The purpose of this study was to explore the preferred information sources and delivery channels for farm-related information among selected northeast Texas farmers and describe these results in a manner which might enable the Texas AgriLife Extension Service and other agriculture-focused entities better position themselves to address the needs of their clientele. An instrument was developed and mailed to (N = 290) randomly selected farmers from existing Extension mailing lists in four northeast Texas counties: Bowie, Rains, Rusk and Shelby. Participants had the option of responding online or via return mail. The highest ranking interpersonal information sources were other farmers, AgriLife Extension personnel, and seminars/workshops. The lowest ranking interpersonal information sources were agricultural lenders/bankers and private consultants. The highest ranking print-based information sources were agricultural newspapers and farm magazines. The lowest ranking print-based information sources were publications from non-governmental farm organizations and daily or weekly newspapers. Respondents were neutral on the usefulness of television and radio as information sources. The Internet was the only electronic information source agreed to as useful by responding farmers. The lowest ranking electronic media source was social media. The most common type of contact between farmers and the Texas AgriLife Extension Service was reading an Extension publication monthly, followed by a yearly visit to the Extension office. Farmers were satisfied with the quality of the agriculture related materials and programs provided by the Texas AgriLife Extension Service and were likely to recommend the agency to others. The majority (91.6%) of respondents had not heard of the national Extension website eXtension and only 4 respondents (2.5%) had reported using the website before. Respondents felt that eXtension would increase the accessibility of Extension programming, should be publicized more by local Extension offices, and would make Cooperative Extension more popular. Internet use among farmers was found to be influenced by age, highest level of education attained, Internet connection type, and other electronic devices used. Perceptions about AgriLife Extension were found to be influenced by Innovativeness Category, primary occupation, gender, and other electronic devices used. Findings in this study support the Uses and Gratifications Theory of media use.

This dissertation is a study of error in long haul optical fiber systems and how to coupe with them. First we characterize error events occurring during transmission, then we determine lower bounds on information capacity (achievable information rates) and at the end we propose coding schemes for these systems.Existing approaches for obtaining probability density functions (PDFs) for pulse energy in long-haul optical fiber transmission systems rely on numerical simulations or analytical approximations. Numerical simulations make far tails of the PDFs difficult to obtain, while existing analytic approximations are often inaccurate, as they neglect nonlinear interaction between pulses and noise.Our approach combines the instanton method from statistical mechanics to model far tails of the PDFs, with numerical simulations to refine the middle part of the PDFs. We combine the two methods by using an orthogonal polynomial expansion constructed specifically for this problem. We demonstrate the approach on an example of a specific submarine transmission system.Once the channel is characterized estimating achievable information rates is done by a modification of a method originally proposed by Arnold and Pfitser. We give numerical results for the same optical transmission system (submarine system at transmission rate 40Gb/s).The achievable information rate varies with noise and length of the bit patterns considered (among other parameters). We report achievable numerical rates for systems with different noise levels, propagation distances and length of the bit patterns considered.We also propose two iterative decoding schemes suitable for high-speed long-haul optical transmission. One scheme is a modification of a method, originally proposed in the context of magnetic media, which incorporates the BCJR algorithm (to overcomeintersymbol interference) and Low-Density Parity-Check (LDPC) codes for additional error resilience. This is a ``soft decision scheme" -meaning that the decoding algorithm operates with probabilities(instead of binary values). The second scheme is ``hard decision" -it operates with binary values. This scheme is based on the maximum likelihood sequence detection-Viterbi algorithm and a hard decision"Gallager B" decoding algorithm for LDPC codes.

Denna kandidatuppsats tar upp ämnet informationsmottagning via extranät. Likt människor kan även extranät och andra kommunikationskanaler ha kommunikationsproblem. Bakgrunden till studien är att det finns ett bristande informationsmottagande hos Subaru Nordic ABs extranätsanvändare. Syftet med denna studie är att ta reda på vilka faktorer som påverkar informationsmottagandet via Subaru Nordics extranät genom att göra en enkätundersökning. En kombination av kvalitativ och kvantitativ metod har använts där data samlats in genom en enkät som skickats ut till Subaru Nordics extranätanvändare. Studien har genomförts på fallföretaget Subaru Nordic som är generalagent för bilmärket Subaru i Norden och Baltikum. Vi identifierade sex faktorer som påverkar informationsmottagandet via ett extranät. Den första faktorn är ”Behov av information” som indikerar att Subaru Nordic och andra företag som använder extranät som informationskanal bör uppdatera informationsmottagaren om sin verksamhet för att de ska utföra sitt arbete på bästa sätt. Den andra faktorn är ”Anpassa information till mottagaren” där det framkom att företag bör skicka ut information som är anpassad till mottagarens arbetsområde. Den tredje faktorn är ”Anpassa information till situation” där vi kunde dra slutsatsen att företag bör sprida ut sina informationsutskick. ”Använda flera informationskanaler” är den fjärde faktorn och slutsatsen för den är att det är effektivt att använda sig av en kompletterande informationskanal för informationsutskick. Den femte faktorn är ”Tillgänglig information” där det framkom att företag bör ha tydliga kategorier för att användarna ska finna information de söker på ett smidigt sätt. Den sjätte och sista faktorn är ”Anpassa rubrik efter information” som företag bör lägga stor vikt på för att väcka informationsmottagarens intresse att läsa information. / This bachelor thesis deals with the subject information receiving via an extranet. Like people an information channel can have communication problems too. The background of the study is that there is a lack of information receiving by the users of Subaru Nordics extranet. The aim of this study is to find out what factors that influence the information received through Subaru Nordics extranet by doing a survey. The methodology used in the study is a combination of qualitative and quantitative methods where the data was collected through an online survey, which was sent to Subaru Nordics extranet users. The study has been made on the research company Subaru Nordic, which is the general agent for the car brand Subaru in the Nordic and Baltic countries. We identified six factors that affect the information received via an extranet. The first factor is the need of information, indicating that companies using extranets as an information channel should update their information receivers about their work related activities so they can accomplish their work in the best way. The second factor is to customize the information to the receiver, where it appeared that companies should send out information tailored to the receivers work. The third factor is to adapt information to the situation where we could conclude that companies should spread out the information they share. Using multiple channels of information is the fourth factor, and the conclusion is that using an additional information channel for information sharing is effective. The fifth factor is to make information available, which stated that companies should have clear categories for users to find information they need in a convenient way. The sixth and final factor is to customize the headings of the information that is sent and therefore companies should put great emphasis on the headings to make the information receiver interested to access the information.

Neste trabalho é apresentado um breve estudo sobre o processo de descoberta de conhecimento em banco de dados, com enfoque na etapa de mineração de dados através de regras de associação. Propostas por Agrawal em 1993, num estudo chamado análise de cesta de mercado, as regras de associação representam que com um certo grau de suporte e confiança um conjunto de itens pode estar presente numa transação visto que outro conjunto está presente. A necessidade de análise semelhante às realizadas por Agrawal surgiu em outros campos e estas foram estendidas a outras aplicações. Neste, são apresentadas as principais variações sobre o tema regras de associação encontradas na literatura. É proposta a mineração de dados através de regras de associação sobre filtros de mensagens e canais de informação do software de catálogo, agenda e correio eletrônico Direto. Para as pesquisas são utilizadas três ferramentas: Intelligent Miner, CBA e Magnus Opus. Elas foram aplicadas sobre uma lista de discussão da Linguagem Java, pois o projeto Direto ainda não possui mensagens públicas. As ferramentas possuem características distintas: o Intelligent Miner permite a definição de hierarquias sobre os dados que serão minerados; o Magnus Opus trabalha com diversos filtros e com a definição de intervalos para o tratamento de campos numéricos; o CBA permite que sejam especificados suportes múltiplos para os itens. / This work presents a brief review about knowledge discovery in database having association rules as the data mining process. Association rules were proposed by Agrawal in 1993 in a basket data analysis. Association rules have been extended to other applications because there is a necessity for similar Agrawal’s analysis in different domains. Here are presented some variations proposed in the literature about association rules along with the main algorithms. This work proposes the use of association rules over message filters and information channels from the Direto, which is a catalog, schedule and e-mail software. Three data mining tools were used: Intelligent Miner, CBA and Magnus Opus. They were applied over a Java discussion list because Direto project does not have public messages. Each tool has distinct features: Intelligent Miner allows to define a hierarchy over the data that will be mined; Magnus Opus works with many filters over the data and permits to define ranges over numeric fields and CBA allows to specify multiple minimum support over the items.

Neste trabalho é apresentado um breve estudo sobre o processo de descoberta de conhecimento em banco de dados, com enfoque na etapa de mineração de dados através de regras de associação. Propostas por Agrawal em 1993, num estudo chamado análise de cesta de mercado, as regras de associação representam que com um certo grau de suporte e confiança um conjunto de itens pode estar presente numa transação visto que outro conjunto está presente. A necessidade de análise semelhante às realizadas por Agrawal surgiu em outros campos e estas foram estendidas a outras aplicações. Neste, são apresentadas as principais variações sobre o tema regras de associação encontradas na literatura. É proposta a mineração de dados através de regras de associação sobre filtros de mensagens e canais de informação do software de catálogo, agenda e correio eletrônico Direto. Para as pesquisas são utilizadas três ferramentas: Intelligent Miner, CBA e Magnus Opus. Elas foram aplicadas sobre uma lista de discussão da Linguagem Java, pois o projeto Direto ainda não possui mensagens públicas. As ferramentas possuem características distintas: o Intelligent Miner permite a definição de hierarquias sobre os dados que serão minerados; o Magnus Opus trabalha com diversos filtros e com a definição de intervalos para o tratamento de campos numéricos; o CBA permite que sejam especificados suportes múltiplos para os itens. / This work presents a brief review about knowledge discovery in database having association rules as the data mining process. Association rules were proposed by Agrawal in 1993 in a basket data analysis. Association rules have been extended to other applications because there is a necessity for similar Agrawal’s analysis in different domains. Here are presented some variations proposed in the literature about association rules along with the main algorithms. This work proposes the use of association rules over message filters and information channels from the Direto, which is a catalog, schedule and e-mail software. Three data mining tools were used: Intelligent Miner, CBA and Magnus Opus. They were applied over a Java discussion list because Direto project does not have public messages. Each tool has distinct features: Intelligent Miner allows to define a hierarchy over the data that will be mined; Magnus Opus works with many filters over the data and permits to define ranges over numeric fields and CBA allows to specify multiple minimum support over the items.

Neste trabalho é apresentado um breve estudo sobre o processo de descoberta de conhecimento em banco de dados, com enfoque na etapa de mineração de dados através de regras de associação. Propostas por Agrawal em 1993, num estudo chamado análise de cesta de mercado, as regras de associação representam que com um certo grau de suporte e confiança um conjunto de itens pode estar presente numa transação visto que outro conjunto está presente. A necessidade de análise semelhante às realizadas por Agrawal surgiu em outros campos e estas foram estendidas a outras aplicações. Neste, são apresentadas as principais variações sobre o tema regras de associação encontradas na literatura. É proposta a mineração de dados através de regras de associação sobre filtros de mensagens e canais de informação do software de catálogo, agenda e correio eletrônico Direto. Para as pesquisas são utilizadas três ferramentas: Intelligent Miner, CBA e Magnus Opus. Elas foram aplicadas sobre uma lista de discussão da Linguagem Java, pois o projeto Direto ainda não possui mensagens públicas. As ferramentas possuem características distintas: o Intelligent Miner permite a definição de hierarquias sobre os dados que serão minerados; o Magnus Opus trabalha com diversos filtros e com a definição de intervalos para o tratamento de campos numéricos; o CBA permite que sejam especificados suportes múltiplos para os itens. / This work presents a brief review about knowledge discovery in database having association rules as the data mining process. Association rules were proposed by Agrawal in 1993 in a basket data analysis. Association rules have been extended to other applications because there is a necessity for similar Agrawal’s analysis in different domains. Here are presented some variations proposed in the literature about association rules along with the main algorithms. This work proposes the use of association rules over message filters and information channels from the Direto, which is a catalog, schedule and e-mail software. Three data mining tools were used: Intelligent Miner, CBA and Magnus Opus. They were applied over a Java discussion list because Direto project does not have public messages. Each tool has distinct features: Intelligent Miner allows to define a hierarchy over the data that will be mined; Magnus Opus works with many filters over the data and permits to define ranges over numeric fields and CBA allows to specify multiple minimum support over the items.