Join us for the Mechanical and Industrial Engineering (MIE) Showcase on November 30th. This event promises to be a convergence of innovative ideas and cutting-edge research. Please note that the deadline to register for the showcase is November 24th. Don’t miss this opportunity to engage with experts and peers in the field. Click here to register. We look forward to seeing you there!
Speaker: Dr. Ronald Harichandran
Speaker: Dr. Kagya Amoako
Speaker: Ms. Magdalena Garcia
Speaker: Mr. Joe Leveillee
Speaker: To Be Announced
Speaker: To Be Announced
Speaker: To Be Announced
Abstract: This research presents a novel approach to enhance Human-Cobot Interaction (HCI) by leveraging Natural Language Processing (NLP). We’ve successfully integrated the CoboVox voice recognition system into the UR3 interface, allowing for seamless voice-activated interaction with collaborative robots (cobots). Our methodology encompasses the development of a specialized vocabulary, NLP model analysis, and practical implementation, enabling individuals without prior expertise to efficiently program and operate cobots through voice commands. This innovation has the potential to promote responsible integration and improve the synergy between humans and robots.
Abstract: An epidemic is termed as an infectious disease that is widespread in a population at a specific time. Due to their contagious nature, epidemics have posed a significant hazard to both humankind and therefore the economy. A poor public health infrastructure and high transmission rates are the main contributors for the uncontrollable and rapid spread of these diseases, which make it difficult to manage the outbreak at its source. To prevent such spread and mitigate the risk and the severity of infection, immediate and informed actions by the local authorities are necessary. Through this study, our main objective is to determine how the local authorities can prevent the spread of an epidemic by imposing lockdown in a planned manner. To simulate an epidemic in the real world, we consider a network of individuals with each node representing an individual. Reinforcement Learning is used to model the actions of the local authority in face of an epidemic outbreak with the aim of minimizing the cumulative cost of the epidemic. It is assumed that the local authority has the choice of imposing lockdown or not. Through these models, we aim to discover a common pattern of optimal actions of the local authority that may serve as a key metric to define pre-informed methods of imposing lockdown in a real-world scenario of an epidemic outbreak
Abstract: Additive manufacturing (AM) technologies have been widely used to fabricate intricate models. However, existing AM processes may prove inadequate for printing curved structures, as the conventional approach of generating extrusion paths solely in a horizontal plane can lead to issues such as inaccuracies and disconnections in the printed components. This study introduces a new AM method for printing non-flat structures. A visual programming language was employed to create a program capable of generating nonplanar print paths for curved structures. An extrusion mechanism was used for printing, comprising a lead screw, gear system, stepper motor, and a syringe-plunger system. The developed system was put to the test in printing free-form structures using thermosetting pre-polymers. The results demonstrate that nonplanar 3D printing effectively overcomes the fabrication limitations associated with conventional planar processes while preserving the functionality of the printed structures.
Abstract: Cancer is a major global health concern. Detecting it early and managing costs are key challenges. Whole Genome Sequencing (WGS) is a thorough but costly method for studying cancer genes to determine the best treatment method. Advances have made it more affordable, yet it’s mostly available in specialized centers and academia and smaller hospitals need to refer patients to larger hospitals for these tests. Since not every hospital conducts WGS, our goal is to devise specific strategies for each hospital, employing agent-based simulation and game theory to determine what is the best referral strategy for those hospitals. Agent-based simulation and game theory are computational modeling techniques that can be used to study complex systems and interactions between different agents. In the case of cancer treatment, these techniques can be used to model the timing of implementation of WGS testing to identify the optimal strategy for different hospitals. By creating a simulation that includes different types of hospitals at different locations with varying levels of testing capabilities, we can model the interactions between hospitals and the decision-making processes involved in referring patients for WGS testing. In the simulation model, we have considered different parameters including the cost of testing, success rates of tests, and the time taken to complete the diagnostic pathway. We have also evaluated the sensitivity of the model to changes in these parameters.
Abstract: One of the most widely used technologies in industries is robotics. The increasing demands and development require complex procedures and precise approach specially in the manufacturing. This is achieved by the introduction of Robotic arms in such workplaces. The most effective usage of the robotic arm is when it is completely autonomous and is intelligent enough to perform the required operations on different types of objects. Synergistic Articulated Robotic Manipulator (SARM) presents this usage by implementing the concepts of Object Detection and Inverse Kinematics using ROS (Robot Operating System). The objects present in the workspace are detected using image processing algorithm and their coordinates in the workspace are determined. The SARM reaches the particular object’s position using inverse kinematics analysis on its own, picks the object with its end effector, and places it at the desired position within the workspace.
The objective is to incorporate automation into the system by using a low-cost and small single-board computer i.e., Raspberry Pi with Arduino. Using Image Processing algorithms, the coordinates of the object in the workspace are determined. Once this is done, the inverse kinematics analysis is performed on the estimated coordinates in Robot Operating System (ROS). This gives the joint angles through which the links of the robotic arm are to be rotated, to reach the object. Hence the arm executes the pick and place task. One of the tasks involved over here is the communication between the two boards i.e., the processor Raspberry Pi and the driving board Arduino. The final key point of this project is the integration of the above-mentioned tasks to form a robust and complex robotic arm system that is smart and also strong enough to detect and pick up objects for the task of sorting as would be done by a human being.
Abstract: “Smart Bag” is a regular luggage bag with extra add-ons that will help people with a hassle-free journey without the fear of their luggage getting lost in their travel, and tracking your luggage on the conveyor belt at the destination airport could be a frustrating experience especially if you are carrying valuable items in it or similar luggage like other passengers.
“Smart Bag” is powered by IoT technology with the features of an inbuilt weighing scale, storing your travel details, reminders on your travel plan and notifications when your luggage reaches your destination airport, display visualizations, and tracking of your luggage. All these features help users track/know their luggage in a smart way and keep them notified or alerted in every situation.
The approach of this project is to leverage the ease of tracking your luggage in any situation with the use of IoT in two-way connectivity between the luggage and the user via a dedicated mobile application. The application communicates with the user via Wi-Fi or Mobile data or Bluetooth or Display signals (Visualizations). All the notifications and alerts are received by the user via a mobile application linked to the user account or through the display signals in the luggage
Abstract: This ambitious project is centered on closing the divide that separates artificial intelligence and emotional intelligence, an area ripe with potential for transformative breakthroughs. In the course of this endeavor, we aim to showcase the remarkable ability of a robot to engage in meaningful conversations, exhibiting emotional responsiveness and intellectual stimulation when interacting with individuals. Our focus extends beyond mere mimicry, delving into the capacity of these AI systems to generate and experience genuine emotions.
In addition to working with emotional intelligence, we’re investigating AI’s role in enhancing drone capabilities, optimizing robot arms for various tasks, and developing biomimicry technologies. By harnessing AI’s potential, we aim to revolutionize these domains, pushing the boundaries of innovation.
Abstract: This project has started by considering one of those industries which are exhausting polluted gas to the atmosphere. The polluted gas comprises of Ozone and Oxygen generally. Ozone is one of the toxic gasses which is essentially accounted for global warming and disruption of ozone layer in the atmosphere. So, I have designed one machine which will be used to filter the ozone from the mixture of gases along with Oxygen in another storage. So, in the final stage we will have pure ozone and pure oxygen in separate storage. Instead of exhausting the ozone gas to the atmosphere we can use it for wastewater treatment and the oxygen we can sell for the market purpose like hospital. The heart of this machine is the bed sleeve material which separates these gases with their precise molecular gap. This machine will not be limited to ozone and oxygen but also, we can use it for all the industries where the exhaust gases comprise of carbon, methane and many other by changing the sleeve of the material with the appropriate molecular weight. Furthermore, I am still working on the aerodynamic case where we can use this machine to separate the gases like NOx and methane and keep these gases under the room temperature with solid and liquid state with the help of carbon capture technology and can reuse the fuel again.
Abstract: Consumer panic buying and stockpiling during supply disruptions pose significant challenges to both consumers and supply chain stakeholders. This research study delves into various aspects of this phenomenon, shedding light on its underlying causes and potential solutions.
The impetus behind this study is to explore the role of social learning in propagating panic buying behavior, emphasizing the need to understand how information spreads through social networks during supply crises. Moreover, this research emphasizes the importance of data-driven demand sensing and collaboration across supply chains to manage and address this disruptive consumer behavior effectively.
Additionally, this study presents an analysis of consumer panic buying and stockpiling behaviors during supply disruptions, offering diverse models and strategies to address this issue. One key aspect explored in this study is the categorization of panic levels among consumers, allowing for a comprehensive understanding of their reactions in crisis situations.
Abstract: Additive manufacturing (AM) technologies have been widely used to fabricate intricate models. However, existing AM processes may prove inadequate for printing curved structures, as the conventional approach of generating extrusion paths solely in a horizontal plane can lead to issues such as inaccuracies and disconnections in the printed components. This study introduces a new AM method for printing non-flat structures. A visual programming language was employed to create a program capable of generating nonplanar print paths for curved structures. An extrusion mechanism was used for printing, comprising a lead screw, gear system, stepper motor, and a syringe-plunger system. The developed system was put to the test in printing free-form structures using thermosetting pre-polymers. The results demonstrate that nonplanar 3D printing effectively overcomes the fabrication limitations associated with conventional planar processes while preserving the functionality of the printed structures.
Abstract: Direct Ink Writing (DIW) 3D printers hold immense potential for the production of multi-material components used in electronics, biomedical devices, and soft robotics. However, existing DIW systems are often complex and costly. This work introduces a cost-effective and accessible multi-material DIW 3D printer. The approach involved modifying an affordable fused filament fabrication 3D printer and integrating a custom-built extrusion mechanism into its existing motion system. The system was designed to enable the simultaneous printing of three different functional inks within a single print. The extrusion mechanism primarily consisted of a syringe-plunger system, lead screws, bearings, spur gears, and stepper motors. A process has been developed to generate the print path for multi-material components. The resulting system successfully demonstrated the capability to 3D print multi-material thermoset polymer components. This development holds significant promise for the fabrication of new materials suitable for applications in electronics and biomedicine, as it facilitates the 3D printing of intricate geometries using non-Newtonian inks.
Abstract: At the University of New Haven, where the main campus is in West Haven, CT, the traffic on the campus variates, which can be more intense in certain weekdays and at certain times of the day. In an experimental study, some data were collected at the main campus of the University of New Haven by a group of students [2]. The number of cars that arrived or passed the main entrance to go to the back parking lots was collected in 13 intervals of 15 min on two days of the week, Monday and Saturday. The data was collected on two nice sunny days between 10 am and 1:15 pm each day.
The purpose of this investigation is to analyze the frequency of the cars that arrive in a certain interval of time and do a comparison between a regular weekday and a weekend day. As well as the estimation and interpretation of the meaning of the probability distribution, calculate the mean and variance of the number of cars per unit of time, and some other analyses of probability events.
Abstract: Additive manufacturing processes have created new opportunities for printed electronics. Commercial 3D printers fall short in printing functional inks, especially, with thermosetting non-Newtonian materials. Also, open-source slicing software are generally designed for thermoplastics. In this work, a 3D printing solution was developed to print with functional thermosetting polymers. Various polymer candidates were investigated to fabricate flexible tactile and strain sensors for electronics applications. A 3D printing system was developed for printing electronics with functional polymers. Finally, printed sensors were characterized in different conditions.
Abstract: This project introduces a customized 3D printer based on the Voron design, incorporating a core XY movement mechanism. The comprehensive process involved assembling mechanical components, configuring electrical and electronic systems, and programming the machine for optimal functionality. The result is a 3D printer that not only achieves significantly faster print speeds but also offers enhanced control over print parameters. This innovative approach in 3D printing technology contributes to more efficient and reliable printing processes, opening new possibilities for a wide range of applications