The market for searching for food online is exploding. According to one expert at Google, “there are over 1 billion restaurant searches on Google every month” (Kelso, 2020). To capture this market and ride the general digital trend of internet personalization (as evidenced by Google search results, ads, YouTube and social media algorithms, etc), we created Munch to be an algorithm meant to help people find food they’ll love. <br/><br/>Munch offers the ability to search for food by restaurant or even as specific as a menu item (ex: search for the best Pad Thai). The best part? It is customized to your preferences based on a quiz you take when you open the app and from that point continuously learns from your behavior.<br/><br/>This thesis documents the journey of the team who founded Munch, what progress we made and the reasoning behind our decisions, where this idea fits in a competitive marketplace, how much it could be worth, branding, and our recommendations for a successful app in the future.

Every communication system has a receiver and a transmitter. Irrespective if it is wired or wireless.The future of wireless communication consists of a massive number of transmitters and receivers. The question arises, can we use computer vision to help wireless communication? To satisfy the high data requirement, a large number of antennas are required. The devices that employ large-antenna arrays have other sensors such as RGB camera, depth camera, or LiDAR sensors.These vision sensors help us overcome the non-trivial wireless communication challenges, such as beam blockage prediction and hand-over prediction.This is further motivated by the recent advances in deep learning and computer vision that can extract high-level semantics from complex visual scenes, and the increasing interest of leveraging machine/deep learning tools in wireless communication problems.[1] <br/><br/>The research was focused solely based on technology like 3D cameras,object detection and object tracking using Computer vision and compression techniques. The main objective of using computer vision was to make Milli-meter Wave communication more robust, and to collect more data for the machine learning algorithms. Pre-build lossless and lossy compression algorithms, such as FFMPEG, were used in the research. An algorithm was developed that could use 3D cameras and machine learning models such as YOLOV3, to track moving objects using servo motors and low powered computers like the raspberry pi or the Jetson Nano. In other words, the receiver could track the highly mobile transmitter in 1 dimension using a 3D camera. Not only that, during the research, the transmitter was loaded on a DJI M600 pro drone, and then machine learning and object tracking was used to track the highly mobile drone. In order to build this machine learning model and object tracker, collecting data like depth, RGB images and position coordinates were the first yet the most important step. GPS coordinates from the DJI M600 were also pulled and were successfully plotted on google earth. This proved to be very useful during data collection using a drone and for the future applications of position estimation for a drone using machine learning. <br/><br/>Initially, images were taken from transmitter camera every second,and those frames were then converted to a text file containing hex-decimal values. Each text file was then transmitted from the transmitter to receiver, and on the receiver side, a python code converted the hex-decimal to JPG. This would give an efect of real time video transmission. However, towards the end of the research, an industry standard, real time video was streamed using pre-built FFMPEG modules, GNU radio and Universal Software Radio Peripheral (USRP). The transmitter camera was a PI-camera. More details will be discussed as we further dive deep into this research report.

The market for searching for food online is exploding. According to one expert at Google, “there are over 1 billion restaurant searches on Google every month” (Kelso, 2020). To capture this market and ride the general digital trend of internet personalization (as evidenced by Google search results, ads, YouTube and social media algorithms, etc), we created Munch to be an algorithm meant to help people find food they’ll love. <br/>Munch offers the ability to search for food by restaurant or even as specific as a menu item (ex: search for the best Pad Thai). The best part? It is customized to your preferences based on a quiz you take when you open the app and from that point continuously learns from your behavior.<br/>This thesis documents the journey of the team who founded Munch, what progress we made and the reasoning behind our decisions, where this idea fits in a competitive marketplace, how much it could be worth, branding, and our recommendations for a successful app in the future.

The market for searching for food online is exploding. According to one expert at Google, “there are over 1 billion restaurant searches on Google every month” (Kelso, 2020). To capture this market and ride the general digital trend of internet personalization (as evidenced by Google search results, ads, YouTube and social media algorithms, etc), we created Munch to be an algorithm meant to help people find food they’ll love. <br/>Munch offers the ability to search for food by the restaurant or even as specific as a menu item (ex: search for the best Pad Thai). The best part? It is customized to your preferences based on a quiz you take when you open the app and from that point continuously learns from your behavior. This thesis documents the journey of the team who founded Munch, what progress we made and the reasoning behind our decisions, where this idea fits in a competitive marketplace, how much it could be worth, branding, and our recommendations for a successful app in the future.

Communication skills are vital for the world we inhabit. Both oral and written communication are some of the most sought-after skills in the job market today; this holds true in science, technology, engineering and mathematics (STEM) fields. Despite the high demand for communication skills, communication classes are not required for some STEM majors (Missingham, 2006). STEM major maps are often so packed with core classes that they nearly exclude the possibility of taking communication courses. Students and job seekers are told they need to be able to communicate to succeed but are not given any information or support in developing their skills. Scientific inquiry and discovery cannot be limited to only those that understand high-level jargon and have a Ph.D. in a subject. STEM majors and graduates must be able to translate information to communities beyond other experts. If they cannot communicate the impact of their research and discoveries, who is going to listen to them?<br/>Overall, the literature around communication in STEM fields demonstrate the need for and value of specific, teachable communication skills. This paper will examine the impact of a communication training module that teaches specific communication skills to BIO 182: General Biology II students. The communication training module is an online module that teaches students the basics of oral communication. The impact of the module will be examined through the observation of students’ presentations.

A large section of United States citizens live far away from supermarkets and do not have<br/>an easy way to get to one. This portion of the population lives in an area called a food desert.<br/>Food deserts are geographic areas in which access to affordable, healthy food, such as fresh<br/>produce, is limited or completely nonexistent due to the absence of convenient grocery stores.<br/>Individuals living in food deserts are left to rely on convenience store snacks and fast food for<br/>their meals because they do not have access to a grocery store with fresh produce in their area.<br/>Unhealthy foods also lead to health issues, as people living in food deserts are typically at a<br/>higher risk of diet-related conditions, such as obesity, diabetes, and cardiovascular disease.<br/>Harvest, a sustainable farming network, is a smartphone application that teaches and guides<br/>people living in small spaces through the process of growing fresh, nutritious produce in their<br/>own homes. The app will guide users through the entire process of gardening, from seed to<br/>harvest. Harvest would give individuals living in food deserts an opportunity to access fresh<br/>produce that they currently can’t access. An overwhelming response based on our user<br/>discussion and market analysis revealed that our platform was in demand. Development of a<br/>target market, brand guide, and full lifecycle were beneficial during the second semester as<br/>Harvest moved forward. Through the development of a website, social media platform, and<br/>smartphone application, Harvest grew traction for our platform. Our social media accounts saw a<br/>1700% growth rate, and this wider audience was able to provide helpful feedback.

A large section of United States citizens live far away from supermarkets and do not have an easy way to get to one. This portion of the population lives in an area called a food desert. Food deserts are geographic areas in which access to affordable, healthy food, such as fresh produce, is limited or completely nonexistent due to the absence of convenient grocery stores. Individuals living in food deserts are left to rely on convenience store snacks and fast food for their meals because they do not have access to a grocery store with fresh produce in their area. Unhealthy foods also lead to health issues, as people living in food deserts are typically at a higher risk of diet-related conditions, such as obesity, diabetes, and cardiovascular disease. Harvest, a sustainable farming network, is a smartphone application that teaches and guides people living in small spaces through the process of growing fresh, nutritious produce in their own homes. The app will guide users through the entire process of gardening, from seed to harvest. Harvest would give individuals living in food deserts an opportunity to access fresh produce that they currently can’t access. An overwhelming response based on our user discussion and market analysis revealed that our platform was in demand. Development of a target market, brand guide, and full-lifecycle were beneficial during the second semester as Harvest moved forward. Through the development of a website, social media platform, and smartphone application, Harvest grew traction for our platform. Our social media accounts saw a 1700% growth rate, and this wider audience was able to provide helpful feedback.

A large section of United States citizens live far away from supermarkets and do not have an easy way to get to one. This portion of the population lives in an area called a food desert. Food deserts are geographic areas in which access to affordable, healthy food, such as fresh produce, is limited or completely nonexistent due to the absence of convenient grocery stores. Individuals living in food deserts are left to rely on convenience store snacks and fast food for their meals because they do not have access to a grocery store with fresh produce in their area. Unhealthy foods also lead to health issues, as people living in food deserts are typically at a higher risk of diet-related conditions, such as obesity, diabetes, and cardiovascular disease. Harvest, a sustainable farming network, is a smartphone application that teaches and guides people living in small spaces through the process of growing fresh, nutritious produce in their own homes. The app will guide users through the entire process of gardening, from seed to harvest. Harvest would give individuals living in food deserts an opportunity to access fresh produce that they currently can’t access. An overwhelming response based on our user discussion and market analysis revealed that our platform was in demand. Development of a target market, brand guide, and full lifecycle were beneficial during the second semester as Harvest moved forward. Through the development of a website, social media platform, and smartphone application, Harvest grew traction for our platform. Our social media accounts saw a 1700% growth rate, and this wider audience was able to provide helpful feedback.