Paivio的雙碼理論(Dual Coding Theory)認為, 語文與視覺處理歷程為互助相輔.但是, Schooler and Englster-Schooler(1990)卻提出 "語文遮蔽效果(verbalovershadowing effect, VOE)", 認為視決刺激在提取階段, 可能因語文訊息的存在,而產生干擾的現象. 這種遮蔽作用, Brandimonte, Hitch, and Bishop(1992a,b)發現同時出現在記憶與登錄階段. Marks(1991)更發現它會隨視覺訊息的屬性差異 - 資料趨勢(data-driven)與概念趨勢(conceptual-driven), 而有不同的影響結果. 資料趨勢的視覺刺激訊息, 傾向於處理物理性的視覺特姓, 故不會因為個體採取語文處理的模式, 而出縣語文遮蔽效果, 干擾記憶與辨市的表現. 相反的, 概念趨勢的視覺訊息,則傾向於處理刺激本質的屬性, 與語文訊息有所關連, 連帶在個體採取語文處理模式 時, 便會因語文遮蔽效果而干擾表現。 本研究主要探討不同視覺刺基屬性於登錄階段與語文處理歷程之間的交互作用關係. 實驗一藉由操弄 "登錄型式(語文描述, 口語抑制, 控制組)" 與 "視覺訊息類別(資料趨勢訊息, 概念趨勢訊息)" 的方式, 檢驗此二獨變項之間的交互作用, 亦即檢驗 "登錄階段將出現VOE" 與 "資料趨勢與概念趨勢訊息的VOE將有所差別" 的假設.實驗結果利用杜恩氏多重比較法證實研究者所提之假設: 不同視決刺激屬性於登錄階段的VOE有所差異 - 資料趨勢訊息於登錄階段並不會出現VOE, 概念趨勢訊息於登錄階段則會出現VOE。 實驗二則主要探討不同視覺刺激屬性於登錄階段出現VOE的導因. 借助Lindsay and Johnson(1989)所提出的 "資源混淆(source confusion)", 與Fallshore and Schooler(1995)所提出的 "特徵轉換(characteristics shift)" 作為理論根據, 研究者同時操弄 "登錄訊息屬性", "語文登錄形式", 與 "有無忽略提示" 三個獨變項, 並檢驗此三獨變項之間的交互作用, 亦即檢驗 "資料趨勢訊息不會出現VOE" 與 "概念趨勢訊息於語文登錄成功前, 會因為資源混淆而出現VOE; 語文登錄成功之後, 則會因特徵轉換而出現VOE" 的假設. 研究結果同樣利用杜恩氏多重比較法進行檢驗, 亦獲支持: 視覺刺激的資料趨勢訊息, 即使以語文描述方式進行視覺刺激登錄, 仍舊不會出現VOE. 而概念趨勢訊息若以親自描述的方式進行語文登錄,則因語文登錄完成, 造成個體處理模式的特徵轉換, 因而不論是否給予忽略提示, 都將因VOE而抑制辨識表現; 若以閱讀他人描述的方式進行語文登錄, 則由於登錄尚未完成, 個體因語文與視覺訊息的提取資源混淆, 故可利用忽略提示的方式, 讓個體區辨視覺與語文訊息的差異, 進而避免VOE的干擾作用。

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Analytic knowledge about the systematic variation in a language has an important place in the description of the language. Such knowledge is interesting e.g. in the language teaching domain, as a background for various types of linguistic studies, and in the development of more dynamic speech technology applications. In previous studies, the effects of single variables or relatively small groups of related variables on the pronunciation of words have been studied separately. The work described in this thesis takes a holistic perspective on pronunciation variation and focuses on a method for creating general descriptions of phone-level pronunciation in discourse context. The discourse context is defined by a large set of linguistic attributes ranging from high-level variables such as speaking style, down to the articulatory feature level. Models of phone-level pronunciation in the context of a discourse have been created for the central standard Swedish language variety. The models are represented in the form of decision trees, which are readable for both machines and humans. A data-driven approach was taken for the pronunciation modelling task, and the work involved the annotation of recorded speech with linguistic and related information. The decision tree models were induced from the annotation. An important part of the work on pronunciation modelling was also the development of a pronunciation lexicon for Swedish. In a cross-validation experiment, several sets of pronunciation models were created with access to different parts of the attributes in the annotation. The prediction accuracy of pronunciation models could be improved by 42.2% by making information from layers above the phoneme level accessible during model training. Optimal models were obtained when attributes from all layers of annotation were used. The goal for the models was to produce pronunciation representations representative for the language variety and not necessarily for the individual speakers, on whose speech the models were trained. In the cross-validation experiment, model-produced phone strings were compared to key phonetic transcripts of actual speech, and the phone error rate was defined as the share of discrepancies between the respective phone strings. Thus, the phone error rate is the sum of actual errors and discrepancies resulting from desired adaptations from a speaker-specific pronunciation to a pronunciation reflecting general traits of the language variety. The optimal models gave an average phone error rate of 8.2%. / QC 20100901

No description available.

No description available.

A challenge for the clinical management of Parkinson's disease (PD) is the large within- and between-patient variability in symptom profiles as well as the emergence of motor complications which represent a significant source of disability in patients. This thesis deals with the development and evaluation of methods and systems for supporting the management of PD by using repeated measures, consisting of subjective assessments of symptoms and objective assessments of motor function through fine motor tests (spirography and tapping), collected by means of a telemetry touch screen device. One aim of the thesis was to develop methods for objective quantification and analysis of the severity of motor impairments being represented in spiral drawings and tapping results. This was accomplished by first quantifying the digitized movement data with time series analysis and then using them in data-driven modelling for automating the process of assessment of symptom severity. The objective measures were then analysed with respect to subjective assessments of motor conditions. Another aim was to develop a method for providing comparable information content as clinical rating scales by combining subjective and objective measures into composite scores, using time series analysis and data-driven methods. The scores represent six symptom dimensions and an overall test score for reflecting the global health condition of the patient. In addition, the thesis presents the development of a web-based system for providing a visual representation of symptoms over time allowing clinicians to remotely monitor the symptom profiles of their patients. The quality of the methods was assessed by reporting different metrics of validity, reliability and sensitivity to treatment interventions and natural PD progression over time. Results from two studies demonstrated that the methods developed for the fine motor tests had good metrics indicating that they are appropriate to quantitatively and objectively assess the severity of motor impairments of PD patients. The fine motor tests captured different symptoms; spiral drawing impairment and tapping accuracy related to dyskinesias (involuntary movements) whereas tapping speed related to bradykinesia (slowness of movements). A longitudinal data analysis indicated that the six symptom dimensions and the overall test score contained important elements of information of the clinical scales and can be used to measure effects of PD treatment interventions and disease progression. A usability evaluation of the web-based system showed that the information presented in the system was comparable to qualitative clinical observations and the system was recognized as a tool that will assist in the management of patients.

Ένας σημαντικός παράγοντας για την αποτελεσματική συνεργασία μεταξύ των μελών ομάδας εργασίας, που είναι πρωταρχικής σημασίας για την επιτυχημένη υλοποίηση των τεχνικών έργων, είναι η αποδοτική επικοινωνία τους. Η επικοινωνία αυτή, όμως, δυσχεραίνεται λόγω του κατακερματισμού του κατασκευαστικού τομέα, του τεράστιου όγκου και της ποικιλομορφίας των πληροφοριών της διαδικασίας κατασκευής, των γεωγραφικών αποστάσεων μεταξύ του κεντρικού γραφείου της κατασκευαστικής εταιρίας και των εργοταξίων, καθώς και της μοναδικότητας και της πολυπλοκότητας των τεχνικών έργων. Οι προηγούμενες ερευνητικές προσπάθειες και οι εμπορικές εφαρμογές που σχετίζονται με τη διαχείριση πληροφοριών στη βιομηχανία των κατασκευών έχουν κυρίως επικεντρωθεί στην ηλεκτρονική διαχείριση εγγράφων (αλλά όχι ουσιαστικά στη διαχείριση πληροφοριών) και έχουν θέσει το εννοιολογικό πλαίσιο των διαδικτυακών βάσεων δεδομένων για τον κατασκευαστικό κλάδο. Περαιτέρω, μερικές ερευνητικές προσπάθειες έχουν οδηγήσει σε πιλοτική ανάπτυξη συστήματος διαχείρισης πληροφοριών, αλλά αυτές έχουν εστιάσει εν γένει σε μεμονωμένα τμήματα της κατασκευαστικής διαδικασίας και στις πιο βασικές πληροφορίες αυτών. Στα πλαίσια της εργασίας σχεδιάστηκε και αναπτύχθηκε ένα διαδικτυακό σύστημα διαχείρισης και διακίνησης πληροφοριών, ως προσπάθεια βελτίωσης της επικοινωνίας των συμμετεχόντων στην κατασκευαστική διαδικασία. Το σύστημα αποτελεί δεδομενο-κεντρική προσέγγιση, σε αντίθεση με τις εγγραφο-κεντρικές προσεγγίσεις των υπαρχόντων συστημάτων, και έχει δώσει έμφαση στον αναλυτικό σχεδιασμό της βάσης δεδομένων. Η ανάπτυξη του συστήματος βασίστηκε σε διερεύνηση που έγινε με χρήση ερωτηματολογίου και έδειξε ότι η ελληνική κατασκευαστική βιομηχανία δεν χρησιμοποιεί γενικά προηγμένα συστήματα διαχείρισης πληροφοριών κυρίως λόγω της περιορισμένης αποτελεσματικότητας των υπαρχόντων συστημάτων. Το προτεινόμενο σύστημα αποτελείται από μία δομημένη σχεσιακή βάση δεδομένων και μία δυναμική, οδηγούμενη από δεδομένα, διαδικτυακή εφαρμογή που επιτρέπει στους χρήστες του συστήματος να αλληλεπιδρούν μακρόθεν με τη βάση δεδομένων. Η βάση δεδομένων σχεδιάστηκε μετά από διερεύνηση και καταγραφή τόσο των χρηστών του συστήματος όσο και των απαιτούμενων πληροφοριών. Ο τελικός σχεδιασμός της βάσης δεδομένων, ο οποίος προέκυψε μετά από βρόχους μοντελοποίησης οντοτήτων και κανονικοποίησης, περιλαμβάνει 32 τύπους οντότητας με 42 σχέσεις μεταξύ τους και 172 ιδιότητες συνολικά. Ο σχεδιασμός της βάσης δεδομένων ολοκληρώθηκε με την ανάπτυξη 70 ερωτημάτων, που αποτελούν είτε συνδυασμό ανάκτησης δεδομένων που πληρούν συγκεκριμένα κριτήρια είτε προϊόντα επεξεργασίας των δεδομένων. Οι χρήστες του συστήματος μπορούν να αλληλεπιδρούν με τη βάση δεδομένων μέσω της διαδικτυακής εφαρμογής και να εκτελούν συγκεκριμένες λειτουργίες, όπως εισαγωγή, αναζήτηση, θέαση, τροποποίηση/ενημέρωση και διαγραφή δεδομένων. Η πρόσβαση στον ιστότοπο του συστήματος ελέγχεται με ονόματα και κωδικούς πρόσβασης. Η υλοποίηση της βάσης δεδομένων και της διαδικτυακής εφαρμογής έγινε με τα λογισμικά MS-Access και Dreamweaver MX αντίστοιχα. Ως τεχνολογία εξυπηρετητή χρησιμοποιήθηκαν οι Active Server Pages, ως γλώσσα προγραμματισμού η VBScript και ως εξυπηρετητής δικτύου ο Internet Information Server. Η λειτουργικότητα και η αποτελεσματικότητα του συστήματος ελέγχθηκαν με την πιλοτική εφαρμογή. Το σύστημα παρουσιάζει ικανοποιητική αποτελεσματικότητα ως προς τη δυναμική ενημέρωση των πληροφοριών, την επεξεργασία των δεδομένων και την παροχή αξιόπιστων αποτελεσμάτων. Με την αποκτηθείσα εμπειρία εκτιμάται ότι τα διαδικτυακά συστήματα διαχείρισης πληροφοριών με σχεδιασμό λεπτομερούς βάσης δεδομένων μπορούν να βελτιώσουν σημαντικά την επικοινωνία των συμμετεχόντων στην κατασκευή τεχνικών έργων με αποτέλεσμα την αύξηση της παραγωγικότητας της κατασκευαστικής ομάδας, την οικονομία χρόνου και πόρων, και τη βελτίωση της ποιότητας κατασκευής. / Communicating effectively among task groups is one of the most important factors for the success of a project. This communication, however, is hindered by the extended fragmentation of the construction industry, the large volumes and wide dissimilarity of the information involved in the construction process, and the uniqueness and complexity of construction projects. The distance between the construction company headquarters and construction sites augments the communication problem. Previous research efforts and commercial applications concerning information management for the construction industry have mainly focused on electronic document management and have set the conceptual framework of web databases for the construction industry. Further, some of the research efforts have included pilot implementation of management systems, but rather on parts of the construction process and including only the most basic information. A web-based system that facilitates construction information management and communication is designed and implemented. Unlike common document-based systems, the present work focuses on demonstrating the potential of data-centric web databases in enhancing the communication process during project execution. The system development has taken into consideration results from a questionnaire-based research in the Greek construction industry, which has indicated the absence of advanced information management systems, mainly because of the limited efficiency of existing systems. The proposed system consists of a relational database and a dynamic, data-driven web application that allows the end users to remotely interact with the database. The database design, which has been preceded by an end users analysis and an information analysis, has involved loops of entity modelling and normalisation. The database contains 32 tables with 42 relationships among them, a total of 172 fields, and 70 queries that constitute either retrieval of data that satisfy preset criteria or products of data processing. End users access the database through the internet and can perform certain transactions, such as insert, search, view, update, and delete data. The access to the system is controlled with usernames and passwords. The system has been implemented using MS-Access as the database management system and Macromedia Dreamweaver MX for developing the data-driven web application. Active Server Pages have been selected as server technology, VBScript as the programming language, and Internet Information Server as the web server. The effectiveness and efficiency of the system has been tested with a pilot application. Results from the pilot application demonstrate the technical feasibility of the system and its enhanced capability, compared to ordinary practices, to provide concise and reliable information, quick/remote access, and prompt updating potential. As a result, communication among project participants can improve, misunderstandings can be reduced or eliminated, and more time can be spent on decision-making. Ultimately, this will lead to increased productivity, time and cost savings, as well as to higher construction quality.

Controle preditivo baseado em modelos (MPC) é uma técnica de controle amplamente utilizada na indústria de processos químicos. Por outro lado, o método de identificação em subespaços (SID) tem se mostrado uma alternativa eficiente para os métodos clássicos de identificação de sistemas. Pela combinação dos conceitos de MPC e SID, surgiu, no final da década de 90, uma nova técnica de controle, denominada controle preditivo com enfoque em subespaços (SPC). Essa técnica também é conhecida como controle preditivo orientado a dados. Ela substitui por um único passo as três etapas do projeto de um MPC: a identificação do modelo, o cálculo do observador de estados e a construção das matrizes de predição. Este trabalho tem como principal objetivo revisar estudos feitos na área de SPC, aplicar esse método em sistemas típicos da indústria química e propor novos algoritmos. São desenvolvidos três algoritmos de excitação interna para o método SPC, que permitem gerar dados persistentemente excitantes enquanto um controle mínimo do processo é garantido. Esses algoritmos possibilitam aplicar identificação em malha fechada, na qual o modelo do controlador SPC é reidentificado utilizando dados previamente excitados. Os controladores SPC e SPC com excitação interna são testados e comparados ao MPC por meio de simulações em dois processos distintos. O primeiro consiste em uma coluna debutanizadora de uma unidade de destilação, para a qual são disponibilizados dois modelos lineares referentes a pontos de operação diferentes. O segundo é um reator de polimerização de estireno com dinâmica não linear, cujo modelo fenomenológico é conhecido. Os resultados dos testes indicam que o SPC é mais suscetível a ruídos de medição. Entretanto, verifica-se que esse controlador corrige perturbações nos set-points das variáveis controladas mais rapidamente que o MPC. Simulações realizadas para o SPC com excitação interna mostram que os algoritmos propostos neste trabalho excitam o sistema satisfatoriamente, de modo que modelos mais precisos são obtidos na reidentificação com os dados excitados. / Model Predictive Control (MPC) technology is widely used in chemical process industries. Subspace identification (SID) on the other hand has proven to be an efficient alternative for classical system identification methods. Based on the results from MPC and SID, it was developed in the late 90s a new control approach, called Subspace Predictive Control (SPC). This approach is also known as data-driven predictive control. In this new method, one single operation replaces the three steps in a MPC controller design: system identification, the state observer design and the predictor matrices construction. The aim of this work is to review studies in the field of SPC, to apply this technology to typical systems of chemical industry and to propose new algorithms. It is developed three internal excitation algorithms for the SPC method, which allow the system to be persistently excited while a minimal control of the process is still guaranteed. These algorithms enable the application of closedloop identification, where the SPC controller model is re-identified using the previously excited data. The SPC controller and the SPC controller with internal excitation are tested through simulation for two different processes. The first one is a debutanizer column of a distillation unit for which two linear models corresponding to two different operating points are available. The second one is a non-linear system consisting of a styrene polymerization reactor. A phenomenological model is provided for this system. Tests results indicate that SPC is more susceptible to measurement noises. However, it is noticed that SPC controller corrects perturbations on set-points faster than MPC. Simulations for the SPC with internal excitation show that the proposed algorithms sufficiently excite the system, in the sense that more precise models are obtained from the re-identification with excited data.

Made available in DSpace on 2016-08-17T14:52:54Z (GMT). No. of bitstreams: 1 Romulo Alves Dias.PDF: 2725851 bytes, checksum: eaa8311ad62c875b230e288dfc66efa3 (MD5) Previous issue date: 2003-11-21 / The obsolescence of the IDS's attack identification mechanisms critically compromises the security level of the networks. This research work presents a proposal of a automatic updating model of the network attack detection mechanism for intrusion detection systems based on a society of intelligent agents. The Security Central Agency, a component of the model, distributes a mini-society of attack detection agents, called SAARA, that uses a neural network trained with data captured from several network traffic sources. A computational implementation of the SAARA model, focusing data driven attack detection, is presented for the multiagent IDS NIDIA. / A obsolescência dos mecanismos de identificação de ataques dos SDI´s tem comprometido de forma crítica o nível de segurança das redes de computadores. Esta dissertação apresenta uma proposta de um modelo de atualização automática do mecanismo de detecção de ataques de rede para sistemas de detecção de intrusão baseados na noção de sociedade de agentes inteligentes. A Agência Central de Segurança integrante deste modelo distribui uma mini-sociedade de agentes de detecção de ataque, denominada de SAARA, que utiliza uma rede neural treinada a partir de dados coletados de diversas fontes de tráfego. Uma implementação computacional da SAARA, abordando detecção de ataques orientados a dados, é apresentada dentro do contexto do SDI multiagentes NIDIA.

For smaller business it is important to have good and concrete data to make decisions because there are no big margins to test and fail or go on intuition. The purpose of this study is to create an understanding of how data can be used as a decision-making tool in small business. This paper studies the data two smaller companies collect and how they use the collected data. The study has a qualitative method with interviews which have been used for collecting result. The informants were selected based on their previous knowledge and experience.The collection of data in smaller business is both from internal and external sources that complement each other. It is important to have an understanding and knowledge of the visualizations otherwise it can be misleading. Visualizations are used to find patterns, trends and other affecting factors in the data. Segmentation is used by smaller business to understand their target market, customers and which customers they should direct their attention to. Data-driven decision making uses different sources of information, visualization and segmentation. With data-driven decision making it is important to maintain the overall perspective of the business, while all parts of the business are involved in the process. / För mindre företag är det viktigt att ha bra och konkret data för att fatta beslut eftersom det inte finns så stora marginaler att testa sig fram eller gå på intuition. Syftet med studien är att skapa förståelse för hur data kan användas som ett beslutsfattande verktyg i mindre företag. Studien undersöker vilken data mindre företag samlar in samt hur de använder den data som samlas in. Studien är en kvalitativ där intervjuer använts för datainsamling. Dessa gjordes på två mindre företag där informanterna valdes ut baserat på deras tidigare kunskaper och erfarenheter.Insamlingen av mindre företagens data sker både från interna och externa källor som kompletterar varandra. Det viktigt att ha förståelse och kunskap om visualiseringarna för att de inte ska bli missvisande. Visualiseringar används för att lättare hitta mönster, trender och andra påverkande faktorer i data. Segmentering används hos mindre företag för att förstå företagets målgrupp, kunder och vilka kunder de ska rikta sin uppmärksamhet till. För datadriven beslutsfattning används olika informationskällor, visualiseringar och segmentering. Med datadriven beslutsfattning är det viktigt att behålla helhetsperspektiv över företaget samtidigt som alla delar av företaget är involverade i processen.