Thermal performance optimization of building aspect ratio and south window size in five cities having different climatic characteristics of Turkey

The aim of the study is to establish optimum building aspect ratios and south window sizes of residential buildings from thermal performance point of view. The effects of 6 different building aspect ratios and eight different south window sizes for each building aspect ratio are analyzed for apartments located at intermediate floors of buildings, by the aid of the computer based thermal analysis program SUNCODE-PC in five cities of Turkey: Erzurum, Ankara, Diyarbakir, Izmir, and Antalya. The results are evaluated in terms of annual energy consumption and the optimum values are driven. Comparison of optimum values and the total energy consumption rates is made among the analyzed cities.

The sample complexity of pattern classification with neural networks: the size of the weights is more important than the size of the network

Sample complexity results from computational learning theory, when applied to neural network learning for pattern classification problems, suggest that for good generalization performance the number of training examples should grow at least linearly with the number of adjustable parameters in the network. Results in this paper show that if a large neural network is used for a pattern classification problem and the learning algorithm finds a network with small weights that has small squared error on the training patterns, then the generalization performance depends on the size of the weights rather than the number of weights. For example, consider a two-layer feedforward network of sigmoid units, in which the sum of the magnitudes of the weights associated with each unit is bounded by A and the input dimension is n. We show that the misclassification probability is no more than a certain error estimate (that is related to squared error on the training set) plus A3 √((log n)/m) (ignoring log A and log m factors), where m is the number of training patterns. This may explain the generalization performance of neural networks, particularly when the number of training examples is considerably smaller than the number of weights. It also supports heuristics (such as weight decay and early stopping) that attempt to keep the weights small during training. The proof techniques appear to be useful for the analysis of other pattern classifiers: when the input domain is a totally bounded metric space, we use the same approach to give upper bounds on misclassification probability for classifiers with decision boundaries that are far from the training examples.

An empirical study of applying ISO 9001 elements in large size Indonesian contractors

The effective implementation of such an ISO 9001 Quality Management System (QMS) in construction companies requires a proper and full implementation of the system to allow companies to improve the way they operate, by this means increasing profitability and market share, producing innovative and sustainable construction products, or improving employee and customer satisfaction. In light of this, this paper discusses the current status of QMS implementation, particularly related to the twenty elements of ISO 9001 within the grade 7 (G-7) category of Indonesian construction companies. A survey was conducted involving 403 respondents from 77 companies, to solicit an evaluation of the current implementation levels of the ISO 9001 elements. The survey findings indicated that for a large percentage of the sector surveyed they had ‘not so fully implemented’ the elements. Scrutiny of the data had also indicated elements that are ‘minimally implemented’, whilst none of the elements fell in the category of ‘fully implemented’. Based on these findings, it is suggested that the G-7 contractors may need to fully commit to practicing control of customer-supplied product and statistical techniques in order to enhance an effective implementation of ISO 9001 elements for ensuring better quality performance. These two elements are recognized as the least implemented of the quality elements.

Size effects on tensile and fatigue behaviour of polycrystalline metal foils at the micrometer scale

Tensile and fatigue properties of as-rolled and annealed polycrystalline Cu foils with different thicknesses at the micrometer scale were investigated. Uniaxial tensile testing results showed that with decreasing foil thickness the uniform elongation decreases for both as-rolled and annealed foils, whereas the yield strength and ultimate tensile strength increase for as-rolled foils, but decrease for the annealed foils. For both the as-rolled or annealed foils, bending fatigue resistance decreases with decreasing the foil thickness. Deformation and fatigue damage behaviour of the free-standing foils were characterised as a function of foil thickness. In addition, the fatigue strength of various small-scale Cu foils was compared to understand they physical mechanisms of size effects on mechanical properties of the metallic material at micrometer scales.

A study on acoustic emission signal propagation of a small size multi-cylinder diesel engine

Acoustic emission has been found effective in offering earlier fault detection and improving identification capabilities of faults. However, the sensors are inherently uncalibrated. This paper presents a source to sensor paths calibration technique which can lead to diagnosis of faults in a small size multi-cylinder diesel engine. Preliminary analysis of the acoustic emission (AE) signals is outlined, including time domain, time-frequency domain, and the root mean square (RMS) energy. The results reveal how the RMS energy of a source propagates to the adjacent sensors. The findings lead to allocate the source and estimate its inferences to the adjacent sensor, and finally help to diagnose the small size diesel engines by minimising the crosstalk from multiple cylinders.

Detection of bacteriophage and respiratory viruses in droplets

Influenza is a widespread disease occurring in seasonal epidemics, and each year is responsible for up to 500,000 deaths worldwide. Influenza can develop into strains which cause severe symptoms and high mortality rates, and could potentially reach pandemic status if the virus’ properties allow easy transmission. Influenza is transmissible via contact with the virus, either directly (infected people) or indirectly (contaminated objects); via reception of large droplets over short distances (one metre or less); or through inhalation of aerosols containing the virus expelled by infected individuals during respiratory activities, that can remain suspended in the air and travel distances of more than one metre (the aerosol route). Aerosol transmission of viruses involves three stages: production of the droplets containing viruses; transport of the droplets and ability of a virus to remain intact and infectious; and reception of the droplets (via inhalation). Our understanding of the transmission of influenza viruses via the aerosol route is poor, and thus our ability to prevent a widespread outbreak is limited. This study explored the fate of viruses in droplets by investigating the effects of some physical factors on the recovery of both a bacteriophage model and influenza virus. Experiments simulating respiratory droplets were carried out using different types of droplets, generated from a commonly used water-like matrix, and also from an ‘artificial mucous’ matrix which was used to more closely resemble respiratory fluids. To detect viruses in droplets, we used the traditional plaque assay techniques, and also a sensitive, quantitative PCR assay specifically developed for this study. Our results showed that the artificial mucous suspension enhanced the recovery of infectious bacteriophage. We were able to report detection limits of infectious bacteriophage (no bacteriophage was detected by the plaque assay when aerosolised from a suspension of 103 PFU/mL, for three of the four droplet types tested), and that bacteriophage could remain infectious in suspended droplets for up to 20 minutes. We also showed that the nested real-time PCR assay was able to detect the presence of bacteriophage RNA where the plaque assay could not detect any intact particles. Finally, when applying knowledge from the bacteriophage experiments, we reported the quantitative recoveries of influenza viruses in droplets, which were more consistent and stable than we had anticipated. Influenza viruses can be detected up to 20 minutes (after aerosolisation) in suspended aerosols and possibly beyond. It also was detectable from nebulising suspensions with relatively low concentrations of viruses.

What determines real-world meal size? Evidence for pre-meal planning

The customary approach to the study of meal size suggests that ‘events’ occurring during a meal lead to its termination. Recent research, however, suggests that a number of decisions are made before eating commences that may affect meal size. The present study sought to address three key research questions around meal size: the extent to which plate cleaning occurs; prevalence of pre-meal planning and its influence on meal size; and the effect of within-meal experiences, notably the development of satiation. To address these, a large-cohort internet-based questionnaire was developed. Results showed that plate cleaning occurred at 91% of meals, and was planned from the outset in 92% of these cases. A significant relationship between plate cleaning and meal planning was observed. Pre meal plans were resistant to modification over the course of the meal: only 18% of participants reported consumption that deviated from expected. By contrast, 28% reported continuing eating beyond satiation, and 57% stated that they could have eaten more at the end of the meal. Logistic regression confirmed pre-meal planning as the most important predictor of consumption. Together, our findings demonstrate the importance of meal planning as a key determinant of meal size and energy intake.