Search results for: Angelina Tarabokija
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10

Search results for: Angelina Tarabokija

10 Cognitive Behavioral Training to Enhance Performance And Well-Being in Collegiate Athletes

Authors: Angelina Tarabokija

Abstract:

This study looks into how cognitive behavioral training (CBT) techniques affect collegiate track and field athletes' anxiety related to performance, with a focus on distance runners. The goal of the research is to discover whether consistent use of cognitive behavioral therapy (CBT) methods, such as progressive muscle relaxation, yoga (Y-CBT), visualization, relaxed breathing, and meditation, can reduce performance anxiety and improve sports performance. Six runners from the Rider Track & Field team, aged eighteen to twenty-three, participated in the quantitative research design used in the technique. Prior to employing CBT techniques every day for two weeks, including before competitions or on race day, participants conducted baseline assessments using the Sport Anxiety Scale-2 (SAS-2). The SAS-2 was used in post-competition evaluations to track alterations in performance anxiety. The findings show that participants' total trait anxiety levels significantly decreased after utilizing CBT techniques for one week. However, after two weeks, a few participants' anxiety levels slightly increased, pointing to the need for more research and regular practice. The study indicates that CBT approaches can effectively reduce performance anxiety and increase athletic performance in collegiate track and field athletes, despite constraints related to participant motivation and potential confounding variables. Future areas for research could entail examining the precise impacts of worry, interruption of attention, and bodily anxiety on performance, as well as adding more controls. Overall, by providing insights into evidence-based strategies to maximize mental states and athletic performance in collegiate athletes, this study advances the area of sports psychology.

Keywords: cognitive behavioral training, performance, athletes, anxiety, well-being, SAS-2, Sport, trait anxiety, somatic anxiety

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9 Nonlinear Finite Element Analysis of Optimally Designed Steel Angelina™ Beams

Authors: Ferhat Erdal, Osman Tunca, Serkan Tas, Serdar Carbas

Abstract:

Web-expanded steel beams provide an easy and economical solution for the systems having longer structural members. The main goal of manufacturing these beams is to increase the moment of inertia and section modulus, which results in greater strength and rigidity. Until recently, there were two common types of open web-expanded beams: with hexagonal openings, also called castellated beams, and beams with circular openings referred to as cellular beams, until the generation of sinusoidal web-expanded beams. In the present research, the optimum design of a new generation beams, namely sinusoidal web-expanded beams, will be carried out and the design results will be compared with castellated and cellular beam solutions. Thanks to a reduced fabrication process and substantial material savings, the web-expanded beam with sinusoidal holes (Angelina™ Beam) meets the economic requirements of steel design problems while ensuring optimum safety. The objective of this research is to carry out non-linear finite element analysis (FEA) of the web-expanded beam with sinusoidal holes. The FE method has been used to predict their entire response to increasing values of external loading until they lose their load carrying capacity. FE model of each specimen that is utilized in the experimental studies is carried out. These models are used to simulate the experimental work to verify of test results and to investigate the non-linear behavior of failure modes such as web-post buckling, shear buckling and vierendeel bending of beams.

Keywords: steel structures, web-expanded beams, angelina beam, optimum design, failure modes, finite element analysis

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8 Feature Selection for Production Schedule Optimization in Transition Mines

Authors: Angelina Anani, Ignacio Ortiz Flores, Haitao Li

Abstract:

The use of underground mining methods have increased significantly over the past decades. This increase has also been spared on by several mines transitioning from surface to underground mining. However, determining the transition depth can be a challenging task, especially when coupled with production schedule optimization. Several researchers have simplified the problem by excluding operational features relevant to production schedule optimization. Our research objective is to investigate the extent to which operational features of transition mines accounted for affect the optimal production schedule. We also provide a framework for factors to consider in production schedule optimization for transition mines. An integrated mixed-integer linear programming (MILP) model is developed that maximizes the NPV as a function of production schedule and transition depth. A case study is performed to validate the model, with a comparative sensitivity analysis to obtain operational insights.

Keywords: underground mining, transition mines, mixed-integer linear programming, production schedule

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7 Emotion Classification Using Recurrent Neural Network and Scalable Pattern Mining

Authors: Jaishree Ranganathan, MuthuPriya Shanmugakani Velsamy, Shamika Kulkarni, Angelina Tzacheva

Abstract:

Emotions play an important role in everyday life. An-alyzing these emotions or feelings from social media platforms like Twitter, Facebook, blogs, and forums based on user comments and reviews plays an important role in various factors. Some of them include brand monitoring, marketing strategies, reputation, and competitor analysis. The opinions or sentiments mined from such data helps understand the current state of the user. It does not directly provide intuitive insights on what actions to be taken to benefit the end user or business. Actionable Pattern Mining method provides suggestions or actionable recommendations on what changes or actions need to be taken in order to benefit the end user. In this paper, we propose automatic classification of emotions in Twitter data using Recurrent Neural Network - Gated Recurrent Unit. We achieve training accuracy of 87.58% and validation accuracy of 86.16%. Also, we extract action rules with respect to the user emotion that helps to provide actionable suggestion.

Keywords: emotion mining, twitter, recurrent neural network, gated recurrent unit, actionable pattern mining

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6 Emotion Mining and Attribute Selection for Actionable Recommendations to Improve Customer Satisfaction

Authors: Jaishree Ranganathan, Poonam Rajurkar, Angelina A. Tzacheva, Zbigniew W. Ras

Abstract:

In today’s world, business often depends on the customer feedback and reviews. Sentiment analysis helps identify and extract information about the sentiment or emotion of the of the topic or document. Attribute selection is a challenging problem, especially with large datasets in actionable pattern mining algorithms. Action Rule Mining is one of the methods to discover actionable patterns from data. Action Rules are rules that help describe specific actions to be made in the form of conditions that help achieve the desired outcome. The rules help to change from any undesirable or negative state to a more desirable or positive state. In this paper, we present a Lexicon based weighted scheme approach to identify emotions from customer feedback data in the area of manufacturing business. Also, we use Rough sets and explore the attribute selection method for large scale datasets. Then we apply Actionable pattern mining to extract possible emotion change recommendations. This kind of recommendations help business analyst to improve their customer service which leads to customer satisfaction and increase sales revenue.

Keywords: actionable pattern discovery, attribute selection, business data, data mining, emotion

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5 Modeling of Gas Extraction from a Partially Gas-Saturated Porous Gas Hydrate Reservoir with Respect to Thermal Interactions with Surrounding Rocks

Authors: Angelina Chiglintseva, Vladislav Shagapov

Abstract:

We know from the geological data that quite sufficient gas reserves are concentrated in hydrates that occur on the Earth and on the ocean floor. Therefore, the development of these sources of energy and the storage of large reserves of gas hydrates is an acute global problem. An advanced technology for utilizing gas is to store it in a gas-hydrate state. Under natural conditions, storage facilities can be established, e.g., in underground reservoirs, where quite large volumes of gas can be conserved compared with reservoirs of pure gas. An analysis of the available experimental data of the kinetics and the mechanism of the gas-hydrate formation process shows the self-conservation effect that allows gas to be stored at negative temperatures and low values of pressures of up to several atmospheres. A theoretical model has been constructed for the gas-hydrate reservoir that represents a unique natural chemical reactor, and the principal possibility of the full extraction of gas from a hydrate due to the thermal reserves of the reservoirs themselves and the surrounding rocks has been analyzed. The influence exerted on the evolution of a gas hydrate reservoir by the reservoir thicknesses and the parameters that determine its initial state (a temperature, pressure, hydrate saturation) has been studied. It has been established that the shortest time of exploitation required by the reservoirs with a thickness of a few meters for the total hydrate decomposition is recorded in the cyclic regime when gas extraction alternated with the subsequent conservation of the gas hydrate deposit. The study was performed by a grant from the Russian Science Foundation (project No.15-11-20022).

Keywords: conservation, equilibrium state, gas hydrate reservoir, rocks

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4 Pattern Discovery from Student Feedback: Identifying Factors to Improve Student Emotions in Learning

Authors: Angelina A. Tzacheva, Jaishree Ranganathan

Abstract:

Interest in (STEM) Science Technology Engineering Mathematics education especially Computer Science education has seen a drastic increase across the country. This fuels effort towards recruiting and admitting a diverse population of students. Thus the changing conditions in terms of the student population, diversity and the expected teaching and learning outcomes give the platform for use of Innovative Teaching models and technologies. It is necessary that these methods adapted should also concentrate on raising quality of such innovations and have positive impact on student learning. Light-Weight Team is an Active Learning Pedagogy, which is considered to be low-stake activity and has very little or no direct impact on student grades. Emotion plays a major role in student’s motivation to learning. In this work we use the student feedback data with emotion classification using surveys at a public research institution in the United States. We use Actionable Pattern Discovery method for this purpose. Actionable patterns are patterns that provide suggestions in the form of rules to help the user achieve better outcomes. The proposed method provides meaningful insight in terms of changes that can be incorporated in the Light-Weight team activities, resources utilized in the course. The results suggest how to enhance student emotions to a more positive state, in particular focuses on the emotions ‘Trust’ and ‘Joy’.

Keywords: actionable pattern discovery, education, emotion, data mining

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3 Determination of the Stability of Haloperidol Tablets and Phenytoin Capsules Stored in the Inpatient Dispensary System (Swisslog) by the Respective HPLC and Raman Spectroscopy Assay

Authors: Carol Yue-En Ong, Angelina Hui-Min Tan, Quan Liu, Paul Chi-Lui Ho

Abstract:

A public general hospital in Singapore has recently implemented an automated unit-dose machine in their inpatient dispensary, Swisslog, with the objective of reducing human error and improving patient safety. However, a concern in stability arises as tablets are removed from their original packaging (bottled loose tablets/capsules) and are repackaged into individual, clear plastic wrappers as unit doses in the system. Drugs that are light-sensitive and hygroscopic would be more susceptible to degradation as the wrapper does not offer full protection. Hence, this study was carried out to study the stability of haloperidol tablets and phenytoin capsules that are light-sensitive and hygroscopic respectively. Validated HPLC-UV assays were first established for quantification of these two compounds. The medications involved were put in the Swisslog and sampled every week for one month. The collected data was analysed and showed no degradation over time. This study also explored an alternative approach for drug stability determination-Raman spectroscopy. The advantage of Raman spectroscopy is its high time efficiency and non-destructive nature. The results suggest that drug degradation can indeed be detected using Raman microscopy, but further research is needed to establish this approach for quantification or qualification of compounds. NanoRam®, a portable Raman spectrocope was also used alongside Raman microscopy but was unsuccessful in detecting degradation in this study.

Keywords: drug stability, haloperidol, HPLC, phenytoin, raman spectroscopy, Swisslog

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2 Transformational Leadership Style of Principal and Conflict Management in Public Secondary Schools in North Central Nigeria

Authors: Odeh Regina Comfort, Angelina Okewu Ogwuche

Abstract:

The study investigated transformational leadership style of principal and conflict management in secondary schools in North Central Nigeria. A descriptive survey design was adopted. The population of the study comprised 34,473 teachers in 1949 public secondary schools in the study area. Proportionate stratified random sampling and simple random sampling techniques were used to select 39 public secondary schools and 689 respondents, respectively, for the study. The researcher utilized a self-structured questionnaire titled 'Influence of Transformational Leadership Style Questionnaire (ITLSQ)'. Face and content validity were ensured. The reliability index of 0.86 was obtained through Cronbach alpha statistics. The instrument was a modified Likert rating scale of Very High Extent (4), High Extent (3), Low Extent (2) and Very Low Extent (1). Mean, and standard deviation were used to answer 2 research questions, while chi-square goodness of fit was used to test the 2 hypotheses at 0.05 level of significance. The results among others indicate: that intellectual stimulation and individualized components of transformational leadership style of principal in public secondary schools in the study area have significant influence on conflict management in secondary schools. Based on the results, it was recommended that principals of secondary schools should be encouraged to practice the intellectual stimulation component of transformational leadership style that would help to consider teachers' levels of knowledge to decide what suits them to reach high levels of attainment thereby minimizing conflict in school settings; also transformational leadership should be taught to all people at all levels of secondary school especially that which pertains to individualized consideration to have a positive impact on the overall performance of teachers and this would help to minimize conflict in schools.

Keywords: conflict management, individualized consideration, intellectual stimulation, transformational leadership style

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1 Structure-Reactivity Relationship of Some Rhᴵᴵᴵ and Osᴵᴵᴵ Complexes with N-Inert Ligands in Ionic Liquids

Authors: Jovana Bogojeski, Dusan Cocic, Nenad Jankovic, Angelina Petrovic

Abstract:

Kinetically-inert transition metal complexes, such as Rh(III) and Os(III) complexes, attract increasing attention as leading scaffolds for the development of potential pharmacological agents due to their inertness and stability. Therefore, we have designed and fully characterized a few novel rhodium(III) and osmium(III) complexes with a tridentate nitrogen−donor chelate system. For some complexes, the crystal X-ray structure analysis was performed. Reactivity of the newly synthesized complexes towards small biomolecules, such as L-methionine (L-Met), guanosine-5’-monophosphate (5’-GMP), and glutathione (GSH) has been examined. Also, the reactivity of these complexes towards the DNA/RNA (Ribonucleic acid) duplexes was investigated. Obtained results show that the newly synthesized complexes exhibit good affinity towards the studied ligands. Results also show that the complexes react faster with the RNA duplex than with the DNA and that in the DNA duplex reaction is faster with 15mer GG than with the 22mer GG. The UV-Vis (Ultraviolet-visible spectroscopy) is absorption spectroscopy, and the EB (Ethidium bromide) displacement studies were used to examine the interaction of these complexes with CT-DNA and BSA (Bovine serum albumin). All studied complex showed good interaction ability with both the DNA and BSA. Furthermore, the DFT (Density-functional theory) calculation and docking studies were performed. The impact of the metal complex on the cytotoxicity was tested by MTT assay (a colorimetric assay for assessing cell metabolic activity) on HCT-116 lines (human colon cancer cell line). In addition, all these tests were repeated in the presence of several water-soluble biologically active ionic liquids. Attained results indicate that the ionic liquids increase the activity of the investigated complexes. All obtained results in this study imply that the introduction of different spectator ligand can be used to improve the reactivity of rhodium(III) and osmium(III) complexes. Finally, these results indicate that the examined complexes show reactivity characteristics needed for potential anti-tumor agents, with possible targets being both the DNA and proteins. Every new contribution in this field is highly warranted due to the current lack of clinically used Metallo-based alternatives to cisplatin.

Keywords: biomolecules, ionic liquids, osmium(III), rhodium(III)

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