Search results for: landscape genetic

Authors: Antonin Ponsich, Eric Alfredo Rincon Garcia, Roman Anselmo Mora Gutierrez, Miguel Angel Gutierrez Andrade, Sergio Gerardo De Los Cobos Silva, Pedro Lara Velzquez

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The electoral zone design problem consists in redrawing the boundaries of legislative districts for electoral purposes in such a way that federal or state requirements are fulfilled. In Mexico, this process has been historically carried out by the National Electoral Institute (INE), by optimizing an integer nonlinear programming model, in which population equality and compactness of the designed districts are considered as two conflicting objective functions, while contiguity is included as a hard constraint. The solution technique used by the INE is a Simulated Annealing (SA) based algorithm, which handles the multi-objective nature of the problem through an aggregation function. The present work represents the first intent to apply a classical Multi-Objective Evolutionary Algorithm (MOEA), the second version of the Non-dominated Sorting Genetic Algorithm (NSGA-II), to this hard combinatorial problem. First results show that, when compared with the SA algorithm, the NSGA-II obtains promising results. The MOEA manages to produce well-distributed solutions over a wide-spread front, even though some convergence troubles for some instances constitute an issue, which should be corrected in future adaptations of MOEAs to the redistricting problem.

Keywords: multi-objective optimization, NSGA-II, redistricting, zone design problem

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Authors: Anuschka Curran, Sandra Barnard

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Coral reefs are of the most diverse and productive ecosystems on the planet, but due to the impact of climate change, these infrastructures are dying off primarily through coral bleaching. Coral bleaching can be described as the process by which zooxanthellae (algal endosymbionts) are expelled from the gastrodermal cavity of the respective coral host, causing increased coral whitening. The general consensus is that mass coral bleaching is due to the dysfunction of photosynthetic processes in the zooxanthellae as a result of the combined action of elevated temperature and light-stress. The question then is, do zooxanthellae have the potential to play a key role in the future of coral reef restoration through genetic engineering? The aim of this study is firstly to review the different zooxanthellae taxa and their traits with respect to environmental stress, and secondly, to review the information available on the protective mechanisms present in zooxanthellae cells when experiencing temperature fluctuations, specifically concentrating on heat shock proteins and the antioxidant stress response of zooxanthellae. The eight clades (A-H) previously recognized were redefined into seven genera. Different zooxanthellae taxa exhibit different traits, such as their photosynthetic stress responses to light and temperature. Zooxanthellae have the ability to determine the amount and type of heat shock proteins (hsps) present during a heat response. The zooxanthellae can regulate both the host’s respective hsps as well as their own. Hsps, generally found in genotype C3 zooxanthellae, such as Hsp70 and Hsp90, contribute to the thermal stress response of the respective coral host. Antioxidant activity found both within exposed coral tissue, and the zooxanthellae cells can prevent coral hosts from expelling their endosymbionts. The up-regulation of gene expression, which may mitigate thermal stress induction of any of the physiological aspects discussed, can ensure stable coral-zooxanthellae symbiosis in the future. It presents a viable alternative strategy to preserve reefs amidst climate change. In conclusion, despite their unusual molecular design, genetic engineering poses as a useful tool in understanding and manipulating variables and systems within zooxanthellae and therefore presents a solution that can ensure stable coral-zooxanthellae symbiosis in the future.

Keywords: antioxidant enzymes, genetic engineering, heat-shock proteins, Symbiodinium

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Authors: N. Guo, C. Xu, Z. C. Yang

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In order to ensure the high reliability of an aircraft, the accurate structural dynamics analysis has become an indispensable part in the design of an aircraft structure. Therefore, the structural finite element model which can be used to accurately calculate the structural dynamics and their transfer relations is the prerequisite in structural dynamic design. A dynamic finite element model updating method is presented to correct the uncertain parameters of the finite element model of a structure using measured modal parameters. The coordinate modal assurance criterion is used to evaluate the correlation level at each coordinate over the experimental and the analytical mode shapes. Then, the weighted summation of the natural frequency residual and the coordinate modal assurance criterion residual is used as the objective function. Moreover, the hybrid pattern search (HPS) optimization technique, which synthesizes the advantages of pattern search (PS) optimization technique and genetic algorithm (GA), is introduced to solve the dynamic FE model updating problem. A numerical simulation and a model updating experiment for GARTEUR aircraft model are performed to validate the feasibility and effectiveness of the present dynamic model updating method, respectively. The updated results show that the proposed method can be successfully used to modify the incorrect parameters with good robustness.

Keywords: model updating, modal parameter, coordinate modal assurance criterion, hybrid genetic/pattern search

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Authors: Azene Tesfaye, Yohannes Petros, Habtamu Zeleke

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To evaluate genetic variation among Ethiopian lentil, laboratory experiment were conducted to screen 12 accessions of lentil (Lens culinaris M.) for salt tolerance. Seeds of 12 Lentil accessions were grown at laboratory (Petri dish) condition with different levels of salinity (0, 2, 4, and 8 dSm-1 NaCl) for 4 weeks. The experimental design was completely randomized design (CRD) in factorial combination with three replications. Data analysis was carried out using SAS software. Average germination time, germination percentage, seedling shoot and root traits, seedling shoot and root weight were evaluated. The two way ANOVA for varieties revealed statistically significant variation among lentil accession, NaCl level and their interactions (p<0.001) with respect to the entire parameters. It was found that salt stress significantly delays germination rate and decreases germination percentage, shoot and root length, seedling shoot and root weight of lentil accessions. The degree of decrement varied with accessions and salinity levels. Accessions 36120, 9235 and 36004 were better salt tolerant than the other accessions. As the result, it is recommended to be used as a genetic resource for the development of lentil accession and other very salt sensitive crop with improved germination under salt stress condition.

Keywords: accession, germination, lentil, NaCl, screening, seedling stage

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Authors: P. K. Singhal, R. Naresh, V. Sharma

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This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: artificial bee colony algorithm, economic dispatch, unit commitment, wind power

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Authors: Muna A. Eissawi, Safaa Abed Elfataah, Haytham Hago, Fatima E Abukunna, Ibtisam Amin Goreish, Nahid Gornas

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The study examined and analyzed the genetic diversity of DRB1locus of exon 2 of major histocompatibility complex of Sudanese desert sheep using PCR-RFLP and DNA sequencing. Five hundred samples belonging to five ecotypes of Desert Sudanese sheep (Abrag (Ab), Ashgar (Ash), Hamari (H), Kabashi (K) and Watish (W) were included. Amplification of exon 2 of the DRB1 gene yielded (300bp) amplified product in different ecotypes. Nine different digestion patterns corresponding to Five distinct alleles were observed with Rsa1 digestion. Genotype (ag) was the most common among all ecotypes, with a percentage comprised (40.4 %). The Hardy-Weinberg equilibrium (HWE) test showed that the studied ecotypes have significantly deviated from the theoretical proportions of Rsa1 patterns; probability values of the Chi-square test for HWE for MHC-DRB1 gene in SDS were 0.00 in all ecotypes. The constructed phylogenetic tree revealed the relation of 22 Sudanese isolates with each other and showed the shared sequences with 47 published foreign sequences randomly selected from different geographic regions. The results of this study highlight the effect of heterozygosity of MHC genes of the Desert sheep of Sudan which may clarify some of genetic back ground of their disease resistance and adaptation to environment.

Keywords: desert sheep, MHC, Ovar-DRB1, polymerase chain reaction (PCR), restriction fragment length polymorphism (RFLP)

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Authors: Ambali Alade Odebowale, Andargachew Mekonnen Berhe, Haroldo T. Hattori, Andrey E. Miroshnichenko

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Solar thermophotovoltaic systems (STPV) have emerged as a promising solution to overcome the Shockley-Queisser limit, a significant impediment in the direct conversion of solar radiation into electricity using conventional solar cells. The STPV system comprises essential components such as an optical concentrator, selective emitter, and a thermophotovoltaic (TPV) cell. The pivotal element in achieving high efficiency in an STPV system lies in the design of a spectrally selective emitter or absorber. Traditional methods for designing and optimizing selective emitters are often time-consuming and may not yield highly selective emitters, posing a challenge to the overall system performance. In recent years, the application of machine learning techniques in various scientific disciplines has demonstrated significant advantages. This paper proposes a novel nanostructure composed of four-layered materials (SiC/W/SiO2/W) to function as a selective emitter in the energy conversion process of an STPV system. Unlike conventional approaches widely adopted by researchers, this study employs a machine learning-based approach for the design and optimization of the selective emitter. Specifically, a random forest algorithm (RFA) is employed for the design of the selective emitter, while the optimization process is executed using genetic algorithms. This innovative methodology holds promise in addressing the challenges posed by traditional methods, offering a more efficient and streamlined approach to selective emitter design. The utilization of a machine learning approach brings several advantages to the design and optimization of a selective emitter within the STPV system. Machine learning algorithms, such as the random forest algorithm, have the capability to analyze complex datasets and identify intricate patterns that may not be apparent through traditional methods. This allows for a more comprehensive exploration of the design space, potentially leading to highly efficient emitter configurations. Moreover, the application of genetic algorithms in the optimization process enhances the adaptability and efficiency of the overall system. Genetic algorithms mimic the principles of natural selection, enabling the exploration of a diverse range of emitter configurations and facilitating the identification of optimal solutions. This not only accelerates the design and optimization process but also increases the likelihood of discovering configurations that exhibit superior performance compared to traditional methods. In conclusion, the integration of machine learning techniques in the design and optimization of a selective emitter for solar thermophotovoltaic systems represents a groundbreaking approach. This innovative methodology not only addresses the limitations of traditional methods but also holds the potential to significantly improve the overall performance of STPV systems, paving the way for enhanced solar energy conversion efficiency.

Keywords: emitter, genetic algorithm, radiation, random forest, thermophotovoltaic

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Authors: Shohnaza Uzokova Beknazarovna

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This research study provides a comprehensive exploration of the Theory of Media Activity and its relevance as a conceptual framework for journalism education. The author offers a thorough review of existing literature on media activity theory, emphasizing its potential to enhance the understanding of the evolving media landscape and its implications for journalism practice. Through a combination of theoretical analysis and practical examples, the paper elucidates the ways in which the Theory of Media Activity can inform and enrich journalism education, particularly in relation to the interactive and participatory nature of contemporary media. The author presents a compelling argument for the integration of media activity theory into journalism curricula, emphasizing its capacity to equip students with a nuanced understanding of the reciprocal relationship between media producers and consumers. Furthermore, the paper discusses the implications of technological advancements on media production and consumption, highlighting the need for journalism educators to prepare students to navigate and contribute to the future of journalism in a rapidly changing media environment. Overall, this research paper offers valuable insights into the potential benefits of embracing the Theory of Media Activity as a foundational framework for journalism education. Its thorough analysis and practical implications make it a valuable resource for educators, researchers, and practitioners seeking to enhance journalism pedagogy in response to the dynamic nature of contemporary media.

Keywords: theory of media activity, journalism education, media landscape, media production, media consumption, interactive media, participatory media, technological advancements, media producers, media consumers, journalism practice, contemporary media environment, journalism pedagogy, media theory, media studies

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Authors: Jingqian Xiao

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The rapid wave of urbanization triggered by China’s economic growth over the past few decades has inevitably impacted the country’s educational landscape. Educational spaces in China shifted during the 1990s when, due to the government’s tax reforms, large numbers of rural schools were abolished or merged with urban schools, resulting in an “urbanization” of school content and values. While urbanized education is now the status quo, there is as yet no literature review, to our best knowledge, that comprehensively summarizes academic work on this phenomenon. Besides, most research on Chinese educational urbanization relies on basic policy deductions, and there is room for improvement in both the quality and quantity of empirical research on this topic. This paper, therefore, reviews relevant literature on educational urbanization in China from three interrelated factors that shape educational inequality between urban and rural China, namely the urbanization in educational space, school content, and educational values. Results find that the main discussion on Chinese educational urbanization often addresses how Chinese rural education can be improved by reforming the urbanization model to revitalize rural society. While the complete urbanization of Chinese education does not seem feasible, the rapidly changing nature of China’s development patterns and political landscape means the course of Chinese education may shift at any time. When the government does decide to fulfill its intentions to improve the countryside, many formerly dilapidated rural schools may be revived, but for the moment, both rural and urban education in China suffers from governmental neglect. In addition, the breakout of COVID-19, which led to a sudden spread of online education that reopened the gap between the educational conditions and the cultural capital of families in rural and urban areas, has also posed new challenges for China’s attempts to resolve conflicting interests between urban and rural schools and promote educational equality.

Keywords: Chinese education, educational inequality, rural and urban education, urbanization in education

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Authors: Sara Jelodarian

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Organic agriculture is a kind of living and dynamic agriculture that was introduced in the early 20^th century. The fundamental basis for organic agriculture is in harmony with nature. This version of farming emphasizes removing growth hormones, chemical fertilizers, toxins, radiation, genetic manipulation and instead, integration of modern scientific techniques (such as biologic and microbial control) that leads to the production of healthy food and the preservation of the environment and use of agricultural products such as forage and manure. Supports from governments for the markets producing organic products and taking advantage of the experiences from other successful societies in this field can help progress the positive and effective aspects of this technology, especially in developing countries. This research proves that till 2030, 25% of the global agricultural lands would be covered by organic farming. Consequently Iran, due to its rich genetic resources and various climates, can be a pioneer in promoting organic products. In addition, for sustainable farming, blend of organic and other innovative systems is needed. Important limitations exist to accept these systems, also a diversity of policy instruments will be required to comfort their development and implementation. The paper was conducted to results of compilation of reports, issues, books, articles related to the subject with library studies and research. Likewise we combined experimental and survey to get data.

Keywords: develop, production markets, progress, strategic role, technology

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Authors: Omar Bouhassoun, Cristian Garrido, César Hueso

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The radiation shielding design is an optimization problem with multiple -constrained- objective functions (radiation dose, weight, price, etc.) that depend on several parameters (material, thickness, position, etc.). The classical approach for shielding design consists of a brute force trial-and-error process subject to previous designer experience. Therefore, the result is an empirical solution but not optimal, which can degrade the overall performance of the shielding. In order to automate the shielding design procedure, the IDOM Shielding Optimization Tool (ISOT) has been developed. This software combines optimization algorithms with the capabilities to read/write input files, run calculations, as well as parse output files for different radiation transport codes. In the first stage, the software was established to adjust the input files for two well-known Monte Carlo codes (MCNP and Serpent) and optimize the result (weight, volume, price, dose rate) using multi-objective genetic algorithms. Nevertheless, its modular implementation easily allows the inclusion of more radiation transport codes and optimization algorithms. The work related to the development of ISOT and its verification on a simple 3D multi-layer shielding problem using both MCNP and Serpent will be presented. ISOT looks very promising for achieving an optimal solution to complex shielding problems.

Keywords: optimization, shielding, nuclear, genetic algorithm

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Authors: Aleksandr Nagay, Gulnoz Khamidullayeva

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It is known that an unbalanced intake of salt (NaCI), lifestyle and genetic predisposition to pathology is a key component of the risk and the development of essential hypertension (EH). Purpose: To study the relationship between salt-sensitivity and blood pressure (BP) on systolic (SBP) and diastolic (DBP) blood pressure, depending on the C825T polymorphism of GNB3 in individuals of Uzbek nationality with EH. Method: studied 148 healthy and 148 patients with EH with I-II degree (WHO/ISH, 2003) with disease duration 6,5±1,3 years. Investigation of the gene GNB3 was produced by PCR-RFLP method. Determination of salt-sensitivity was performed by the method of R. Henkin. Results: For a comparative analysis of BP, the groups with carriage of CТ and TT genotypes were combined. The analysis showed that carriers of CC genotype and low salt-sensitivity were determined by higher levels of SBP compared with carriers of CT and TT genotypes, and low salt-sensitivity of SBP: 166,2±4,3 against 158,2±9,1 mm Hg (p=0,000). A similar analysis on the values of DBP also showed significantly higher values of blood pressure in carriers of CC genotype DBP: 105,8±10,6 vs. 100,5±7,2 mm Hg, respectively (p=0,001). The average values of SBP and DBP in groups with carriers of CC genotype at medium or high salt-sensitivity in comparison with carriers of CT or TT genotype did not differ statistically SBP: 165,0±0,1 vs. 160,0±8,6 mm Hg (p=0,275) and DBP: 100,1±0,1 vs. 101,6±7,6 mm Hg (p=0,687), respectively. Conclusion: It is revealed that in patients with EH CC genotype of the gene GNB3 given salt-sensitivity has a negative effect on blood pressure profile. Since patients with EH with the CC genotype of GNB3 gene with low-salt taste sensitivity is determined by a higher level of blood pressure, both on SBP and DBP.

Keywords: salt sensitivity, essential hypertension EH, blood pressure BP, genetic predisposition

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Authors: Rouhallah Bagheri, Morteza Mahmoudi, Hadi Moheb-Alizadeh

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This paper aims at developing a multi-objective model for supplier selection and order allocation problem in stochastic environment, where purchasing cost, percentage of delivered items with delay and percentage of rejected items provided by each supplier are supposed to be stochastic parameters following any arbitrary probability distribution. In this regard, dependent chance programming is used which maximizes probability of the event that total purchasing cost, total delivered items with delay and total rejected items are less than or equal to pre-determined values given by decision maker. The abovementioned stochastic multi-objective programming problem is then transformed into a stochastic single objective programming problem using minimum deviation method. In the next step, the further problem is solved applying a genetic algorithm, which performs a simulation process in order to calculate the stochastic objective function as its fitness function. Finally, the impact of stochastic parameters on the given solution is examined via a sensitivity analysis exploiting coefficient of variation. The results show that whatever stochastic parameters have greater coefficients of variation, the value of the objective function in the stochastic single objective programming problem is deteriorated.

Keywords: supplier selection, order allocation, dependent chance programming, genetic algorithm

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Authors: Valentina Adduci

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The developing research aims to define in general the criteria of environmental sustainability of rural buildings in Puglia and particularly in the manor farm. The main part of the study analyzes the relationship / dependence between the rural building and the landscape which, after many stratifications, results clearly identified and sometimes also characterized in a positive way. The location of the manor farm, in fact, is often conditioned by the infrastructural network and by the structure of the agricultural landscape. The manor farm, without the constraints due to the urban pattern’s density, was developed in accordance with a logical settlement that gives priority to the environmental aspects. These vernacular architectures are the most valuable example of how our ancestors have planned their dwellings according to nature. The 237 farms, analysis’ object, have been reported in cartography through the GIS system; a symbol has been assigned to each of them to identify the architectural typology and a different color for the historical period of construction. A datasheet template has been drawn up, and it has made possible a deeper understanding of each manor farm. This method provides a faster comparison of the most recurring characters in all the considered buildings, except for those farms which benefited from special geographical conditions, such as proximity to the road network or waterways. Below there are some of the most frequently constants derived from the statistical study of the examined buildings: southeast orientation of the main facade; placement of the sheep pen on the ground tilted and exposed to the south side; larger windowed surface on the south elevation; smaller windowed surface on the north elevation; presence of shielding vegetation near the more exposed elevations to the solar radiation; food storage’s rooms located on the ground floor or in the basement; animal shelter located in north side of the farm; presence of tanks and wells, sometimes combined with a very accurate channeling storm water system; thick layers of masonry walls, inside of which were often obtained hollow spaces to house stairwells or depots for the food storage; exclusive use of local building materials. The research aims to trace the ancient use of bioclimatic constructive techniques in the Apulian rural architecture and to define those that derive from an empirical knowledge and those that respond to an already encoded design. These constructive expedients are especially useful to obtain an effective passive cooling, to promote the natural ventilation and to built ingenious systems for the recovery and the preservation of rainwater and are still found in some of the manor farms analyzed, most of them are, today, in a serious state of neglect.

Keywords: bioclimatic devices, farmstead, rural landscape, sustainability

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Authors: Marina Nechayeva, Malgorzata Marciniak, Vladimir Przhebelskiy, A. Dragutan, S. Lamichhane, S. Oikawa

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This presentation is a progress report on a faculty-student research collaboration at CUNY LaGuardia Community College (LaGCC) aimed at designing a small horizontal axis wind turbine optimized for the wind patterns on the roof of our campus. Our project combines statistical and engineering research. Our wind modeling protocol is based upon a recent wind study by a faculty-student research group at MIT, and some of our blade design methods are adopted from a senior engineering project at CUNY City College. Our use of genetic algorithms has been inspired by the work on small wind turbines’ design by David Wood. We combine these diverse approaches in our interdisciplinary project in a way that has not been done before and improve upon certain techniques used by our predecessors. We employ several estimation methods to determine the best fitting parametric probability distribution model for the local wind speed data obtained through correlating short-term on-site measurements with a long-term time series at the nearby airport. The model serves as a foundation for engineering research that focuses on adapting and implementing genetic algorithms (GAs) to engineering optimization of the wind turbine design using Blade Element Momentum Theory. GAs are used to create new airfoils with desirable aerodynamic specifications. Small scale models of best performing designs are 3D printed and tested in the wind tunnel to verify the accuracy of relevant calculations. Genetic algorithms are applied to selected airfoils to determine the blade design (radial cord and pitch distribution) that would optimize the coefficient of power profile of the turbine. Our approach improves upon the traditional blade design methods in that it lets us dispense with assumptions necessary to simplify the system of Blade Element Momentum Theory equations, thus resulting in more accurate aerodynamic performance calculations. Furthermore, it enables us to design blades optimized for a whole range of wind speeds rather than a single value. Lastly, we improve upon known GA-based methods in that our algorithms are constructed to work with XFoil generated airfoils data which enables us to optimize blades using our own high glide ratio airfoil designs, without having to rely upon available empirical data from existing airfoils, such as NACA series. Beyond its immediate goal, this ongoing project serves as a training and selection platform for CUNY Research Scholars Program (CRSP) through its annual Aerodynamics and Wind Energy Research Seminar (AWERS), an undergraduate summer research boot camp, designed to introduce prospective researchers to the relevant theoretical background and methodology, get them up to speed with the current state of our research, and test their abilities and commitment to the program. Furthermore, several aspects of the research (e.g., writing code for 3D printing of airfoils) are adapted in the form of classroom research activities to enhance Calculus sequence instruction at LaGCC.

Keywords: engineering design optimization, genetic algorithms, horizontal axis wind turbine, wind modeling

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Authors: Sela Adjei

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This research delves into the nuanced representations of queerness in Ghana, presented through photographs, illustrations, film and music videos on social media and streaming platforms. The study focuses on the works of five Ghanaian artists (Va-Bene Elikem Fiatsi, Angel Maxine, Josephine Kuuire, Bright Ackwerh and Philip Nee Whang) within the context of Ghana's evolving media landscape. Of primary concern is a need to uncover the various aspects of queerness captured within the distinct artistic expressions of these five creatives. This study adopts a qualitative approach by analyzing artistic expressions of queerness in Ghana’s digital media spaces. Content analysis and visual semiotics served as the guiding tools to discuss and decipher the nuanced messages embedded in their works, considering both the visual and narrative aspects. This dual approach takes into account both the visual aesthetics and narrative elements, enhancing our understanding of the complex interplay between queerness and gender representation in the media. This study's contribution is twofold. First, it enriches the discourse surrounding queerness as portrayed by artists within Ghana's vibrant media landscape and situates their works within the broader discourse of global gender identities. Secondly, analyzing the creative output of these five Ghanaian artists broadens our understanding of gender minorities and the various challenges they face in Ghana (currently debating in parliament to pass an anti-LGBTQ+ bill that criminalizes activities related to gender minority groups). While focusing on the intersection of queerness, art, and gender identities, the reflections in this study challenge existing narratives and offer fresh insights into how these artists navigate and challenge societal norms through their creative expressions.

Keywords: queer, film, representation, streaming, media, gender

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Authors: Ramesh Joshi, Nisha Khatik

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Murraya koenigii (L.) Spreng locally known as “Curry patta” or “Meetha neem” belonging to the family Rutaceae that grows wildly in Southern Asia. Its aromatic leaves are commonly used as the raw material for traditional medicinal formulations in India. The leaves contain essential oil and also used as a condiment. Several monomeric and binary carbazol alkaloids present in the various plant parts. These alkaloids have been reported to possess anti-microbial, mosquitocidal, topo-isomerase inhibition and antioxidant properties. Some of the alkaloids reported in this plant have showed anti carcinogenic and anti-diabetic properties. The conventional method of propagation of this tree is limited to seeds only, which retain their viability for only a short period. Hence, a biotechnological approach might have an advantage edging over traditional breeding as well as the genetic improvement of M. koenigii within a short period. The development of a reproducible regeneration protocol is the prerequisite for ex situ conservation and micropropagation. An efficient protocol for high frequency regeneration of in vitro plants of Murraya koenigii via different explants such as- nodal segments, intermodal segments, leaf, root segments, hypocotyle, cotyledons and cotyledonary node explants is described. In the present investigation, assessment of clonal fidelity in the micropropagated plantlets of Murraya koenigii was attempted using RAPD and ISSR markers at different pathways of plant tissue culture technique. About 20 ISSR and 40 RAPD primers were used for all the samples. Genomic DNA was extracted by CTAB method. ISSR primer were found to be more suitable as compared to RAPD for the analysis of clonal fidelity of M. koenigii. The amplifications however, were finally performed using RAPD, ISSR markers owing to their better performance in terms of generation of amplification products. In RAPD primer maximum 75% polymorphism was recorded in OPU-2 series which exhibited out of 04 scorable bands, three bands were polymorphic with a band range of size 600-1500 bp. In ISSR primers the UBC 857 showed 50% polymorphism with 02 band were polymorphic of band range size between 400-1000 bp.

Keywords: genetic fidelity, Murraya koenigii, aromatic plants, ISSR primers

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Authors: Alvaro Javier Ortega

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A large number of companies face the challenge of matching highly-skilled professionals to high-end positions by human resource deployment professionals. However, when the professional list and tasks to be matched are larger than a few dozens, this process result is far from optimal and takes a long time to be made. Therefore, an automated assignment algorithm for this workforce management problem is needed. The majority of companies are divided into several sectors or departments, where trained employees with different experience levels deal with a large number of tasks daily. Also, the execution order of all tasks is of mater consequence, due to some of these tasks just can be run it if the result of another task is provided. Thus, a wrong execution order leads to large waiting times between consecutive tasks. The desired goal is, therefore, creating accurate matches and a near-optimal execution order that maximizes the number of tasks performed and minimizes the idle time of the expensive skilled employees. The problem described before can be model as a mixed-integer non-linear programming (MINLP) as it will be shown in detail through this paper. A large number of MINLP algorithms have been proposed in the literature. Here, genetic algorithm solutions are considered and a comparison between two different mutation approaches is presented. The simulated results considering different complexity levels of assignment decisions show the appropriateness of the proposed model.

Keywords: employees, genetic algorithm, industry management, workforce

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Authors: Mamta Rana, K. K. Singh, Nisha Kumari

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The simulation models with its soil-weather-plant atmosphere interacting system are important tools for assessing the crops in changing climate conditions. The CERES-Wheat & Rice vs. 4.6 DSSAT was calibrated and evaluated for one of the major producers of wheat and rice state- Haryana, India. The simulation runs were made under irrigated conditions and three fertilizer applications dose of N-P-K to estimate crop yield and other growth parameters along with the phenological development of the crop. The genetic coefficients derived by iteratively manipulating the relevant coefficients that characterize the phenological process of wheat and rice crop to the best fit match between the simulated and observed anthesis, physological maturity and final grain yield. The model validated by plotting the simulated and remote sensing derived LAI. LAI product from remote sensing provides the edge of spatial, timely and accurate assessment of crop. For validating the yield and yield components, the error percentage between the observed and simulated data was calculated. The analysis shows that the model can be used to simulate crop yield and yield components for wheat and rice cultivar under different management practices. During the validation, the error percentage was less than 10%, indicating the utility of the calibrated model for climate risk assessment in the selected region.

Keywords: simulation model, CERES-wheat and rice model, crop yield, genetic coefficient

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Authors: Richard G. Boakye, Dara A Stanley, Mathavan Vickneswaran, Blanaid White

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The cultivation of cocoa (Theobroma cocoa), an important cash crop that contributes immensely towards the economic growth of several Western African countries, depends almost entirely on pesticide application owing to the plant’s vulnerability to pest and disease attacks. However, the extent to which pesticides inputted for cocoa cultivation impact bees and bee products has rarely received attention in research. Through this study, the effects of pesticides applied for cocoa cultivation on honey in Ghana were examined by evaluating honey samples from cocoa and forest ecosystems in Ghana. An analysis of five honey samples from each land use type confirmed pesticide contaminants from these land use types at measured concentrations for acetamiprid (0.051mg/kg); imidacloprid (0.004-0.02 mg/kg), thiamethoxam (0.013-0.017 mg/kg); indoxacarb (0.004-0.045 mg/kg) and sulfoxaflor (0.004-0.026 mg/kg). None of the observed pesticide concentrations exceeded EU maximum residue levels, indicating no compromise of the honey quality for human consumption. However, from the results, it could be inferred that toxic effects on bees may not be ruled out because observed concentrations largely exceeded the threshold of 0.001 mg/kg at which sublethal effects on bees have previously been reported. One of the most remarkable results to emerge from this study is the detection of imidacloprid in all honey samples analyzed, with sulfoxaflor and thiamethoxam also being detected in 93% and 73% of the honey samples, respectively. This suggests the probable prevalence of pesticide use in the landscape. However, the conclusions reached in this study should be interpreted within the scope of pesticide applications within Bia West District and not necessarily extended to other cocoa-producing districts in Ghana. Future studies should therefore include multiple cocoa-growing districts and other non-cocoa farming landscapes. Such an approach can give a broader outlook on pesticide residues in honey produced in Ghana.

Keywords: honey, cocoa, pesticides, bees, land use, landscape, residues, Ghana

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Authors: Pankaj K. Jha, Ajeet K. Jha, Pravin Mishra

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Goat raising is a popular livestock sub-commodity of mixed farming system in Nepal. Besides food and nutritional security, it has an important role in the economy of many peoples. Goat breeding through AI is commonly practiced worldwide. It is a very basic tool to speed up genetic improvement and increase productivity. For the goat genetic improvement program, the government of Nepal has imported some specialized exotic goat breeds and semen. Some progress has been made in the initiation of selective breeding within the local breeds and practice of AI with imported semen. Importance of AI in goats has drawn more attention among goat farmers. However, importing semen is not a permanent solution at national level; rather, it is more important to develop and establish its own frozen semen production technique. Semen quality and its relationship with fertility are said to be a major concern in animal production, hence accurate measurement of semen fertilizing potential is of great importance. The survivability of sperm cells depends on semen quality. Survivability of sperm cells is assessed through visual and microscopic evaluation of spermatozoal progressive motility and morphology. In Nepal, there is lack of scientific information on seminal attributes of buck semen, its dilution, cooling and freezing technique under management conditions of Nepal. Therefore, the objective of this review was to provide brief information about breeding system, semen production and artificial insemination in Nepalese goat.

Keywords: artificial insemination, goat, Nepal, semen

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Authors: Tohid Rahimi, Yahya Naderi, Babak Yousefi, Seyed Hossein Hoseini

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Today’s modern interconnected power system is highly complex in nature. In this, one of the most important requirements during the operation of the electric power system is the reliability and security. Power and frequency oscillation damping mechanism improve the reliability. Because of power system stabilizer (PSS) low speed response against of major fault such as three phase short circuit, FACTs devise that can control the network condition in very fast time, are becoming popular. However, FACTs capability can be seen in a major fault present when nonlinear models of FACTs devise and power system equipment are applied. To realize this aim, the model of multi-machine power system with FACTs controller is developed in MATLAB/SIMULINK using Sim Power System (SPS) blockiest. Among the FACTs device, Static synchronous series compensator (SSSC) due to high speed changes its reactance characteristic inductive to capacitive, is effective power flow controller. Tuning process of controller parameter can be performed using different method. However, Genetic Algorithm (GA) ability tends to use it in controller parameter tuning process. In this paper, firstly POD controller is used to power oscillation damping. But in this station, frequency oscillation dos not has proper damping situation. Therefore, FOD controller that is tuned using GA is using that cause to damp out frequency oscillation properly and power oscillation damping has suitable situation.

Keywords: power oscillation damping (POD), frequency oscillation damping (FOD), Static synchronous series compensator (SSSC), Genetic Algorithm (GA)

Procedia PDF Downloads 476

Authors: Atul C. Mahajan, A. K. Chakravarty, V. Jamuna, C. S. Patil, Neeraj Kashyap, Bharti Deshmukh, Vijay Kumar

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The selection of Sahiwal bulls on the basis of dams best lactation milk yield under breeding programme in herd of the country neglecting fertility traits leads to deterioration in their performances and economy. The goal of this study was to explore polymorphism of CRISP2 gene and their association with semen traits (Post Thaw Motility, Hypo-osmotic Swelling Test, Acrosome Integrity, DNA Fragmentation and capacitation status), scrotal circumference, expected predicted difference (EPD) for milk yield and fertility. Sahiwal bulls included in present study were 60 bulls used in breeding programme as well as 50 young bulls yet to be included in breeding programme. All the Sahiwal bulls were found to be polymorphic for CRISP2 gene (AA, AG and GG) present within exon 7 to the position 589 of CRISP2 mRNA by using PCR-SSCP and Sequencing. Semen analysis were done on 60 breeding bulls frozen semen doses pertaining to four season (winter, summer, rainy and autumn). The scrotal circumference was measured from existing Sahiwal breeding bulls in the herd (n=47). The effect of non-genetic factors on reproduction traits were studied by least-squares technique and the significant difference of means between subclasses of season, period, parity and age group were tested. The data were adjusted for the significant non-genetic factors to remove the differential environmental effects. The adjusted data were used to generate traits like Waiting Period (WP), Pregnancy Rate (PR), Expected Predicted Difference (EPD) of fertility, respectively. Genetic and phenotypic parameters of reproduction traits were estimated. The overall least-squares means of Age at First Calving (AFC), Service Period (SP) and WP were estimated as 36.69 ± 0.18 months, 120.47 ± 8.98 days and 79.78 ± 3.09 days respectively. Season and period of birth had significant effect (p < 0.01) on AFC. AFC was highest during autumn season of birth followed by summer, winter and rainy. Season and period of calving had significant effect (p < 0.01) on SP and WP of sahiwal cows. The WP for Sahiwal cows was standardized based on four developed predicted model for pregnancy rate 42, 63, 84 and 105 days using all lactation records. The WP for Sahiwal cows were standardized as 42 days. A selection criterion was developed for Sahiwal breeding bulls and young Sahiwal bulls on the basis of EPD of fertility. The genotype has significant effect on expected predicted difference of fertility and some semen parameters like post thaw motility and HOST. AA Genotype of CRISP2 gene revealed better EPD for fertility than EPD of milk yield. AA genotype of CRISP2 gene has higher scrotal circumference than other genotype. For young Sahiwal bulls only AA genotypes were present with similar patterns. So on the basis of association of genotype with seminal traits, EPD of milk yield and EPD for fertility status, AA and AG genotype of CRISP2 gene was better for higher fertility in Sahiwal bulls.

Keywords: expected predicted difference, fertility, sahiwal, waiting period

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Authors: Thiago Ribeiro de Alencar, Jacyro Gramulia Junior, Patricia Teixeira Leite

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The area of the electricity sector that deals with energy needs by the hydroelectric in a coordinated manner is called Operation Planning of Hydrothermal Power Systems (OPHPS). The purpose of this is to find a political operative to provide electrical power to the system in a given period, with reliability and minimal cost. Therefore, it is necessary to determine an optimal schedule of generation for each hydroelectric, each range, so that the system meets the demand reliably, avoiding rationing in years of severe drought, and that minimizes the expected cost of operation during the planning, defining an appropriate strategy for thermal complementation. Several optimization algorithms specifically applied to this problem have been developed and are used. Although providing solutions to various problems encountered, these algorithms have some weaknesses, difficulties in convergence, simplification of the original formulation of the problem, or owing to the complexity of the objective function. An alternative to these challenges is the development of techniques for simulation optimization and more sophisticated and reliable, it can assist the planning of the operation. Thus, this paper presents the development of a computational tool, namely Hydro-IA for solving optimization problem identified and to provide the User an easy handling. Adopted as intelligent optimization technique is Genetic Algorithm (GA) and programming language is Java. First made the modeling of the chromosomes, then implemented the function assessment of the problem and the operators involved, and finally the drafting of the graphical interfaces for access to the User. The results with the Genetic Algorithms were compared with the optimization technique nonlinear programming (NLP). Tests were conducted with seven hydroelectric plants interconnected hydraulically with historical stream flow from 1953 to 1955. The results of comparison between the GA and NLP techniques shows that the cost of operating the GA becomes increasingly smaller than the NLP when the number of hydroelectric plants interconnected increases. The program has managed to relate a coherent performance in problem resolution without the need for simplification of the calculations together with the ease of manipulating the parameters of simulation and visualization of output results.

Keywords: energy, optimization, hydrothermal power systems, artificial intelligence and genetic algorithms

Procedia PDF Downloads 420

Authors: Omar Youssef, Aija Knuuttila, Paivi Piirilä, Virinder Sarhadi, Sakari Knuutila

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Exhaled breath condensate (EBC) is a unique sample that allows studying different genetic changes in lung carcinoma through a non-invasive way. With the aid of next generation sequencing (NGS) technology, analysis of genetic mutations has been more efficient with increased sensitivity for detection of genetic variants. In order to investigate the possibility of applying this method for cancer diagnostics, mutations in EBC DNA from lung cancer patients and healthy individuals were studied by using NGS. The key aim is to assess the feasibility of using this approach to detect clinically important mutations in EBC. EBC was collected from 20 healthy individuals and 9 lung cancer patients (four lung adenocarcinomas, four 8 squamous cell carcinoma, and one case of mesothelioma). Mutations in hotpot regions of 22 genes were studied by using Ampliseq Colon and Lung cancer panel and sequenced on Ion PGM. Results demonstrated that all nine patients showed a total of 19 cosmic mutations in APC, BRAF, EGFR, ERBB4, FBXW7, FGFR1, KRAS, MAP2K1, NRAS, PIK3CA, PTEN, RET, SMAD4, and TP53. In controls, 15 individuals showed 35 cosmic mutations in BRAF, CTNNB1, DDR2, EGFR, ERBB2, FBXW7, FGFR3, KRAS, MET, NOTCH1, NRAS, PIK3CA, PTEN, SMAD4, and TP53. Additionally, 45 novel mutations not reported previously were also seen in patients’ samples, and 106 novel mutations were seen in controls’ specimens. KRAS exon 2 mutations G12D was identified in one control specimen with mutant allele fraction of 6.8%, while KRAS G13D mutation seen in one patient sample showed mutant allele fraction of 17%. These findings illustrate that hotspot mutations are present in DNA from EBC of both cancer patients and healthy controls. As some of the cosmic mutations were seen in controls too, no firm conclusion can be drawn on the clinical importance of cosmic mutations in patients. Mutations reported in controls could represent early neoplastic changes or normal homeostatic process of apoptosis occurring in lung tissue to get rid of mutant cells. At the same time, mutations detected in patients might represent a non-invasive easily accessible way for early cancer detection. Follow up of individuals with important cancer mutations is necessary to clarify the significance of these mutations in both healthy individuals and cancer patients.

Keywords: exhaled breath condensate, lung cancer, mutations, next generation sequencing

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Authors: Amirhossein Chambari

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This article proposes a bi-objective model for the facility location problem subject to congestion (overcrowding). Motivated by implementations to locate servers in internet mirror sites, communication networks, one-server-systems, so on. This model consider for situations in which immobile (or fixed) service facilities are congested (or queued) by stochastic demand to behave as M/M/1/K queues. We consider for this problem two simultaneous perspectives; (1) Customers (desire to limit times of accessing and waiting for service) and (2) Service provider (desire to limit average facility idle-time). A bi-objective model is setup for facility location problem with two objective functions; (1) Minimizing sum of expected total traveling and waiting time (customers) and (2) Minimizing the average facility idle-time percentage (service provider). The proposed model belongs to the class of mixed-integer nonlinear programming models and the class of NP-hard problems. In addition, to solve the model, controlled elitist non-dominated sorting genetic algorithms (Controlled NSGA-II) and controlled elitist non-dominated ranking genetic algorithms (NRGA-I) are proposed. Furthermore, the two proposed metaheuristics algorithms are evaluated by establishing standard multiobjective metrics. Finally, the results are analyzed and some conclusions are given.

Keywords: bi-objective, facility location, queueing, controlled NSGA-II, NRGA-I

Procedia PDF Downloads 583

Authors: Md. Obidul Haque, Abbasi Khanm

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Port city Chittagong, the commercial capital of Bangladesh, is flourished with fascinating topography and climatic context along with basic resources for livelihood; both shape this city and become living archives of its ecologies. Chittagong has been witnessing numerous urban development measures being taken by city development authority, though some of those seem incomplete because of lack of proper planning. Due to this unplanned trail, the blessings of nature have become the reason of sufferings for city dwellers. One of which is the water clogging due to heavy rainfall, seepage, high tide, absence of well-knit underground drainage system, and so on. The problem has reached such an extent that the first monsoon rain is enough to shut down the entire city and causing immense sufferings to livestock, specially most vulnerable groups such as children and office going people. Study shows that total discharge is higher than present drainage capacity of the canals, thus, resulting in overflow, as major channels are clogged up by dumping waste or illegal encroachment, which are supposed to flush out rain water. This paper aims to address natural and manmade causes behind urban water clogging, adverse socio-environmental hazardous effects, possibilities for probable solutions on basis of local people’s experience and rational urban planning and landscape architectural proposals such as facilitating well planned drainage system, along with waste management policies etc. which can be able to intervene in these movements to activate the mighty port city’s unfulfilled potentials.

Keywords: drainage, high-tide, urban storm water logging (USWL), urban planning, water management

Procedia PDF Downloads 333

Authors: Muqdad Al-Juboori, Bithin Datta

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Hydraulic structures such as gravity dams are classified as essential structures, and have the vital role in providing strong and safe water resource management. Three major aspects must be considered to achieve an effective design of such a structure: 1) The building cost, 2) safety, and 3) accurate analysis of seepage characteristics. Due to the complexity and non-linearity relationships of the seepage process, many approximation theories have been developed; however, the application of these theories results in noticeable errors. The analytical solution, which includes the difficult conformal mapping procedure, could be applied for a simple and symmetrical problem only. Therefore, the objectives of this paper are to: 1) develop a surrogate model based on numerical simulated data using SEEPW software to approximately simulate seepage process related to a hydraulic structure, 2) develop and solve a linked simulation-optimization model based on the developed surrogate model to describe the seepage occurring under a concrete gravity dam, in order to obtain optimum and safe design at minimum cost. The result shows that the linked simulation-optimization model provides an efficient and optimum design of concrete gravity dams.

Keywords: artificial neural network, concrete gravity dam, genetic algorithm, seepage analysis

Procedia PDF Downloads 224

Authors: Rana Sameeh

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The city is the greatest symbol of human civilization and has been built for safety and comfort. However, uncontrolled urban growth caused some anonymous and unsightly images of the cities such as unused or abandoned spaces. When social interaction is missed in a public space it means the public space is lost since public spaces reflect the social life and interaction of people. Accordingly; this space became one of the most meaningless parts of the cities and has broken the continuity of the urban fabric. Lost urban spaces are the leftover unstructured landscape within the urban fabric. They are generally the unrecognized urban areas that are in need of redesign, since they have a great value that can add to their surrounding urban context. The research significance lies within the importance of urban open spaces, their value and their impact on the urban fabric. The research also addresses the reuse and reclamation of lost urban spaces in order to increase the percentage of green areas along the urban fabric, provide urban open spaces, develop a sustainable approach towards urban landscape and enhance the quality of the public open space and user experience. In addition, the reuse of lost space will give it the identity and function it lacks while also providing places for presence, spending time and observing. Creating continuity in a broken urban fabric represents an exploratory process in the relationship between infrastructure and the urban fabric and seeks to establish an architectural solution to leftover space within the city. In doing so, the research establishes a framework (criteria) for adaptive reuse of lost urban space throughout inductive and deductive methodology, analytical methodology; by analyzing some relevant examples and similar cases of lost spaces and finally through field methodology; by applying the achieved criteria on a case study in Alexandria and carrying on SWOT analysis and evaluation of the potentials of this case study.

Keywords: adaptive reuse, lost urban space, quality of public open space, urban fabric

Procedia PDF Downloads 648

Authors: C. Manjula, Lilly Florence

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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

Procedia PDF Downloads 329