A Chain-Based Wireless Sensor Network Model Using the Douglas-Peucker Algorithm in the Iot Environment

WSNs which are the major component in the IoT mainly use interconnected intelligent wireless sensors. These wireless sensors sense monitor and gather data from their surroundings and then deliver them to users or access connected IoT devices remotely. One of the main issues in WSNs is that sensor nodes are generally powered by batteries, but because of the rugged environments, it is difficult to add energy. The other one may cause an unbalanced energy consumption among sensor nodes due to the uneven distribution of sensors. For these reasons, the death of nodes by the energy exhausting and the performance of the network may rapidly decrease. Hence, an efficient algorithm study for prolonging the network lifetime of WSNs is one of important challenges. In this paper, a chain-based wireless sensor network model is proposed to improve network performance with balanced energy consumption via the solution of the long-distance communication problem. The proposed algorithm is consisted of three phases: Segmentation, Chain Formation, and Data Collection. In segmentation phase, an optimal distance tolerance is determined, and then the network field is divided into small sub-regions according to its value. The chain formation is started from the sub-region far away from the sink, and then extended, and sensed data are collected along a chain and transmitted to a sink. Simulations have been performed to compare with PEGASIS and Enhanced PEGASIS using an OMNET++ simulator. The simulation results from this study showed that the proposed algorithm prolonged the network lifetime via the achievement of the balanced energy consumption compared to PEGASIS and Enhanced PEGASIS. The proposed algorithm can be used in any applications to improve network performance of WSNs

Whom Do You Want to Be Friends With: An Extroverted or an Introverted Avatar? Impacts of the Uncanny Valley Effect and Conversational Cues

With the rapid growth of social virtual reality platforms, an increasing number of people will be interacting with others as avatars in virtual environments. Therefore, it is essential to develop a better understanding of the factors that could impact initial personality assessments and how they affect the willingness of people to befriend one another. Thin-slice judgment constitutes a quick judgment of a personality based on an avatar, and it could be impacted by the avatar’s appearance, particularly if the avatar elicits an uncanny valley effect that brings negative emotions such as eerieness. However, personality judgments and friendship decisions could also be influenced by social cues, such as conversational style. This experimental study investigated how these factors impact willingness to make friends with others in a virtual world. Drawing upon the uncanny valley effect and thin-slice judgment, this study examined how different levels of realism and conversational cues influence trustworthiness, likeability, and the willingness to be a friend. Furthermore, the current study tried to shed light on the interaction effects of realism and conversational cues to the dependent variables. In other words, this study investigated how this eventually influences one’s willingness to be a friend under the thin-slice judgment when personality judgments result from the negative feeling (i.e., eeriness) of the uncanny valley effect and social cues are conflicted. To this end, a 2 (realism: cartoonish vs. hyper-realistic) x 2 (conversational cues: extroverted vs. introverted) between-subjects online experiment was conducted. The results showed that trustworthiness and likeability significantly impacted the willingness to be a friend. Furthermore, realism and conversational cues marginally affected the willingness to be a friend. Keywords: uncanny valley effect, thin-slice judgment, avatar, personality judgment, willingness to be a frien

How do People Process and Share Fake News on Social Media?: In the context of Dual-Process of Credibility with Partisanship, Cognitive Appraisal to Threat, and Corrective Action

The objective of this study is to examine how the information processing of news users happens on social media in the context of spreading fake news. This study is intended to shed light on how fake news spreads on social media with the effects of two moderators (i.e., partisanship and source credibility) from political attitude consistency to message credibility and the effect of mediation (i.e., cognitive appraisal to threat) from message credibility to intent to share fake news on social media and corrective action. As a theoretical lens, dual-process theories were adopted in this paper. For this, a 2 (news topic: Immigration vs. Gun control) X 2 (news topic stance: Positive vs. Negative) X 2 (source: major (i.e., Associated Press) vs. minor (i.e., blog news) between-subject online experiment with 507 participants was conducted for both immigration and gun control topics. As a result, in the moderation effects, although partisanship was significant for both topic immigration and gun control news, source credibility was significant only for immigration news. Plus, the mediation effect of the cognitive appraisal to threats was significant between message credibility and the intent to share fake news on social media for both news topics. Lastly, even though the relations between message credibility and corrective action had to be negatively associated, they were positively correlated

Comparison of New Business Entities between the United States and United Kingdom: Are U.S. LLC and U.K. LLP really useful alternatives?

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Unbalanced contrast

The purpose of this project was to create a unique ready-to-wear style for professional working women. I desired to make a two-piece jacket and skirt reinventing the tartan kilt as a new key design element for women’s ready-to-wear that could be appealing to various professional working women regardless of age and race. Principles of design such as harmony, balance, proportion, emphasis, similarity, and contrast have been incorporated in an unconventional way. Various sizes of knife pleats were created using the tartan fabric and partially attached to the collar, sleeve, and bodies of the jacket, skirt, and pocket flap. This outfit features strong contrasts by mixing colors and patterns in addition to asymmetrically dominated lines and curves for the beauty of unbalance. Unbalanced contrast made out of cotton contributes to the mass market by offering professional working women positive aspects of clothing attributes such as comfort, washability, durability, affordability, and high fashion

U.S Audiences' Perceptions of Covid-19 and Conservative News Frames

During the early stages of the COVID-19 pandemic, U.S. conservative news downplayed the threat of the virus. Perceived risks of COVID-19 are an important factor in influencing citizens' willingness to comply with risk prevention measures. An online survey (N=269) of U.S. residents was conducted March 30 - April 1, 2020. We found that those who used partisan conservative news sources as their primary source of information about the virus were significantly less likely to view it as a threat, compared to those who cited Far Left, Center Left, and Center Right news sources. Politically conservative Far Right news audiences reported significantly lower estimates of their own COVID-19 risk, as well as that of their age group peers, the average person in the U.S., and the average senior citizen in the U.S