The theme of this issue of the St. Gallen Business Review is "Harmony". For this reason, we would like to discuss whether two aspects of our life- world are in harmony, namely economic optimization and morality. What is the relation between them? According to a widely shared view, which is one aspect of the doctrine of "mainstream economics", the functioning of an economic system does not require moral behaviour on the part of the individual economic agent. In what follows, we (...) will try to convince you that this is false. If all economic agents – managers, employees, bankers, consumers and so on – were purely self-interested, as mainstream economics assumes, our economic practice would fail. There are various reasons for this. Here we will focus on one of them, namely the pivotal role of interpersonal communication. (shrink)

This dissertation is an attempt to find a single framework for understanding two seemingly conflicting aspects of Nabokov's Russian novels---the metaphysical and the existential. The metaphysical aspect is analyzed according to Leibniz's "Monadology," with its key concepts of the monad, pre-established harmony, the optimization of the universe, and sufficient reason. The existential aspect is examined according to Sartre's theory of the gaze from "Being and Nothingness"; its main notions are being-for-another, radical individuation and intersubjective struggle. Concern with the level of (...) being is assumed to be the most basic and unifying element of the Nabokovian worldview. It is shown that Nabokov conceives individual being as value, and that he understands self-authorship as self-ownership. The value of individual being is threatened by intersubjective contact: the other, via the gaze, can undermine its property status, and eventually alienate it. All particular plots are derived from these underlying premises. The key Nabokovian themes of blindness, non-transparency, loss, memory and art are demonstrated to refer back to the root concepts of the gaze and self-protection. ;The dissertation develops two original conceptual tools: a theory of unreliable focalization and a theory of paranoid experience ;Close readings of Nabokov's texts have resulted in several philological findings. Structural and textual parallels have been discovered between "Mashen'ka" and Shakespeare's "Hamlet," as well as between "Priglashenie na kazn'" and Descartes' "Meditations." It has also been shown that the protagonist's story in "Zashchita Luzhina" is repeated four times and not two. (shrink)

Let us start by some general definitions of the concept of complexity. We take a complex system to be one composed by a large number of parts, and whose properties are not fully explained by an understanding of its components parts. Studies of complex systems recognized the importance of “wholeness”, defined as problems of organization (and of regulation), phenomena non resolvable into local events, dynamics interactions in the difference of behaviour of parts when isolated or in higher configuration, etc., in (...) short, systems of various orders (or levels) not understandable by investigation of their respective parts in isolation. In a complex system it is essential to distinguish between ‘global’ and ‘local’ properties. Theoretical physicists in the last two decades have discovered that the collective behaviour of a macro-system, i.e. a system composed of many objects, does not change qualitatively when the behaviour of single components are modified slightly. Conversely, it has been also found that the behaviour of single components does change when the overall behaviour of the system is modified. There are many universal classes which describe the collective behaviour of the system, and each class has its own characteristics; the universal classes do not change when we perturb the system. The most interesting and rewarding work consists in finding these universal classes and in spelling out their properties. This conception has been followed in studies done in the last twenty years on second order phase transitions. The objective, which has been mostly achieved, was to classify all possible types of phase transitions in different universality classes and to compute the parameters that control the behaviour of the system near the transition (or critical or bifurcation) point as a function of the universality class. This point of view is not very different from the one expressed by Thom in the introduction of Structural Stability and Morphogenesis (1975). It differs from Thom’s program because there is no a priori idea of the mathematical framework which should be used. Indeed Thom considers only a restricted class of models (ordinary differential equations in low dimensional spaces) while we do not have any prejudice regarding which models should be accepted. One of the most interesting and surprising results obtained by studying complex systems is the possibility of classifying the configurations of the system taxonomically. It is well-known that a well founded taxonomy is possible only if the objects we want to classify have some unique properties, i.e. species may be introduced in an objective way only if it is impossible to go continuously from one specie to another; in a more mathematical language, we say that objects must have the property of ultrametricity. More precisely, it was discovered that there are conditions under which a class of complex systems may only exist in configurations that have the ultrametricity property and consequently they can be classified in a hierarchical way. Indeed, it has been found that only this ultrametricity property is shared by the near-optimal solutions of many optimization problems of complex functions, i.e. corrugated landscapes in Kauffman’s language. These results are derived from the study of spin glass model, but they have wider implications. It is possible that the kind of structures that arise in these cases is present in many other apparently unrelated problems. Before to go on with our considerations, we have to pick in mind two main complementary ideas about complexity. (i) According to the prevalent and usual point of view, the essence of complex systems lies in the emergence of complex structures from the non-linear interaction of many simple elements that obey simple rules. Typically, these rules consist of 0–1 alternatives selected in response to the input received, as in many prototypes like cellular automata, Boolean networks, spin systems, etc. Quite intricate patterns and structures can occur in such systems. However, what can be also said is that these are toy systems, and the systems occurring in reality rather consist of elements that individually are quite complex themselves. (ii) So, this bring a new aspect that seems essential and indispensable to the emergence and functioning of complex systems, namely the coordination of individual agents or elements that themselves are complex at their own scale of operation. This coordination dramatically reduces the degree of freedom of those participating agents. Even the constituents of molecules, i.e. the atoms, are rather complicated conglomerations of subatomic particles, perhaps ultimately excitations of patterns of superstrings. Genes, the elementary biochemical coding units, are very complex macromolecular strings, as are the metabolic units, the proteins. Neurons, the basic elements of cognitive networks, themselves are cells. In those mentioned and in other complex systems, it is an important feature that the potential complexity of the behaviour of the individual agents gets dramatically simplified through the global interactions within the system. The individual degrees of freedom are drastically reduced, or, in a more formal terminology, the factual space of the system is much smaller than the product of the state space of the individual elements. That is one key aspect. The other one is that on this basis, that is utilizing the coordination between the activities of its members, the system then becomes able to develop and express a coherent structure at a higher level, that is, an emergent behaviour (and emergent properties) that transcends what each element is individually capable of. (shrink)

For many contemporary artists, failure has been an instrument of experimentation and self-expression, of investigation into existential questions and manifestation of utopian tensions. In this paper, I will discuss how some of the well-known strategies of experimental and avant-garde artistic practices with failure involve risky actions, challenging or impossible attempts, loss of control, and compulsive repetition of inconclusive acts. In those experimentations, the ideal model of an effective and successful action performance (in which a goal is defined through a (...) clear intention, a plan and a well-controlled execution) is willfully sabotaged in its stages. In this regard, a distinction between failure and mistake will be highlighted: if failure could be traced back to the tradition of heroic or tragic defeat in front of adverse odds, mistake on the contrary means doing something wrong that one is expected to control. While failure negatively reflects our tension toward autonomy, the focus on mistakes is the expression of rigidity and heightened risk aversion in contexts where maximal efficiency and self-optimization are expected. This paper will argue that equating the category of failure with that of mistake is not faithful to the motives underlying those artistic traditions. In this respect, artistic experimentations in the “aesthetic of failure” can also be viewed as a critical response toward a general mindset defined by the anxiety of control and obsessive mistake avoidance that seems typical of our current times. (shrink)

The research introduces a novel framework that incorporates real-time monitoring, dynamic resource allocation, and adaptive threshold settings to ensure consistent SLA adherence while optimizing computing performance. Extensive simulations are conducted using synthetic and real-world datasets to evaluate the performance of the proposed algorithm. The results demonstrate that the optimized load balancing approach outperforms traditional algorithms in terms of SLA compliance, resource utilization, and energy efficiency. The findings suggest that the integration of optimization techniques into load balancing algorithms can significantly enhance (...) the operational efficiency of data centers, paving the way for future advancements in autonomous and self-optimizing data centers. (shrink)

The future of human computation benefits from examining tasks that agents already perform and designing environments to give those tasks computational significance. We call this natural human computation. We consider the possible future of NHC through the lens of Swarm!, an application under development for Google Glass. Swarm! motivates users to compute the solutions to a class of economic optimization problems by engaging the attention dynamics of crowds. We argue that anticipating and managing economies of attention provides one of the (...) most tantalizing future applications for NHC. (shrink)

Biological order provided by α-helical secondary protein structures is an important resource exploitable by living organisms for increasing the efficiency of energy transport. In particular, self-trapping of amide I energy quanta by the induced phonon deformation of the hydrogen-bonded lattice of peptide groups is capable of generating either pinned or moving solitary waves following the Davydov quasiparticle/soliton model. The effect of applied in-phase Gaussian pulses of amide I energy, however, was found to be strongly dependent on the site of (...) application. Moving solitons were only launched when the amide I energy was applied at one of the α-helix ends, whereas pinned solitons were produced in the α-helix interior. In this paper, we describe a general mechanism that launches moving solitons in the interior of the α-helix through phase-modulated Gaussian pulses of amide I energy. We also compare the predicted soliton velocity based on effective soliton mass and the observed soliton velocity in computer simulations for different parameter values of the isotropy of the exciton-phonon interaction. The presented results demonstrate the capacity for explicit control of soliton velocity in protein α-helices, and further support the plausibility of gradual optimization of quantum dynamics for achieving specialized protein functions through natural selection. (shrink)

The potential for Large Language Models (LLMs) to attain technological singularity—the point at which artificial intelligence (AI) surpasses human intellect and autonomously improves itself—is a critical concern in AI research. This paper explores the feasibility of current LLMs achieving singularity by examining the philosophical and practical requirements for such a development. We begin with a historical overview of AI and intelligence amplification, tracing the evolution of LLMs from their origins to state-of-the-art models. We then proposes a theoretical framework to assess (...) whether existing LLM technologies could satisfy the conditions for singularity, with a focus on Recursive Self-Improvement (RSI) and autonomous code generation. We integrate key component technologies, such as Reinforcement Learning from Human Feedback (RLHF) and Direct Preference Optimization (DPO), into our analysis, illustrating how these could enable LLMs to independently enhance their reasoning and problem-solving capabilities. By mapping out a potential singularity model lifecycle and examining the dynamics of exponential growth models, we elucidate the conditions under which LLMs might self-replicate and rapidly escalate their intelligence. We conclude with a discussion of the ethical and safety implications of such developments, underscoring the need for responsible and controlled advancement in AI research to mitigate existential risks. Our work aims to contribute to the ongoing dialogue on the future of AI and the critical importance of proactive measures to ensure its beneficial development. (shrink)

ANNOTATION Sardak S.E. Global Regulatory System of Human Resources Development. – Manuscript. Thesis for the Doctor of Economic Science academic degree with major in 08.00.02 – World Economy and international economic relations. – SHEE «Kyiv National Economic University named after Vadym Hetman», Kyiv, 2014. The preconditions and factors of the global economic system with the identified relevant subjects areas and mechanisms of regulation instruments have been investigated. The crucial role of humans in the global economic system as a key factor (...) of production, the main resource, the producer and the consumer of economic and social benefits that are exposed to global threats, problems, challenges, trends and subjects has been confirmed. There have been revealed the causes and consequences of the public institutions transformation under the influence of globalization, which formed a qualitatively new conditions for social and economic development that determine the need for further changes in the areas of conceptual guideline for the management of human resources development, optimization of tasks, state and international institutions activity forms, integration of efforts as for monitoring, planning and forecasting. The modern major instruments and spheres of international cooperation to ensure human development have been determined. The integrated characteristic of human resources and their role in social development both from the standpoint of their use in labour processes and as a medium of civilization and social utility with the help of the categorical classification system organizing and expanding which enables to design and apply the appropriate approaches at all managerial levels have been defined. The necessity and the concept of human resources development in the context of the content of managerial influence identifying (self-development, self-management and external control of development) at different administrative levels that ensures the growth of human capital to the limits of its potential have been analysed. The survey of human activity system aspects in the global world, taking into account the parametrization of the global environment, its structure, management and development have been realized. The formed methodology principles of managerial influence on the development of human resources with scientific schools, hardness degrees, available models, research and providing theoretical and practical implementation peculiarities for groups of countries and territories of the world taken into consideration have been examined. There have been noted civilization and national differences in the forms of managerial influence on the development of human resources, which lead to the formation of human resources development national control systems conditioned by different value public strategic guidelines, especially in relation to social security, education, national management and state migration policy. The current and future requirements for global human resources development which are proposed to be achieved by the development and formalization of global civilizational paradigm of social development due to social coordination interaction have been given. The influence of the institute of state on the human resources development has been evaluated and it has been proved that in the beginning of the XXI century in the global environment the institute of state is the ultimate guarantor of its citizens’ labour ability and vital activity renewal, that makes it the main instrument of managerial influence on human development. The methodology of countries and territories matrix positioning by human development qualitative criteria and population size quantitative parameters which allows to design unified managerial measures as for human resources for similar national economies in the context of global regulatory trends has been proposed. The strategic trends of improvement of human resources development in the national economy, taking into account the differences in the development of human resources in different countries and areas which vary and differ in their focus, content and ways of implementation for such groups. The varying criteria for evaluating the effectiveness of the global impact on human resources development, taking into account the natural, biological, technological, economic, social and management dimensions and the results of human resources development management in social and economic systems at various levels have been revealed. The periodization and the forecast of the global dynamics of human resources development by analyzing and modeling the values of the absolute and relative terms correlation character have been carried out, which enables to make their retrospective and prospective comparison and to find chronological boundaries of qualitatively different periods. The configuration of the human resource development global coordinate system as a set of interrelated principles, components, fields, tools, frameworks, management levels and forms of managerial influence that allows with the help of institutional means to adapt the state of human resources development to a globally varying environment. (shrink)

Critical theory has long resisted the notion that an “invisible hand” can operate within the real social dynamics of a free market. But despite the most radical desires of the socially critical imagination, the optimization of that “spontaneous order” or depersonalized way of ordering things known as “the economy” has become the dominant playing field and decisive electoral issue of modern politics. Within this broad contemporary context, Michel Foucault made a strange theoretical intervention that, to this day, continues to baffle (...) readers. During a lecture, he argued that Adam Smith’s invisible hand was, after all, truly and purposively, that is, for technical rather than ideological reasons, “invisible.” This article argues that there is a counter-positivism or tactical irony contained within the logic of such a controversial thesis; namely, that when one acknowledges that the principle of economic competition encourages an efficient self-organizing effect at all times, regardless of context, one is also immediately in a position to appreciate why the art of government should always maintain its political primacy over the spontaneous order of the market. (shrink)

Ob im Fitnessstudio, in der Mode oder bei der Ernährung – heute wird ständig Körperoptimierung betrieben. Durch neue technologische Entwicklungen wie Neuroimplantate und Brain-Computer-Interfaces (neurologisches Enhancement) wird die Körperoptimierung auf eine neue Ebene gehoben. Mittels Pharmazeutika sollen Kognition (kognitives Enhancement) oder moralische Verhaltensweisen (moralisches Enhancement) verbessert werden, Prothesen werden in den Körper integriert und es werden ästhetisch-chirurgische Eingriffe vorgenommen. 2019 wurden insgesamt 983.432 ästhetische Eingriffe in Deutschland unternommen.1 Im Alltag sind Wearables wie Smartwatches mit ihren Fitnessprogrammen und vielfältige Smartphone-Apps zur (...) Körperoptimierung allgegenwärtig. Technologische Körperoptimierung spielt eine wichtige Rolle im menschlichen Leben und bedarf einer ethischen Auseinandersetzung. Der Beitrag behandelt die Frage, wie die gegenwärtigen technologischen Körperoptimierungen ethisch bewertet werden können und stellt dabei die Autonomie ins Zentrum der ethischen Überlegungen. Inwiefern kann die Entscheidung für eine Körperoptimierung autonom getroffen werden? Welche ethischen Aspekte spielen eine Rolle und wie wirken sich die Optimierungen auf das Selbstverständnis des Individuums aus? -/- Die Fülle an Optimierungsmaßnahmen macht es notwendig, in Kap. 1 zunächst in den Begriff, die Formen und Ziele der Körperoptimierung einzuführen und Differenzierungen vorzunehmen. In Kap. 2 wird die Autonomie in den Fokus gerückt und mit Rückgriff auf Foucaults Konzepte der „Bio-Macht“ und „Technologien des Selbst“ untersucht, wie die Optimierungsentscheidungen zwischen individueller Selbstbestimmung und gesellschaftlicher Fremdbestimmung verortet werden können. Daran anknüpfend wird in Kap. 3 nach einer ethischen Bewertung der Optimierungsmaßnahmen gefragt. Der Aufsatz sucht nach einer ethischen Einordnung der Körperoptimierungen und gelangt letztlich zu wichtigen Erkenntnissen über den Zusammenhang von Identität/ Körper, Gesellschaft und Technik. Kap. 4 führt dazu die These aus, dass Technik mithervorbringt, was Körper bedeutet und zeigt auf, wie Technologien auf diese Weise eine Chance sein können, das Menschenund Körperverständnis neu und inklusiv auszuhandeln. Aus den Untersuchungsergebnissen werden letztlich in Kap. 5 Schlüsse für die Theologie abgeleitet und Wege dargestellt, wie die Theologie einen Beitrag zu den Optimierungen leisten kann. Abschließend wird in Kapitel 6 ein Fazit gezogen und ein Ausblick für die zukünftige ethische Forschung eröffnet. (shrink)

Sex is an important part of human life. It is a source of pleasure and intimacy, and is integral to many people’s self-identity. This chapter examines the opportunities and challenges posed by the use of AI in how humans express and enact their sexualities. It does so by focusing on three main issues. First, it considers the idea of digisexuality, which according to McArthur and Twist (2017) is the label that should be applied to those ‘whose primary sexual identity (...) comes through the use of technology’, particularly through the use of robotics and AI. While agreeing that this phenomenon is worthy of greater scrutiny, the chapter questions whether it is necessary or socially desirable to see this as a new form of sexual identity. Second, it looks at the role that AI can play in facilitating human-to-human sexual contact, focusing in particular on the use of self-tracking and predictive analytics in optimising sexual and intimate behaviour. There are already a number of apps and services that promise to use AI to do this, but they pose a range of ethical risks that need to be addressed at both an individual and societal level. Finally, it considers the idea that a sophisticated form of AI could be an object of love. Can we be truly intimate with something that has been ‘programmed’ to love us? Contrary to the widely-held view, this chapter argues that this is indeed possible. (shrink)

The rise of social-media-mediated celebrity culture raises several philosophical concerns. Therefore, it is not uncommon to see, for example, Hollywood actors being placed in the same bracket as YouTube artists and Instagram influencers. The increased perceived ‘connectivity’ afforded by social media allows online celebrities to reach more fans and increases the perceived engagement or intimacy in the fan-celebrity relationship. In this paper I argue that this online relationship, which is beneficial to celebrities (for brand development) and social media companies (in (...) profiting from the high engagement), has the potential to cause harm to both the celebrities as well as their fanbases (and sometimes innocent third parties). Firstly, I argue that celebrities’ attempts to be more intimate or authentic with their fanbase can turn out to be – more often than not – acts of Sartrean bad faith. Celebrities who tend to project a certain self-styled ‘online authenticity’, given the context of social media’s attention economy, can run the risk of treating a fan as a means-to-an-end, rather than an autonomous for-itself. Secondly, I argue that this phenomenon can catalyse real-world harms, by drawing upon network theory and social psychology. I argue that the connectedness of social media, ‘blending into the crowd’, and social media technologies’ ethos of optimising-for-engagement, leads to real harms to human well-being when fans do not engage critically and mindfully with online celebrities. Examples include Trump-esque celebrity politicians trying to drum up populist influence; celebrities feuding online encouraging fans’ conduct of harmful trolling and harassment; and vilification of those who do not subscribe to the same perceived worldview of a celebrity’s fandom. Following my arguments within, I shall outline an online celebrity’s ethical duties in their social media engagement, with emphasis on the duties that celebrity status comes with, particularly in preventing harms that transcend the online into the offline. (shrink)

The relations between rationality and optimization have been widely discussed in the wake of Herbert Simon's work, with the common conclusion that the rationality concept does not imply the optimization principle. The paper is partly concerned with adding evidence for this view, but its main, more challenging objective is to question the converse implication from optimization to rationality, which is accepted even by bounded rationality theorists. We discuss three topics in succession: (1) rationally defensible cyclical choices, (2) the revealed preference (...) theory of optimization, and (3) the infinite regress of optimization. We conclude that (1) and (2) provide evidence only for the weak thesis that rationality does not imply optimization. But (3) is seen to deliver a significant argument for the strong thesis that optimization does not imply rationality. (shrink)

This article presents a simple derivation of optimization models for reaction networks leading to a generalized form of the mass-action law, and compares the formal structure of Minimum Information Divergence, Quadratic Programming and Kirchhoff type network models. These optimization models are used in related articles to develop and illustrate the operation of ontology alignment algorithms and to discuss closely connected issues concerning the epistemological and statistical significance of sharp or precise hypotheses in empirical science.

In today's data-driven world, the efficient management of network resources is crucial for optimizing performance in data centers and large-scale networks. Load balancing is a critical process in ensuring the equitable distribution of data across multiple paths, thereby enhancing network throughput and minimizing latency. This paper presents a comprehensive approach to load balancing using advanced optimization techniques integrated with multipath routing protocols. The primary focus is on dynamically allocating network resources to manage the massive volume of data generated by modern (...) applications. By leveraging algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), the proposed method efficiently distributes data across multiple paths, ensuring balanced network utilization. The combination of these algorithms with multipath routing significantly reduces congestion and improves overall network performance. (shrink)

: In today's data-driven world, the efficient management of network resources is crucial for optimizing performance in data centers and large-scale networks. Load balancing is a critical process in ensuring the equitable distribution of data across multiple paths, thereby enhancing network throughput and minimizing latency. This paper presents a comprehensive approach to load balancing using advanced optimization techniques integrated with multipath routing protocols. The primary focus is on dynamically allocating network resources to manage the massive volume of data generated by (...) modern applications. By leveraging algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), the proposed method efficiently distributes data across multiple paths, ensuring balanced network utilization. The combination of these algorithms with multipath routing significantly reduces congestion and improves overall network performance. Simulations conducted on various network scenarios demonstrate the effectiveness of this approach, showcasing improvements in data throughput, reduced packet loss, and enhanced quality of service (QoS). (shrink)

The Genetic Algorithm (GA) and Simulated Annealing (SA), two techniques for global optimization, were applied to a reduced (simplified) form of the phase problem (RPP) in computational crystallography. Results were compared with those of "enhanced pair flipping" (EPF), a more elaborate problem-specific algorithm incorporating local and global searches. Not surprisingly, EPF did better than the GA or SA approaches, but the existence of GA and SA techniques more advanced than those used in this study suggest that these techniques still hold (...) promise for phase problem applications. The RPP is, furthermore, an excellent test problem for such global optimization methods. (shrink)

Wireless Sensor Networks (WSNs) have become increasingly prevalent in various applications, ranging from environmental monitoring to smart cities. However, the limited energy resources of sensor nodes pose significant challenges in maintaining network longevity and data transmission efficiency. Duty-cycled WSNs, where sensor nodes alternate between active and sleep states to conserve energy, offer a solution to these challenges but introduce new complexities in data transmission. This paper presents an optimized approach to aggregated packet transmission in duty-cycled WSNs, utilizing advanced optimization techniques (...) to enhance energy efficiency, reduce latency, and improve network throughput. By aggregating data packets from multiple nodes before transmission, the proposed method minimizes the number of transmissions, thereby conserving energy. Optimization algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) are employed to determine the optimal aggregation and transmission schedules, taking into account factors such as network topology, node energy levels, and data urgency. T. (shrink)

In today's data-driven world, the efficient management of network resources is crucial for optimizing performance in data centers and large-scale networks. Load balancing is a critical process in ensuring the equitable distribution of data across multiple paths, thereby enhancing network throughput and minimizing latency. This paper presents a comprehensive approach to load balancing using advanced optimization techniques integrated with multipath routing protocols. The primary focus is on dynamically allocating network resources to manage the massive volume of data generated by modern (...) applications. By leveraging algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), the proposed method efficiently distributes data across multiple paths, ensuring balanced network utilization. The combination of these algorithms with multipath routing significantly reduces congestion and improves overall network performance. (shrink)

In this article I analyse two complaints of white vilification, which are increasingly occurring in Australia. I argue that, though the complainants (and white people generally) are not harmed by such racialized speech, the complainants in fact harm Australians of colour through these utterances. These complaints can both cause and constitute at least two forms of epistemic injustice (willful hermeneutical ignorance and comparative credibility excess). Further, I argue that the complaints are grounded in a dual misrecognition: the complainants misrecognize themselves (...) in their own privileged racial specificity, and they misrecognize others in their own marginal racial specificity. Such misrecognition preserves the cultural imperialism of Australia’s dominant social imaginary—a means of oppression that perpetuates epistemic insensitivity.Bringing this dual misrecognition to light best captures the indignity that is suffered by the victims of the aforementioned epistemic injustices. I argue that it is only when we truly recognize difference in its own terms, shifting the dominant social imaginary, that “mainstream Australians”can do their part in bringing about a just society. (shrink)

Cardiovascular diseases (CVD) represent a significant cause of morbidity and mortality worldwide, necessitating early detection for effective intervention. This research explores the application of machine learning (ML) algorithms in predicting cardiovascular diseases with enhanced accuracy by integrating optimization techniques. By leveraging data-driven approaches, ML models can analyze vast datasets, identifying patterns and risk factors that traditional methods might overlook. This study focuses on implementing various ML algorithms, such as Decision Trees, Random Forest, Support Vector Machines, and Neural Networks, optimized through (...) techniques like hyperparameter tuning, cross-validation, and feature selection to improve prediction accuracy. (shrink)

Emergency response times play a critical role in saving lives, especially in urban settings where traffic congestion and unpredictable events can delay ambulance arrivals. This paper explores a novel framework for smart route optimization for emergency vehicles, leveraging artificial intelligence (AI), Internet of Things (IoT) technologies, and dynamic traffic analytics. We propose a real-time adaptive routing system that integrates machine learning (ML) for predictive modeling and IoT-enabled communication with traffic infrastructure. The system is evaluated using simulated urban environments, achieving a (...) 35% reduction in response times compared to traditional methods. This work lays the foundation for future advancements in intelligent emergency systems and their integration into smart cities. (shrink)

This paper will be concerned with hard choices—that is, choice situations where an agent cannot make a rationally justified choice. Specifically, this paper asks: if an agent cannot optimize in a given situation, are they facing a hard choice? A pair of claims are defended in light of this question. First, situations where an agent cannot optimize because of incompleteness of the binary preference or value relation constitute a hard choice. Second, situations where agents cannot optimize because the binary preference (...) or value relation violates acyclicity do not constitute a hard choice. (shrink)

Emergency response times play a critical role in saving lives, especially in urban settings where traffic congestion and unpredictable events can delay ambulance arrivals. This paper explores a novel framework for smart route optimization for emergency vehicles, leveraging artificial intelligence (AI), Internet of Things (IoT) technologies, and dynamic traffic analytics. We propose a real-time adaptive routing system that integrates machine learning (ML) for predictive modeling and IoT-enabled communication with traffic infrastructure. The system is evaluated using simulated urban environments, achieving a (...) 35% reduction in response times compared to traditional methods. This work lays the foundation for future advancements in intelligent emergency systems and their integration into smart cities. (shrink)

The article examines the process of formation inventory of the enterprise and determines the optimal volume of commodity resources for sale. A generalization of author’s approaches to the formation and evaluation of inventories of the enterprise is carried out. The marketing-logistic approach was applied for the purpose of distribution groups of commodity resources due to the risk of non-fulfillment the order for the supply of goods of the enterprise. In order to ensure an effective process of commodity provision of the (...) enterprises, the costs associated with the formation of inventories are determined. The formalized scheme of the formation commodity provision and the process of optimization inventory of the enterprise is offered. The analysis the structure of the company’s inventory is carried out, the volume of goods turnover is defined, the stocks are grouped for various clustering characteristics. To conduct the study, statistical information was used on commodity resources of the enterprises, statistical methods (grouping, structure analysis, estimation of dynamic series), tools for assessing the efficiency of inventory use, HML-FMR clustering were used. The necessity of using XYZ and ABC analysis is indicated in order to obtain more reliable results and forecast values of the product support of the enterprise. Economic-mathematical modeling is applied and graphically shown the difference in the formation of commodity resources by various features of HML-FMR clustering. The calculations allow the enterprise to determine the optimal amount of commodity resources in accordance with the needs of consumers and their solvent demand, to plan financial resources for the formation of inventories, to develop assortment policy in accordance with demand for products and their implementation. The results of calculations the volume of merchandising of the enterprise, taking into account the HML-FMR clustering affect the formation of final financial performance of the enterprise — income and profits. (shrink)

This qualitative case study investigates the environmental implications of tourist arrivals in Matabungkay Beach, Lian, and their impact on the destination image. Through in-depth interviews with seven key stakeholders, including local residents, business owners, and environmental activists, the study explores perceptions, concerns, and potential solutions regarding the intersection of tourism and environmental sustainability. Findings reveal a complex relationship between tourism and environmental degradation, with participants expressing concerns about poor waste management, impacts on destination image, and health concerns. These challenges not (...) only threaten the natural beauty and biodiversity of the area but also tarnish the destination's image, affecting its appeal to tourists and potential investors. Despite these challenges, participants highlight existing initiatives and potential solutions, including community-based conservation efforts, sustainable tourism practices, and enhanced regulations. Collaboration among stakeholders is emphasized as crucial for achieving a balance between tourism development and environmental preservation. The study underscores the need for comprehensive strategies includes formulated an ordinance for comprehensive waste management and pollution control ordinance to optimize the destination image of Matabungkay Beach while addressing its environmental challenges. By integrating sustainable practices and fostering community engagement, the destination can enhance its appeal while safeguarding its natural resources for future generations. (shrink)

The Internet of Things (IoT) connects schemes, programs, data management, and operations, and as they continuously assist in the corporation, they may be a fresh entryway for cyber-attacks. Presently, illegal downloading and virus attacks pose significant threats to IoT security. These risks may acquire confidential material, causing reputational and financial harm. In this paper hybrid optimization mechanism and deep learning,a frame is used to detect the attack prevention in IoT. To develop a cybersecurity warning system in a huge data set, (...) the cybersecurity warning systems index system is first constructed, then the index factors are picked and measured, and finally, the situation evaluation is done.Numerous bio-inspired techniques were used to enhance the productivity of an IDS by lowering the data dimensionality and deleting unnecessary and noisy input. The Grey Wolf Optimization algorithm (GWO) is a developed bio-inspired algorithm that improves the efficacy of the IDS in detecting both regular and abnormal congestion in the network. The smart initialization step integrates the different pre-processing strategies to make sure that informative features are incorporated in the early development stages, has been improved. Researchers pick multi-source material in a big data environment for the identification and verification of index components and present a parallel reduction approach based on the classification significance matrix to decrease data underlying data characteristics. For the simulation of this situation, grey wolf optimization and whale optimization were combined to detect the attack prevention and the deep learning approach was presented. Utilizing system software plagiarism, the TensorFlow deep neural network is intended to classify stolen software. To reduce the noise from the signal and to zoom the significance of each word in the perspective of open-source plagiarism, the tokenization and weighting feature approaches are utilized. Malware specimens have been collected from the Mailing database for testing purposes. The experimental findings show that the suggested technique for measuring cyber security hazards in IoT has superior classification results to existing methods. Hence to detect the attack prevention in IoT process Whale with Grey wolf optimization (WGWO) and deep convolution network is used. (shrink)

t Intentional sampling methods are non-randomized procedures that select a group of individuals for a sample with the purpose of meeting specific prescribed criteria. In this paper we extend previous works related to intentional sampling, and address the problem of sequential allocation for clinical trials with few patients. Roughly speaking, patients are enrolled sequentially, according to the order in which they start the treatment at the clinic or hospital. The allocation problem consists in assigning each new patient to one, and (...) only one, of the alternative treatment arms. The main requisite is that the profiles in the alternative arms remain similar with respect to some relevant patients’ attributes (age, gender, disease, symptom severity and others). We perform numerical experiments based on a real case study and discuss how to conveniently set up perturbation parameters, in order to yield a suitable balance between optimality – the similarity among the relative frequencies of patients in the several categories for both arms, and decoupling – the absence of a tendency to allocate each pair of patients consistently to the same arm. (shrink)

Phishing attacks remain one of the most prevalent cybersecurity threats, affecting individuals and organizations globally. The rapid evolution of phishing techniques necessitates more sophisticated detection and classification methods. In this paper, we propose a novel approach to phishing content classification using a Genetic Ranking Optimization Algorithm (GROA), combined with dynamic weighting, to improve the accuracy and ranking of phishing versus legitimate content. Our method leverages features such as URL structure, email content analysis, and user behavior patterns to enhance the detection (...) system's decision-making process. (shrink)

Application of the reliability of repairable systems on solving problems from constructing production systems takes an important place in the process of finding the optimal solution among the suggested system choices. The basic hypothesis when using the reliability of the repairable systems is that every machine is representing a component, a fact that is debatable when talking about technical sciences. However, considering the second assumption of the stationary process, the function of the availability is introduced. It represents the measure between (...) the reliability and the benefit of maintaining the components and the system as a whole one. An additional and the last reason for analyzing constructing machine as a whole one has an economic reason. From the aspect of the total cost and the capacity of the system, the function of the availability is catching more and more impact in the process of determinating the total cost in bill of quantities as the most important part of tender documents. Until former works, techno-economic optimisation usually ran over when choosing the system of the construction machines. In the work, there are shown the methodologies for gathering and analyzing the indicators of availabilities per unit of a company's machine park. The time of demission and reparation have been investigated among 34 components in the period of 6 years. Based on the obtained result for different conditions of machine exploitation and facilities, it is suggested the methodology of the future behaviour of the corresponding within the model optimization availability of constructing production system with the aim of eliminating extra criterion. The suggested model takes in consideration the total cost of the components when they are functional, and when they are not. This kind of approach enables the one who take choices decision of the height of profits, in the lenght of work in function of the projection of cash flow and managing with real indicators of functioning the system at the project level. Given the fact that the maintanance policy of machines is based on availability, and not on reliability of components, with the aim of maximizing the availability of different budget scenarios, a logical approach to the selection of the objective function in the terms of management of construction production systems is to minimize costs for a given availability of system constructing machinery is based on the use of historical data base with the values of the operational availability of components, conditions in which they function, in the process of forecasting the project availability for projects that follow. Ranking variant solutions is the result of the adopted function of the aim as a consequence due to enlargement methods of availability for serial parallel systems with the associated restrictions. For optimal system availability is taken a value that belongs to minimal total cost. However, it is predicted that after the end of the financial year, the real and projected indicators of system functions get compared to each other. Informational support to the proposed model is informational company system, which was built in the PHP programming language on the Linux software platform, and with data based in My SQL. The suggested model is tested on the system for the production and embedding bitumen bound materials on the specific project. Obtained results confirm the assumptions used in work. (shrink)

Intentional sampling methods are non-probabilistic procedures that select a group of individuals for a sample with the purpose of meeting specific prescribed criteria. Intentional sampling methods are intended for exploratory research or pilot studies where tight budget constraints preclude the use of traditional randomized representative sampling. The possibility of subsequently generalize statistically from such deterministic samples to the general population has been the issue of long standing arguments and debates. Nevertheless, the intentional sampling techniques developed in this paper explore pragmatic (...) strategies for overcoming some of the real or perceived shortcomings and limitations of intentional sampling in practical applications. (shrink)

The research methodology involves data preprocessing, feature engineering, model training, and performance evaluation. We employ optimization methods such as Genetic Algorithms and Grid Search to fine-tune model parameters, ensuring robust and generalizable models. The dataset used includes patient medical records, with features like age, blood pressure, cholesterol levels, and lifestyle habits serving as inputs for the ML models. Evaluation metrics, including accuracy, precision, recall, F1-score, and the area under the ROC curve (AUC-ROC), assess the model's predictive power.

In modern data centers, managing the distribution of workloads efficiently is crucial for ensuring optimal performance and meeting Service Level Agreements (SLAs). Load balancing algorithms play a vital role in this process by distributing workloads across computing resources to avoid overloading any single resource. However, the effectiveness of these algorithms can be significantly enhanced through the integration of advanced optimization techniques. This paper proposes an SLA-driven load balancing algorithm optimized using methods such as genetic algorithms, particle swarm optimization, and simulated (...) annealing. By focusing on both resource utilization and SLA compliance, the proposed approach aims to reduce latency, improve throughput, and maximize overall system efficiency. (shrink)

This capstone is centered around the development of an efficient electronic property inventory system tailored for school assets, driven by the overarching objective of resource optimization to ensure equitable access to vital materials for all learners. The methodology follows the “ISSO” framework (Ignite, Strategize, Systematize, Operationalize), complemented by a Logical Framework. The project employs a homegrown digitalized system constructed through a waterfall model approach, which undergoes alpha and beta testing. The study’s analysis utilizes a t-Test to evaluate its impact. The (...) outcomes reveal that real-time property monitoring significantly enhances custodianship, while digitalization yields improvements in reliability, efficiency, and usability, effectively overhauling the conventional inventory process. The electronic system fosters stakeholder engagement, supporting communication, budget allocation, and audits. Comparative testing demonstrates clear advantages over traditional manual methods. In conclusion, this study underscores the merits of a refined electronic property inventory system. Notably, the research suggests a need for careful consideration of process complexities in outsourcing decisions and showcases the swift, precise, and transparent accounting provided by e-AIMSS deployments, thereby nurturing transparency and public confidence. This innovative approach holds promise for broader application within the realm of e-government processes. (shrink)

A comment on Paul Schoemaker's target article in Behavioral and Brain Sciences, 14 (1991), p. 205-215, "The Quest for Optimality: A Positive Heuristic of Science?" (https://doi.org/10.1017/S0140525X00066140). This comment argues that the optimizing model of decision leads to an infinite regress, once internal costs of decision (i.e., information and computation costs) are duly taken into account.

Clark acknowledges but resists the indirect mind–world relation inherent in prediction error minimization (PEM). But directness should also be resisted. This creates a puzzle, which calls for reconceptualization of the relation. We suggest that a causal conception captures both aspects. With this conception, aspects of situated cognition, social interaction and culture can be understood as emerging through precision optimization.

The Genetic Ranking Optimization Algorithm (GROA) is used to rank phishing content based on multiple features by optimizing the ranking system through iterative selection and weighting. Dynamic weighting further enhances the process by adjusting the weights of features based on their importance in real-time. This hybrid approach enables the model to learn from the data, improving classification over time. The classification system was evaluated using benchmark phishing datasets, and the results demonstrated a significant improvement in detection accuracy and reduced false (...) positives. (shrink)

Cloud computing is the provision of IT resources (IaaS) on-demand using a pay as you go model over the internet. It is a broad and deep platform that helps customers builds sophisticated, scalable applications. To get the full benefits, research on a wide range of topics is needed. While resource over provisioning can cost users more than necessary, resource under provisioning hurts the application performance. The cost effectiveness of cloud computing highly depends on how well the customer can optimize the (...) cost of renting resources (VMs) from cloud providers. The issue of resource provisioning optimization from cloud-consumer potential is a complicated optimization issue, which includes much uncertainty parameters. There is a much research avenue available for solving this problem as it is in the real-world. Here, in this paper we provide details about various optimization techniques for resource provisioning. (shrink)

Purpose: Due to the increase in energy demand and the effects of global warming, energy-efficient buildings have gained significant importance in the modern construction industry. To create a suitable framework with the aim of reducing energy consumption in the building sector, the external walls of a residential building were considered with two criteria of global warming potential and energy consumption. -/- Design/methodology/approach: In the first stage, to achieve a nearly zero-energy building, energy analysis was performed for 37 different states of (...) thermal insulation. Then, the insulation materials’ life cycle assessment was performed. These results were used to find a set of optimal modes in the Pareto front by using non-dominated sorting genetic algorithm II multi-objective genetic algorithm. Thus, based on the data obtained from this method, it was possible to compare and choose different thermal insulation materials based on the distance from the Pareto front, reducing the environmental effects. -/- Findings: The results showed that replacing the windows was possible to save 3.24% in energy consumption. Also, selecting the proper insulation reduced energy consumption value by 63.13%. Finally, this building can save 69.31% of energy consumption compared to the base building by following the zero-energy building standard. As a result, the Pareto curve was introduced as a guide for the optimal design of the building’s wall insulation. -/- Originality/value: The proposed method provides designers with a framework for latent carbon analysis to access quickly and select optimal scenarios. It can also be used without restrictions for other decisions with different goals and criteria. (shrink)

The predictive coding (PC) theory of attention identifies attention with the optimization of the precision weighting of prediction error. Here we provide some challenges for this identification. On the one hand, the precision weighting of prediction error is too broad a phenomenon to be identified with attention because such weighting plays a central role in multimodal integration. Cases of crossmodal illusions such as the rubber hand illusion and the McGurk effect involve the differential precision weighting of prediction error, yet attention (...) does not shift as one would predict. On the other hand, the precision weighting of prediction error is too narrow a phenomenon to be identified with attention, because it cannot accommodate the full range of attentional phenomena. We review criticisms that PC cannot account for volitional attention and affect-biased attention, and we propose that it may not be able to account for feature-based and intellectual attention. (shrink)

The rapid increase of the old age people imposes the reconsideration of the rehabilitation techniques and procedures and/or the development of the existing ones, at least from two points of view: the limitation use of the pharmaceutical drugs because of their secondary effects in the debilitated organisms and their avoidance; the high risk of the induced anxiety states, depression or other symptoms as a consequence of the main disease, i.e. the neuro-degenerative or mobility dysfunctions, limiting again the use of such (...) excessive drug medication. Moreover, Alzheimer’s or Parknson’s diseases are otherwise incurable, so the application of rehabilitating procedures like music-based therapy becomes preferential. The advances both in the identification of the specific auditory musical-sensitive circuits and of the non- musical neuro-connections but activated indirectly by music, otherwise inaccessible by other techniques, and in the understanding of consciousness, which can be described by seven cognitive centers, allows to improve and develop the music based therapy. A multitask procedure based on the activation of these cognition centers is presented, allowing to increase the personal psychical engagement of the patient in the recommended music based therapeutic program, addressed both to the rehabilitation of the main degenerative disease and to the secondary induced dysfunctions. This procedure combines the evidence based medicine assisted by laboratory expertise for the determination of a correct diagnostic, and narrative based medicine allowing to quantify the personal engaging qualities of the patient with respect to the proposed music based program, reducing in this way the gap between these two basic procedures and bringing in a first plane the patient care, not only the disease, with beneficial consequence for the therapy efficiency and for the patient-medical care relations. (shrink)

The rapid evolution of phishing techniques necessitates more sophisticated detection and classification methods. In this paper, we propose a novel approach to phishing content classification using a Genetic Ranking Optimization Algorithm (GROA), combined with dynamic weighting, to improve the accuracy and ranking of phishing versus legitimate content. Our method leverages features such as URL structure, email content analysis, and user behavior patterns to enhance the detection system's decision-making process. The Genetic Ranking Optimization Algorithm (GROA) is used to rank phishing content (...) based on multiple features by optimizing the ranking system through iterative selection and weighting. Dynamic weighting further enhances the process by adjusting the weights of features based on their importance in real-time. This hybrid approach enables the model to learn from the data, improving classification over time. (shrink)

This article examines the Buddhist idea of anātman, ‘no- self ’ and pudgala, ‘the person’ in relation to the notion of ‘self ’ emerging from contemporary cognitive science. The Buddhist no-self doctrine is enriched by the cognitive scientist’s understanding of the multiple facets of selfhood, or structures of experience, and the causative action of a functional self in the world. A proper understanding of the Buddhist concepts of anātman and pudgala proves critical to mindfulness-based therapeutic interventions: (...) this is as the ‘person’, as constituted by various structures of selfhood, including—the ecological, interpersonal, extended, private, narrative, relational and conceptual selves—which may be disrupted by traumatic events which disorder one’s experience of time, defence, relationality, memory, resource and agency. In the absence of this understanding, the no-self doctrine might encourage a sort of bypass, in which traumatic facets of selfhood are overlooked in the quest for spiritual liberation. With a proper understanding of the function served by the Buddhist concepts of no-self and ‘person’, psychotherapeutic work may be situated as a necessary ‘preliminary practice’ for meditative exploration of deeper transpersonal domains and soteriological goals. (shrink)

In this paper we advance a new solution to Quinn’s puzzle of the self-torturer. The solution falls directly out of an application of the principle of instrumental reasoning to what we call “vague projects”, i.e., projects whose completion does not occur at any particular or definite point or moment. The resulting treatment of the puzzle extends our understanding of instrumental rationality to projects and ends that cannot be accommodated by orthodox theories of rational choice.

This paper will be concerned with hard choices—that is, choice situations where an agent cannot make a rationally justified choice. Specifically, this paper asks: if an agent cannot optimize in a given situation, are they facing a hard choice? A pair of claims are defended in light of this question. First, situations where an agent cannot optimize because of incompleteness of the binary preference or value relation constitute a hard choice. Second, situations where agents cannot optimize because the binary preference (...) or value relation violates acyclicity do not constitute a hard choice. (shrink)

Objective: A deep understanding of the relationship between a scarce drug's dose and clinical response is necessary to appropriately distribute a supply-constrained drug along these lines. Summary of key data: The vast majority of drug development and repurposing during the COVID-19 pandemic – an event that has made clear the ever-present scarcity in healthcare systems –has been ignorant of scarcity and dose optimisation's ability to help address it. Conclusions: Future pandemic clinical trials systems should obtain dose optimisation data, (...) as these appear necessary to enable appropriate scarce resource allocation according to societal values. (shrink)