Browsing by Author "Maciag, Timothy"

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Open Access
2011 University of Regina Graduate Students' Association Student Research Conference Abstracts
(University of Regina Graduate Students' Association, 2011-04-01) Maciag, Timothy; Dosselmann, Richard; Starks, Elizabeth
On behalf of the University of Regina Graduate Students' Association executive I would like to welcome you to the sixth annual Student Research Conference, titled Creating Community Consciousness: Students Expanding Knowledge & Creativity. The aim of the conference has remained the same as in previous years ~ to provide a platform for students to share their academic knowledge and creative works with the academic and local community. In helping organize this annual event I have had the unique perspective of witnessing first-hand the excitement of students in all disciplines ~ eager to come together and share their knowledge and creative works. It truly is something great. I wish to thank the university community and all of the sponsors for supporting this year's conference. I also wish to thank the many volunteers who have helped in organizing the event. I specifically wish to thank Richard Dosselmann, Elizabeth Starks, and Bahman Ahmadi for their ongoing help and support. I also wish to thank all of the members of the GSA executive: Adam Belton, Jane Rose, Emenike Ezechikwelu, Adewale Babatunde Aderoju, and Dorothea Wojtowicz, all of whom have helped make this conference possible. I wish to provide a special thanks to Bill Brown and the executive members of the GNU/Linux Open Source Users of Regina, Saskatchewan (LOSURS). With their participation in this year's event, it is my hope that it is the beginning of more collaborative efforts between university students and local community groups. I also wish to thank our two keynote speakers: Robert J Sawyer and Dr. Richard Stallman for their participation. Both of these speakers are people I admire very much and I am grateful I was given the opportunity to bring them to Regina to speak at this event ~ helping expose their work to the academic and local community. I hope that you take this opportunity to explore the research and creative works throughout the 2 day event and engage the presenters with questions and comments.
Open Access
Cellular network KPI prediction on simulated 5G-NR V2N traffic dataset using machine learning
(Faculty of Graduate Studies and Research, University of Regina, 2023-03) Pusapati, Suryanarayanaraju; Peng, Wei; Khan, Sharfuddin; Maciag, Timothy; Wang, Zhanle
The arrival of 5G has brought a promise of better connectivity for users, but also a challenge for cellular networks to maintain high-quality service and energy efficiency. To optimize the network and meet user demands, a resource management system is used to allocate resources in the 5G Radio Access Network (RAN). However, manual tuning of this system is complex and time-consuming. By predicting the future behavior of Network Key Performance Indexes (KPIs) of the 5G network using Artificial Intelligence (AI) and its subfield, Machine Learning (ML), this study can automate the operations of the Resource Management system, improve resource allocation, and satisfy QoS requirements while optimizing energy consumption. However, to develop a better performing ML model, a high-quality dataset is essential. Since there is a lack of open datasets available on 5G systems, many researchers rely on synthetically generated datasets. This thesis work utilized 5G simulation tool to simulate 5G New Radio (NR) Vehicle-to-Network (V2N) communication using OMNeT++ and SUMO simulators. The NR V2N communication was simulated in a Regina downtown scenario using the proposed simulation framework, and the simulation results were processed using the developed new_df Python module into synthetic datasets that were validated by comparing with technical specifications to ensure their quality. The synthetic datasets were then used to develop proposed Network KPI prediction models using ML. Three ML models are trained and tested, which can predict multiple KPIs, bi-directional Signal to Interference and Noise Ratio (SINR) and classify uplink Channel Quality Indicator (CQI) respectively. The multi-output regression models have shown outstanding performance with MSE as low as 0.002, and the multi-class classification model has a high accuracy. In summary, this study contributes to the development of efficient and automated Resource Management systems for 5G networks using AI and ML techniques. An open source V2N simulation framework was developed using OMNeT++ and SUMO simulators that can simulate 5G-NR V2N communication in a realistic urban scenario. Moreover, a new_df Python function was developed for processing simulation results into an aggregated dataset and spatiotemporal dataset, providing a high-quality dataset that can be used to train and test ML models for predicting Network KPIs of the 5G network.
Open Access
Customer satisfaction as a critical success factor for ERP design
(Faculty of Graduate Studies and Research, University of Regina, 2022-12) Plunkett, Jamie Oren; Gelowitz, Craig; Maciag, Timothy; Laforge, Paul
Enterprise Resource Planning (ERP) has been an important tool over the last number of years in managing business processes for large corporations. An ERP is a software system that links various departments and allows them to work together through a centralized software system. An example would be a hotel management ERP where multiple departments such as accounting, front desk, housekeeping and human resources share vital business information. However, more research needs to be done on ERP initiatives for small to midsized enterprises (SME) to also help them reach their productivity goals effectively. This is, in part, the motivation behind this thesis. This thesis first looks at various methodologies and metrics that can help inform the design and implementation of an ERP. This thesis also incorporates customer satisfaction as a Critical Success Factor (CSF) and metric for analyzing an SME’s ERP design and implementation. Prior to the design and implementation phase, gathered quantitative customer experience data is used as a guide to inform the design criteria with respect to the implementation of an ERP for an SME. This thesis demonstrates that ERP design and implementation concepts can utilize the sentiment of an SME’s customer base to subsequently help key issues get resolved in the ERP design process which may also lead to a successful ERP implementation for an SME. In this thesis, an ERP is designed and developed that is informed through customer satisfaction as a CSF in addition to other techniques such as the As-Is, To-Be and Balanced Scorecard methodologies [1]. Customer Satisfaction is used quantitatively before and after the design and implementation of an ERP to both inform and evaluate the success of the ERP design and implementation for an SME.
Open Access
Designing open-source, cross-platform user interfaces for improving home care
(Faculty of Graduate Studies and Research, University of Regina, 2024-04) Rhythm, S M Rizwan Islam; Maciag, Timothy; Sharma, Yogesh
Long-term care (LTC) facilities, once the primary source of healthcare for aging citizens face critical shortages that are increasing due to heightened demand for healthcare services. In Canada, LTC facilities struggle to meet the growing needs, which have only increased since the COVID-19 pandemic. As a result, there is a shift in preference among aging citizens towards staying in their homes, emphasizing the importance of robust home care (HC) systems. Local data suggests that by 2038, over half of Saskatchewan's population is estimated to be 55 and older, emphasizing the pressing local demands. Furthermore, statistics released in 2020 indicate around 11 percent of Canadians in LTC facilities could have stayed at home with appropriate care. Effective and effcient HC support can enrich lives, foster independence, and support families. However, the increasing global demand for healthcare services challenges seamless HC service delivery. This research focuses on augmenting HC interactions through digital technologies. Given the existing demand, there is a need for improvement in HC service delivery and data, information, and knowledge management, particularly in handling digital records and effciently documenting HC activities. Software technologies similar to electronic health records (EHRs) and electronic medical records (EMRs) offer promising solutions that enhance administrative effciency. However, challenges persist in adapting these technologies to meet the unique needs of HC, including concerns over proprietary systems, patient data management, and software system security. The primary focus of this research lies in the front-end design of user-centric software systems to advance HC experiences. Designing a user interface (UI) that prioritizes utility, usability, and delightfulness is essential. By incorporating User Experience (UX) principles, the research aims to create a exible, community-centred software system that improves HC operations and management. This research investigates the challenges in HC service delivery management, particularly from the administration and service provider perspective. Partnering with Eden Care Communities, a local Saskatchewan-based HC organization, a software system is engineered to explore how digital technologies can improve various aspects of HC from a people, process, and technology lens. The collaborative processes that guide the software engineering work, the engineering work, and the outcomes of the engineered solution are described. Future work is also discussed.
Open Access
Electrical Considerations for Siting of a Small Modular Reactor: A Case Study of Saskatchewan, Canada
(Faculty of Graduate Studies and Research, University of Regina, 2019-05) Shrestha, Reena; Al-Anbagi, Irfan; Laforge, Paul; Bais, Abdul; Wagner, Douglas; Maciag, Timothy
Distributed generation resources (DGs) can help to mitigate the growth in electricity demand and the large burden on the central grid by reducing transmission and distribution power losses. DGs are typically small-scale power sources that can produce electricity close to the distribution network. Choosing a suitable site for a new DG is a critical step in DG planning for long-term e cient power generation. Locating optimal sites for DGs involves consideration of many factors (e.g., such as economic, social, environment, geographic, availability of electrical infrastructure, etc.). Solar panels, micro wind turbines, small hydropower units, fuel cells and Small Modular Reactors (SMRs) are some examples of DGs used in power systems. SMRs are a unique alternative to traditional small fossil fuel power plants. Saskatchewan (SK), Canada has been selected as a case study for the selection of the location of SMRs in this thesis. SK can bene t from SMR power generation because its remote northern communities can be best served by small distributed resources such as SMRs. In addition, based on the load centres and existing power grid infrastructure, SMRs could be more suitable when compared to large power plants for SK. In this thesis, an Analytical Hierarchy Process (AHP) and Fuzzy AHP (FAHP) algorithm are implemented to develop a ranking system to choose proper sites for SMR power generation units in SK. Electrical and non-electrical loads, existing and retiring generation, transmission lines, and switching stations in location-dependent scenarios are considered to determine preferable sites. An improved result is obtained by implementing a fuzzy logic-based AHP algorithm that deals with the linguistic vagueness and uncertainty for siting of SMRs in SK. Renewable energy sources such as wind and solar require increased load-following capabilities with respect to the remaining conventional generation. In this thesis, the top two locations from the results of AHP and FAHP are validated for SMR siting using PowerWorld Simulator (PWS) to show the support of intermittent generation and non-electrical applications. The existing power system network of the Provincial Electrical Utility (PEU), SaskPower is modelled with the integration of an SMR in these two areas to analyze the system behavior of an SMR. The growing integration of intermittent renewable energies is a motivating factor to consider SMRs, which are demand-following in nature; any excess power can also be utilized for co-generation purposes. In this thesis, an assumption that the surplus power from SMRs is utilized for industrial applications in the selected high ranked locations is made. Additionally, the quality of support for non-electrical applications with the integration of SMR to both wind and solar energy is compared.
Open Access
Kiannet: An attention-based CNN-RNN model for violence detection
(Faculty of Graduate Studies and Research, University of Regina, 2024-04) Ahmadi Vosta Kolaei, Soheil; Yow, Kin-Choong; Chan, Christine; Maciag, Timothy; Zilles, Sandra; Eramian, Mark
Violent behaviour poses a significant risk to societal stability and public safety. As part of proactive strategies to counteract this threat, many organizations and institutions have implemented surveillance systems to monitor and identify potential violent instances. Nevertheless, manual review and analysis of vast surveillance footage can be a daunting and error-prone task for human operators, necessitating the advent of automated systems for efficient and precise violence detection. This study introduces a novel approach for violence detection composed of a CNNRNN structure based on an attention mechanism for binary and multi-class classification of abnormal behaviours. We called our proposed model KianNet because Kian is the name of an intelligent innocent murdered in a violent incident, and we chose his name as a representative of all people who suffered from violent behaviours. In this technique, a CNN-RNN structure is applied to an input video to extract features from a sequence of frames and by adding a combination of Multi-Head Self-Attention (MHSA) and ConvLSTM layers, it can detect the violent event and determine the type of the observed anomaly. The key to KianNet’s performance is implementing the MHSA layer, which allows the model to focus on specific spatiotemporal regions of relevance, improving its capacity to differentiate between normal and violent events. Consequently, the MHSA layer boosts KianNet’s discriminatory power, enabling it to discern violent incidents from regular activities better. Through empirical evaluations, KianNet has proven its superior performance in violence detection tasks. Our findings reveal that KianNet outperforms its closest competitors’ accuracy by roughly 10 percent. This substantial performance margin substantiates the robustness and reliability of KianNet, cementing its potential as an effective tool in automated surveillance systems for violence detection.
Open Access
Operationalizing Ethics in Food Choice Decisions
(Springer, 2014-06) Hepting, Daryl H.; Jaffe, JoAnn; Maciag, Timothy
There is a large gap between attitude and action when it comes to consumer purchases of ethical food. Amongst the various aspects of this gap, this paper focuses on the difficulty in knowing enough about the various dimensions of food production, distribution and consumption to make an ethical food purchasing decision. There is neither one universal definition of ethical food. We suggest that it is possible to support consumers in operationalizing their own ethics of food with the use of appropriate information and communication technology. We consider eggs as an example because locally produced options are available to many people on every continent. We consider the dimensions upon which food ethics may be constructed, then discuss the information required to assess it and the tools that can support it. We then present an overview of opportunities for design of a new software tool. Finally, we offer some points for discussion and future work.
Open Access
Performance Analysis of Received Signal Strength Indicator-Based Localization for Underground Mines
(Faculty of Graduate Studies and Research, University of Regina, 2021-04) Herzberger, Tessa Faith; Al-Anbagi, Irfan; Laforge, Paul; Maciag, Timothy
Wireless sensor networks (WSNs) have been implemented in a variety of scenarios, including tracking, smart grid, and equipment monitoring. Often times, devices in WSNs are required to know their locations with respect to other devices in the network. This act, known as localization, is the art of predicting the location of a device using anchor devices with known locations in the same network. Localization is essential for many critical industrial applications including underground mines, as the location of devices and employees is vital in helping to guarantee the safety of mining personnel. To the best of our knowledge, existing works have not yet performed extensive research into the use of numerical lters for localization accuracy enhancement. Other works have looked into the use of a speci c numerical lter, however none have covered all of the lters used in this paper. In this thesis, a WSN system that performs localization in an underground mine is proposed. This system uses the Zigbee communication protocol, received signal strength indicator (RSSI) measurements and the trilateration algorithm. The focus of the system is to maximize the accuracy of the predicted location by minimizing the radial error, which is the distance between the predicted location and actual location of a node. Point-to-point tests are performed to determine the best choice of hardware and RSSI model. These were determined to be Texas Instrument's (TI) CC2538 devices and the Piecewise RSSI model respectively. Next, trilateration experiments were performed using nodes containing the CC2538 devices positioned in a star topology. The localization results showed that the system was able to predict the location of a node with some error, which can be improved. Lastly, this thesis discusses the use of numerical ltering algorithms to enhance the accuracy of the predicted location by decreasing the radial error. These lters are as follows: the Statistical Average (SA) lter, the Gaussian lter, the Gaussian and Statistical Average (GSA) lter, the Kalman lter, the Kalman and Statistical Average (KSA) lter, as well as the Alpha-Trimmed Mean (ATM) lter.
Open Access
Regina Lawn Bowling Club Open-source Accessibility Project
(Faculty of Graduate Studies and Research, University of Regina, 2024-09) Watson, Brandon Scott Cooper; Marsh, Charity; Maciag, Timothy; french, Lindsey
This critical engagement paper supports and documents an interdisciplinary project, integrating maker culture, people-centered design, and community-based research to address key issues identified by the members of the Regina Lawn Bowling Club (RLBC) community, including concerns around the ability of the aging members to continue participating in the sport, potential for addressing social isolation, and other concerns related to health and wellness. The questions guiding my creative research were: (1) How could integrating maker culture, people-centered design, and community-based research address identified concerns by the RLBC such as isolation, engagement, and accessibility to continue play and social involvement?; and (2) What kinds of innovative technologies could we produce and build together to create sustainable social connections for the aging community at the Regina Lawn Bowling Club? With the support of the Regina Lawn Bowling Club community, (including consultation, collaboration, and user testing), I designed two devices: an inclusively designed music playing device called the User-Friendly Jukebox (UFJ) and an inclusively designed, electronic-based lawn bowling bowl distance measuring device called the Easy-Shot. This report will discuss the projects and the results of evaluation as a community-based project.
Open Access
Screen Space Reflection Techniques
(Faculty of Graduate Studies and Research, University of Regina, 2020-01) Beug, Anthony Paul; Butz, Cory; Hamilton, Howard J.; Gerhard, David; Maciag, Timothy
Ray tracing is a rendering technique in computer graphics that can simulate a variety of optical effects, such as reflection from smooth surfaces, refraction through transparent objects, and light scattering on rough surfaces. Ray tracing can produce visual realism of a higher quality than other rendering techniques, such as rasterization techniques, but at a much higher computational cost. Screen Space Reflection (SSR) is a group of approximation techniques that utilize data already generated by common rasterization techniques, such as deferred shading, to produce limited reflection effects. Most rasterization algorithms use two basic data structures, an image buffer storing the colour of a surface point visible from the camera at each pixel, and a depth buffer (or Z-Buffer) storing the depth from the camera to the corresponding surface point. For each surface point, SSR techniques generate a reflection ray and project the reflection ray onto the depth buffer. Values in the depth buffer along the projected path are compared with the depth of the reflection ray to determine a potential intersection. A traversal process along the projected path is necessary. If an intersection is found, the corresponding colour in the image buffer contributes to the reflection. Several SSR techniques exists. In this research, SSR techniques are defined using a common algorithm schema and five noteworthy SSR techniques including ray marching, digital differential analyzers (both conservative and non-conservative), and hierarchical depth buffers (both minimum and minimum-maximum) are implemented as instances of this schema for the purpose of performance analysis. In the performance analysis, the average GPU time for traversing a projected path in the depth buffer was recorded for each of the five SSR techniques on different testing scenes, different image resolutions, and under variable control parameters associated with each technique. The analysis shows a statistically significant difference in average traversal time between different SSR techniques for 98% of the test configurations. Visualizations are also generated to facilitate the analysis. Detailed analysis results are presented in the thesis