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Project Description:

A telemedicine app is designed to connect patients with suitable medical professionals based on the patient’s symptoms, needs, and availability. A well-designed telemedicine app will allow patients access to treatment without the need to manually search for a suitable doctor, and provides them a means of access to healthcare services without needing to leave their home. The app makes it easier and more convenient for patients to connect with the right providers by providing a web-based solution they can access from their mobile device or home computer.

Safe and convenient access to healthcare services is very important to Canadians. Ensuring a patient is connected with the correct medical professional is critical to minimize wait times for treatment, and to avoid the patient being needlessly redirected before receiving proper treatment. Furthermore, the COVID-19 pandemic has placed strain on the healthcare system, increased mental health burden on Canadians, and exacerbated the difficulty for patients to access necessary healthcare in person due to the safety measures meant to limit the spread of COVID-19.

This application simplifies the handoff to the correct healthcare professional by understanding the patient’s needs and assigning them a suitable doctor. This helps reduce strain on the healthcare system by minimizing unnecessary visits and making more efficient use of available doctors’ time. Since the application is a mobile app, patients are able to schedule appointments from home. All of these outcomes ultimately have the effect of minimizing face-to-face time with patients, and preventing patients from physically visiting healthcare facilities when unnecessary, thereby helping to reduce risk to healthcare professionals and the general public.

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Project Description:

The Ethical Benchmark has two major parts, the user view and the administrator view. The Admin is responsible for adding and editing content for the user to consume, as of this report, the content he is able to manage is mainly questionnaires which helps the user self-evaluate their company, and annexed content, which provides information regarding the subjects covered in the questionnaire. Additionally, the administrator is able to get metrics on how companies are performing, having the possibility to filter by fields such as location and industry.

Meanwhile, the user is able to consume the toolkit without having to create an account. As for the User, whenever he answers a question, he is presented with additional information on the subject he answered. At the completion of the questionnaire, the user is provided a benchmark which reflects every weak point the company has, as well as a comparison to the other user’s answers.

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Project Description:

Client of this project:
The client for this project is Trevor Jamison, is the owner of the RiverOak Skating Trail located in Ottawa. The trail meanders through Jamison’s property at RiverOak Estates, leading skates into his orchard and its snow-covered tree canopy.

Purpose of the project:
The purpose of this project is to upgrade the pre-existing app that was made by previous students and make it more user interactable. The app needs more interactive features and presents more professionalism to the users. The problem with this project is so far it did not launch yet, so the priority for this task is to launch the project first. The purpose of this project is to make the app more interactive and fun for the users so it will attract more guests to RiverOak.

Requirement for the Project:

The main priorities of the app are:
• Publishing the app.
• User accounts.
• Geotagged locations / QR codes.
• Promotional sales.
• Instant Messaging.
• Clean up the bottom toolbar of the app.
• Link buttons/UI to payment links on the website.

The Users of this Project:
•Random clients and previous customers will be the main users of this system. Although, anyone can use the system who wants to enjoy skating or any other event that the trail has to offer. The users will need to buy tickets for skating and other events either through the app or on the trailing site.
•The major functionality of this system is to make it more interactive and professional-looking. The app needs to be more user-friendly. The system should present a more beneficial application when it will be operated by the users.
•The skills levels that are required in order to use the app by the users are basic knowledge of using smartphone devices such as Android and iPhone.

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Project Description:

Many people are familiar with the term vicarious trauma, where victim service providers may be exposed to their clients’ trauma and in turn can feel the negative effects. This is what we think of oftentimes since these providers work day in and day out with people who have been through very traumatic events. We may think that their work can cause them to be pessimistic, depressed, and burnt out to the point where they leave the field. More recently, research has explored the idea of vicarious resilience since victim service providers may also witness their clients perseverance, strength, and growth. Through witnessing this, service providers may experience growth within themselves and benefits such as their physical and mental health improving, making proactive decisions, and forming connections with clients.

We are interested in examining how vicarious resilience plays a role in service providers’ lives, how their well-being is shaped with the help of their organization, and how systemic barriers can impact their work. Recently the Victimology Research Centre has launched a detailed survey on vicarious resilience and the survey has been distributed to over 700 service care providers across Canada. While we wait for more survey responses, our team has been working to gather relevant literature on vicarious resilience and what service providers need.

Just this month we held a national conference with victim service providers and volunteers where they were able to come together from across Canada. It started with a keynote speaker that discussed the notion of overwhelming trauma with ideas of how to cope and then we moved into discussion groups where the providers were able to talk about their own experiences. The questions examined any change they experienced due to exposure of their client’s trauma, how the COVID-19 pandemic has affected their work, and what resources they received from their organization that support their well-being. From this, specific themes are highlighted in relation to victim service providers and their vicarious resilience. The findings will be presented in a report and we aim to create a toolkit in the coming years. The goal of this project is to create a toolkit for service providers that will allow them to further develop vicarious resilience and maintain wellbeing.

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Project Description:

Caremada, an Ottawa-based company whose goal is to provide a user-friendly application that aims to establish connections between local caregivers and clients that require their services. Suki Lee, the leader of Caremada has tasked our team with the development of a recommender system to help caregivers decide on which jobs are best suited for them.

Our method of implementing a recommender system consists of several steps. First, data must be imported with the id of the caregiver, the user id, the users rating, and the username of the client that they rated. Then we preprocess this data to convert it into something the recommender can use, Next we create a model to represent the structure of the system. And train the model with a substantial amount of the converted data using the rest for validation. After the training and validation are complete the recommender system is finally ready to generate recommendations. When a caregiver is then passed into the recommender system it generates a list of the most recommended clients for that caregiver to choose from.

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Project Description:

Recording at home can be an annoying task if you live with roommates, pets, or in a busy neighborhood filled with loud traffic and sirens. Maybe you have a small recording area set up but it’s the middle of the summer and you would like some windows open. All that background noise can be hard to filter out without the proper equipment, and most software will degrade the quality of the audio. This was the pitch that our client had sent out. He was looking for a way to utilize a neural network to filter out unwanted background noises from his recordings. Whether it was a dog barking outside, or a fire truck going by, he wanted to be able to have clear, pristine recordings without all the hassle of manually cleaning the audio himself.

We took it upon ourselves to create an application that would do this for our client. Deciding to use the Rnnoise open source neural network as our base, we made a simple application that will accept audio files and put them through the neural network to filter out that unwanted background noise. We also implemented the functionality to convert mp3 and ogg-vorbis files to wav format, as well as stereo files to mono. Another script was added that will clean any audio spikes in the recordings from sudden noises.

While researching neural networks for this project we learned a lot about them and some of the tools out there to help create them, such as Keras API and Tensorflow. While we didn’t create a neural network ourselves, we were able to train one using Rnnoise, and trained different models with a slew of audio files to try and find the right combination for our project. We also learned python and how to connect python with other languages like C/C++ to call external functions from those files.

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Project Description:

contextere is transforming the future of work using AI to deliver actionable intelligence to the last tactical mile, empowering your workforce and improving asset performance. Our products and services enable our customers to navigate the fourth industrial revolution, and global skills gap successfully.

The Contextere AVA is an ML question-answering recommendation platform designed specifically for industrial technicians and operators. It uses Natural Language Processing (NLP) and neural networks to extract meaning from industrial enterprise data and determine the appropriate contextually relevant micro-guidance or insights. The AVA ‘bot app’ for Microsoft Teams enables users to ask questions and receive answers in real-time.

The Data Analytics Research Centre, a team, composed of Karim Shaloh, Research Assistant and the project lead, was formed for the sole purpose of accomplishing the client’s project brief. To manage the project’s scope, the client used an online management tool, Azure DevOps, to help alleviate stress, increase productivity and meet deadlines. Throughout the project, I learned how to communicate remotely and collaborate with an external team of developers. More importantly, I honed my python programming skills and learned Azure cloud services.

Although we faced many challenges along the way, it was an experience that deepened my knowledge regarding Machine Learning, NLP Projects, and cloud technologies. I am grateful to have worked with a fantastic client that was always understanding, supportive, patient and flexible with us.

Thank you to our client, the team from contextere, and Data Analytics Research Centre at Algonquin College for this incredible opportunity.

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Project Description:

The project that we worked on is the Tne Trader company. TnE Trader is a new business offering a platform to buy and sell used high-end tools. Their mission is to provide a straightforward process to buy and sell high-quality trades tools and equipment at a “fair market value.” They provide high-end used tools in an online marketplace, validate the quality of the sellers’ tools and equipment, fair market pricing for the quality of product, provide ongoing customer support and dynamic feedback on buyers/sellers.

Our client’s name is Mark Maclean, a business owner of Snap-on Tools, TnE Trader and a Multi-Franchisee from Ottawa. The client’s goal was to gain awareness to potential sellers and buyers and learn about his platform, to show that the new platform is reliable, to make potential users feel excited that there are high-end tools available on this website and to promote the platform through our video.

The problem that the client was facing was technicians spend thousands of dollars every year on high-end tools with no means of sourcing or selling high-end used tools. With a 20% market turnover rate, this allows for a large market of unsold high-end tools and equipment. Our team has created a video educating potential clients to trade used high-end automotive tools and equipment and to view the TnE Trader website as a “one-stop market platform” for all technicians to acquire and sell high-end tools and equipment.

Our team has gained great experience working together on our project. We have prioritized each member’s opinion and contributed work equally by having weekly team meetings and making every voice heard. Working for TnE Trader allowed us to gain networks with each other and our main goal was to satisfy our client at any cost. Additionally, we had weekly client meetings where we showcased each week’s progress through a presentation, which always has impressed our clients. Any suggestion that the client requested for change was met swiftly. Finally, in the end, we have created a motion graphic animated video for the TnE Trader to promote their platform which has matched and exceeded the expectations of the client.

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Project Description:

insightScope web application allows researchers to conduct and manage crowdsourced systematic and scoping reviews. It was started in 2018 by a team of Algonquin students from SLiDE led by Kevin Holmes and Sanket Patel, and researchers from CHEO led by Dr. Dayre McNally. Since its inception, insightScope strived to revolutionize the systematic review process. By using insightScope to build a large vetted team, the systematic review process is significantly accelerated from months and years to days and weeks.

During the last term, the insightScope team developed, refactored, tested, and deployed various features of the application. One major highlight is the significant enhancement of Data Abstraction. Data Abstraction occurs after full-text screening whereby the study team identifies and records relevant data, such as research design, type and number of participants, and patient outcome from the articles in the review. This involves collecting duplicate user responses to questions logically classified into study-type forms. Once reviewers have finished extracting data for an article, results are compared to find conflicts. The study team then resolves the conflicts, finalizing data elements for analysis and presentation of findings.

Early research from the team suggested that Data Abstraction by insightScope reduces the conflict resolution work by 50 percent. It increases the potential of running even more systematic reviews with better efficiency on our platform, increasing our prospects for scholarly output that drives evidence-based patient care.

The previous version of insightScope was limiting the types of data points that researchers could abstract as they relied on preconfigured forms. To overcome this, the team refactored the Data Abstraction to be configured by the principal investigator. Study type forms can now be created with multiple question types that accept answers in single or multiple choices, text, number, or date formats. One unique feature is the assignment of dynamic sub-questions that are toggled based on user selections. Further additions include help texts, comment enforcement, custom ordering of forms and questions, marking questions as not applicable, shared database of forms for reuse across multiple projects, assessments auto-save, etc.

 
The design and development phases of these features came with their own set of struggles and learning opportunities. An increase in customization surged logic complexity and edge cases which can potentially introduce bugs. One arduous thing was to devise a simple yet efficient conflict detection algorithm supporting all question types. Dramatic database changes could introduce anomalies. Through research, design sessions, demos, and close collaboration with the CHEO team, we delivered a robust solution. The team tackled a significant codebase refactor focusing on business logic abstraction, reusability, testability, maintainability and reducing technical debt. The team was provided with exciting opportunities to work with technologies like Amazon Web Services, Python data structures, HTML 5, CSS3, JavaScript, and open-source libraries like Draggable from Shopify.

We are proud of the accessible, user-friendly, and intuitive user interfaces that we developed. We were able to manage ourselves effectively using an agile development mindset. Throughout this process, we acquired many invaluable skills and experiences that aided us to accomplish our goals.

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Project Description:

Currently, the process of independently researching necessary safety, operational, and market-related information is laborious and time-consuming as explained by the client in personal correspondence; machinery safety and pricing information is accessed via internet searches or paper manuals. This causes inconvenience in that there can be delays when attempting to retrieve the information; the information is not at hand when needed; the information accessed may not be the most current information. Currently, there are some alternate websites that can be utilized to retrieve relevant information; however, they are not as convenient to use and do not encompass everything the client is looking for. In summary, there is no centralized system currently in place to address these concerns. The concerns are to be addressed by creating an app that can organize information about each machine, provide safety measures, and act as a central hub for woodworkers. There is a solution recommended for the client, which is to build a database desktop application to summarize all resources that the client needs.

This project has been conducted as a collaborative effort between a team of students from the Computer Engineering Technology–Computing Science program. This group of students possess specialized knowledge and technical programming skills in creating an interactive desktop application using Electron Framework and JavaScript-based programming language. The desktop software of our team has created will enable the client to precisely manage the woodworking tool resources, which enables classifying the fastest and most convenient catalogue and dividing the hazard levels of woodworking tools. The application will be compatible with Windows operating system and compatible with a future system update.

This desktop application implemented will:
• Allow data entry of an item manually
• Import and export data from Excel or CSV files
• Calculate the cost for a particular tool category
• Produce graphs and reports
• Print all the information related to a specific tool chosen by the client
• Export data to a usable file format such as ASCII TXT format, should the application become unusable due to age
• Be intuitive and easy to operate
• Be compatible with Windows OS and compatible with future OS updates
• Not be rendered obsolete by newer technologies for an extended period of time
• Contain search features to facilitate product information acquisition
• Quickly and accurately retrieve relevant safety and operational information
• Includes all required resources documentation of woodworking in Resources library
• Simplifying and easy to get started with User interface

The scope of this project is as follows: keyword query, produce graphs and reports, display specific item details, sum calculation of item costing, documentation of all woodworking tools description, a listing of woodworking tools, linked pictures, and application guides manual for operators. The application will not include features such as purchase and payment. Interpretation of literature content attributable to the source. The finished application will be given to Mr. Donaldson to address the current issues being faced. This project is not transferred to the public domain and will not be used in any commercial capacity.

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