Search results for: genetic aetiology

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: 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: Nurlaili Syafar Wulan, Almurdi, Suprianto Kosno

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Introduction: Periodontitis defined as an inflammatory disease of teeth supporting tissue with irritation of specific pathogens as the main aetiology. Periodontitis can be cured by giving medical action accompanied by administration of an antibiotic, but the use of antibiotic has a side effect that can cause bacterial resistance. This side effect can be corrected by probiotic, which has antibiotic-like substance but do not have bacterial resistance effect; it makes probiotic became a promising future periodontitis medication. West Sumatran people has their own typical traditional food product made from fermented buffalo’s milk called dadih, and it contained probiotics. Objectives: The aim of this study was to determine the ability of probiotic Pediococcus pentosaceus isolated from dadih in inhibiting the growth of bacteria Aggregatibacter actinomycetemcomitans. Material and Method: This was a true experimental study with post-test and control group design. This study was conducted on 36 samples of 2 treatment groups, the test group with probiotic Pediococcus pentosacesus isolated from dadih and the negative control group with sterile aquadest. The antibacterial effect was tested using the Kirby-Bauer disk diffusion method and calculated by measuring the zone of inhibition on MHA around paper disk using a sliding caliper with 0.5 mm accuracy. Result: The result of bivariate analysis using Independent t-test was p=0.00 where p < 0.05 means that there is a significant difference between the tested group and negative control group. Conclusion: Probiotic Pediococcus pentosaceus isolated from dadih are able to inhibit the growth of Aggregatibacter actinomycetemcomitans.

Keywords: aggregatibacter actinomycetemcomitans, antibacterial activities, periodontitis, probiotic Pediococcus pentosaceus

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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: 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: 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: 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

Procedia PDF Downloads 190

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 459

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

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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

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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

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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

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Authors: Muhammad Fadli Muslimin

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Negeri Para Bedebah is known as one of the works of Tere Liye, an Indonesia author. In the literary works, the fiction as always tries to reflect the reality of the society where the author or the social groups lived in. The essential or nature of society is generally a reality while literary work is fiction and both of them are social fact. Negeri Para Bedebah is a novel fiction which is a social fact and which holds an important role in reality. It is more likely as the representation of social, economy and politic aspects in Indonesia. The purpose of this study is to reveal the world view of Tere Liye throughout novel Negeri Para Bedebah. By analyzing the object using genetic structuralism Lucien Goldmann which chiefly focuses on world view, it is stated that the literary work is an structure and it has homology with the structure in society. The structure of literary work is not chiefly homolog to the structure of society but homolog to the world view which is growing and developing inside the society. The methodological research used in this paper is a dialectic method which focuses on the starting and ending points lied in the literary text by paying attention to the coherent meanings. The result of this study is that Tere Liye shows us his world view about the structure of the society where he is living in, but one is an imaginative form of the world and the homology to the reality itself.

Keywords: homology, literary work, society, structure, world view

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Authors: Yasser Y. Lenis, Daniela Garcia Gonzalez, Cristian Solarte Bacca, Diego F. Carrillo González, Amy Jo Montgomery, Dursun Barrios

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Introduction: Artificial insemination in bovines helps to promote genetic improvement and can positively impact the rural economy. The Colombian armed conflict has forced a large portion of the rural population to abandon their territory, affecting their education, family integration, and economics. Justification: The achievement of education in rural populations was one of the Millennium Development Goals (MDGs) made by the United Nations. During the last World Summit on Sustainable Development (WSSD), it was concluded that most of the world’s poor, illiterate and undernourished population lives in rural areas; therefore, access to education is considered one of the most significant challenges for governments in countries with developing economies. Objectives: To study the effects of training in artificial insemination and rural management on the perception of knowledge and the level of knowledge in rural residents affected by the armed conflict in Nariño, Colombia. Methods: The perception of knowledge and the theoretical-practical knowledge of 63 rural residents were evaluated on the topics of bovine agribusiness management, artificial insemination, and genetic improvement through the application of three surveys. 1) evaluated the perceived level of knowledge each rural resident had about each topic using the Likert scale, 2) evaluated the theoretical knowledge before training, and 3) evaluated the theoretical knowledge upon completion of training. Results/discussion: Of the surveyed rural residents, 54% stated that they knew how business management improved the performance of their bovine agribusiness, 54% answered the pre-training knowledge test correctly, while 83% correctly answered the post-training knowledge test. Only 6% of surveyed residents perceived that they had prior knowledge of artificial insemination and reproductive anatomy topics. Before training, 35% of surveyed residents answered correctly on these topics, while upon completion of training, 65% answered correctly. Regarding genetic improvement, 11% of participating rural residents stated that they knew this subject. The correct answers on this topic went from 57% to 89% before and post-training. Conclusion: Rural extension programs contribute to closing knowledge gaps in relation to the use of reproductive biotechnologies and bovine management in rural areas affected by armed conflict.

Keywords: agribusiness, insemination, knowledge, reproduction

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Authors: Shryas Bhurat, Aryan Vashistha, Sampreet Dinakar Nayak, Ayush Gupta

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As the technology is advancing more towards high computational resources, there is a paradigm shift in the usage of these resources to optimize the design process. This paper discusses the usage of ‘Generative Design using Artificial Intelligence’ to build better models that adapt the operations like selection, mutation, and crossover to generate results. The human mind thinks of the simplest approach while designing an object, but the intelligence learns from the past & designs the complex optimized CAD Models. Generative Design takes the boundary conditions and comes up with multiple solutions with iterations to come up with a sturdy design with the most optimal parameter that is given, saving huge amounts of time & resources. The new production techniques that are at our disposal allow us to use additive manufacturing, 3D printing, and other innovative manufacturing techniques to save resources and design artistically engineered CAD Models. Also, this paper discusses the Genetic Algorithm, the Non-Domination technique to choose the right results using biomimicry that has evolved for current habitation for millions of years. The computer uses parametric models to generate newer models using an iterative approach & uses cloud computing to store these iterative designs. The later part of the paper compares the topology optimization technology with Generative Design that is previously being used to generate CAD Models. Finally, this paper shows the performance of algorithms and how these algorithms help in designing resource-efficient models.

Keywords: genetic algorithm, bio mimicry, generative modeling, non-dominant techniques

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Authors: Bedilu Tafesse

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Home gardens are important social and cultural spaces where knowledge related to agricultural practice is transmitted and through which households may improve their income and livelihood. High levels of inter- and intra-specific plant genetic diversity are preserved in home gardens. Plant diversity is threatened by rapid and unplanned urbanization, which increases environmental problems such as heating, pollution, loss of habitats and ecosystem disruption. Tropical home gardens have played a significant role in conserving plant diversity while providing substantial benefits to households. This research aimed to understand the relationship between household characteristics and plant diversity in western Ethiopia home gardens and the contributions of plants to the household economy. Plant diversity and different uses of plants were studied in a random sample of 111 suburban home gardens in the Ilu Ababora, Jima and Wellega suburban area, western Ethiopia, based on complete garden inventories followed by household surveys on socio-economic status during 2012. A total of 261 species of plants were observed, of which 41% were ornamental plants, 36% food plants, and 22% medicinal plants. Of these 16% were sold commercially to produce income. Avocado, bananas, and other fruits produced in excess. Home gardens contributed the equivalent of 7% of total annual household income in terms of food and commercial sales. Multiple regression analysis showed that education, time spent in gardening, land for cultivation, household expenses, primary conservation practices, and uses of special techniques explained 56% of the total plant diversity. Food, medicinal and commercial plant species had significant positive relationships with time spent gardening and land area for gardening. Education and conservation practices significantly affected food and medicinal plant diversity. Special techniques used in gardening showed significant positive relations with ornamental and commercial plants. Reassessments in different suburban and urban home gardens and proper documentation using same methodology is essential to build a firm policy for enhancing plant diversity and related values to households and surroundings.

Keywords: plant genetic diversity, urbanization, suburban home gardens, Ethiopia

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Authors: Amean A. Yasir, Zainab Kh. A. Al-Mahdi Al-Amean

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In both developed and developing countries, obesity among women is increasing, but in different patterns and at very different speeds. It may have a negative effect on health, leading to reduced life expectancy and/or increased health problems. This research studied the age distribution among obese women, the types of overweight and obesity, and the extent of the problem of overweight/obesity and the obesity etiological factors among women in Hillah city in central Iraq. A total of 322 overweight and obese women were included in the study, those women were randomly selected. The Body Mass Index was used as indicator for overweight/ obesity. The incidence of overweight/obesity among age groups were estimated, the etiology factors included genetic, environmental, genetic/environmental and endocrine disease. The overweight and obese women were screened for incidence of infection and/or diseases. The study found that the prevalence of 322 overweight and obese women in Hillah city in central Iraq was 19.25% and 80.78%, respectively. The obese women types were recorded based on BMI and WHO classification as class-1 obesity (29.81%), class-2 obesity (24.22%) and class-3 obesity (26.70%), the result was discrepancy non-significant, P value < 0.05. The incidence of overweight in women was high among those aged 20-29 years (90.32%), 6.45% aged 30-39 years old and 3.22% among ≥ 60 years old, while the incidence of obesity was 20.38% for those in the age group 20-29 years, 17.30% were 30-39 years, 23.84% were 40-49 years, 16.92% were 50-59 years group and 21.53% were ≥ 60 years age group. These results confirm that the age can be considered as a significant factor for obesity types (P value < 0.0001). The result also showed that the both genetic factors and environmental factors were responsible for incidents of overweight or obesity (84.78%) p value < 0.0001. The results also recorded cases of different repeated infections (skin infection, recurrent UTI and influenza), cancer, gallstones, high blood pressure, type 2 diabetes, and infertility. Weight stigma and bias generally refers to negative attitudes; Obesity can affect quality of life, and the results of this study recorded depression among overweight or obese women. This can lead to sexual problems, shame and guilt, social isolation and reduced work performance. Overweight and Obesity are real problems among women of all age groups and is associated with the risk of diseases and infection and negatively affects quality of life. This result warrants further studies into the prevalence of obesity among women in Hillah City in central Iraq and the immune response of obese women.

Keywords: obesity, overweight, Iraq, body mass index

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Authors: Elchin Hajiyev, Afet Memmedova Dadash, Sabina Hajiyeva, Aynur Karimova, Ramiz Aliyev

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Although potatoes have a wide distribution range, the yield potential of varieties varies greatly depending on the region. Our country is made up of agricultural regions with very different environmental characteristics.In this case, we cannot expect the introduced varieties to show the same adaptation to the different conditions of our country. For this reason, in our country, varieties with high general adaptability should be used, rather than varieties with special adaptability in certain areas. Soil salinization has become a global problem.Increased salinity has a serious impact on food security by reducing plant productivity. Plants have protective mechanisms of adaptation to salt stress, such as the synthesis of physiologically active substances, resistance to antioxidant stress and oxidation of membrane lipids. One of these substances is free proline. Our study revealed genetic variation in proline accumulation among samples exposed to stress factors.Changes in proline content under stress conditions were studied in 50 samples. There was wide variation across all treatments.The amount of proline varied between 7.2–37.7 μM/g under salinity conditions.The lowest rate was in the SF33 genotype (1.5 times more than the control (2.5 μM/g)).The highest level of proline under the influence of salt stress was in the SF45 genotype (7.25 times higher than the control (32.5 μM/g)). Our studies have found that the protective system reacts differently to the influence of stress factors. According to the results obtained on the amount of proline, adaptation mechanisms must be more actively activated to maintain metabolism and ensure viability in sensitive forms under the influence of stress factors. At high doses of the salt stressor, a tenfold increase in proline compared to the control indicates significant damage to the plant organism as a result of stress.To prevent damage to the body, the antioxidant system needs to quickly mobilize and work at full capacity in adverse conditions. An increase in the dose of the stress factor salt in our study caused a greater increase in the amount of free proline in plant tissues. Considering the functions of proline as an osmoprotector and antioxidant, it was found that increasing its amount is aimed at protecting the plant from the acute effects of stressors.

Keywords: genetic variability, potato, genotypes, proline, stress

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Authors: Maria Lucia G. Lourenco, Keylla H. N. P. Pereira, Viviane Y. Hibaru, Fabiana F. Souza, Joao C. P. Ferreira, Simone B. Chiacchio, Luiz H. A. Machado

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Congenital malformations are organ defects due to genetic or teratogenic causes, which can lead to high mortality in dog litters. This study assessed and described the congenital malformations in newborn dogs. The study included litters attend in the São Paulo State University (UNESP) Veterinary Hospital, Botucatu, Sao Paulo, Brazil. One hundred seventy-eight litters and 803 newborns were evaluated. The occurrence of litters with malformations was 24.7%, and of newborns was 6.7%. Twenty-seven different malformations were registered: anasarca, anal atresia, cleft lip, cleft palate, duplicated right ribcage, equinovarus, exencephaly, gastroschisis, hydrocephaly, lissencephaly, macroglossia, microphthalmia, mitral valve dysplasia, omphalocele, eyelid agenesis, persistent urachus, polydactyly, pulmonary hypoplasia, pulmonary valve stenosis, rectovaginal fistula, agenesis of abdominal muscles, rib hypoplasia, scoliosis, segmental aplasia of the intestines, tricuspid valve dysplasia, unilateral kidney agenesis, and vaginal atresia. 68.7% of newborns died as a result of malformations. The pure breeds with the highest chances of manifesting malformations in contrast with mixed breeds were French Bulldog, Pug, English Bulldog, Rottweiler, German Spitz, Pinscher, Pitbull, Yorkshire Terrier, and Shih-Tzu. Significant values (P<0.05) occurred in races French Bulldogs and Pugs. The causes of congenital disabilities are possibly related to hereditary genetic factors considering that the highest incidence of malformations was observed among purebreds. There as one case of exposure to a teratogenic agent, but no other mothers were exposed to such agents during pregnancy. Two cases of consanguineal breeding between siblings were reported. The mortality rate was high. Genetic breeding programs for reproduction, avoiding consanguineous mating, care in choosing parents, and avoiding maternal exposure to teratogenic agents are of utmost importance in reducing dog malformations and consequent mortality.

Keywords: congenital defects, teratogenesis, canine neonatology, newborn puppy

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Authors: Michael Josef Schwerer

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Background: Analyzing any aircraft accident is mandatory based on the regulations of the International Civil Aviation Organization and the respective country’s criminal prosecution authorities. Legal medicine investigations are unavoidable when fatalities involve the flight crew or when doubts arise concerning the pilot’s aeromedical health status before the event. As a result of frequently tremendous blunt and sharp force trauma along with the impact of the aircraft to the ground, consecutive blast or fire exposition of the occupants or putrefaction of the dead bodies in cases of delayed recovery, relevant findings can be masked or destroyed and therefor being inaccessible in standard pathology practice comprising just forensic autopsy and histopathology. Such cases are of considerable risk of remaining unsolved without legal consequences for those responsible. Further, no lessons can be drawn from these scenarios to improve flight safety and prevent future mishaps. Aims and Methods: To learn from previously unsolved aircraft accidents, re-evaluations of the investigation files and modern molecular pathology studies were performed. Genetic testing involved predominantly PCR-based analysis of gene regulation, studying DNA promotor methylations, RNA transcription and posttranscriptional regulation. In addition, the presence or absence of infective agents, particularly DNA- and RNA-viruses, was studied. Technical adjustments of molecular genetic procedures when working with archived sample material were necessary. Standards for the proper interpretation of the respective findings had to be settled. Results and Discussion: Additional molecular genetic testing significantly contributes to the quality of forensic pathology assessment in aviation mishaps. Previously undetected cardiotropic viruses potentially explain e.g., a pilot’s sudden incapacitation resulting from cardiac failure or myocardial arrhythmia. In contrast, negative results for infective agents participate in ruling out concerns about an accident pilot’s fitness to fly and the aeromedical examiner’s precedent decision to issue him or her an aeromedical certificate. Care must be taken in the interpretation of genetic testing for pre-existing diseases such as hypertrophic cardiomyopathy or ischemic heart disease. Molecular markers such as mRNAs or miRNAs, which can establish these diagnoses in clinical patients, might be misleading in-flight crew members because of adaptive changes in their tissues resulting from repeated mild hypoxia during flight, for instance. Military pilots especially demonstrate significant physiological adjustments to their somatic burdens in flight, such as cardiocirculatory stress and air combat maneuvers. Their non-pathogenic alterations in gene regulation and expression will likely be misinterpreted for genuine disease by inexperienced investigators. Conclusions: The growing influence of molecular pathology on legal medicine practice has found its way into aircraft accident investigation. As appropriate quality standards for laboratory work and data interpretation are provided, forensic genetic testing supports the medico-legal analysis of aviation mishaps and potentially reduces the number of unsolved events in the future.

Keywords: aviation medicine, aircraft accident investigation, forensic pathology, molecular pathology

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Authors: P. Suresh, K. Gunasekaran, R. Thanigaivelan

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Radio frequency identification (RFID) technology has been attracting considerable attention with the expectation of improved supply chain visibility for consumer goods, apparel, and pharmaceutical manufacturers, as well as retailers and government procurement agencies. It is also expected to improve the consumer shopping experience by making it more likely that the products they want to purchase are available. Recent announcements from some key retailers have brought interest in RFID to the forefront. A modified K- Means Cluster based Heuristic approach, Hybrid Genetic Algorithm (GA) - Simulated Annealing (SA) approach, Hybrid K-Means Cluster based Heuristic-GA and Hybrid K-Means Cluster based Heuristic-GA-SA for Open Loop Supply Chain Network problem are proposed. The study incorporated uniform crossover operator and combined crossover operator in GAs for solving open loop supply chain distribution network problem. The algorithms are tested on 50 randomly generated data set and compared with each other. The results of the numerical experiments show that the Hybrid K-means cluster based heuristic-GA-SA, when tested on 50 randomly generated data set, shows superior performance to the other methods for solving the open loop supply chain distribution network problem.

Keywords: RFID, supply chain distribution network, open loop supply chain, genetic algorithm, simulated annealing

Procedia PDF Downloads 148

Authors: Xiaolian Jiang, Dongling Liu, Kun Liu

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Aims: To examine the prevalence of POST-TRAUMATIC STRESS DISORDER (PTSD) symptoms among Tibetan adolescents in heavily-hit disaster area three years after Yushu earthquake, and to explore the interactions of the psycho-social-genetic risk factors. Methods: This was a three-stage study. Firstly, demographic variables，PTSD Checklist-Civilian Version （PCL-C），the Internality、Powerful other、Chance Scale，（IPC），Coping Style Scale（CSS），and the Social Support Appraisal（SSA）were used to explore the psychosocial factors of PTSD symptoms among adolescent survivors. PCL-C was used to examine the PTSD symptoms among 4072 Tibetan adolescents，and the Structured Clinical Interview for DSM-IV Disorders（SCID）was used by psychiatrists to make the diagnosis precisely. Secondly，a case-control trial was used to explore the relationship between PTSD and gene polymorphisms. 287adolescents diagnosed with PTSD were recruited in study group, and 280 adolescents without PTSD in control group. Polymerase chain reaction-restriction fragment length polymorphism technology（PCR-RFLP）was used to test gene polymorphisms. Thirdly，SPSS 22.0 was used to explore the interactions of the psycho-social-genetic risk factors of PTSD on the basis of the above results. Results and conclusions: 1．The prevalence of PTSD was 9.70%. 2．The predictive psychosocial factors of PTSD included earthquake exposure, support from others, imagine, abreact, tolerant, powerful others and family support. 3．Synergistic interactions between A1 gene of DRD2 TaqIA and the external locus of control, negative coping style, severe earthquake exposure were found. Antagonism interactions between A1 gene of DRD2 TaqIA and poor social support was found. Synergistic interactions between A1/A1 genotype and the external locus of control, negative coping style were found. Synergistic interactions between 12 gene of 5-HTTVNTR and the external locus of control, negative coping style, severe earthquake exposure were found. Synergistic interactions between 12/12 genotype and the external locus of control, negative coping style, severe earthquake exposure were also found.

Keywords: adolescents, earthquake, PTSD, risk factors

Procedia PDF Downloads 131

Authors: Dylan Santos De Pinho, Nabil Ouerhani

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Energy consumption of machine-tools is becoming critical for machine-tool builders and end-users because of economic, ecological and legislation-related reasons. Many machine-tool builders are seeking for solutions that allow the reduction of energy consumption of machine-tools while preserving the same productivity rate and the same quality of machined parts. In this paper, we present the first results of a project conducted jointly by academic and industrial partners to reduce the energy consumption of a Swiss-Type lathe. We employ genetic algorithms to find optimal machining parameters – the set of parameters that lead to the best trade-off between energy consumption, part quality and tool lifetime. Three main machining process parameters are considered in our optimization technique, namely depth of cut, spindle rotation speed and material feed rate. These machining process parameters have been identified as the most influential ones in the configuration of the Swiss-type machining process. A state-of-the-art multi-objective genetic algorithm has been used. The algorithm combines three fitness functions, which are objective functions that permit to evaluate a set of parameters against the three objectives: energy consumption, quality of the machined parts, and tool lifetime. In this paper, we focus on the investigation of the fitness function related to energy consumption. Four different energy consumption related fitness functions have been investigated and compared. The first fitness function refers to the Kienzle cutting force model. The second fitness function uses the Material Removal Rate (RMM) as an indicator of energy consumption. The two other fitness functions are non-deterministic, learning-based functions. One fitness function uses a simple Neural Network to learn the relation between the process parameters and the energy consumption from experimental data. Another fitness function uses Lasso regression to determine the same relation. The goal is, then, to find out which fitness functions predict best the energy consumption of a Swiss-Type machining process for the given set of machining process parameters. Once determined, these functions may be used for optimization purposes – determine the optimal machining process parameters leading to minimum energy consumption. The performance of the four fitness functions has been evaluated. The Tornos DT13 Swiss-Type Lathe has been used to carry out the experiments. A mechanical part including various Swiss-Type machining operations has been selected for the experiments. The evaluation process starts with generating a set of CNC (Computer Numerical Control) programs for machining the part at hand. Each CNC program considers a different set of machining process parameters. During the machining process, the power consumption of the spindle is measured. All collected data are assigned to the appropriate CNC program and thus to the set of machining process parameters. The evaluation approach consists in calculating the correlation between the normalized measured power consumption and the normalized power consumption prediction for each of the four fitness functions. The evaluation shows that the Lasso and Neural Network fitness functions have the highest correlation coefficient with 97%. The fitness function “Material Removal Rate” (MRR) has a correlation coefficient of 90%, whereas the Kienzle-based fitness function has a correlation coefficient of 80%.

Keywords: adaptive machining, genetic algorithms, smart manufacturing, parameters optimization

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Authors: Raya Morag

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This paper proposes a new paradigm for cinema/trauma studies - the trauma of the perpetrator. Canonical trauma research from Freud’s Aetiology of Hysteria to the present has been carried out from the perspective of identification with the victim, as have cinema trauma research and contemporary humanities-based trauma studies, climaxing during the 1990s in widespread interest in the victim vis-à-vis the Holocaust, war, and domestic violence. Breaking over 100 years of repression of the abhorrent and rejected concept of the perpetrator in psychoanalytic-based research proposes an uncanny shift in our conception of psychoanalysis' trajectory from women's 'hysteria' to 'post-traumatic stress disorder'. This new paradigm is driven by the global emergence of new waves of films (2007-2015) representing trauma suffered by perpetrators involved in the new style of war entailing deliberate targeting of non-combatants. Analyzing prominent examples from Israeli post-second Intifada documentaries (e.g., Ari Folman’s Waltz with Bashir), and post post-Iraq (and Afghanistan) War American documentaries (e.g., Errol Morris' Standard Operating Procedure), the paper discusses the limitations of victim trauma by the firm boundaries it (rightly) set in order to defend such victims of nineteenth and especially twentieth-century catastrophes; the epistemological processes needed in order to consider perpetrators’ trauma as an inevitable part of psychiatric-psychological and cultural perspectives on trauma, and, thus, the definition of perpetrators' trauma in contrast to victims'. It also analyzes the perpetrator's figure in order to go beyond the limitation of current trauma theory's relation to the Real, thus transgressing the 'unspeakableness' of the trauma itself. The paper seeks an exploration of what perpetrator trauma teaches us not only as a counter-paradigm to victim trauma, but as a reflection on the complex intertwining of the two paradigms in the twenty-first century collective new war unconscious, and on what psychoanalysis might offer us in the first decade of this terrorized-ethnicized century.

Keywords: American war documentaries, Israeli war documentaries, 'new war', perpetrator trauma

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