Assessment of Mould Growth on Building Materials using Spatial and Frequency Domain Analysis Techniques

The phenomenon of Sick Building Syndrome (SBS), Building Related Illness (BRI) and some other indoor related diseases have been attributed to mould and fungi exposure in the indoor environment. Despite the growing concern over mould and fungi infestations on building materials, little has been reported in the literature on the development of an objective tool and criteria for measuring and characterizing the shape and the level of severity of such parasitic phenomenon. In this paper, an objective based approach of mould and fungi growth assessment using spatial and frequency domain information is proposed. The spatial domain analysis of the acquired Mould Infested Images (MII) is achieved using Ratio Test (RT), Compactness Test (CT) and Visual Test (VT) while the frequency domain analysis uses the popular Discrete Fourier Transform (DFT) implemented in the form of Fast Fourier Transform (FFT) in analyzing the boundary pixel sequence. The resulting frequency components (Fourier Descriptors (FD)) can now be analyzed or stored for reconstruction purposes. Application of structural similarity measures on the reconstructed MII in spatial domain shows that the use of relative low number of FD is sufficient for analyzing, characterizing and reconstruction of the original spatial domain boundary pixels

Damage index: Assessment of mould growth on building materials using digital image processing technique

There is a growing concern over the adverse health effects of exposure to high concentration of mould spores in the indoor environments. Copious epidemiological studies have shown a direct relationship between the exposure to indoor mould and several adverse health effects. The phenomenon of Sick building syndrome (SBS) and Building Related Illness (BRI) have also been attributed to moulds exposure in the indoor environment. In spite of this growing concern, little have been reported on the development of an objective mould assessment particularly criteria for visual inspection of mould growth on building materials. The main premise of this study is that visual inspection related with mould damaged material can lead to objective ranking of the severity of damaged material, and reduce the subjective nature of mould dam-aged estimation by the use digital image processing (DIP) techniques. A four stage technique procedure, involving image preprocessing, Image segmentation and mould analysis and classification stage for the detection of mould growth is examined in this paper. Results obtained when this proposed algorithm was applied to acquired digital images collected from different infested building materials indicates the appropriateness of this method in enhancing the visual assessment and grading associated with mould growth on building material

Development of a new method of crack modeling and prediction algorithm

In this report, the well known parametric method of signals and systems representation is extended to modeling and prediction of cracks on building and road surfaces. Also, a new algorithm based on complex value autoregressive neural network with split linear activation function for the determination of Complex-Value Autoregressive Moving average (CARMA) coefficients is also proposed in this report. Furthermore, mathematical derivation and detail analysis of the proposed CARMA based Complex-Value Neural Network (CVNN) algorithm is also discussed in this work

Investigation of waste heat recovery system at supercritical conditions with vehicle drive cycles

Waste heat recovery (WHR) for internal combustion engines in vehicles using Organic Rankine cycle (ORC) has been a promising technology. The operation of the ORC WHR system in supercritical conditions has a potential to generate more power output and thermal efficiency compared with the conventional subcritical conditions. However, in supercritical conditions, the heat transfer process in the evaporator, the key component of the ORC WHR system, becomes unpredictable as the thermo-physical properties of the working fluid change with the temperature. Furthermore, the transient heat source from the vehicle’s exhaust makes the operation of the WHR system difficult. We investigated the performance of the ORC WHR system at supercritical conditions with engine’s exhaust data from real city and highway drive cycles. The effects of operating variables, such as refrigerant flow rates, evaporator and condenser pressure, and evaporator outlet temperature, on the performance indicators of the WHR system in supercritical conditions were examined. Simulation of operating parameters and the boundary of the WHR system are also included in this paper

Dynamic model of supercritical Organic Rankine Cycle waste heat recovery system for internal combustion engine

The supercritical Organic Rankine Cycle (ORC) for the Waste Heat Recovery (WHR) from Internal Combustion (IC) engines has been a growing research area in recent years, driven by the aim to enhance the thermal efficiency of the ORC and engine. Simulation of a supercritical ORC-WHR system before a real-time application is important as high pressure in the system may lead to concerns about safety and availability of components. In the ORC-WHR system, the evaporator is the main contributor to thermal inertia of the system and is considered to be the critical component since the heat transfer of this device influences the efficiency of the system. Since the thermo-physical properties of the fluid at supercritical pressures are dependent on temperature, it is necessary to consider the variations in properties of the working fluid. The wellknown Finite Volume (FV) discretization method is generally used to take those property changes into account. However, a FV model of the evaporator in steady state condition cannot be used to predict the thermal inertia of the cycle when it is subjected to transient heat sources. In this paper, a dynamic FV model of the evaporator has been developed and integrated with other components in the ORC-WHR system. The stability and transient responses along with the performance of the ORC-WHR system for the transient heat source are investigated and are also included in this paper

Maternal contribution to ultrasound fetal measurements at mid-pregnancy

Background: Maternal variables are known contributors to fetal variables and can be assessed during pregnancy. Objective: To assess maternal contribution to some mid-pregnancy fetal ultrasound measurements. Materials and Methods: A prospective study involving 87 pregnant women scanned at 18–23 weeks of pregnancy was carried out. The fetal measurements were head circumference (HC), abdominal circumference (AC), femur length (FL), and biparietal diameter (BPD) while the maternal variables were age, parity, height, weight, and BMI. Results: There were intercorrelations between some maternal and fetal variables respectively. Parity correlated significantly with all the ultrasound fetal measurements (P .05). Significant correlation between parity and age remained the same with simple and partial correlations (P 6.7%). The generated models revealed HC having the highest standardized regression coefficient (b = 5.07;P < .05) while FL had the least (b = 1.08;P < .05). Conclusion: The results suggested that parity contributed significantly to fetal ultrasound measurements at mid-pregnancy while maternal height, weight, and BMI made no significant impact