Search results for: paraconsistent annotated logic

Authors: Nurlan Smagulov, Aiman Konkabayeva, Akerke Sadykova, Arailym Serik

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Introduction. Adverse environmental factors do not immediately lead to pathological changes in the body. They can exert the growth of pre-pathology characterized by shifts in physiological, biochemical, immunological and other indicators of the body state. These disorders are unstable, reversible and indicative of body reactions. There is an opportunity to objectively judge the internal structure of the adaptive body reactions at the level of individual organs and systems. In order to obtain a stable response of the body to the chronic effects of unfavorable environmental factors of low intensity (compared to production environment factors), a time called the «lag time» is needed. The obtained results without considering this factor distort reality and, for the most part, cannot be a reliable statement of the main conclusions in any work. A technique is needed to reduce methodological errors and combine mathematical logic using statistical methods and a medical point of view, which ultimately will affect the obtained results and avoid a false correlation. Objective. Development of a methodology for assessing and predicting the environmental factors impact on the population health considering the «lag time.» Methods. Research objects: environmental and population morbidity indicators. The database on the environmental state was compiled from the monthly newsletters of Kazhydromet. Data on population morbidity were obtained from regional statistical yearbooks. When processing static data, a time interval (lag) was determined for each «argument-function» pair. That is the required interval, after which the harmful factor effect (argument) will fully manifest itself in the indicators of the organism's state (function). The lag value was determined by cross-correlation functions of arguments (environmental indicators) with functions (morbidity). Correlation coefficients (r) and their reliability (t), Fisher's criterion (F) and the influence share (R2) of the main factor (argument) per indicator (function) were calculated as a percentage. Results. The ecological situation of an industrially developed region has an impact on health indicators, but it has some nuances. Fundamentally opposite results were obtained in the mathematical data processing, considering the «lag time». Namely, an expressed correlation was revealed after two databases (ecology-morbidity) shifted. For example, the lag period was 4 years for dust concentration, general morbidity, and 3 years – for childhood morbidity. These periods accounted for the maximum values of the correlation coefficients and the largest percentage of the influencing factor. Similar results were observed in relation to the concentration of soot, dioxide, etc. The comprehensive statistical processing using multiple correlation-regression variance analysis confirms the correctness of the above statement. This method provided the integrated approach to predicting the degree of pollution of the main environmental components to identify the most dangerous combinations of concentrations of leading negative environmental factors. Conclusion. The method of assessing the «environment-public health» system (considering the «lag time») is qualitatively different from the traditional (without considering the «lag time»). The results significantly differ and are more amenable to a logical explanation of the obtained dependencies. The method allows presenting the quantitative and qualitative dependence in a different way within the «environment-public health» system.

Keywords: ecology, morbidity, population, lag time

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Authors: Pablo Chico De Guzman, Cesar Sanchez

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Microservice architectures are increasingly in distributed cloud applications due to the advantages on the software composition, development speed, release cycle frequency and the business logic time to market. On the other hand, these architectures also introduce some challenges on the testing and release phases of applications. Container technology solves some of these issues by providing reproducible environments, easy of software distribution and isolation of processes. However, there are other issues that remain unsolved in current container technology when dealing with multiple machines, such as networking for multi-host communication, service discovery, load balancing or data persistency (even though some of these challenges are already solved by traditional cloud vendors in a very mature and widespread manner). Container cluster management tools, such as Kubernetes, Mesos or Docker Swarm, attempt to solve these problems by introducing a new control layer where the unit of deployment is the container (or the pod — a set of strongly related containers that must be deployed on the same machine). These tools are complex to configure and manage and they do not follow a pure immutable infrastructure approach since servers are reused between deployments. Indeed, these tools introduce dependencies at execution time for solving networking or service discovery problems. If an error on the control layer occurs, which would affect running applications, specific expertise is required to perform ad-hoc troubleshooting. As a consequence, it is not surprising that container cluster support is becoming a source of revenue for consulting services. This paper presents i2kit, a deployment tool based on the immutable infrastructure pattern, where the virtual machine is the unit of deployment. The input for i2kit is a declarative definition of a set of microservices, where each microservice is defined as a pod of containers. Microservices are built into machine images using linuxkit —- a tool for creating minimal linux distributions specialized in running containers. These machine images are then deployed to one or more virtual machines, which are exposed through a cloud vendor load balancer. Finally, the load balancer endpoint is set into other microservices using an environment variable, providing service discovery. The toolkit i2kit reuses the best ideas from container technology to solve problems like reproducible environments, process isolation, and software distribution, and at the same time relies on mature, proven cloud vendor technology for networking, load balancing and persistency. The result is a more robust system with no learning curve for troubleshooting running applications. We have implemented an open source prototype that transforms i2kit definitions into AWS cloud formation templates, where each microservice AMI (Amazon Machine Image) is created on the fly using linuxkit. Even though container cluster management tools have more flexibility for resource allocation optimization, we defend that adding a new control layer implies more important disadvantages. Resource allocation is greatly improved by using linuxkit, which introduces a very small footprint (around 35MB). Also, the system is more secure since linuxkit installs the minimum set of dependencies to run containers. The toolkit i2kit is currently under development at the IMDEA Software Institute.

Keywords: container, deployment, immutable infrastructure, microservice

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Authors: Farzaneh Sasanpour, Saeed Amini Varaki

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Resilience is an important goal for cities as urban areas face an increasing range of challenges in the 21st century; therefore, according to the characteristics of risks, adopting an approach that responds to sensitive conditions in the risk management process is the resilience of cities. In the meantime, most of the resilience assessments have dealt with natural hazards and less attention has been paid to pandemics.In the covid-19 pandemic, the country of Iran and especially the metropolis of Tehran, was not immune from the crisis caused by its effects and consequences and faced many challenges. One of the methods that can increase the resilience of Tehran's metropolis against possible crises in the future is future studies. This research is practical in terms of type. The general pattern of the research will be descriptive-analytical and from the point of view that it is trying to communicate between the components and provide urban resilience indicators with pandemic crises and explain the scenarios, its future studies method is exploratory. In order to extract and determine the key factors and driving forces effective on the resilience of Tehran's urban areas against pandemic crises (Covid-19), the method of structural analysis of mutual effects and Micmac software was used. Therefore, the primary factors and variables affecting the resilience of Tehran's urban areas were set in 5 main factors, including physical-infrastructural (transportation, spatial and physical organization, streets and roads, multi-purpose development) with 39 variables based on mutual effects analysis. Finally, key factors and variables in five main areas, including managerial-institutional with five variables; Technology (intelligence) with 3 variables; economic with 2 variables; socio-cultural with 3 variables; and physical infrastructure, were categorized with 7 variables. These factors and variables have been used as key factors and effective driving forces on the resilience of Tehran's urban areas against pandemic crises (Covid-19), in explaining and developing scenarios. In order to develop the scenarios for the resilience of Tehran's urban areas against pandemic crises (Covid-19), intuitive logic, scenario planning as one of the future research methods and the Global Business Network (GBN) model were used. Finally, four scenarios have been drawn and selected with a creative method using the metaphor of weather conditions, which is indicative of the general outline of the conditions of the metropolis of Tehran in that situation. Therefore, the scenarios of Tehran metropolis were obtained in the form of four scenarios: 1- solar scenario (optimal governance and management leading in smart technology) 2- cloud scenario (optimal governance and management following in intelligent technology) 3- dark scenario (optimal governance and management Unfavorable leader in intelligence technology) 4- Storm scenario (unfavorable governance and management of follower in intelligence technology). The solar scenario shows the best situation and the stormy scenario shows the worst situation for the Tehran metropolis. According to the findings obtained in this research, city managers can, in order to achieve a better tomorrow for the metropolis of Tehran, in all the factors and components of urban resilience against pandemic crises by using future research methods, a coherent picture with the long-term horizon of 2050, from the path Provide urban resilience movement and platforms for upgrading and increasing the capacity to deal with the crisis. To create the necessary platforms for the realization, development and evolution of the urban areas of Tehran in a way that guarantees long-term balance and stability in all dimensions and levels.

Keywords: future research, resilience, crisis, pandemic, covid-19, Tehran

Procedia PDF Downloads 42

Authors: Salvatore Luongo, Carlo Luongo

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This paper discusses the implementation solutions to reduce the computational load for the Traffic Situational Awareness with Alerts (TSAA) application, based on Automatic Dependent Surveillance-Broadcast (ADS-B) technology. In 2008, there were 23 total mid-air collisions involving general aviation fixed-wing aircraft, 6 of which were fatal leading to 21 fatalities. These collisions occurred during visual meteorological conditions, indicating the limitations of the see-and-avoid concept for mid-air collision avoidance as defined in the Federal Aviation Administration’s (FAA). The commercial aviation aircraft are already equipped with collision avoidance system called TCAS, which is based on classic transponder technology. This system dramatically reduced the number of mid-air collisions involving air transport aircraft. In general aviation, the same reduction in mid-air collisions has not occurred, so this reduction is the main objective of the TSAA application. The major difference between the original conflict detection application and the TSAA application is that the conflict detection is focused on preventing loss of separation in en-route environments. Instead TSAA is devoted to reducing the probability of mid-air collision in all phases of flight. The TSAA application increases the flight crew traffic situation awareness providing alerts of traffic that are detected in conflict with ownship in support of the see-and-avoid responsibility. The relevant effort has been spent in the design process and the code generation in order to maximize the efficiency and performances in terms of computational load and memory consumption reduction. The TSAA architecture is divided into two high-level systems: the “Threats database” and the “Conflict detector”. The first one receives the traffic data from ADS-B device and provides the memorization of the target’s data history. Conflict detector module estimates ownship and targets trajectories in order to perform the detection of possible future loss of separation between ownship and each target. Finally, the alerts are verified by additional conflict verification logic, in order to prevent possible undesirable behaviors of the alert flag. In order to reduce the computational load, a pre-check evaluation module is used. This pre-check is only a computational optimization, so the performances of the conflict detector system are not modified in terms of number of alerts detected. The pre-check module uses analytical trajectories propagation for both target and ownship. This allows major accuracy and avoids the step-by-step propagation, which requests major computational load. Furthermore, the pre-check permits to exclude the target that is certainly not a threat, using an analytical and efficient geometrical approach, in order to decrease the computational load for the following modules. This software improvement is not suggested by FAA documents, and so it is the main innovation of this work. The efficiency and efficacy of this enhancement are verified using fast-time and real-time simulations and by the execution on a real device in several FAA scenarios. The final implementation also permits the FAA software certification in compliance with DO-178B standard. The computational load reduction allows the installation of TSAA application also on devices with multiple applications and/or low capacity in terms of available memory and computational capabilities

Keywords: traffic situation awareness, general aviation, aircraft conflict detection, computational load reduction, implementation solutions, software certification

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Authors: Mohammadreza Kashizadeh, Mohammadamin Hashemi

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Solymorph, a kinetic building facade designed for optimal energy capture and architectural expression, is explored in this paper. The system integrates photovoltaic panels with soft robotic actuators for precise solar tracking, resulting in enhanced electricity generation compared to static facades. Driven by the growing interest in dynamic building envelopes, the exploration of novel facade systems is necessitated. Increased energy generation and regulation of energy flow within buildings are potential benefits offered by integrating photovoltaic (PV) panels as kinetic elements. However, incorporating these technologies into mainstream architecture presents challenges due to the complexity of coordinating multiple systems. To address this, Solymorph leverages soft robotic actuators, known for their compliance, resilience, and ease of integration. Additionally, the project investigates the potential for employing Large Language Models (LLMs) to streamline the design process. The research methodology involved design development, material selection, component fabrication, and system assembly. Grasshopper (GH) was employed within the digital design environment for parametric modeling and scripting logic, and an LLM was experimented with to generate Python code for the creation of a random surface with user-defined parameters. Various techniques, including casting, 3D printing, and laser cutting, were utilized to fabricate the physical components. Finally, a modular assembly approach was adopted to facilitate installation and maintenance. A case study focusing on the application of Solymorph to an existing library building at Politecnico di Milano is presented. The facade system is divided into sub-frames to optimize solar exposure while maintaining a visually appealing aesthetic. Preliminary structural analyses were conducted using Karamba3D to assess deflection behavior and axial loads within the cable net structure. Additionally, Finite Element (FE) simulations were performed in Abaqus to evaluate the mechanical response of the soft robotic actuators under pneumatic pressure. To validate the design, a physical prototype was created using a mold adapted for a 3D printer's limitations. Casting Silicone Rubber Sil 15 was used for its flexibility and durability. The 3D-printed mold components were assembled, filled with the silicone mixture, and cured. After demolding, nodes and cables were 3D-printed and connected to form the structure, demonstrating the feasibility of the design. Solymorph demonstrates the potential of soft robotics and Artificial Intelligence (AI) for advancements in sustainable building design and construction. The project successfully integrates these technologies to create a dynamic facade system that optimizes energy generation and architectural expression. While limitations exist, Solymorph paves the way for future advancements in energy-efficient facade design. Continued research efforts will focus on cost reduction, improved system performance, and broader applicability.

Keywords: artificial intelligence, energy efficiency, kinetic photovoltaics, pneumatic control, soft robotics, sustainable building

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Authors: Wafaa Hasan

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In May of 2022, Palestinian parents in Toronto, Canada, became aware that educators and staff in the Toronto District School Board were attempting to include the International Holocaust and Remembrance Definition of Antisemitism (IHRA) in The Child Abuse and Neglect Policy of the largest school board in Canada, The Toronto District School Board (TDSB). The idea was that if students were to express any form of antisemitism, as defined by the IHRA, then an investigation could follow with Child Protective Services (CPS). That is, the student’s parents could be reported to the state and investigated for custodial rights to their children. The TDSB has set apparent goals for “Decolonizing Pedagogy” (“TDSB Equity Leadership Competencies”), Culturally Responsive and Relevant Practices (CRRP) and inclusive education. These goals promote the centering of colonized, racialized and marginalized voices. CRRP cannot be effective without the application of anti-racist and settler colonial analyses. In order for CRRP to be effective, school boards need a comprehensive understanding of the ways in which the vilification of Palestinians operates through anti-indigenous and white supremacist systems and logic. Otherwise, their inclusion will always be in tension with the inclusion of settler colonial agendas and worldviews. Feminist maternalism frames racial mothering as degenerate (viewing the contributions of racialized students and their parents as products of primitive and violent cultures) and also indirectly inhibits the actualization of the tenets of CRRP and inclusive education through its extensions into the welfare state and public education. The contradiction between the tenets of CRRP and settler colonial systems of erasure and repression is resolved by the continuation of tactics to 1) force assimilation, 2) punish those who push back on that assimilation and 3) literally fragment familial and community structures of racialized students, educators and parents. This paper draws on interdisciplinary (history, philosophy, anthropology) critiques of white feminist “maternalism” from the 19th century onwards in North America and Europe (Jacobs, Weber), as well as “anti-racist education” theory (Dei), and more specifically,” culturally responsive learning,” (Muhammad) and “bandwidth” pedagogy theory (Verschelden) to make its claims. This research contributes to vibrant debates about anti-racist and decolonial pedagogies in public education systems globally. This paper also documents first-hand interviews and experiences of diasporic Palestinian mothers and motherhoods and situates their experiences within longstanding histories of white feminist maternalist (and eugenicist) politics. This informal qualitative data from "participatory conversations" (Swain) is situated within a set of formal interview data collected with Palestinian women in the West Bank (approved by the McMaster University Humanities Research Ethics Board) relating to white feminist maternalism in the peace and dialogue industry.

Keywords: decolonial feminism, maternal feminism, anti-racist pedagogies, settler colonial studies, motherhood studies, pedagogy theory, cultural theory

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Authors: Agboka Komi Mensah, John Odindi, Elfatih M. Abdel-Rahman, Onisimo Mutanga, Henri Ez Tonnang

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Ecosystems are networks of organisms and populations that form a community of various species interacting within their habitats. Such habitats are defined by abiotic and biotic conditions that establish the initial limits to a population's growth, development, and reproduction. The habitat’s conditions explain the context in which species interact to access resources such as food, water, space, shelter, and mates, allowing for feeding, dispersal, and reproduction. Dispersal is an essential life-history strategy that affects gene flow, resource competition, population dynamics, and species distributions. Despite the importance of dispersal in population dynamics and survival, understanding the mechanism underpinning the dispersal of organisms remains challenging. For instance, when an organism moves into an ecosystem for survival and resource competition, its progression is highly influenced by extrinsic factors such as its physiological state, climatic variables and ability to evade predation. Therefore, greater spatial detail is necessary to understand organism dispersal dynamics. Understanding organisms dispersal can be addressed using empirical and mechanistic modelling approaches, with the adopted approach depending on the study's purpose Cellular automata (CA) is an example of these approaches that have been successfully used in biological studies to analyze the dispersal of living organisms. Cellular automata can be briefly described as occupied cells by an individual that evolves based on proper decisions based on a set of neighbours' rules. However, in the ambit of modelling individual organisms dispersal at the landscape scale, we lack user friendly tools that do not require expertise in mathematical models and computing ability; such as a visual analytics framework for tracking and forecasting the dispersal behaviour of organisms. The term "visual analytics" (VA) describes a semiautomated approach to electronic data processing that is guided by users who can interact with data via an interface. Essentially, VA converts large amounts of quantitative or qualitative data into graphical formats that can be customized based on the operator's needs. Additionally, this approach can be used to enhance the ability of users from various backgrounds to understand data, communicate results, and disseminate information across a wide range of disciplines. To support effective analysis of the dispersal of organisms at the landscape scale, we therefore designed Pydisp which is a free visual data analytics tool for spatiotemporal dispersal modeling built in Python. Its user interface allows users to perform a quick and interactive spatiotemporal analysis of species dispersal using bioecological and climatic data. Pydisp enables reuse and upgrade through the use of simple principles such as Fuzzy cellular automata algorithms. The potential of dispersal modeling is demonstrated in a case study by predicting the dispersal of Fopius arisanus (Sonan), endoparasitoids to control Bactrocera dorsalis (Hendel) (Diptera: Tephritidae) in Kenya. The results obtained from our example clearly illustrate the parasitoid's dispersal process at the landscape level and confirm that dynamic processes in an agroecosystem are better understood when designed using mechanistic modelling approaches. Furthermore, as demonstrated in the example, the built software is highly effective in portraying the dispersal of organisms despite the unavailability of detailed data on the species dispersal mechanisms.

Keywords: cellular automata, fuzzy logic, landscape, spatiotemporal

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Authors: Ali R. Alshawawreh, Francisco Liébana-Cabanillas, Francisco J. Blanco-Encomienda

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Collaboration between marketing and business intelligence (BI) is crucial in today's ever-evolving business landscape. These two domains play pivotal roles in molding customers' experiential knowledge. Marketing insights offer valuable information regarding customer needs, preferences, and behaviors, thus refining marketing strategies and enhancing overall customer experiences. Conversely, BI facilitates data-driven decision-making, leading to heightened operational efficiency, product quality, and customer satisfaction. The analysis of customer data through BI unveils patterns and trends, informing product development, marketing campaigns, and customer service initiatives aimed at enriching experiences and knowledge. Customer experiential knowledge (CEK) encompasses customers' implicit comprehension of consumption experiences influenced by diverse factors, including social and cultural influences. This study primarily focuses on telecommunications companies in Jordan, scrutinizing how experiential customer knowledge mediates the relationship between marketing intelligence, business intelligence, and innovation in product and service offerings. Drawing on theoretical frameworks such as the resource-based view (RBV) and service-dominant logic (SDL), the research aims to comprehend how organizations utilize their resources, particularly knowledge, to foster innovation. Employing a quantitative research approach, the study collected and analyzed primary data to explore hypotheses. The chosen method was justified for its efficacy in handling large sample sizes. Structural equation modeling (SEM) facilitated by Smart PLS software evaluated the relationships between the constructs, followed by mediation analysis to assess the indirect associations in the model. The study findings offer insights into the intricate dynamics of organizational innovation, uncovering the interconnected relationships between business intelligence, customer experiential knowledge-based innovation (CEK-DI), marketing intelligence (MI), and product and service innovation (PSI), underscoring the pivotal role of advanced intelligence capabilities in developing innovative practices rooted in a profound understanding of customer experiences. Organizations equipped with cutting-edge BI tools are better positioned to devise strategies informed by precise insights into customer needs and behaviors. Furthermore, the positive impact of BI on PSI reaffirms the significance of data-driven decision-making in shaping the innovation landscape. Companies leveraging BI demonstrate adeptness in identifying market opportunities guiding the development of novel products and services. The substantial impact of CEK-DI on PSI highlights the crucial role of customer experiences in driving organizational innovation. Firms actively integrating customer insights into their innovation processes are more likely to create offerings aligned with customer expectations, fostering higher levels of product and service innovation. Additionally, the positive and significant effect of MI on CEK-DI underscores the critical role of market insights in shaping innovative strategies. While the relationship between MI and PSI is positive, a slightly weaker significance level indicates a nuanced association, suggesting that while MI contributes to innovation, other factors may also influence the innovation landscape, warranting further exploration. In conclusion, the study underscores the essential role of intelligence capabilities, particularly artificial intelligence, in driving innovation, emphasizing the necessity for organizations to leverage market and customer intelligence for effective and competitive innovation practices. Collaborative efforts between marketing and business intelligence serve as pivotal drivers of innovation, influencing experiential customer knowledge and shaping organizational strategies and practices, ultimately enhancing overall customer experiences and organizational performance.

Keywords: marketing intelligence, business intelligence, product, customer experiential knowledge-driven innovation

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