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Important Horsemanship Skills to be Taught in College Curricula
No full textMany colleges offer equine programs through their agricultural science programs. During their time in these programs, equine science students should gain working and technical knowledge to excel in their careers within the equine industry. This includes experiential learning classes on how to ride and handle horses. The purpose of this study is to identify what skills AQHA and APHA listed professional horsemen define as important basic horsemanship skills. This study uses a modified Delphi approach to identify these skills. By the second round 18 skills were identified as basic horsemanship skills. In the third round these skills were categorized and ranked in importance within horsemanship or stewardship skills
COVID-19, Price of Silver and Corporate Performance: An Analysis of Four Leading Corporations
No full textA Light in Students’ Lives: K-12 Teachers’ Experiences (Re)Building Caring Relationships During Remote Learning
No full textThis study illuminates the experiences of K-12 educators as they strove to (re)build caring relationships with students during the COVID-19 pandemic. The study was conducted during a graduate course for experienced K-12 teachers in the spring of 2020 at a four-year comprehensive university in the United States. Data was collected from reflective learning journals and asynchronous peer discussions, which captured educators’ experiences as they transitioned to remote learning in real-time. Qualitative content analysis was used to identify pertinent themes. Findings suggest that remote learning revealed relationships in need of repair. Educators practiced authentic care and cultivated connectedness by (a) acting as warm demanders, (b) responding to students’ social-emotional needs, and (c) trying to bridge the digital divide. The article concludes with implications for practice and areas for future research as schools, districts, states, and countries consider the “new normal” in K-12 schooling
The Effectiveness of the Use of the Big Five Personality and Gottman’s Seven Principles for Making Marriage Work on Couples’ Relationship Satisfaction
No full textResearch shows that couples who are satisfied with their relationship are better able to understand, honor, and respect each other and their marriage while many unhappy couples may experience psychological difficulties. Individuals have unique personalities, and these patterns of behavior impacts their relationships. Because individuals frequently lack tools to understand themselves and improve their communication skills couples are increasingly faced with problems in their relationship.The Big Five Personality Test is an inventory that can be used to increase partners awareness of each other’s personality traits. The Dyadic Adjustment Scale (DAS) measures couple’s relationship satisfaction. The Gottman Seven Principles for Making Marriage Work is an approach to develop couples’ communication skills. In this experimental study, the DAS was administered to 60 couples to get a measure on their relationship satisfaction. All couples took the Big Five Personality Test, and they were informed of their personality traits. In the next step, DAS was administered to 60 couples for the second time. Then participants were randomly assigned into two experimental (30 couple) and control (30 couple) groups. The experimental group received three group educational intervention via Zoom Webinar on the Gottman Seven Principles for Making Marriage Work. DAS administrated for the third time. The results were analyzed. Across all participants, DAS scores improved over the three administrations of the procedure (M1 = 75.64, M2 = 90.14, M3 = 100.33), F (1.89, 232) = 590.242, p \u3c .001, partial eta squared = 0.84). The interaction between DAS sequence and treatment group was significant, F (1.89,118) = 100.42, p \u3c.001. By contrast, on the second DAS administration (experimental M = 86.26 and control M = 94.01). F (1,118) = 17.85, p, = .001. By the time of the third DAS administration (experimental M = 100.32, while the control M = 94.15
Methods of Neural Network Analysis to Identify Weapons in Augmented Reality
No full textAugmented reality (AR) is a technology being utilized to help give an individual insightwhile doing their job by overlaying information on the real world in real-time. The military is working on using AR to help soldiers on the battlefield to make more informed decisions. The battlefield is a dynamic environment and requires real-time, clear, and effective ways of getting information to the soldier. Convolutional Neural Networks (CNN) are used in this study to classify images of weapons in videos. The YouTube8M video dataset was explored and another hand-picked image dataset was created based on image content and then used in training three ImageNet pre-trained models, Xception, ResNet50, and MobileNet using transfer learning. The effectiveness of this dataset and models were evaluated for speed and accuracy. We found that ResNet50 was more accurate but slightly slower than MobileNet. The Xception pre-trained base was overfitting even though it performed well on the test data. Further research is discussed
Anion Recognition Properties of Chiral Porphyrin Atropisomers
No full textThis project centered on the synthesis and study of multiple synthetic porphyrin-based hosts for recognition of anions and amines that could aid in sensor development for chiral compounds, chiral separations or the determination of enantiomeric excess of chiral mixtures. The porphyrin host compounds have an axis of chirality and thus exist as atropisomers. One aspect of the project is the synthesis of a porphyrin host that can function as a chiral molecular switch. The key aspect of the project is centered around the synthesis of a chiral porphyrin host consisting of a monoamino-tetraphenyl porphyrin scaffold with an arm containing an axis of chirality substituted on one of the four meso aryl groups. This design should position the chiral arm directly over the metal core creating a binding pocket for induced fit binding of target guests. The axial chirality of the host compounds stems from modification of an indole-phenyl core with various groups that will increase the rotational barrier around the indole-phenyl bond. Some of the host derivatives could thus contain a mechanism for a switching stimuli to respond to the 3-dimensional structure of a guest molecule. Depending on the absolute stereochemistry of the guest, the host could exist in one of two atropisomeric forms. A computational study has also been conducted to study the effects of the addition of substituents at various locations on the indole-phenyl arm for the determination of the effect on the rotational barrier; the systems studied computationally are model compounds for the host compounds discussed here
The Effect of Distinctive Internal versus External Facial Features on Eyewitness Identification
No full textPerpetrators of a crime can have distinctive features on the internal or external region of their face. The purpose of this study was to compare the effects of internal versus external distinctive features on eyewitness identification. I also compared these effects with two timed conditions of encoding, a 2 and 6 second condition, in order to investigate relatively short encoding times that mimic real world conditions. Finally, I tested two methods that police could utilize to deal with a distinctive feature: replicating it among all lineup members or removing it entirely. I found that an encoding time of 6 seconds resulted in better discriminability than 2 seconds and that a distinctive feature located on the internal region of the face reduced discriminability compared to the external region of their face. I found little difference between replication and removal of distinctive features across lineup members, although replication marginally improved discriminability over removal. Finally, I found a strong confidence-accuracy relationship across all conditions, suggesting that high eyewitness confidence in their lineup selection is indicative of accuracy in their choice of lineup member
The Portrayal of Abused Characters in Adolescent Novels: A Content Analysis
No full textThis content analysis used a critical lens to analyze the portrayal of characters victimized by abuse in adolescent literature. Child abuse is an issue prevalent around the globe (Berkowitz, 2017). The study analyzed ten adolescent novels published over a period of sixteen years to determine character traits and themes. The analysis was conducted to provide information on how literature portrayed victims. The researcher identified aspects of authenticity and explored methods empowering characters to overcome to promote strength, empathy, acknowledgment, and advocacy.The overarching questions guiding the study included: What adolescent literature for grades 6-12 is available from 1999 to 2015 portraying characters victimized by physical and sexual abuse during their youth? This question was answered by researching novels meeting the criteria for the study and organizing them in a chart. What methods or support systems do characters utilize to overcome or cope with the effects of abuse? What are the underlying themes? Do the texts depict realistic interpretations? How are these interpretations developed? These questions were answered using a questionnaire (Rudman, 1995), Power Continuum questions (Botelho & Rudman, 2009), and across-text comparisons. The theoretical framework included various theories but was based on Critical Literacy (Foucault, 1972). Foucault found that readers utilized background experiences to connect with and gain better understandings of pertinent issues related to the world around them. Reading about abuse, promotes social awareness and justice leading to social transformation (Freire, 2000). The findings were significant, providing evidence of authenticity, potential to help bring about change, and offering support to adolescents affected by abuse
A Method of Autonomous Vehicle Path Planning Through Constrained Artificial Bee Colony Optimization
No full textFor vehicle routing, the ability to optimize path planning and travel time, allows an or-ganization to reduce time and money to deliver cargo. This is particularly important for vehicles such as ambulances, where the fastest path to the hospital can save lives. The progress of artificial intelligence has shown remarkable results to the application of vehicle lane change optimization, as well as showing applicability for autonomous vehicles. Currently, systems for autonomous driving are mainly focused on staying in one lane, and following a set rate of speed to reduce the amount of uncertainty of the systems against human driver behaviors. However, upon a change of information, for example, debris upon a roadway, a vehicle will have to modify its planned path to best fit this change of data, while also maintaining a buffer of safety for the surrounding vehicles. Due to the time constraints for decision-making, this paper explores a method of heuristically searching for a safer path through the Artificial Bee Colony Algorithm, while also applying Constraint Satisfaction techniques to optimize its search space relative to the vehicles current position. Keywords: Artificial Bee Colony Algorithm, Path Planning, Constraint Satisfaction, Constraint Programming
The Automatic Multi-Class Classification of Hate Speech on Twitter
No full textThe spread of hate speech on social media is becoming a significant concern. To address this concern, various scholars from diverse disciplines such as sociology, legal studies and computer science have attempted to define, analyze and detect hate speech. However, hate speech has not been adequately addressed and analyzed as a sociolinguistic phenomenon. Therefore, the aim of this study is to shed more light on understanding hate speech as a sociolinguistic concept. To achieve this goal, three main phases have been performed. First, the study incorporates the theory of speech acts along with the existing academic and non-academic definitions of hate speech along to propose a more comprehensive definition. Using the new definition, the study proposed a fine-grained taxonomy of hate speech. In addition, the study proposed the main components of hate speech which can distinguish this concept from the general profanity. In the next phase, two hate speech datasets are created and an annotation scheme was developed based on the proposed taxonomy. Finally, using the annotated hate speech dataset, several multi-class, multi-label classification of hate speech are conducted to investigate the impact of the new annotation framework