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Corporate brand coherency : examining the effects of the advertising congruence antecedent on consumer attitudes.Paula, Arbouw January 2014 (has links)
The overall aim of this thesis is to investigate the effects of coherence in the corporate branding process. Specifically, this thesis defines and develops the concept of corporate brand coherency (CBC) using four antecedents and four dimensions, and investigates the effects of incongruence based on the advertising antecedent by manipulating ad-brand congruence. Using the Elaboration Likelihood Model (ELM), the research tests whether two-sided messages aid the resolution of incongruence following central route processing and whether greater number of arguments could act as a peripheral cue. Accordingly, a conceptual model was developed to test the effects of ad-brand congruence, message sidedness and argument quantity on corporate credibility, attention and elaboration, attitude towards the ad and attitude towards the corporate brand.
To empirically test this model an online experiment (using a 3x2x2 between-subjects factorial design) was conducted, where subjects were exposed to a modified print advertisement for a grocery store. A total of 528 responses were collected from New Zealand Internet users. Two- and three-way ANCOVAs as well as path analysis was used to analyse the hypothesised relationships.
The results indicate support for CBC, as it was found that congruence led to positive evaluations and higher corporate credibility. Two-sided messages were not found to be effective in reducing the negative effect of incongruence. Instead, two-sided messages led to less favourable evaluations of incongruence. Regardless of the incongruence, the results show that two-sided messages did not lead to positive evaluations, while an increased number of arguments did lead to more favourable attitudes. Overall, the findings show the ELM is not applicable to explain consumers’ responses to incongruence, as incongruence was not found to affect message processing. Additionally, there was no support that message sidedness and argument quantity, respectively, acted as central and peripheral cues. Furthermore, findings indicate that incongruity in advertising can lead to positive evaluations when consumers have a negative prior brand attitude. The theoretical and managerial implications as well as directions for future research based on these findings are discussed.
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Attracting Digital Native Students Through Digital MarketingVennberg, Karin January 2018 (has links)
As the world economies have shifted from being production-based to knowledge-based each country has to develop their technologically literate workforces to stay globally competitive. A low interest in the engineering profession among younger students has caused insufficient support for the workforce demand. Marketers must adapt their efforts to recruiting young people even before they attend college as this focused cohort tend to make career plans early. As today’s teenagers have been using digital media constantly since they grew up, they are frequently called digital natives. They perceive social networking sites, where they can communicate with friends and exchange information with people all over the world, as essential parts of their lives. This makes social networks great promotional tools, as digital natives share experiences and opinions about products and services online, creating a kind of electronic word-of-mouth, which is characterized as the future of social media marketing communications. To investigate in what ways digital natives’ absorb online marketing, the purpose of this research is to provide a better understanding of how technical high schools can address digital marketing activities to attract more students. The thesis was compiled after inquiries from the Swedish nationwide senior high school Teknikcollege, and it is conducted as a quantitative explanatory study, where primary data was collected through an online questionnaire distributed among junior high school students in Luleå and Överkalix. A total of 239 answers were collected and 182 answers were analyzed using statistical techniques. The results suggested that senior high schools should focus their online marketing efforts on visual social media channels, and that people based trust is the most important factor when using the peripheral route to persuade digital natives.
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Adaptive or maladaptive : exploring adolescents' responses to on-line persuasion attemptsButler, Sydney Louw 02 1900 (has links)
Technology is changing the structure and dynamics of how humans communicate. Channels of
communication are also used for attempts at persuasion, but until now persuasion that (if accepted)
would promote the adoption of misinformation could not spread as readily through historical information
channels. With the advent of the Internet and World Wide Web this has changed dramatically.
In this dissertation it is argued that modern digital communication media such as YouTube,
in confluence with what theories of persuasion have to say about how humans deal with persuasion,
may create a situation in which misinformation may spread and be accepted on a large scale. The
research in this dissertation explores this notion by presenting a group of 120 adolescents who are
familiar with the Web with such a misinforming persuasive message. The purpose of which is to determine
whether they accept the misinformation presented in the Web-context or are sceptical of it.
Different manipulations were done to the persuasive message, known to increase the likelihood of
persuasion. The research found that, for this group of participants, no attempt to increase uncritical
acceptance of a persuasive message made a statistical difference between different groupings of
participants. When intended behaviour was measured in addition to attitude towards the misinformation,
participants were even less persuaded. The results are interesting as a starting point for further
study, but its generalizability and certain design features must be called into question / Psychology / M.A. (Psychology)
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Surface Water and Groundwater Hydrology of Borrow-Pit Wetlands and Surrounding Areas of the Lewisville Lake Environmental Learning Area, Lewisville, TexasDodd-Williams, Lynde L. 08 1900 (has links)
The focus of this study was to characterize the surface water and groundwater hydrology of borrow-pit wetlands located within the borders of the Lewisville Lake Environmental Learning Area (LLELA), east of the Elm Fork of the Trinity River. The wetlands were excavated into alluvial deposits downstream of the Lewisville Lake Dam. Both surface water and groundwater contribute to the hydro-period of the borrow-pit wetlands. Nearby marshes exhibit characteristics of groundwater discharge. Salinity in groundwater-fed wetlands could affect establishment of vegetation, as suggested from plant surveys. Surface water input from storm events dilutes salinity levels. Management of LLELA wetlands should include long-term evaluation of hydrology and plantings to enhance habitat. Plans for additional wetlands should consider both surface water and groundwater inputs.
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Bezdrátový sběr diagnostických dat z automobilu podporujících OBD-II / Wireless gathering of diagnostic data of cars supporting OBD-IIFadrný, Jaroslav January 2014 (has links)
Read up protocol OBD-II and familiarize yourself with the concept of existing devices, which use this protocol for wireless data transmission diagnostics car. Different conception mutually compare and suggest own concept device. The device should be consist from standard components without development own hardware. Implement the proposed device. Verify function of device and measure its range and data throughput. Discuss the connection to the database server and simple presentation of data.
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Bekämpning av almsjuka med vaccinpreparat : konsekvenser för den biologiska mångfalden i almar / Control of Dutch elm disease with vaccine preparation : consequences of biodiversity in elm treesHansson, Tobias January 2022 (has links)
Biodiversitet innebär en hög artsammansättning och är viktigt för fungerande ekosystem. Almar (Ulmus-arter) är ett träd som hyser en mängd andra arter och som värderas högt i urbana miljöer. Almar drabbas tyvärr av svampsjukdomen almsjukan som leder till att trädet dör. Detta kan dock motverkas med hjälp av vaccinet Dutch Trig®. Det är känt att vaccinet motverkar almsjukan men kunskapen om vaccinet möjligen påverkar andra arter och organismer än almsjukan är låg. Denna studie utfördes i syfte att undersöka och jämföra om epifyters mångfald och allmäntillståndet mellan ovaccinerade och vaccinerade almar skiljde sig. Metoden för studien delades upp i två delar, en tillväxtmätning och visuell granskning samt en kartläggning av epifyter. Resultatet och analysen visade att skillnaden mellan grupperna hos en variabel var signifikant, hos resterande variabler kunde skillnaderna bero på slumpen. Trots detta kunde ändå vissa mönster utläsas och slutsatsen att det fanns en skillnad både i allmäntillstånd och biodiversitet kunde dras.
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Agricultural Social Media Content Processing utilizing the Elaboration Likelihood ModelWeymouth, Hannah G. 03 August 2023 (has links)
No description available.
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ONLINE NEWS AND THE EFFECTS OF HEURISTIC CUES ON AUDIENCES' ATTITUDESYang, Hocheol 23 May 2014 (has links)
No description available.
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Crowdfunding som investeringsalternativ : En investeringsanalys om potentiella investerares beslutsfattande inom equity- och debt baserad crowdfundingShawkat, Jana, Friskytt, Nathalie January 2018 (has links)
Studien syftar till att analysera equity- och debt baserad crowdfunding i förhållande till studiens primära teori om elaboration likelihood model (ELM) och hur dess variabler påverkar potentiella investerares investeringsbedömningar. Informationsasymmetri och behavioral finance har inkluderats i studien som två kompletterande delteorier. För att undersöka detta har studien avgränsats till potentiella investerare som geografiskt är bosatta i Stockholms län. Undersökningen har genomförts med hjälp av semistrukturerade intervjuer där totalt elva potentiella investerare har intervjuats. Respondenterna har baserats på ett snöbollsurval. Intervjuerna har skett genom att respondenterna tagit del av fyra scenarion som innehåller variabler kopplade till teorin om ELM. Studiens resultat påvisar att potentiella investerare bedömer samt väljer investeringsprojekt utifrån den centrala vägen i ELM teorin, som karaktäriseras av projektets kvalitet vilken är motsatsen till den perifera vägen som istället belyser elektronisk word of mouth (WoM). / The study aims to investigate how equity- and debt based crowdfunding in relation to the study’s primary theory of elaboration likelihood model (ELM) and its variables effect on potential investors’ investment decision. Information asymmetry and behavioral finance has also been included in the study as two complementary theories. To investigate this, the study has been delimited to potential investors who are geographically resident in Stockholm County. The survey has been conducted using semi-structured interviews, where a total of eleven potential investors have been interviewed based on a chain sampling. The potential investors have been presented four scenarios that contain variables linked to the theory of ELM. The study's findings show that potential investors assess and choose investment projects based on the central path of ELM theory, characterized by the quality of the project and opposite to the peripheral road that instead illuminates the electronic word of mouth (WoM).
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Desenvolvimento de um algoritmo morfológico para detecção e classificação de lesões em imagens de mamografiaLIMA, Sidney Marlon Lopes de 25 February 2016 (has links)
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Previous issue date: 2016-02-25 / REUNI / O câncer de mama é a principal causa de morte de mulheres adultas por
câncer no mundo. Do ponto de vista clínico, a mamografia é ainda a mais efetiva
tecnologia de diagnóstico do câncer de mama, dada a grande difusão de uso e
interpretações dessas imagens. De acordo com o estado da arte da classificação de
lesões em mamogramas, as wavelets têm apresentado os melhores resultados do
ponto de vista da taxa de classificação, quando utilizadas como etapa de préprocessamento
que decompõe a imagem original em imagens de detalhes (verticais,
horizontais e diagonais) e aproximações para, a partir dessas imagens
componentes, serem extraídos atributos de textura. Neste trabalho, propõe-se a
Decomposição baseada em Aproximações Morfológicas em regiões de interesse em
mamogramas. O método proposto tem por base a decomposição inspirada em
wavelets que emprega filtros não lineares passa-baixas e passa-altas, baseados em
aberturas e fechamentos, que por sua vez são construídos a partir dos operadores
morfológicos clássicos de erosão e dilatação. Neste trabalho, são propostas
aproximações aritméticas para esses dois operadores morfológicos clássicos,
substituindo os desvios condicionais, presentes na Morfologia Matemática, por
operações aritméticas de somas, subtrações e multiplicações, computacionalmente
mais rápidas. O trabalho proposto compara o tempo estimado de execução entre as
aproximações aritméticas propostas e as operações morfológicas clássicas
utilizando a notação Big-Oh e também faz uso de estimativas baseadas em
arquitetura de hardware pipeline. Em todas as estimativas e cenários reais, as
aproximações morfológicas propostas são mais rápidas do que a morfologia
clássica. Além disso, por não empregar unidade de hardware em ambiente pipeline
para tratamento de desvios condicionais, as aproximações morfológicas propostas
se tornam uma solução mais barata, ocupa menos espaço, mais propícia à
miniaturização, consome menos energia e reduz o número de codificações da UC
(Unidade de Controle). Logo, as Aproximações Morfológicas criadas são superiores
à morfologia clássica nos principais requisitos para o bom funcionamento do
hardware. Quanto à classificação, a Decomposição baseada em Aproximações
Morfológicas alcança um desempenho médio de 84,65% na distinção entre casos
normais, benignos e malignos. Os classificadores empregados são redes neurais
ELM e SVM, cujas classes são definidas de acordo com os critérios da American
College of Radiology. Foram usadas 355 imagens de mama adiposa da base de
dados IRMA, com 233 casos normais, 66 benignos e 56 malignos. Como método de
tratamento da base de dados, foram estudados pesos ponderando a fronteira de
decisão das redes neurais. / According to the World Health Organization, breast cancer is the main cause of
death of women round the world. From the clinical point of view, mammography is
still the most effective diagnostic technology, given the wide diffusion of the use and
interpretation of these images. According the state-of-the-art lesions classification on
mammograms, wavelets have produced the best results from the viewpoint of
precision, when used as a preprocessing step that decomposes the original image
into approximation and detail images (vertical, horizontal and diagonal) in order to,
from these components images, extract shape or texture attributes. This work
proposes the decomposition Morphological-based in regions of interest on
mammograms. The proposed method is inspired on wavelets decomposition
employing nonlinear low-pass and high-pass filters, based on openings and closings,
which are constructed from classical morphological operators of erosion and dilation.
In this work, we propose approaches of classical morphology, replacing the
conditional branches, present in Mathematical Morphology, by arithmetic operations
of addition, subtraction and multiplication, computationally faster. The proposed work
compares the estimated run time of proposed arithmetic approximations and classical
morphological operations using Big-Oh notation and also the thesis uses notation
based on pipeline hardware architecture. In all real scenarios, our morphological
operations are faster than classical morphology. Also, by not employing hardware
unit in pipeline environment for treating conditional branches, the proposed
morphology approximation becomes a cheaper solution, occupies less space, more
propitious to miniaturization, consumes less power, and reduces the Control Unit
coding number. Then, our approaches of classical morphology are superior to
classical morphology in key requirements of hardware solution. Regarding the
classification, the proposed decomposition reaches an average performance of
84.65% in distinguishing normal, benign, and malignant cases. Classifiers are neural
networks ELM and SVM, classes are defined according American College of
Radiology criteria. They are employed 355 adipose breast images with 233 normal
cases, 66 benign and 56 malignant. As database processing method, weights were
studied considering the decision boundary of neural networks.
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