Environmental assessment tools and efficiency in housing and office refurbishment

Most environmental sustainability assessment tools are focused on new construction while refurbishment of buildings presents a different picture. Short term, local environmental effects such as noise or dust are more frequent in a refurbishment process since both occupants and neighbours are affected whereas in new construction only neighbours might be affected. The purpose of this paper is to provide a framework in order to assess strength and weaknesses of environmental assessment tools for housing and office refurbishment projects, taking into account practical aspects, fundamentals of sustainability as well as conflicts between sustainability and efficiency. A review of literatures on sustainability, measurement systems in general and major environmental assessment tools confirms that these tools focus on energy consumption, heat insulation, air quality, light, noise, water efficiency and material consumption in new construction, but rarely in a refurbishment context. Short term, negative effects during a renovation process are not covered by current environmental assessment tools. The conflict between local and global effects of sustainable refurbishment, users' needs, workers' efficiency during the refurbishment process, problems caused by occupants and waste management should be reflected in a framework for indicators to be used in refurbishment projects. Since there are important effects on building users involved in most refurbishment processes, more attention should be paid to the relation between their productivity and both economic and social sustainability

REPORTING UNCERTAINITY BY SPLINE FUNCTION APPROXIMATION OF LOG-LIKELIHOOD

Reporting uncertainty is one of the most important tasks in any statistical paradigm.Likelihood functions from independent studies can be easily combined, and the combined likelihood function serves as a meaningful indication of the support the observed data give to the various parameter values. This fact has led us to suggest using the likelihood function as a summary of post-data uncertainty concerning the parameter. However, a serious difficulty arises because likelihood functions may not be expressible in a compact, easily-understood mathematical form suitable for communication or publication. To overcome this difficulty, we propose to approximate log-likelihood functions by using piecewise polynomials governed by a minimal number of parameters. Our goal is to find the function of the parameter(s) that approximates the log-likelihood function with the minimum integrated (square) error over the parameter space. We achieve several things by approximating the log-likelihood; first, we significantly reduce the numerical difficulty associated with finding the maximum likelihood estimator. Second, in order to be able to combine the likelihoods that come from independent studies, it is important that the approximation of the log-likelihood should depend only upon a few parameters so that the results can be communicated compactly. By the simulation studies we compared natural cubic spline approximation with the conventional modified likelihood methods in terms of coverage probability and interval length of highest density region obtained from the likelihood and the mean squared error of the maximum likelihood estimator

Duodenum birinci kısım divertikülünden kaynaklanan nadir bir schwannom olgusu

Bu yazıda periferal sinir schwann hücrelerinden köken alan nadir bir duodenal schwannoma olgusu sunulmuştur. 57 yaşında bayan hasta anemi tetkiki sırasında ateş ve karın ağrısı şikayeti ile başvurdu. Fizik muayenesinde karın sağ üst kadranda hassasiyet tespit edildi. Laboratuar değerlerinde 15 300/l olan lökositoz haricinde anormallik yoktu. Tüm tümör belirteçleri normal değerlerdeydi. Ultrasonografide duodenuma yapışık hipoekoik kitle tespit edildi. Bilgisayarlı tomografi ve manyetik rezonans incelemede aynı lokalizasyonda 4x3 cm'lik kitle ve 8x11x12 cm'lik karaciğer sağ lobda abse bulundu. Hepatik abse drenajı ve duodenal divertikülektomi yapıldı. Histopatolojik incelemede şekil ve büyüklükte hafif derecede değişiklikler gösteren kesişen iğsi hücre kümeleri içeren tümöral kitle görüldü. İmmünohistokimyasal olarak tümör hücrelerinin S100 protein ile kuvvetli pozitiflik vermesi nedeni ile duodenal schwannoma tanısı kondu. Ameliyat sonrası dönemi sorunsuz geçen hasta 8. gün taburcu oldu.A case of duodenal schwannoma, a rare tumor arising from schwannian cells of peripheral nerves is presented. A 57-year-old woman was admitted with abdominal pain and fever during investigation of anemia. Physical examination revealed tenderness in the right side of the upper abdomen. Laboratory tests showed no abnormality except for leucocytosis of 15 300/l. All tumor markers were negative. Ultrasonography revealed a hypoechoic mass adjacent to the duodenum. Computed tomography and magnetic resonance imaging showed a 4x3 cm mass in the same region and an abscess with dimensions of 8x11x12 cm in the right lobe of liver. Hepatic abscess drainage and duodenal diverticulectomy was performed. Histopathological examination revealed a tumorous mass composed of interlacing bundles of spindle cells, showing mild variations in nuclear shape and size. Immunohistochemically tumor cells were positive for S100 protein, thus, schwannoma of the duodenum was diagnosed. The postoperative course was uneventful and the patient was discharged on the eighth day of operation

Financial Trading Model with Stock Bar Chart Image Time Series with Deep Convolutional Neural Networks

Even though computational intelligence techniques have been extensively utilized in financial trading systems, almost all developed models use the time series data for price prediction or identifying buy-sell points. However, in this study we decided to use 2-D stock bar chart images directly without introducing any additional time series associated with the underlying stock. We propose a novel algorithmic trading model CNN-BI (Convolutional Neural Network with Bar Images) using a 2-D Convolutional Neural Network. We generated 2-D images of sliding windows of 30-day bar charts for Dow 30 stocks and trained a deep Convolutional Neural Network (CNN) model for our algorithmic trading model. We tested our model separately between 2007-2012 and 2012-2017 for representing different market conditions. The results indicate that the model was able to outperform Buy and Hold strategy, especially in trendless or bear markets. Since this is a preliminary study and probably one of the first attempts using such an unconventional approach, there is always potential for improvement. Overall, the results are promising and the model might be integrated as part of an ensemble trading model combined with different strategies.Comment: accepted to be published in Intelligent Automation and Soft Computing journa

Effects of construction industry support for PhD projects: The case of a Swedish scheme

One of the many varieties of university–industry collaboration is industry engagement in doctoral programmes. A scheme operated by the Development Fund of the Swedish Construction Industry since the early 1990s has supported thesis projects for about 150 PhD candidates. While they were doctoral students they were employed by contractors as industrial doctoral candidates or by universities. The purpose of this investigation was to analyse how, as PhD graduates, they perceived the benefits of doctoral studies for themselves as individuals and also how they have contributed to the organization that employs them. Results from a survey with 125 respondents show that the greatest individual benefit is that of being able to access relevant information more rapidly, and that the greatest perceived organizational benefit arises from their ability to cooperate with knowledgeable clients

Optimal detector randomization in cognitive radio receivers in the presence of imperfect sensing decisions

Ankara : The Department of Electrical and Electronics Engineering and the Graduate School of Engineering and Science of Bilkent Univ., 2013.Thesis (Master's) -- Bilkent University, 2013.Includes bibliographical references leaves 36-39.In cognitive radio systems, spectrum sensing is one of the crucial tasks to be performed by secondary users in order to limit the interference to primary users. Therefore various spectrum sensing methods have been proposed in the literature. Once secondary users make a sensing decision, they adapt their communication parameters accordingly, which means that they perform communications when the channel is sensed as idle whereas they either do not transmit at all or transmit at a reduced power when the channel is sensed as busy. However, in practical systems, sensing decisions of secondary users are never perfect; hence, there can be cases in which the sensing decision is idle (busy) but primary user activity actually exists (does not exist). Therefore, the optimal design of secondary systems requires the consideration of imperfect sensing decisions. In this thesis, optimal detector randomization is developed for secondary users in a cognitive radio system in the presence of imperfect spectrum sensing decisions. Also, suboptimal detector randomization is proposed under the assumption of perfect sensing decisions. It is shown that the minimum average probability of error can be achieved by employing no more than four maximum a-posteriori probability (MAP) detectors at the secondary receiver. Optimal and suboptimal MAP detectors and generic expressions for their average probability of error are derived in the presence of possible sensing errors. Numerical results are presented and the importance of taking possible sensing errors into account is illustrated in terms of average probability of error optimization.Sezer, Ahmet DündarM.S

Refurbishment certification schemes: aspects of productivity and sustainability

Sustainability rating tools can be analysed in a productivity perspective. Governmentregulations, including taxes and fees that make firms internalize negative environmental externalities,reduce the gap between sustainability and productivity. Productivity measurement methods for newconstruction are difficult to apply to refurbishment projects, and there is no consensus on measuringthe sustainability of refurbishment processes. The purpose here is to investigate how sustainabilityconcepts in building certification schemes for refurbishment are related to productivity, usingBREEAM Refurbishment Domestic Buildings and LEED for New Construction and Major Renovationsas examples. A set of criteria for analysis is developed here. While this BREEAM scheme has its focusspecifically on refurbishment, the LEED version has less that is specific to refurbishment processes.These schemes mainly focus on post-refurbishment assessment. Long-term productivity is related toeconomic sustainability, and recent refurbishment versions of certification schemes in Germany andJapan recognize more than environmental sustainability

Contractor Monitoring of Productivity and Sustainability in Building Refurbishment

The aging building stock in Europe and regulatory requirements to decrease energy consumption make sustainable refurbishment a valuable alternative to other construction activities. The construction industry appears to suffer from low productivity growth, and the construction productivity debate concludes that productivity measurement is difficult, not least due to changes in input and output qualities. Building certification schemes are one way to measure sustainability. However, existing schemes focus mainly on environmental sustainability and new construction, while refurbishment differs from new construction. The purpose of this research is to analyse the relation between the theoretical concepts of sustainability and productivity in the context of measurement, and to investigate the performance measures used in housing and office refurbishment projects. This thesis is based mainly on literature reviews in the areas of sustainability, productivity, performance measurement and building refurbishment. The empirical data were collected through eight semi-structured interviews - five with site managers employed by large contractors, and three with general or site managers from small and medium sized enterprises (SMEs). All the interviewees were involved in housing refurbishment projects. The findings of this thesis suggest that current methods of measuring productivity in the construction industry are unsatisfactory. Simple area-based methods and measurement of labour productivity do not capture changes in input and output qualities. Most existing building certification schemes have not taken account of the overall sustainability of the refurbishment process. They reflect the fundamentals of sustainability very poorly, and they tend to hide conflicts between sustainability and productivity. They mostly lack a clear refurbishment focus, even in schemes that are supposed to include refurbishment. Lack of time is a frequent excuse for not measuring productivity on sites, although perceived time pressure might be a symptom of complex resource allocation. SMEs pay little attention to sustainability measurement because they do not see it providing economic benefits, while large contractors invoke lack of client demand