The Lived Experience of Cultural Immersion

This article presents the findings of a grounded theory study of 3 graduate students\u27 lived experience of cultural immersion. Results indicated that participants experienced 3 phases (goal setting, interaction, and evaluation) and 4 themes (bias, gender, barriers, and self-awareness) during immersion. Recommendations for the implementation of immersion experiences are discussed

Open source environment to define constraints in route planning for GIS-T

Route planning for transportation systems is strongly related to shortest path algorithms, an optimization problem extensively studied in the literature. To find the shortest path in a network one usually assigns weights to each branch to represent the difficulty of taking such branch. The weights construct a linear preference function ordering the variety of alternatives from the most to the least attractive.Postprint (published version

Advancing early leukemia diagnostics: a comprehensive study incorporating image processing and transfer learning.

Disease recognition has been revolutionized by autonomous systems in the rapidly developing field of medical technology. A crucial aspect of diagnosis involves the visual assessment and enumeration of white blood cells in microscopic peripheral blood smears. This practice yields invaluable insights into a patient's health, enabling the identification of conditions of blood malignancies such as leukemia. Early identification of leukemia subtypes is paramount for tailoring appropriate therapeutic interventions and enhancing patient survival rates. However, traditional diagnostic techniques, which depend on visual assessment, are arbitrary, laborious, and prone to errors. The advent of ML technologies offers a promising avenue for more accurate and efficient leukemia classification. In this study, we introduced a novel approach to leukemia classification by integrating advanced image processing, diverse dataset utilization, and sophisticated feature extraction techniques, coupled with the development of TL models. Focused on improving accuracy of previous studies, our approach utilized Kaggle datasets for binary and multiclass classifications. Extensive image processing involved a novel LoGMH method, complemented by diverse augmentation techniques. Feature extraction employed DCNN, with subsequent utilization of extracted features to train various ML and TL models. Rigorous evaluation using traditional metrics revealed Inception-ResNet's superior performance, surpassing other models with F1 scores of 96.07% and 95.89% for binary and multiclass classification, respectively. Our results notably surpass previous research, particularly in cases involving a higher number of classes. These findings promise to influence clinical decision support systems, guide future research, and potentially revolutionize cancer diagnostics beyond leukemia, impacting broader medical imaging and oncology domains

Program Evaluation in the Context of Debates in the Field: The Evaluation of PR-CETP

This paper rationalizes the selection of the concept of energy as the central theme of a new capstone course aimed at science education majors. It describes the goals of the course and the activities that preceded the course design and led to the selection of the topics, of the educational materials, and of the teaching methodologies. It presents a sequential description of the manner in which the conceptual knowledge of energy was to be developed. The specific experiments, interactive demonstrations and other educational materials utilized for the conceptual development of the concept of energy in context are described and referenced. The course objectives are described, as well as the instruments utilized to assess student learning. It also presents the activities utilized to assess the course, in addition to the modifications made to the course syllabus based on this assessment

Towards an analytics and an ethics of expertise: Learning from decision aiding experiences in public risk assessment and risk management

Public expertise in safety, security and environment is a process that is increasingly submitted to control and transparency. It therefore requires an oversight, a monitoring and an aiding approach on its conduct and its governance. Difficulties learned from experiences in framing risk problems and sharing expertise conclusions and recommendations are pointed. Our practice of expertise has made clear to us that "expertise is a decision aiding process for a decision-maker which contains other decision aiding processes for the experts involved. To overcome this paradox, we argue on the need of a generic integrated framework for expertise that allows framing a valid and a legitimate expertise process and conclusions. Public expertise is then defined and mai

Case-Based Reasoning Systems: From Automation to Decision-Aiding and Stimulation

Over the past decade, case-based reasoning (CBR) has emerged as a major research area within the artificial intelligence research field due to both its widespread usage by humans and its appeal as a methodology for building intelligent systems. Conventional CBR systems have been largely designed as automated problem-solvers for producing a solution to a given problem by adapting the solution to a similar, previously solved problem. Such systems have had limited success in real-world applications. More recently, there has been a search for new paradigms and directions for increasing the utility of CBR systems for decision support. This paper focuses on the synergism between the research areas of CBR and decision support systems (DSSs). A conceptual framework for DSSs is presented and used to develop a taxonomy of three different types of CBR systems: 1) conventional, 2) decision-aiding, and 3) stimulative. The major characteristics of each type of CBR system are explained with a particular focus on decision-aiding and stimulative CBR systems. The research implications of the evolution in the design of CBR systems from automation toward decision-aiding and stimulation are also explored

Explaining public support for counterproductive homeless policy: the role of disgust

Federal, state, and city governments spend substantial funds on programs intended to aid homeless people, and such programs attract widespread public support. In recent years, however, state and local governments have increasingly enacted policies, such as bans on panhandling and sleeping in public, that are counterproductive to alleviating homelessness. Yet these policies also garner substantial support from the public. Given that programs aiding the homeless are so popular, why are these counterproductive policies also popular? We argue that disgust plays a key role in the resolution of this puzzle. While disgust does not decrease support for aid policies or even generate negative affect towards homeless people, it motivates the desire for physical distance, leading to support for policies that exclude homeless people from public life. We test this argument using survey data, including a national sample with an embedded experiment. Consistent with these expectations, our findings indicate that those respondents who are dispositionally sensitive to disgust are more likely to support exclusionary policies, such as banning panhandling, but no less likely to support policies intended to aid homeless people. Furthermore, media depictions of the homeless that include disease cues activate disgust, increasing its impact on support for banning panhandling. These results help explain the popularity of exclusionary homelessness policies and challenge common perspectives on the role of group attitudes in public life.Accepted manuscrip

From Bounded Rationality to Behavioral Economics

The paper provides an brief overview of the “state of the art” in the theory of rational decision making since the 1950’s, and focuses specially on the evolutionary justification of rationality. It is claimed that this justification, and more generally the economic methodology inherited from the Chicago school, becomes untenable once taking into account Kauffman’s Nk model, showing that if evolution it is based on trial-and-error search process, it leads generally to sub- optimal stable solutions: the ‘as if’ justification of perfect rationality proves therefore to be a fallacious metaphor. The normative interpretation of decision-making theory is therefore questioned, and the two challenging views against this approach , Simon’s bounded rationality and Allais’ criticism to expected utility theory are discussed. On this ground it is shown that the cognitive characteristics of choice processes are becoming more and more important for explanation of economic behavior and of deviations from rationality. In particular, according to Kahneman’s Nobel Lecture, it is suggested that the distinction between two types of cognitive processes – the effortful process of deliberate reasoning on the one hand, and the automatic process of unconscious intuition on the other – can provide a different map with which to explain a broad class of deviations from pure ‘olympian’ rationality. This view requires re-establishing and revising connections between psychology and economics: an on-going challenge against the normative approach to economic methodology.Bounded Rationality, Behavioral Economics, Evolution, As If