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Institute
Dynamic Real-Time Range Queries (DRRQ) are widely used to discover local context between mobile clients in high-density areas where both clients requested by the query and inquirers are mobile. Unlike the very well-known continuous range queries only a few approaches such as Adaptive Quad Streaming (AQS) address scalability and real-time requirements that are important for ad-hoc mobility challenges in fully distributed client networks. In this paper we address fundamental limitations of AQS presenting the new lightweight AQSdynamic which supports arbitrary, individual, and time-dependent range query shapes instead of fixed circular ones, thus covering much more realistic scenarios. More important, AQSdynamic combines the decentralized streaming approach of AQS with "subscriptions"guaranteeing a real-time behavior with constant complexity with to the number of clients.
Stress management is becoming increasingly important in our society. It is evident that stress, whether measured subjectively or physiologically, has a detrimental effect on decision-making abilities and significantly impacts an individual's health and well-being, as well as the private and public economy. While technological advances simplify our daily lives, managing stress is more challenging than ever due to individual perceptions, cultural nuances, and personality traits. The need to respond quickly to workplace challenges, traffic, and the drive to achieve more is making chronic stress more prevalent, underscoring the importance of understanding, measuring, and predicting stress. In this work, stress is defined as the body's response to a stressor. Stressors can be either short-term or long-term, causing the body to function differently than it should, but also helping it respond to and cope with situations. Common ways of measuring stress include two main approaches: the classic method using questionnaires or direct conversations, and the use of physiological signals. In this research, we used questionnaires and heart rate characteristics to determine baseline stress levels, compared stress with physical activity, and studied the relationship between stress, personality traits, and demographics of the participants. It is important to remember that stress cannot be entirely avoided in our lives. Stress optimizes bodily functions and assists in coping with dangerous or challenging situations. However, it is possible to develop a system that helps us understand and detect stress more efficiently, thereby avoiding dangerous or hazardous situations. This could lead to significant improvements in sectors where errors are costly or can influence health. By doing so, a better understanding, better management, and a reduction of the negative long-term effects of stress can be achieved.
The Hadamard product of two matrices of the same order is obtained by entry-wise multiplication of their coefficients. In a similar way, the Hadamard power of a matrix and a polynomial is formed by real powers of their coefficients. Results for the Hadamard product of some important classes of matrices, e.g., positive definite matrices, conditionally negative definite matrices, and matrices with one positive eigenvalue are presented. The results are extended to give sufficient conditions for symmetric matrices to have exactly one positive eigenvalue. A Hurwitz (or stable) polynomial is a real polynomial whose roots are located in the open left half of the complex plane. Results for the Hadamard square root of Hurwitz polynomials of degree five are given. Also, a type of Oppenheim's inequality for Hurwitz matrices is presented. Finally, interval matrices, i.e., matrices with intervals as entries are studied, and new results for the interval property of several classes of matrices, e.g., inverse M-matrices, conditionally positive (negative) semidefinite matrices, and infinitely divisible matrices are given.
In this study, we quantify and compare the energy saving potential of intelligent thermostats in a seminar room under five different scenarios using a combination of thermal simulations and measurements. Coupling the thermostats to occupancy and window contact sensors results to be the most effective installation to maximize energy savings under minimal loss of comfort by lower temperatures.
The proliferation of the Internet of Things (IoT) has enriched modern life, but their increasing ubiquity raises concerns about environmental impact. To address this, comprehensive Life Cycle Assessments (LCAs) of IoT products, which have historically been manual, costly, and time-consuming, are vital. Noting the recurring nature of core components in IoT devices, such as CPUs and sensors, we propose to use graphs and machine learning to simplify and scale LCA estimations for IoT products. This paper introduces a novel approach to representing IoT devices as graphs with specific component characteristics and interconnections. Applied to a preliminary dataset of smart home IoT devices, the methodology unveils insights into structural similarities using a composite kernel approach. This initial phase lays the groundwork for the machine learning component. The integration of machine learning planned as part of ongoing research, provides a pathway for efficient and timely ecological assessments, ensuring that the rapid growth of IoT aligns with sustainable practices.
Flowculate ist eine Software zur Simulation der Bewegung von Personenströmen und der damit verbundenen Ausbreitung von Infektionskrankheiten. Um die Software verwenden zu können, müssen die Polygone eines gegebenen Grundrisses zunächst durch manuelle Nachzeichnung aller Wände extrahiert werden, ein Prozess, der sowohl fehleranfällig als auch zeitaufwändig ist. Diese Arbeit untersucht, ob das CNN-Modell CubiCasa, das speziell für die Extraktion von Polygonzügen auf Grundrissen trainiert wurde, diesen Schritt automatisieren kann. Dazu wurde die Modellvorhersage in das von Flowculate benötigte JSON-Format umgewandelt und in der Software dargestellt. Die Ergebnisse der Studie, die manuell erstellte Zeichnungen der Teilnehmenden mit den durch CubiCasa generierten vergleicht, verdeutlichen das Potenzial der automatisierten Extraktion mithilfe eines CNN-Modells. Das Modell übertrifft die Teilnehmenden sowohl in Bezug auf Präzision als auch auf Geschwindigkeit deutlich.
Digitalization requires organizations to strategically invest in information technology (IT). As a result, the costs associated with IT in companies are rising and technological progress changes the setting for IT management. This poses challenges for IT managers to ensure spend-efficiency and manage IT costs transparently. However, no current literature review gives an overview of how IT cost management (ITCM) research dealt with past transformations. This paper aims to investigate ITCM concepts considering their historical context. It then derives implications for the digital age and identifies future research fields. The historical literature review reveals that ITCM research evolved with technological advances and the target to manage all IT-related costs and evaluate the impact of IT spend. However, the presented concepts lack consideration of current changes that hamper spend-efficiency and strategic decisions. Hence, this paper enables future research to address the identified research gaps. Additionally, practitioners gain awareness of how they can benefit from developed ITCM concepts.
