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Project Orange Lens

Project Orange Lens

Client Deanna Cormier
Professor(s) Reginald Dyer,
Program Computer Programming
Students May Aboalrejal​

Svetlana Dukkardt​

Khushboo Khushboo​

Tejus Revi​

Badriah Watt​

Project Description:

Deanna Cormier has been using a Facebook page for booking and updates, as well as Instagram for portfolio and gallery updates. However, in addition to having a social media presence she would like a professional website that will merge all functions into a single location. Our task was to make a website that included functionalities such as a calendar that displayed her current commitments and potential bookings, allows customers to book through the site, have her portfolio displayed through an online gallery, an “About Me” section, as well as social media links. We also added testimonials and photo highlights. This website now encompasses all the requirements from the client as well as all the features needed to stand out as a professional photography website.

Short Description:

The creation of a professional website that merged booking, portfolio, and customer experiences into one location.

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Project Orange Lens Project Orange Lens
Project Orange Lens Project Orange Lens

 

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BlitzTech – RCMPODVA

BlitzTech - RCMPODVA

Client Ed Strange
Professor(s) Todd Kelly,
Program Computer Engendering Technology – Computing Science
Students James Keir
Jason MacFarlane
Harrison Lee
Jarrod Mason
Daisy Rani Gupta
Eric Cousineau

Project Description:

The purpose of this report is to detail the extent to which Blitz Tech has accomplished within three months on the RCMPODVA website and app. The objective of the website was to reduce the dependence on php so that it would be easier for someone with no coding experience to update the website (https://ottawadivisionvaweb.site). The objective for the app was to be able to provide information about Ottawa veterans.

Short Description:

Convert a complex PHP-based website into a a format that is simple to maintain and to create a cross-platform mobile app to facilitate delivery of news, updates, and events to interested users.

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BlitzTech - RCMPODVA BlitzTech - RCMPODVA
BlitzTech - RCMPODVA BlitzTech - RCMPODVA

 

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The Performance Characteristics of PEX Hot-Water Systems

The Performance Characteristics of PEX Hot-Water Systems

Client Uponor Ltd.
Professor(s) Dr. Ali Elwafi, Dr. Maria Parra / Dr. Federico Fernandez
Program Building Science
Centre Manager:
Dr. Theodore Mirtchev

Investigators:
Dr. Ali Elwafi (Principal Investigator)
Dr. Maria Parra (Collaborator Professor)
Dr. Federico Fernandez (Collaborator prof.)
Mrs. Marialuisa Arnal
Mr. Karl Murray (Research Assistant)
Mr. Michael Stevens (Research Assistant)
Mr. George Zanetti (Research Assistant)
Mr. Leandro Carandina
Mr. Simon Hunt (Research Assistant)

Uponor Team
Mr. Kevin Wong (Canadian Codes Manager)
Mr. Craig Bradfield (Director of Marketing)
Mr. Joey D’Addese (Construction Services Supervisor)
Mr. Rene Paris (From klimar Agency)

Valuable Contributors
Mr. Alexander Yang (CRC Manager)
Mr. Shane Barteaux (Technologist)
Mr. Eduardo Milito (Professor)
Mr. Ramzija Sabotic (Senior Technologist)
Mr. Nicholas Boudreault (Technician B)

Project Description:

The project impacts advancement of propagating energy and water efficient piping system by helping the industrial partner validate the superior performance of new technology—both quantitatively and qualitatively. In particular, the project is enabling College students and professors to perform a range of applied research activities to test, categorize, and benchmark the performance of the company systems against conventional piping materials and their associated installations. The industrial partner has particular interest in assessing energy efficiency, thermal comfort, water quality and usage efficiency, regulatory compliance, product life-time, ease of installation, and ease of maintenance of its systems. The project will accomplish this by using scale models, full-scale test systems, and computer simulations. The ultimate aim of the project is to help our industry to understand the superiority of PEX technology.

This project is divided into three phases with the following objectives:

Phase I: Actual Installation for Hot Water Delivery (HWD) System: HWD system designed and built specifically to investigate water delivery time, water volume waste, water-flow and zero-flow heat loss, as well as the overall energy efficiency of the system. The 30.48 m (100 ft) real-life test system was developed to imitate the layouts and sizes that would be found in a residential condominium installation using Uponor’s PEX pipes, commercially available fittings and outlets to ensure that the data obtained is as consistent with real-world practices as possible.

The results showed UA values for flow condition heat loss and estimates of cooldown times for zero-flow conditions. In addition, the activation of the re-circulation system reduced the usable hot water delivery time by approximately 84% and consequently reduced the wastewater volume by about 76 %. These results suggest that the test systems and methodology that have been created for this project phase is able to provide realistic and accurate results.

Phase II: Hydronic heating system: Installation for hydronic heating system with a renewable energy source zone control for a typical space where measurable such as actual energy use, occupant comfort, insulations, optical windows with different renewable energy source can be evaluated.

Phase III: Preparation, surface engineering and material optimisation

1. Preparation: Securing the technical requirements and necessities including developing design experiment methodologies, standards, and weather data for the entire project.

Experimental work: Developing small scale models and metallographic preparation for samples to evaluate PEX surfaces, insulations and walls composites prior to and after being introduced to the thermal and environmental conditions.

2. Numerical Simulation: Creating Finite element models, using Ansys™ to test the response of the surfaces to mechanical scratch, mechanical indentation, freeze- thaw cycle prior to and after being exposed to the thermal and environmental conditions.

The project is funded by NSERC and the industrial partner (Uponor Ltd.) contributing cash and in-kind annually to this project for three years. Uponor is the world’s largest manufacturer of PEX piping with 100 years of expertise in piping and home building. This project is one of only four ARD-2 grants in Algonquin College’s history

Short Description:

The 3-year Uponor-Algonquin College project investigates the performance characteristics of water piping systems utilizing Uponor PEX (Cross-Linked Polyethylene) pipe. This project focus on hot water delivery and hydronic heating systems.

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The Performance Characteristics of PEX Hot-Water Systems The Performance Characteristics of PEX Hot-Water Systems
The Performance Characteristics of PEX Hot-Water Systems The Performance Characteristics of PEX Hot-Water Systems
The Performance Characteristics of PEX Hot-Water Systems  

 

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Cheetah Networks PulseView™ Solution

Cheetah Networks PulseView™ Solution

Client Cheetah Networks
Professor(s) Theo Mirtchev,
Program Data Analytics Center at Algonquin College
Students Ryan Arreola
Shuting Yang

Project Description:

The Cheetah Networks PulseView™ solution provides actionable, real-time, edge-to-cloud analytics for heterogenous loT network infrastructure. It delivers unprecedented visibility into the quality of experience of machines and users at the edge of the network. It allows users to have real-time visibility into the service or application experience, giving the user timely data to pre-empt and resolve network issues before they impact service. The PulseView™ solution also provides predictive analytics to forecast application needs and trends.

Our research for PulseView™ was split up between the front-end development for the user dashboard and outage maps design and functionality (Shuting), and the back-end development for network data collection, analysis, and aggregation (Ryan).

It is imperative for the PulseView™ solution to have a clean, stable, and highly functional UI that displays critical QoE and outage information to the customer. Shuting has aided Cheetah Networks immensely in meeting those critical needs during her time as a software engineer and research assistant.

What makes the PulseView solution unique from other network analytics software is its ability to provide real-time visibility and analytics of QoE from edge-to-cloud on a network. Ryan has been researching and developing the real-time data collection and aggregation components of the PulseDirector™ since September 2020 as a Cheetah Networks software engineer and research assistant.

During our time as software engineers and research assistants for Cheetah Networks, we learned many valuable lessons in engineering, design, initiative, and teamwork.
The development of large-scale and cutting-edge software is multi-faceted and being faced with the challenges that come with the rapid growth at Cheetah Networks is not an easy task. As students seeking to hone our craft, we had the opportunity to grow under pressure and under tremendous circumstances. We have learned and applied:
– Software design specification/review process
– Integration of new components with an existing and rapidly growing software
– Full-stack web development
– Networking protocols and standards
And much more through the guidance of our mentors and their trust in us to achieve and persevere through these challenging times.

Our progress with this research project has gone very well and we are looking forward to continuing our work on the future of network analytics with Cheetah Networks.

Short Description:

The CN PulseView™ solution provides actionable, real-time, edge-to-cloud analytics for heterogenous IoT network infrastructure, delivering unprecedented visibility into the quality of machines and users at the edge of the network.

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Cheetah Networks PulseView™ Solution Cheetah Networks PulseView™ Solution
Cheetah Networks PulseView™ Solution Cheetah Networks PulseView™ Solution
Cheetah Networks PulseView™ Solution Cheetah Networks PulseView™ Solution

 

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SLiDE Fall 2020

SLiDE Fall 2020 banner image.

Client Just Food / Wabano Fine Chocolates / Hidden Harvest
Professor(s) Kevin Holmes,
Program SLiDE / Social Innovation Lab
Students Molly Drinnan, Suhir Maghuor, Tori Sheen, Trevor Siu, Alexei Tipenko, Michaela Trottier

Project Description:

Our team has worked remotely with three local non-profit organizations to accelerate the slide into change. For Hidden Harvest (green), we evolved their website to guide their volunteers and connected them over social media with their users. For Just Food (multi-coloured earth tones), we developed a series of logos, designed an illustrated orientational map, and created a website for their new rental spaces to generate revenue that will continue to fund their initiatives. And for Wabano Fine Chocolates (colour-blocked rainbow), we established a brand image on social media, crafted a colourful logo, and launched a Shopify storefront to feed the world bite-sized culture. With the generous support of ICTC and IBM, we, as students, are able to gain valuable experience all while making contributions to the social sector in our community here in Ottawa. By supporting one, we support many. We are strong like a drum, eager like a violin, and innovative like the electric guitar. We inspire each other to compose great work. We are in tune with the world around us. We adapt our individual ways to create harmony. And we celebrate our victories triumphantly with emoji reactions over Zoom. We are SLiDE.

Short Description:

For Hidden Harvest, we evolved their website. For Just Food, we created a series of logos, an illustrated map, and developed a website. For Wabano Fine Chocolates, we created a brand image on social media, a colourful logo, and a Shopify storefront.

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SLiDE Fall 2020 project team. Just Food project.
Just food website redesign. Hidden groves website redesign.
Indigenous chocolate company website build.

 

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Automatic Drive-Thru for Restaurant

Automatic Drive-Thru for Restaurant
Client Restaurant Chains
Professor(s) Gino Rinaldi,
Program Electro-Mechanical Engineering Technician
Students Hiren Garambha
Heet Patel
Karthick Palanisankar

 

Project Description:

 

 

Short Description:

Drive-thru system that is aimed at making the food
serving aspect of a restaurant’s drive-thru an
automatic process. To build the prototype we are using
a web application, an Arduino uno board, few sensors and
couple conveyor belts.

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Victim Services Providers and Vicarious Resilience

Victim Services Providers and Vicarious Resilience

Client Victim Service Providers
Professor(s) Dr. Benjamin Roebuck, Diana McGlinchey
Program Victimology
Students Theresia Bedard, Amy Boileau, Connar Tague, Katherine Thompson

Project Description:

This project builds off from prior Algonquin College research in the area of resilience in victims of violence. The project will focus on the area of victim service providers. The purpose of the research is to review best practices, locate systemic barriers that service providers encounter when serving clients, develop tools that will help foster resilience for service providers, and to collaborate with service providers to identify what additional training will be helpful.
The methodology involves consultation with supporting victim service organizations to assess research needs and how we can make the project as useful as possible. Consultation will entail collaboration to build an online mixed-methods questionnaire, as well as focus groups and interview protocols.
Next, our collaborators from different sectors will distribute the online questionnaire to approximately 300-500 victim service providers from across Canada. We will also form 5-7 focus groups to generate group discussion about our research themes and to facilitate information sharing about innovative approaches in victims services. We will conduct in-depth interviews with victim service providers to find what is most effective for supporting victims of crime, systemic barriers that victims encounter, and to discuss service provider wellness.
The importance of this project is that it will allow examination of a broad range of services across multiple jurisdictions as prior research has primarily focused on one specific victimization type (e.g., domestic violence shelters). This project will also provide a needed update to our national data on victim service data in Canada as the last national survey on victim services in Canada happened in 2011/2012. We hope to co-construct a new understanding of vicarious resilience for service providers. We also have rare access to a large number of service providers across the country. Despite the rapid expansion of services for victims of crime, there has been limited research on the victim service sector in Canada and how service providers balance helping victims of crime navigate the complexities of violence while caring for their personal well-being.
We are actively working on creating and editing the questionnaire in SurveyMonkey and the next steps are to consult with our supporting organizations. The process of learning how to input questions onto SurveyMonkey was a slight learning curve, but we were able to navigate this process with relatively few difficulties. We received feedback from our lab director, Dr. Benjamin Roebuck, and incorporated any necessary changes. We have also been engaged in researching the relevant literature on service provider needs, vicarious resilience, and related concepts of vicarious resilience that are applicable to the study. We are also currently navigating the literature on current toolkits for compassion fatigue, burnout, vicarious resilience, and vicarious trauma for common themes and what was incorporated into creating these toolkits. This will help to create a foundation for the development of the toolkit for vicarious resilience that will ultimately be created from this project. We have collaborated together as a team by delegating tasks and communicating with each other about any struggles we have encountered during the process.

Short Description:

We are studying vicarious resilience in service workers, reviewing systemic barriers, developing tools for resilience and creating more training.

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Victim Services Providers and Vicarious Resilience Victim Services Providers and Vicarious Resilience
Victim Services Providers and Vicarious Resilience Victim Services Providers and Vicarious Resilience
Victim Services Providers and Vicarious Resilience Victim Services Providers and Vicarious Resilience

 

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Machine Learning Recommender Engine

Machine Learning Recommender Engine
Client Suki Lee
Professor(s) Todd Kelly,
Program Computing Engineering Technology
Students Hasan Al-Braich, Andy Ta, Alex Carrozzi, Tyson Budarick, Johnathan Mangos, Sharusshan Sinnadurai

 

Project Description:

 

Caremada provides an online service that connects caretakers with patients in need of specific or general care. Caremada’s service is similar to Uber in that service providers book their own time slots to work and clients find a suitable provider. Caremada has two core users; caregivers, and clients. Caremada categorizes its caregivers by the services they provide (caretypes). Carmada wished to implement machine learning tools to provide better assistance in finding caregivers and services to nearby patients.

Caremads is a startup company, meaning they have not gone to market yet, and Artificial Incoherence is called to implement a foundation to what will become a caregiver recommendation system used by their clients. With the current technology used, Caremada was struggling in connecting carertakes with patients. There was a lack of connection between the users, causing confusion. The requirement that the client needed was a proof of concept on a recommendation system, which they can later implement with their datasets.

This project was broken down into two phases. The first phase was the actual creation of a recommendation system. We first started a research phase, we went through different machine learning algorithms, to pick the best algorithm which would suit the clients needs. We ended with: Cosine Similarity, and Single Value Decomposition (SVD). This algorithm best works on “text base”, meaning we are able to make an accurate prediction based on the type of care the client chooses. The S.V.D algorithm makes predictions based on user-to-user interaction. This means, it makes predictions based on similar patterns of patients who have similar needs.
The second phase of the project was to implement a web interface to easily interact with the recommendation system, and to provide a visual outcome of the system . There is little use to have a recommendation system where the data cannot be easily seen by the user. We converted our recommendation system into a standalone server, where the web interface can communicate and retrieve the most suitable solution data for the user. We also implemented a database that would work hand in hand with our recommender system.

Throughout the progress of this project, this has provided us a chance to understand higher-level math that is involved, and new methodologies used by machine learning, as well as new software that is used in the industry. The final prototype was above and beyond the client’s expectations, as we were provided very little resources in data to begin with. We proved the data structure required for the startup company business model.

 

Short Description:

Web implementation of recommender engine powered by machine learning

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Machine Learning Recommender Engine Machine Learning Recommender Engine
Machine Learning Recommender Engine

 

 

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Species Protection (SW Application)

Species Protection (SW Application)

Client Claude Lloyd
Professor(s) Todd Kelley,
Program Computer Engineering Technology – Computing Science
Students – Qisen Wang (Team Leader)
– Justin Henwood
– Daniel Podsadowski
– Charles Guo
– Jeffrey McNally

Project Description:

This project is being created at the request and direction of Claude Lloyd. This project is not part of any existing company or entity, rather it is a personal project of Claude’s. For many years, Claude has had a dream to one day start a nonprofit with the main goal of making it easier for people to access information and get involved with endangered species. This idea stems from Claude’s passion for the protection and conservation of endangered species, whether they be here in Canada or anywhere else in the world. The purpose of the project is to create a Web Application (currently going by the name SW) that has two defining features. The first is a news feed that will provide up to date news and information about endangered species. This is designed as a way for Claude and others like him to get information about important subject matter to a wider audience in an easily consumable form. The second feature is a donation page which will allow users who create an account with the website to make monetary donations. These donations will go towards directly helping endangered species in a variety of ways.

Short Description:

Our goal for this application is to help increase awareness on endangered species. By helping them, we can continue appreciating what the earth has to offer.

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Species Protection (SW Application) Species Protection (SW Application)
Species Protection (SW Application) Species Protection (SW Application)
Species Protection (SW Application) Species Protection (SW Application)

 

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Blockchain Inventory Technology Solutions

Blockchain Inventory Technology Solutions

Client Piicomm (Richard Hagemeyer)
Professor(s) Jason Mombourquette,
Program Computer Technology Engineering – Computer Science
Students Alexander Elia, Corey Groenke, Ian Robinson, Conrad Simard, and Roy Sullivan

Project Description:

BITS integrates an inventory tracker with a ticketing system to deal with any serialized assets. This information is all stored as cryptographic hash’s encapsulated by blockchain security. Due to our initial client’s department dissolving, we have utilized the existing technology we created to assist in our new clients’ needs. As Richard Hagemeyer transition from our Algonquin College technology staff mentor to Piicomm employee, he saw further use for our project as an inventory system. This system would be highly beneficial to Piicomm as their customers require secure data validation from public and private healthcare, government, transportation and telecommunications. We have since designed our product around Piicomm’s needs, thanks to our weekly meetings with Richard’s input on beneficial integrations keeping security at the helm.

With the domino of Algonquin College’s Micro-Credential Division closure into our project left without a client, we scrambled for a new purpose. With Piicomm’s vision, we were about to pivot successfully. This pivot in our project’s scope meant we faced our most formidable challenge; produce a new product in under four months. Since our initial project was solely based on diploma blockchain technology, our remaining time was spend integrating this into a new user interface from both the provider and client sides. We wanted to ensure every need of our new client was met, knowing we had lost months of progress. This pressure fortified our team’s time management ability as all of our members were participating in a full course load while working full or part-time.

Having Piicomm’s acknowledgement of our progression was the reassurance that pushed us to finish the product to the state you see it in. As it stands, our BITS product will cease this semester. We hope that our final product draws enough attention from Piicomm to integrate into their software development group.

Short Description:

BITS utilizes the latest blockchain security to encapsulate a user-friendly asset tracking, management, and support solution. BITS is an extension solution to any asset management service provider that needs a secure way to track their technology.

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Blockchain Inventory Technology Solutions Blockchain Inventory Technology Solutions
Blockchain Inventory Technology Solutions Blockchain Inventory Technology Solutions

 

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