Search results for "Black box"
showing 10 items of 26 documents
Application of Selected Methods of Black Box for Modelling the Settleability Process in Wastewater Treatment Plant
2017
Abstract The paper described how the results of measurements of inflow wastewater temperature in the chamber, a degree of external and internal recirculation in the biological-mechanical wastewater treatment plant (WWTP) in Cedzyna near Kielce, Poland, were used to make predictions of settleability of activated sludge. Three methods, namely: multivariate adaptive regression splines (MARS), random forests (RF) and modified random forests (RF + SOM) were employed to compute activated sludge settleability. The results of analysis indicate that modified random forests demonstrate the best predictive abilities.
Power losses in power-split CVTs: A fast black-box approximate method
2018
Abstract This paper addresses the mechanical losses of planetary transmissions, with particular attention to power-split CVTs in their hybrid electric versions. It provides unified layout-independent analytical relationships, which can be used for both analysis, design and control purposes, and a simplified approach; the latter overcomes the necessity to segment the operating range of the power-split CVT in order to keep its loss model physically consistent. An example of application to a real hybrid electric PS-CVT is performed to show the simplicity, accuracy and generality of the proposed method.
Providing a general framework about spin-off success factors in complex environments
2018
Spin-off organisations are the main vehicle for knowledge transfer from universities and/or high educational institutions (HEIs) to the economic system. Spin-off firms are complex phenomenon which requires particular conditions to its creation, survival and development. In the last decade, the scientific debate recognised the importance and the role of spin-off organisations, but the main factors and actors that impact on their creation, survival and development are not always clear. This paper aims to fill this gap, shedding light on this black box. In a first step, this research will identify the main 'success factors' for creation of spin-offs. In the second step, the relationship betwee…
Explaining Individual and Collective Programming Students’ Behavior by Interpreting a Black-Box Predictive Model
2021
Predicting student performance as early as possible and analysing to which extent initial student behaviour could lead to failure or success is critical in introductory programming (CS1) courses, for allowing prompt intervention in a move towards alleviating their high failure rate. However, in CS1 performance prediction, there is a serious lack of studies that interpret the predictive model’s decisions. In this sense, we designed a long-term study using very fine-grained log-data of 2056 students, collected from the first two weeks of CS1 courses. We extract features that measure how students deal with deadlines, how they fix errors, how much time they spend programming, and so forth. Subs…
Computing the Cell
2015
Here I call for the need to revisit cell theory. The idea that the cell is the basic unit of life is well-known and foundational to Biology, but it has not received sufficient attention. We have increasingly detailed knowledge of the intracellular world and all its components, but these are often considered independently. On the other hand, there is excessive theorising about the cell on the basis of its being a black box. The time is ripe to formulate an integrative cell theory .
Combining conjunctive rule extraction with diffusion maps for network intrusion detection
2013
Network security and intrusion detection are important in the modern world where communication happens via information networks. Traditional signature-based intrusion detection methods cannot find previously unknown attacks. On the other hand, algorithms used for anomaly detection often have black box qualities that are difficult to understand for people who are not algorithm experts. Rule extraction methods create interpretable rule sets that act as classifiers. They have mostly been combined with already labeled data sets. This paper aims to combine unsupervised anomaly detection with rule extraction techniques to create an online anomaly detection framework. Unsupervised anomaly detectio…
Experimental System Identification and Black Box Modeling of Hydraulic Directional Control Valve
2015
Directional control valves play a large role in most hydraulic systems. When modeling the hydraulic systems, it is important that both the steady state and dynamic characteristics of the valves are modeled correctly to reproduce the dynamic characteristics of the entire system. In this paper, a proportional valve (Brevini HPV 41) is investigated to identify its dynamic and steady state characteristics. The steady state characteristics are identified by experimental flow curves. The dynamics are determined through frequency response analysis and identified using several transfer functions. The paper also presents a simulation model of the valve describing both steady state and dynamic charac…
Building energy performance forecasting: A multiple linear regression approach
2019
Abstract Different ways to evaluate the building energy balance can be found in literature, including comprehensive techniques, statistical and machine-learning methods and hybrid approaches. The identification of the most suitable approach is important to accelerate the preliminary energy assessment. In the first category, several numerical methods have been developed and implemented in specialised software using different mathematical languages. However, these tools require an expert user and a model calibration. The authors, in order to overcome these limitations, have developed an alternative, reliable linear regression model to determine building energy needs. Starting from a detailed …
Co-Evolutionary Coupling via a Digital-bio Ecosystem – A Suggestion for a New R&D Model in the Digital Economy
2019
A solution to the critical problem of a dilemma between R&D expansion and productivity decline that a majority of information and communication technology (ICT) leaders have been confronting in the digital economy is expected. It can be expected by a spinoff from economic functionality-seeking GDP-based coevolution cycle to supra-functionality beyond an economic value-seeking uncaptured GDP-driven coevolution cycle. However, the transformation dynamism remains a black box. By means of numerical simulations based on empirical analyses of the development trajectories of global ICT leaders, focusing on Amazon and Finland, together with an intensive review of preceding analyses, this paper atte…
A local linear black-box identification technique for power converters modeling
2009
In this paper, a black-box modeling technique for power electronic converters, also used in automotive environment is presented. The aim of this work is to provide a simple yet versatile and powerful tool to schematize complex electric devices in vehicular appliances, in order to fulfill the electromagnetic compatibility already during the project stage. By using input and output measured data, a composite local linear state space model is built up. Radial basis functions are used as weights for the local systems. The proposed approach is validated and applied in modeling a DC/DC converter for DC motors, a pulse width modulation inverter and a controlled rectifier.