Existence and uniqueness of tripled fixed points for mixed monotone operators with perturbations and application

In this article, we get the existence and uniqueness of tripled fixed points without assuming the operator to be compact or continuous, which extends the existing corresponding results. As applications, we utilize the results obtained in this paper to study the existence and uniqueness of positive solutions for a fractional differential equation boundary value problem.Publisher's Versio

Indoor Occupancy Detection Based on Environmental Data Using CNN-XGboost Model:Experimental Validation in a Residential Building

Indoor occupancy prediction can play a vital role in the energy-efficient operation of building engineering systems and maintaining satisfactory indoor climate conditions at the lowest possible energy use by operating these systems on the basis of occupancy data. Many methods have been proposed to predict occupancy in residential buildings according to different data types, e.g., digital cameras, motion sensors, and indoor climate sensors. Among these proposed methods, those with indoor climate data as input have received significant interest due to their less intrusive and cost-effective approach. This paper proposes a deep learning method called CNN-XGBoost to predict occupancy using indoor climate data and compares the performance of the proposed method with a range of supervised and unsupervised machine learning algorithms plus artificial neural network algorithms. The comparison is performed using mean absolute error, confusion matrix, and F1 score. Indoor climate data used in this work are CO2, relative humidity, and temperature measured by sensors for 13 days in December 2021. We used inexpensive sensors in different rooms of a residential building with a balanced mechanical ventilation system located in northwest Copenhagen, Denmark. The proposed algorithm consists of two parts: a convolutional neural network that learns the features of the input data and a scalable end-to-end tree-boosting classifier. The result indicates that CNN-XGBoost outperforms other algorithms in predicting occupancy levels in all rooms of the test building. In this experiment, we achieved the highest accuracy in occupancy detection using inexpensive indoor climate sensors in a mechanically ventilated residential building with minimum privacy invasion

Old Keys May Not Open New Doors: The Necessity of Agility in Cybersecurity Policymaking

The volatile and dynamic nature of cyberspace has raised concerns over security and organisations are trying to make policies to protect their digital assets. However, policymaking in this field is still using traditional methods, which are slow and incompatible with the pace of change in the environment. Thus, it is vital to increase the speed of policy development in an agile and flexible manner. The question is, what does agility mean here and why is it important for organisations? To answer these questions, this study uses a systematic literature review approach and investigates 42 selected papers. By analysing the selected papers, a definition of cybersecurity policymaking agility is provided, and its importance in combating new cyberthreats is discussed. Building on and extending the organisational agility, policymaking and cybersecurity management research streams, the findings of this study propose new research opportunities for future studies