Search results for: legal judgment and decision making

Authors: Journey Whitfield

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This study investigates the United States' ongoing violation of Black Americans' fundamental human rights, as evidenced by mass incarceration, social injustice, and economic deprivation. It argues that the U.S. contravenes Article 9 of the International Covenant on Civil and Political Rights through policies that uphold systemic racism. The analysis dissects current practices within the criminal justice system, social welfare programs, and economic policy, uncovering the racially disparate impacts of seemingly race-neutral policies. This study establishes a clear lineage between past systems of oppression – slavery and Jim Crow – and present-day racial disparities, demonstrating their inextricable link. The thesis proposes that only a comprehensive reparations program for Black Americans can begin to redress these systemic injustices. This program must transcend mere financial compensation, demanding structural reforms within U.S. institutions to dismantle systemic racism and promote transformative justice. This study explores potential forms of reparations, drawing upon historical precedents, comparative case studies from other nations, and contemporary debates within political philosophy and legal studies. The research employs both qualitative and quantitative methods. Qualitative methods include historical analysis of legal frameworks and policy documents, as well as discourse analysis of political rhetoric. Quantitative methods involve statistical analysis of socioeconomic data and criminal justice outcomes to expose racial disparities. This study makes a significant contribution to the existing literature on reparations, human rights, and racial injustice in the United States. It offers a rigorous analysis of the enduring consequences of historical oppression and advocates for bold, justice-centered solutions.

Keywords: Black Americans, reparations, mass incarceration, racial injustice, human rights, united states

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Authors: Chitra Rajagopal, Indra Deo Kumar, Ruchi Joshi, Binoy Bhargavan

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Role of fighter planes in modern network centric military warfare scenarios has changed significantly in the recent past. New generation fighter planes have multirole capability of engaging both air and ground targets with high precision. Multirole aircraft undertakes missions such as Air to Air combat, Air defense, Air to Surface role (including Air interdiction, Close air support, Maritime attack, Suppression and Destruction of enemy air defense), Reconnaissance, Electronic warfare missions, etc. Designers have primarily focused on development of technologies to enhance the combat performance of the fighter planes and very little attention is given to human factor aspects of technologies. Unique physical and psychological challenges are imposed on the pilots to meet operational requirements during these missions. Newly evolved technologies have enhanced aircraft performance in terms of its speed, firepower, stealth, electronic warfare, situational awareness, and vulnerability reduction capabilities. This paper highlights the impact of emerging technologies on human factors for various military operations and missions. Technologies such as ‘cooperative knowledge-based systems’ to aid pilot’s decision making in military conflict scenarios as well as simulation technologies to enhance human performance is also studied as a part of research work. Current and emerging pilot protection technologies and systems which form part of the integrated life support systems in new generation fighter planes is discussed. System safety analysis application to quantify the human reliability in military operations is also studied.

Keywords: combat effectiveness, emerging technologies, human factors, systems safety analysis

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Authors: Ahmed Al-Adaileh

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Renewable energy sources, domestic storage systems, controllable loads and machine learning technologies will be key components of future smart homes management systems. An energy management scheme that uses a Deep Learning (DL) approach to support the smart home management systems, which consist of a standalone photovoltaic system, storage unit, heating ventilation air-conditioning system and a set of conventional and smart appliances, is presented. The objective of the proposed scheme is to apply DL-based machine learning to predict various running parameters within a smart home's environment to achieve maximum comfort levels for occupants, reduced electricity bills, and less dependency on the public grid. The problem is using Reinforcement learning, where decisions are taken based on applying the Continuous-time Markov Decision Process. The main contribution of this research is the proposed framework that applies DL to enhance the system's supervised dataset to offer unlimited chances to effectively support smart home systems. A case study involving a set of conventional and smart appliances with dedicated processing units in an inhabited building can demonstrate the validity of the proposed framework. A visualization graph can show "before" and "after" results.

Keywords: smart homes systems, machine learning, deep learning, Markov Decision Process

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Authors: Karen Bell

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While there is broad agreement among governments and civil society globally about the need to develop more sustainable societies, the best way to achieve this is still contested. In particular, there are differences regarding whether to continue to implement market-based approaches or to move to alternative redistributive-based approaches. In this paper, ‘Green Economy’ and ‘Living Well’ strategies are compared as examples of these two different strategies for achieving social, ecological and economic sustainability. The paper is based on a 3-year ESRC funded project on transitions to sustainability which examines the implementation of the ‘Green Economy’ paradigm in South Korea and the 'Living Well' paradigm in Bolivia. As well as outlining and analysing secondary data, the paper also draws on over 100 interviews with a range of local stakeholders in these countries carried out by the author between and including 2016 and 2018. The work indicates that the Living Well paradigm seems to better integrate social, ecological and economic concerns and may better deliver sustainability in the time frame necessary than the dominant Green Economy paradigm. This seems to be primarily because Living Well emphasises redistribution to reduce inequality and ensure human needs are met; living in harmony with nature, taking into account natural limits and cycles; respecting traditional values and practices where these support sustainability and human well-being; sovereignty and local control of natural resources; and participative decision-making, based on grassroots community organising. It is, therefore, argued that to achieve inclusive, just and effective transitions to sustainability we should aim to foster equality, respect planetary limits, build on local traditions, bring resources into public ownership and enhance participatory democracy. This will require a radically different approach to that offered within the market-based agenda currently dominating global sustainability debates and activities.

Keywords: environmental transition, green economy, inclusive sustainability, living well, sustainable transition

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Authors: Ebtissem Sassi, Abdellatif Benabdelhafid, Sami Hammami

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Congestion, pollution and space misuse are the major risks in the hinterland. Management of these risks is a major issue for all the actors intervening in territory management. A good mastery of these risks is based on the consideration of environmental and physical constraints since the implementation of a policy integrates simultaneously an efficient use, territorial resources, and financial resources which become increasingly rare. Yet, this balance can be difficult to establish simultaneously by all the actors. Indeed, every actor has often the tendency to favor these objectives in detriment to others. In this framework, we have fixed the objective of designing and achieving a model which will centralize multidisciplinary data and serve the analysis tool as well as a decision support tool. In this article, we will elaborate some methodological axes allowing the good management of the territory system through (i) determination of the structural factors of the decision support system, (ii) integration of methods tools favoring the territorial decisional process. Logistics territory geographic information system is a model dealing with this issue. The objective of this model is to facilitate the exchanges between the actors around a common question which was the research subject of human sciences researchers (geography, economy), nature sciences (ecology) as well as finding an optimal solution for simultaneous responses to all these objectives.

Keywords: complexity, territory, logistics, territory planning, conceptual model, GIS, MCA

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Authors: Oluwaseun K. Oyebode, Josiah A. Adeyemo

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Hydrological modelling plays a crucial role in the planning and management of water resources, most especially in water stressed regions where the need to effectively manage the available water resources is of critical importance. However, due to the complex, nonlinear and dynamic behaviour of hydro-climatic interactions, achieving reliable modelling of water resource systems and accurate projection of hydrological parameters are extremely challenging. Although a significant number of modelling techniques (process-based and data-driven) have been developed and adopted in that regard, the field of hydrological modelling is still considered as one that has sluggishly progressed over the past decades. This is majorly as a result of the identification of some degree of uncertainty in the methodologies and results of techniques adopted. In recent times, evolutionary computation (EC) techniques have been developed and introduced in response to the search for efficient and reliable means of providing accurate solutions to hydrological related problems. This paper presents a comprehensive review of the underlying principles, methodological needs and applications of a promising evolutionary computation modelling technique – genetic programming (GP). It examines the specific characteristics of the technique which makes it suitable to solving hydrological modelling problems. It discusses the opportunities inherent in the application of GP in water related-studies such as rainfall estimation, rainfall-runoff modelling, streamflow forecasting, sediment transport modelling, water quality modelling and groundwater modelling among others. Furthermore, the means by which such opportunities could be harnessed in the near future are discussed. In all, a case for total embracement of GP and its variants in hydrological modelling studies is made so as to put in place strategies that would translate into achieving meaningful progress as it relates to modelling of water resource systems, and also positively influence decision-making by relevant stakeholders.

Keywords: computational modelling, evolutionary algorithms, genetic programming, hydrological modelling

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Authors: Mark Morgan, Christine Li, Shuangyu Xu, Jenny McCarty

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The National Wild and Scenic Rivers System was created by the U.S. Congress in 1968 (Public Law 90-542; 16 U.S.C. 1271 et seq.) to preserve outstanding natural, cultural, and recreational values of some U.S. rivers in a free-flowing condition for the enjoyment of present and future generations. This Act is notable for safeguarding the special character of these rivers while supporting management action that encourages public participation for co-creating river protection goals and strategies. This is not an easy task. To meet the challenges of modern ecosystem management, federal resource agencies must address many legal, environmental, economic, political, and social issues. The U.S. Forest Service manages a 44-mile section of the Eleven Point National Scenic River (EPR) in southern Missouri, mainly for outdoor recreation purposes. About half of the acreage is in private lands, while the remainder flows through the Mark Twain National Forest. Private land along the river is managed by scenic easements to ensure protection of scenic values and natural resources, without public access. A portion of the EPR lies adjacent to a 16,500-acre tract known as the Irish Wilderness. The spring-fed river has steep bluffs, deep pools, clear water, and a slow current, making it an ideal setting for outdoor enthusiasts. A 10-month visitor study was conducted at five access points along the EPR during 2019 so the US Forest Service could update their river management plan. A mail-back survey was administered to 560 on-site visitors, yielding a response rate of 53%. Although different types of visitors use the EPR, boating and fishing were the predominant forms of outdoor recreation. Some river use was from locals, but other visitors came from farther away. Formulating unbiased policies for outdoor recreation is difficult because managers must assign relative values to recreational activities and travel distance. Because policymaking is a subjective process, management decisions can affect user groups in different ways (i.e., boaters vs. fishers; proximate vs. distal visitors), as seen through a GIS analysis.

Keywords: activity selection, forest recreation, policy, travel distance

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Authors: Edoba Bright Omoregie

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Nigeria became a federation in 1954 six years before it gained independence away from British colonial rule. The country has remained a federation since then despite the challenging circumstances of military rule and civil strife which have tasked its federal credentials. Since 1961, when it first decided a federalism dispute, cases over vertical and horizontal powers have inundated the country’s Supreme Court. In its current practice of federalism after democratic rule was resumed in 1999, the country has witnessed a spell of intergovernmental disputes over a good number of federalism issues. Such conflicts have eventually found their way to the Supreme Court for resolution, not as a final appellate court (which it is in other non-federal matters) but as a court of first and final instance following the constitutional provision granting the court such power. However, in April 2014 one of such disputes was denied hearing by the court when it declined original jurisdiction to determine the matter. The suit was instituted by one state of the federation against the federal government and the other 35 states challenging the collection of value added tax (a consumption tax)on certain goods and services within the state. The paper appraises the rationale of the court’s decision and reason that its decision to decline jurisdiction is the result of an avoidable misunderstanding of the dual sovereignty instituted by the federal system of Nigeria as well as a misconception of the role which the court is constitutionally assigned to play in resolving intergovernmental schisms in the federal system.

Keywords: dual sovereignty, federalism, intergovernmental conflict, Supreme Court

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Authors: Sonto Maputle

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Background: Support during labour increase women's chances of having positive childbirth experiences as well as childbirth outcomes. The purpose of this study was to determine the support provided by midwives to women during labour at the public hospital in Limpopo Province. The study was conducted at the Tertiary hospital in Limpopo Province. Methods: A qualitative, participant observation approach was used. Population consisted of all women that were admitted to deliver their babies and the midwives who provided midwifery care in the obstetric unit of one tertiary public hospital in Limpopo Province. Non-probability, purposive and convenience sampling were used to sample 24 women and 12 midwives. Data were collected through participant observations which included unstructured conversations with the use of observational guide, field notes of events and conversations that occurred when women interact with midwives were recorded verbatim and a Visual Analog Scale to complement the observations. Data was analysed qualitatively but were presented in the tables and bar graphs. Results: Five themes emerged as support provided by midwives during labour, namely; communication between women and midwives, informational support, emotional support activities, interpretation of the experienced labour pain and supportive care activities during labour. Conclusion: The communication was occurring when the midwife was rendering midwifery care and very limited for empowering. The information sharing focused on the assistive actions rather than on the activities that would promote mothers’ participation. The emotional support activities indicated lack of respect and disregard cultural preferences and this contributed to inability to exercise choices in decision-making. The study recommended the implementation of Batho Pele principles in order to provide woman-centred care during labour.

Keywords: communication between women and midwives, labour pains, informational and emotional support, physical comforting measures

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Authors: Fatima Saab

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This paper attempts to study colloquialism in audio-visual translation, with particular emphasis given to investigating the difficulties and challenges encountered by subtitlers in translating Lebanese colloquial into English. To achieve the main objectives of this study, ample and thorough cultural and translational analysis of examples drawn from the subtitled movie Capernaum are presented in order to identify the strategies used to overcome cultural barriers and differences and to show the process of decision-making by the translator. Also, special attention is given to explain the technicalities in translating subtitles and how they affect the translation process. The research is a descriptive analytical study whereby the writer sets out empirical observations, consisting of descriptive and analytical examination of the difficulties and problems associated with translating Arabic colloquialisms, specifically Lebanese, into English in the subtitled film, Capernaum. The research methodology utilizes a qualitative approach to group the selected data into the subtitling strategies presented by Gottlieb under the domesticating or foreignizing strategies according to Venuti's Model. It is shown that producing the same meanings to a foreign audience is not an easy task. The background of cultural elements and the stories that make up the history and mindset of the Lebanese and Arabic peoples leads to the use of the transfer and paraphrase methodologies most of the time (81% of the sample used for analysis). The research shows that translating and subtitling colloquialism needs special skills by the translators to overcome the challenges imposed by the limited presentation space as well as cultural differences. Translation of colloquial Arabic/Lebanese can be achieved to a certain extent and delivering the meaning and effect of the source language culture is accomplished in as much as the translator investigates and relates to the target culture.

Keywords: Lebanese colloquial, audio-visual translation, subtitling, Capernaum

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Authors: María-Dolores Olvera-Lobo, Bryan John Robinson, Juncal Gutierrez-Artacho

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Graduates are equipped with a wide range of generic competencies which complement solid curricular competencies and facilitate their access to the labour market in diverse fields and careers. However, some generic competencies such as instrumental, personal and systemic competencies related to teamwork and interpersonal communication skills, decision-making and organization skills are seldom taught explicitly and even less often assessed. In this context, translator training has embraced a broad range of competencies specified in the undergraduate program currently taught at universities and opens up the learning experience to cover areas often ignored due to the difficulties inherent in both teaching and assessment. In practice, translator training combines two well-established approaches to teaching/learning: project-based learning and genuinely cooperative – or merely collaborative – learning. Our professional approach to translator training is a model focused on and adapted to the teleworking context of professional translation and presented through the medium of blended e-learning. Teamwork-related competencies are extremely relevant, and they require explicit and implicit teaching so that graduates can be confident about their capacity to make their way in professional contexts. In order to highlight the importance of teamwork and intra-team relationships beyond the classroom, we aim to raise awareness of teamwork processes so as to empower translation students in managing their interaction and ensure that they gain valuable pre-professional experience. With these objectives, at the University of Granada (Spain) we have developed a range of classroom activities and assessment tools. The results of their application are summarized in this study.

Keywords: blended learning, collaborative teamwork, cross-curricular competencies, higher education, intra-team relationships, students’ perceptions, translator training

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Authors: Mohammad Rahman, Guy Burton, Megan Mathias

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Strategic management as an organizational practice was adopted by the public sector in the New Public Management (NPM) era that began in most parts of the world in the 1980s. Strategy as a new public management concept was subscribed by governments in both developed and developing world, as they were persuaded that clearly defined vision, mission and goals, as well as programs and projects - aligned with the goals - could potentially help achieve government vision at the national level and organizational goals at the service-delivery level. The advocates for strategic management in the public sector saw an inherent link between strategy and performance, claiming that the implementation of organizational strategy has an effect on the overall performance of an organization. Arguably, many government entities that have failed in enhancing team and individual performance had poorly-designed strategy or weak strategy implementation. Another key argument about low-level performance is linked with lack of strategic sense-making and orientation by middle managers in particular. Scholars maintain that employees at all levels need to understand strategic management plan in order to facilitate its implementation. Therefore, involving employees (particularly the middle managers) from the beginning potentially helps an organization avoid the drop in performance, and on the contrary would increase their commitment. The United Arab Emirates (UAE) is well known for adopting public sector reform strategies and tools since the 1990s. This observation is contextually pertinent in the case of the Government of Dubai, which has provided a Strategy Execution Guide to all of its entities to achieve high level strategic success in service delivery. The Dubai public sector also adopts road maps for e-Government, Smart Dubai, Expo 2020, investment, environment, education, health and other sectors. Evidently, some of these strategies are bringing tangible (e.g. Smart Dubai transformation) results in a transformational manner. However, the amount of academic research and literature on the strategy process vis-à-vis staff performance in the Government of Dubai is limited. In this backdrop, this study examines how individual performance of public sector employees in Dubai is linked with their sense-making, engagement and orientation with strategy development and implementation processes. Based on a theoretical framework, this study will undertake a sample-based questionnaire survey amongst middle managers in Dubai public sector to (a) measure the level of engagement of middle managers in strategy development and implementation processes as perceived by them; (b) observe the organizational landscape in which role expectations are placed on middle managers; and (c) examine the impact of employee engagement in strategy development process and the conditions for role expectations on individual performance. The paper is expected to provide new insights on the interface between strategic sense-making and performance in order to contribute a better understanding of the current culture/practices of staff engagement in strategic management in the public sector of Dubai.

Keywords: employee performance, government of Dubai, middle managers, strategic sense-making

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Authors: Yun-na Wu, Zhen Wang

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Due to the economic downturn and the deterioration of the living environment, the development of residential buildings as high energy consuming building is gradually changing from “extensive” to green building in China. So, the evaluation system of green building is continuously improved, but the current evaluation work has the following problems: (1) There are differences in the cost of the actual investment and the purchasing power of residents, also construction target of green residential building is single and lacks multi-objective performance development. (2) Green building evaluation lacks regional characteristics and cannot reflect the different regional residents demand. (3) In the process of determining the criteria weight, the experts’ judgment matrix is difficult to meet the requirement of consistency. Therefore, to solve those problems, questionnaires which are about the green residential building for Ningxia area are distributed, and the results of questionnaires can feedback the purchasing power of residents and the acceptance of the green building cost. Secondly, combined with the geographical features of Ningxia minority areas, the evaluation criteria system of green residential building is constructed. Finally, using the improved group AHP method and the grey clustering method, the criteria weight is determined, and a real case is evaluated, which is located in Xing Qing district, Ningxia. A conclusion can be obtained that the professional evaluation for this project and good social recognition is basically the same.

Keywords: evaluation, green residential building, grey clustering method, group AHP

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Authors: Anjali Chouksey, Riya Nimje, Jahanvi Saraf

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Online transactions have increased dramatically in this new ‘social-distancing’ era. With online transactions, Fraud in online payments has also increased significantly. Frauds are a significant problem in various industries like insurance companies, baking, etc. These frauds include leaking sensitive information related to the credit card, which can be easily misused. Due to the government also pushing online transactions, E-commerce is on a boom. But due to increasing frauds in online payments, these E-commerce industries are suffering a great loss of trust from their customers. These companies are finding credit card fraud to be a big problem. People have started using online payment options and thus are becoming easy targets of credit card fraud. In this research paper, we will be discussing machine learning algorithms. We have used a decision tree, XGBOOST, k-nearest neighbour, logistic-regression, random forest, and SVM on a dataset in which there are transactions done online mode using credit cards. We will test all these algorithms for detecting fraud cases using the confusion matrix, F1 score, and calculating the accuracy score for each model to identify which algorithm can be used in detecting frauds.

Keywords: machine learning, fraud detection, artificial intelligence, decision tree, k nearest neighbour, random forest, XGBOOST, logistic regression, support vector machine

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Authors: N. Gopalakrishna Kini, Ranjana Paleppady, Akshata K. Naik

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Password authentication is one of the widely used methods to achieve authentication for legal users of computers and defense against attackers. There are many different ways to authenticate users of a system and there are many password cracking methods also developed. This paper is mainly to propose how best password cracking can be performed on a CPU-GPGPU based system. The main objective of this work is to project how quickly a password can be cracked with some knowledge about the computer security and password cracking if sufficient security is not incorporated to the system.

Keywords: GPGPU, password cracking, secret key, user authentication

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Authors: Klaus Peter Scherer, Daniel Knöll, Constantin Rieder

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Problem and Purpose: Intelligent systems are available and helpful to support the human being decision process, especially when complex surgical eye interventions are necessary and must be performed. Normally, such a decision support system consists of a knowledge-based module, which is responsible for the real assistance power, given by an explanation and logical reasoning processes. The interview based acquisition and generation of the complex knowledge itself is very crucial, because there are different correlations between the complex parameters. So, in this project (semi)automated self-learning methods are researched and developed for an enhancement of the quality of such a decision support system. Methods: For ophthalmic data sets of real patients in a hospital, advanced data mining procedures seem to be very helpful. Especially subgroup analysis methods are developed, extended and used to analyze and find out the correlations and conditional dependencies between the structured patient data. After finding causal dependencies, a ranking must be performed for the generation of rule-based representations. For this, anonymous patient data are transformed into a special machine language format. The imported data are used as input for algorithms of conditioned probability methods to calculate the parameter distributions concerning a special given goal parameter. Results: In the field of knowledge discovery advanced methods and applications could be performed to produce operation and patient related correlations. So, new knowledge was generated by finding causal relations between the operational equipment, the medical instances and patient specific history by a dependency ranking process. After transformation in association rules logically based representations were available for the clinical experts to evaluate the new knowledge. The structured data sets take account of about 80 parameters as special characteristic features per patient. For different extended patient groups (100, 300, 500), as well one target value as well multi-target values were set for the subgroup analysis. So the newly generated hypotheses could be interpreted regarding the dependency or independency of patient number. Conclusions: The aim and the advantage of such a semi-automatically self-learning process are the extensions of the knowledge base by finding new parameter correlations. The discovered knowledge is transformed into association rules and serves as rule-based representation of the knowledge in the knowledge base. Even more, than one goal parameter of interest can be considered by the semi-automated learning process. With ranking procedures, the most strong premises and also conjunctive associated conditions can be found to conclude the interested goal parameter. So the knowledge, hidden in structured tables or lists can be extracted as rule-based representation. This is a real assistance power for the communication with the clinical experts.

Keywords: an expert system, knowledge-based support, ophthalmic decision support, self-learning methods

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Authors: Philippa Hunter

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How might history education support teachers and students to see the past as a provocation, be open to possible futures, and act differently? As teacher educators in an age of diversity and uncertainty, we need to question history’s curriculum nature, pedagogy, and policy intent. The cultural politics of history’s identity in the senior secondary curriculum influences educational socialization (disciplinary, professional, research) and engagement with curriculum decision-making. This paper reflects on curriculum disturbance that shaped a critical pedagogy stance to problematize school history’s certainties. The context is situated in an Aotearoa New Zealand university-based initial teacher education programme. A pedagogic innovation was activated whereby problematized history pedagogy [PHP] was conceptualized as the phenomenon and method of inquiry and storied in doctoral work. The PHP was a reciprocal research process involving history class’ participants and the teacher as researcher, in fashioning teaching identities, identifying with, and thinking critically about history pedagogy. PHP findings revealed evocative discourses of embodiment, nostalgia, and connectedness about living ‘inside the past’. Participants expressed certainty about their abilities as teachers living ‘outside the past’ to interpret historical perspectives. However, discomfort was evident in relation to ‘difficult knowledge’ or unfamiliar contexts of the past that exposed exclusion, powerlessness, or silenced voices. Participants identified history programmes as strongly masculine and conflict-focused. A normalized inquiry-transmission approach to history pedagogy was identified and critiqued. Individuals’ reflexive accounts of PHP implemented whilst on practicum indicate possibilities of history pedagogy as; inclusive and democratic, social and ethical reconstruction, and as a critical project. The PHP sought to reimagine history curriculum and identify spaces of possibility in secondary postgraduate teacher education.

Keywords: curriculum, pedagogy, problematise, reciprocal

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Authors: S. B. D. Samarasinghe, Malini Herath

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Participatory planning is a very important process for decision making and choosing the best alternative options for community welfare, development of the society and its interactions among community and professionals. People’s involvement is considered as the key guidance in participatory planning. Presently, Participatory planning is being used in many fields. It's not only limited to planning but also to disaster management, poverty, housing, etc. In the past, Disaster management practice was a top-down approach, but it raised many issues as it was converted to a bottom-up approach. There are several approaches that can aid disaster management. Community-Based Disaster Risk Management (CBDRM) is a very successful participatory approach to risk management that is often successfully applied by other disaster-prone countries. In the local context, CBDRM has been applied to prevent Diseases as well as to prevent disasters such as landslides, tsunamis and floods. From three years before, Sri Lanka has initiated the CBDRM approach to minimize landslide vulnerability. Hence, this study mainly focuses on the impact of CBDRM approaches on landslide hazards. Also to identify their successes and failures from both implementing parties and community. This research is carried out based on a qualitative method combined with a descriptive research approach. A successful framework was prepared via a literature review. Case studies were selected considering landslide CBDRM programs which were implemented by Disaster Management Center and National Building Research Organization in Badulla. Their processes were evaluated. Data collection is done through interviews and informal discussions. Then their ideas were quantified by using the Relative Effectiveness index. The resulting numerical value was used to rank the program effectiveness and their success, failures and impacting factors. Results show that there are several failures among implementing parties and the community. Overcoming those factors can make way for better conduction of future CBDRM programs.

Keywords: community-based disaster risk management, disaster management, preparedness, landslide

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Authors: Keroles Akram Saed Ghatas

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The near future will bring significant changes in modern organizations and management due to the growing role of intangible assets and knowledge workers. The area of copyright, intellectual property, digital (intangible) assets and media redistribution appears to be one of the greatest challenges facing business and society in general and management sciences and organizations in particular. The proposed article examines the views and perceptions of fairness in digital media sharing among Harvard Law School's LL.M.s. Students, based on 50 qualitative interviews and 100 surveys. The researcher took an ethnographic approach to her research and entered the Harvard LL.M. in 2016. at, a Face book group that allows people to connect naturally and attend in-person and private events more easily. After listening to numerous students, the researcher conducted a quantitative survey among 100 respondents to assess respondents' perceptions of fairness in digital file sharing in various contexts (based on media price, its availability, regional licenses, copyright holder status, etc.). to understand better . .). Based on the survey results, the researcher conducted long-term, open-ended and loosely structured ethnographic interviews (50 interviews) to further deepen the understanding of the results. The most important finding of the study is that Harvard lawyers generally support digital piracy in certain contexts, despite having the best possible legal and professional knowledge. Interestingly, they are also more accepting of working for the government than the private sector. The results of this study provide a better understanding of how “fairness” is perceived by the younger generation of lawyers and pave the way for a more rational application of licensing laws.

Keywords: cognitive impairments, communication disorders, death penalty, executive function communication disorders, cognitive disorders, capital murder, executive function death penalty, egyptian law absence, justice, political cases piracy, digital sharing, perception of fairness, legal profession

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Authors: Vaiddehi Bansal, Ridhi Sahai, Kareem Kysia

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Overseas labor migration is currently one of the most important contributors to the economy of Bangladesh and is a highly profitable form of labor for Gulf Cooperative Council (GCC) countries. In 2019, 700,159 migrant workers from Bangladeshtraveled abroad for employment. GCC countries are a major destination for Bangladeshi migrant workers, with Saudi Arabia being the most common destination for Bangladeshi migrant workers since 2016. Despite the high rate of migration between these countries every year, the OLR industry remains complex and often leaves migrants susceptible to human trafficking, forced labor, and modern slavery. While the prevalence of forced labor among Bangladeshi migrants in GCC countries is still unknown, the IOM estimates international migrant workers comprise one fourth of the victims of forced labor. Moreover, the onset of the global COVID-19 pandemic has exposed migrant workers to additional adverse situations, making them even more vulnerable to forced labor and health risks. This paper presents findings from a rapid assessment of the impacts of COVID-19 on OLR in Bangladesh, with an emphasis on the increased risk of forced labor among vulnerable migrant worker populations, particularly women.Rapid reviews are a useful approach to swiftly provide actionable evidence for informed decision-making during emergencies, such as the COVID-19 pandemic. The research team conducted semi-structured key information interviews (KIIs) with a range of stakeholders, including government officials, local NGOs, international organizations, migration researchers, and formal and informal recruiting agencies, to obtain insights on the multi-facted impacts of COVID-19 on the OLR sector. The research team also conducted a comprehensive review of available resources, including media articles, blogs, policy briefs, reports, white papers, and other online content, to triangulate findings from the KIIs. After screening for inclusion criteria, a total of 110 grey literature documents were included in the review. A total of 31 KIIs were conducted, data from which was transcribed and translated from Bangla to English, andanalyzed using a detailed codebook. Findings indicate that there was limited reintegration support for returnee migrants. Facing increasing amounts of debt, financial insecurity, and social discrimination, returnee migrants, were extremely vulnerable to forced labor and exploitation. Growing financial debt and limited job opportunities in their home country will likely push migrants to resort to unsafe migration channels. Evidence suggests that women, who are primarily domestic works in GCC countries, were exposed to increased risk of forced labor and workplace violence. Due to stay-at-home measures, women migrant workers were tasked with additional housekeeping working and subjected to longer work hours, wage withholding, and physical abuse. In Bangladesh, returnee women migrant workers also faced an increased risk of domestic violence.

Keywords: forced labor, migration, gender, human trafficking

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Authors: Aynura Valiyeva, Basil John Thomas

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Intra-firm communication is critical for building synergy amongst internal business units of a firm, where employees from various functional departments and ranks incorporate their decision-making, understanding of organizational objectives, as well as common norms and culture for better organizational effectiveness. This study builds on and assesses a framework of the causes and consequences of effective communication in business interactions between customer and supplier firms, and the path for efficient communication within a firm. The proposed study’s structural equation modeling (SEM) analysis based on 352 sample responses collected from firm representatives at different job positions ranging from marketing to logistics operations, reveals that, in the frame of reference of intra-organizational communication, organization characteristics and shared values, top management support and style of leadership, as well as information technology, are all significantly related to communication effectiveness. Furthermore, the frequency and variety of interactions enhance the outcome of communication, that improves a company’s performance. The results reveal that cultural factors are significantly related to communication effectiveness, as well as the shared beliefs and goals. In terms of organizational factors, leadership style, top management support and information technology are significant determinants of effective communication. Among the contextual factors, interaction frequency and diversity are found to be priority factors. This study also tests the relationship between supplier and supplier firm performance in the context of communication effectiveness, and finds that they are closely related, when trust and commitment is built between business partners. When firms do business in other multicultural contexts, language and shared values with destination country must be considered significant elements of communication process.

Keywords: business performance, intra-firm communication, inter-firm communication, structural equation modeling

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Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

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In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

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Authors: Siti N. I. Mat Kamal, Othman Ibrahim, Mehrbakhsh Nilashi, Jafalizan M. Jali

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The use of digital forensics (DF) is nowadays essential for law enforcement agencies to identify analysis and interpret the digital information derived from digital sources. In Malaysia, the engagement of Malaysian Law Enforcement Agencies (MLEA) with this new technology is not evenly distributed. To investigate the factors influencing the adoption of DF in Malaysia law enforcement agencies’ operational environment, this study proposed the initial theoretical framework based on the integration of technology organization environment (TOE), institutional theory, and human organization technology (HOT) fit model. A questionnaire survey was conducted on selected law enforcement agencies in Malaysia to verify the validity of the initial integrated framework. Relative advantage, compatibility, coercive pressure, normative pressure, vendor support and perceived technical competence of technical staff were found as the influential factors on digital forensics adoption. In addition to the only moderator of this study (agency size), any significant moderating effect on the perceived technical competence and the decision to adopt digital forensics by Malaysian law enforcement agencies was found insignificant. Thus, these results indicated that the developed integrated framework provides an effective prediction of the digital forensics adoption by Malaysian law enforcement agencies.

Keywords: digital forensics, digital forensics adoption, digital information, law enforcement agency

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Authors: Claudeny Simone Alves Santana, Alexandre Simas De Medeiros, Marcelino Aurélio Vieira Da Silva

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The aim of the study was to assess the performance of pavements over time, considering the principles of Life Cycle Assessment (LCA) and the ability to withstand vehicle loads and associated environmental impacts. Within the study boundary, pavement design was conducted using the Mechanistic-Empirical Method, adopting criteria based on pavement cracking and wheel path rutting while also considering factors such as soil characteristics, material thickness, and the distribution of forces exerted by vehicles. The Ecoinvent® 3.6 database and SimaPro® software were employed to calculate emissions, and SICRO 3 information was used to estimate costs. Consequently, the study sought to identify the service that had the greatest impact on greenhouse gas emissions. The results were compared for design life periods of 10 and 30 years, considering structural performance and load-bearing capacity. Additionally, environmental impacts in terms of CO2 emissions per standard axle and construction costs in dollars per standard axle were analyzed. Based on the conducted analyses, it was possible to determine which pavement exhibited superior performance over time, considering technical, environmental, and economic criteria. One of the findings indicated that the mechanical characteristics of the soils used in the pavement layer directly influence the thickness of the pavement and the quantity of greenhouse gases, with a difference of approximately 7000 Kg CO2 Eq. The transportation service was identified as having the most significant negative impact. Other notable observations are that the study can contribute to future project guidelines and assist in decision-making regarding the selection of the most suitable pavement in terms of durability, load-bearing capacity, and sustainability.

Keywords: life cycle assessment, greenhouse gases, urban paving, service cost

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Authors: Calvin Rong, Regina Agassian, Mindy Engle-Friedman

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Climate changes, including rising sea levels and increases in global temperature, can have major effects on resource availability, leading to increased competition for resources and rising food prices. The abstract nature and often delayed consequences of many ecological problems cause people focus on immediate, specific, and personal events and circumstances that compel immediate and emotional involvement. This finding may be explained by the challenges humans have in imagining themselves in the future, a shortcoming that interferes with decision-making involving far-off rewards, and leads people to indicate a lower concern toward the future than to present circumstances. The present study sought to assess whether priming people to think of themselves in the future might strengthen the connection to their future selves and stimulate environmentally-protective behavior. We hypothesize that priming participants to think about themselves in the future would increase concern for the future environment. 45 control participants were primed to think about themselves in the present, and 42 participants were primed to think about themselves in the futures. After priming, the participants rated their concern over access to clean water, food, and energy on a scale of 1 to 10. They also rated their predicted care levels for the environment at age points 40, 50, 60, 70, 80, and 90 on a scale of 1(not at all) to 10 (very much). Predicted care levels at age 90 for the experimental group was significantly higher than for the control group. Overall the experimental group rated their concern for resources higher than the control. In comparison to the control group (M=7.60, SD=2.104) participants in the experimental group had greater concern for clean water (M=8.56, SD=1.534). In comparison to the control group (M=7.49, SD=2.041) participants in the experimental group were more concerned about food resources (M=8.41, SD=1.830). In comparison to the control group (M=7.22, SD=1.999) participants in the experimental group were more concerned about energy resources (M=8.07, SD=1.967). This study assessed whether a priming strategy could be used to encourage pro-environmental practices that protect limited resources. Future-self priming helped participants see past short term issues and focus on concern for the future environment.

Keywords: climate change, future, priming, global warming

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Authors: Gajendra Kumar Mourya, Dinesh Bhatia, Akash Handique, Sunita Warjri, Syed Achaab Amir

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Nowadays, Medical imaging has become an integral part of modern healthcare. Abdominal CT images are an invaluable mean for abdominal organ investigation and have been widely studied in the recent years. Diagnosis of liver pathologies is one of the major areas of current interests in the field of medical image processing and is still an open problem. To deeply study and diagnose the liver, segmentation of liver is done to identify which part of the liver is mostly affected. Manual segmentation of the liver in CT images is time-consuming and suffers from inter- and intra-observer differences. However, automatic or semi-automatic computer aided segmentation of the Liver is a challenging task due to inter-patient Liver shape and size variability. In this paper, we present a technique for automatic segmenting the liver from CT images using Random Forest Classifier. Random forests or random decision forests are an ensemble learning method for classification that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes of the individual trees. After comparing with various other techniques, it was found that Random Forest Classifier provide a better segmentation results with respect to accuracy and speed. We have done the validation of our results using various techniques and it shows above 89% accuracy in all the cases.

Keywords: CT images, image validation, random forest, segmentation

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Authors: A. Talaei, M. Ahiduzzaman, A. Kumar

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In Canada, an increase in the production of iron and steel is anticipated for satisfying the increasing demand of iron and steel in the oil sands and automobile industries. It is predicted that GHG emissions from iron and steel sector will show a continuous increase till 2030 and, with emissions of 20 million tonnes of carbon dioxide equivalent, the sector will account for more than 2% of total national GHG emissions, or 12% of industrial emissions (i.e. 25% increase from 2010 levels). Therefore, there is an urgent need to improve the energy intensity and to implement energy efficiency measures in the industry to reduce the GHG footprint. This paper analyzes the current energy consumption in the Canadian iron and steel industries and identifies energy efficiency opportunities to improve the energy intensity and mitigate greenhouse gas emissions from this industry. In order to do this, a demand tree is developed representing different iron and steel production routs and the technologies within each rout. The main energy consumer within the industry is found to be flared heaters accounting for 81% of overall energy consumption followed by motor system and steam generation each accounting for 7% of total energy consumption. Eighteen different energy efficiency measures are identified which will help the efficiency improvement in various subsector of the industry. In the sintering process, heat recovery from coolers provides a high potential for energy saving and can be integrated in both new and existing plants. Coke dry quenching (CDQ) has the same advantages. Within the blast furnace iron-making process, injection of large amounts of coal in the furnace appears to be more effective than any other option in this category. In addition, because coal-powered electricity is being phased out in Ontario (where the majority of iron and steel plants are located) there will be surplus coal that could be used in iron and steel plants. In the steel-making processes, the recovery of Basic Oxygen Furnace (BOF) gas and scrap preheating provides considerable potential for energy savings in BOF and Electric Arc Furnace (EAF) steel-making processes, respectively. However, despite the energy savings potential, the BOF gas recovery is not applicable in existing plants using steam recovery processes. Given that the share of EAF in steel production is expected to increase the application potential of the technology will be limited. On the other hand, the long lifetime of the technology and the expected capacity increase of EAF makes scrap preheating a justified energy saving option. This paper would present the results of the assessment of the above mentioned options in terms of the costs and GHG mitigation potential.

Keywords: Iron and Steel Sectors, Energy Efficiency Improvement, Blast Furnace Iron-making Process, GHG Mitigation

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Authors: Sarah Ullrich, Juliane Rolle, Christian Beste, Nicole Wolff

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Inhibition and cognitive flexibility are essential parts of executive functions in our daily lives, as they enable the avoidance of unwanted responses or selectively switch between mental processes to generate appropriate behavior. There is growing interest in improving inhibition and response selection through brief mindfulness-based meditations. Arguably, open-monitoring meditation (OMM) improves inhibitory and flexibility performance by optimizing cognitive control and information processing. Yet, the underlying neurophysiological processes have been poorly studied. Using the Simon-Go/Nogo paradigm, the present work examined the effect of a single 15-minute smartphone app-based OMM on inhibitory performance and response selection in meditation novices. We used both behavioral and neurophysiological measures (event-related potentials, ERPs) to investigate which subprocesses of response selection and inhibition are altered after OMM. The study was conducted in a randomized crossover design with N = 32 healthy adults. We thereby investigated Go and Nogo trials in the paradigm. The results show that as little as 15 minutes of OMM can improve response selection and inhibition at behavioral and neurophysiological levels. More specifically, OMM reduces the rate of false alarms, especially during Nogo trials regardless of congruency. It appears that OMM optimizes conflict processing and response inhibition compared to no meditation, also reflected in the ERP N2 and P3 time windows. The results may be explained by the meta control model, which argues in terms of a specific processing mode with increased flexibility and inclusive decision-making under OMM. Importantly, however, the effects of OMM were only evident when there was the prior experience with the task. It is likely that OMM provides more cognitive resources, as the amplitudes of these EKPs decreased. OMM novices seem to induce finer adjustments during conflict processing after familiarization with the task.

Keywords: EEG, inhibition, meditation, Simon Nogo

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Authors: Eyob Seife, Tesfalem Teshome, Bereket Seyoum, Behailu Getachew, Yohans Demis

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Developing countries continue to face preventable communicable diseases, such as vaccine-preventable diseases. The Expanded Programme on Immunization (EPI) was established by the World Health Organization in 1974 to control these diseases. Health data use is crucial in decision-making, but ensuring data quality remains challenging. The study aimed to assess the accuracy ratio, timeliness, and quality index of regular immunization programme data in the Birkod district of the Somali Region, Ethiopia. For poor data quality, technical, contextual, behavioral, and organizational factors are among contributors. The study used a quantitative cross-sectional design conducted in September 2022GC using WHO-recommended data quality self-assessment tools. The accuracy ratio and timeliness of reports on regular immunization programmes were assessed for two health centers and three health posts in the district for one fiscal year. Moreover, the quality index assessment was conducted at the district level and health facilities by trained assessors. The study found poor data quality in the accuracy ratio and timeliness of reports at all health units, which includes zeros. Overreporting was observed for most facilities, particularly at the health post level. Health centers showed a relatively better accuracy ratio than health posts. The quality index assessment revealed poor quality at all levels. The study recommends that responsible bodies at different levels improve data quality using various approaches, such as the capacitation of health professionals and strengthening the quality index components. The study highlighted the need for attention to data quality in general, specifically at the health post level, and improving the quality index at all levels, which is essential.

Keywords: Birkod District, data quality, quality index, regular immunization programme, Somali Region-Ethiopia

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Authors: Yolina A. Petrova, Georgi I. Petkov

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The paper presents a symbolic model for category learning and categorization (called RoleMap). Unlike the other models which implement learning in a separate working mode, role-governed category learning and categorization emerge in RoleMap while it does its usual reasoning. The model is based on several basic mechanisms known as reflecting the sub-processes of analogy-making. It steps on the assumption that in their everyday life people constantly compare what they experience and what they know. Various commonalities between the incoming information (current experience) and the stored one (long-term memory) emerge from those comparisons. Some of those commonalities are considered to be highly important, and they are transformed into concepts for further use. This process denotes the category learning. When there is missing knowledge in the incoming information (i.e. the perceived object is still not recognized), the model makes anticipations about what is missing, based on the similar episodes from its long-term memory. Various such anticipations may emerge for different reasons. However, with time only one of them wins and is transformed into a category member. This process denotes the act of categorization.

Keywords: analogy-making, categorization, category learning, cognitive modeling, role-governed categories

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