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  Mercy Health

  Joseph George Charbel, Eric William Mullet

  Formulary rationalization

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  Metal Layer Architectures for 2D TMD Heterostructures

  Anna K. Benton

  The purpose of this investigation is to control the formation of atomically thin metal films of transition metals on silicon wafers with a 200 nm oxide layer. Metals have physical characteristics that are dependent on the thickness and structure of the material. The thickness and the structure of the material change depending on the conditions of metal deposition. By varying the metal deposition conditions, the desired physical characteristics, such as roughness and crystalline domain size, can be attained. This project focuses on depositing a transition metal film using a sputtering chamber at different growth conditions using low power, medium power, and high power. Film thickness and structure were observed using an atomic force microscope (AFM). Surface features were observed using a scanning electron microscope (SEM). Conductivity data was used to indicate film structure. The metal films will then be exposed to a vapor containing sulfur or selenium to create thin heterostructures of transition metal dichalcogenides (TMDs). The heterostructure films will then be characterized using an AFM, SEM and Raman Spectroscopy. Once the relationship between metal film structure and reactivity with chalcogen vapors is understood, different transition metal films will be deposited sequentially to form a bilayer of two transition metals. After film growth, the bilayers will be observed using an AFM and SEM. Conductivity data will indicate film structure. The bilayer films will be exposed to vapor containing sulfur or selenium to create two layers of TMDs. One of the applications of this project is to be able to tune the electronic and optical properties of semiconductors by varying the stacking pattern of many TMD layers. This will allow desirable band gaps to be achieved for transistors and sensors. Stacking two layers is the first step in understanding how effective this novel approach for development of synthetic superlattices can be.

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  Mike Sells

  Jillian Therese DeWitt, Nicholas T. Hoskins, Allison Marie Veverka

  Real-time production statistics reporting

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  Military Alliances and Their Role in the 21st Century: Examining Bilateral and Multilateral Realtionships

  Tyler Andrew Johnson

  Throughout history, military alliances have proved pivotal in shaping international politics and determining the outcome of conflicts. The complexities behind alliances in the 20th and 21st centuries have brought a new dynamic to international conflict resolution. With the resurgence of China and Russia as contenders on the world stage, the focus for organizations such as NATO have shifted from counterterroism to preparing to fight a near peer adversary. This research examines the dynamics behind the United States' international military partnerships, and the differences in how the United States utilizes alliances to deter China and Russia.

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  Mindfulness, Self-Compassion, and Emotion Regulation in Wellbeing Among Childhood Maltreatment Survivors

  Kelsey Julian, Abagail Petit, Alicia Selvey

  Mindfulness and self-compassion have been linked to the capacity for emotion regulation and to better outcomes, including among survivors of childhood maltreatment (CM). Mindfulness is multifaceted and includes observing, describing, acting with awareness, non-judging, and non-reactivity, yet little research has examined the roles of specific facets of trait mindfulness in positive outcomes after CM. This study used self-report measures from 157 undergraduates who endorsed CM experiences, and tested combined parallel-sequential multiple mediation models of wellbeing. Hypothesized models linked CM severity to lower wellbeing through reduced self-compassion and subsequent emotion dysregulation and through lower trait mindfulness and subsequent emotion dysregulation. As anticipated, there was a negative indirect effect of CM on wellbeing through lower self-compassion and more emotion dysregulation (CI = -.09, -.01). Unexpectedly, there was no indirect effect through mindfulness and emotion dysregulation. When facets of mindfulness were tested separately, a negative indirect effect only emerged through lower non-judging and emotion dysregulation (CI = -.22, -.02). Results suggest that, in mindfulness-based interventions with CM survivors, self-compassion and non-judging may be critical targets for fostering wellbeing, as their absence may impede emotion regulation capacity.

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  Minster

  Mark Robert Vezina, Yuexin Zhou, Drew T. Zimmer

  Machine capability study

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  Mission of Mary Cooperative's Net-Zero Initiative

  Salahaldin Alshatshati, Jaime Howard, Nathan Mansour

  Mission of Mary Cooperative is the first net-zero energy organization in Dayton, Ohio. Over the past two years, students from the ETHOS Center have helped to improve the energy efficiency of the building through structural and behavioral changes. Mission of Mary Cooperative looks to inspire and educate the community on the importance of energy behavior, efficiency improvement, and sustainable development.

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  Modeling and Validation of Pilot-Aircraft Cybernetic Systems

  Benjamin Moidel

  A notable example of adverse dynamic coupling within modern cybernetic systems is spatial disorientation of pilots in flight. In this presentation we propose a preliminary methodology for developing and validating pilot-aircraft models to predict adverse coupling modes present in the interactions between human and machine. The realism of a Cessna 152 model within the University of Dayton’s Merlin 521 Flight Simulator was validated through both pilot feedback using the Cooper-Harper handling rating scale and comparisons of real in-flight dynamic responses to the response data output by the simulator.This simulator has the unique capability that any aircraft can be modeled and simulated through an easy-to-use user interface. Its capsule provides an immersive experience for users, delivering realistic physics and 6 DOF motion within a typical cockpit layout. Time-varying data can be extracted post-simulation, including ambient environmental conditions, control inputs, and dynamic responses. To validate the model, simulator data was compared to accelerometer and GPS data collected in-flight from a Cessna 152.In the near future, following an Institutional Review Board approved protocol, a group of 5-10 pilots with extensive experience will be asked to fly the Cessna 152 model, both with and without capsule motion. The pilots’ experience qualifies them to provide reliable feedback on the handling characteristics of the model using the Cooper-Harper handling rating scale. Tasks such as a coordinated turn and a constant-speed climb will be used to assign handling ratings to the model. The responses will be compared to the pilots’ initial handling rating of the real Cessna 152 based on their experience. Pilot ratings will be supplemented with additional feedback on the apparent realism of the model. Overall validation of the model will require both the flight data output and pilot feedback for the model to align with that of the real aircraft.

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  Modeling Bullying in Teenagers: Assessing the Behavioral Effects of Social Defeat Stress in Adolescent Mice

  John Richard Coffey, Patrick Robert Flaherty

  Depression, anxiety, and other stressed-induced cognitive deficits severely affect millions of people worldwide. Strikingly, an estimated one in four adolescents around the globe suffer from a mental health disorder. It has long been known that drastic developmental changes occur in the adolescent brain which makes teenagers far more susceptible to various stressors, most prominent being social and physical defeat from stronger peers (i.e., bullying). In order to investigate the behavioral effects of social defeat stress in adolescence, an adolescent mouse model was utilized. Adolescent mice were subjected to chronic resident-intruder stress and immediately following the completion of the paradigm, a battery of behavioral tests were conducted in order to assess levels of anxiety, depression, and cognitive flexibility.

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  Momentum from Tiny Choices: the Power of Rethinking Our Habits

  Theresa Isemann

  Tess shares some of her sustainability experiences at UD and how they have inspired her to this day. She offers reflection questions to encourage your own exploration of your personal connection to making sustainable choices. Tess speaks to the importance of rethinking our daily habits to internalize climate action in our everyday lives.

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  Motion Assessments in Virtual Reality Environments

  Lanna Klausing

  Traditional upper extremity rehabilitation techniques are often tedious and repetitive. Recent improvements to Virtual Reality games have allowed for increased customizability and show potential in the area of rehabilitation, creating a more integrative and exciting rehabilitation environment. The purpose of this thesis is to use Virtual Reality (VR) and motion capture to quantify different movement deficits that may arise due to MS, and to understand how the reaching motions of patients with MS may differ from healthy controls. Reaching motions are one of the motions commonly used in upper extremity rehabilitation measures, and through the study of reaching motions this research will have a long-term purpose of determining whether virtual reality can be used as an effective upper extremity rehabilitation tool. During data collection participants will wear a motion capture suit and a VR headset that displays movement targets. Participants will perform 3 levels focused on motions involving single arm movements and dual arm movements, in which they will be asked to perform reaching motions to hit the movement targets. The motion data collected from participants’ motion capture suits will then be analyzed and compared between MS and control groups.

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  Motivations and Constraints for Fan Attendance at Sporting Events: A Case Study of the NCAA First Four Games

  Sam Taro Banke, John M. Barrett, Emily Rose Fritz, Tom Jebron Graf, Matthew Joseph Green

  Fans are motivated to attend sporting events for a variety of different factors. These motivations may vary depending on the level of competition, the location the event is being held, and the demographic that makes up an area’s fan base. Our study will investigate the most prevalent factors that motivate fans to attend sporting events. The research will consist of a survey given to University of Dayton students, faculty, fans, and residents of Dayton who have interest in attending sport events. This survey will allow us to determine variables that most commonly motivate individuals to attend the First Four games, which may be unique because these games do not include the presence of University of Dayton’s men’s basketball team. We believe the results of this study can be useful for arenas who host neutral site events similar to the First Four.

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  Multi-modal Data Analysis and Fusion for Robust Object Detection in 2D/3D Sensing

  Quinn Graehling, Jonathan Schierl

  Multi-modal data is useful for complex imaging scenarios due to the exclusivity of information found in each modality, but there is a lack of meaningful comparisons of different modalities for object detection. In our work, we propose three contributions: (1) Release of a multi-modal ground-based small object detection dataset, (2) A performance comparison of 2D and 3D modalities using state-of-the-art algorithms on data captured in the same environment, and (3) a multi-modal fusion framework for 2D/3D sensing. The new dataset encompasses various small objects for detection in EO, IR, and LiDAR modalities. The labeled data has comparable resolutions across each modality for better performance analysis. The modality comparison conducted in this work uses advanced deep learning algorithms, such as Mask R-CNN for 2D imaging and PointNet++ for 3D imaging. The comparisons are conducted with similar parameter sizes and the results are analyzed for specific instances where each modality performed the best. To complement the effectiveness of different data modalities, we developed a fusion strategy to combine the region proposals of one modality with the classification strength of a different modality for accurate detection and region segmentation. We investigated the functionality of the You Only Look Once (YOLO) algorithm, which computes partitioned image classification and region proposals in parallel for detection. Our fusion strategy learns the optimum features of different modality combinations for appropriate candidate selection for classification. The effectiveness of the proposed fusion method is being evaluated on the multi-modal dataset for object detection and segmentation and we observe superior performance when compared to single-modality algorithms.

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  Multi-modal Data Analysis and Fusion for Robust Object Detection in 2D/3D Sensing

  Jonathan Schierl

  Even with current testing and evaluations in state-of-the-art deep learning, there is a lack of comparison between different modalities in object detection. To improve this, we created an in-house dataset directly for the comparison of 2D infrared captures and 3D LiDAR point clouds. The sensors used to capture this dataset were placed next to each other to retain a similar point of view and resolution. Individually, these modalities were evaluated using state-of-the-art deep learning architectures. For 2D Infrared, a neighborhood-based image enhancement algorithm called Retinex was used to improve the contrast of the images. These enhanced images were then processed using the Mask R-CNN architecture. For 3D point clouds, PointNet++ was used for feature extraction and classification. The detection accuracy and overall performance were compared between these modalities. Generally, the 3D approach performed better, with higher rates of detection and better accuracy. In comparing these architectures, we learned about the pros and cons of each modality. To further increase the accuracy of detection, we propose a fusion network that incorporates the strengths of both modalities and processes them in one architecture. This network would extract features in 2D using Mask R-CNN and in 3D using KPConv. These feature spaces would be combined and sent through the region proposal network and rest of the Mask R-CNN architecture for a higher detection accuracy.

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  Multi Structural Tunable Filters Using Optical Phase Change Material (O-PCM) for the Visible and IR Region

  Remona Heenkenda

  Phase change materials provide an ideal platform in designing optical switches and tunable optical components. This is due to the large reversible refractive index changes induced in phase change materials. In this work, we design and develop a tunable optical thin film filter for visible and infrared (IR) regions using optical phase change materials. In our prior work, we examined Ge2Sb2Te5 (GST) phase change material, which undergoes an amorphous to crystalline phase change. Ge2Sb2Se4Te1(GSST) is a newer phase change material that undergoes a similar phase transition around ~300 C, and it is more suitable for operation in the IR region. It has low optical loss compared to Ge2Sb2Te5 (GST) in both crystalline and amorphous states. Therefore, for many applications, GSST can be used over GST to achieve better performance. Based on the studies we have conducted so far, it was evident that using GSST, designing a tunable filter that equally performs in both crystalline and amorphous states, could be challenging. Therefore, other phase change materials (GeSe, GeTe, Ge3Te7 and Sb2Te3) need to be studied for application in tunable filter design. Findings of the detailed analysis of above-mentioned phase change materials for achieving the proposed objective will be discussed. This information will greatly contribute in expanding the scope of our research since there are numerous applications for these optically active materials.

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  MyWebGuard: Toward a User-Oriented Tool for Security and Privacy Protection on the Web.

  Jack A. Armentrout, Panchakshari N. Hiremath

  We introduce a novel approach to implementing a browser-based tool for web users to protect their privacy. We propose to monitor the behaviors of JavaScript code within a webpage, especially operations that can read data within a browser or can send data from a browser to outside. Our monitoring mechanism is to ensure that all detected leakage is automatically prevented by our context-aware policies that can be modified and redefined by the user. Our method advances the conventional same-origin policy standard of the Web by enforcing different policies for either each source of the code, or groups of related API. Although we develop the tool as a browser extension, our approach is browser-agnostic as it is based on standard JavaScript. Also, our method stands from existing proposals in the industry and literature. In particular, it does not rely on network request interception and blocking mechanisms provided by browsers, which face various technical issues and lead to an “all or nothing” approach to privacy on the web. We implement a proof-of-concept prototype and perform practical evaluations to demonstrate the effectiveness of our approach. Our experimental results evidence that the proposed method can detect and prevent data leakage channels not captured by the leading tools such as Ghostery and uBlock Origin. We show that our prototype is compatible with major browsers and popular real-world websites with promising runtime performance.

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  Neurochemical alterations upon retinectomy in the developing chick embryo: a preliminary study

  John Richard Coffey

  Chick embryos, between 3.5 and 4.5 days of development, have been found to be able to completely regenerate a removed retina in the presence of fibroblast growth factor 2 (FGF2). FGF2 activates the trans-differentiation of the retinal pigmented epithelium, providing a necessary step in the regenerative process. While the regenerative capabilities of the chick embryo are known, the injury signals, which stem from the retinal injury, effect on the brain’s neurochemistry is not known. The ISE summer CoRPs project aimed to use HPLC analysis of the chick embryo brain tissue during periods of 30 minutes, two hours, and three days post-retinectomy for both embryos with and without fibroblast growth factor 2 to analyze the impact injury signals and subsequent regeneration had on the brain’s neurochemistry. Samples of embryo brain tissue were harvested at Miami University and brought back to the University of Dayton, where they were subjected to ex vivo neurochemical analysis with high performance liquid chromatography. Herein, we present first preliminary evidence for intriguing neurochemical alterations upon retinectomy in the chick embryo.

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  New Insights into Hierarchical Structures in Polymer Nanocomposites: A Dissipative Particle Dynamics (DPD) Simulation Study

  Ashish Gogia

  Polymeric systems such as natural rubber used in car and truck tires require the addition of suitable additives for the enhancement of numerous properties, including reinforcement and durability. The behavior of such fillers, (carbon black, silica, and metal oxides and some combination thereof), and their influence on nanocomposite effectiveness, depends on the filler structure, the interaction between filler-polymer matrix as well as the processing history. To understand this problem, we perform Dissipative Particle Dynamics (DPD) simulation of these blends, varying polymer-polymer, filler-filler, and polymer-filler interaction energy. We will discuss the effects of interaction strength, the scaling of polymer chains, and methods to quantify the filler percolation threshold and mesh size as a function of filler concentration. In addition, the simulation results are also validated experimentally through small-angle x-ray scattering data to provide insight and understanding of how these complex structures develop in these multicomponent systems.

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  Novel Combinational Therapy Targets Pseudomonas aeruginosa Biofilm Infections in a Flow Model

  Jessica Elizabeth Geyer

  The rise of multidrug resistant (MDR) pathogens is one of the greatest medical concerns of the century. In MDR infections, the use of antibiotics is almost entirely useless, leaving patients at a higher risk of mortality. Almost 80% of human infections involve biofilms. The biofilm-associated cells of Pseudomonas aeruginosa are up to 1000-fold more resistant to antibiotics than planktonic cells. The danger caused by the resistance of these pathogens has initiated an urgent need to look for alternative antimicrobial therapies such as phage therapy, which uses the natural relationship of lytic bacteriophages to eliminate infections. Our lab has examined a successful combinational therapy that treats biofilms of P. aeruginosa using a lytic bacteriophage (PEV2) and our novel patented porphyrin (ZnPor). The objectives of this proposal are to evaluate the synergistic antibacterial effectiveness of ZnPor and PEV2. Biofilm flow models were constructed to represent a in vitro infection model using CDC approved bioreactors. Bioreactors were inoculated with wild type strain of P. aeruginosa and grown for 16~18 hours, then treated with a combination of PEV2 and ZnPor both alone and combined. Phage and bacterial burden were quantified and biofilm structure was observed using confocal laser scanning microscopy. The therapy we have developed involves a novel patented porphyrin (ZnPor), which rendered biofilms more porous and less strongly attached. The subsequent addition of bacteriophage PEV2 resulted in the killing of virtually all the remaining cells. The significance of our novel approach of antimicrobial management is that, unlike other protocols involving biofilm eradication, our strategy addresses the issue of resistance. The ability to disrupt the inherent structure of biofilms and make cells accessible to treatment promotes little resistance and decreases bacterial success in colonization of biomaterials. The treatment of life-threatening infections is foundational to UD’s mission of Research for the Common Good.

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  Novel Intelligent Control System for Combating Ventilator Induced Lung Injury

  Jason Andrew Cahill

  Mechanical ventilation, as a resource for critical care, is a balancing act. Every day physicians, nurses, and respiratory therapists rely on this life saving intervention to support patients who are too weak or ill to breathe on their own. Unfortunately, structural and physiological damage can easily occur as a result of aggressive or long-term ventilator use. Because of the cardiopulmonary system’s tremendous complexity as well as the innate variability in parameters due to disease, individuality, and time, most ventilators require continual adjustment to avoid these side effects, essentially making the physician the controller. This project proposes a radical step forwardin design, a three-part control method that will bring the patient into the loop in an unprecedented way. First, a nonlinear controller utilizing a generic model of the cardiopulmonary system. Second, a neural network-based adaptive controller capable of reducing the immediate deviation between the first controller and the real patient. Finally, an intelligent system identification algorithm that optimizes the parameters of the first controller in real-time, thereby further reducing error associated with long term variations. At each step the controller will be analyzed, developed, and tested via simulation, with the final product signifying a leap forward in respiratory care.

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  Number Sense in Every Color

  Jordan Trenkamp

  Identify the importance of getting creative in your classroom especially with number sense. Students need multiple ways to learn how to engage in number sense and understand numbers. This presentation identifies the who, what, why, and how of strategies that help students better understand number sense.

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  Olympic Games Event Recognition via Adaptive Convolutional Neural Networks

  Yousef Idris Yousef Mohamad

  Automatic event recognition based on human action is both interesting and valuable research topic in the field of computer vision and deep learning. With the rapid increase and the explosive spread of data which is being captured momentarily, the need of fast and precise access to the right information has become challenging task with considerable importance for multiple practical applications, e.g., image and video search, sport data analysis, healthcare monitoring applications, monitoring and surveillance systems for indoor and outdoor activities, and video captioning. This research, part of my master’s thesis, develops an adaptive content-aware convolution neural network with the capability of analyzing, recognizing and interpreting the sport event in the Olympic games based on human action. 20 of the 33 sports scheduled for inclusion in the Olympic Games Tokyo 2020 will be included in the collected data set to evaluate the proposed method. This method combines convolutional neural network (CNN) and transfer learning (fine-tuning method) to potentially achieve best performance with high accuracy and precision of the event recognition.

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  On Isomorphism Theorems and Characterizing Properties of Groups

  Jack M. Dalton

  In group theory, understanding properties of groups is essential. However, in some circumstances determining the properties of groups is challenging because of the structure or ambiguity of a group. The Isomorphism Theorems provide a solution to this challenge. When two groups are isomorphic to one another, it is said that those two groups have the same properties as each other. Given a group G and subgroups N and K of G, the First, Second, and Third Isomorphism Theorems allow us to find isomorphisms between different groups. In this study, we examine the proofs for the Isomorphism Theorems to understand which groups we can claim are isomorphic to each other.

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  Optimization of Aluminum Scandium Nitride Growth for Piezoelectric Applications

  Ryan P. Laing

  The piezoelectric coefficient of aluminum nitride (AlN), a material important for radio frequency communication applications, has been shown to depend strongly on film crystallinity. Aluminum scandium nitride (AlScN) is an alloy of AlN and ScN that has been demonstrated to have up to a 5x increase in piezoelectric coefficient compared to pure AlN. The correlation between synthesis conditions, film crystallinity, and the piezoelectric coefficient is still being extensively studied. AlScN films were deposited on thin layers of titanium nitride on sapphire substrates using reactive magnetron sputtering. Films were grown with a variety of sputter powers and substrate temperatures to ascertain the effect of these conditions on film crystallinity and surface morphology. The full-width half-max of x-ray diffraction (XRD) rocking curve scans was used to determine the film crystallinity, while atomic force microscopy revealed the surface morphology. This characterization is preliminary work for a greater study in which the d33 piezoelectric coefficient will be measured with piezoelectric force microscopy, which will be correlated with the XRD rocking curve to find the deposition conditions with the highest piezoelectric performance.

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  Optimization of Solar Array Positioning Actuators for Small Satellites

  Mohamed Ali Alsadig Mohamed

  The goal of this research is to evaluate the benefit of actuating solar arrays for small satellites. CubeSats are small satellites that are built to standard dimensions (Units or “U”) of 10 cm x 10 cm x 10 cm. They can be 1U, 2U, 3U, or 6U in size, and weigh less than 1.33 kg (3 lbs) per U. Since their introduction in 1999 by California Polytechnic State University and Stanford University engineers, more than 1100 have been deployed into orbit. CubeSats rely solely on a solar array to generate energy from the sun. The size and weight limitations place constraints on solar panels' size and thus the available power budget and stored energy reserves, which decrease the CubeSat functions. The CubeSats capabilities could be greatly enhanced by increasing the available on-board power. This research determined the energy capturing capability from various solar panel configurations and positioning. Optimal angles of one and two degree-of-freedom positioning. Each configuration of solar cell is simulated for a CubeSats satellite in geo-synchronous and sun-synchronous orbits. In addition, this research will create design models of these various mechanisms configurations by using Sarrus linkage mechanism that elevates the solar cell away from the body of satellite to make sure that these configurations are suitable for the size and weight of the CubeSat.