Self Optimization

Die Praxis, den eigenen Körper und das eigene Leben mithilfe von digitalen Technologien aufzuzeichnen und zu analysieren, scheint insbesondere mit der Einführung von mobilen Alltagstechnologien wie Smartphones, Smartwatches und Fitnesstrackern rasant an Beliebtheit zu gewinnen. Diese Beliebtheit jedoch alleinig auf die technologische Realisierbarkeit zurückzuführen, muss im Anbetracht des breiten Konsenses um Theorien einer wechselseitigen Co-Production von Technologien und gesellschaftlichen Tatbeständen als antiquiert betrachtet werden. Diese Arbeit hat das Ziel, die Hintergründe der Beliebtheit von Selbstvermessungspraktiken zu ergründen und fokussiert sich dabei auf die zuvor genannten sozialen Tatbestände, um so die Bedeutungen der Technologie im Kontext des soziokulturellen Status quo in den deutschsprachigen Ländern des globalen Nordens nachvollziehen zu können. Dieser soziokulturelle Status quo lässt sich im besagten geografischen Kontext wohl am besten über die sozialwissen...

Food is essential for human survival. Some of the most crucial factors to think about are minimising food waste, optimising the supply chain, and enhancing food logistics, delivery, and safety. The achievement of these goals is greatly aided by the application of AI and ML. Proliferation of ever-more-powerful and pervasive computer networks has enabled modern logistical and industrial systems. Within these networks, there is a continual influx of fresh data from many sources, generated by sensors, equipment, systems, intelligent devices, and humans. Thanks to computers' ever-improving capabilities, we can now analyse Big Data more quickly, thoroughly, and in-depth than ever before. These developments have rejuvenated and ushered in a new era called Industry 4.0 or the Smart Factory, which has increased the importance of artificial information technology (AI). Machine learning and artificial intelligence are discussed in this article within the context of the food industry and business. Important uses of this technique include supply chain optimisation, crop selection, logistics, food distribution, and processing plant predicting maintenance.

This paper presents the Self-Optimization Principle (SOP) as a comprehensive framework for understanding complex systems across disciplines, including biology, artificial intelligence, materials science, and social sciences. Rooted in the foundational axioms of fractality, balance, evolution, and tolerance, the SOP elucidates the mechanisms that drive system emergence, adaptability, and resilience. By integrating the paradox of equivalence and examples from plasma-organic systems, we highlight the universality of these principles in linking diverse domains. Case studies demonstrate SOP's applications in AI development, advanced material design, and social dynamics, offering actionable insights for innovation and sustainability.

This paper presents an analysis of technologically mediated self-relations that materi- alise in the use of self-tracking (ST) devices and data to monitor and track one’s bodily, emotional, habitual, or productivity-related aspects. Based on ethnographical research and postphenomenological framing, two analytical concepts are employed: self-care and self-control. While seemingly op- posed, both simultaneously appear and co-exist in ST practices that trans- cend mere self-optimisation. The dialectic interplay between self-control and self-care provides uncertainty-reducing confirmation of prior hunches, emotionally relieving reminders and algorithmic recommendations, de- tailed data that might be helpful in the future for pattern recognition or treatments, and an orientation that offers safety with regard to current and future decisions. Self-tracking technologies can be seen as assisting self- and life-regulation that can ultimately support personal balance and har- mony. The article contributes theoretically to ST literature by extending the concept of self-optimisation to include the balancing of needs and desires between self-responsibility and gratification, goal-tracking and self- affirmation, discipline and letting go.

The Autonomic Computing paradigm was first presented almost 15 years ago as a 20-30 year long research agenda. Organizations like NASA have explored the possibilities of an autonomic system along with the biologically inspired Swarm and Agents approaches. These Systems are unfolding circumstances rather than preconceived scenarios. This paper focuses on the aspect of the Autonomic System, were, adaptive self-optimization are explored using an intelligent machine model layers such as Reaction, Routine and Reflection. In the experimentation, a Pioneer P3-DX Robot is used to simulate a Planetary Rover. The Pioneer Robot has been the subject of hardware faultingin the case Wheel Integrity. Using the Microsoft Robotics Developer Studio (MRDS) and Microsoft SQL Server, a framework has been developed, that records the Pioneer Robot's sensor data before and after hardware faulting. The Autonomic system elements, such as self-adaptive and self-optimizing are used to process the data. The Reaction, Routine and Reflection responses are determined at the appropriate response rates from the evaluation of these and form part of the self-healing, selfconfiguring, self-optimizing and self-protecting strategy to enable the Robot to continue to function, even with hardware issues such as a faulty wheel.

NASA, ESA, and NSSC space agencies have plans to put planetary rovers on Mars in 2020. For these future planetary rovers to succeed, they will heavily depend on sensors to detect obstacles. This will also become of vital importance in the future, if rovers become less dependent on commands received from earthbased control and more dependent on self-configuration and selfdecision making. These planetary rovers will face harsh environments and the possibility of hardware failure is high, as seen in missions from the past. In this paper, we focus on using Autonomic principles where self-healing, self-optimization, and selfadaption are explored using the MAPE-K model and expanding this model to encapsulate the attributes such as Awareness, Analysis, and Adjustment (AAA-3). In the experimentation, a Pioneer P3-DX research robot is used to simulate a planetary rover. The sonar sensors on the P3-DX robot are used to simulate the sensors on a planetary rover (even though in reality, sonar sensors cannot operate in a vacuum). Experiments using the P3-DX robot focus on how our software system can be adapted with the loss of sonar sensor functionality. The autonomic manager system is responsible for the decision making on how to make use of remaining 'enabled' sonars sensors to compensate for those sonar sensors that are 'disabled'. The key to this research is that the robot can still detect objects even with reduced sonar sensor capability.

CrossFit is one of the fastest growing fitness phenomena of the last decade. Considered the largest fitness business today, CrossFit's widespread popularity has attracted increasing interest from a variety of disciplines. Despite this burgeoning scholarly attention, few analyses have focused on examining CrossFit's discourse of self-optimization and the role it plays in shaping the ideal image of the CrossFitter. The present paper addresses this question by examining the popular literature on CrossFit using a Critical Discourse Approach (CDA). Findings reveal CrossFit's understanding of self-optimization as a polyhedral and demanding process that goes beyond physical discipline to encompass all facets of the self. Five main themes of self-optimization are identified in the popular CrossFit literature: 1) failure and weakness, 2) pain and constant preparedness, 3) integral selfwork and passionate commitment, 4) constant self-improvement, and 5) community support. Drawing on previous research on the topic, the paper also reflects on the relationship between CrossFit and neoliberalism, suggesting CrossFit as a fertile ground for the humanities and social sciences to further explore the intersections between the fields of health, sport, selfoptimization, and identity.

T.S. Eliot's 1915 poem 'The Love Song of J. Alfred Prufrock' repeatedly registers the need to self-optimize in response to provocations. Yet, the narrator is never able to respond to them in a way that would either improve his personal standing or bring him favorable social recognition. As he never denies the need to improve, the inability transitions into disinterest in the question of improvement itself. This essay argues that the narrator's (in) ability to support or oppose self-optimization in 'Prufrock' indicates a liminal position with respect to the problem, a position in which the self is impassive, indifferent, and perhaps even bored. However, even as this configuration of (in)capacity leading to disinterest is repeatedly brought forth in the poem, it cannot be taken to be ineffectual and pointless. Rather, the apparently endless iteration of the arrangement brings about new possibilities for the imagination of the self--possibilities of the self 's coexistence with contingencies of time, space, and expression.

This is the first part of a two-part paper on the design of intelligent controllers for a class of exercise machines. The control objective is to cause the user to exercise in a manner which optimizes a criterion related to the user's mechanical power. The optimal exercise strategy is determined by a biomechanical behavior of the individual user, which is assumed to satisfy an affine force-velocity relationship dependent on the body geometric configuration. Consequently, the control scheme must simultaneously: 1) identify the user's biomechanical behavior; 2) optimize the controller; and 3) stabilize the system to the estimated optimal states. Moreover, to ensure that the exercise machine is safe to operate, the control system guarantees that the interaction between the exercise machine and the user is passive. In this first part of the paper, we formulate the control problem and propose a controller structure which satisfies the safety requirement and is capable of causing the user to execute an arbitrary exercise strategy if the user's biomechanical behavior is known. The controller is of the form of a dynamic damper and can be implemented using only passive mechanical components. Part II of this paper is concerned with the self-optimization problem, in which both the determination of the optimal exercise strategy and the execution of that strategy, when the user's biomechanical behavior is unknown, must be considered.

Der Erfolg von Kondō Maries Aufräummethoden hängt mit der geschickten Vermarktung von vermeintlich japanischer Spiritualität zusammen. Diese wird sowohl durch die Plättung spezifischer kultureller Praxen in der englischen Übersetzung von Kondōs Buch "The Life-Changing Magic of Tidying Up", als auch von dem von Kondō betriebenen Branding im Westen unterstützt. Diese Hausarbeit streift dabei auch das Missverständnis von religiös-kultureller Alltagspraxis, dem nichtjapanische Beobachter oft aufgesessen sind.

In the ever-evolving landscape of technology, the imperative for adaptive and selfoptimizing systems has become increasingly evident. This research endeavors to probe the intricate intersection of artificial intelligence, machine learning, and automation, specifically within the realm of platform engineering. By addressing the necessity for intelligent automation platforms capable of dynamic adaptation and self-optimization, this paper aims to elucidate their role in navigating the complexities of contemporary systems. Through an exploration of challenges, opportunities, and recent advancements, the research endeavors to offer a nuanced understanding of the pivotal role played by dynamic adaptation and self-optimization in shaping the trajectory of automation platforms. In this paper, we embark on a journey to investigate the multifaceted dimensions of dynamic adaptation and self-optimization, critically analyzing their implications for continuous improvement. With the pervasive integration of automation in diverse industries, conventional static approaches prove insufficient to contend with the dynamic and unpredictable nature of contemporary environments. The conceptualization of dynamic adaptation and self-optimization emerges as a crucial paradigm shift, signifying a departure from static frameworks towards intelligent systems that can not only react to changes but also autonomously enhance their efficiency over time. As the paper unfolds, the myriad challenges and opportunities associated with dynamic adaptation and self-optimization in platform automation are meticulously explored. Challenges span from the intricacies of managing real-time data to ensuring the stability of systems, with ethical considerations looming large. Simultaneously, opportunities manifest in the form of heightened efficiency, reduced downtime, and increased adaptability to unforeseen circumstances. This section provides a comprehensive examination of the intricate balance required to harness the potential benefits while mitigating the challenges posed by the integration of intelligent systems into automation platforms.

Psychische Krankheiten in Fernsehserien der letzten 15 Jahre sind häufig hochfunktional: Sie verleihen den Figuren spezielle Begabungen, mit deren Hilfe sie Konflikte effizienter lösen als ihr Umfeld. Dieser Beitrag untersucht anhand von drei exemplarischen Serien-Dexter, Mr. Robot und Homeland-, welche gesellschaftlichen Vorstellungen sich in dieser positiven Konnotation spiegeln. Die Analyse stellt dabei den Begriff der "Produktivität" in den Fokus. Ausgehend von Thomas Elsaessers Überlegungen zu mindgame movies und produktiven Pathologien analysiert der Aufsatz die ästhetische Produktivität der psychischen Krankheit. Darüber hinaus lassen sich die Darstellungen im Sinne einer Selbstoptimierung als symptomatisch für eine zeitgenössische Leistungsgesellschaft lesen. Psychische Krankheiten sind hier nicht nur Begabung, sondern persönliche Leistung der Figuren. _______ Melanie Mika (M.A.) ist Doktorandin am Institut für Theater-, Film-und Medienwissenschaft der Goethe-Universität Frankfurt am Main. Sie studierte Musik-und Medienwissenschaft in Tübingen sowie Film und audiovisuelle Medien in Frankfurt, Montreal und Amsterdam. Seit 2019 ist sie Lehrbeauftragte am Institut für Medienwissenschaft der Universität Tübingen. Zu ihren Forschungsschwerpunkten gehören Film-und Figurentheorie sowie mediale Repräsentationen von psychischen Krankheiten.

In dense wireless networks, inter-cell interference highly limits the capacity and quality of service perceived by users. Previous work has shown that approaches based on frequency reuse provide important capacity gains. We model a wireless network with Inter-Cell Interference Coordination (ICIC) at the flow level where users arrive and depart dynamically, in order to optimize quality of service indicators perceivable by users such as file transfer time for elastic traffic. We propose an algorithm to tune the parameters of ICIC schemes automatically based on measurements. The convergence of the algorithm to a local optimum is proven, and a heuristic to improve its convergence speed is given. Numerical experiments show that the distance between local optima and the global optimum is very small, and that the algorithm is fast enough to track changes in traffic on the time scale of hours. The proposed algorithm can be implemented in a distributed way with very small signaling load.

We propose in this paper an enhanced Inter Cell Interference Coordination (ICIC) mechanism based on Multi Armed Bandit (MAB) approach that aims at maximizing not only the throughputs of the attached users but also their HandOver (HO) performances evaluated through 3GPP Mobility Robustness Optimization (MRO) indicators. To this end, the MAB procedure explicitly takes into account the HO performances to configure the optimal spectrum split. The simulation results highlight the benefits of the proposed solution: higher throughputs and reduced HO failures. This is particularly the case, for high and medium speed users for which HO performances are more sensitive to interference.

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.

The recent development of Big Data, Internet of Things (IoT) and 5G network technology offers a plethora of opportunities to the IT industry and mobile network operators. 5G cellular technology promises to offer connectivity to massive numbers of IoT devices while meeting low-latency data transmission requirements. A deficiency of the current 4G networks is that the data from IoT devices and mobile nodes are merely passed on to the cloud and the communication infrastructure does not play a part in data analysis. Instead of only passing data on to the cloud, the system could also contribute to data analysis and decision-making. In this work, a Big Data driven self-optimized 5G network design is proposed using the knowledge of emerging technologies CRAN, NVF and SDN. Also, some technical impediments in 5G network optimization are discussed. A case study is presented to demonstrate the assistance of Big Data in solving the resource allocation problem.

In Web Services designs classical optimization techniques are not applicable. A possible solution to guarantee critical requirements is the use of an autonomic architecture, able to autoconfigure and to auto-tune. This study presents MAWeS (MetaPL/HeSSE Autonomic Web Services), a framework whose aim is to support the development of self-optimizing predictive autonomic systems for Web service architectures. It adopts a simulation-based methodology, which allows to predict system performance in different status and load conditions. The predicted results are used for a feedforward control of the system, which self-tunes before the new conditions and the subsequent performance losses are actually observed.

Fifth-generation (5G) cellular wireless networks are envisioned to predispose service-oriented, flexible, and spectrum/energy-efficient edge-to-core infrastructure, aiming to offer diverse smart-X (city, grid, and phones) applications. Convergence of software-defined networking (SDN), software-defined radio (SDR) compatible with multiple radio access technologies (RATs), and virtualization on the concept of 5G software-defined wireless networking (5G-SDWN) is a promising approach to provide such a dynamic network. The principal technique behind the 5G-SDWN framework is the separation of the control and data planes, from the deep core entities to edge wireless access points (APs). This separation allows the abstraction of resources as transmission parameters of each user over the 5G-SDWN. Similar to traditional wireless networks, in this user-centric, service-oriented and integrated environment, resource management plays a critical role to achieve efficiency and reliability. However, it is natural to wonder if 5G-SDWN can be leveraged to enable converged multi-layer (CML) resource management over the portfolio of resources, and reciprocally, if CML resource management can effectively provide performance enhancement and reliability for 5G-SDWN. We believe that replying to these questions and investigating this mutual synergy are not trivial, but multidimensional and complex for 5G-SDWN, which consists of different technologies and also inherits legacy generations of wireless networks. In this paper, we propose a flexible protocol structure based on three mentioned pillars for 5G-SDWN, which can handle all the required functionalities in a more crosslayer manner compared to the legacy wireless networks (2G, 3G and 4G). Based on this, we demonstrate how the general framework of CML resource management can control the enduser quality of experience. For two scenarios of 5G-SDWN, including both macro-cells and small-cells, we investigate the effects of joint user-association and resource allocation via CML resource management to improve performance in a virtualized network.

This paper is the review of Self organization in future mobile network. As for now self organization is being applied to autonomic computer, or wireless network but presently self organization in mobile network is the emerging field with lot of research direction in various field related to mobile communication. In this paper a brief introduction of the term self organization and SON is presented. Also paper contains the weakness of existing system with increasing complexity. Key objectives for the deployment of self organization in system are to ensure excellent coverage and capacity with reduced interference. Deployment of SON also reduces capital operating expenditure as it eliminates the need of skilled labour. SON is mainly classified in three type’s viz. self configuration, self optimization and self healing which covers almost all parameters and function related to mobile communication. Lastly it concludes with few research directions and the areas which need more research wo...

Fifth-generation (5G) cellular wireless networks are envisioned to predispose service-oriented, flexible, and spectrum/energy-efficient edge-to-core infrastructure, aiming to offer diverse smart-X (city, grid, and phones) applications. Convergence of software-defined networking (SDN), software-defined radio (SDR) compatible with multiple radio access technologies (RATs), and virtualization on the concept of 5G software-defined wireless networking (5G-SDWN) is a promising approach to provide such a dynamic network. The principal technique behind the 5G-SDWN framework is the separation of the control and data planes, from the deep core entities to edge wireless access points (APs). This separation allows the abstraction of resources as transmission parameters of each user over the 5G-SDWN. Similar to traditional wireless networks, in this user-centric, service-oriented and integrated environment, resource management plays a critical role to achieve efficiency and reliability. However, it is natural to wonder if 5G-SDWN can be leveraged to enable converged multi-layer (CML) resource management over the portfolio of resources, and reciprocally, if CML resource management can effectively provide performance enhancement and reliability for 5G-SDWN. We believe that replying to these questions and investigating this mutual synergy are not trivial, but multidimensional and complex for 5G-SDWN, which consists of different technologies and also inherits legacy generations of wireless networks. In this paper, we propose a flexible protocol structure based on three mentioned pillars for 5G-SDWN, which can handle all the required functionalities in a more crosslayer manner compared to the legacy wireless networks (2G, 3G and 4G). Based on this, we demonstrate how the general framework of CML resource management can control the enduser quality of experience. For two scenarios of 5G-SDWN, including both macro-cells and small-cells, we investigate the effects of joint user-association and resource allocation via CML resource management to improve performance in a virtualized network.

The recent development of Big Data, Internet of Things (IoT) and 5G network technology offers a plethora of opportunities to the IT industry and mobile network operators. 5G cellular technology promises to offer connectivity to massive numbers of IoT devices while meeting low-latency data transmission requirements. A deficiency of the current 4G networks is that the data from IoT devices and mobile nodes are merely passed on to the cloud and the communication infrastructure does not play a part in data analysis. Instead of only passing data on to the cloud, the system could also contribute to data analysis and decision-making. In this work, a Big Data driven self-optimized 5G network design is proposed using the knowledge of emerging technologies CRAN, NVF and SDN. Also, some technical impediments in 5G network optimization are discussed. A case study is presented to demonstrate the assistance of Big Data in solving the resource allocation problem.

Psychische Krankheiten in Fernsehserien der letzten 15 Jahre sind häufig hochfunktional: Sie verleihen den Figuren spezielle Begabungen, mit deren Hilfe sie Konflikte effizienter lösen als ihr Umfeld. Dieser Beitrag untersucht anhand von drei exemplarischen Serien – Dexter, Mr. Robot und Homeland –, welche gesellschaftlichen Vorstellungen sich in dieser positiven Konnotation spiegeln. Die Analyse stellt dabei den Begriff der "Produktivität" in den Fokus. Ausgehend von Thomas Elsaessers Überlegungen zu mindgame movies und produktiven Pathologien analysiert der Aufsatz die ästhetische Produktivität der psychischen Krankheit. Darüber hinaus lassen sich die Darstellungen im Sinne einer Selbstoptimierung als symptomatisch für eine zeitgenössische Leistungsgesellschaft lesen. Psychische Krankheiten sind hier nicht nur Begabung, sondern persönliche Leistung der Figuren.

This paper is the review of Self organization in future mobile network. As for now self organization is being applied to autonomic computer, or wireless network but presently self organization in mobile network is the emerging field with lot of research direction in various field related to mobile communication. In this paper a brief introduction of the term self organization and SON is presented. Also paper contains the weakness of existing system with increasing complexity. Key objectives for the deployment of self organization in system are to ensure excellent coverage and capacity with reduced interference. Deployment of SON also reduces capital operating expenditure as it eliminates the need of skilled labour. SON is mainly classified in three type’s viz. self configuration, self optimization and self healing which covers almost all parameters and function related to mobile communication. Lastly it concludes with few research directions and the areas which need more research wo...

Formal verification techniques need to deal with the complexity of the systems being verified. Most often, this problem is solved by taking an abstract model of the system and aiming at a complete verification of an approximation of the system. This paper proposes a complementary verification approach, in which the approximation is introduced into the verification algorithm, instead of the system model: we achieve an approximate verification of a fair~y complete and detailed system model. The proposed technique relies on coupling a Genetic Algorithm with a simulator of the system under verification, and is especially suited for verifying performance-related aspects. To prove the effectiveness of our approach, we applied it to the quantitative verification of a network protocol: the TCP protocol operating on a given network. A Genetic Algorithm is able to find a configuration of the traffic over the network that sensitizes a critical problem in the TCP protocol that would be difficult to find both with exact techniques and stochastic ones.

The field of wireless sensor network (WSN) is an important and challenging research area today. Advancements in sensor networks enable a wide range of environmental monitoring and object tracking applications. Secure routing in sensor networks is a difficult problem due to the resources limitations in WSN. Moreover, multihop routing in WSN is affected by new nodes constantly entering/leaving the system. Therefore, biologically inspired algorithms are reviewed and enhanced to tackle problems arise in WSN. Ant routing and human security has shown an excellent performance for sensor networks. Certain parameters like energy level, link quality, lose rate are considered while making decisions. These decisions will come up with the optimal route and also to take best action against the security attacks. In this paper, the design and initial work on biological-inspired self-organized secure autonomous routing algorithm for sensor networks are presented. The proposed bio-inspired algorithm will also meet the enhanced sensor network requirements, including energy consumption, success rate and time delay.

Abstract—The field of wireless sensor network (WSN) is an important and challenging research area today. Advancements in sensor networks enable a wide range of environmental monitoring and object tracking applications. Secure routing in sensor networks is a difficult problem ...

Psychische Krankheiten in Fernsehserien der letzten 15 Jahre sind häufig hochfunktional: Sie verleihen den Figuren spezielle Begabungen, mit deren Hilfe sie Konflikte effizienter lösen als ihr Umfeld. Dieser Beitrag untersucht anhand von drei exemplarischen Serien-Dexter, Mr. Robot und Homeland-, welche gesellschaftlichen Vorstellungen sich in dieser positiven Konnotation spiegeln. Die Analyse stellt dabei den Begriff der "Produktivität" in den Fokus. Ausgehend von Thomas Elsaessers Überlegungen zu mindgame movies und produktiven Pathologien analysiert der Aufsatz die ästhetische Produktivität der psychischen Krankheit. Darüber hinaus lassen sich die Darstellungen im Sinne einer Selbstoptimierung als symptomatisch für eine zeitgenössische Leistungsgesellschaft lesen. Psychische Krankheiten sind hier nicht nur Begabung, sondern persönliche Leistung der Figuren. _______ Melanie Mika (M.A.) ist Doktorandin am Institut für Theater-, Film-und Medienwissenschaft der Goethe-Universität Frankfurt am Main. Sie studierte Musik-und Medienwissenschaft in Tübingen sowie Film und audiovisuelle Medien in Frankfurt, Montreal und Amsterdam. Seit 2019 ist sie Lehrbeauftragte am Institut für Medienwissenschaft der Universität Tübingen. Zu ihren Forschungsschwerpunkten gehören Film-und Figurentheorie sowie mediale Repräsentationen von psychischen Krankheiten.

Anna Heitger, BA, born 1992 in Washington, D.C., raised in Austria, studying Cultural and Social Anthropology at the University of Vienna since 2012, currently in the Master program. I aim to write from the intersection of Anthropology and STS, with theoretical frameworks of practice theory, feminist and posthuman theories, and a special interest in affectivity and the role of emotions and affects in the practices we engage in. Investigating self-tracking technologies allows me to bring together these fields of interests within a particular kind of assemblage of human body and technological device.

The aim of this paper is to analyse the metaphors and ideologies of optimization which is being prevalently used in descriptions of goals of people using self tracking devices or apps (Ruckenstein 2014, Schüll 016).
Optimization was originally a concept used within computer science, engineering, physics, chemistry and public management. Increasingly, however, the term has entered everyday life as a mode of being or a strategy of „making the most“ of life, on a physical, economic, social, mental and spiritual level. It is also associated with a surge of new technologies as medical enhancements, cosmetic surgery, meditation wearables, dietary fashions, as well as a variety of technological devices for tracking and monitoring the self ....