Building a Culture of Equity, Diversity, Inclusion and Social Justice at a Community College

Over the past number of years, it has become apparent that Canada is facing a significant skilled labour shortage. As the world emerges from the Covid-19 pandemic, the pressure to train and hire skilled trades workers has only increased; in order to fill the growing labour gap, intentional measures are needed to attract and retain a more diverse group of students. This organizational improvement plan aims to capitalize on a recent strategic plan and its central commitment to equity, diversity, inclusion and social justice. Through a case study focused on balanced enrolment by gender in trades training, this document considers a number of potential solutions before focusing on policies and practices related to recruitment, application, and admission of women into two trades programs. Principles of transformational leadership and transformative leadership theory are entwined with a change roadmap and a change process of appreciative inquiry to create a matrix for change at College on the Water (a pseudonym). A project community map is created and key responsibilities are outlined, as are the critical elements of a communication plan. Lessons learned from this case study can be applied to other programs that are inequitable in representation, whether by gender, socioeconomic status, race, or other differentiation. The immediate goal is to ameliorate an imbalance in student enrolment, and the larger goal is to help the institution’s social justice focus and responsibilities progress. To this end, a global benchmarking tool will be used to measure the institution’s current state and to set a pathway for a better future

Exploring the use of machine learning and explainability in Marketing Mix Modeling

[EN] Marketing Mix Modeling (MMM) employs statistical techniques, typically linear regressions, to assess the impact of advertising expenditure on sales. Despite advancements in statistics and machine learning, the field of MMM has remained relatively unchanging due to a few reasons: (1) its primary focus on practical business applications, (2) the proprietary nature of MMM solutions by specialized companies, and (3) the difficulty in interpreting complex models beyond linear regressions for business purposes. Recently, there has been increased emphasis on the interpretability of complex machine learning models. To address this, model explainers such as SHAP have been introduced, enabling the application of non-linear machine learning algorithms in the realm of MMM. This provides a solution to the various issues associated with traditional MMM methods, including variable interactions, non-linear relationships, and interpretability. This presentation outlines a method for incorporating machine learning algorithms with explainability techniques in the context of MMM in the retail industry.Kisilevich, S.; Herrmann, M. (2023). Exploring the use of machine learning and explainability in Marketing Mix Modeling. Editorial Universitat Politècnica de València. 235-236. http://hdl.handle.net/10251/20170023523

ДИФФЕРЕНЦИАЛЬНАЯ ДИАГНОСТИКА ОКРУГЛЫХ ОБРАЗОВАНИЙ В ЛЕГКИХ: ОТ ТУБЕРКУЛЕЗА К ЭХИНОКОККОЗУ

One of the significant problems in pediatrics remains tuberculosis in children and adolescents. Particular attention in the verification of the radiological syndrome, as a “rounded” shadow, is given to tuberculosis. This is not always justified. Echinococcosis is a parasitic disease of cyclic nature, affecting vital organs, including the lungs. One of the radiological manifestations of echinococcosis in the lungs is a rounded shadow syndrome, which requires a multidisciplinary approach to diagnosis.Tuberculoza la copii și adolescenți rămâne una dintre problemele semnificative ale pediatriei. O atenție deosebită în verificarea sindromului de raze X al umbrei „rotunde” este acordată tuberculozei, ceea ce nu este întotdeauna justificat. Echinococoza este o boală parazitară de natură ciclică care afectează organele vitale, inclusiv plămânii. Una dintre ma- nifestările radiografice ale echinococozei în plămâni este sindromul umbrei rotunde, care necesită o abordare integrată în diagnosticul bolilor.Одной из значимых проблем педиатрии остается туберкулез у детей и подростков. Особое внимание при верификации рентгенологического синдрома «округлой» тени уделяется туберкулезу, что не всегда обосновано. Эхинококкоз – паразитарное заболевание цикличного характера, поражающее жизненно важные органы, в том числе и лёгкие. Одним из рентгенологических проявлений эхинококкоза в легких является синдром округлой тени, требующий комплексного подхода в диагностике заболеваний

САНАТОРНО-КУРОРТНАЯ ПУТЕВКА КАК ПЕРВИЧНЫЙ УЧЕТНЫЙ ДОКУМЕНТ

Purpose. The goal is to study the organization of the correct document flow of spa-resort vouchers taking into account the introduction of strict reporting forms as a payment document and the validity of the application of value-added tax exemption.Methodology. The article used monographic, economic-statistical, abstract-logical research methods; used the personal experience of the authors as auditors, consultants on the subject.Results. The necessity of introducing the form of forms of a sanatorium-resort voucher and coursework, the determination of the minimum duration of a voucher, the possible inclusion in the state program “Electronic voucher” is revealed.Practical implications. The results obtained should be applied by sanatorium-resort organizations and recreation organizations.Цель – изучение организации правильного документооборота санаторно-курортных путевок с учетом введения бланков строгой отчетности как платежного документа и обоснованности применения освобождения по налогу на добавленную стоимость.Метод или методология проведения работы: в статье использовались монографический, экономико-статистический, абстрактно-логический методы исследования; использован личный опыт авторов в качестве аудиторов, консультантов по рассматриваемой тематике.Результаты: выявлена необходимость введения формы бланков санаторно-курортной путевки и курсовок, определения минимальной продолжительности путевки, возможного включения в государственную программу «Электронная путевка».Область применения результатов: полученные результаты целесообразно применять санаторно-курортным организациями и организациями отдыха

A conceptual framework and taxonomy of techniques for analyzing movement

Movement data link together space, time, and objects positioned in space and time. They hold valuable and multifaceted information about moving objects, properties of space and time as well as events and processes occurring in space and time. We present a conceptual framework that describes in a systematic and comprehensive way the possible types of information that can be extracted from movement data and on this basis defines the respective types of analytical tasks. Tasks are distinguished according to the type of information they target and according to the level of analysis, which may be elementary (i.e. addressing specific elements of a set) or synoptic (i.e. addressing a set or subsets). We also present a taxonomy of generic analytic techniques, in which the types of tasks are linked to the corresponding classes of techniques that can support fulfilling them. We include techniques from several research fields: visualization and visual analytics, geographic information science, database technology, and data mining. We expect the taxonomy to be valuable for analysts and researchers. Analysts will receive guidance in choosing suitable analytic techniques for their data and tasks. Researchers will learn what approaches exist in different fields and compare or relate them to the approaches they are going to undertake

Analysis of user generated spatio-temporal data : Learning from collections of geotagged photos

Large collections of geotagged photos publicly accessible through photo-sharing web sites such as Flickr or Panoramio, present an opportunity for the entire Internet community to access the wealth of visual and textual data stored on photos. At the same time, it presents the challenge of how to efficiently and effectively turn this data into information about locations of interest and people's movement preferences.Geotagged photos can be viewed in a dual way: as independent spatio-temporal events and as trajectories of people in the geographical space. These two views imply, however, two different approaches to an analysis that will yield different kinds of valuable knowledge about places as well as people. In this thesis, geotagged photos are therefore primarily regarded in the context of (event-based) movement rather than multimedia content and present several exploratory and analytical techniques corresponding to event-based and trajectory-based movement analysis.Moreover, geotagged photos are contextually rich data that combine geographical information about the places where photos were taken with textual information. This information includes for the most part titles and tags attached to photos by owners of these photos as well as comments that can be written by other users. This unique combination is what makes the geotagged photos special for analysis of people's movement and behavior in contrast to the general purpose spatio-temporal data like GPS-based records. Analysis of spatio-temporal data is challenging since it always requires combining different analytical methods like geocomputation and geographical analytics, algorithms like aggregation and clustering, technologies in which the data is appropriately visualized on the map and scalable with the amount of the data.Taking into consideration the above mentioned aspects, we propose in this thesis a systematic approach to an analysis of people's movement and events using geotagged photos. We make contributions in four main research areas: (1) geovisual analytics - interactive exploration of patterns of people's trajectories and interesting routes that they take during photographing; (2) data mining - development of techniques and algorithms for discovery of attractive areas and finding frequent sequential patterns of people's movement; (3) text mining and computational linguistics - development of approaches for extraction and analysis of comments that people write for photos, and (4) systems engineering - development of a GIS-based tool to facilitate handling of geotagged photos. Moreover, while some of the approaches were targeted towards the imaginary domain expert, some approaches proposed in this thesis were deliberately usercentered in order to demonstrate how the proposed approaches can be used in user-centered scenarios if implemented and delivered by a service provider. Finally, the research demonstrated in this thesis will be useful for practical reasons, such as future research targeting people's preferences for urban locations, landmarks and corresponding travel itineraries. It may also benefit (research) areas like city promotion and advertising, public safety, tourism, and civic minded activities

Analysis of Privacy in Online Social Networks of Runet

In recent years, social networking sites (SNSs) gained high popularity among Internet users as they combine the best of both worlds: befriending people outside real life situations and staying in touch with people already known. An important aspect of any SNS is user profiles, which allow users to virtually publish anything about themselves, including highly personal or sensitive information. With the inception of SNSs, the problem of personal information disclosure and privacy implications has turned into a serious issue. While privacy issues in SNSs have been extensively analyzed in the past five years showcasing flagships of “western ” SNSs like Facebook and MySpace, SNSs that target mainly Russian speaking audiences are not yet analyzed and demand investigation. The goals of this paper are twofold: (1) to raise the awareness of the public to the problems of information revelation by studying the amount and type of information disclosed by users of Runet (Russian Segment of the Internet) SNSs (2) to compare our findings to the results of previous studies in the context of “western ” SNSs. We investigate different aspects of information revelation of more than 30 million user profiles collected from five Runet SNSs considered in this paper. In addition, we conducted a survey among a Russian speaking population to assess both the level of awareness of the privacy issues and the level of trust, and compared the results to previous studies. While the results indicate that Runet users tend to disclose less information and are more concerned about privacy implications, there is still a substantial gap between western and Runet SNS providers in understanding of privacy implications and implementation of security measures, which leads to exposure of extensive amounts of personal information

Exploring country level gender differences in the context of online dating using classification trees

The key component of Social Networking Sites (SNS), gaining increasing popularity among Internet users, is the user profile, which plays a role of a self-advertisement in the aggregated form. While computer scientists investigate privacy implications of information disclosure, social scientists test or generate social or behavioral hypotheses based on the information provided by users in their profiles. Statistical analysis of the SNS phenomenon often is performed using only a very small sample of information extracted from a particular SNS or by interviewing students from a particular university. In this paper, we apply classification algorithm to a large-scale SNS dataset obtained from more than 10 million public profiles with 50 different attributes extracted from one of the largest dating sites in the Russian segment of the Internet. In particular we build gender classification models for the residents of the most active countries, and investigate the particular differences between genders in one country and the differences between the same-genders in different countries. The preliminary results are reported in this paper. To the best of our knowledge, this is the first attempt to conduct a large-scale analysis of SNS profiles and compare gender differences on a country level

Exploring gender differences in member profiles of an online dating site across 35 countries

Online communities such as forums, general purpose social networking and dating sites, have rapidly become one of the important data sources for analysis of human behavior fostering research in different scientific domains such as computer science, psychology, anthropology, and social science. The key component of most of the online communities and Social Networking Sites (SNS) in particular, is the user profile, which plays a role of a self-advertisement in the aggregated form. While some scientists investigate privacy implications of information disclosure, others test or generate social and behavioral hypotheses based on the information provided by users in their profiles or by interviewing members of these SNS. In this paper, we apply a number of analytical procedures on a large-scale SNS dataset of 10 million public profiles with more than 40 different attributes from one of the largest dating sites in the Russian segment of the Internet to explore similarities and differences in patterns of self-disclosure. Particularly, we build gender classification models for the residents of the 35 most active countries, and investigate differences between genders within and across countries. The results show that while Russian language and culture are unifying factors for people’s interaction on the dating site, the patterns of self-disclosure are different across countries. Some geographically close countries exhibit higher similarity between patterns of self-disclosure which was also confirmed by studies on cross-cultural differences and personality traits. To the best of our knowledge, this is the first attempt to conduct a large-scale analysis of SNS profiles, emphasize gender differences on a country level, investigate patterns of self-disclosure and to provide exact rules that characterize genders within and across countries