Search results for: Artificial Neural network

Authors: Laura N. Bolivar T.

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The tourism importance for regional development is mainly highlighted by the collaborative, cooperating and competitive relationships of the involved agents. The fostering of associativity processes, in particular, the cluster approach emphasizes the beneficial outcomes from the concentration of enterprises, where innovation and entrepreneurship flourish and shape the dynamics for tourism empowerment. Considering the department of Huila, it is located in the south-west of Colombia and holds the biggest coffee production in the country, although it barely contributes to the national GDP. Hence, its economic development strategy is looking for more dynamism and Huila could be consolidated as a leading destination for cultural, ecological and heritage tourism, if at least the public policy making processes for the tourism management of La Tatacoa Desert, San Agustin Park and Bambuco’s National Festival, were implemented in a more efficient manner. In this order of ideas, this study attempts to address the potential restrictions and beneficial factors for the consolidation of the tourism sector of Huila-Colombia as a cluster and how could it impact its regional development. Therefore, a set of theoretical frameworks such as the Tourism Routes Approach, the Tourism Breeding Environment, the Community-based Tourism Method, among others, but also a collection of international experiences describing tourism clustering processes and most outstanding problematics, is analyzed to draw up learning points, structure of proceedings and success-driven factors to be contrasted with the local characteristics in Huila, as the region under study. This characterization involves primary and secondary information collection methods and comprises the South American and Colombian context together with the identification of involved actors and their roles, main interactions among them, major tourism products and their infrastructure, the visitors’ perspective on the situation and a recap of the related needs and benefits regarding the host community. Considering the umbrella concepts, the theoretical and the empirical approaches, and their comparison with the local specificities of the tourism sector in Huila, an array of shortcomings is analytically constructed and a series of guidelines are proposed as a way to overcome them and simultaneously, raise economic development and positively impact Huila’s well-being. This non-exhaustive bundle of guidelines is focused on fostering cooperating linkages in the actors’ network, dealing with Information and Communication Technologies’ innovations, reinforcing the supporting infrastructure, promoting the destinations considering the less known places as well, designing an information system enabling the tourism network to assess the situation based on reliable data, increasing competitiveness, developing participative public policy-making processes and empowering the host community about the touristic richness. According to this, cluster dynamics would drive the tourism sector to meet articulation and joint effort, then involved agents and local particularities would be adequately assisted to cope with the current changing environment of globalization and competition.

Keywords: innovative strategy, local development, network of tourism actors, tourism cluster

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Authors: Schulz Peter, Kee Kalya, Lwin May, Goh Wilson, Chia Kendrikck, Chueng Max, Lam Thomas, Sung Joseph

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As Artificial Intelligence (AI) is progressively making inroads into clinical practice, questions have arisen as to whether acceptance of AI is skewed toward certain medical practitioner segments, even within particular specializations. This study examines distinct AI acceptance among gastroenterologists with contrasting levels of seniority/experience when interacting with AI typologies. Data from 319 gastroenterologists show the presence of four distinct clusters of clinicians based on experience levels and perceived risk typologies. Analysis of cluster-based responses further revealed that acceptance of AI was not uniform. Our findings showed that clinician experience and risk perspective have an interactive role in influencing AI acceptance. Senior clinicians with low-risk perceptions were highly accepting of AI, but those with high-risk perceptions of AI were substantially less accepting. In contrast, junior clinicians were more inclined to embrace AI when they perceived high risk, yet they hesitated to adopt AI when the perceived risk was minimal.

Keywords: risk perception, acceptance, trust, medicine

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Authors: Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu

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Causal inference from observational data is receiving wide applications in many fields. However, unidentifiable situations, where causal effects cannot be uniquely computed from observational data, pose critical barriers to applying causal inference to complicated real applications. In this paper, we develop a bounding method for estimating the average causal effect (ACE) under unidentifiable situations due to hidden confounders. We propose to parameterize the unknown exogenous random variables and structural equations of a causal model using neural networks and implicit generative models. Then, with an adversarial learning framework, we search the parameter space to explicitly traverse causal models that agree with the given observational distribution and find those that minimize or maximize the ACE to obtain its lower and upper bounds. The proposed method does not make any assumption about the data generating process and the type of the variables. Experiments using both synthetic and real-world datasets show the effectiveness of the method.

Keywords: average causal effect, hidden confounding, bound estimation, generative adversarial learning

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Authors: Oleksii Bychkov

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The fundamental difference between randomness and vagueness is that the former requires statistical research. These issues were studied by Zadeh L, Dubois D., Prad A. The theory of possibility works with expert assessments, hypotheses, etc. gives an idea of the characteristics of the problem situation, the nature of the goals and real limitations. Possibility theory examines experiments that are not repeated. The article discusses issues related to the formalization of a fuzzy, uncertain idea of reality. The author proposes to expand the classical model of the theory of possibilities by introducing a measure of necessity. The proposed model of the theory of possibilities allows us to extend the measures of possibility and necessity onto a Boolean while preserving the properties of the measure. Thus, upper and lower estimates are obtained to describe the fact that the event will occur. Knowledge of the patterns that govern mass random, uncertain, fuzzy events allows us to predict how these events will proceed. The article proposed for publication quite fully reveals the essence of the construction and use of the theory of probability and the theory of possibility.

Keywords: possibility, artificial, modeling, axiomatics, intellectual approach

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Authors: Ananda Perera

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Computer-Assisted Medical Evaluation of Symptoms (CAMEOS) is a medical expert system designed to help General Practices (GPs) make an accurate diagnosis. CAMEOS comprises a knowledge base, user input, inference engine, reasoning module, and output statement. The knowledge base was developed by the author. User input is an Html file. The physician user collects data in the consultation. Data is sent to the inference engine at servers. CAMEOS uses set theory to simulate diagnostic reasoning. The program output is a list of differential diagnoses, the most probable diagnosis, and the diagnostic reasoning.

Keywords: CDSS, computerized decision support systems, expert systems, general practice, diagnosis, diagnostic systems, primary care diagnostic system, artificial intelligence in medicine

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Authors: Shady Gamal Aziz Shehata

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Difficulty in defining construction quality arises due to perception based on the nature and requirements of the market, the different partners themselves and the results they want. Quantitative research was used in this constructivist research. A case-based study was conducted to assess the structures of positive attitudes and expectations in the context of quality improvement. A survey based on expert opinions was analyzed among construction organizations/companies operating in the construction industry in Pakistan. The financial strength, management structure and construction experience of the construction companies formed the basis of their selection. A good concept is visible at the project level and is seen as the most valuable part of the construction project. Each quality improvement technique was expected to increase the user's profits by improving the efficiency of the construction project. The Survey is useful for construction professionals to evaluate current construction concepts and expectations for the application of quality improvement techniques in construction projects.

Keywords: correlation analysis, lean construction tools, lean construction, logistic regression analysis, risk management, safety construction quality, expectation, improvement, perception

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Authors: Sarah Reker, Christiane H. Kellner

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From the perspective of people with disabilities, inequalities can also emerge from spatial segregation, the lack of social contacts or limited economic resources. In order to reduce or even eliminate these disadvantages and increase general well-being, community-based participation as well as decentralisation efforts within exclusively residential homes is essential. Therefore, the new research project “Index for participation development and quality of life for persons with disabilities”(TeLe-Index, 2014-2016), which is anchored at the Technische Universität München in Munich and at a large residential complex and service provider for persons with disabilities in the outskirts of Munich aims to assist the development of community-based living environments. People with disabilities should be able to participate in social life beyond the confines of the institution. Since a diverse society is a society in which different individual needs and wishes can emerge and be catered to, the ultimate goal of the project is to create an environment for all citizens–regardless of disability, age or ethnic background–that accommodates their daily activities and requirements. The UN-Convention on the Rights of Persons with Disabilities, which Germany also ratified, postulates the necessity of user-centered design, especially when it comes to evaluating the individual needs and wishes of all citizens. Therefore, a multidimensional approach is required. Based on this insight, the structure of the town-like center will be remodeled to open up the community to all people. This strategy should lead to more equal opportunities and open the way for a much more diverse community. Therefore, macro-level research questions were inspired by quality of life theory and were formulated as follows for different dimensions: •The user dimension: what needs and necessities can we identify? Are needs person-related? Are there any options to choose from? What type of quality of life can we identify? The economic dimension: what resources (both material and staff-related) are available in the region? (How) are they used? What costs (can) arise and what effects do they entail? •The environment dimension: what “environmental factors” such as access (mobility and absence of barriers) prove beneficial or impedimental? In this context, we have provided academic supervision and support for three projects (the construction of a new school, inclusive housing for children and teenagers with disabilities and the professionalization of employees with person-centered thinking). Since we cannot present all the issues of the umbrella-project within the conference framework, we will be focusing on one project more in-depth, namely “Outpatient Housing Options for Children and Teenagers with Disabilities”. The insights we have obtained until now will enable us to present the intermediary results of our evaluation. The most central questions pertaining to this part of the research were the following: •How have the existing network relations been designed? •What meaning (or significance) does the existing service offers and structures have for the everyday life of an external residential group? These issues underpinned the environmental analyses as well as the qualitative guided interviews and qualitative network analyses we carried out.

Keywords: decentralisation, environmental analyses, outpatient housing options for children and teenagers with disabilities, qualitative network analyses

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Authors: Julius Y Asamoah

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Mobile money has seen faster adoption in the decade. Its emergence serves as an essential driver of financial inclusion and an innovative financial service delivery channel, especially to the unbanked population. The rising importance of mobile money services has caught policymakers and regulators' attention, seeking to understand the many issues emerging from this context. At the same time, it is unlocking the potential of knowledge of this new technology. Regulatory responses and support are essential, requiring significant changes to current regulatory practices in Ghana. The article aims to answer the following research questions: "What risk does an unregulated mobile money service pose to consumers and the financial system? "What factors stimulate and hinder the introduction of mobile payments in developing countries? The sample size used was 250 respondents selected from the study area. The study has adopted an analytical approach comprising a combination of qualitative and quantitative data collection methods. Actor-network theory (ANT) is used as an interpretive lens to analyse this process. ANT helps analyse how actors form alliances and enrol other actors, including non-human actors (i.e. technology), to secure their interests. The study revealed that government regulatory policies impact mobile money as critical to mobile money services in developing countries. Regulatory environment should balance the needs of advancing access to finance with the financial system's stability and draw extensively from Kenya's work as the best strategies for the system's players. Thus, regulators need to address issues related to the enhancement of supportive regulatory frameworks. It recommended that the government involve various stakeholders, such as mobile phone operators. Moreover, the national regulatory authority creates a regulatory environment that promotes fair practices and competition to raise revenues to support a business-enabling environment's key pillars as infrastructure.

Keywords: actor-network theory (ANT), cashless future, Developing countries, Ghana, Mobile Money

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Authors: Enrique Barra, Aldo Gordillo, Juan Quemada

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This paper presents the Virtual Science Hub platform. It is an open source platform that combines a social network, an e-learning authoring tool, a video conference service and a learning object repository for science teaching enrichment. These four main functionalities fit very well together. The platform was released in April 2012 and since then it has not stopped growing. Finally we present the results of the surveys conducted and the statistics gathered to validate this approach.

Keywords: e-learning, platform, authoring tool, science teaching, educational sciences

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Authors: Daniela Tapusi, Adrian Andronic, Naomi Tufan, Ruxandra Erbașu, Ioana Teodorescu

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The proposed theme of this article falls within the policy of reducing carbon emissions imposed by the ‘Green New Deal’ by replacing structural elements made of energy-intensive materials with ecological materials. In this sense, wood has many qualities (high strength/mass and stiffness/mass ratio, low specific gravity, recovery/recycling) that make it competitive with classic building materials. The topological optimization of the linear glulam elements, resulting from different types of analysis (Finite Element Method, simple regression on metamodels), tests on models or by Monte-Carlo simulation, leads to a material reduction of more than 10%. This article proposes a method of obtaining topologically optimized shapes for different types of glued laminated timber beams. The results obtained will constitute the database for AI training.

Keywords: timber, glued laminated timber, artificial-intelligence, environment, carbon emissions

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Authors: Andrew D. Henshaw, James M. Austin

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Introduction: Human trafficking is an increasingly serious transnational criminal enterprise and social security issue. Despite ongoing efforts to mitigate the phenomenon and a significant expansion of security scrutiny over past decades, it is not receding. This is true for many nations in Southeast Asia, widely recognized as the global hub for trafficked persons, including men, women, and children. Clearly, human trafficking is difficult to address because there are numerous drivers, causes, and motivators for it to persist, such as non-military and non-traditional security challenges, i.e., climate change, global warming displacement, and natural disasters. These make displaced persons and refugees particularly vulnerable. The issue is so large conservative estimates put a dollar value at around $150 billion-plus per year (Niethammer, 2020) spanning sexual slavery and exploitation, forced labor, construction, mining and in conflict roles, and forced marriages of girls and women. Coupled with corruption throughout military, police, and civil authorities around the world, and the active hands of powerful transnational criminal organizations, it is likely that such figures are grossly underestimated as human trafficking is misreported, under-detected, and deliberately obfuscated to protect those profiting from it. For example, the 2022 UN report on human trafficking shows a 56% reduction in convictions in that year alone (UNODC, 2022). Our Approach: To better understand this, our research utilizes a bespoke methodology. Applying a JAM (Juxtaposition Assessment Matrix), which we previously developed to detect flows of dark money around the globe (Henshaw, A & Austin, J, 2021), we now focus on the human trafficking paradigm. Indeed, utilizing a JAM methodology has identified key indicators of human trafficking not previously explored in depth. Being a set of structured analytical techniques that provide panoramic interpretations of the subject matter, this iteration of the JAM further incorporates behavioral and driver indicators, including the employment of Open-Source Artificial Intelligence (OS-AI) across multiple collection points. The extracted behavioral data was then applied to identify non-traditional indicators as they contribute to human trafficking. Furthermore, as the JAM OS-AI analyses data from the inverted position, i.e., the viewpoint of the traffickers, it examines the behavioral and physical traits required to succeed. This transposed examination of the requirements of success delivers potential leverage points for exploitation in the fight against human trafficking in a new and novel way. Findings: Our approach identified new innovative datasets that have previously been overlooked or, at best, undervalued. For example, the JAM OS-AI approach identified critical 'dark agent' lynchpins within human trafficking that are difficult to detect and harder to connect to actors and agents within a network. Our preliminary data suggests this is in part due to the fact that ‘dark agents’ in extant research have been difficult to detect and potentially much harder to directly connect to the actors and organizations in human trafficking networks. Our research demonstrates that using new investigative techniques such as OS-AI-aided JAM introduces a powerful toolset to increase understanding of human trafficking and transnational crime and illuminate networks that, to date, avoid global law enforcement scrutiny.

Keywords: human trafficking, open-source intelligence, transnational crime, human security, international human rights, intelligence analysis, JAM OS-AI, Dark Money

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Authors: Ademola Ibukunolu Atanda

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Research undertakings are meant to proffer solutions to issues and challenges in society. This justifies the need for research in ivory towers. Multinational and non-governmental organisations, as well as foundations, commit financial resources to support research endeavours. In recent times, the direction and dimension of research undertaking encourage collaborations, whereby experts from different disciplines or specializations would bring their expertise in addressing any identified problem, whether in humanities or sciences. However, the extent to which collaborative research undertakings are perceived and embraced by academic staff would determine the impact collaborative research would have on society. To this end, this study investigated academic staff’s perception and willingness to be involved in collaborative research for the purpose of proffering solutions to societal problems. The study adopted a descriptive research design. The population comprised academic staff in southern Nigeria. The sample was drawn through a convenient sampling technique. The data were collected using a questionnaire titled “Perception and Willingness to Participate in Collaborative Research Questionnaire (PWPCRQ)’ using Google Forms. Data collected were analyzed using descriptive statistics of simple percentages, mean and charts. The findings showed that Academic Staff’s readiness to participate in collaborative research is to a great extent (89%) and they participate in collaborative research very often (51%). The Academic Staff was involved more in collaboration research among their colleagues within their universities (1.98) than participation in inter-disciplines collaboration (1.47) with their colleagues outside Nigeria. Collaborative research was perceived to impact on development (2.5). Collaborative research offers the following benefits to members’ aggregation of views, the building of an extensive network of contacts, enhancement of sharing of skills, facilitation of tackling complex problems, increased visibility of research network and citations and promotion of funding opportunities. The study concluded that Academic staff in universities in the South-West of Nigeria participate in collaborative research but with their colleagues within Nigeria rather than outside the country. Based on the findings, it was recommended that the management of universities in South-West Nigeria should encourage collaborative research with some incentives.

Keywords: collaboration, research, development, participation

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Authors: Mona Mikhail Shakhloul Gadalla

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The brand-new media revolution, which features a huge range of new media technologies like blogs, social networking, visual worlds, and wikis, has had a tremendous impact on communications, traditional media and across different disciplines. This paper gives an evaluation of the impact of recent media technology on the news, social interactions and conventional media in developing and advanced nations. The look points to the reality that there is a widespread impact of recent media technologies on the news, social interactions and the conventional media in developing and developed nations, albeit undoubtedly and negatively. Social interactions have been considerably affected, in addition to news manufacturing and reporting. It's miles reiterated that regardless of the pervasiveness of recent media technologies, it might now not carry a complete decline of conventional media. This paper contributes to the theoretical framework of the new media and will assist in assessing the extent of the effect of the new media in special places.

Keywords: court reporting, offenders in media, quantitative content analysis, victims in mediamedia literacy, ICT, internet, education communication, media, news, new media technologies, social interactions, traditional media

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Authors: Chao Wang

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Under rapid innovation of information technology, the media plays a very important role in the dissemination of information, and it has a totally different analogy generations face. However, the involvement of narrative images provides more possibilities of narrative text. "Images" through the process of aperture, a camera shutter and developable photosensitive processes are manufactured, recorded and stamped on paper, displayed on a computer screen-concretely saved. They exist in different forms of files, data, or evidence as the ultimate looks of events. By the interface of media and network platforms and special visual field of the viewer, class body space exists and extends out as thin as sebum layer, extremely soft and delicate with real full tension. The physical space of sebum layer of confuses the fact that physical objects exist, needs to be established under a perceived consensus. As at the scene, the existing concepts and boundaries of physical perceptions are blurred. Sebum layer physical simulation shapes the “Topical-Similarity" immersing, leading the contemporary social practice communities, groups, network users with a kind of illusion without the presence, i.e. a non-real illusion. From the investigation and discussion of literatures, digital movies editing manufacture and produce the variability characteristics of time (for example, slices, rupture, set, and reset) are analyzed. Interactive eBook has an unique interaction in "Waiting-Greeting" and "Expectation-Response" that makes the operation of image narrative structure more interpretations functionally. The works of digital editing and interactive technology are combined and further analyze concept and results. After digitization of Interventional Imaging and interactive technology, real events exist linked and the media handing cannot be cut relationship through movies, interactive art, practical case discussion and analysis. Audience needs more rational thinking about images carried by the authenticity of the text.

Keywords: sebum layer, topical and similarity, interactive technology, image narrative

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Authors: Mehmet Karaata

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Given two distinct vertices (nodes) source s and target t of a graph G = (V, E), the two node-disjoint paths problem is to identify two node-disjoint paths between s ∈ V and t ∈ V . Two paths are node-disjoint if they have no common intermediate vertices. In this paper, we present an algorithm with O(m)-time complexity for finding two node-disjoint paths between s and t in arbitrary graphs where m is the number of edges. The proposed algorithm has a wide range of applications in ensuring reliability and security of sensor, mobile and fixed communication networks.

Keywords: disjoint paths, distributed systems, fault-tolerance, network routing, security

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Authors: Shankaran Sitarama

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Teamwork is an extremely effective pedagogical tool in engineering education. New Product Development (NPD) has been an effective strategy of companies to streamline and bring innovative products and solutions to customers. Thus, Engineering curriculum in many schools, some collaboratively with business schools, have brought NPD into the curriculum at the graduate level. Teamwork is invariably used during instruction, where students work in teams to come up with new products and solutions. There is a significant emphasis of grade on the semester long teamwork for it to be taken seriously by students. As the students work in teams and go through this process to develop the new product prototypes, their effectiveness and learning to a great extent depends on how they function as a team and go through the creative process, come together, and work towards the common goal. A core attribute of a successful NPD team is their creativity and innovation. The team needs to be creative as a group, generating a breadth of ideas and innovative solutions that solve or address the problem they are targeting and meet the user’s needs. They also need to be very efficient in their teamwork as they work through the various stages of the development of these ideas resulting in a POC (proof-of-concept) implementation or a prototype of the product. The simultaneous requirement of teams to be creative and at the same time also converge and work together imposes different types of tensions in their team interactions. These ideational tensions / conflicts and sometimes relational tensions / conflicts are inevitable. Effective teams will have to deal with the Team dynamics and manage it to be resilient enough and yet be creative. This research paper provides a computational analysis of the teams’ communication that is reflective of the team dynamics, and through a superimposition of latent semantic analysis with social network analysis, provides a computational methodology of arriving at patterns of visual interaction. These team interaction patterns have clear correlations to the team dynamics and provide insights into the functioning and thus the effectiveness of the teams. 23 student NPD teams over 2 years of a course on Managing NPD that has a blend of engineering and business school students is considered, and the results are presented. It is also correlated with the teams’ detailed and tailored individual and group feedback and self-reflection and evaluation questionnaire.

Keywords: team dynamics, social network analysis, team interaction patterns, new product development teamwork, NPD teams

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Authors: Doaa El-Shereef

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The Canaanite civilization was one of the early great civilizations of the Near East, they influenced and been influenced from the civilizations of the ancient world especially the Egyptian and Mesopotamia civilizations. The development of the Canaanite trade started from the Chalcolithic Age to the Iron Age through the oldest trade route in the Middle East. This paper will focus on defining the Canaanites and from where did they come from and the meaning of the term Canaan and how the Ancient Manuscripts define the borders of the land of Canaan and this essay will describe the Canaanite trade route and their exported goods such as cedar wood, and pottery.

Keywords: archaeology, bronze age, Canaanite, colonies, Massilia, pottery, shipwreck, vineyards

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Authors: Jing Jin

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The incorporation of artificial intelligence (AI) and machine learning (ML) in aircraft manufacturing and aerospace supply chains leads to the generation of a substantial amount of data among various tiers of suppliers and OEMs. Identifying the high-quality information challenges decision-makers. The application of AI/ML models necessitates access to 'high-quality' information to yield desired outputs. However, the process of information sharing introduces complexities, including distortion through various communication channels and biases introduced by both human and AI entities. This phenomenon significantly influences the quality of information, impacting decision-makers engaged in configuring supply chain systems. Traditionally, distorted information is categorized as 'low-quality'; however, this study challenges this perception, positing that distorted information, contributing to stakeholder goals, can be deemed high-quality within supply chains. The main aim of this study is to identify and evaluate the dimensions of information quality crucial to the UK aerospace supply chain. Guided by a central research question, "What information quality dimensions are considered when defining information quality in the UK aerospace supply chain?" the study delves into the intricate dynamics of information quality in the aerospace industry. Additionally, the research explores the nuanced impact of information distortion on stakeholders' decision-making processes, addressing the question, "How does the information distortion phenomenon influence stakeholders’ decisions regarding information quality in the UK aerospace supply chain system?" This study employs deductive methodologies rooted in positivism, utilizing a cross-sectional approach and a mono-quantitative method -a questionnaire survey. Data is systematically collected from diverse tiers of supply chain stakeholders, encompassing end-customers, OEMs, Tier 0.5, Tier 1, and Tier 2 suppliers. Employing robust statistical data analysis methods, including mean values, mode values, standard deviation, one-way analysis of variance (ANOVA), and Pearson’s correlation analysis, the study interprets and extracts meaningful insights from the gathered data. Initial analyses challenge conventional notions, revealing that information distortion positively influences the definition of information quality, disrupting the established perception of distorted information as inherently low-quality. Further exploration through correlation analysis unveils the varied perspectives of different stakeholder tiers on the impact of information distortion on specific information quality dimensions. For instance, Tier 2 suppliers demonstrate strong positive correlations between information distortion and dimensions like access security, accuracy, interpretability, and timeliness. Conversely, Tier 1 suppliers emphasise strong negative influences on the security of accessing information and negligible impact on information timeliness. Tier 0.5 suppliers showcase very strong positive correlations with dimensions like conciseness and completeness, while OEMs exhibit limited interest in considering information distortion within the supply chain. Introducing social network analysis (SNA) provides a structural understanding of the relationships between information distortion and quality dimensions. The moderately high density of ‘information distortion-by-information quality’ underscores the interconnected nature of these factors. In conclusion, this study offers a nuanced exploration of information quality dimensions in the UK aerospace supply chain, highlighting the significance of individual perspectives across different tiers. The positive influence of information distortion challenges prevailing assumptions, fostering a more nuanced understanding of information's role in the Industry 4.0 landscape.

Keywords: information distortion, information quality, supply chain configuration, UK aerospace industry

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Authors: Helen Pushkarskaya, Michael Smithson, Jane E. Joseph, Christine Corbly, Ifat Levy

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Studies of decision making under uncertainty generally focus on imprecise information about outcome probabilities (“ambiguity”). It is not clear, however, whether conflicting information about outcome probabilities affects decision making in the same manner as ambiguity does. Here we combine functional Magnetic Resonance Imaging (fMRI) and a simple gamble design to study this question. In this design, the levels of ambiguity and conflict are parametrically varied, and ambiguity and conflict gambles are matched on both expected value and variance. Behaviorally, participants avoided conflict more than ambiguity, and attitudes toward ambiguity and conflict did not correlate across subjects. Neurally, regional brain activation was differentially modulated by ambiguity level and aversion to ambiguity and by conflict level and aversion to conflict. Activation in the medial prefrontal cortex was correlated with the level of ambiguity and with ambiguity aversion, whereas activation in the ventral striatum was correlated with the level of conflict and with conflict aversion. This novel double dissociation indicates that decision makers process imprecise and conflicting information differently, a finding that has important implications for basic and clinical research.

Keywords: decision making, uncertainty, ambiguity, conflict, fMRI

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Authors: Thulane Paepae, Tumisang Seodigeng

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This paper demonstrates the use of a method of synthesizing process flowsheets using a graphical tool called the GH-plot and in particular, to look at how it can be used to compare the reactions of a combined simultaneous process with regard to their thermodynamics. The technique uses fundamental thermodynamic principles to allow the mass, energy and work balances locate the attainable region for chemical processes in a reactor. This provides guidance on what design decisions would be best suited to developing new processes that are more effective and make lower demands on raw material and energy usage.

Keywords: attainable regions, dimethyl ether, optimal reaction network, GH Space

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Authors: Lawrence Williams

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As the mechanism which converts domains to internet protocol (IP) addresses, Domain Name System (DNS) is an essential part of internet usage. It was not designed securely and can be subject to attacks. DNS attacks have become more frequent and sophisticated and the need for detecting and preventing them becomes more important for the modern network. DNS tunnelling attacks are one type of attack that are primarily used for distributed denial-of-service (DDoS) attacks and data exfiltration. Discussion of different techniques to detect and prevent DNS tunneling attacks is done. The methods, models, experiments, and data for each technique are discussed. A proposal about feasibility is made. Future research on these topics is proposed.

Keywords: DNS, tunneling, exfiltration, botnet

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Authors: Manavjit Singh Dhindsa, Ursula Das, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts.

Keywords: artificial intelligence, deep learning, forest fire management, fire risk assessment, fire simulation, machine learning, remote sensing, wildfire modeling

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Authors: Eugene Stepanov, Arkadi Ponossov

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Many mathematical models used in biological and other applications are ill-posed. The reason for that is the nature of differential equations, where the nonlinearities are assumed to be step functions, which is done to simplify the analysis. Prominent examples are switched systems arising from gene regulatory networks and neural field equations. This simplification leads, however, to theoretical and numerical complications. In the presentation, it is proposed to apply the theory of hybrid feedback controls to regularize the problem. Roughly speaking, one attaches a finite state control (‘automaton’), which follows the trajectories of the original system and governs its dynamics at the points of ill-posedness. The construction of the automaton is based on the classification of the attractors of the specially designed adjoint dynamical system. This ‘hybridization’ is shown to regularize the original switched system and gives rise to efficient hybrid numerical schemes. Several examples are provided in the presentation, which supports the suggested analysis. The method can be of interest in other applied fields, where differential equations contain step-like nonlinearities.

Keywords: hybrid feedback control, ill-posed problems, singular perturbation analysis, step-like nonlinearities

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Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

Abstract:

The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.

Keywords: augmented reality, machine learning, object recognition, virtual laboratories

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Authors: Ali Soroush, Mehdi Mirzaei Alavijeh, Touraj Ahmadi Jouybari, Fazel Zinat-Motlagh, Abbas Aghaei, Mari Ataee

Abstract:

Diabetes is a disease with long cardiovascular, renal, ophthalmic and neural complications. It is prevalent all around the world including Iran, and its prevalence is increasing. The aim of this study was to determine the factors related to self-care behavior based on health belief model among sample of Iranian diabetic patients. This cross-sectional study was conducted among 301 type 2 diabetic patients in Gachsaran, Iran. Data collection was based on an interview and the data were analyzed by SPSS version 20 using ANOVA, t-tests, Pearson correlation, and linear regression statistical tests at 95% significant level. Linear regression analyses showed the health belief model variables accounted for 29% of the variation in self-care behavior; and perceived severity and perceived self-efficacy are more influential predictors on self-care behavior among diabetic patients.

Keywords: diabetes, patients, self-care behaviors, health belief model

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Authors: Raghad A. Altowairgi

Abstract:

With the wide spread of social media platforms, young people tend to use them extensively as the first means of communication due to their ease and modernity. But these platforms often create a fertile ground for bullies to practice their aggressive behavior against their victims. Platform usage cannot be reduced, but intelligent mechanisms can be implemented to reduce the abuse. This is where machine learning comes in. Understanding and classifying text can be helpful in order to minimize the act of cyberbullying. Artificial intelligence techniques have expanded to formulate an applied tool to address the phenomenon of cyberbullying. In this research, machine learning models are built to classify text into two classes; cyberbullying and non-cyberbullying. After preprocessing the data in 4 stages; removing characters that do not provide meaningful information to the models, tokenization, removing stop words, and lowering text. BoW and TF-IDF are used as the main features for the five classifiers, which are; logistic regression, Naïve Bayes, Random Forest, XGboost, and Catboost classifiers. Each of them scores 92%, 90%, 92%, 91%, 86% respectively.

Keywords: cyberbullying, machine learning, Bag-of-Words, term frequency-inverse document frequency, natural language processing, Catboost

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Authors: Khalid Obaed Mahmod, Mesut Cevik

Abstract:

The term smart city has appeared recently and was accompanied by many definitions and concepts, but as a simplified and clear definition, it can be said that the smart city is a geographical location that has gained efficiency and flexibility in providing public services to citizens through its use of technological and communication technologies, and this is what distinguishes it from other cities. Smart cities connect the various components of the city through the main and sub-networks in addition to a set of applications and thus be able to collect data that is the basis for providing technological solutions to manage resources and provide services. The basis of the work of the smart city is the use of artificial intelligence and the technology of the Internet of Things. The work presents the concept of smart cities, the pillars, standards, and evaluation indicators on which smart cities depend, and the reasons that prompted the world to move towards its establishment. It also provides a simplified hypothetical way to measure the ideal smart city model by defining some indicators and key pillars, simulating them with logic circuits, and testing them to determine if the city can be considered an ideal smart city or not.

Keywords: factors, indicators, logic gates, pillars, smart city

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Authors: Mohammed Nabeel Khan, C. Perisamy

Abstract:

Convective vortices are normal highlights of air that ingest lower-entropy-energy at higher temperatures than they dismiss higher-entropy-energy to space. By means of the thermodynamic proficiency, it has been anticipated that the force of convective vortices relies upon the profundity of the convective layer. The atmospheric vortex engine is proposed as a gadget for delivering mechanical energy by methods for artificially produced vortex. The task of the engine is in view of the certainties that the environment is warmed from the base and cooled from the top. By generation of the artificial vortex, it is planned to take out the physical solar updraft tower and decrease the capital of the solar chimney power plants. The study shows the essentials of the atmospheric vortex engine, furthermore, audits the cutting edge in subject. Moreover, the study talks about a thought on using the solar energy as heat source to work the framework. All in all, the framework is attainable and promising for electrical power production.

Keywords: AVE, atmospheric vortex engine, atmosphere, updraft, vortex

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Authors: Gabriele Barrocas, Habon Issa

Abstract:

The amygdala is one of various brain regions that tend to be pathological in individuals with autism spectrum disorder (ASD). ASD is a prevalent and heterogeneous developmental disorder affecting all ethnic and socioeconomic groups and consists of a broad range of severity, etiology, and behavioral symptoms. Common features of ASD include but are not limited to repetitive behaviors, obsessive interests, and anxiety. Neuroscientists view the amygdala as the core of the neural system that regulates behavioral responses to anxiogenic and threatening stimuli. Despite this consensus, many previous studies and literature reviews on the amygdala’s alterations in individuals with ASD have reported inconsistent findings. In this review, we will address these conflicts by highlighting recent studies which reveal that anatomical and related socio-emotional differences detected between individuals with and without ASD are highly age-dependent. We will specifically discuss studies using functional magnetic resonance imaging (fMRI), structural MRI, and diffusion tensor imaging (DTI) to provide insights into the neuroanatomical substrates of ASD across development, with a focus on amygdala volumes, cell densities, and connectivity.

Keywords: autism, amygdala, development, abnormalities

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Authors: Beatriz Cortés, Andrés Boza, David Pérez, Llanos Cuenca

Abstract:

The Internet of Things (IoT) field is been applied in industries with different purposes. Sensing Enterprise (SE) is an attribute of an enterprise or a network that allows it to react to business stimuli originating on the internet. These fields have come into focus recently on the enterprises and there is some evidence of the use and implications in supply chain management while finding it as an interesting aspect to work on. This paper presents a revision and proposals of IoT applications in supply chain management.

Keywords: industrial, internet of things, production systems, sensing enterprises, sensor, supply chain management

Procedia PDF Downloads 429