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The purpose of this paper is to propose a simple, fast, and effective method for detecting measurement errors in data collected with low-cost environmental sensors…
The purpose of this paper is to propose a simple, fast, and effective method for detecting measurement errors in data collected with low-cost environmental sensors typically used in building monitoring, evaluation, and automation applications.
The method combines two unsupervised learning techniques: a distance-based anomaly detection algorithm analyzing temporal patterns in data, and a density-based algorithm comparing data across different spatially related sensors.
Results of tests using 60,000 observations of temperature and humidity collected from 20 sensors during three weeks show that the method effectively identified measurement errors and was not affected by valid unusual events. Precision, recall, and accuracy were 0.999 or higher for all cases tested.
The method is simple to implement, computationally inexpensive, and fast enough to be used in real-time with modest open-source microprocessors and a wide variety of environmental sensors. It is a robust and convenient approach for overcoming the hardware constraints of low-cost sensors, allowing users to improve the quality of collected data at almost no additional cost and effort.
Executives are challenged every day to make important decisions that affect the performance of their business enterprises and, as a result, the success of their own…
Executives are challenged every day to make important decisions that affect the performance of their business enterprises and, as a result, the success of their own careers. Based on that scenario, one cannot expect that only the rational approach works like a panacea for all managerial problems. This paper aims to propose that the best solution tends to embrace a complementary or integrated decision‐making approach.
The paper seeks to demonstrate that the convergence between rational and non‐rational decision‐making processes can be optimized by integrating several religious tenets.
The paper finds strong evidence that a religion‐based framework might enrich the sensitive topic of decision‐making processes in organizations.
Overall, the paper strives to show that intuition and prayer are two faces of the same coin, and argues that both forms of decision processes (e.g. rational and non‐rational analysis) might coexist perfectly in an integrative frame.
The article proposes prayer as a transcendent coping mechanism whereby executives might refine their intuition flux. As a result, it depicts a conceptual framework encapsulating all those constructs.