University Technology Exposure Program 2022: July-August Final Update

This article is a part of our University Technology Exposure Program. The program aims to recognize and reward innovation from engineering students and researchers across the globe.

#1. Conceptual design of smart multi-farm produce dehydrator using a low-cost PLC and Raspberry Pi  By Sunkanmi Oluwaleye

Processing food/crop often requires removing moisture content without affecting their nutritional values. To carry out the process effectively, a special dehydrator/oven is required that can evenly distribute the generated heat and remove all moisture.

This student article by Sunkanmi proposes a low-cost raspberry pi and programmable logic controller (PLC) based dehydrator that gives the users the flexibility to control both the drying chamber’s temperature and humidity from its web interface via a mobile device or the dehydrator’s human machine interface (HMI).

Read the complete write-up here.

#2. New Image Recognition Technique for Intuitive Understanding in Class of the Dynamic Response of High-Rise Buildings By Rocio Porras Soriano

Structural engineering is a subject of civil engineering that requires students to develop an intuition of the structural response of different construction designs. In this article, Rocio explains how complementing traditional master classes with additional activities can improve students’ learning experiences.

An image-recognition algorithm is proposed to identify the dynamic response (deflections, velocity, and accelerations) of small-scale buildings on an educational shaking table. Students are challenged to improve the seismic behavior of a reference small-scale building. Then, the proposed algorithm is used to compare the different typologies proposed. A survey conducted at the end of the course indicates an improvement in the student's confidence and motivation.

Read more about the methodology and the results here.

#3. A Machine Learning Approach for an Improved Inertial Navigation System Solution By Ashraf Abosekeen

An inertial Navigation System (INS) is a component of mechanical devices that uses the data collected from sensors like accelerometers and gyroscopes to plan movements. The system depends on the accuracy of the Inertial Measurement Unit (IMU), which provides INS with the required data. IMUs used in low-cost micro-electro-mechanical systems (MEMSs) suffer from huge error sources such as bias, the scale factor, scale factor instability, and highly non-linear noise.

This article by Ashraf proposes a machine-learning-based adaptive neuro-fuzzy inference system (ML-based-ANFIS) that improves the traditional INS by up to 70% in 2D positioning and 92% in 2D velocity.

Visit this link for all details.

#4. Combining SLA 3D printing and soft lithography for fast, versatile, and accessible high-resolution fabrication of customised multiscale cell culture devices with complex designs By Cathleen Hagemann

Taking advantage of low-cost, high-resolution desktop resin 3D printers combined with Polydimethylsiloxane (PDMS) soft-lithography, this article explains the optimized microfabrication pipeline capable of generating a wide variety of customizable devices for cell culture and tissue engineering in an easy, fast reproducible way for a fraction of the cost of conventional microfabrication or commercial alternatives. 

This technique enables the manufacture of complex devices across scales bridging the gap between microfabrication and fused deposition molding (FDM) printing.

Here is the link to the student article.

#5. Spatio-Temporal Analysis of Archived Web News for Precise Political Event Detection and Impact Analysis in India's Southern States By Pratik Dhabal Deo

A nation’s political system directly impacts its economy. Every political party has its own economic policies, which have a major impact on the economic stability of the nation.

This student article by Pratik explains Precise Political Event Detection using Spatio-Temporal Analysis (PPED-STA) schemes proposed by political event mapping through the extraction of data from the archives of web news. The aim is to use machine learning algorithms to predict precisely the possibilities of political events.

Read the submission here.

#6. Artificial Intelligence Assisted Architected Materials in Additive Manufacturing By Mohammad Mirzaali

The current advancement in multi-material additive manufacturing technologies has provided unique opportunities to create 3D printed structures with not only complex geometries at several length scales but arbitrary deposition of multiple materials (i.e., soft or hard) in 3D space.

In this article, Mohammad Mirzaali shares the design approaches and (bio)fabrication techniques for creating (bio)materials with tailor-made properties. Two frontier technologies, namely multi-material 3D printing and AI, are used to create various types of “digital materials” with rare properties.

Access the full article here.

#7. DOT-HAZMAT: An Android application for detection of hazardous materials (HAZMAT) By Mihir Pamnani

HAZMAT signs play a crucial role in rescue operations and hence an accurate detection tool is required in cases of accidents caused by hazardous materials. There are several approaches and methods for HAZMAT sign detection but the ones that use deep learning are the most successful ones.

In this submission, Mihir explains DOT-HAZMAT, an Android application based on Machine Learning and Computer Vision that locates and categorizes HAZMAT placards in perilous rescue operations. The article explains the enormous potential of neural networks and open-source libraries with computer vision for solving problems of extreme importance.

Check out all the details by visiting this link.

#8. Optimization of Mechanical Design Bladeless Wind Turbine for Electricity Fulfillment in Nusa Tenggara Timur, Indonesia By Muhammad Farhan Ramadhany

In this article, Muhammad Farhan Ramadhany explains the concept of Bladeless Wind Turbine wind power plants that can work optimally in areas with low wind speeds (3 to 8 m/s). The article explores how the design can be optimized to work in places with even lower wind availability.

Using the optimized designs, electricity demands in areas with low wind speeds can be met. The author has considered the case of Nusa Tenggara Timur, Indonesia, as an example of a region with low wind speed.

Here is the link to the complete article.

#9. High-Performance Amorphous Carbon Coated Lithium-Nickel-Manganese-Cobalt-Oxide (NMC622) Cathode Material with Improved Capacity Retention for Lithium-Ion Batteries By Anish Raj Kathribail

Ni-rich NMC has attracted great attention in the battery community due to a combination of high reversible capacity and high operating voltage that stems from two-dimensional lithium-ion diffusion and good lithium-ion conductivity. Coating conducting polymers onto active cathode materials has been proven to mitigate issues at high current densities stemming from the limited conducting abilities of the metal-oxides.

However, in spite of these advantages, the material is known to possess problems such as surface side reactions and chemical instability at the highly de-lithiated stages. This student article shows the synergetic effects of a furfuryl polymer coating and subsequent calcination leading to improved electrochemical performance of nickel-rich NMC622.

Check out the article here.

#10. FEXGAN-META: Facial Expression Generation With Meta Humans By J Rafid Siddiqui

The subtleness of human facial expressions and a large degree of variation in the level of intensity to which a human expresses them is what makes it challenging to robustly classify and generate images of facial expressions. The lack of good quality data can hinder the performance of deep learning models utilizing this data.

This student article by J Rafid Siddiqui proposes a Facial Expression Generation method for Meta-Humans (FExGAN-Meta) that deals with the challenge of robustly classifying and generating images of facial expressions while maintaining subtleness and intensity.

Read the article by visiting this link.

#11. Dynamic simulation and optimization of anaerobic digestion processes using MATLAB by Prabakaran Ganeshan

This student article explains a dynamic model that can predict biomethane production with time series developed based on a modified hill’s model using MATLAB.

This model predicts the biomethane production for both batch and continuous processes across substrates and under diverse conditions such as total solids, loading rate, and days of operation. The deviation between the literature and the developed model is less than ± 7.6%, which shows the accuracy and robustness of this model.

Visit this link to read the submission.

#12. Quasioptics for Increasing the Beam Efficiency of Wireless Power Transfer Systems By Pereira Ricardo

The highest beam efficiency in a wireless power transfer (WPT) system that uses focusing components was 51%. Achieved by William Brown in 1964, it used a ~ 3 m diameter reflector for a transfer distance of 7.62 m. This record was unbeaten for 58 years until now, as this student article presents a system that surpasses Brown’s work by 25%. 

Read the article summarizing the research work here.

Submissions received throughout the program are under review by the jury. Stay tuned to know who makes it to the list of winners.

Till then, check out the featured UTEP articles by visiting these links:

• UTEP Interview: Building the Worlds Fastest Hyperloop Tunneling Robot with Swissloop Tunneling

Here are the articles summarizing the previous UTEP submissions:

• University Technology Exposure Program 2022: June Update

• University Technology Exposure Program 2022: May Update

• University Technology Exposure Program 2022: April Update

• University Technology Exposure Program 2022: March Update

• University Technology Exposure Program 2022: February Update

About the University Technology Exposure Program 2022

Wevolver, in partnership with Mouser Electronics and Ansys, is excited to announce the launch of the University Technology Exposure Program 2022. The program aims to recognize and reward innovation from engineering students and researchers across the globe. Learn more about the program here.