2,235 research outputs found
Protecting Privacy in Indian Schools: Regulating AI-based Technologies' Design, Development and Deployment
Education is one of the priority areas for the Indian government, where Artificial Intelligence (AI) technologies are touted to bring digital transformation. Several Indian states have also started deploying facial recognition-enabled CCTV cameras, emotion recognition technologies, fingerprint scanners, and Radio frequency identification tags in their schools to provide personalised recommendations, ensure student security, and predict the drop-out rate of students but also provide 360-degree information of a student. Further, Integrating Aadhaar (digital identity card that works on biometric data) across AI technologies and learning and management systems (LMS) renders schools a âpanopticonâ.
Certain technologies or systems like Aadhaar, CCTV cameras, GPS Systems, RFID tags, and learning management systems are used primarily for continuous data collection, storage, and retention purposes. Though they cannot be termed AI technologies per se, they are fundamental for designing and developing AI systems like facial, fingerprint, and emotion recognition technologies. The large amount of student data collected speedily through the former technologies is used to create an algorithm for the latter-stated AI systems. Once algorithms are processed using machine learning (ML) techniques, they learn correlations between multiple datasets predicting each studentâs identity, decisions, grades, learning growth, tendency to drop out, and other behavioural characteristics. Such autonomous and repetitive collection, processing, storage, and retention of student data without effective data protection legislation endangers student privacy.
The algorithmic predictions by AI technologies are an avatar of the data fed into the system. An AI technology is as good as the person collecting the data, processing it for a relevant and valuable output, and regularly evaluating the inputs going inside an AI model. An AI model can produce inaccurate predictions if the person overlooks any relevant data. However, the state, school administrations and parentsâ belief in AI technologies as a panacea to student security and educational development overlooks the context in which âdata practicesâ are conducted. A right to privacy in an AI age is inextricably connected to data practices where data gets âcookedâ. Thus, data protection legislation operating without understanding and regulating such data practices will remain ineffective in safeguarding privacy.
The thesis undergoes interdisciplinary research that enables a better understanding of the interplay of data practices of AI technologies with social practices of an Indian school, which the present Indian data protection legislation overlooks, endangering studentsâ privacy from designing and developing to deploying stages of an AI model. The thesis recommends the Indian legislature frame better legislation equipped for the AI/ML age and the Indian judiciary on evaluating the legality and reasonability of designing, developing, and deploying such technologies in schools
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
30th European Congress on Obesity (ECO 2023)
This is the abstract book of 30th European Congress on Obesity (ECO 2023
Making Connections: A Handbook for Effective Formal Mentoring Programs in Academia
This book, Making Connections: A Handbook for Effective Formal Mentoring Programs in Academia, makes a unique and needed contribution to the mentoring field as it focuses solely on mentoring in academia. This handbook is a collaborative institutional effort between Utah State Universityâs (USU) Empowering Teaching Open Access Book Series and the Mentoring Institute at the University of New Mexico (UNM). This book is available through (a) an e-book through Pressbooks, (b) a downloadable PDF version on USUâs Open Access Book Series website), and (c) a print version available for purchase on the USU Empower Teaching Open Access page, and on Amazon
No Walk in the Park: Urban Green Space Planning for Health Equity and Environmental Justice
Cities are complex socio-ecological systems where social, cultural, economic, political, and environmental factors influence health outcomes. With the global population growing increasingly urbanized, understanding how urban environmental conditions affect human health has become a topic of interest among researchers across multiple disciplines. Urban green spaceâwhich includes all vegetated land cover (e.g., trees, grass, shrubs, and woodlands), as well as any land uses with publicly available recreational amenities (e.g., parks, schoolyards, university campuses, and conservation areas) located within a cityâs geographic boundaryâprovides multiple health and health-promoting benefits. As such, disparities in park access, park quality, and green cover exposure (i.e., tree canopy and all other vegetation) are considered environmental justice and health equity issues. A wealth of recent research has found that, in general, increased access to parks has been associated with greater likelihood that residents will participate in physical activities and meet physical activity guidelines, and increased exposure to vegetated land cover has corresponded with improved psychological well-being and reduced risk of some mental illnesses. Yet, urban green spaces, and the health benefits such spaces afford, are not distributed equitably, and disparities in urban green space access and exposure based on race, ethnicity, or income represent environmental justice and health equity concerns.
In this dissertation, I build upon the existing body of knowledge to 1) investigate how issues of health have shaped urban landscapes in the United States and how the policies and decisions that have shaped urban landscapes have exacerbated health inequities, 2) build upon existing research at the nexus of health and urban green space to improve understanding of relationships between urban green space access/exposure, physical activity, and mental well-being, and 3) develop a method for identifying distributional justice concerns related to urban green space access/exposure to inform urban green space planning for health equity
Cross-Supply Chain Collaboration Platform for Pallet Management
Standardized pallets are an important factor in today's logistics sector to enable efficient processes in transport, storage and handling. By using an open exchange pool for pallets, additional opportunities arise for horizontal and vertical collaboration of various actors from different supply chains. The dissertation "Cross-Supply Chain Collaboration Platform for Pallet Management" investigates the potential of a digital platform for such cross-actor collaboration in pallet management. The designed platform has special mechanisms for balancing pallet debts that arise in the network and for joint planning of empty pallet flows. Therefore, the impact of the designed platforms on logistic processes, especially transports, is explored using simulation modeling. Furthermore, blockchain technology is investigated, which could be used for the implementation of the platform concept and could generate trust in a network of unknown actors. In this context, an empirical online-experiment is used to analyze in a differentiated way which specific features of the blockchain technology generate trust in technology and how these features interact with each other
ML-based data-entry automation and data anomaly detection to support data quality assurance
Data playsacentralroleinmodernsoftwaresystems,whichare
very oftenpoweredbymachinelearning(ML)andusedincriticaldo-
mains ofourdailylives,suchasfinance,health,andtransportation.
However,theeffectivenessofML-intensivesoftwareapplicationshighly
depends onthequalityofthedata.Dataqualityisaffectedbydata
anomalies; dataentryerrorsareoneofthemainsourcesofanomalies.
The goalofthisthesisistodevelopapproachestoensuredataquality
by preventingdataentryerrorsduringtheform-fillingprocessandby
checking theofflinedatasavedindatabases.
The maincontributionsofthisthesisare:
1. LAFF, anapproachtoautomaticallysuggestpossiblevaluesofcat-
egorical fieldsindataentryforms.
2. LACQUER, anapproachtoautomaticallyrelaxthecompleteness
requirementofdataentryformsbydecidingwhenafieldshould
be optionalbasedonthefilledfieldsandhistoricalinputinstances.
3. LAFF-AD, anapproachtoautomaticallydetectdataanomaliesin
categorical columnsinofflinedatasets.
LAFF andLACQUERfocusmainlyonpreventingdataentryerrors
during theform-fillingprocess.Bothapproachescanbeintegratedinto
data entryapplicationsasefficientandeffectivestrategiestoassistthe
user duringtheform-fillingprocess.LAFF-ADcanbeusedofflineon
existing suspiciousdatatoeffectivelydetectanomaliesincategorical
data.
In addition,weperformedanextensiveevaluationofthethreeap-
proaches,assessingtheireffectivenessandefficiency,usingreal-world
datasets
Security considerations in the open source software ecosystem
Open source software plays an important role in the software supply chain, allowing stakeholders to
utilize open source components as building blocks in their software, tooling, and infrastructure. But
relying on the open source ecosystem introduces unique challenges, both in terms of security and trust,
as well as in terms of supply chain reliability.
In this dissertation, I investigate approaches, considerations, and encountered challenges of stakeholders in the context of security, privacy, and trustworthiness of the open source software supply
chain. Overall, my research aims to empower and support software experts with the knowledge and
resources necessary to achieve a more secure and trustworthy open source software ecosystem. In the
first part of this dissertation, I describe a research study investigating the security and trust practices
in open source projects by interviewing 27 owners, maintainers, and contributors from a diverse set
of projects to explore their behind-the-scenes processes, guidance and policies, incident handling, and
encountered challenges, finding that participantsâ projects are highly diverse in terms of their deployed
security measures and trust processes, as well as their underlying motivations. More on the consumer
side of the open source software supply chain, I investigated the use of open source components in
industry projects by interviewing 25 software developers, architects, and engineers to understand their
projectsâ processes, decisions, and considerations in the context of external open source code, finding
that open source components play an important role in many of the industry projects, and that most
projects have some form of company policy or best practice for including external code. On the side of
end-user focused software, I present a study investigating the use of software obfuscation in Android
applications, which is a recommended practice to protect against plagiarism and repackaging. The
study leveraged a multi-pronged approach including a large-scale measurement, a developer survey, and
a programming experiment, finding that only 24.92% of apps are obfuscated by their developer, that
developers do not fear theft of their own apps, and have difficulties obfuscating their own apps. Lastly,
to involve end users themselves, I describe a survey with 200 users of cloud office suites to investigate
their security and privacy perceptions and expectations, with findings suggesting that users are generally
aware of basic security implications, but lack technical knowledge for envisioning some threat models.
The key findings of this dissertation include that open source projects have highly diverse security
measures, trust processes, and underlying motivations. That the projectsâ security and trust needs are
likely best met in ways that consider their individual strengths, limitations, and project stage, especially
for smaller projects with limited access to resources. That open source components play an important
role in industry projects, and that those projects often have some form of company policy or best
practice for including external code, but developers wish for more resources to better audit included
components.
This dissertation emphasizes the importance of collaboration and shared responsibility in building and maintaining the open source software ecosystem, with developers, maintainers, end users,
researchers, and other stakeholders alike ensuring that the ecosystem remains a secure, trustworthy, and
healthy resource for everyone to rely on
The Low Retention Rates of Nontraditional Students in Community Colleges: An Exploratory Case Study
The purpose of this exploratory case study was to explore nontraditional community college students\u27 experiences with student support services, their connectedness to the institutions, and their overall satisfaction with the institution. Tintoâs integration framework guided this study to test connectedness and its association with student retention rates. The central research question for this study was: What are nontraditional community college students\u27 perceptions of their overall satisfaction with the institution? The study was conducted at Waynesboro Community College in Waynesboro, NC. The purposeful sample size selected included 10 nontraditional students as research participants. The triangulation of data collection methods used in this study consisted of an interview, journal prompts, and a questionnaire. The data also included field notes and memos were also analyzed by finding commonalities in categories through coding, common themes, and phrases that were synthesized to address the research questions using exploratory analysis. Results indicated that nontraditional students do not feel connected to their institution and need support services that are unique to their needs. Four themes were identified in this study: 1) nontraditional student connectedness is not strong within the college, 2) nontraditional students need additional student support services, 3) nontraditional students with strong academic relationships are satisfied with their college experience, and 4) nontraditional students have personal factors that challenge their success in college. The sub-themes identified are nontraditional students need more knowledgeable and consistent faculty members and they have personal responsibilities that affect their success and need more social interaction in and out of the classroom
Generativity and Aspirational Dignity in Old Age - The Engagement of Older People for Younger People among Elite Professionals in Delhi and other Indian Cities
The dissertation titled, âGenerativity and Aspirational Dignity in Old Age â Engagement of Older People for Younger People among Elite Professionals in Delhi and other Indian Citiesâ is an empirical study that seeks to study occupational and personal potential of older people who chose to work after retirement. The study explores the questions on the extent to which the elderly can use their expertise and personal strengths in intergenerational relations, the extent to which elderly are actively involved in work post-retirement, the interest of the elderly in such an engagement and the importance of this commitment for the individual's emotional condition. The study also examines how far older people in the commitment described here see an opportunity to realize their personal criteria of a good life.
The theoretical framework of the study takes into consideration the fundamental and pertinent concepts of ageism, generativity, ageing with dignity, respect and social inclusion, cultural values and attitudes, health and wellbeing, meaningful involvement and productive ageing. In this study âGenerativityâ theory of human development stages by Erikson (1950/1963), by McAdams and de. St. Aubin (1992) and dignity of older people by Nordenfelt (2003) have been adopted to explain the meaningful engagement of older people in work environment in the changing intergenerational relations in urban Indian societies.
The research design chosen for the study is âdescriptiveâ as it involves quantitative data and qualitative data. The composites of independent variables in the form of scales are used to learn Generativity using Loyola Generativity Scale (LGS) and Well-being using Ryffâs Scale. Indepth interviews are conducted to understand respondentsâ and employersâ perspectives and views.
The study is based on the responses of 83 retired professionals who took up second inning and 14 select employers. The respondents were selected based on identified criteria and the supposition that they possess the required knowledge and experience and they will be able to provide information that is both detailed (depth) and generalizable (breadth) on motives for engagement in job post retirement. Also, who would make first cautious statements about possible influences of individual personality characteristics on this engagement. The samples were selected from services, public and industry sectors including startups from different zones in India. The sample was also designed keeping in mind socio-demographic factors (extrinsic factors) and to represent the industrial, service and the public sectors. The purposive sampling method is deployed to help reach the target group. The interviews were conducted in person or on phone. The data is collected from the field and the analysis is based on the field data.
The quantitative data relates to the study of generativity and well-being of the sampling units, both individually and on an average basis. Data is analysed from the responses of the Ryffâs Scale and The Loyola Generativity Scale. The overall score from the Ryffâs Scale is a measure of well being and that from the Loyola Generativity Scale is a measure of generativity. In order to create composite index scores different questions are added together and the scores compared across respondents in order to assess their overall performance. The scores can be interpreted as High Scores and Low Scores.
The qualitative data is collected through in-depth interviews, which were conducted to explore respondentsâ perspective and views vis a vis the research questions. The questions revolved on the themes of Generativity and wellbeing. The participants were observed during the interview and field notes taken.
In the research study selective employers were interviewed in depth in order to understand their perspective and to provide information on possible support of the elderly in new workplace. In addition, information about the assessment of this support by the employers was also collected qualitatively. The employers were categorized into two categories, those who hired the retired elderly and those elderly who were the business owners. The result based on responses of the employers elicited that the employers perceived certain qualities of elderly positively, while some qualities negatively vis-Ă -vis productivity and relations with co-workers. Across sectors there doesnât exist any policy for hiring the retired. Individuals retiring from influential posts with strong networks are headhunted and mid-performers are hired through references.
For the analysis of generativity, the respondents, based on the mean scores were divided into two groups, namely high performers (those who scored equal to or above the Mean score on LGS) and low performers (those who scored below the Mean score on LGS). The scores were substantiated with the qualitative findings from in-depth interviews and the scaled statements described. The interview responses and LGS scores threw light on commonalities among various groups of respondents, their distinct characteristics and at the same time highlighted issues and challenges. The results indicated that elderly feel responsible for the young generation and that generativity at work has several relationships while the low scoring respondents faced issues with relationships at work. Statistically, the results showed that average scores of low and high scoring respondents significantly differ in overall LGS score and its subcategories. Each subcategory is significantly associated with each other which shows that improvement in one category can lead to improvement in other category. But Job type doesnât have a significant effect on average LGS score.
The qualitative data on wellbeing was collected with the help of in-depth interviews based on the objectives and quantitative data was collected from the responses using Ryffâs Scale. Based on the Mean scores, the respondents under each subcategory were divided into two groups, namely high performers (those who scored equal to or above the Mean score on Ryffâs Scale) and low performers (those who scored below the Mean score on Ryffâs Scale). In-depth interviews were taken and the Ryffâs Scale scores and interview responses threw light on commonalities among various groups of respondents, their distinct characteristics and at the same time highlighted issues and challenges. The results also showed that wellbeing at workplace meant more than working and performing. Dignity was found to be important to the retired rehired and it was seen as a multidimensional notion while the low scoring respondents faced unfavourable work conditions. Statistically, the results showed that average scores of low and high scoring respondents significantly differ in overall Ryffâs Scale score and its subcategories. Each subcategory is significantly associated with each other which shows that improvement in one category can lead to improvement in other category. But Job type doesnât have a significant effect on average Ryffâs Scale score. Further, it was found the respondents with high performance or scores in Personal Growth and Autonomy have a better chance to perform well in Generativity, whereas the high scoring respondents in Self-Acceptance and Positive Relations too have a chance to perform well with two subcategories of LGS. Same holds for high scorers in Purpose in Life who stand a chance to perform well on one subcategory of LGS.
For qualitative data analysis, the Ideal typical grouping technique conceptualised and methodology developed by Uta Gerhardt (1994) is used. The study deals with the three objectives; to understand the extent to which elderly people in India have an opportunity to use their expertise and personal strengths in intergenerational relations; to examine the extent to which elderly people are actively involved in the reemployment/second innings, the interest of the elderly in such an engagement and the importance of this commitment, above all, for the individualâs emotional condition and; to what extent older people in the commitment described here see as opportunity to realize their personal criteria of good life. It emerged that five ideal typical groups may be identified based on similarity in psychological wellbeing, generativity, psychological characteristics and sociodemographic factors. And factors such as past professional life, age, organizational support, personal resources, circumstantial second innings and past unfulfilled professional lives are important determinants. The analysis, however does not represent the whole population of elderly in India. Rather, this study represents the experiences of relatively privileged elderly.
Overall, the result confirms that our Hypothesis is met. The result confirms that the high scoring elderly in India avail opportunity to use their expertise and personal strengths in intergenerational relations. The high scoring elderly are actively involved in the reemployment, they have interest in such an engagement and this commitment is important for their emotional condition. The high scoring elderly in the commitment see this opportunity to realize their personal criteria of good life. The low scoring elderly donât avail opportunity fully to use their expertise and personal strengths in intergenerational relations and they are not performing well in terms of active involvement in reemployment/second innings, they have low interest in such an engagement and it is not favoring their emotional condition, thereby failing them to realize their personal criteria of good life.
It is recommended that it is a joint responsibility of the government, private sector and the individuals to make structured plans and open up for meaningful engagement in work-life post retirement. Physical, social and cultural opportunities be provided for the elderly. Efforts to promote generativity and wellbeing of the elderly at workplace will help improve their work efficiency and organizational productivity, bring the young and old generations together for better work environment and positively affect health of the elderly, thereby reducing economic burden on the government machinery. The government and the corporate would have to work in tandem to create Age-friendly environment. At the same time the elderly should practice self-actualization and be ready to take up work post retirement. Those in active service should perform and maintain the mindset that basis their past performance they could apply for extension or continue to work post retirement in some other organization or in form of being self-employed. Lastly, the potential of elderly should be utilized by the society through voluntary service or unpaid work
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