新創科技公司源源不斷的產生，是經濟發展的主要動力。美國1995年後崛起的公司，其中大部份為科技公司，所創造的股東價值是《財星》500大企業的二倍。台灣新竹科學園區，20年以來成立了300多家公司，創造出台灣GDP約10%的產值，新創科技公司之重要性可見一斑。 新創科技公司具有新創公司及科技公司兩者的特性，其營運不確定性高，創業者的創業精神及意志力是公司成敗關鍵，建立團隊、資金募集、及產品研發是創業者最主要的工作。 由於資本市場與產業市場快速的變化，新創科技公司在資金募集及研發管理上，面臨從所未有的變局。過去一年，在矽谷有上千家新創科技公司因資金募集不順或研發管理失利，而關門大吉。這是矽谷從所未有的現象。 究竟新創科技公司的資金募集及研發管理，有何關鍵要素以及資金募集及研發管理二者績效之關聯性如何，本研究以矽谷及台灣19家新創科技公司為研究對象，所包含產業有IC設計業，光電業，光通訊業，IC設備業，醫療設備業，及電子材料業等，獲得『影響新創科技公司資金募集及研發管理績效之關鍵要素』，以及二者之關聯性之結論如下： 一、資金募集 根據文獻研讀，影響新創科技公司資金募集績效的關鍵要素有：創業團隊能力因素，環境因素，及報酬與風險因素；而根據個案研究結果，創業者必須在不同發展階段，掌握不同的關鍵要素，分述如下： １　種子期 (1) 完善的營運計劃 (2) 募資時機的掌握 (3) 創業者所具備達成超高報酬率之條件 (4) 具號召力股東的參與 (5) 明確了解募資對象的決策特質，投資偏好、及投資策略 ２　創建期 除了種子期之關鍵要素之外，另產品要獲得關鍵客戶之認可，研發進度要等合原設定目標，關鍵股東或董事對募資的持續支持，亦均為關鍵要素。 ３　擴張期 公司商品化及量產能力，行銷、財務管理能力之優劣為此時期資金募集成敗之關鍵要素。 二、研發管理 根據文獻探討，影響新創科技公司研發管理績效的關鍵要素有：產品定位，外部資源運用及整合能力，內部資源管理及整合能力。另經個案研究發現，新創科技公司因研發資源有限，所以要研發什麼產品，不但要有方向感（即產品定位），同時尚要能因應技術及市場的變化，降低研發風險，所以要有產品組合之規劃。且創業者不但要具備良好技術背景，同時要藉創業精神及領導力，來吸引優秀人才加入『前途未卜』的新創科技公司。另外，新創公司之研發進度往往落後於設定目標，所以利害關係人（董事、股東、顧客、供應商、及員工）的耐心支持，亦是非常重要的。歸納個案研究發現下列五項影響研發管理績效關鍵要素： 1　明確的產品定位及產品組合 2　良好的研發專案管理能力 3　CEO或CTO應具良好的技術背景及領導力，以吸引優良技術人才加入 4　公司內外部研發資源良好之整合能力 5　利害關係人的支持 三、資金募集及研發管理二者績效之關聯性 依個案研究分析結果，對於二者之關聯性可獲得下述之結論： 1. 研發管理績效不佳者，資金募集通常難以成功，而研發管理具良好績效者，其資金募集較易成功。 2. 資金募集績效良好者，必須具備良好之研發管理，而資金募集績效不佳者，未必研發管理績效不佳。 / High-tech start-ups are the powerhouses of economic development. The total market value of high-tech start-ups that launched after 1995 is twice of that of Fortune 500 companies combined. The Hsinchu Science Park of Taiwan has incubated some 300 companies since her inception 20 years ago. To date these 300 companies generate in total a revenue of about 10% value of Taiwan’s GDP. High-tech start-ups have the attributes of start-ups and high-techs. As start-ups, they face so many uncertainties along the way. And as high-techs, they face dynamic market environments and short life cycle of products. Only through the founders’ entrepreneurship and strong motivation, can the high-tech start-ups survive and prosper. Team building, fund raising and R&D are the main jobs of every founder. Recently, because of the unpredictable change of capital markets and industry markets, the high-tech start-ups have experienced a great challenge in fund raising and R&D management. For the past year alone in Silicon Valley, there have been more than 1000 high-tech start-ups filed Chapter 11 or Chapter 7, out of the failure of funding or R&D. A cruel scene has never been seen for the past two decades. OBJECTIVE The objectives of this thesis intend to explore the key success factors (KSFs) of fund raising and R&D management for high-tech start-ups, and the relationship between the success of fund raising and R&D management. This study was conducted by using case study methodology covering 19 samples of high-tech start-ups. The accidental sampling was collected from 9 samples located in the Silicon Valley and 10 in Taiwan, with industries ranging from IC design, opto-electronics, opto-communications, IC equipment, health care equipment to electronics components. The data was obtained by interviewing the top management of these companies and venture capitalist to validate the information. CONCLUSION The result of this study found that the KSFs of fund raising are as follows, 1. According to the research papers and readings, three key factors determine the success of fund raising--- the core competence of the management team, the economic, industrial and social environment, and the investment return vs. risk. 2. This study shows that the KSFs are related to the maturity of high-tech start-ups’ development levels. They are not all the same. In embryo stage, the KSFs are the solid business plan, the right timing of fund raising, the team’s track record, and the knowledge to know the prospective investor’s decision criteria, investment preferences and investment strategy. In early stage, the KSFs should add two more points; one is that the products shall have design-wins from strategic customers with the achievement of milestone complying with schedule, the other is the continuing support from strategic investors. In expansionary stage, the KSFs are the products’ marketability and manufacturability. Also the marketing ability and financial ability are no less important. Moreover, the key factors affect the success of R&D management as follows, 1. In the research papers and readings, three determinants to the success of R&D management are the products’ positioning, the application and integration ability of external resources, as well as the management and integration ability of internal resources. 2. In the analysis of this study, the KSFs, emphasize more on the sides of strategic thinking and founders’ entrepreneurship as follows: a. The right product positioning and products portfolio; b. The good R&D project management skills; 　c. The founders’ good technical background and leadership to attract top-notched technical staff to join; d. The good integration ability of internal and external resources; e. The full support of shareholders. Above all, regarding the relationship between the success of fund raising and R&D management, the poor performance of R&D will, in general, leads to the failure of fund raising, whilst the good performance of R&D will help the success of fund raising. However, one with the success of fund raising, must couple with the good performance of R&D, and one with the failure of fund raising, not necessarily goes with poor performance of R&D.

Head-up display (HUD) är en beprövad teknik inom flyg och bil, vilken gör det möjligt för piloter och förare att få tillgång till information utan att uppmärksamheten avleds från omvärlden. Liknande fördelar kan uppnås genom installation av HUD i tåg. Syftet med denna studie är att utveckla ett användargränssnitt för HUD baserat på European Rail Traffic Management System (ERTMS). HUD kommer att vara en extra säkerhetsfunktion för tågen för att förhindra förare från att skifta fokus mellan instrumentpanelen och omgivningen, vilket leder till minskad förareutmattning och bättre observation av spåren framåt. Scenario Based Design-metoden har använts för att genomföra projektarbetet och i rapporten diskuteras metodens  fördelar och begränsningar. Användningen av scenarier har gjort det möjligt för designteamet att på djupet förstå de situationer som förarna står inför samt  har hjälpt till att under workshops få en bättre förståelse för drivrutinerna. Dessutom har rekommendationer för hårdvara, installation och framtida arbete beskrivits för fortsatt genomförande av projektet. / Head-up display (HUD) has a proven track record in the aviation and automobile sectors, allowing pilots and drivers to access information without diverting attention from the outside world. Similar benefits may be realized by the installation of HUD in locomotive cabs. The objective of this thesis work is to develop the user interface for HUD based on the ERTMS system. The HUD will be an added safety feature to the trains to prevent drivers from refocusing between the instrument panel and the outside view thus leading to reduced driver fatigue and better observation of the tracks ahead. Scenario Based Design method has been used to implement the project work with discussions regarding its advantages and limitations. The use of scenarios has allowed the design team to understand the scenarios that the drivers face in depth and has aided during the workshops to understand the drivers’ routine better. Additionally, recommendations for the hardware, installation and future work have been provided to support further implementation of the project.

Metabolomics is the methodical scientific study of biochemical processes associated with the metabolome—which comprises the entire collection of metabolites in any biological entity. Metabolome changes occur as a result of modifications in the genome and proteome, and are, therefore, directly related to cellular phenotype. Thus, metabolomic analysis is capable of providing a snapshot of cellular physiology. Untargeted metabolomics is an impartial, all-inclusive approach for detecting as many metabolites as possible without a priori knowledge of their identity. Hence, it is a valuable exploratory tool capable of providing extensive chemical information for discovery and hypothesis-generation regarding biochemical processes. A history of metabolomics and advances in the field corresponding to improved analytical technologies are described in Chapter 1 of this dissertation. Additionally, Chapter 1 introduces the analytical workflows involved in untargeted metabolomics research to provide a foundation for Chapters 2 – 5. Part I of this dissertation which encompasses Chapters 2 – 3 describes the utilization of mass spectrometry (MS)-based untargeted metabolomic analysis to acquire new insight into cancer detection. There is a knowledge deficit regarding the biochemical processes of the origin and proliferative molecular mechanisms of many types of cancer which has also led to a shortage of sensitive and specific biomarkers. Chapter 2 describes the development of an in vitro diagnostic multivariate index assay (IVDMIA) for prostate cancer (PCa) prediction based on ultra performance liquid chromatography-mass spectrometry (UPLC-MS) metabolic profiling of blood serum samples from 64 PCa patients and 50 healthy individuals. A panel of 40 metabolic spectral features was found to be differential with 92.1% sensitivity, 94.3% specificity, and 93.0% accuracy. The performance of the IVDMIA was higher than the prevalent prostate-specific antigen blood test, thus, highlighting that a combination of multiple discriminant features yields higher predictive power for PCa detection than the univariate analysis of a single marker. Chapter 3 describes two approaches that were taken to investigate metabolic patterns for early detection of ovarian cancer (OC). First, Dicer-Pten double knockout (DKO) mice that phenocopy many of the features of metastatic high-grade serous carcinoma (HGSC) observed in women were studied. Using UPLC-MS, serum samples from 14 early-stage tumor DKO mice and 11 controls were analyzed. Iterative multivariate classification selected 18 metabolites that, when considered as a panel, yielded 100% accuracy, sensitivity, and specificity for early-stage HGSC detection. In the second approach, serum metabolic phenotypes of an early-stage OC pilot patient cohort were characterized. Serum samples were collected from 24 early-stage OC patients and 40 healthy women, and subsequently analyzed using UPLC-MS. Multivariate statistical analysis employing support vector machine learning methods and recursive feature elimination selected a panel of metabolites that differentiated between age-matched samples with 100% cross-validated accuracy, sensitivity, and specificity. This small pilot study demonstrated that metabolic phenotypes may be useful for detecting early-stage OC and, thus, supports conducting larger, more comprehensive studies. Many challenges exist in the field of untargeted metabolomics. Part II of this dissertation which encompasses Chapters 4 – 5 focuses on two specific challenges. While metabolomic data may be used to generate hypothesis concerning biological processes, determining causal relationships within metabolic networks with only metabolomic data is impractical. Proteins play major roles in these networks; therefore, pairing metabolomic information with that acquired from proteomics gives a more comprehensive snapshot of perturbations to metabolic pathways. Chapter 4 describes the integration of MS- and NMR-based metabolomics with proteomics analyses to investigate the role of chemically mediated ecological interactions between Karenia brevis and two diatom competitors, Asterionellopsis glacialis and Thalassiosira pseudonana. This integrated systems biology approach showed that K. brevis allelopathy distinctively perturbed the metabolisms of these two competitors. A. glacialis had a more robust metabolic response to K. brevis allelopathy which may be a result of its repeated exposure to K. brevis blooms in the Gulf of Mexico. However, K. brevis allelopathy disrupted energy metabolism and obstructed cellular protection mechanisms including altering cell membrane components, inhibiting osmoregulation, and increasing oxidative stress in T. pseudonana. This work represents the first instance of metabolites and proteins measured simultaneously to understand the effects of allelopathy or in fact any form of competition. Chromatography is traditionally coupled to MS for untargeted metabolomics studies. While coupling chromatography to MS greatly enhances metabolome analysis due to the orthogonality of the techniques, the lengthy analysis times pose challenges for large metabolomics studies. Consequently, there is still a need for developing higher throughput MS approaches. A rapid metabolic fingerprinting method that utilizes a new transmission mode direct analysis in real time (TM-DART) ambient sampling technique is presented in Chapter 5. The optimization of TM-DART parameters directly affecting metabolite desorption and ionization, such as sample position and ionizing gas desorption temperature, was critical in achieving high sensitivity and detecting a broad mass range of metabolites. In terms of reproducibility, TM-DART compared favorably with traditional probe mode DART analysis, with coefficients of variation as low as 16%. TM-DART MS proved to be a powerful analytical technique for rapid metabolome analysis of human blood sera and was adapted for exhaled breath condensate (EBC) analysis. To determine the feasibility of utilizing TM-DART for metabolomics investigations, TM-DART was interfaced with traveling wave ion mobility spectrometry (TWIMS) time-of-flight (TOF) MS for the analysis of EBC samples from cystic fibrosis patients and healthy controls. TM-DART-TWIMS-TOF MS was able to successfully detect cystic fibrosis in this small sample cohort, thereby, demonstrating it can be employed for probing metabolome changes. Finally, in Chapter 6, a perspective on the presented work is provided along with goals on which future studies may focus.