Search results for: efficient frontier

Authors: K. Thamizhmaran, Akshaya Devi Arivazhagan, M. Anitha

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On the case of most important systematic issue that must need to be solved in means of implementing a data transmission algorithm on the source of Mobile adhoc networks (MANETs). That is, how to save mobile nodes energy on meeting the requirements of applications or users as the mobile nodes are with battery limited. On while satisfying the energy saving requirement, hence it is also necessary of need to achieve the quality of service. In case of emergency work, it is necessary to deliver the data on mean time. Achieving quality of service in MANETs is also important on while. In order to achieve this requirement, Hence, we further implement the Energy-Aware routing protocol for system of Mobile adhoc networks were it being proposed, that on which saves the energy as on every node by means of efficiently selecting the mode of energy efficient path in the routing process by means of Enhanced AODV routing protocol.

Keywords: Ad-Hoc networks, MANET, routing, AODV, EAODV

Procedia PDF Downloads 370

Authors: Ekin Nurbaş

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One of the essential challenges in array signal processing, which has drawn enormous research interest over the past several decades, is estimating the direction of arrival (DOA) of plane waves impinging on an array of sensors. In recent years, the Compressive Sensing based DoA estimation methods have been proposed by researchers, and it has been discovered that the Compressive Sensing (CS)-based algorithms achieved significant performances for DoA estimation even in scenarios where there are multiple coherent sources. On the other hand, the Genetic Algorithm, which is a method that provides a solution strategy inspired by natural selection, has been used in sparse representation problems in recent years and provides significant improvements in performance. With all of those in consideration, in this paper, a method that combines the Genetic Algorithm (GA) and the Multi-Criteria Decision Making (MCDM) approaches for Direction of Arrival (DoA) estimation in the Compressive Sensing (CS) framework is proposed. In this method, we generate a multi-objective optimization problem by splitting the norm minimization and reconstruction loss minimization parts of the Compressive Sensing algorithm. With the help of the Genetic Algorithm, multiple non-dominated solutions are achieved for the defined multi-objective optimization problem. Among the pareto-frontier solutions, the final solution is obtained with the multiple MCDM methods. Moreover, the performance of the proposed method is compared with the CS-based methods in the literature.

Keywords: genetic algorithm, direction of arrival esitmation, multi criteria decision making, compressive sensing

Procedia PDF Downloads 147

Authors: Chaima Babi, Said Gadri

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The rapid increase in fake news continues to grow at a very fast rate; this requires implementing efficient techniques that allow testing the re-liability of online content. For that, the current research strives to illuminate the fake news problem using deep learning DL and machine learning ML ap-proaches. We have developed the traditional LSTM (Long short-term memory), and the bidirectional BiLSTM model. A such process is to perform a training task on almost of samples of the dataset, validate the model on a subset called the test set to provide an unbiased evaluation of the final model fit on the training dataset, then compute the accuracy of detecting classifica-tion and comparing the results. For the programming stage, we used Tensor-Flow and Keras libraries on Python to support Graphical Processing Units (GPUs) that are being used for developing deep learning applications.

Keywords: machine learning, deep learning, natural language, fake news, Bi-LSTM, LSTM, multiclass classification

Procedia PDF Downloads 95

Authors: Abrar Hussain, Kuen-Song Lin, Sayed Maeen Badshah, Jamshid Hussain

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The conversion of CO₂ into versatile, useful compounds such as fuels and other chemicals remains a challenging frontier in research, demanding the innovation of increasingly effective catalysts. In the present work, a catalyst-incorporating zirconium (Zr) modification within CuO–ZnO–Al₂O₃ (CZA) was synthesized via a co-precipitation method to convert CO₂ into methanol. Furthermore, bio-HZSM-5 was used to promote methanol dehydration to produce dimethyl ether (DME). We prepared the porous hierarchy bio-HZSM-5 with remarkable pore connectivity by utilizing an economical loofah sponge and rice husks as biotemplates. The synthesized catalysts were characterized using Field Emission Scanning Electron Microscopy (FE-SEM), X–ray diffraction (XRD), N₂ adsorption (BET), temperature-programmed desorption (NH₃-TPD) and thermogravimetric analysis (TGA). The Zr addition improved the performance of the CZZA catalyst as a structural promoter, leading to increased DME selectivity and total carbon conversion by enhancing active sites, surface area, and the synergistic interfaces between CuO and ZnO. The presence of silicon in the biomass, notably from the loofah sponge (0.016 wt %) and rice husks (8.3 wt %), also performed a pivotal role in the preparation of bio-HZSM-5. Furthermore, contrasted to the CZZA/com-ZSM-5 catalyst, the integration of CZZA with bio-HZSM-5-L bifunctional catalyst achieved the highest DME yield (12.1 %), DME selectivity (58.6%), CO₂ conversion (22.5%) at 280 °C and 30 bar. The payback time for 5 and 10-tons per day (5 and10-TPD) DME formation using the catalytic process of CO₂ from petrochemical refinery plant waste gas emissions was 2.98 and 2.44 years, respectively.

Keywords: Cost assessment, Dimethyl ether, low-cost bio-HZSM-5, CZZA catalyst, CO₂ hydrogenation

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Authors: Aya M. H. Eissa, Ayman H. A. Mahmoud

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When it comes to energy efficient thermal regulation system, natural systems do not only offer an inspirational source of innovative strategies but also sustainable and even regenerative ones. Using biomimetic design an energy efficient thermal regulation system can be developed. Although, conventional design process methods achieved fairly efficient systems, they still had limitations which can be overcome by using parametric design software. Accordingly, the main objective of this study is to apply and assess the efficiency of heat regulation strategies inspired from termite mounds in residential buildings’ thermal regulation system. Parametric design software is used to pave the way for further and more complex biomimetic design studies and implementations. A hot arid region is selected due to the deficiency of research in this climatic region. First, the analysis phase in which the stimuli, affecting, and the parameters, to be optimized, are set mimicking the natural system. Then, based on climatic data and using parametric design software Grasshopper, building form and openings height and areas are altered till settling on an optimized solution. Finally, an assessment of the efficiency of the optimized system, in comparison with a conventional system, is determined by firstly, indoors airflow and indoors temperature, by Ansys Fluent (CFD) simulation. Secondly by and total solar radiation falling on the building envelope, which was calculated using Ladybug, Grasshopper plugin. The results show an increase in the average indoor airflow speed from 0.5m/s to 1.5 m/s. Also, a slight decrease in temperature was noticed. And finally, the total radiation was decreased by 4%. In conclusion, despite the fact that applying a single bio-inspired heat regulation strategy might not be enough to achieve an optimum system, the concluded system is more energy efficient than the conventional ones as it aids achieving indoors comfort through passive techniques. Thus demonstrating the potential of parametric design software in biomimetic design.

Keywords: biomimicry, heat regulation systems, hot arid regions, parametric design, thermal comfort

Procedia PDF Downloads 294

Authors: Spartak Makovskyi, Volodymir Klochykhin, Valery Zakharchenko, Konstantyn Balushok, Eduard Tsyvirko, Anatoly Shalomeyev

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A highly efficient, cost-effective grain refinement technique for ML5 magnesium alloy with a commercially pure carbon nanopowder has been proposed. An experimental casting of testing specimens with incremental additions of a carbon nanopowder (0.001 - 0.1 wt.% ) was performed. It has been found that the carbon nanoparticle inoculation of the alloy structure is efficient in a narrow concentration range. The additions of 0.005-0.01 wt. % the grain refiner in the alloy resulted in a maximum increase of ductility properties (appr. Twofold) and improved tensile strength. However, further expansion of the grain refiner content led to the deterioration of the alloy's mechanical properties. In particular, the introduction of 0.1 wt.% of the nanocarbon and more caused internal defects in the metal. The carbon nanoparticle inoculation is a promising way of improving the properties of the Mg-Al-Zn alloys for critical lightweight aerospace applications on an industrial scale.

Keywords: carbon nanopowder, inoculation, melt, tensile strength

Procedia PDF Downloads 208

Authors: Rauf R. Hussein, Devon M. Ramey

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Integrating Ground Penetrating Radar (GPR) with Geographic Information Systems (GIS) can provide valuable insights for various applications, such as archaeology, transportation, and utility locating. Although there has been progress toward automating the integration of GPR data with GIS, fully automatic integration has not been achieved yet. Additionally, manually integrating GPR data with GIS can be a time-consuming and error-prone process. In this study, actual, real-world GPR applications are presented, and a software named GPR-GIS 10 is created to interactively extract subsurface targets from GPR radargrams and automatically integrate them into GIS. With this software, it is possible to quickly and reliably integrate the two techniques to create informative subsurface maps. The results indicated that automatic integration of GPR with GIS can be an efficient tool to map and view any subsurface targets in their appropriate location in a 3D space with the needed precision. The findings of this study could help GPR-GIS integrators save time and reduce errors in many GPR-GIS applications.

Keywords: GPR, GIS, GPR-GIS 10, drone technology, automation

Procedia PDF Downloads 92

Authors: Xiaoyan Wang, Zhongde Wang

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The issue of climate change, which originated in the middle of the twentieth century, has become a focus of international political, academic, and non-governmental organizations and public attention. In order to address the problems caused by climate change, the Chinese government has proposed a dual-carbon target and taken some national measures, such as ecological priority and green low-carbon development. These goals and measures are highly aligned with the values of the landscape architecture industry. This is an opportunity for the architectural discipline and the landscape architecture industry, so it is very necessary to summarize and analyze the hotspots related to climate change in the field of building science in China, which can assist the landscape architecture industry and related organizations in formulating more rational professional goals and taking actions that contribute to the betterment of societal, environmental development. Through the study, it is found as follows: firstly, after 20 years of rapid development, the research on climate change in the major architectural disciplines has shown a trend of diversification of research perspectives, interdisciplinary cross-cutting, and broadening of content; secondly, the research contents of landscape architecture focuses on the strategies to adapt to climate change, such as selection of urban tree species, the urban green infrastructure space layout, and the resilient city. Finally, in the future, climate change-based landscape architecture research will make the content system more diversified, but at the same time, it is still necessary to further deepen the research on quantitative methodology and construct scale systematic planning and design methods.

Keywords: climate change, landscape architecture, knowledge mapping, cites-pace

Procedia PDF Downloads 54

Authors: Peifei Zhu, Zisheng Li, Yasuki Kakishita, Mayumi Suzuki, Tomoaki Chono

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Segmentation of left ventricle (LV) from cardiac ultrasound images provides a quantitative functional analysis of the heart to diagnose disease. Active Shape Model (ASM) is a widely used approach for LV segmentation but suffers from the drawback that initialization of the shape model is not sufficiently close to the target, especially when dealing with abnormal shapes in disease. In this work, a two-step framework is proposed to improve the accuracy and speed of the model-based segmentation. Firstly, a robust and efficient detector based on Hough forest is proposed to localize cardiac feature points, and such points are used to predict the initial fitting of the LV shape model. Secondly, to achieve more accurate and detailed segmentation, ASM is applied to further fit the LV shape model to the cardiac ultrasound image. The performance of the proposed method is evaluated on a dataset of 800 cardiac ultrasound images that are mostly of abnormal shapes. The proposed method is compared to several combinations of ASM and existing initialization methods. The experiment results demonstrate that the accuracy of feature point detection for initialization was improved by 40% compared to the existing methods. Moreover, the proposed method significantly reduces the number of necessary ASM fitting loops, thus speeding up the whole segmentation process. Therefore, the proposed method is able to achieve more accurate and efficient segmentation results and is applicable to unusual shapes of heart with cardiac diseases, such as left atrial enlargement.

Keywords: hough forest, active shape model, segmentation, cardiac left ventricle

Procedia PDF Downloads 339

Authors: Asma Rebaya, Imen Amari, Kaouther Gasmi, Salem Hasnaoui

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Over these last years, the number of cores witnessed a spectacular increase in digital signal and general use processors. Concurrently, significant researches are done to get benefit from the high degree of parallelism. Indeed, these researches are focused to provide an efficient scheduling from hardware/software systems to multicores architecture. The scheduling process consists on statically choose one core to execute one task and to specify an execution order for the application tasks. In this paper, we describe an efficient scheduler that calculates the optimal number of cores required to schedule an application, gives a heuristic scheduling solution and evaluates its cost. Our proposal results are evaluated and compared with Preesm scheduler results and we prove that ours allows better scheduling in terms of latency, computation time and number of cores.

Keywords: computation time, hardware/software system, latency, optimization, multi-cores platform, scheduling

Procedia PDF Downloads 283

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 126

Authors: Salah Al-Din I. Badran, Samad Ahmadi, Dylan Menzies, Ismail Shahin

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This paper describes a new efficient blind source separation method; in this method we use a non-uniform filter bank and a new structure with different sub-bands. This method provides a reduced permutation and increased convergence speed comparing to the full-band algorithm. Recently, some structures have been suggested to deal with two problems: reducing permutation and increasing the speed of convergence of the adaptive algorithm for correlated input signals. The permutation problem is avoided with the use of adaptive filters of orders less than the full-band adaptive filter, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each sub-band than the input signal at full-band, and can promote better rates of convergence.

Keywords: Blind source separation, estimates, full-band, mixtures, sub-band

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Authors: Reham Al-Zahrani, Noura Aleisa

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The proliferation of Radio Frequency Identification (RFID) technology has raised concerns about system security, particularly regarding tag impersonation attacks. Regarding RFID systems, an appropriate authentication protocol must resist active and passive attacks. A tag impersonation occurs when an adversary's tag is used to fool an authenticating reader into believing it is a legitimate tag. This paper analyzed the security of the efficient, secure, and practical ultra-lightweight RFID Authentication Scheme (ESRAS). Then, the paper presents a comprehensive analysis of the Efficient, Secure, and Practical Ultra-Lightweight RFID Authentication Scheme (ESRAS) in the context of radio frequency identification (RFID) systems that employed the Scyther tool to examine the protocol's security against a tag impersonation attack.

Keywords: RFID, impersonation attack, authentication, ultra-lightweight protocols

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Authors: Agarana Michael C., Akinlabi Esther T., Pule Kholopane

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In order to sustain the advantages of an advanced manufacturing technique, such as laser sintering, minimization of total processing cost of the parts being produced is very important. An efficient time management would usually very important in optimal cost attainment which would ultimately result in an efficient advanced manufacturing process planning and control. During Laser Scanning Process Scanning (SLS) procedures it is possible to adjust various manufacturing parameters which are used to influence the improvement of various mechanical and other properties of the products. In this study, Modelling and mathematical analysis, including sensitivity analysis, of the laser sintering process time were carried out. The results of the analyses were represented with graphs, from where conclusions were drawn. It was specifically observed that achievement of optimal total scanning time is key for economic efficiency which is required for sustainability of the process.

Keywords: modeling and analysis, optimal planning and control, laser sintering process, scanning time

Procedia PDF Downloads 98

Authors: Rocco Lioy, Tom Dusseldorf, Aline Lehnen, Romain Reding

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A study concerning both the rentability and ecological performance of dairy production in Luxembourg was carried out for the years 2017, 2018 and 2019. The data of 100 dairy farms, referring to the Greenhouse gas emissions (ecology) and the profitability (economy) of dairy production, were evaluated, and the average was compared to the corresponding figures of 80 Luxembourgish dairy farms evaluated in the years 2014, 2015 and 2016. The ecological evaluation could confirm that farm efficiency (especially defined as the lowest ratio between used feedstuff and produced milk) is the key driver for significantly reducing the level of emissions in dairy farms. In both farm groups and in the two periods, the efficient farms show almost the same level of emissions per kg ECM (1,17 kg CO2-eq) in comparison with intensive farms (1,13 kg CO2-eq), and at the same time a by far lowest level of emissions related to the production surface (9,9 vs. 13,9 t CO2-eq/ha). Concerning the economic performances, it could be observed that in the years 2017, 2018 and 2019, the intensive farms (we define intensity in the first place in terms of produced milk pro ha) reached a higher profit (incomes minus costs, only consideration for subsidies) than the efficient farms (4,8 vs. 2,6 €-cent/kg ECM), in contradiction with the observation of the years 2014, 2015 and 2015 (1,5 vs. 3,7 €-cent/kg ECM). The most important reason for this divergent behavior was a change in income and cost structure in the considered periods. In the last period (2017, 2018 and 2019), the milk price was considerably higher than in the previous period, and the production costs were lower. This was of advantage for intensive farms, which produce the highest quantity of milk with a high amount of production means. In the period 2014, 2015 and 2016, with lower milk prices but comparable production costs, the advantage was with efficient farms. In conclusion, we expect that in the next future, when especially the production costs will presumably be much higher than in the last years, the profitableness of dairy farming will decrease. In this case, we assume that efficient farms will provide not only an ecologically but also an economically better performance than production-intensive farms. High milk prices and low production costs are no good incentives for carbon-smart farming.

Keywords: efficiency, intensity, dairy, emissions, prices, costs

Procedia PDF Downloads 97

Authors: Ahmad M. Awwad, Jehad Al-Sadi

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The star network is one of the promising interconnection networks for future high speed parallel computers, it is expected to be one of the future-generation networks. The star network is both edge and vertex symmetry, it was shown to have many gorgeous topological proprieties also it is owns hierarchical structure framework. Although much of the research work has been done on this promising network in literature, it still suffers from having enough algorithms for load balancing problem. In this paper we try to work on this issue by investigating and proposing an efficient algorithm for load balancing problem for the star network. The proposed algorithm is called Star Clustered Dimension Exchange Method SCDEM to be implemented on the star network. The proposed algorithm is based on the Clustered Dimension Exchange Method (CDEM). The SCDEM algorithm is shown to be efficient in redistributing the load balancing as evenly as possible among all nodes of different factor networks.

Keywords: load balancing, star network, interconnection networks, algorithm

Procedia PDF Downloads 319

Authors: Yao-Hong Tsai

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This paper presents an efficient fusion algorithm for iris images to generate stable feature for recognition in unconstrained environment. Recently, iris recognition systems are focused on real scenarios in our daily life without the subject’s cooperation. Under large variation in the environment, the objective of this paper is to combine information from multiple images of the same iris. The result of image fusion is a new image which is more stable for further iris recognition than each original noise iris image. A wavelet-based approach for multi-resolution image fusion is applied in the fusion process. The detection of the iris image is based on Adaboost algorithm and then local binary pattern (LBP) histogram is then applied to texture classification with the weighting scheme. Experiment showed that the generated features from the proposed fusion algorithm can improve the performance for verification system through iris recognition.

Keywords: image fusion, iris recognition, local binary pattern, wavelet

Procedia PDF Downloads 367

Authors: Kanya L. Khatri, Ashfaque A. Memon, Rod J. Smith, Shamas Bilal

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The viability and sustainability of crop production is currently threatened by increasing water scarcity. Water scarcity problems can be addressed through improved water productivity and the options usually presumed in this context are efficient water use and conversion of surface irrigation to pressurized systems. By replacing furrow irrigation with drip or centre pivot systems, the water efficiency can be improved by up to 30 to 45%. However, the installation and application of pumps and pipes, and the associated fuels needed for these alternatives increase energy consumption and cause significant greenhouse gas emissions. Hence, a balance between the improvement in water use and the potential increase in energy consumption is required keeping in view adverse impact of increased carbon emissions on the environment. When surface water is used, pressurized systems increase energy consumption substantially, by between 65% to 75%, and produce greenhouse gas emissions around 1.75 times higher than that of gravity based irrigation. With gravity based surface irrigation methods the energy consumption is assumed to be negligible. This study has shown that a novel real-time infiltration model REIP has enabled implementation of real-time optimization and control of surface irrigation and surface irrigation with real-time optimization has potential to bring significant improvements in irrigation performance along with substantial water savings of 2.92 ML/ha which is almost equivalent to that given by pressurized systems. Thus real-time optimization and control offers a modern, environment friendly and water efficient system with close to zero increase in energy consumption and minimal greenhouse gas emissions.

Keywords: pressurised irrigation, carbon emissions, real-time, environmentally-friendly, REIP

Procedia PDF Downloads 503

Authors: Shuyi Wu, Chuang Li, Quanshui Zheng, Luping Xu

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Stretching and snipping DNA molecule by microfluidic has important application value in gene analysis by lab on a chip. Movement, deformation and fragmenting of DNA in microfluidic are typical fluid-solid coupling problems. An efficient and common simulation system for researching the movement, deformation and fragmenting of DNA by microfluidic has not been well developed. In our study, Brownian dynamics-finite element method (BD-FEM) is used to simulate the dynamic process of stretching and fragmenting DNA by contraction flow. The shape and parameters of micro-channels are changed to optimize the stretching and fragmenting properties of DNA. Our results indicate that strain rate, resulting from contraction microchannel, is the main control parameter for stretching and fragmenting DNA. There is good consistency between the simulation data and previous experimental result about the single DNA molecule behavior and averaged fragmenting properties in this study. BD-FEM method is an efficient calculating tool to research stretching and fragmenting behavior of single DNA molecule and optimize microfluidic devices for manipulating, stretching and fragmenting DNA.

Keywords: fragmenting, DNA, microfluidic, optimize.

Procedia PDF Downloads 328

Authors: F. Gökgöz, M. E. Atmaca

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Electricity has an indispensable role in human daily life, technological development and economy. It is a special product or service that should be instantaneously generated and consumed. Sources of the world are limited so that effective and efficient use of them is very important not only for human life and environment but also for technological and economic development. Competitive electricity market is one of the important way that provides suitable platform for effective and efficient use of electricity. Besides benefits, it brings along some risks that should be carefully managed by a market player like Electricity Generation Company. Risk management is an essential part in market players’ decision making. In this paper, risk management through diversification is applied with the help of Value at Risk methods for case studies. Performance of optimal electricity sale solutions are measured and the portfolio performance has been evaluated via Sharpe-Ratio, and compared with conventional approach. Biennial historical electricity price data of Turkish Day Ahead Market are used to demonstrate the approach.

Keywords: electricity market, portfolio optimization, risk management, value at risk

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Authors: Yulia A. Kononova, Znang X. Ning

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Nowadays, architectural development is getting faster and faster. Nevertheless, modern architecture often does not meet all the points, which could help our planet to get better. As we know, people are spending an enormous amount of energy every day of their lives. Because of the uncontrolled energy usage, people have to increase energy production. As energy production process demands a lot of fuel sources, it courses a lot of problems such as climate changes, environment pollution, animals’ distinction, and lack of energy sources also. Nevertheless, nowadays humanity has all the opportunities to change this situation. Architecture is one of the most popular fields where it is possible to apply new methods of saving energy or even creating it. Nowadays we have kinds of buildings, which can meet new willing. One of them is energy effective buildings, which can save or even produce energy, combining several energy-saving principles. The main aim of this research is to provide information that helps to apply energy-saving methods while designing an environment-friendly building. The research methodology requires gathering relevant information from literature, building guidelines documents and previous research works in order to analyze it and sum up into a material that can be applied to energy-efficient building design. To mark results it should be noted that the usage of all the energy-saving methods applied to a design project of building results in ultra-low energy buildings that require little energy for space heating or cooling. As a conclusion it can be stated that developing methods of passive house design can decrease the need of energy production, which is an important issue that has to be solved in order to save planet sources and decrease environment pollution.

Keywords: accumulation, energy-efficient building, storage, superinsulation, passive house

Procedia PDF Downloads 262

Authors: Toufic Abd El-Latif Sadek

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The asphalt object represents the asphalted areas like roads, and the concrete object represents the concrete areas like concrete buildings. The efficient extraction of asphalt and concrete objects from one satellite thermal image occurred at a specific time, by preventing the gaps in times which give the close and same brightness values between asphalt and concrete, and among other objects. So that to achieve efficient extraction and then better analysis. Seven sample objects were used un this study, asphalt, concrete, metal, rock, dry soil, vegetation, and water. It has been found that, the best timing for capturing satellite thermal images to extract the two objects asphalt and concrete from one satellite thermal image, saving time and money, occurred at a specific time in different months. A table is deduced shows the optimal timing for capturing satellite thermal images to extract effectively these two objects.

Keywords: asphalt, concrete, satellite thermal images, timing

Procedia PDF Downloads 322

Authors: A. S. Salimzhanova, J. C. Sardinas, O. A. Yanovskaya

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The objective of this research work is to discuss the concept of green growth in the Republic of Kazakhstan introduced by its government in the National Sustainable Development Strategy with the objective of transition to a resource-efficient, green economy. We believe that emerging economies like Kazakhstan can pursue a cleaner and more efficient development path by introducing an environmental tax system based on resource consumption rather than only income and labor. The key issues discussed in this article are the eco-efficiency, which refers to closing the gap between economic and ecological efficiencies, and the structural change of the economy toward green growth. We also strongly believe that studying the experience of East Asian countries on green reform including eco-innovation and green solutions in business is essential to the case of Kazakhstan. All of these will raise the status of Kazakhstan to the level of one of the thirty developed countries over the next decades.

Keywords: economic strategy, green growth, green solutions, natural resource management, environmental tax system

Procedia PDF Downloads 279

Authors: Lipi Agarwal, Siddhant Patni

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The corporate organizations are seeking for the spaces that are energy efficient and maximize occupant health and productivity. Thus, designing workplaces that effectively steward resources and supports the health, the well-being of its occupants has become a dire need of the hour. The purpose of this paper is to understand the design approach for creating sustainable interiors in corporate offices. The objective is to identify the factors that aid energy efficient design and elevates the well-being in building and communities. The paper will employ qualitative methodology and undertake case study approach to comprehend the role of Leadership in Energy and Environmental Design (LEED) and WELL (a global rating system for health and wellness) in providing sustainable interiors. The findings help the design fraternity in designing a workspace that optimizes the use of resources and advances the human health inside the built environment. The paper suggests the framework that leads to interior environment which is sustainable in nature.

Keywords: corporate interiors, energy efficiency, LEED, sustainability, WELL, well-being

Procedia PDF Downloads 128

Authors: Farzad Sharifi, Raziyeh Shamsi

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In this paper, we obtain the projection of inefficient units in data envelopment analysis (DEA) in the case of stochastic inputs and outputs using the multi-objective programming (MOP) structure. In some problems, the inputs might be stochastic while the outputs are deterministic, and vice versa. In such cases, we propose molti-objective DEA-R model, because in some cases (e.g., when unnecessary and irrational weights by the BCC model reduces the efficiency score), an efficient DMU is introduced as inefficient by the BCC model, whereas the DMU is considered efficient by the DEA-R model. In some other case, only the ratio of stochastic data may be available (e.g; the ratio of stochastic inputs to stochastic outputs). Thus, we provide multi objective DEA model without explicit outputs and prove that in-put oriented MOP DEA-R model in the invariable return to scale case can be replacing by MOP- DEA model without explicit outputs in the variable return to scale and vice versa. Using the interactive methods for solving the proposed model, yields a projection corresponding to the viewpoint of the DM and the analyst, which is nearer to reality and more practical. Finally, an application is provided.

Keywords: DEA, MOLP, STOCHASTIC, DEA-R

Procedia PDF Downloads 398

Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

Procedia PDF Downloads 357

Authors: Yaacoub Tina, Youssef Roua, Radoi Emanuel, Burel Gilles

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Recently, low-complexity sub-Nyquist sampling schemes based on the Finite Rate of Innovation (FRI) theory have been introduced to sample parametric signals at minimum rates. The multichannel modulating waveforms (MCMW) is such an efficient scheme, where the received signal is mixed with an appropriate set of arbitrary waveforms, integrated and sampled at rates far below the Nyquist rate. In this paper, the MCMW scheme is adapted to the special case of ultra wideband (UWB) channel estimation, characterized by dense multipaths. First, an appropriate structure, which accounts for the bandpass spectrum feature of UWB signals, is defined. Then, a novel approach to decrease the number of processing channels and reduce the complexity of this sampling scheme is presented. Finally, the proposed concepts are validated by simulation results, obtained with real filters, in the framework of a coherent Rake receiver.

Keywords: coherent rake receiver, finite rate of innovation, sub-nyquist sampling, ultra wideband

Procedia PDF Downloads 256

Authors: Sarah M. Asar, Nabeel M. Elhady

Abstract:

Egypt’s current per capita water share indicates that the country suffers and has been suffering from water poverty. The abundant utilization of turfgrass in Egypt’s new urban settlements, the reliance on freshwater for irrigation, and the inadequate plant selection increase the water demand in such settlements. Decreasing the surface area of turfgrass by using alternative landscape features such as mulching, using ornamental low-maintenance plants, increasing pathways, etc., could significantly decrease the water demand of urban landscapes. The use of Ammochloa palaestina, Cenchrus crientalis (Oriental Fountain Grass), and Cistus parviflorus (with water demands of approximately 0.005m³/m²/day) as alternatives for Cynodon dactylon (0.01m³/m²/day), which is the most commonly used grass species in Egypt’s landscape, could decrease an area’s water demand by approximately 40-50%. Moreover, creating hydro-zones of similar water demanding plants would enable irrigation facilitation rather than the commonly used uniformed irrigation. Such a practice could further reduce water consumption by 15-20%. These results are based on a case-study analysis of one of Egypt’s relatively new urban settlements, Al-Rehab. Such results emphasize the importance of utilizing native, drought-tolerant vegetation in the urban landscapes of Egypt to reduce irrigation demands. Furthermore, proper implementation, monitoring, and maintenance of automated irrigation systems could be an important factor in a space’s efficient water use. As most new urban settlements in Egypt adopt sprinkler and drip irrigation systems, the lack of maintenance leads to the manual operation of such systems, and, thereby, excessive irrigation occurs.

Keywords: alternative landscape, native plants, efficient irrigation, low water demand

Procedia PDF Downloads 77

Authors: Sandesh Achar

Abstract:

The cloud computing industry has set new goals for better service delivery and deployment, so anyone can access services such as computation, application, and storage anytime. Cloud computing promises new possibilities for approaching sustainable solutions to deploy and advance their services in this distributed environment. This work explores energy-efficient approaches and how cloud-based architecture can reduce energy consumption levels amongst enterprises leveraging cloud computing services. Adopting cloud-based networking, database, and server machines provide a comprehensive means of achieving the potential gains in energy efficiency that cloud computing offers. In energy-efficient cloud computing, virtualization is one aspect that can integrate several technologies to achieve consolidation and better resource utilization. Moreover, the Green Cloud Architecture for cloud data centers is discussed in terms of cost, performance, and energy consumption, and appropriate solutions for various application areas are provided.

Keywords: greener cloud, cloud computing, energy efficiency, energy consumption, metadata tags, green cloud advisor

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Authors: Umesh Kumar Singh, Abhishek Raghuvanshi, Suyash Kumar Singh

Abstract:

As IoT networks gain popularity, they are more susceptible to security breaches. As a result, it is crucial to analyze the IoT platform as a whole from the standpoint of core security concepts. The Internet of Things relies heavily on wireless networks, which are well-known for being susceptible to a wide variety of attacks. This article provides an analysis of many techniques that may be used to identify vulnerabilities in the software and hardware associated with the Internet of Things (IoT). In the current investigation, an experimental setup is built with the assistance of server computers, client PCs, Internet of Things development boards, sensors, and cloud subscriptions. Through the use of network host scanning methods and vulnerability scanning tools, raw data relating to IoT-based applications and devices may be collected. Shodan is a tool that is used for scanning, and it is also used for effective vulnerability discovery in IoT devices as well as penetration testing. This article presents an efficient mitigation plan for encountering vulnerabilities in the Internet of Things.

Keywords: internet of things, security, privacy, vulnerability identification, mitigation plan

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