2,792 research outputs found
A review of abnormal behavior detection in activities of daily living
Abnormal behavior detection (ABD) systems are built to automatically identify and recognize abnormal behavior from various input data types, such as sensor-based and vision-based input. As much as the attention received for ABD systems, the number of studies on ABD in activities of daily living (ADL) is limited. Owing to the increasing rate of elderly accidents in the home compound, ABD in ADL research should be given as much attention to preventing accidents by sending out signals when abnormal behavior such as falling is detected. In this study, we compare and contrast the formation of the ABD system in ADL from input data types (sensor-based input and vision-based input) to modeling techniques (conventional and deep learning approaches). We scrutinize the public datasets available and provide solutions for one of the significant issues: the lack of datasets in ABD in ADL. This work aims to guide new research to understand the field of ABD in ADL better and serve as a reference for future study of better Ambient Assisted Living with the growing smart home trend
PARAMETRIC APPROACHES TO BALANCE STORMWATER MANAGEMENT AND HUMAN WELLBEING WITHIN URBAN GREEN SPACE
Through rapid urbanisation, urban green spaces (UGS) have become increasingly limited and valuable in high-density urban environments. However, meeting the diverse requirements of sustainable urban development often leads to conflicts in UGS usage. For example, the presence of stormwater treatment facilities may hinder residents' access to adjacent UGS.
Traditional approaches to UGS design typically focus on separate evaluations of human wellbeing and stormwater management. However, using questionnaires, interviews, and surveys for human wellbeing evaluation can be challenging to generalise across different projects and cities. Additionally, professional hydrological models used for stormwater management require extensive knowledge of hydrology and struggle to integrate their 2D evaluation methods with 3D models.
To address these challenges, this thesis proposes a novel framework to integrate the two types of analysis within a system for balancing the needs of human wellbeing and stormwater management in UGS design. The framework incorporates criteria and parameters for evaluating human wellbeing and stormwater management in a 3D model and introduces an approach to compare these two needs in terms of UGS area and suitable location. The contributions of this thesis to multi-objective UGS design are as follows: (1) defining human wellbeing evaluation through Accessibility and Usability assessment, which considers factors such as connectivity, walking distance, space enclosure, and space availability; (2) simplifying stormwater evaluation using particle systems and design curves to streamline complex hydrological models; (3) integrating the two evaluations by comparing their quantified requirements for UGS area and location; and (4) incorporating parameters to provide flexibility and accommodate various design scenarios and objectives.
The advantages of this evaluation framework are demonstrated through two case studies: (1) the human wellbeing analysis based on spatial parameters in the framework shows sensitivity to site variations, including UGS quantity and distribution, population density, terrain, road context, height of void space, and more; (2) the simplified stormwater analysis effectively captures site variations represented by UGS quantity and distribution, building distribution, as well as terrain, providing recommendations for each UGS with different types and sizes of stormwater facilities. (3) With the features of spatial parameter evaluation, the framework is feasible to adjust relevant thresholds and include more parameters to respond to specific project needs. (4) By quantifying the two different requirements for UGS and comparing them, any UGS with high usage conflicts can be easily identified. By evaluating all proposed criteria for UGSs in the 3D model, designers can conveniently observe simulation and adjust design scenarios to address identified usage conflicts. Thus, the proposed evaluation framework in this thesis would be valuable in effectively supporting further multi-objective UGS design
2023-2024 Boise State University Undergraduate Catalog
This catalog is primarily for and directed at students. However, it serves many audiences, such as high school counselors, academic advisors, and the public. In this catalog you will find an overview of Boise State University and information on admission, registration, grades, tuition and fees, financial aid, housing, student services, and other important policies and procedures. However, most of this catalog is devoted to describing the various programs and courses offered at Boise State
The Narratives of Europol on Terrorism: The Causal Layered Analysis of the European Union Terrorism Situation and Trend Reports (TE-SAT)
The thesis researches terrorism and counterterrorism because terrorism is falsely represented as something novel threat in the 21st century. Yet terrorism has always been and will continue to exist in the future. The study takes Critical Terrorism Study's (CTS) outlook towards an international police agency Europol, which aims to foster European-wide intelligence-led policing (ILP) solutions. However, terrorism does not have universal consensuses. Indeed, often, one's terrorist is another's freedom fighter. Neither academics nor United Nations have unanimity regarding terrorism. Still, Europol has settled some understanding of terrorism in its yearly Terrorism Situation and Trend Reports (Te-sat). The reports do say nothing about the political and religious goals of terrorists, though they should be the essence of an academic terrorism definition. In ILP, an analyst proactively interprets a terrorist environment to produce an intelligence product so that a customer can impact the environment. By investigating the terrorism reports from Europol, the thesis yields four of Europol's overall narratives on terrorism. Secondly, the study dissects the worldviews and myths about terrorism that the interpretations of Europol depend on. Methodologically, the research adopts a case study as its research strategy, where document analysis by a sampling method led to select five terrorism reports to interpret them with causal layered analysis that is a narrative foresight method to unpack more profound stories from the future. The thesis will suggest paying more attention to emerging right-wing terrorism and giving practical recommendations on improving Europol's foresight work so it would not depoliticise terrorism
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Black Lives Matter in Higher Education: Empowering Student-Scholar Voices
My study documents the formation and impact of the student-led movement of Black Lives Matter in Higher Education (BLMHE) that is housed within Teachers College Higher and Postsecondary Education Program (HPSE). This group consists of HPSE students and faculty that have come together to analyze the effects of systemic societal forces on members of the HPSE community and their broader effects on higher education. BLMHE has since come together to show solidarity and support for students of color at TC through demonstrating their general commitment to social justice in the form of an educational seminar program.
This study, which relies on oral history interviews with BLMHE’s three student co-founders, examines the formation and impact of BLMHE, how they analyze the effects of systemic societal forces on members of their community, and their broader effects on higher education. I am interested in learning to what extent BLMHE plays a role in increasing equitable spaces for Black students who identify as scholars on campus because I want to find out how this form of student activism empowers students as agents for change against systemic racism within higher education. This will permit me to understand how this form of student advocacy compares to other forms of advocacy that seeks to address such inequality in higher education.
This exploratory oral history study centers on three themes: student advocacy within the realms of equitable epistemological spaces, how BLMHE is distinctive from the Black Studies and Black Lives Matter movements, and the role of Teachers College in supporting equitable epistemological spaces that can combat racism in higher education. BLMHE applies an alternative mode of viable activism beyond rallies and protests. I am interested in exploring the effect that involvement in student-led groups such as BLMHE have on increasing equitable spaces for these students as critical scholars within higher education scholarship, as well as their impact on TC as an institution. This student group is challenging not just the inequities within institutional infrastructures of higher education, but the thought processes behind what frames higher education scholarship itself, and which types of academic spaces for this scholarship need to be created for people of color. Further, their work demonstrates the degree to which marginalized Black and Indigenous People of Color (BIPOC) students are not content to sit on the sidelines.
This study also goes in-depth in discussing how inclusive archiving that accompanies this research can actively support and empower communities in the collective documentation of their own histories. Study findings will portray how these student members of BLMHE perceived social inequities in higher education, along with their experiences and reflections on microaggressions, diversity and inclusion, have informed their forays with activism. Study findings indicate that in order for higher education to better support these students, it is critical to center them in the process of knowledge creation via educational seminars; this, in turn, can inform change in scholarship. This study concludes that inclusive epistemological spaces created by BLMHE challenge dominant views of power in higher education, validating BIPOC-centered methods and theories while providing resources for scholars of color to thrive in the academy
Traffic Prediction using Artificial Intelligence: Review of Recent Advances and Emerging Opportunities
Traffic prediction plays a crucial role in alleviating traffic congestion
which represents a critical problem globally, resulting in negative
consequences such as lost hours of additional travel time and increased fuel
consumption. Integrating emerging technologies into transportation systems
provides opportunities for improving traffic prediction significantly and
brings about new research problems. In order to lay the foundation for
understanding the open research challenges in traffic prediction, this survey
aims to provide a comprehensive overview of traffic prediction methodologies.
Specifically, we focus on the recent advances and emerging research
opportunities in Artificial Intelligence (AI)-based traffic prediction methods,
due to their recent success and potential in traffic prediction, with an
emphasis on multivariate traffic time series modeling. We first provide a list
and explanation of the various data types and resources used in the literature.
Next, the essential data preprocessing methods within the traffic prediction
context are categorized, and the prediction methods and applications are
subsequently summarized. Lastly, we present primary research challenges in
traffic prediction and discuss some directions for future research.Comment: Published in Transportation Research Part C: Emerging Technologies
(TR_C), Volume 145, 202
Computational Intelligence for Cooperative Swarm Control
Over the last few decades, swarm intelligence (SI) has shown significant benefits in many practical applications. Real-world applications of swarm intelligence include disaster response and wildlife conservation. Swarm robots can collaborate to search for survivors, locate victims, and assess damage in hazardous environments during an earthquake or natural disaster. They can coordinate their movements and share data in real-time to increase their efficiency and effectiveness while guiding the survivors. In addition to tracking animal movements and behaviour, robots can guide animals to or away from specific areas. Sheep herding is a significant source of income in Australia that could be significantly enhanced if the human shepherd could be supported by single or multiple robots.
Although the shepherding framework has become a popular SI mechanism, where a leading agent (sheepdog) controls a swarm of agents (sheep) to complete a task, controlling a swarm of agents is still not a trivial task, especially in the presence of some practical constraints. For example, most of the existing shepherding literature assumes that each swarm member has an unlimited sensing range to recognise all other members’ locations. However, this is not practical for physical systems. In addition, current approaches do not consider shepherding as a distributed system where an agent, namely a central unit, may observe the environment and commu- nicate with the shepherd to guide the swarm. However, this brings another hurdle when noisy communication channels between the central unit and the shepherd af- fect the success of the mission. Also, the literature lacks shepherding models that can cope with dynamic communication systems. Therefore, this thesis aims to design a multi-agent learning system for effective shepherding control systems in a partially observable environment under communication constraints.
To achieve this goal, the thesis first introduces a new methodology to guide agents whose sensing range is limited. In this thesis, the sheep are modelled as an induced network to represent the sheep’s sensing range and propose a geometric method for finding a shepherd-impacted subset of sheep. The proposed swarm optimal herding point uses a particle swarm optimiser and a clustering mechanism to find the sheepdog’s near-optimal herding location while considering flock cohesion. Then, an improved version of the algorithm (named swarm optimal modified centroid push) is proposed to estimate the sheepdog’s intermediate waypoints to the herding point considering the sheep cohesion. The approaches outperform existing shepherding methods in reducing task time and increasing the success rate for herding.
Next, to improve shepherding in noisy communication channels, this thesis pro- poses a collaborative learning-based method to enhance communication between the central unit and the herding agent. The proposed independent pre-training collab- orative learning technique decreases the transmission mean square error by half in 10% of the training time compared to existing approaches. The algorithm is then ex- tended so that the sheepdog can read the modulated herding points from the central unit. The results demonstrate the efficiency of the new technique in time-varying noisy channels.
Finally, the central unit is modelled as a mobile agent to lower the time-varying noise caused by the sheepdog’s motion during the task. So, I propose a Q-learning- based incremental search to increase transmission success between the shepherd and the central unit. In addition, two unique reward functions are presented to ensure swarm guidance success with minimal energy consumption. The results demonstrate an increase in the success rate for shepherding
Understanding Secularized People of Metro Manila: A Case Study Approach for a Contextualized Urban Ministry Strategy
Problem
Secularization shapes people\u27s thinking, feeling, and behaving in the cities. Yearly, there is a rise in the number of de-religionized or secularized people in cities of the world who engage in pursuits of materialism and show declining interest in religion. Sociologists and missiologists postulate about the spectrum of secularity and the variety of secularism in different context. Since Metro Manila is one of the world\u27s top highly urbanized and densely populated cities, the Seventh-day Adventist Church encounters challenges in reaching its secularized people. It is a new turf for the church. Pastors trained for rural settings may not understand what attracts and retains the secularized people to the church. Many do not know that the secularized is an emerging people group and that they have some special needs that the traditional Adventist Church does not address. Hence, there is a need for a biblically sound and yet culturally sensitive approach to the secularized people. --
Method
This case study looked into the phenomena of evangelizing secularized persons in Metro Manila. It aimed to determine the characteristics of the secularized Manileños and what attracted them to God and the church. In addition, the study also answered the questions of what retains in them in church and what make them leave the church—in an attempt to put together a contextualized strategy for the secularized people. Personal interviews and focus group discussions were conducted among 30 participants comprising of non-Adventists who are secularized (12), secularized Adventists (10), and urban ministry practitioners (8). Document analysis and observation (church visit and online worship) followed the interviews. Coded data analysis provided categories for themes that answered the research questions. The interviews, FGI, document analysis, and observation were triangulated to ensure the reliability and credibility of the research findings.
Results
The secularized Manileños are found to be at the beginning of the spectrum of the secularization process. They are between the U1-U3 stages in Reiner’s Scale on Receptivity to the Gospel. They also identify with twenty-four characteristics of secularized individuals. Several analysis cycles resulted in nine recurring themes that emerged from the data. These themes are four life encounters with Grace, six relational factors, seven good experiences in the Adventist church, three unique features that are specific to Adventists, three church-related factors impacting retention among secularized individuals, four personal factors influencing their decision-making process when it comes to joining or leaving religious institutions. The study also revealed five barriers hindering efforts to reach out and engage secular audiences, as well as five best qualities of the ministry workers and five approaches for successful ministry toward this group.
Conclusions
Analyzing these findings and insights resulted in twelve proposed strategies that Adventist organizations and conferences can use as examples in developing effective ministry programs targeting secularized people in Metro Manila. These strategies can also be applied to other cities with diverse population segments, including those currently disconnected from organized religion like the secularized people
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