Wie verändern sich Mensch und Körper durch Technik? Und welches Menschenverständnis vertritt der Transhumanismus? Anna Puzio befasst sich in der ersten philosophischen Studie zur Anthropologie des Transhumanismus mit führenden Personen des Feldes, u. a. mit Nick Bostrom, David Pearce und Natasha Vita-More. Neben Körperoptimierung und Medizintechnologien beleuchtet sie auch Alltagstechnologien wie Wearables. Dabei entwickelt sie einen neuen Ansatz zur Technikanthropologie und ein neues inklusives Menschen- und Körperverständnis im Anschluss an Donna Haraway und den Kritischen Posthumanismus im amerikanischen Raum.

Mit den Fortschritten in Generativer Künstlicher Intelligenz, Large Language Models, Brain-Computer Interfaces und genetischen Eingriffen gewinnt auch der Transhumanismus an Relevanz. Der Transhumanismus ist ein beliebtes Thema der Medien und wird in Tages- und Wochenzeitungen sowie im Fernsehen gerne aufgegriffen. Außerdem gibt es inzwischen viele Filme, die den Transhumanismus thematisieren, z. B. die Dokumentation „Endlich unendlich“ (2021, Regie: Stephan Bergmann). Der Transhumanismus wurde in Österreich auch Gegenstand einer Verschwörungserzählung, über die der Bayrische Rundfunk aufgeklärt hat. Auf den Wahlplakaten der „Partei (...) für Gesundheitsforschung“ ist der Transhumanist Aubrey de Grey abgebildet, der ein in Cambridge lebender Brite ist, aber auf Plakaten in Deutschland dargestellt wird. Diese und weitere Entwicklungen machen es notwendig, sich mit dem Transhumanismus aus wissenschaftlicher Perspektive auseinanderzusetzen. Was ist der Transhumanismus? Alle sprechen von Transhumanismus, aber was der Transhumanismus letztlich ist, bleibt häufig unklar. Der Transhumanismus (TH) ist eine philosophisch-technologische Bewegung des 20. und 21. Jahrhunderts, die es sich zum Ziel setzt, mittels neuer Technologien den Menschen grundlegend zu transformieren. Wichtig ist dabei, dass sich der TH nicht mit den Optimierungsbestrebungen in der Gesellschaft oder technologischem Fortschritt gleichsetzen lässt. Vielmehr verstehe ich unter TH die Gruppe, die sich um die Organisation Humanity+ in Kalifornien versammelt und die Personen, die sich explizit alsVertreter*innen des TH verstehen. Der TH hat eine ganz eigene Agenda, eigene Institutionen, Organisationen und Publikationsorgane.4 Zu den Themen und Visionen gehören die Lebensverlängerung von mehreren Hundert Jahren bis zur Unsterblichkeit, Kryonik (das Einfrieren des Körpers, der wieder aufgetaut werden soll, wenn nach transhumanistischer Vorstellung Unsterblichkeit ermöglicht werden kann), umfassendes Enhancement und die Verschmelzung von Körper und Technik sowie Beseitigung allen Leids, aller Krankheiten und Aufhebung des Alterns. Der TH strebt danach, mittels Technik neue Sinnesfähigkeiten zu erlangen und neue (virtuelle) Erfahrungswelten zu erschließen. Außerdem wird von vielen Transhumanist*innen auch die hochspekulative Vision des Mind Uploading vertreten, die streng genommen dem Posthumanismus zugeordnet werden muss Gemäß dieser Vision soll durch das maschinelle Lesen des Gehirns der ganze Mensch auf ein externes Medium hochgeladen werden können. Die Vision des Mind Uploadings ist aus naturwissenschaftlicher Perspektive hochumstritten, ist aber ein sehr beliebtes Motiv, das auch außerhalb des TH Wirkung zeigt und in viele Science-Fiction- Filme Eingang gefunden hat (z.B. die Amazon Serie „Upload“, 2020, Regie: Greg Daniels). Das Bestreben des TH, den Menschen grundlegend zu transformieren, wirft zunächst die Frage auf, wie der TH den Menschen überhaupt versteht. Dieser Frage nach dem Menschenverständnis des TH habe ich mich in meinem Buch „Über-Menschen. Philosophische Auseinandersetzung mit der Anthropologie des Transhumanismus“ gewidmet. Philosophische Anthropologie bezeichnet die wissenschaftlichen, philosophischen Reflexionen auf den Menschen. Welches Menschenverständnis vertritt der TH und lässt sich unsere Anthropologie auf dieser Grundlage weiterentwickeln? Das Buch gliedert sich in drei Teile: Teil 1 führt zuerst in die Bewegung des TH ein, worauf Teil II aufbaut, der sich mit dem Menschenverständnis des TH beschäftigt. Teil III betrachtet schließlich heutige Optimierungsbestrebungen in der Gesellschaft sowie neue Ansätze für die Technikanthropologie (z. B. Kritischer Posthumanismus und Neuer Materialismus). Die nachfolgenden Kapitel dieses Aufsatzes sind ein Ausschnitt aus Teil II, der Untersuchung des transhumanistischen Menschenverständnisses. Dieser Aufsatz widmet sich dem „genetisch codierten Menschen“ im TH, also der transhumanistischen Sicht auf den Menschen als jemanden, die*der vollständig von ihren*seinen Genen bestimmt ist. Der genetische Diskurs ist nur einer von fünf im TH dominanten Diskursen, die das transhumanistische Menschenverständnis ausmachen. Zu den anderen Diskursen bzw. transhumanistischen Bestimmungen des Menschen gehören: der Diskurs um die „Natur des Menschen“, der Maschinendiskurs – die Bestimmung des Menschen als Maschine –, der neurowissenschaftliche Diskurs – die Gleichsetzung des Menschen mit dem Gehirn bzw. Neuronalem und zuletzt die metaphysischen Verhältnisbestimmungen von Geist und Körper (PUZIO, Über-Menschen, Kap. 4). Diese transhumanistischen Bestimmungen des Menschen werden am Ende ausgewertet. Ohne die Ergebnisse dieses Kapitels im Detail vorwegnehmen zu wollen, kann für die Gesamtuntersuchung des TH gesagt werden, dass das transhumanistische Menschenverständnis sich als hochproblematisch erweist. Die transhumanistischen Argumentationsstrukturen sind nicht tragfähig und der TH behauptet sich auf die Naturwissenschaften zu berufen, widerspricht allerdings den aktuellen Ergebnissen der Naturwissenschaften. Dies wird in den nachfolgenden Kapiteln gut deutlich werden. Der TH hat ein reduktionistisches Menschenverständnis und reduziert den Menschen beispielsweise auf „Information“. Viele Ausführungen sind diskriminierend z. B. gegenüber Kranken, Alternden und Menschen mit Behinderungen und letztendlich wird sogar jeder Mensch, auch der gesunde junge Mensch, gegenüber der Maschine abgewertet, die aus transhumanistischer Sicht den Menschen weit übertrifft. Im weiteren Verlauf der Arbeit werden sogar „ideologische Elemente“ im TH identifiziert. Daher wird in der Arbeit abgelehnt, den TH als Grundlage für die Weiterentwicklung der Anthropologie zu verwenden und stattdessen werden im letzten Teil der Arbeit alternative Ansätze für die Technikanthropologie präsentiert. Wie bereits erwähnt, richtet sich die Kritik am TH jedoch nicht gegen die heutige Optimierung in der Gesellschaft, die ebenfalls im letzten Teil der Arbeit diskutiert wird. Optimierungsbestrebungen hat es schon immer gegeben und sie werden nun durch neue Technologien weiter verändert, sie sind aber nicht mit der Bewegung des TH gleichzusetzen. Das Kapitel ist eingebettet zwischen dem Maschinendiskurs (Mensch als Maschine) mit seinen Ausführungen zu Information und Kybernetik und dem neurowissenschaftlichen Diskurs („Der Mensch ist ihr*sein Gehirn“). Es wird im Folgenden der genetische Diskurs im TH untersucht, also wie der TH den Menschen vollständig auf Gene zurückführt, und dies schließlich kritisch geprüft. Sind „gute Gene“ alles? Kann der Mensch vollständig über ihre*seine Gene bestimmt werden? Und was hat es mit der trügerischen „genetischen Information“ auf sich? Zunächst wird der genetische Diskurs im TH dargestellt, also die genetischen Ausführungen des TH präsentiert (Kap. 2), danach wird der Blick auf den Gebrauch der genetischen Metaphern im TH gerichtet (Kap. 3) und zuletzt werden die genetischen Vorstellungen des TH kritisiert (Kap. 4). Der Aufsatz schließt in Kap. 5mit einer (vorläufigen) Zusammenführung der Ergebnisse und einem Ausblick. (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)

In various documents the view emerges that contemporary biotechnosciences are currently experiencing a scientific revolution: a massive increase of pace, scale and scope. A significant part of the research endeavours involved in this scientific upheaval is devoted to understanding and, if possible, ameliorating humankind: from our genomes up to our bodies and brains. New developments in contemporary technosciences, such as synthetic biology and other genomics and “post-genomics” fields, tend to blur the distinctions between prevention, therapy and enhancement. An important dimension (...) of this development is “biomimesis”: i.e. the tendency of novel technologies and materials to mimic or plagiarize nature on a molecular and microscopic level in order to optimise prospects for the embedding of technological artefacts in natural systems such as human bodies and brains. In this paper, these developments are read and assessed from a psychoanalytical perspective. Three key concepts from psychoanalysis are used to come to terms with what is happening in research laboratories today. After assessing the general profile of the current revolution in this manner, I will focus on a particular case study, a line of research that may serve as exemplification of the vicissitudes of contemporary technosciences, namely viral biomaterials. Viral life forms can be genetically modified (their genomes can be rewritten) in such a manner that they may be inserted in human bodies in order to produce substances at specific sites such as hormones (testosterone), neurotransmitters (dopamine), enzymes (insulin) or bone and muscle tissue. Notably, certain target groups such as top athletes, soldiers or patients suffering from degenerative diseases may become the pioneers serving as research subjects for novel applications. The same technologies can be used for various purposes ranging from therapy up to prevention and enhancement. (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.

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)

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 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)

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)

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)

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)

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)

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)

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 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.

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)

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.

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)

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)

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.

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)

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)

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)

The health of plants plays a crucial role in ensuring agricultural productivity and food security. Early detection of plant diseases can significantly reduce crop losses, leading to improved yields. This paper presents a novel approach for plant disease recognition using deep learning techniques. The proposed system automates the process of disease detection by analyzing leaf images, which are widely recognized as reliable indicators of plant health. By leveraging convolutional neural networks (CNNs), the model identifies various plant diseases with high accuracy. (...) The experimental setup includes a dataset consisting of healthy and diseased leaf images of different plant species. The dataset is preprocessed to remove noise and augmented to address the issue of class imbalance. The CNN model is then trained, validated, and tested on this dataset. (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)

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 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)

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)

In TSCH, which is a MAC mechanism set of the IEEE 802.15.4e amendment, calculation, construction, and maintenance of the packet transmission schedules are not defined. Moreover, to ensure optimal throughput, most of the existing scheduling methods are based on the assumption that instantaneous and accurate Channel State Information (CSI) is available. However, due to the inevitable errors in the channel estimation process, this assumption cannot be materialized in many practical scenarios. In this paper, we propose two alternative and realistic approaches. (...) In our first approach, we assume that only the statistical knowledge of CSI is available a priori. Armed with this knowledge, the average packet rate on each link is computed and then, using the results, the throughput-optimal schedule for the assignment of (slot-frame) cells to links can be formulated as a max-weight bipartite matching problem, which can be solved efficiently using the well-known Hungarian algorithm. In the second approach, we assume that no CSI knowledge (even statistical) is available at the design stage. For this zero-knowledge setting, we introduce a machine learning-based algorithm by formally modeling the scheduling problem in terms of a combinatorial multi-armed bandit (CMAB) process. Our CMAB-based scheme is widely applicable to many real operational environments, thanks to its reduced reliance on design-time knowledge. Simulation results show that the average throughput obtained by the statistical CSI-based method is within the margin of 15% from the theoretical upper bound associated with perfect instantaneous CSI. The aforesaid margin is around 18% for our learning-theoretic solution. (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)

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)

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)

Plastic waste is a significant environmental problem for almost all countries; therefore, protecting the environment from the problem is crucial. The most sensible solution to these problems is substituting the natural aggregates with substantial plastic waste in various building materials. This study aimed to optimise the mixed design ratio of cement brick containing plastic waste as aggregate replacement. Plastic cement brick mixtures were prepared by the incorporation of four different types of plastic waste such as polyethylene terephthalate (PET), high-density polyethylene, (...) low-density polyethylene and polypropylene into cement bricks with different cement contents (150, 300 and 450 g) and plastic replacement percentages (0, 3 and 6%). Compressive strength and water absorption of the plastic cement bricks were analysed using a statistical model through the response surface methodology. It revealed the optimum cement brick mixed design is C3-1% PET with the compressive strength of 27.50 MPa and water absorption of 1.16%. The optimised plastic cement brick also satisfied the general ASTM C62-17 requirements for building bricks despite the higher porosity observed by the scanning electron microscopy. The results from Fourier transform infrared spectroscopy analysis also showed that the addition of the plastic waste into cement brick was unlikely to modify the chemical compound within the cement brick mixtures. Thus, the proposed mathematical model can predict the required hardened properties of plastic cement bricks and could lead to greater utilisation of plastic waste in building materials. (shrink)

Teachers' pedagogical strategy in teaching reading comprehension cannot be neglected because when learners fail to comprehend text and give meaning to it, they experience difficulties understanding other subjects taught. This study, therefore, examined reading comprehension strategies adopted by teachers to enhance reading comprehension among primary school learners. This study adopted a qualitative research method with an interpret visit paradigm. Ten (10) teachers were purposively selected for the study one each from ten (10) primary schools. Data was collected the selected participants (...) using semi-structured interview. The researchers ensured the trustworthiness of the interview through disclosure and corroboration. The data collected were transcribed for the purpose of analysis using the atlasti software and the thematic data analysis technique. Findings indicate that some teachers did not understand the various strategies to optimise reading comprehension. Teachers also lacked knowledge of the different learners learning preferences to plan their reading comprehension lessons. Furthermore, the lack of appropriate reading material and differentiated reading exercises for slow learners were highlighted among the challenges that hampered reading comprehension. The study recommends capacity-building programmes to provide strategies for differentiated teaching, to learn to accommodate slow learners and to provide appropriate resources by the education department. (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)

O fenômeno de aceleração social, intimamente ligado a nossa modernização tecnológica e os sistemas políticos e sociais que adotamos, vem sendo alvo de questionamentos por parte da teoria crítica por diversos filósofos e sociólogos, principalmente em relação a se tal "aceleração" seja algo que, possa ser justificável pelo bem comum da sociedade. De fato, as rápidas mudanças que ocorreram no último século causaram uma tremenda mudança em nossos estilos-de-vida, e na maneira como experienciamos o mundo. Que a nossa sociedade mudou (...) e continua a mudar é um fato evidente quando olhamos criticamente para o passado e presente, e comparamos diferentes épocas da história humana. Neste ensaio tentaremos explorar algumas possíveis hipóteses que fundamentem o comportamento aceleracionista em certos fatores e mecanismo biológicos que caracterizam os sistemas de motivação e saciação humanos. Também tentaremos mostrar como certos fenômenos sociais podem auxiliar em fortalecer este tipo de comportamento, e suas possíveis origens evolutivas. Este estudo tem como objetivo principal fundamentar a Tese Aceleracionista em evidências neurofisiológicas, cognitivo-comportamentais, evolutivas e sociais. Palavras-chave: aceleração; recompensa; saciação; ciências cognitivas; teoria dos gêneros. (shrink)

The classification system was evaluated using benchmark phishing datasets, and the results demonstrated a significant improvement in detection accuracy and reduced false positives. The proposed model outperformed traditional machine learning algorithms, showing promise for real-world deployment in phishing detection systems. We conclude with suggestions for future improvements, such as incorporating more behavioral data and deploying the system in realtime monitoring applications.

The IPAP Schizophrenia Algorithm was originally designed in the form of a flow chart to help physicians optimise the treatment of schizophrenic patients. We examined the current version from the perspective of recent work on terminologies and ontologies thereby drawing on the resources of Basic Formal Ontology, and this with the objective to make the algorithm appropriate for Semantic Web applications. We found that Basic Formal Ontology is a rich enough theory to represent all the entities involved and that applying (...) the theory to the IPAP schizophrenia algorithm results in a representation that can be used by software agents to perform monitoring and control in a referent tracking environment. (shrink)

Exploring the intimate tie between body movement and space and time, Lee begins with the position that body movement generates space and time and explores the ethical implications of this responsibility for the situations one’s body movements generate. Whiteness theory has come to recognize the ethical responsibility for situations not of one’s own making and hence accountability for the results of more than one’s immediate personal conscious decisions. Because of our specific history, whites have developed a particular (...) embodiment and body movement that generates places that can only be characterized as more comfortable and more enabling to whites. (shrink)

Body checking, characterized by the repeated visual or physical inspection of particular parts of one’s own body (e.g. thighs, waist, or upper arms) is one of the most prominent behaviors associated with eating disorders, particularly Anorexia Nervosa (AN). In this paper, we explore the explanatory potential of the Recalcitrant Fear Model of AN (RFM) in relation to body checking. We argue that RFM, when combined with certain plausible auxiliary hypotheses about the cognitive and epistemic roles of emotions, (...) is able to explain key characteristics of body checking, including how body checking behavior becomes habitual and compulsive. (shrink)

A body schema is an agent's model of its own body that enables it to act on affordances in the environment. This paper presents a body schema system for the Learning Intelligent Decision Agent (LIDA) cognitive architecture. LIDA is a conceptual and computational implementation of Global Workspace Theory, also integrating other theories from neuroscience and psychology. This paper contends that the ‘body schema' should be split into three separate functions based on the functional role of consciousness (...) in Global Workspace Theory. There is (1) an online model of the agent's effectors and effector variables (Current Body Schema), (2) a long-term, recognitional storage of embodied capacities for action and affordances (Habitual Body Schema), and (3) "dorsal" stream information feeding directly from early perception to sensorimotor processes (Online Body Schema). This paper then discusses how the LIDA model of the body schema explains several experiments in psychology and ethology. (shrink)

This paper takes a new look at an old question: what is the human self? It offers a proposal for theorizing the self from an enactive perspective as an autonomous system that is constituted through interpersonal relations. It addresses a prevalent issue in the philosophy of cognitive science: the body-social problem. Embodied and social approaches to cognitive identity are in mutual tension. On the one hand, embodied cognitive science risks a new form of methodological individualism, implying a dichotomy not (...) between the outside world of objects and the brain-bound individual but rather between body-bound individuals and the outside social world. On the other hand, approaches that emphasize the constitutive relevance of social interaction processes for cognitive identity run the risk of losing the individual in the interaction dynamics and of downplaying the role of embodiment. This paper adopts a middle way and outlines an enactive approach to individuation that is neither individualistic nor disembodied but integrates both approaches. Elaborating on Jonas’ notion of needful freedom it outlines an enactive proposal to understanding the self as co-generated in interactions and relations with others. I argue that the human self is a social existence that is organized in terms of a back and forth between social distinction and participation processes. On this view, the body, rather than being identical with the social self, becomes its mediator. (shrink)

This chapter presents an account of Merleau-Ponty’s interpretation of the body schema as an operative intentionality that is not only opposed to, but also complexly intermingled with, the representation-like grasp of the world and one’s own body, or the body image. The chapter reconstructs Merleau-Ponty’s position primarily based on his preparatory notes for his 1953 lecture ‘The Sensible World and the World of Expression’. Here, Merleau-Ponty elaborates his earlier efforts to show that the body schema is (...) a perceptual ground against which the perceived world stands out as a complex of perceptual figures. The chapter clarifies how Merleau-Ponty’s renewed interpretation of the figure-ground structure makes it possible for him to describe the relationship between body schema and perceptual (body) image as a strictly systematic phenomenon. Subsequently, the chapter shows how Merleau-Ponty understands apraxia, sleep, and perceptual orientation as examples of dedifferentiation and subtler differentiation of the body-schematic system. The last section clarifies how such body-schematic differentiating processes give rise to relatively independent superstructures of vision and symbolic cognition which constitute our body image. It, moreover, explains how, according to Merleau-Ponty, the cognitive superstructures always need to be supported by praxic operative intentionality to maintain their full sense, even though, in some cases, they have the power to compensate for praxic deficiencies. (shrink)

This book investigates the concept of body shame and explores its significance when considering philosophical accounts of embodied subjectivity, providing phenomenological reflections on how the body is shaped by social forces.