leadership development. Advanced career preparation is the primary motivating factor for participating in these activities. The study also investigated the extent to which the Leadership Competencies Framework for Physical Therapy provided a framework for integrating leadership development into Doctor of Physical Therapy (DPT) pre-professional educational programs. Study findings indicated the Self-Leadership and Leading Others tiers of the framework were initially validated for limited use of the framework within DPT education

Sustainable lighting product development underpinned by online data mining and life cycle assessment

The accurate acquisition of customer requirement information is an important part in product planning and positioning, it plays a decisive role in the success of products in the market. the rapid development of e-commerce makes increasing more consumers shopping online and a big volume of customer reviews are posted on different Websites. The online reviews contain valuable opinions of customers, enabling designers to understand their concerns. In this research, an integrated approach has been developed to mine customer requirements according to the online reviews collected from e-commerce sites to form product design specifications. The main research contents include the following aspects: (1) development of useful online review prediction and classification approach; (2) online review implicit product features and sentiment analysis based on the constructed feature and sentiment lexicon; (3) built a knowledge base containing customer requirements mined from online reviews; (4) conduct a dedicated environmental and social LCA on the proposed domestic lighting product by using a professional LCA software. In this study, multiple models and technologies/methods have been successfully implemented: review helpfulness classification model has been constructed based on the training set and test set by tuning and optimizing; proposes a new approach to implicit feature and sentiment analysis, based on explicit formal feature-emotion sentences, implicit feature sentences and implicit sentiment sentences, combined with a feature lexicon, a 1V1/1Vn sentiment-feature rule base and the feature-emotion word pairs are extracted; based on the preliminary analysis results of feature extraction and sentiment analysis, combined with KANO model to establish user requirement mining rules, and consider satisfaction, propose the user demand priority to obtain the final list of user requirements; a real industrial context with lighting product manufacturer (ONA) in Spain has involved with the lighting product life cycle analysis and development for new product. The analytical results of these studies present an in-depth modelling and analysis on the sustainable lighting product lifecycle with the aid of real manufacturing data

Town report Milford, New Hampshire 2021.

This is an annual report containing vital statistics for a town/city in the state of New Hampshire

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse