Handel via internet har vuxit i rekordfart vilket har lett till fler hemleveranser och därmed fler transporter. Samtidigt ökar behovet av att minska konsumtionens klimatpåverkan. Symboler har varit ett frekvent använt verktyg för att förmedla produkters miljöpåverkan. Hur konsumenter anser att transportens miljöpåverkan sak kommuniceras är ännu ett outforskat område. Syftet med studien är att undersöka hur e-handelskonsumenter anser att kommunikation av miljövänligare transport bör utformas för att det miljövänligare alternativet ska framstå som mer attraktivt. Vidare vill vi undersöka om det finns skillnader och likheter i frågan mellan konsumenter med olika karaktärsdrag och i sådana fall vilka skillnader och likheter. Denna kvantitativa studie antar en deduktiv ansats där undersökningen utformas med tidigare forskning som bakgrund. En tvärsnittsdesign ligger till grund för det empiriska materialet och urvalet är e-handelskonsumenter av dagligvaror. Studiens resultat visar att enligt konsumenterna ska kommunikationen av miljövänligare transport bestå av formatet symbol och informationen ska ta hänsyn till att de motiveras mest av att göra gott för omvärlden och miljön, att ta eget ansvar samt att förstå konsekvenserna av sina val. Det största hindret enligt konsumenterna är pris. Vidare upptäcktes vissa samband mellan konsumenternas karaktärsdrag och vilken kommunikation de anser gör den miljövänligare transporten mer attraktiv. / Introduction Online shopping has grown rapidly which has led to an increased home delivery transportation. At the same time, the importance of decreasing the climate impact from consumption is a fact. Symbols have been a popular tool to communicate the environmental impact of products. The consumers’ opinions regarding how the communication of environmentally friendly transports should be made, is still an unexplored area. Purpose The purpose of the study is to investigate how e-commerce consumers consider that communication of environmentally friendly transportation should be designed to make that option more attractive. Furthermore, we want to investigate whether there may be differences and similarities between consumers with different characteristics and, in such cases, which those are. Method This quantitative study has a deductive approach and the survey was designed upon a foundation of previous research. The empirical material consists of a survey where the selection was ecommerce consumers of groceries. Conclusion This study’s results show that, according to the consumers, communication of environmentally friendly transportation should consist of the format symbol and the information should consider that they are mostly motivated by doing good for their surrounding world, acting responsibly and understanding the consequences of their action. The largest obstacle for the consumers is the price. Furthermore, some relationships were identified between consumer characteristics and what type of communication they consider makes more environmentally friendly transport attractive.

This project is a web application for two types of bookstores an E-Bookstore and a PDF-Bookstore. Both are document sellers, however, The E-Bookstore is not a currency user. The PDF-Bookstore sells PDF documents and issues a lightweight currency called Scart. Customers can sell their PDF documents to earn Scart currency and buy PDF documents by paying with Scart.

This dissertation focuses on the data exchange bibliographic formats that have been used in the libraries since the 1960s. There have not been many changes over the decades although librarians have been calling for them. Since the beginning of the new millennium, there has been a growing pressure for change. The aim of this dissertation is to try to summarize the activities in this field and to outline possible future development. The formats used in the past and in the present are analysed in the first part. It is possible to predict the future development on the basis of the analysis of individual projects and on the basis of surveys. The results of the analysis suggest that these activities are headed to a linked data publication model that preserves the current cataloguing procedures. Keywords: exchange formats, bibliographic data, MARC format, MARC 21 format, linked data, BIBFRAME, Schema.org, cataloguing

I will present the issue of passportization in my work. I will analyze the current status of the BUT buildings. I will describe possible solutions of passportization at the BUT in the future. I will focus on the analysis of the "obr" format through the method of reverse engineering. I will do the analysis of the acquired data. I will describe the way of saving of the passportization information. I will design a graphic browser and a passportization editor.

This thesis deals with an issue of how can graphical modifications of response options in online questionnaire influence the respondents' answers. Online questionnaire as a data collection method offers a wide range of visual adjustments. Therefore, it is necessary for the graphical format to be treated with caution, because it can produce significant differences in respondents' answers. The goal of this thesis is to find out, with the help of two versions of online questionnaire that differ in the graphical format of response options, whether and what differences in answers these modifications produce. The attention is also payed to the response time differences. Together there are eleven modifications tested, each of them is represented twice. The analysis shows that the differences in graphical format of response options do influence the answers; there were 7 of 11 hypotheses confirmed. One of the surprising findings is that in the case of comparing the format of check boxes and the format of writing answers into text boxes, respondents answered with a maximum number of allowed answers in both version. This type of result was not expected in the case of the "writing into text boxes" format. Other findings show that some modifications influence more women than men, for example the use of a...

De nombreuses applications en calcul scientifique traitent des matrices creuses de grande taille ayant des structures régulières ou irrégulières. Pour réduire à la fois la complexité spatiale et la complexité temporelle du traitement, ces matrices nécessitent l'utilisation d'une structure particulière de stockage (ou de compression) des données ainsi que l’utilisation d’architectures cibles parallèles/distribuées. Le choix du format de compression le plus adéquat dépend généralement de plusieurs facteurs dont, en particulier, la structure de la matrice creuse, l'architecture de la plateforme cible et la méthode numérique utilisée. Etant donné la diversité de ces facteurs, un choix optimisé pour un ensemble de données d'entrée peut induire de mauvaises performances pour un autre. D’où l’intérêt d’utiliser un système permettant la sélection automatique du meilleur format de compression (MFC) en prenant en compte ces différents facteurs. C’est dans ce cadre précis que s’inscrit cette thèse. Nous détaillons notre approche en présentant la modélisation d'un système automatique qui, étant donnée une matrice creuse, une méthode numérique, un modèle de programmation parallèle et une architecture, permet de sélectionner automatiquement le MFC. Dans une première étape, nous validons notre modélisation par une étude de cas impliquant (i) Horner, et par la suite le produit matrice-vecteur creux (PMVC), comme méthodes numériques, (ii) CSC, CSR, ELL, et COO comme formats de compression, (iii) le data parallèle comme modèle de programmation et (iv) une plateforme multicœurs comme architecture cible. Cette étude nous permet d’extraire un ensemble de métriques et paramètres qui influent sur la sélection du MFC. Nous démontrons que les métriques extraites de l'analyse du modèle data parallèle ne suffisent pas pour prendre une décision (sélection du MFC). Par conséquent, nous définissons de nouvelles métriques impliquant le nombre d'opérations effectuées par la méthode numérique et le nombre d’accès à la mémoire. Ainsi, nous proposons un processus de décision prenant en compte à la fois l'analyse du modèle data parallèle et l'analyse de l’algorithme. Dans une deuxième étape, et en se basant sur les données que nous avons extrait précédemment, nous utilisons les algorithmes du Machine Learning pour prédire le MFC d’une matrice creuse donnée. Une étude expérimentale ciblant une plateforme parallèle multicœurs et traitant des matrices creuses aléatoires et/ou provenant de problèmes réels permet de valider notre approche et d’évaluer ses performances. Comme travail futur, nous visons la validation de notre approche en utilisant d'autres plateformes parallèles telles que les GPUs. / Several applications in scientific computing deals with large sparse matrices having regular or irregular structures. In order to reduce required memory space and computing time, these matrices require the use of a particular data storage structure as well as the use of parallel/distributed target architectures. The choice of the most appropriate compression format generally depends on several factors, such as matrix structure, numerical method and target architecture. Given the diversity of these factors, an optimized choice for one input data set will likely have poor performances on another. Hence the interest of using a system allowing the automatic selection of the Optimal Compression Format (OCF) by taking into account these different factors. This thesis is written in this context. We detail our approach by presenting a design of an auto-tuner system for OCF selection. Given a sparse matrix, a numerical method, a parallel programming model and an architecture, our system can automatically select the OCF. In a first step, we validate our modeling by a case study that concerns (i) Horner scheme, and then the sparse matrix vector product (SMVP), as numerical methods, (ii) CSC, CSR, ELL, and COO as compression formats; (iii) data parallel as a programming model; and (iv) a multicore platform as target architecture. This study allows us to extract a set of metrics and parameters that affect the OCF selection. We note that data parallel metrics are not sufficient to accurately choose the most suitable format. Therefore, we define new metrics involving the number of operations and the number of indirect data access. Thus, we proposed a new decision process taking into account data parallel model analysis and algorithm analysis.In the second step, we propose to use machine learning algorithm to predict the OCF for a given sparse matrix. An experimental study using a multicore parallel platform and dealing with random and/or real-world random matrices validates our approach and evaluates its performances. As future work, we aim to validate our approach using other parallel platforms such as GPUs.

This thesis is interested in format of executable files EXE. It is focused on parts relevant for reverse engineering. It is interested in assembler, binary representation of instruction and disassembling. Follow I introduce converting from executables to control flow graph, basic structures (branches, cycles) detection.

In this study we explore the possibility of using ChatGPT, to summarise large contents of educational content and put it in a template that later can be used for dialogue purposes and will explore the challenges and solutions that occur during the implementation. Today there is a problem for users to create wellmade prompts for learning scenarios that fulfill all the requirements set by the user. This problem is significant as it addresses the challenges of information overload and how generating prompts for dialogue purposes can be trivialized for users. We solved this problem by doing an implementation for the company Fictive Reality in their application, conducting research, and performing tests. The implementation was made with the help of OpenAI’s application programming interface, ChatGPT-4 which is a model that is popular due to its wide range of domain knowledge, and we connected it to a web page where users could upload text or audio files. The method to find a suitable prompt to summarise text was primarily through experimentation supported by previous research. We used automatic metrics for evaluation like ROUGE, BERTScore, and ChatGPT(Self-Evaluation), we also had users give feedback on the implementation and quality of the result. This study shows that ChatGPT effectively summarizes extensive educational content and transforms it into dialogue templates for ChatGPT to use. The research demonstrates streamlined and improved prompt creation, addressing the challenges of information overload. The efficiency and quality were either equal to or surpassed user-generated prompts while preserving almost relevant information, and reduced the time-consumption of this task by a substantial margin. The biggest struggle we had was getting ChatGPT to grasp our instructions. However, with research and with an iterative approach the process became much smoother. ChatGPT exhibits robust potential for enhancing educational prompt generation. Future work could be dedicated to improving the prompt further, by making it more flexible. / I denna studie utforskar vi möjligheten att använda ChatGPT för att sammanfatta stora mängder utbildningsinnehåll och placera det i en mall som senare kan användas för dialogändamål. Vi kommer att undersöka de utmaningar och lösningar som uppstår under implementeringen. Idag finns det ett problem för användare att skapa välgjorda uppmaningar för lärandescenarier som uppfyller alla krav som användaren ställer. Detta problem är betydande då det tar upp utmaningarna med informationsöverbelastning och hur generering av uppmaningar för dialogändamål kan förenklas för användare. Vi löste detta problem genom att göra en implementation hos Fictive Reality där vi gjorde forskning, tester och programvara. Implementeringen gjordes med hjälp av OpenAI:s applikationsprogrammeringsgränssnitt, ChatGPT-4, som är en modell som är populär på grund av dess breda kunskap inom olika områden. Vi anslöt den till en webbsida där användare kunde ladda upp text- eller ljudfiler. Metoden för att hitta en lämpliga instruktioner för att sammanfatta texter var främst genom experimentering med stöd av tidigare forskning i området. Vi använde automatiska utvärderings verktyg, såsom ROUGE, BERTScore och ChatGPT (självutvärdering). Vi hade också användare som gav feedback om implementeringen och resultatets kvalitet. Denna studie visar att ChatGPT effektivt sammanfattar omfattande utbildningsinnehåll och omvandlar det till dialogmallar redo för ett lärnings scenario med ChatGPT. Forskningen visade bra resultat vid skapandet av instruktioner, vilket tacklar utmaningarna med informationsöverbelastning. Effektiviteten och kvaliteten var antingen likvärdig eller bättre än användarskapade instruktioner samtidigt som nästan all relevant information bevarades, och tidsåtgången för denna uppgift minskades avsevärt. Den största utmaningen vi stod inför var att få ChatGPT att förstå våra instruktioner. Dock blev processen mycket smidigare med forskning och en iterativ metodik. ChatGPT visar på stark potential för att förbättra genereringen av utbildningssammanfattningar. Framtida arbete kan fokusera på att ytterligare förbättra instruktionerna genom att göra den mer flexibel.

International Telemetering Conference Proceedings / October 18-21, 2004 / Town & Country Resort, San Diego, California / This paper presents a new approach for the effective generation of translator scripts that can be used to automate the translation of data display configurations from one vendor format to another. Our approach uses the IDEF5 ontology description method to capture the ontology of each vendor format and provides simple rules for performing mappings. In addition, the method includes the specification of mappings between a language-specific ontology and its corresponding syntax specification, that is, either an eXtensible Markup Language (XML) Schema or Document Type Description (DTD). Finally, we provide an algorithm for automatically generating eXtensible Stylesheet Language Transformation (XSLT) scripts that transform XML documents from one language to another. The method is implemented in a graphical tool called the Data Display Translator Generator (DDTG) that supports both inter-language (ontology-to-ontology) and intra-language (syntax-to-ontology) mappings and generates the XSLT scripts. The tool renders the XML Schema or DTD as trees, provides intuitive, user-friendly interfaces for performing the mappings, and provides a report of completed mappings. It also generates data type conversion code when both the source and target syntaxes are XML Schema-based. Our approach has the advantage of performing language mappings at an abstract, ontology level, and facilitates the mapping of tool ontologies to a common domain ontology (in our case, Data Display Markup Language or DDML), thereby eliminating the O(n^2) mapping problem that involves a number of data formats in the same domain.

ITC/USA 2005 Conference Proceedings / The Forty-First Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2005 / Riviera Hotel & Convention Center, Las Vegas, Nevada / The focus of this paper is to describe a unified methodology for developing both internal and external data display translators between an Instrumentation Support System (ISS) format and Data Display Markup Language (DDML), a neutral language for describing data displays. The methodology includes aspects common to both ISSs that have a well documented text-based save format and those that do not, as well as aspects that are unique to each type. We will also describe the means by which an external translator can be integrated into a translator framework. Finally, we will describe how an internal translator can be integrated directly into the ISS.