Search results for: efficiency analysis and selection bias

Authors: Zakariya B. H., Idris M. I., Jungudo M. A.

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High energy consumptions of urban settlements in Nigeria are escalating due to strong population growth and migration as a result of crises. The demand for lighting, heating, ventilation and air conditioning (LHVAC) is becoming higher. Conversely, there is a poor electricity supply to both rural and urban settlement in Nigeria. Generators were mostly used in Nigeria as a source of energy for LHVAC. Energy efficiency can be defined as any measure taken to reduce the amount of energy consumed for heating ventilation and air-conditioning (HVAC), and house hold appliances like computers, stoves, refrigerators, televisions etc. The aim of the study was to minimize energy consumption in building through the integration of energy efficiency and renewable energy in building sector. Some of the energy efficient buildings within the study area were identified, the study covers there major cities of Nigeria namely, Abuja, Kaduna and Lagos city. The cost of investment on the energy efficiency and renewable energy was determined and compared with other fossil energy source for conventional building. Findings revealed that the low energy and energy efficient buildings in Nigeria are cheaper than the conventional ones. Based on the finding of the research, construction stake holders are strongly encouraged to abandon the conventional buildings and consider energy efficiency and renewable energy in buildings.

Keywords: energy, efficiency, LHVAC, sustainable development

Procedia PDF Downloads 582

Authors: Katri K. Cornelissen, Lise Gulli Brokjob, Kristofor McCarty, Jiri Gumancik, Martin J. Tovee, Piers L. Cornelissen

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Recent research has shown that body size estimation of healthy women is driven by independent attitudinal and perceptual components. The attitudinal component represents psychological concerns about body, coupled to low self-esteem and a tendency towards depressive symptomatology, leading to over-estimation of body size, independent of the Body Mass Index (BMI) someone actually has. The perceptual component is a normal bias known as contraction bias, which, for bodies is dependent on actual BMI. Women with a BMI less than the population norm tend to overestimate their size, while women with a BMI greater than the population norm tend to underestimate their size. Women whose BMI is close to the population mean are most accurate. This is indexed by a regression of estimated BMI on actual BMI with a slope less than one. It is well established that body dissatisfaction, i.e. an attitudinal distortion, leads to body size overestimation in eating disordered individuals. However, debate persists as to whether women with eating disorders may also suffer a perceptual body distortion. Therefore, the current study was set to ask whether women with eating disorders exhibit the normal contraction bias when they estimate their own body size. If they do not, this would suggest differences in the way that women with eating disorders process the perceptual aspects of body shape and size in comparison to healthy controls. 100 healthy controls and 33 women with a history of eating disorders were recruited. Critically, it was ensured that both groups of participants represented comparable and adequate ranges of actual BMI (e.g. ~18 to ~40). Of those with eating disorders, 19 had a history of anorexia nervosa, 6 bulimia nervosa, and 8 OSFED. 87.5% of the women with a history of eating disorders self-reported that they were either recovered or recovering, and 89.7% of them self-reported that they had had one or more instances of relapse. The mean time lapsed since first diagnosis was 5 years and on average participants had experienced two relapses. Participants were asked to fill number of psychometric measures (EDE-Q, BSQ, RSE, BDI) to establish the attitudinal component of their body image as well as their tendency to internalize socio-cultural body ideals. Additionally, participants completed a method of adjustment psychophysical task, using photorealistic avatars calibrated for BMI, in order to provide an estimate of their own body size and shape. The data from the healthy controls replicate previous findings, revealing independent contributions to body size estimation from both attitudinal and perceptual (i.e. contraction bias) body image components, as described above. For the eating disorder group, once the adequacy of their actual BMI ranges was established, a regression of estimated BMI on actual BMI had a slope greater than 1, significantly different to that from controls. This suggests that (some) eating disordered individuals process the perceptual aspects of body image differently from healthy controls. It therefore is necessary to develop interventions which are specific to the perceptual processing of body shape and size for the management of (some) individuals with eating disorders.

Keywords: body image distortion, perception, recovery, relapse, BMI, eating disorders

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Authors: Milind Anurag

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This study investigates cutting-edge truss design improvements, which are specifically adapted to satisfy the structural demands and difficulties associated with high-performance facades and roofs in modern architectural environments. With a growing emphasis on sustainability, energy efficiency, and eye-catching architectural aesthetics, the structural components that support these characteristics play an important part in attaining the right balance of form and function. The paper seeks to contribute to the evolution of truss design methods by combining data from these investigations, giving significant insights for architects, engineers, and researchers interested in the creation of high-performance building envelopes. The findings of this study are meant to inform future design standards and practices, promoting the development of structures that seamlessly integrate architectural innovation with structural robustness and environmental responsibility.

Keywords: truss design, high-performance, facades, finite element analysis, structural efficiency

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Authors: Lusine S. Stepanyan, Elina V. Asriyan.

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It is known, that the efficiency of management depend on individual characteristics of manager. In case, was shown the role of personal position in the efficiency of management. Current research is aimed at reveal psychological and psychophysiological basis efficiency of management and finding ways of increasing the productivity of management that is most essential and topical problems of modern society. To understand the investigated phenomenon it was applied a complex approach. The Eysenk questionnaire was used for determining the level of aggression, frustration, anxiety and rigidity. The test of egocentric associations was used for determining the level of egocentrism. The test of COS (communicativeness and organizational skills) was used for diagnosing the level of communicativeness. The integral index of job satisfaction was used for diagnosis the efficiency of management activity. Then, the relationship between the above mentioned mental state, communicativeness, self-esteem, job satisfaction, locus of control, and egocentrism was investigated. The obtained results have shown the positive correlation between the egocentrism and frustration, anxiety and also the negative correlation with job satisfaction and communicativeness. Intergroup analyses has revealed the significant differences by communicativeness and the internality’ level. The revealed results can be used for diagnosis of efficiency of management.

Keywords: egocentrism, locus control, mental state, job satisfaction, professional activity

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Authors: Hamda M. Al-Ali

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From addressing fundamental questions about the history of the solar system to exploring other planets for any signs of life have always been the core of human space exploration. This triggered humans to explore whether other planets such as Mars could support human life on them. Therefore, many planned space missions to other planets have been designed and conducted to examine the feasibility of human survival on them. However, space missions are expensive and consume a large number of various resources to be successful. To overcome these problems, material efficiency shall be maximized through the use of reusable launch vehicles (RLV) rather than disposable and expendable ones. Material efficiency is defined as a way to achieve service requirements using fewer materials to reduce CO2 emissions from industrial processes. Materials such as aluminum-lithium alloys, steel, Kevlar, and reinforced carbon-carbon composites used in the manufacturing of spacecrafts could be reused in closed-loop cycles directly or by adding a protective coat. Material efficiency is a fundamental principle of a circular economy. The circular economy aims to cutback waste and reduce pollution through maximizing material efficiency so that businesses can succeed and endure. Five strategies have been proposed to improve material efficiency in the space industry, which includes waste minimization, introduce Key Performance Indicators (KPIs) to measure material efficiency, and introduce policies and legislations to improve material efficiency in the space sector. Another strategy to boost material efficiency is through maximizing resource and energy efficiency through material reusability. Furthermore, the environmental effects associated with the rapid growth in the number of space missions include black carbon emissions that lead to climate change. The levels of emissions must be tracked and tackled to ensure the safe utilization of space in the future. The aim of this research paper is to examine and suggest effective methods used to improve material efficiency in space missions so that space and Earth become more environmentally and economically sustainable. The objectives used to fulfill this aim are to identify the materials used in space missions that are suitable to be reused in closed-loop cycles considering material efficiency indicators and circular economy concepts. An explanation of how spacecraft materials could be re-used as well as propose strategies to maximize material efficiency in order to make RLVs possible so that access to space becomes affordable and reliable is provided. Also, the economic viability of the RLVs is examined to show the extent to which the use of RLVs has on the reduction of space mission costs. The environmental and economic implications of the increase in the number of space missions as a result of the use of RLVs are also discussed. These research questions are studied through detailed critical analysis of the literature, such as published reports, books, scientific articles, and journals. A combination of keywords such as material efficiency, circular economy, RLVs, and spacecraft materials were used to search for appropriate literature.

Keywords: access to space, circular economy, material efficiency, reusable launch vehicles, spacecraft materials

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Authors: Oriahi Love Ndidi

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High concentration photovoltaic promises a more efficient, higher power output than traditional photovoltaic modules. One of the driving forces of this high system efficiency has been the continuous improvement of III-V multi-junction solar cell efficiencies. Multi-junction solar cells built from III-V semiconductors are being evaluated globally in concentrated photovoltaic systems designed to supplement electricity generation for utility companies. The high efficiency of this III-V multi-junction concentrator cells, with demonstrated efficiency over 40 percent since 2006, strongly reduces the cost of concentrated photovoltaic systems, and makes III-V multi-junction cells the technology of choice for most concentrator systems today.

Keywords: cost of multi-junction solar cell, efficiency, photovoltaic systems, reliability

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Authors: Innocent Pangapanga-Phiri, Eric Dada Mungatana

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This study estimates the effect of climate-induced rural-urban migrants (RUM) on maize productivity. It uses panel data gathered by the National Statistics Office and the World Bank to understand the effect of RUM on the technical efficiency of maize production in rural Malawi. The study runs the two-stage Tobit regression to isolate the real effect of rural-urban migration on the technical efficiency of maize production. The results show that RUM significantly reduces the technical efficiency of maize production. However, the interaction of RUM and climate-smart agriculture has a positive and significant influence on the technical efficiency of maize production, suggesting the need for re-investing migrants’ remittances in agricultural activities.

Keywords: climate-smart agriculture, farm productivity, rural-urban migration, panel stochastic frontier models, two-stage Tobit regression

Procedia PDF Downloads 134

Authors: Bisi S. Olawoyin

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This study attempts an exploration into behavioural finance in which the traditional assumptions of expected utility maximization with rational investors in efficient markets are dropped. It reviews prior research and evidence about how psychological biases affect investors behaviour and stock selection. This study examined the relationship between demographic variables and financial behaviour biases among public sector retirees who invested in the Nigerian Stock Exchange prior to their retirement. By using questionnaire survey method, a total of 214 valid convenient samples were collected in order to determine how specific demographic and psychological trait affect stock selection between dividend paying and non-dividend paying stocks. Descriptive statistics and OLS were used to analyse the results. Findings showed that most of the retirees prefer dividend paying stocks in few years preceding their retirement but still hold on to their non-dividend paying stock on retirement. A significant difference also exists between senior and junior retirees in preference for non-dividend paying stocks. These findings are consistent with the clientele theories of dividend.

Keywords: behavioural finance, clientele theories, dividend paying stocks, stock selection

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Authors: Shenko Chura Aredo, Hailu Belay, Kevin T. Kornegay

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In light of Adama City’s smart city development vision, this study thoroughly investigates the performance of smart security systems with Fifth Generation (5G) network capabilities. It can be logistically difficult to install a lot of cabling, particularly in big or dynamic settings. Moreover, latency issues might affect linked systems, making it difficult for them to monitor in real time. Through a focused analysis that employs Adama City as a case study, the performance has been evaluated in terms of spectrum and energy efficiency using empirical data and basic signal processing formulations at different frequency resources. The findings also demonstrate that cameras working at higher 5G frequencies have more capacity than those operating at sub-6 GHz, notwithstanding frequency-related issues. It has also been noted that when the beams of such cameras are adaptively focussed based on the distance of the last cell edge user rather than the maximum cell radius, less energy is required than with conventional fixed power ramping.

Keywords: 5G, energy efficiency, safety, smart security, spectral efficiency

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Authors: Mengying Wang, Xiaohui Wang, Chun Deng, Bei Liu, Changyu Sun, Guangjin Chen, Mahmoud El-Halwagi

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Significant amounts of natural gas hydrates (NGHs) are considered potential new sustainable energy resources in the future. However, common used methods for methane gas recovery from hydrate sediments require high investment but with low gas production efficiency, and may cause potential environment and security problems. Therefore, there is a need for effective gas production from hydrates. The natural gas hydrate production method by CO₂/H₂ replacement coupling steam methane reforming can improve the replacement effect and reduce the cost of gas separation. This paper develops a simulation model of the gas production process integrated with steam reforming and membrane separation. The process parameters (i.e., reactor temperature, pressure, H₂O/CH₄ ratio) and the composition of CO₂ and H₂ in the feed gas are analyzed. Energy analysis is also conducted. Two design scenarios with different composition of CO₂ and H₂ in the feed gas are proposed and evaluated to assess the energy efficiency of the novel system. Results show that when the composition of CO₂ in the feed gas is between 43 % and 72 %, there is a certain composition that can meet the requirement that the flow rate of recycled gas is equal to that of feed gas, so as to ensure that the subsequent production process does not need to add feed gas or discharge recycled gas. The energy efficiency of the CO₂ in feed gas at 43 % and 72 % is greater than 1, and the energy efficiency is relatively higher when the CO₂ mole fraction in feed gas is 72 %.

Keywords: Gas production, hydrate, process integration, steam reforming

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Authors: Mafarja Majdi, Salwani Abdullah, Najmeh S. Jaddi

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One of the global combinatorial optimization problems in machine learning is feature selection. It concerned with removing the irrelevant, noisy, and redundant data, along with keeping the original meaning of the original data. Attribute reduction in rough set theory is an important feature selection method. Since attribute reduction is an NP-hard problem, it is necessary to investigate fast and effective approximate algorithms. In this paper, we proposed two feature selection mechanisms based on memetic algorithms (MAs) which combine the genetic algorithm with a fuzzy record to record travel algorithm and a fuzzy controlled great deluge algorithm to identify a good balance between local search and genetic search. In order to verify the proposed approaches, numerical experiments are carried out on thirteen datasets. The results show that the MAs approaches are efficient in solving attribute reduction problems when compared with other meta-heuristic approaches.

Keywords: rough set theory, attribute reduction, fuzzy logic, memetic algorithms, record to record algorithm, great deluge algorithm

Procedia PDF Downloads 456

Authors: Byeongcheol Kang, Junyi Kim, Hyungsik Jung, Hyungjun Yang, Jaewoo An, Jonggeun Choe

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It is important to figure out reservoir properties for better production management. Due to the limited information, there are geological uncertainties on very heterogeneous or channel reservoir. One of the solutions is to generate multiple equi-probable realizations using geostatistical methods. However, some models have wrong properties, which need to be excluded for simulation efficiency and reliability. We propose a novel method of model selection scheme, based on distance-based clustering for reliable application of production optimization algorithm. Distance is defined as a degree of dissimilarity between the data. We calculate Hausdorff distance to classify the models based on their similarity. Hausdorff distance is useful for shape matching of the reservoir models. We use multi-dimensional scaling (MDS) to describe the models on two dimensional space and group them by K-means clustering. Rather than simulating all models, we choose one representative model from each cluster and find out the best model, which has the similar production rates with the true values. From the process, we can select good reservoir models near the best model with high confidence. We make 100 channel reservoir models using single normal equation simulation (SNESIM). Since oil and gas prefer to flow through the sand facies, it is critical to characterize pattern and connectivity of the channels in the reservoir. After calculating Hausdorff distances and projecting the models by MDS, we can see that the models assemble depending on their channel patterns. These channel distributions affect operation controls of each production well so that the model selection scheme improves management optimization process. We use one of useful global search algorithms, particle swarm optimization (PSO), for our production optimization. PSO is good to find global optimum of objective function, but it takes too much time due to its usage of many particles and iterations. In addition, if we use multiple reservoir models, the simulation time for PSO will be soared. By using the proposed method, we can select good and reliable models that already matches production data. Considering geological uncertainty of the reservoir, we can get well-optimized production controls for maximum net present value. The proposed method shows one of novel solutions to select good cases among the various probabilities. The model selection schemes can be applied to not only production optimization but also history matching or other ensemble-based methods for efficient simulations.

Keywords: distance-based clustering, geological uncertainty, particle swarm optimization (PSO), production optimization

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Authors: Umesh Kumar Sinha, Y. K. Nayak, N. Kumar, Swapnil Saurav, Monika Kashyap

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The authors investigate the effect of system and operating parameters on the performance of high temperature solar concentrator for power generation. The effects of system and operating parameters were investigated using the developed mathematical expressions for collector efficiency, heat removal factor, fluid outlet temperature and power, etc. The results were simulated using C++program. The simulated results were plotted for investigation like effect of thermal loss parameter and radiative loss parameters on the collector efficiency, heat removal factor, fluid outlet temperature, rise of temperature and effect of mass flow rate of the fluid outlet temperature. In connection with the power generation, plots were drawn for the effect of (TM–TAMB) on the variation of concentration efficiency, concentrator irradiance on PM/PMN, evaporation temperature on thermal to electric power efficiency (Conversion efficiency) of the plant and overall efficiency of solar power plant.

Keywords: parabolic trough solar collector, radiative and thermal loss parameters, collector efficiency, heat removal factor, fluid outlet and inlet temperatures, rise of temperature, mass flow rate, conversion efficiency, concentrator irradiance

Procedia PDF Downloads 322

Authors: Ayoola T. Brimmo, Mohamed I. Hassan

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The push to mitigate the aluminum smelting industry’s enormous energy consumption and high emission releases is now even more persistent with the recent climate change happenings. Common approaches to achieve this have been focused on improving energy efficiency in the pot line and cast house sections of the smelter. However, the conventional energy efficiency analyses are based on the first law of thermodynamics, which do not shed proper light on the smelter’s degradation of energy. This just gives a general idea of the furnace’s performance with no reference to locations where improvement is a possibility based on the second law of thermodynamics. In this study, we apply exergy analyses on the pot line and cast house sections of the smelter to identify the locality and causes of energy degradation. The exergy analyses, which are based on a real life smelter conditions, highlight the possible locations for technology improvement in a typical smelter. With this established, methods of minimizing the smelter’s exergy losses are assessed.

Keywords: exergy analysis, electrolytic cell, furnace, heat transfer

Procedia PDF Downloads 289

Authors: A. Robbin

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Language selection can be an efficient negotiation strategy employed by both service or product providers and their customers to achieve transactional success. The transactional scenario in Gbagi Market, Ibadan, Nigeria provides an appropriate setting for the exploration of the Nigerian multilingual situation with its own interesting linguistic peculiarities which questions the functionality of the ‘Lingua Franca’ in trade situations. This study examined English Language proficiency among Yoruba Traders in Gbagi Market, Ibadan and its use as determinants of transactional success during service encounters. Randomly selected Yoruba-English bilingual traders and customers were administered questionnaires and the data subjected to statistical and descriptive analysis using Giles Communication Accommodation Theory. Findings reveal that only fifty percent of the traders used for the study were proficient in speaking English language. Traders with minimal proficiency in Standard English, however, resulted in the use of the Nigerian Pidgin English. Both traders and customers select the Mother Tongue, which is the Yoruba Language during service encounters but are quick to converge to the other’s preferred language as the transactional exchange demands. The English language selection is not so much for the prestige or lingua franca status of the language as it is for its functions, which include ease of communication, negotiation, and increased sales. The use of English during service encounters is mostly determined by customer’s linguistic preference which the trader accommodates to for better negotiation and never as a first choice. This convergence is found to be beneficial as it ensures sales and return patronage. Although the English language is not a preferred code choice in Gbagi Market, it serves a functional trade strategy for transactional success during service encounters in the market.

Keywords: communication accommodation theory, language selection, proficiency, service encounter, transaction

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Authors: Ali Asghar Memon

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A cautious and astute selection of switching devices used in power electronic converters of a switched reluctance (SR) motor is required. It is a matter of choice of best switching devices with respect to their switching ability rather than fulfilling the number of switches. This paper highlights the computational determination of switching losses comprising of switch-on, switch-off and conduction losses respectively by using experimental data in simulation model of a SR machine. The finding of this research is helpful for proper selection of electronic switches and suitable converter topology for switched reluctance motor.

Keywords: converter, operating modes, switched reluctance motor, switching losses

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Authors: Siti Noor Baiti Binti Mustafa

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Energy management studies regarding energy efficiency investments in Malaysia has yet to address the lack of empirical research that examines pro- sustainability behavior of managers in the industrial sector and how it influences energy efficiency investment decision-making. This study adopts the Theory of Planned Behavior (TPB) to examine the relationship between personal attitude, subjective norms, and perceived behavioral control (PBC), the intention of energy efficiency investments, and how perceptions of Non-Energy Benefits (NEB) influence these intentions among managers in the industrial sector in Malaysia. Managers from various sub-sectors in the industrial sector were selected from a sample of companies that are participants of the Government-led program named the Energy Audit Conditional Grant (EACG) that aimed to promote energy efficiency. Data collection was conducted through an online semi-structured, open-ended questionnaire and then later interviewed. The results of this explorative sequential qualitative study showed that perceived behavioral control was a significant predictor of energy efficiency investment intentions as compared to factors such as attitude and subjective norms. The level of awareness and perceptions towards NEB further played a significant factor in influencing energy efficiency investment decision-making as well. Various measures and policy recommendations are provided together with insights on factors that influence decision-makers intention to invest in energy efficiency, whilst new knowledge on NEB perceptions will be useful to enhance the attractiveness of energy-efficient investments.

Keywords: energy efficiency investments, non-energy benefits, theory of planned behavior, personal attitude, subjective norms, perceived behavioral control, Malaysia industrial sector

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Authors: Nisa Ertoy Inci, Cengiz Toker

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Winter or autumn-sown faba bean (Vicia faba L.) is one the most efficient ways to overcome drought since faba bean is usually grown under rainfed where drought and high-temperature stresses are the main growth constraints. The objectives of this study were assessment of (i) relationships between cold tolerance and agro-morphological traits, and (ii) the most suitable agro-morphological trait(s) under cold conditions. Three species of the genus Vicia L. includes 109 genotypes of faba bean (Vicia faba L.), three genotypes of narbon bean (V. narbonensis L.) and two genotypes of V. montbretii Fisch. & C.A. Mey. Davis and Plitmann were sown in autumn at highland of Mediterranean region of Turkey. All relatives of faba bean were more cold-tolerant than the faba bean genotypes. Three faba bean genotypes, ACV-42, ACV-84 and ACV-88, were selected as sources of cold tolerance under field conditions. Path and correlation coefficients and factor and principal component analyses indicated that biological yield should be evaluated in selection for cold tolerance under cold conditions ahead of many agro-morphological traits. The seed weight should be considered for selection in early breeding generations because they had the highest heritability.

Keywords: cold tolerance, faba bean, narbon bean, selection

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Authors: Muftah H. El-Naas, Ameera F. Mohammad, Mabruk I. Suleiman, Mohamed Al Musharfy, Ali H. Al-Marzouqi

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CO₂ capture and storage technologies play a significant role in contributing to the control of climate change through the reduction of carbon dioxide emissions into the atmosphere. The present study evaluates and optimizes CO₂ capture through a process, where carbon dioxide is passed into pH adjusted high salinity water and reacted with sodium chloride to form a precipitate of sodium bicarbonate. This process is based on a modified Solvay process with higher CO₂ capture efficiency, higher sodium removal, and higher pH level without the use of ammonia. The process was tested in a bubble column semi-batch reactor and was optimized using response surface methodology (RSM). CO₂ capture efficiency and sodium removal were optimized in terms of major operating parameters based on four levels and variables in Central Composite Design (CCD). The operating parameters were gas flow rate (0.5–1.5 L/min), reactor temperature (10 to 50 ^oC), buffer concentration (0.2-2.6%) and water salinity (25-197 g NaCl/L). The experimental data were fitted to a second-order polynomial using multiple regression and analyzed using analysis of variance (ANOVA). The optimum values of the selected variables were obtained using response optimizer. The optimum conditions were tested experimentally using desalination reject brine with salinity ranging from 65,000 to 75,000 mg/L. The CO₂ capture efficiency in 180 min was 99% and the maximum sodium removal was 35%. The experimental and predicted values were within 95% confidence interval, which demonstrates that the developed model can successfully predict the capture efficiency and sodium removal using the modified Solvay method.

Keywords: CO2 capture, water desalination, Response Surface Methodology, bubble column reactor

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Authors: Zafar Mahmood, Fahimullah Babar, Surriyia Naz, Hafiz Ur Rehman

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Cadmium Sulphide (CdS) was deposited on a Tec 15 glass substrate with the help of CBD (chemical bath deposition process) and then cadmium telluride CdTe was deposited on CdS with the help of CSS (closed spaced sublimation technique) for the construction of a solar cell. The thicknesses of all the deposited materials were measured with the help of Elipsometry. The IV graphs were drawn in order to observe the current voltage output. The efficiency of the cell was graphed with the fill factor as well (graphs not given here).The efficiency came out to be approximately 16.5 % and the CIGS (copper- indium –gallium- selenide) maximum efficiency is 20 %.The efficiency of a solar cell can further be enhanced by adapting quality materials, good experimental devices and proper procedures. The grain size was analyzed with the help of scanning electron microscope using RBS (Rutherford backscattering spectroscopy).

Keywords: CBD, CdS, CdTe, CSS

Procedia PDF Downloads 364

Authors: Songul Cinaroglu

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Regional planning in health has gained speed for developing countries in recent years. In Turkey, 89 different Public Hospital Unions (PHUs) were conducted based on provincial levels. In this study technical efficiencies of 89 PHUs were examined by using Data Envelopment Analysis (DEA) and machine learning techniques by dividing them into two clusters in terms of similarities of input and output indicators. Number of beds, physicians and nurses determined as input variables and number of outpatients, inpatients and surgical operations determined as output indicators. Before performing DEA, PHUs were grouped into two clusters. It is seen that the first cluster represents PHUs which have higher population, demand and service density than the others. The difference between clusters was statistically significant in terms of all study variables (p ˂ 0.001). After clustering, DEA was performed for general and for two clusters separately. It was found that 11% of PHUs were efficient in general, additionally 21% and 17% of them were efficient for the first and second clusters respectively. It is seen that PHUs, which are representing urban parts of the country and have higher population and service density, are more efficient than others. Random forest decision tree graph shows that number of inpatients is a determinative factor of efficiency of PHUs, which is a measure of service density. It is advisable for public health policy makers to use statistical learning methods in resource planning decisions to improve efficiency in health care.

Keywords: public hospital unions, efficiency, data envelopment analysis, random forest

Procedia PDF Downloads 127

Authors: Gokhan Sir, Muhammed Ergun, Onder Balioglu

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Nowadays, laundry dryers containing heaters and heat pumps are used to provide fast and efficient drying. In this system, as the drying capacity changes, the sensible and latent heat transfer rate in the evaporator changes. Therefore, the drying time measured for the unit capacity increases as the drying capacity decreases. The objective of this study is to investigate the evaporator efficiency according to load amount and textile type in hybrid heat pump dryers. Air side flow rate and system temperatures (air side and refrigeration side) were monitored instantly, and the specific moisture extraction rate (SMER), evaporator efficiency, and heat transfer mechanism between the textile and hybrid heat pump system were examined. Evaporator efficiency of heat pump dryers for cotton and synthetic based textile types in load amounts of 2, 5, 8 and 10 kg were investigated experimentally. As a result, the maximum evaporator efficiency (%72) was obtained in drying cotton and synthetic based textiles with a capacity of 5 kg; the minimum evaporator efficiency (%40) was obtained in drying cotton and synthetic based textiles with a capacity of 2 kg. The experimental study also reveals that capacity-dependent flow rate changes are the major factor for evaporator efficiency.

Keywords: evaporator, heat pump, hybrid, laundry dryer, textile

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Authors: Vipresh Mehta , Aman Abhishek, Jatin Batra, Gautam Iyer

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Huge amount of solar radiation reaching the earth can be harnessed to provide electricity through Photo voltaic (PV) panels. The solar PV is an exciting technology but suffers from low efficiency. A study on low efficiency in multi MW solar power plants reveals that the electric yield of the PV modules is reduced due to reflection of the irradiation from the sun and when a module’s temperature is elevated, as there is decrease in the voltage and efficiency. We intend to alter the structure of the PV system, We also intend to improve the efficiency of the Solar Photo Voltaic Panels by active cooling to reduce the temperature losses considerably and decrease reflection losses to some extent. Reflectors/concentrators and anti-reflecting coatings are also used to intensify the amount of output produced from the system. Apart from this, transformer-less Grid-tied Inverter. And also, a T-LCL immitance circuit is used to reduce the harmonics and produce a constant output from the entire system.

Keywords: PV panels, efficiency improvement, active cooling, quantum dots, organic-inorganic hybrid 3D panel, ground water tunneling

Procedia PDF Downloads 773

Authors: Anitha Narasimhan, Aarthy Anandan, Madhan Karky, C. N. Subalalitha

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Games can be the excellent tools for teaching a language. There are few e-learning games in Indian languages like word scrabble, cross word, quiz games etc., which were developed mainly for educational purposes. This paper proposes a Tamil word game called, “Porul”, which focuses on education as well as on players’ thinking and decision-making skills. Porul is a multiple choice based quiz game, in which the players attempt to answer questions correctly from the given multiple options that are generated using a unique algorithm called the Option Selection algorithm which explores the semantics of the question in various dimensions namely, synonym, rhyme and Universal Networking Language semantic category. This kind of semantic exploration of the question not only increases the complexity of the game but also makes it more interesting. The paper also proposes a Scoring Algorithm which allots a score based on the popularity score of the question word. The proposed game has been tested using 20,000 Tamil words.

Keywords: Porul game, Tamil word game, option selection, flash card, scoring, algorithm

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Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

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Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

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Authors: Chenhong Peng

Abstract:

Beijing, the capital city of China, is running out of water. The water resource per capita in Beijing is only 106 cubic meter, accounts for 5% of the country’s average level and less than 2% of the world average level. The tension between water supply and demand is extremely serious. For one hand, the surface and ground water have been over-exploited during the last decades; for the other hand, water demand keep increasing as the result of population and economic growth. There is a massive gap between water supply and demand. This paper will focus on addressing the water shortage in Beijing city by increasing water use efficiency in domestic sector. First, we will emphasize on the changing structure of water supply and demand in Beijing under the economic development and restructure during the last decade. Second, by analyzing the water use efficiency in agriculture, industry and domestic sectors in Beijing, we identify that the key determinant for addressing the water crisis is to increase the water use efficiency in domestic sector. Third, this article will explore the two primary causes for the water use inefficiency in Beijing: The ineffective water pricing policy and the poor water education and communication policy. Finally, policy recommendation will offered to improve the water use efficiency in domestic sector by making and implementing an effective water pricing policy and people-engaged water education and communication policy.

Keywords: Beijing, water use efficiency, domestic sector, water pricing policy, water education policy

Procedia PDF Downloads 542

Authors: Rawan A. Abdelrazeq, Ahmed M. Khalafallah, Nabil A. Kartam

Abstract:

Selection of competent contractors for construction projects is usually accomplished through competitive bidding or negotiated contracting in which the contract bid price is the basic criterion for selection. The evaluation of contractor’s safety performance is still not a typical criterion in the selection process, despite the existence of various safety prequalification procedures. There is a critical need for practical and automated systems that enable owners and decision makers to evaluate contractor safety performance, among other important contractor selection criteria. These systems should ultimately favor safety-conscious contractors to be selected by the virtue of their past good safety records and current safety programs. This paper presents an exploratory sequential mixed-methods approach to develop a framework for an automated decision support system that evaluates contractor safety performance based on a multitude of indicators and metrics that have been identified through a comprehensive review of construction safety research, and a survey distributed to domain experts. The framework is developed in three phases: (1) determining the indicators that depict contractor current and past safety performance; (2) soliciting input from construction safety experts regarding the identified indicators, their metrics, and relative significance; and (3) designing a decision support system using relational database models to integrate the identified indicators and metrics into a system that assesses and rates the safety performance of contractors. The proposed automated system is expected to hold several advantages including: (1) reducing the likelihood of selecting contractors with poor safety records; (2) enhancing the odds of completing the project safely; and (3) encouraging contractors to exert more efforts to improve their safety performance and practices in order to increase their bid winning opportunities which can lead to significant safety improvements in the construction industry. This should prove useful to decision makers and researchers, alike, and should help improve the safety record of the construction industry.

Keywords: construction safety, contractor selection, decision support system, relational database

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Authors: Pranas Baltrėnas, Dainius Paliulis

Abstract:

Cyclones are widely used for separating particles from gas in energy production objects. Efficiency of normal centrifugal air cleaning devices ranges from 85 to 90%, but weakness of many cyclones is low collection efficiency of particles less than 10 μm in diameter. Many factors have impact on cyclone efficiency – humidity, temperature, gas (air) composition, airflow velocity and etc. Many scientists evaluated only effect of origin and size of PM on cyclone efficiency. Effect of gas (air) composition and temperature on cyclone efficiency still demands contributions. Complex experimental research on efficiency of cylindrical eight-channel system with adjustable half-rings for removing fine dispersive particles (< 20 μm) was carried out. The impact of gaseous smoke components on removal of wood ashes was analyzed. Gaseous components, present in the smoke mixture, with the dynamic viscosity lower than that of same temperature air, decrease the d50 value, simultaneously increasing the overall particulate matter removal efficiency in the cyclone, i.e. this effect is attributed to CO2 and CO, while O2 and NO have the opposite effect. Air temperature influences the d50 value, an increase in air temperature yields an increase in d50 value, i.e. the overall particulate matter removal efficiency declines, the reason for this being an increasing dynamic air viscosity. At 120 °C temperature the d50 value is approximately 11.8 % higher than at air temperature of 20 °C. With an increase in smoke (gas) temperature from 20 °C to 50 °C, the aerodynamic resistance in a 1-tier eight-channel cylindrical cyclone drops from 1605 to 1380 Pa, from 1660 to 1420 Pa in a 2-tier eight-channel cylindrical cyclone, from 1715 to 1450 Pa in a 3-tier eight-channel cylindrical cyclone. The reason for a decline in aerodynamic resistance is the declining gas density. The aim of the paper is to analyze the impact of gaseous smoke components on the eight–channel cyclone with tangential inlet.

Keywords: cyclone, adjustable half-rings, particulate matter, efficiency, gaseous compounds, smoke

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Authors: K. Sathishkumar, V. Thiagarasu

Abstract:

Due to recent advances in DNA microarray technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs. Many scientists around the world use the advantage of this gene profiling to characterize complex biological circumstances and diseases. Microarray techniques that are used in genome-wide gene expression and genome mutation analysis help scientists and physicians in understanding of the pathophysiological mechanisms, in diagnoses and prognoses, and choosing treatment plans. DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. This work presents an analysis of several clustering algorithms proposed to deals with the gene expression data effectively. The existing clustering algorithms like Support Vector Machine (SVM), K-means algorithm and evolutionary algorithm etc. are analyzed thoroughly to identify the advantages and limitations. The performance evaluation of the existing algorithms is carried out to determine the best approach. In order to improve the classification performance of the best approach in terms of Accuracy, Convergence Behavior and processing time, a hybrid clustering based optimization approach has been proposed.

Keywords: microarray technology, gene expression data, clustering, gene Selection

Procedia PDF Downloads 325

Authors: Tao Song, Hao Cheng, Guangfeng Tian, Chuang Xu

Abstract:

An autonomous emergency braking system is an advanced driving assistance system that enables vehicle collision avoidance and pedestrian collision avoidance to improve vehicle safety. At present, because the pedestrian target is small, and the mobility is large, the pedestrian AEB system is faced with more technical difficulties and higher functional requirements. In this paper, a method of pedestrian target selection based on a variable width funnel is proposed. Based on the current position and predicted position of pedestrians, the relative position of vehicle and pedestrian at the time of collision is calculated, and different braking strategies are adopted according to the hazard level of pedestrian collisions. In the CNCAP standard operating conditions, comparing the method of considering only the current position of pedestrians and the method of considering pedestrian prediction position, as well as the method based on fixed width funnel and variable width funnel, the results show that, based on variable width funnel, the choice of pedestrian target will be more accurate and the opportunity of the intervention of AEB system will be more reasonable by considering the predicted position of the pedestrian target and vehicle's lateral motion.

Keywords: automatic emergency braking system, pedestrian target selection, TTC, variable width funnel

Procedia PDF Downloads 158