Visuals misleading consumers? Testing the visual superiority effect in advertising

Purpose The purpose of this study is to test the visual superiority effect in a verisimilar scenario that an industry association seeks to manipulate consumers using a visual element in its ad while providing an ostensibly balanced claim about the potential health effects of stevia. Design/methodology/approach Two experiments were conducted. In Study 1, an online experiment was conducted with a sample of 112 adult consumers using a two-group (headline frame type: gain vs loss), post-test only design with additional planned analysis of an individual difference (i.e. regulatory focus). In Study 2, another online experiment was implemented with a sample of 175 adults using a 2 (headline frame type: gain vs loss) × 2 (image valence: positive vs negative) between-subjects design with additional planned analysis of regulatory focus. The hypotheses were tested by running the PROCESS macro on SPSS. Findings The results showed that when exposed to the advertising message designed to elicit uncertainty, participants relied more on the visual than the textual content (i.e. framed headline and body text) in forming attitude toward the behavior (i.e. consuming stevia). Analysis of cognitive responses also revealed that those who received the stimulus ad with an image added (Study 2) generated significantly fewer thoughts related to the textual content of the ad than those who received the ad with no image (Study 1). Originality/value This study represents one of the earliest experimental inquiries into the visual superiority effect in an advertising context. While earlier studies have tended to rely on dual-processing models to test the effects of advertising stimuli featuring both textual and visual elements, the findings of this study (e.g. visual content overwhelmed its textual counterpart in producing persuasive effects) somewhat contradict the premise of dual-processing models.

The transfer of stylised artistic images in eye movement experiments based on fuzzy differential equations

In many aspects of people's production and life, artistic images have been widely used. Because the image has the function of transmitting information, it can provide necessary space environment information for people. However, there are many problems in the design of stylised art images, and hence the usability of images is affected. Due to its unique advantages, the study of artistic eye movement has gradually become a research hotspot. The fuzzy differential equation is an important branch of differential equation theory, which can be used to study eye movement experiments in the field of the art research. In the process of observation, experiment and maintenance, errors cannot be avoided, and the variables and parameters obtained are often fuzzy, incomplete and inaccurate. And fuzzy differential equations can deal with these uncertainties well. At first, this paper studies the migration-image-study-related theory and art image, based on the study of an artistic image that can be divided into instructions image and symbol and image, with the help of eye movement experiment method to investigate the effects of two types of image on people read mechanism. This research mainly uses the fuzzy differential equation for the visual search experimental paradigm to identify the influence of the difference of the effect.

A Mirror-image Analysis of Psychiatric Hospitalisations among People with Serious Mental Illness using Independent Supported Housing

PurposeEvidence on the effectiveness of Independent Supported Housing (ISH) for non-homeless people with mental illness primarily comes from observational cohort studies, which have high risk of bias due to confounding by time-invariant sample characteristics. The present study proposes an alternative study design known from pharmacology to overcome this bias and strengthen evidence. MethodsWe conducted a retrospective mirror-image analysis with medical records of 144 ISH service users to assess the effectiveness of ISH in reducing the number and duration of hospitalisations. Outcomes occurring in equal periods before and during ISH utilisation were compared for every ISH user. Differences between the periods were tested with incidence rate ratios (IRR). ResultsIncluded service users were on average 38.2 years old, female (54%) and predominately had an affective (28.5%) or a schizophrenic or psychotic (22.9%) disorder with ISH utilisation days ranging from 36-960. Fewer admissions (IRR=0.41, 95%-CI 0.27-0.64) and fewer person-days hospitalised (IRR=0.38, 95%-CI 0.35-0.41) were observed during utilisation period compared to prior to their ISH utilisation. While the reduction in psychiatric admissions may be somewhat confounded by time-variant characteristics, the substantial reduction in hospitalised bed-bays represents at least partially an intervention effect. ConclusionsThe mirror-image study design allowed for a cost-effective investigation of ISH effectiveness in reducing hospitalisation without confounding by time-invariant sample characteristics. We provide recommendations for the design’s application and suggest further research with larger samples.

The Influence of Suandei Fall on Art of Carving Artists in Woinap Village, Yapen Island District

The art of carving, known as carving, or decoration with various flora, fauna, figurative and even geometric motifs which is an ornate image with some parts being concave and some parts convex both horizontally and vertically and elliptically arranged in a very beautiful image. (Study of Cultural Anthropology)(1) The carvings, which are known in the works of Decorative Arts, still survive and are in demand and are found in various areas such as the Biak Numfor Islands, Yapen Islands, Waropen Wondama Bay and various other areas that are included in the Kuripasai cultural family, Mananarmakeri, and Sairei. A special highlight in this writing is the carving motifs that are still practiced by carving craftsmen in Woinap Village, Wonawa District, Yapen Islands Regency, where until now there are very few carvers. This carving motif was inspired by the legend of "Suandei" by Drs. Frits Maurid Kirihio, alumni of the University of Leyden, the Netherlands, in the 1950s, who was recorded in the book “Dongen Tanah Kita,(2) Descriptive analysis method is a method used to analyze data by describing or describing the data that has been collected as it is without intending to make conclusions that apply to generalization or generalization, Sugiyono (2014:21)(3) Excellence Carving motifs based on beliefs that have been practiced so far in the village of Woinap, Yapen Islands Regency. or skulls, all of which are manifested and the decorations that are usually displayed on family tools such as boats, wooden pans (sempe) art tools (tifa) net buoys, all take symbolic or philosophical meanings from their original form.(4) The indigenous people of Woinap are a community categorized as living in the outermost area of ​​the Yap . Islands Regency en and still isolated from the rapid development of the era. However, it cannot be separated from local wisdom techniques that are often adopted from neighboring areas which are more innovative in people's lifestyles because culture is dynamic and always moves with the times, so the people of Woinap also move with the habit of living with the times by way of -a new way that is still considered cultural even though indigenous cultural values ​​have been eroded.(5) The cultural heritage of the Papuan people in the saireri strait region, especially the unique carving art of the Woinap community, has an economic potential that can bring ecotourism and increase the PAD of the Islands district government Yapen.(6)

A Deep Recurrent Neural Network with Gated Momentum Unit for CT Image Reconstruction

<div><div><div><p>Many algorithms and methods have been proposed for Computed Tomography (CT) image reconstruction, partic- ularly with the recent surge of interest in machine learning and deep learning methods. The majority of recently proposed methods are, however, limited to the image domain processing where deep learning is used to learn the mapping from a noisy image data set to a true image data set. While deep learning-based methods can produce higher quality images than conventional model-based post-processing algorithms, these methods have lim- itations. Deep learning-based methods used in the image domain are not sufficient for compensating for lost information during a forward and a backward projection in CT image reconstruction especially with a presence of high noise. In this paper, we propose a new Recurrent Neural Network (RNN) architecture for CT image reconstruction. We propose the Gated Momentum Unit (GMU) that has been extended from the Gated Recurrent Unit (GRU) but it is specifically designed for image processing inverse problems. This new RNN cell performs an iterative optimization with an accelerated convergence. The GMU has a few gates to regulate information flow where the gates decide to keep important long-term information and discard insignificant short- term detail. Besides, the GMU has a likelihood term and a prior term analogous to the Iterative Reconstruction (IR). This helps ensure estimated images are consistent with observation data while the prior term makes sure the likelihood term does not overfit each individual observation data. We conducted a synthetic image study along with a real CT image study to demonstrate this proposed method achieved the highest level of Peak Signal to Noise Ratio (PSNR) and Structure Similarity (SSIM). Also, we showed this algorithm converged faster than other well-known methods.</p></div></div></div>

A Deep Recurrent Neural Network with Gated Momentum Unit for CT Image Reconstruction

<div><div><div><p>Many algorithms and methods have been proposed for Computed Tomography (CT) image reconstruction, partic- ularly with the recent surge of interest in machine learning and deep learning methods. The majority of recently proposed methods are, however, limited to the image domain processing where deep learning is used to learn the mapping from a noisy image data set to a true image data set. While deep learning-based methods can produce higher quality images than conventional model-based post-processing algorithms, these methods have lim- itations. Deep learning-based methods used in the image domain are not sufficient for compensating for lost information during a forward and a backward projection in CT image reconstruction especially with a presence of high noise. In this paper, we propose a new Recurrent Neural Network (RNN) architecture for CT image reconstruction. We propose the Gated Momentum Unit (GMU) that has been extended from the Gated Recurrent Unit (GRU) but it is specifically designed for image processing inverse problems. This new RNN cell performs an iterative optimization with an accelerated convergence. The GMU has a few gates to regulate information flow where the gates decide to keep important long-term information and discard insignificant short- term detail. Besides, the GMU has a likelihood term and a prior term analogous to the Iterative Reconstruction (IR). This helps ensure estimated images are consistent with observation data while the prior term makes sure the likelihood term does not overfit each individual observation data. We conducted a synthetic image study along with a real CT image study to demonstrate this proposed method achieved the highest level of Peak Signal to Noise Ratio (PSNR) and Structure Similarity (SSIM). Also, we showed this algorithm converged faster than other well-known methods.</p></div></div></div>

Analysis of IKM Perceptions on The Role of Events to Moderate the Influence of Product Quality and Product Value on Brand Image (Study on Denpasar Festival)

The development of the Creative Economy sector in collaboration with the IKM Sector to maintain local culture so it continues to grow and be sustainable. The development of IKM creativity is facilitated by the Denpasar City Government through the Denpasar Festival which is expected to be able to build an ecosystem, brand image and creative economy networking. For this reason, event implementation as one of the promotional media, so that the IKM brand image can be known by the wider community, both domestically and abroad. The purpose of this study is to examine and analyze the effect of product quality and product value on the brand image of IKM and moderated by the event. Respondents in this study were IKM who participated in the Denpasar Festival event for 3 consecutive years (2017 to 2019). The number of respondents used was 154 IKM using a sampling technique called Proportionate Stratified Random Sampling. This research used SEM analysis with SmartPLS 3.0 program. The results showed that product quality has a positive and significant effect on brand image, product value has no effect on brand image, events can moderate the effect of product quality on brand image, and events are not able to moderate the effect of product value on brand image.