Search results for: vulnerability intelligence

Authors: Farzaneh Badinloo, Niloufar Jalali-Moghadam, Reza Kormi-Nouri

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The aim of this study was to explore the short-term and working memory performances across age and gender in school aged children. Most of the studies have been interested in looking into memory changes in adult subjects. This study was instead focused on exploring both short-term and working memories of children over time. Totally 410 school child participants belonging to four age groups (approximately 8, 10, 12 and 14 years old) among which were 201 girls and 208 boys were employed in the study. digits forward and backward tests of the Wechsler children intelligence scale-revised were conducted respectively as short-term and working memory measures. According to results, there was found a general increment in both short-term and working memory scores across age (p ˂ .05) by which whereas short-term memory performance was shown to increase up to 12 years old, working memory scores showed no significant increase after 10 years old of age. No difference was observed in terms of gender (p ˃ .05). In conclusion, this study suggested that both short-term and working memories improve across age in children where 12 and 10 years of old are likely the crucial age periods in terms of short-term and working memories development.

Keywords: age, gender, short-term memory, working memory

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Authors: Brian Connett, Bryan O'Halloran

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Systems assets within critical infrastructures were seemingly safe from the exploitation or attack by nefarious cyberspace actors. Now, critical infrastructure is a target and the resources to exploit the cyber physical systems exist. These resources are characterized in terms of patience, stealth, replication-ability and extraordinary robustness. System owners are obligated to maintain a high level of protection measures. The difficulty lies in knowing when to fortify a critical infrastructure against an impending attack. Models currently exist that demonstrate the value of knowing the attacker’s capabilities in the cyber realm and the strength of the target. The shortcomings of these models are that they are not designed to respond to the inherent fast timing of an attack, an impetus that can be derived based on open-source reporting, common knowledge of exploits of and the physical architecture of the infrastructure. A useful model will inform systems owners how to align infrastructure architecture in a manner that is responsive to the capability, willingness and timing of the attacker. This research group has used an existing theoretical model for estimating parameters, and through analysis, to develop a decision tool for would-be target owners. The continuation of the research develops further this model by estimating the variable parameters. Understanding these parameter estimations will uniquely position the decision maker to posture having revealed the vulnerabilities of an attacker’s, persistence and stealth. This research explores different approaches to improve on current attacker-defender models that focus on cyber threats. An existing foundational model takes the point of view of an attacker who must decide what cyber resource to use and when to use it to exploit a system vulnerability. It is valuable for estimating parameters for the model, and through analysis, develop a decision tool for would-be target owners.

Keywords: critical infrastructure, cyber physical systems, modeling, exploitation

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Authors: Frederic Jumelle, Kelvin So, Didan Deng

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A method and system for neuropsychological performance test, comprising a mobile terminal, used to interact with a cloud server which stores user information and is logged into by the user through the terminal device; the user information is directly accessed through the terminal device and is processed by artificial neural network, and the user information comprises user facial emotions information, performance test answers information and user chronometrics. This assessment is used to evaluate the cognitive performance and emotional response of the subject to a series of dichotomous questions describing various situations of daily life and challenging the users' knowledge, values, ethics, and principles. In industrial applications, the timing of this assessment will depend on the users' need to obtain a service from a provider, such as opening a bank account, getting a mortgage or an insurance policy, authenticating clearance at work, or securing online payments.

Keywords: artificial intelligence, neurofinance, neuropsychology, risk management

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Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

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Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: classification, data mining, spam filtering, naive bayes, decision tree

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Authors: Mbuso Siwela

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Background: The Sub-Saharan Africa region has the greatest number of people eligible to receive antiretroviral treatment (ART). Multi-month Drug dispensing (MMD) of antiretroviral treatment (ART) aims to reduce patient-related barriers to access long-term treatment and improve health system efficiency. In Eswatini, however, few children and adolescents are on MMD. Young Heroes is implementing an HIV program that aims to avert new HIV infections in children and youth and improve treatment outcomes for children and adolescents living with HIV (C/ALHIV: 0-19 Years) and OVC caregivers with HIV prevention and impact mitigation interventions that prevent new HIV infections and reduce vulnerability. Aim of the study: The study aimed to ascertain factors that are associated with the assignment of the MMD model on C/ALHIVs. Methodology: The project provides treatment adherence support through well-trained community cadres (Home Visitors - HVs) at both community and health facility levels. During door-to-door visits, HVs track all C/ALHIV enrolled in the project monthly and refer any who might have stopped or interrupted treatment. C/ALHIV with unsuppressed viral load is supported through case conferencing and teen clubs. A quantitative cross-sectional analysis was conducted using STATA for children and adolescents living with HIV enrolled in the project. Bivariate analysis was conducted, and the Logistic Regression model was used to ascertain the effects of duration on ART on the choice of MMD model. Results: Data for 544 C/ALHIV (0-19 Years) was analyzed in STATA. Results show a strong association between (duration on ART, Age, being in teen club) and enrolment in an MMD model. Duration on ART is a major predictor for the choice of MMD model at (95% CI: 0.0012905 – 0.0039812; P = <0.0001). C/ALHIV who have been on ART for less than a year are less likely to be on MMD. C/ALHIVs who are 1 or more years on ART are more likely to be in 3 months dispensing, while those who are 5 years or more are most likely to be in 6 months model.

Keywords: C/ALHIV, OVC, HIV, treatment

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Authors: Rolland Epafras Fanggidae

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The impact of climate change such as natural disasters, crop failures, increasing crop pests, bad gisi on children and other impacts, will indirectly affect education, health, food safety, as well as the economy. The impact of climate change has put a man in a situation of vulnerability, which was powerless to meet the minimum requirements, it is in close contact with poverty. When talking about poverty, the most plausible is female. The role of women in Indonesia, particularly in East Nusa Tenggara in Domestic aktifity very central and dominant. This makes Indonesian woman can say "outstanding actor in the face of climate change mitigation and adaptation and applying local knowledge", but still ignored when women based on gender division of work entrusted role in domestic activities. Similarly, in public activity is an extension of the Domestic example, trading activity in the market lele / mama. Although men are also affected by climate change, but most feel is female. From the above problems, it can be said that Indonesia's commitment has not been followed by optimal empowerment of women's role in addressing climate change, it is necessary to learn to know how the role of women in the face of climate change impacts that hit on her role as a woman, a housewife or head of the family and will be input in order to determine how women find a solution to tackle the problem of climate change. This study focuses on the efforts made by women cope with the impacts of climate change, efforts by the government, empowerment model used in Playing the impact of climate change. The container with the formulation of the title "The Role of Women in Climate Change Impact in Kupang district". Where the assessment in use types Research mix Methods combination of quantitative research and qualitative research. While the location of the research conducted in Kupang regency, East Nusa Tenggara, namely: District of East Kupang is a district granary in Kupang district. Subdistrict West Kupang, especially Tablolong Village is the center of seaweed cultivation in Kupang district.

Keywords: climate change, women, women's roles, gender, family

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Authors: Shahbaz G. Hassan

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Water quality models are very important to predict the changes in surface water quality for environmental management. The aim of this paper is to give an overview of the water qualities, and to provide directions for selecting models in specific situation. Water quality models include one kind of model based on a mechanistic approach, while other models simulate water quality without considering a mechanism. Mechanistic models can be widely applied and have capabilities for long-time simulation, with highly complexity. Therefore, more spaces are provided to explain the principle and application experience of mechanistic models. Mechanism models have certain assumptions on rivers, lakes and estuaries, which limits the application range of the model, this paper introduces the principles and applications of water quality model based on the above three scenarios. On the other hand, mechanistic models are more easily to compute, and with no limit to the geographical conditions, but they cannot be used with confidence to simulate long term changes. This paper divides the empirical models into two broad categories according to the difference of mathematical algorithm, models based on artificial intelligence and models based on statistical methods.

Keywords: empirical models, mathematical, statistical, water quality

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Authors: Igor A. Krichtafovitch

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The evolutionary processes are not linear. Long periods of quiet and slow development turn to rather rapid emergences of new species and even phyla. During Cambrian explosion, 22 new phyla were added to the previously existed 3 phyla. Contrary to the common credence the natural selection or a survival of the fittest cannot be accounted for the dominant evolution vector which is steady and accelerated advent of more complex and more intelligent living organisms. Neither Darwinism nor alternative concepts including panspermia and intelligent design propose a satisfactory solution for these phenomena. The proposed hypothesis offers a logical and plausible explanation of the evolutionary processes in general. It is based on two postulates: a) the Biosphere is a single living organism, all parts of which are interconnected, and b) the Biosphere acts as a giant biological supercomputer, storing and processing the information in digital and analog forms. Such supercomputer surpasses all human-made computers by many orders of magnitude. Living organisms are the product of intelligent creative action of the biosphere supercomputer. The biological evolution is driven by growing amount of information stored in the living organisms and increasing complexity of the biosphere as a single organism. Main evolutionary vector is not a survival of the fittest but an accelerated growth of the computational complexity of the living organisms. The following postulates may summarize the proposed hypothesis: biological evolution as a natural life origin and development is a reality. Evolution is a coordinated and controlled process. One of evolution’s main development vectors is a growing computational complexity of the living organisms and the biosphere’s intelligence. The intelligent matter which conducts and controls global evolution is a gigantic bio-computer combining all living organisms on Earth. The information is acting like a software stored in and controlled by the biosphere. Random mutations trigger this software, as is stipulated by Darwinian Evolution Theories, and it is further stimulated by the growing demand for the Biosphere’s global memory storage and computational complexity. Greater memory volume requires a greater number and more intellectually advanced organisms for storing and handling it. More intricate organisms require the greater computational complexity of biosphere in order to keep control over the living world. This is an endless recursive endeavor with accelerated evolutionary dynamic. New species emerge when two conditions are met: a) crucial environmental changes occur and/or global memory storage volume comes to its limit and b) biosphere computational complexity reaches critical mass capable of producing more advanced creatures. The hypothesis presented here is a naturalistic concept of life creation and evolution. The hypothesis logically resolves many puzzling problems with the current state evolution theory such as speciation, as a result of GM purposeful design, evolution development vector, as a need for growing global intelligence, punctuated equilibrium, happening when two above conditions a) and b) are met, the Cambrian explosion, mass extinctions, happening when more intelligent species should replace outdated creatures.

Keywords: supercomputer, biological evolution, Darwinism, speciation

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Authors: Jukka Törrönen

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In the article, we examine the interplay between the practices of heavy drinking and exercise among young people as patterned around the ‘social’ and ‘physical health’ approaches. The comparison helps us to clarify why young people are currently drinking less than earlier and how the neoliberal healthism discourse, as well as the feminine tradition of taking care of one’s body, are modifying young people’s heavy drinking practices. The data is based on interviews (n = 56) in Sweden among 15-16-year-olds and 18˗19-year-olds. By drawing on Pierre Bourdieu’s concepts of habitus, field, and capital, we examine what kinds of resources of wellbeing young people accumulate in the fields of heavy drinking and exercise, how these resources carry symbolic value for distinction, and what kind of health-related habitus they imply. The analysis suggests that as heavy drinking is no longer able to stand as a practice through which one may acquire capital that is more valuable than the capital acquired in other fields, this lessens peer pressure to drink among young people. Our analysis further shows that the healthism discourse modifies young people’s heavy drinking practices both from inside and from outside. The interviewees translate the symbolic value of healthism discourse to social vulnerability and deploy it for the purposes of increasing one’s social status among peers. Moreover, our analysis demonstrates that the social spaces and positions in intoxication and exercise are shaped by gendered dualisms of masculine dominance. However, while the interviewees naturalize the gender binaries in intoxication as based on biological drives, they understand gender binaries in exercise as normative social constructions of neoliberal society. As these binaries emphasize the struggle for recognition of the symbolic value of bodily look, they may shift young men’s attention from risk-taking to issues that traditionally have been female concerns.

Keywords: young people, decline in drinking , health, intoxication, exercise, Bourdieu

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Authors: Jennifer Nutton, Gayle Ployer, Ky Scott, Jenny Morgan

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Working in a circle within higher education creates a decolonial space of mutual respect, responsibility, and reciprocity that facilitates collaborative learning and deep connections among learners and instructors. This approach is beyond simply facilitating a group in a circle but opens the door to creating a sacred space connecting each member to the land, to the Indigenous peoples who have taken care of the lands since time immemorial, to one another, and to one’s own positionality. These deep connections not only center human knowledges and relationships but also acknowledges responsibilities to land. Working in a circle as a relational pedagogical praxis also disrupts institutional power dynamics by creating a space of collaborative learning and deep connections in the classroom. Inherent within circle work is to facilitate connections not just academically but emotionally, physically, culturally, and spiritually. Recent literature supports the use of online talking circles, finding that it can offer a more relational and experiential learning environment, which is often absent in the virtual world and has been made more evident and necessary since the pandemic. These deeper experiences of learning and connection, rooted in both knowledge and the land, can then be shared with openness and vulnerability with one another, facilitating growth and change. This process of beginning with the land is critical to ensure we have the grounding to obstruct the ongoing realities of colonialism. The authors, who identify as both Indigenous and non-Indigenous, as both educators and learners, reflect on their teaching and learning experiences in circle. They share a relational pedagogical praxis framework that has been successful in educating future social workers, environmental activists, and leaders in social and human services, health, legal and political fields.

Keywords: circle work, relational pedagogies, decolonization, distance education

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Authors: Lauren A. Bailey, Amber R. Childs, Nicola C. James, Murray I. Duncan, Alexander Winkler, Warren M. Potts

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For the persistence of fished populations in the Anthropocene, it is critical to predict how fished populations will respond to the coupled threats of exploitation and climate change for adaptive management. The resilience of fished populations will depend on their capacity for physiological plasticity and acclimatization in response to environmental shifts. However, there is evidence for the selection of physiological traits by capture fisheries. Hence, fish populations may have a limited scope for the rapid expansion of their tolerance ranges or physiological adaptation under fishing pressures. To determine the physiological vulnerability of fished populations in the Anthropocene, the metabolic performance was compared between a fished and spatially protected Chrysoblephus laticeps population in response to thermal variability. Individual aerobic scope phenotypes were quantified using intermittent flow respirometry by comparing changes in energy expenditure of each individual at ecologically relevant temperatures, mimicking variability experienced as a result of upwelling and downwelling events. The proportion of high and low-performance individuals were compared between the fished and spatially protected population. The fished population had limited aerobic scope phenotype diversity and fewer high-performance phenotypes, resulting in a significantly lower aerobic scope curve across low (10 °C) and high (24 °C) thermal treatments. The performance of fished populations may be compromised with predicted future increases in cold upwelling events. This requires the conservation of the physiologically fittest individuals in spatially protected areas, which can recruit into nearby fished areas, as a climate resilience tool.

Keywords: climate change, fish physiology, metabolic shifts, over-fishing, respirometry

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Authors: Mina Fawzy Ishak Gad Elsaid

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There is a strong link between technology and development. Architecture as a profession is a call to service and society. Maybe next to soldiers, engineers and patriots. However, unlike soldiers, they always remain employees of society under all circumstances. Despite the construction profession's role in society, there appears to be a lack of respect as some projects fail. This paper focuses on the need to improve development engineering performance in developing countries, using engineering education in Nigerian universities as a tool for discussion. A purposeful survey, interviews and focus group discussions were conducted on one hundred and twenty (120) prominent companies in Nigeria. The subject is approached through a large number of projects that companies have been involved in from the planning stage, some of which have been completed and even reached the maintenance and monitoring stage. It has been found that certain factors beyond the control of engineers are hindering the full development and success of the construction sector in developing countries. The main culprit is corruption and its eradication will put the country on a stable path to develop construction and combat poverty.

Keywords: decision analysis, industrial engineering, direct vs. indirect values, engineering management

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Authors: Haneen Joseph Habib Yeldoka

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There is a strong link between technology and development. Architecture as a profession is a call to service and society. Maybe next to soldiers, engineers and patriots. However, unlike soldiers, they always remain employees of society under all circumstances. Despite the construction profession's role in society, there appears to be a lack of respect as some projects fail. This paper focuses on the need to improve development engineering performance in developing countries, using engineering education in Nigerian universities as a tool for discussion. A purposeful survey, interviews and focus group discussions were conducted on one hundred and twenty (120) prominent companies in Nigeria. The subject is approached through a large number of projects that companies have been involved in from the planning stage, some of which have been completed and even reached the maintenance and monitoring stage. It has been found that certain factors beyond the control of engineers are hindering the full development and success of the construction sector in developing countries. The main culprit is corruption and its eradication will put the country on a stable path to develop construction and combat poverty.

Keywords: decision analysis, industrial engineering, direct vs. indirect values, engineering management

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Authors: Ava Salmanpour, Hanieh Saeedi, Payam Rouhi, Elahe Hamzeil, Shima Alimohammadi, Siamak Hossein Khalaj, Mohammad Asadian

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Software-defined network (SDN) is a network architecture designed to control network using software application in a central manner. This ability enables remote control of the whole network regardless of the network technology. In fact, in this architecture network intelligence is separated from physical infrastructure, it means that required network components can be implemented virtually using software applications. Today, power networks are characterized by a high range of complexity with a large number of intelligent devices, processing both huge amounts of data and important information. Therefore, reliable and secure communication networks are required. SDNs are the best choice to meet this issue. In this paper, SDN networks capabilities and characteristics will be reviewed and different basic controllers will be compared. The importance of using SDNs to escalate efficiency and reliability in utility power networks is going to be discussed and the comparison between the SDN-based power networks and traditional networks will be explained.

Keywords: software-defined network, SDNs, utility network, open flow, communication, gas and electricity, controller

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Authors: Lin Wenli, Fu Linchun, Zhang Yi, Wu Ming

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To meet the demands of long-life and high-intelligence for satellites, the electrical power system should be provided with self-health condition evaluation capability. Any over-stress events in operations should be recorded. Based on Linear stresses accumulation damage theory, accumulative damage analysis was performed on thermal-mechanical-electrical united stresses for three components including the solar array, the batteries and the power conditioning unit. Then an overall health percentage evaluation model for satellite electrical power system was built. To obtain the accurate quantity for system health percentage, an automatic feedback closed-loop correction method for all coefficients in the evaluation model was present. The evaluation outputs could be referred as taking earlier fault-forecast and interventions for Ground Control Center or Satellites self.

Keywords: satellite electrical power system, health percentage, linear stresses accumulation damage, evaluation model

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Authors: Sagir M. Yusuf, Chris Baber

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We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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Authors: Yosra Mefteh Rekik

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A computational agent-based model of financial markets stresses interactions and dynamics among a very diverse set of traders. The growing body of research in this area relies heavily on computational tools which by-pass the restrictions of an analytical method. The main goal of this research is to understand how the stock market operates and behaves how to invest in the stock market and to study traders’ behavior within the context of the artificial stock markets populated by heterogeneous agents. All agents are characterized by adaptive learning behavior represented by the Artificial Neuron Networks. By using agent-based simulations on artificial market, we show that the existence of heterogeneous agents can explain the price dynamics in the financial market. We investigate the relation between market diversity and market efficiency. Our empirical findings demonstrate that greater market heterogeneity play key roles in market efficiency.

Keywords: agent-based modeling, artificial stock market, heterogeneous expectations, financial stylized facts, computational finance

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Authors: Shidratul Moontaha Suha

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Violence is organized and utilized differently in various communities across the globe. The capacity to employ violence in numerous societies is largely limited to the apparatus of the state, like law enforcement officers, and in a small share of contexts, it is controlled within the state institutions as per the rule of law. Contrastingly, in many other societies, a broad array of players, mainly organized criminal gangs, are using violence on a substantial scale to agitate against social ills or attain personal interests. The present paper examined the role of social injustice in driving children living off and on the streets of Dhaka, Bangladesh, into joining organized criminal gangs and committing crimes. The study entailed a comprehensive review of existing literature with theoretical analyses based on three theories: the Marxist’s theory of capitalism and class struggle, the Weberian model of social stratification theory, and the social disorganization theory. The analysis revealed that, in Dhaka, Bangladesh, criminal gangs emerged from social disorganization of communities characterized by absolute poverty, residential mobility, and population heterogeneity, which promote deviance among the youth, and subsequently, led to the rise of organized gangs and delinquency. Although the latter was formed as a response to class struggle, they have been employed by the state and police as the tools of exploitation and oppression to rule the working class. The criminal gangs exploit the vulnerability of street children by using them as sources of cheap labor to peddle drugs, extort, or kill specific individuals who are against their ideals. In retrospect, the street children receive individual, group, and social protection. Therefore, social class struggle plays a central role in the proliferation of organized criminal gangs and the engagement of street children in criminal activities in Dhaka, Bangladesh.

Keywords: cheap labor, organized crimes, poverty, social stratification, social children

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Authors: Diego De Castro Rodrigues, Marcelo Lisboa Rocha, Daniela M. De Q. Trevisan, Marcos Dias Da Conceicao, Gabriel Rosa, Rommel M. Barbosa

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The use of association rules algorithms within data mining is recognized as being of great value in the knowledge discovery in databases. Very often, the number of rules generated is high, sometimes even in databases with small volume, so the success in the analysis of results can be hampered by this quantity. The purpose of this research is to present a method for reducing the quantity of rules generated with association algorithms. Therefore, a computational algorithm was developed with the use of a Weka Application Programming Interface, which allows the execution of the method on different types of databases. After the development, tests were carried out on three types of databases: synthetic, model, and real. Efficient results were obtained in reducing the number of rules, where the worst case presented a gain of more than 50%, considering the concepts of support, confidence, and lift as measures. This study concluded that the proposed model is feasible and quite interesting, contributing to the analysis of the results of association rules generated from the use of algorithms.

Keywords: data mining, association rules, rules reduction, artificial intelligence

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Authors: F. Allag, S. Bouharati, M. Belmahdi, R. Zegadi

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The rapid expansion of deserts in recent decades as a result of human actions combined with climatic changes has highlighted the necessity to understand biological processes in arid environments. Whereas physical processes and the biology of flora and fauna have been relatively well studied in marginally used arid areas, knowledge of desert soil micro-organisms remains fragmentary. The objective of this study is to conduct a diversity analysis of bacterial communities in unvegetated arid soils. Several biological phenomena in hot deserts related to microbial populations and the potential use of micro-organisms for restoring hot desert environments. Dry land ecosystems have a highly heterogeneous distribution of resources, with greater nutrient concentrations and microbial densities occurring in vegetated than in bare soils. In this work, we found it useful to use techniques of artificial intelligence in their treatment especially artificial neural networks (ANN). The use of the ANN model, demonstrate his capability for addressing the complex problems of uncertainty data.

Keywords: desert soil, climatic changes, bacteria, vegetation, artificial neural networks

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Authors: Samuel Kehinde Okunade, Daniel Sunday Tolorunshagba

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Globally women are classified to be part of the vulnerable group in any environment. In a conflict-ridden environment, women being vulnerable often suffer the consequences as it relates to security and access to basic social services such as medical care. This is the situation in border communities in Nigeria where cross-border crimes are on the rife, thus, putting women at a disadvantaged position and, eventually, victims of such inimical activities. Border communities in the Saki/Iseyin area of Oyo state are a case in point where the lives of inhabitants are daily threatened most, especially women. In light of the above, this article examined the security situation of the Saki/Iseyin area of Oyo State with a view to ascertaining its status in terms of safety of lives and property. This paper also explored the experiences of women in the border communities within the area as it relates to their safety, the safety of their children, access to good health facilities in their immediate environment, and above all, how they have been able to cope or manage the situation. The qualitative research model was adopted utilizing a phenomenological case study approach. A Focused Group Discussion was conducted with 10 pregnant women and 10 mothers in Okerete and Abugudu communities while a Key Informant Interview was conducted with the women leaders in both communities of the Saki/Iseyin border area of Oyo State. The findings of the study revealed the poor state of basic infrastructure. So bad to a point that inhabitants of these communities no longer see themselves as Nigerians because they have been neglected by the government for too long. The only solution is for the government to embark on developmental projects within these communities so that they can live a good life just as those in the cities do. More importantly, this will increase the loyalty of these communities to the Nigeria state by defending and resisting all forms of cross-border criminal activities that go on along the porous borders.

Keywords: security, women, Saki/Iseyin border area, cross-border criminalities, basic infrastructure

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Authors: Zakir Husain

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Main objective of a power transformer design optimization problem requires minimizing the total overall cost and/or mass of the winding and core material by satisfying all possible constraints obligatory by the standards and transformer user requirement. The constraints include appropriate limits on winding fill factor, temperature rise, efficiency, no-load current and voltage regulation. The design optimizations tasks are a constrained minimum cost and/or mass solution by optimally setting the parameters, geometry and require magnetic properties of the transformer. In this paper, present the above design problems have been formulated by using genetic algorithm (GA) and simulated annealing (SA) on the MATLAB platform. The importance of the presented approach is stems for two main features. First, proposed technique provides reliable and efficient solution for the problem of design optimization with several variables. Second, it guaranteed to obtained solution is global optimum. This paper includes a demonstration of the application of the genetic programming GP technique to transformer design.

Keywords: optimization, power transformer, genetic algorithm (GA), simulated annealing technique (SA)

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Authors: Eliana Bergamin

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This philosophical inquiry, influenced by the seminal works of Annemarie Mol and Jeannette Pols, critically examines the transformative impact of artificial intelligence (AI) on emotional caregiving practices within virtual healthcare. Rooted in the traditions of philosophy of care, philosophy of emotions, and applied philosophy, this study seeks to unravel nuanced shifts in the moral and emotional fabric of healthcare mediated by AI-powered technologies. Departing from traditional empirical studies, the approach embraces the foundational principles of care ethics and phenomenology, offering a focused exploration of the ethical and existential dimensions of AI-mediated emotional caregiving. At its core, this research addresses the introduction of AI-powered technologies mediating emotional and care practices in the healthcare sector. By drawing on Mol and Pols' insights, the study offers a focused exploration of the ethical and existential dimensions of AI-mediated emotional caregiving. Anchored in ethnographic research within a pioneering private healthcare company in the Netherlands, this critical philosophical inquiry provides a unique lens into the dynamics of AI-mediated emotional practices. The study employs in-depth, semi-structured interviews with virtual caregivers and care receivers alongside ongoing ethnographic observations spanning approximately two and a half months. Delving into the lived experiences of those at the forefront of this technological evolution, the research aims to unravel subtle shifts in the emotional and moral landscape of healthcare, critically examining the implications of AI in reshaping the philosophy of care and human connection in virtual healthcare. Inspired by Mol and Pols' relational approach, the study prioritizes the lived experiences of individuals within the virtual healthcare landscape, offering a deeper understanding of the intertwining of technology, emotions, and the philosophy of care. In the realm of philosophy of care, the research elucidates how virtual tools, particularly those driven by AI, mediate emotions such as empathy, sympathy, and compassion—the bedrock of caregiving. Focusing on emotional nuances, the study contributes to the broader discourse on the ethics of care in the context of technological mediation. In the philosophy of emotions, the investigation examines how the introduction of AI alters the phenomenology of emotional experiences in caregiving. Exploring the interplay between human emotions and machine-mediated interactions, the nuanced analysis discerns implications for both caregivers and caretakers, contributing to the evolving understanding of emotional practices in a technologically mediated healthcare environment. Within applied philosophy, the study transcends empirical observations, positioning itself as a reflective exploration of the moral implications of AI in healthcare. The findings are intended to inform ethical considerations and policy formulations, bridging the gap between technological advancements and the enduring values of caregiving. In conclusion, this focused philosophical inquiry aims to provide a foundational understanding of the evolving landscape of virtual healthcare, drawing on the works of Mol and Pols to illuminate the essence of human connection, care, and empathy amid technological advancements.

Keywords: applied philosophy, artificial intelligence, healthcare, philosophy of care, philosophy of emotions

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Authors: Aby Nesan Raj, Sumil K. Raj, Sumesh Jayan

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The objective of the study is to formulate a self-regulation model that shall enhance the usage of Intelligent Transportation Systems by understanding the theory of self-efficacy. The core logic of the self-regulation model shall monitor driver's behavior based on the situations related to the various sources of Self Efficacy like enactive mastery, vicarious experience, verbal persuasion and physiological arousal in addition to the vehicle data. For this study, four different vehicle data, speed, drowsiness, diagnostic data and surround camera views are considered. This data shall be given to the self-regulation model for evaluation. The oddness, which is the output of self-regulation model, shall feed to Intelligent Transportation Systems where appropriate actions are being taken. These actions include warning to the user as well as the input to the related transportation systems. It is also observed that the usage of vehicle as a sensor reduces the wastage of resource utilization or duplication. Altogether, this approach enhances the intelligence of the transportation systems especially in safety, productivity and environmental performance.

Keywords: emergency management, intelligent transportation system, self-efficacy, traffic management

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Authors: Nermin Noshi Esraeil Abdalla

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Inclusive schooling offerings for college kids with Autism stays in its early developmental levels in Thailand. despite many greater youngsters with autism are attending schools since the Thai authorities brought the training Provision for human beings with Disabilities Act in 2008, the services students with autism and their families obtain are typically missing. This quantitative examine used attitude and Preparedness to educate college students with Autism Scale (APTSAS) to investigate 110 number one faculty teachers’ attitude and preparedness to educate college students with autism inside the widespread training school room. Descriptive statistical evaluation of the records discovered that scholar behavior changed into the most good sized factor in constructing teachers’ terrible attitudes students with autism. the majority of teachers additionally indicated that their pre-service schooling did not put together them to fulfill the mastering needs of children with autism especially, folks who are non-verbal. The take a look at is substantial and offers path for enhancing trainer education for inclusivity in Thailand.

Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills

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Authors: Zewdneh Zana Zate

Abstract:

The study focuses on the evolutionary and ecological genomics of both wild and cultivated Coffea arabica L. at its center of origin, Ethiopia, aiming to uncover how this vital species may withstand future climate changes. Utilizing bioclimatic models, we project the future distribution of Arabica under varied climate scenarios for 2050 and 2080, identifying potential conservation zones and immediate risk areas. Through whole-genome resequencing of accessions from Ethiopian gene banks, this research assesses genetic diversity and divergence between wild and cultivated populations. It explores relationships, demographic histories, and potential hybridization events among Coffea arabica accessions to better understand the species' origins and its connection to parental species. This genomic analysis also seeks to detect signs of natural or artificial selection across populations. Integrating these genomic discoveries with ecological data, the study evaluates the current and future ecological and genomic vulnerabilities of wild Coffea arabica, emphasizing necessary adaptations for survival. We have identified key genomic regions linked to environmental stress tolerance, which could be crucial for breeding more resilient Arabica varieties. Additionally, our ecological modeling predicted a contraction of suitable habitats, urging immediate conservation actions in identified key areas. This research not only elucidates the evolutionary history and adaptive strategies of Arabica but also informs conservation priorities and breeding strategies to enhance resilience to climate change. By synthesizing genomic and ecological insights, we provide a robust framework for developing effective management strategies aimed at sustaining Coffea arabica, a species of profound global importance, in its native habitat under evolving climatic conditions.

Keywords: coffea arabica, climate change adaptation, conservation strategies, genomic resilience

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Authors: Nael Y. Zabel, Maged E. Georgy, Moheeb E. Ibrahim

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A knowledge-based expert system with the acronym RASPE is developed as an application tool to help decision makers in construction companies make informed decisions about managing risks in pipeline construction projects. Choosing to use expert systems from all available artificial intelligence techniques is due to the fact that an expert system is more suited to representing a domain’s knowledge and the reasoning behind domain-specific decisions. The knowledge-based expert system can capture the knowledge in the form of conditional rules which represent various project scenarios and potential risk mitigation/response actions. The built knowledge in RASPE is utilized through the underlying inference engine that allows the firing of rules relevant to a project scenario into consideration. This paper provides an overview of the knowledge acquisition process and goes about describing the knowledge structure which is divided up into four major modules. The paper shows one module in full detail for illustration purposes and concludes with insightful remarks.

Keywords: expert system, knowledge management, pipeline projects, risk mismanagement

Procedia PDF Downloads 309

Authors: D.Mendes, J. Henriques, P. Carvalho, T. Rocha, S. Paredes, R. Cabiddu, R. Trimer, R. Mendes, A. Borghi-Silva, L. Kaminsky, E. Ashley, R. Arena, J. Myers

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The continued exploration of clinically relevant predictive models continues to be an important pursuit. Cardiorespiratory fitness (CRF) portends clinical vital information and as such its accurate prediction is of high importance. Therefore, the aim of the current study was to develop a data-driven model, based on computational intelligence techniques and, in particular, clustering approaches, to predict CRF. Two prediction models were implemented and compared: 1) the traditional Wasserman/Hansen Equations; and 2) an interpretable clustering approach. Data used for this analysis were from the 'FRIEND - Fitness Registry and the Importance of Exercise: The National Data Base'; in the present study a subset of 10690 apparently healthy individuals were utilized. The accuracy of the models was performed through the computation of sensitivity, specificity, and geometric mean values. The results show the superiority of the clustering approach in the accurate estimation of CRF (i.e., maximal oxygen consumption).

Keywords: cardiorespiratory fitness, data-driven models, knowledge extraction, machine learning

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Authors: Gbone Akou Sophie

Abstract:

Lome state in Togo is considered to have the highest HIV prevalence in Togo according to NAIIS 2023, with the prevalence of 5.5%, Female Sex Workers (FSW) are one of the most vulnerable population, and they are vital in HIV programming. They have the highest HIV prevalence compared to others such as HRM, PWID and Transgender in lome State, Togo. Evidence from Integrated Biological Behavioral Surveillance Survey shows increasing burden of HIV infection from 13.7% in 20018 to 17.2% in 2020 and now 22.9% in 2021 among Female Sex Workers (FSW). This shows their HIV prevalence has been rising over time. The vulnerability status of the FSW in the riverine areas of lome is heightened because of cultural and economic issues where there is exchange of sex for commodities with cross border traders as well as limited access to HIV prevention information. Methods:A cross sectional study which recruited 120 FSW from two Riverine LGAs of Agoe and Kpehenou LGA of Lome State using both snowballing and simple random sampling technique. While semi-structured questionnaire was used as an instrument for data collection among the 120 FSW respondents. Additional information was also elicited from 10 FSW key opinion leaders and community members through in-depth interviews (IDI). Results: 44(36%) of respondents were willing to receive regular HIV care and services as well as visit for STI check-ups at any service point. However, 47(40%) were willing to receive services at private facilities alone, 10 (8%) were willing to receive services at public facilities, 6 (5%) were willing to access services in their homes rather than in the health facility. 13 (11%) were also willing to have peers assist in getting HIV testing services. Conclusion: integrated differentiated model of care for HIV services helps improve HIV services uptake among FSW community especially in the hard- to reach riverine areas which will further lead to epidemic control. Also targeted HIV information should be designed to suit the learning needs of the hard-to reach communities like the riverine areas. More peer educators should be engaged to ensure information and other HIV services reach the riverine communities.

Keywords: female sex workers ( FSW), human immuno-deficiency virus(HIV), prevanlence, service delivery

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Authors: Akhil Dubey, Rajnesh Singh

Abstract:

In modern days there occur many rapid modifications in field of ad hoc network. These modifications create many revolutionary changes in the routing. Predictive energy efficient routing is inspired on the bee’s behavior of swarm intelligence. Predictive routing improves the efficiency of routing in the energetic point of view. The main aim of this routing is the minimum energy consumption during communication and maximized intermediate node’s remaining battery power. This routing is based on food searching behavior of bees. There are two types of bees for the exploration phase the scout bees and for the evolution phase forager bees use by this routing. This routing algorithm computes the energy consumption, fitness ratio and goodness of the path. In this paper we review the literature related with predictive routing, presenting modified routing and simulation result of this algorithm comparison with artificial bee colony based routing schemes in MANET and see the results of path fitness and probability of fitness.

Keywords: mobile ad hoc network, artificial bee colony, PEEBR, modified predictive routing

Procedia PDF Downloads 411