Föreliggande magisteruppsats skrivs inom fältet Svenska med didaktisk inriktning (Smdi). Syftet är att undersöka digitalt meningsskapande i olika nätgemenskaper utifrån barnets perspektiv, nämligen sju flickor i årskurs 7 och 8. Forskningsfrågorna fokuserar på drivkrafterna bakom deltagande i olika nätgemenskaper, hur man kommunicerar och interagerar med varandra och vad man lär sig. Studien har en kvalitativ ansats.Metoden är semistrukturerade intervjuer.Studiens övergripande teoretiska plattformär ett sociokulturellt perspektiv på meningsskapande.Med teori och begrepp, som kommunikativ handling, även från medieekologin, multiliteracies och samhälls- och medievetenskapen analyseras vad flickorna ger uttryck för att deras digitala meningsskapande består av.Undersökningen visar att de kommunikativa handlingarna läsande, skrivande, lärande, relations- och identitetsskapande samspelar med olika modaliteter, medier och konventioner. De syftar till att inför likasinnade visa upp sig, sina intressen och berättelser, men också om att pröva nya roller och lära sig mer om sig själv.Meningsskapandet handlar även om att kollektivt och i interaktion med andra lösa problemsamt bidra till medskapande för att därigenom bekräfta tillhörigheten inom nätgemenskapen.

Η παρούσα διδακτορική διατριβή έχει ως αντικείμενο την ανάπτυξη στρατηγικών ελέγχου του ρομπότ για το χειρισμό υφασμάτων κατά τη διαδικασία της ραφής. Ένα βασικό πρόβλημα που παρουσιάζουν τα υφάσματα σε σχέση με τα στερεά αντικείμενα είναι η δυσκολία χειρισμού τους εξαιτίας της πολύ δύσκολα προβλέψιμης συμπεριφοράς τους. Πιο συγκεκριμένα, τα υφάσματα έχουν χαμηλή αντίσταση σε κάμψη που συνεπάγεται την εμφάνιση παραμορφώσεων που μεταβάλλουν το σχήμα τους και επιπλέον, παρουσιάζουν έντονη μη-γραμμικότητα και ανισοτροπία με αποτέλεσμα τη μεγάλη δυσκολία μοντελοποίησής τους κυρίως για εφαρμογές πραγματικού χρόνου. Η έρευνα για την εκπόνηση της παρούσας διδακτορικής διατριβής επικεντρώθηκε στην ανάπτυξη στρατηγικών ελέγχου που βασίζονται σε μεθόδους Υπολογιστικής Νοημοσύνης (Ασαφή Λογική, Γενετικούς Αλγόριθμους και Νευρωνικά Δίκτυα) και Ανάδραση Όρασης. Τα ευφυή συστήματα ελέγχου με χρήση τεχνητής όρασης παρέχουν τη δυνατότητα στο ρομπότ να διεκπεραιώσει με επιδεξιότητα εργασίες σχετικές με τη ραφή υφασμάτων σε πραγματικό περιβάλλον με σκοπό την υψηλότερη ευελιξία και αυτοματισμό. Οι ειδικότεροι στόχοι της διατριβής είναι η ελαχιστοποίηση του συνολικού χρόνου εργασίας του ρομπότ για την ολοκλήρωση της ραφής και ο περιορισμός των σφαλμάτων στη ραφή μέσα στα αποδεκτά όρια. Στο πλαίσιο της διατριβής αυτής, αναπτύχθηκε ένα ευφυές σύστημα για τη ραφή υφασμάτων που υλοποιήθηκε σε μια εργαστηριακή διάταξη που περιλαμβάνει ρομπότ, κάμερες και ραπτομηχανή, καθώς και μια ποικιλία υφασμάτων που χρησιμοποιήθηκαν ως δοκίμια. Το ρομποτικό σύστημα ραφής υφασμάτων περιλαμβάνει διαδικασίες που προηγούνται της ραφής, καθώς και τη διαδικασία της ραφής πάνω στο τραπέζι εργασίας μέχρι να ολοκληρωθούν όλες οι ραφές στο ύφασμα. Για τη ραφή των υφασμάτων πάνω στο τραπέζι εργασίας, αναπτύχθηκε ένα Ασαφές Σύστημα ελέγχου χρησιμοποιώντας μια ποικιλία διαφορετικών υφασμάτων. Ιδιαίτερη έμφαση δόθηκε στην ανάπτυξη του συστήματος ικανού να ανταπεξέρχεται στις πτυχώσεις που εμφανίζονται κατά τη διάρκεια του χειρισμού του υφάσματος από το ρομπότ, χωρίς να οδηγείται σε αστοχία. Στη συνέχεια, αναπτύχθηκαν μέθοδοι βελτιστοποίησης της διαδικασίας της ραφής με κριτήριο την ελαχιστοποίηση του συνολικού χρόνου εργασίας της ραφής θέτοντας εκ των προτέρων τα μέγιστα αποδεκτά σφάλματα για τη ραφή. Η ρύθμιση των παραμέτρων του Ασαφούς Συστήματος πραγματοποιήθηκε με Γενετικούς Αλγόριθμους εκτός της παραγωγικής διαδικασίας (off-line) και με ένα εποπτεύον Ασαφές Σύστημα εντός της παραγωγικής διαδικασίας (on-line). Για την πειραματική επαλήθευση του συστήματος, χρησιμοποιήθηκαν υφάσματα που αποτελούνται από ευθύγραμμα τμήματα. Σε επόμενο στάδιο, αναπτύχθηκε μια στρατηγική ελέγχου για τη ραφή υφασμάτων που αποτελούνται από καμπύλα τμήματα με αυθαίρετη καμπυλότητα. Η προτεινόμενη μέθοδος συνδυάζει τη μέθοδο εντοπισμού των κυρίαρχων σημείων με ένα μικρο-Γενετικό Αλγόριθμο με σκοπό την πολυγωνική προσέγγιση των καμπύλων τμημάτων. Το πρόβλημα που διαμορφώθηκε είχε στόχο την ελαχιστοποίηση των πολυγωνικών τμημάτων που προσεγγίζουν τα καμπύλα τμήματα με δεδομένα τα μέγιστα ανεκτά όρια για το σφάλματα στη ραφή. Επιπλέον, αναπτύχθηκε ένα προσαρμοστικό νευρο-ασαφές σύστημα για τη ραφή υφασμάτων με καμπύλα τμήματα που έχει την ικανότητα να μαθαίνει από πρωθύστερη γνώση. Το σύστημα εκπαιδεύτηκε διεξάγοντας πειράματα ραφής με ένα αριθμό υφασμάτων διαφορετικών καμπυλοτήτων, οπότε καθίσταται ικανό να ανταποκριθεί με αξιοπιστία στη ραφή άλλων υφασμάτων, δηλ. υφασμάτων που δε χρησιμοποιήθηκαν στη διαδικασία εκπαίδευσης. Η δημιουργία του νευρο-ασαφούς αυτού συστήματος βασίστηκε στη χρήση μιας πρωτότυπης μεθόδου ομαδοποίησης δεδομένων. Η προτεινόμενη αυτή μέθοδος ομαδοποίησης βασίστηκε στην ανάπτυξη ενός Γενετικού Αλγόριθμου με χρωμοσώματα μεταβλητού μήκους, ο οποίος έχει το πλεονέκτημα ότι εξασφαλίζει ευελιξία όσον αφορά στον αριθμό των ομάδων που προκύπτουν. Η συμβολή της μεθόδου είναι διττή: αφενός, παράγει αυτόματα τον αριθμό των κέντρων των ομάδων και αφετέρου, αναζητά τα κέντρα σε όλο το πεδίο ορισμού, χωρίς να περιορίζεται στα δεδομένα. Η προτεινόμενη μέθοδος έχει γενικότερη αξία και δεν περιορίζεται μόνο στη χρήση της από το νευρο-ασαφές σύστημα. Αξίζει να σημειωθεί ότι όλες οι στρατηγικές ελέγχου του ρομπότ που αναπτύχθηκαν για το χειρισμό των υφασμάτων, εφαρμόστηκαν σε υφάσματα διαφορετικά ως προς το σχήμα (με ευθύγραμμα και καμπύλα τμήματα), το χρώμα και τις ιδιότητες / The objective of this thesis is the development of control strategies for robot handling of flexible sheets towards the sewing. Besides the difficulties that emerge when handling rigid materials using robots, flexible materials pose additional problems due to due to their unpredictable behavior. In particular, fabrics present low resistance in bending that leads to the appearance of deformations that change their shape and present non-linearity and anisotropy, which poses difficulty in modeling them for real-time applications. The research for this thesis has been focused on the development of control strategies based on Artificial Intelligence techniques (Fuzzy Logic, Genetic algorithms and Neural Networks) and Visual Servoing. The intelligent control systems with artificial vision enable robot to perform skilful tasks related to sewing fabrics in realistic environments towards higher flexibility and automation. The control strategies that have been developed are based on Artificial Intelligence techniques (Fuzzy Logic, Genetic algorithms and Neural Networks) and Visual Servoing. The basic goals of this thesis are the minimization of the total time for robot sewing fabrics and the constraint for the stitching errors inside the acceptable limits. In the context of this thesis, a complete intelligent system has been developed for the handling of fabrics towards sewing. This system is comprised of a robot, two cameras and a sewing machine and a wide range of fabric pieces that was used for experimental purposes. The sewing process is decomposed into preprocess planning and on-line handling subtasks (transferring towards the needle, stitching process and the rotation around the needle). A fuzzy control system was developed for robot handling fabrics on a worktable using a wide range of fabrics. Special emphasis was also given on the development of a system capable of tolerating deformations that may appear on the fabric towards robot handling. Next, optimization methods concerning the handling subtasks were developed in the direction of minimizing the total time for robot sewing fabrics considering the maximum allowable error limits. The parameters were tuned using Genetic Algorithms as an off-line process and a Supervisory fuzzy system in an on-line process. Fabrics comprised of straight edges were used for the experimental verification of the system. The next step concerns the development of a control strategy for robot sewing fabric comprised of curved edges with arbitrary curvatures. The proposed method combines the dominant point detection approach with a micro-Genetic Algorithm for the polygonal approximation of the curved edges. The optimization problem aims at the minimization of the polygonal edges that approximate the curved edges without exceeding the maximum acceptable error limits. In addition, an adaptive neuro-fuzzy system for robot sewing fabrics of curved edges is developed, which has learning capabilities. The system was trained through experiments with various fabrics of different curvatures and is capable to respond to new fabrics, which had not been included in the training process. The construction of the proposed neuro-fuzzy system is based on the use of a novel clustering method. The proposed clustering method is based on the development of a Genetic Algorithm with variable-length chromosomes that has the advantage of flexibility as far as the number of the resulting clusters is concerned. The contribution of the proposed method is twofold. On the one hand, the method evolves automatically the appropriate number of cluster centers, as well as the partitioning of the data, without a priori assumption on the cluster centers. On the other hand, it searches for candidate cluster centers in the universe of discourse and not only among data. The proposed approach is general and it is not limited to the construction of the neuro-fuzzy system. It is also worth noting that all developed control strategies have been applied to fabrics of different shape (with or without curvatures), color and properties.

Named Data Networking (NDN) is a recently proposed new Internet architecture. By naming data instead of locations, it changes the very basic network service abstraction from "delivering packets to given destinations" to "retrieving data of given names." This fundamental change creates an abundance of new opportunities as well as many intellectual challenges in application development, network routing and forwarding, communication security and privacy. The focus of this dissertation is a unique feature introduced by NDN: its adaptive forwarding plane. Communication in NDN is done by exchanges of Interest and Data packets. Consumers send Interest packets to request desired Data, routers forward them based on data names, and producers answer with Data packets, which take the same path of Interests but in reverse direction. During this process, routers maintain state information of pending Interests. This state information, coupled with the symmetric exchange of Interest and Data, enables NDN routers to detect loops, observe data retrieval performance, and explore multiple forwarding paths, all at the forwarding plane. Since NDN is still in its early stage, however, none of these powerful features has been systematically designed, valuated, or explored. In this dissertation, we present a concrete design of NDN's forwarding plane to make the network resilient and efficient. First, we design the basic adaptation mechanism and evaluate its effectiveness in circumventing prefix hijack attacks. Second, we propose a novel NACK mechanism for fast failure detection and evaluate its benefits in handling network failures. We also show that a resilient forwarding plane makes routing more stable and more scalable. Third, we design a congestion control mechanism, Dynamic Interest Limiting, to adapt traffic rate in a hop-by-hop and multipath fashion, which is effective even with a large number of flows in a large network topology.

Considering that the current technology is constantly improving, it becomes increasingly important to have an efficient logistics in a company to maintain profitability while achieving a competitive business. Efficient logistics may be accomplished by improving the internal materials handling. In this thesis the internal material handling of steel frames has been studied at a factory in Vaggeryd. The goal of this study is to investigate the problems that exist with the current production flow of products and provide suggestions on how it can be developed to reduce unnecessary handling and movement. The study has a deductive approach where the authors has been using literature studies parallel with empirical analyzes conducted at a company to achieve the purpose of the study. Documentation from the company and interviews with staff and observations form the basis for the data collection carried out. Based on this choice of method, the authors have identified possible problems in the internal material handling at the company and by using well known theories they have accomplished a result. The authors present the improvement proposals in two different ways. The first, specific suggestions, involving problems caused by different rates of operation times, poor communication between operations, poor designed production layout which leads to inefficient material handling of steel frames. These specific suggestions for improvement has led to the second, overall suggestions for improvement, which the authors presents a proposal for a new production layout. The overall improvement proposed by the authors is to switch to a hybrid solution in terms of production system. Merging operations such as painting, installation and packaging in terms of a line, turns out to make the internal materials handling more efficient. Finally, the study ends with a discussion of the results and the method used in this thesis.

No description available.

No description available.

A project was developed to determine the feasibility of using liquid hog manure as a nutrient source (Nitrogen) for the potato crop. A survey of liquid hog manure storage facilities on Prince Edward Island (P.E.I.) provided a sampling technique and the range of nutrients found on hog farms. It was concluded from the data that there were large differences between farms and on farm manure sampling was required to determine accurate nutrient applications. An infrastructure was designed, constructed and tested for storage, handling and the application of liquid hog manure at the Harrington Research Farm, Crops and Livestock Research Centre, Charlottetown, P.E.I. Data from the first of two three year experiments determined that the placement of liquid hog manure under the sown potato row and beside the row (0.23 m) provided yields better than manure placed between the sown rows. These yields were not different for the extra Nitrogen fertilizer treatment. The second field experiment examined the placement of liquid hog manure by various injector designs between the rows after the potato crop was planted. Potato tuber yield data over the three years indicated no differences among injector design nor between the injector treatments and the treatment which received the extra Nitrogen fertilizer. Over both experiments there was a decline in the severity of Rhizoctonia ( Rhizoctonia solani) in one year for plots receiving manure compared to those which received only inorganic fertilizer. There were no differences in the incidence or severity of scab (Streptomyces scabies) over the study. In general liquid manure can be used as nutrient source for the potato crop on P.E.I.

Thesis (M.Tech.: Chiropractic)-Dept. of Chiropractic, Durban Institute of Technology, 2006 129, [21] leaves / The first objective was to investigate the injury profiles of South African cyclists, especially those relating to mountain bicycle use on the road, as there appears to be no knowledge available on mountain bicycle use on the road and related injuries. Secondly, to see if there is an association between injuries and bicycle set-up in a South African context.

Thesis (M.Tech.: Quality)-Dept. of Operations & Quality Management, Durban Institute of Technology, 2005 xiii, 68 leaves / The increasing awareness and demand of consumers for safe and high quality food have lead many companies to undertake a comprehensive evaluation and reorganisation of their food control systems in order to improve efficiency, rationalisation of human resources and to harmonise approaches. This evaluation in food control systems has resulted towards the necessity to shift from the traditional approach that relied heavily on end-product sampling and inspection and to move towards the implementation of a preventative safety and quality approach, based on risk analysis and on the principles of the hazard analysis critical control point (HACCP) system. Yoghurt is the most popular fermented milk world-wide; the estimated annual consumption in South Africa amounts to nearly 67 million litres. The aim of this study was to implement a HACCP program in a commercial yoghurt factory and then to evaluate the program during certain critical stages of the manufacturing process.

Stearoyl-coA desaturase-1 (SCD1) activity has been linked to the development of obesity and the metabolic syndrome (MetS) through its central role in lipid metabolism. Understanding how changes in SCD1 activity affect obesity and MetS risk biomarkers and investigating how these changes in activity affect nutrient handling in non-hepatic tissues is also important. This study investigated how acute SCD1 inhibition effected plasma lipids, skeletal muscle nutrient handling and insulin signaling in mice fed a high-carbohydrate very-low fat diet for 10 weeks. This study demonstrated that SCD1 inhibition created acute dyslipidemia, altered nutrient handling protein activity and increased the percentage of saturated fatty acids (SFA) in hepatic and muscle tissue, independent of dietary oleic acid content. However, the molecular controls of protein synthesis in the mTOR pathway were not affected by the loss of SCD1 activity. In conclusion, we observed that inhibiting hepatic SCD1 activity and subsequently changing the monounsaturated fatty acid (MUFA) to SFA ratios in tissues alters normal nutrient handling in skeletal muscle.