Search results for: dominant growth models

Authors: Shang-Han Tsai, Yong-Hong Lin, Chung-Ruey Yen

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Wax apple is an important tropical fruit in Taiwan. The famous producing area is located on the coast in Pingtung county. Land subsidence and climate change will tend to soil alkalization more seriously. This study was to evaluate the effects of NaCl in wax apple seedlings. NaCl salinity reduced wax apple shoot growth, it may due to reducing relative water content in leaf and new shoot. Leaf Cl and Na concentration were increased but K, Ca, and Mg content had no significant difference after irrigated with NaCl for six weeks. In roots, Na and Cl content increase significantly with 90 mM NaCl treatment, but K, Ca, and Mg content was reduced. 30-90 mM Nacl treatment do not affect K/Na, Ca/Na, and Mg/Na ratio, but decrease significantly in 90 mM treatment in roots. The leaf and root electrolyte leakage were significantly affected by 90 mM NaCl treatment. Suggesting 90 mM was optimum concentration for sieve out other tolerance wax apple verities.

Keywords: growth, NaCl stress, nutrient, wax apple

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Authors: Raymond Feng, Shadi Ghiasi

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An electroencephalogram (EEG) is a non-invasive technique that records electrical activity in the brain using scalp electrodes. Researchers have studied the use of EEG to detect emotions and moods by collecting signals from participants and analyzing how those signals correlate with their activities. In this study, researchers investigated the relationship between EEG signals and music enjoyment. Participants listened to music while data was collected. During the signal-processing phase, power spectral densities (PSDs) were computed from the signals, and dominant brainwave frequencies were extracted from the PSDs to form a comprehensive feature matrix. A machine learning approach was then taken to find correlations between the processed data and the music enjoyment level indicated by the participants. To improve on previous research, multiple machine learning models were employed, including K-Nearest Neighbors Classifier, Support Vector Classifier, and Decision Tree Classifier. Hyperparameters were used to fine-tune each model to further increase its performance. The experiments showed that a strong correlation exists, with the Decision Tree Classifier with hyperparameters yielding 85% accuracy. This study proves that EEG is a reliable means to detect music enjoyment and has future applications, including personalized music recommendation, mood adjustment, and mental health therapy.

Keywords: EEG, electroencephalogram, machine learning, mood, music enjoyment, physiological signals

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Authors: Forrest Kaatz, Adhemar Bultheel

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Au-Cu and Pt-M (M = Fe, Co, and Ni) nanocluster alloys are currently being investigated worldwide by many researchers for their interesting catalytic and nanophase properties. The low-temperature behavior of the phase diagrams is not well understood for alloys with nanometer sizes and shapes. These systems have similar bulk phase diagrams with the L12 (Au3Cu, Pt3M, AuCu3, and PtM3) structurally ordered intermetallics and the L10 structure for the AuCu and PtM intermetallics. We consider three models for low temperature ordering in the phase diagrams of Au–Cu and Pt–M nanocluster alloys. These models are valid for sizes ~ 5 nm and approach bulk values for sizes ~ 20 nm. We study the phase transition in nanoclusters with cubic, octahedral, and cuboctahedral shapes, covering the compositions of interest. These models are based on studying the melting temperatures in nanoclusters using the regular solution, mixing model for alloys. Experimentally, it is extremely challenging to determine thermodynamic data on nano–sized alloys. Reasonable agreement is found between these models and recent experimental data on nanometer clusters in the Au–Cu and Pt–M nanophase systems. From our data, experiments on nanocubes about 5 nm in size, of stoichiometric AuCu and PtM composition, could help differentiate between the models. Some available evidence indicates that ordered intermetallic nanoclusters have better catalytic properties than disordered ones. We conclude with a discussion of physical mechanisms whereby ordering could improve the catalytic properties of nanocluster alloys.

Keywords: catalytic reactions, gold nanoalloys, phase transitions, platinum nanoalloys

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Authors: Delphine Mukaneza, Lin Qiao, Wang Pengxin, Li Yan, Chen Yingyi

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Human activities on land use make the land-cover gradually change or transit. In this study, we examined the use of Landsat TM data to detect the land use change of Kigali between 1987 and 2009 using remote sensing techniques and analysis of data using ENVI and ArcGIS, a GIS software. Six different categories of land use were distinguished: bare soil, built up land, wetland, water, vegetation, and others. With remote sensing techniques, we analyzed land use data in 1987, 1999 and 2009, changed areas were found and a dynamic situation of land use in Kigali city was found during the 22 years studied. According to relevant Landsat data, the research focused on land use change in accordance with the role of remote sensing in the process of urbanization. The result of the work has shown the rapid increase of built up land between 1987 and 1999 and a big decrease of vegetation caused by the rebuild of the city after the 1994 genocide, while in the period of 1999 to 2009 there was a reduction in built up land and vegetation, after the authority of Kigali city established, a Master Plan where all constructions which were not in the range of the master Plan were destroyed. Rwanda's capital, Kigali City, through the expansion of the urban area, it is increasing the internal employment rate and attracts business investors and the service sector to improve their economy, which will increase the population growth and provide a better life. The overall planning of the city of Kigali considers the environment, land use, infrastructure, cultural and socio-economic factors, the economic development and population forecast, urban development, and constraints specification. To achieve the above purpose, the Government has set for the overall planning of city Kigali, different stages of the detailed description of the design, strategy and action plan that would guide Kigali planners and members of the public in the future to have more detailed regional plans and practical measures. Thus, land use change is significantly the performance of Kigali active human area, which plays an important role for the country to take certain decisions. Another area to take into account is the natural situation of Kigali city. Agriculture in the region does not occupy a dominant position, and with the population growth and socio-economic development, the construction area will gradually rise and speed up the process of urbanization. Thus, as a developing country, Rwanda's population continues to grow and there is low rate of utilization of land, where urbanization remains low. As mentioned earlier, the 1994 genocide massacres, population growth and urbanization processes, have been the factors driving the dramatic changes in land use. The focus on further research would be on analysis of Rwanda’s natural resources, social and economic factors that could be, the driving force of land use change.

Keywords: land use change, urbanization, Kigali City, Landsat

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Authors: Gustavo Rodrigues, Hans Weber, Larissa Driemeier

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The prevision of post-impact conditions and the behavior of the bodies during the impact have been object of several collision models. The formulation from Hertz’s theory is generally used dated from the 19^th century. These models consider the repulsive force as proportional to the deformation of the bodies under contact and may consider it proportional to the rate of deformation. The objective of the present work is to analyze the behavior of the bodies during impact using the Finite Element Method (FEM) with elastic and plastic material models. The main parameters to evaluate are, the contact force, the time of contact and the deformation of the bodies. An advantage of using the FEM approach is the possibility to apply a plastic deformation to the model according to the material definition: there will be used Johnson–Cook plasticity model whose parameters are obtained through empirical tests of real materials. This model allows analyzing the permanent deformation caused by impact, phenomenon observed in real world depending on the forces applied to the body. These results are compared between them and with the model-based Hertz theory.

Keywords: collision, impact models, finite element method, Hertz Theory

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Authors: Saeed Moarrefi, Shou-Han Zhou, Liyuan Fan

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Coupling with solid oxide fuel cells, methane dry reforming is a promising pathway for energy production while mitigating carbon emissions. However, the influence of carbon dioxide and electrochemical reactions on the internal dry reforming reaction within the fuel cells remains debatable, requiring accurate kinetic models to describe the internal reforming behaviors. We employed the Power-Law and Langmuir Hinshelwood–Hougen Watson models in an electrolyte-supported solid oxide fuel cell with a NiO-GDC-YSZ anode. The current density used in this study ranges from 0 to 1000 A/m2 at 973 K to 1173 K to estimate various kinetic parameters. The influence of the electrochemical reactions on the adsorption terms, the equilibrium of the reactions, the activation energy, the pre-exponential factor of the rate constant, and the adsorption equilibrium constant were studied. This study provides essential parameters for future simulations and highlights the need for a more detailed examination of reforming kinetic models.

Keywords: dry reforming kinetics, Langmuir Hinshelwood–Hougen Watson, power-law, SOFC

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Authors: Ramesh Kumar, Rajesh Kumar, Shaktiman Singh, Atar Singh, Anshuman Bhardwaj, Ravindra Kumar Sinha, Anupma Kumari

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A detailed study of the ion chemistry of the Shaune Garnag glacier meltwater has been carried out to assess the role of active glacier in the chemical denudation rate. The chemical compositions of various ions in meltwater of the Shaune Garang glacier were analyzed during the melting period 2015 and 2016. Total 112 of melt water samples twice in a day were collected during ablation season of 2015 and 2016. To identify various factors controlling the dissolved ionic strength of Shaune Garang Glacier meltwater statistical analysis such as correlation matrix, Principle Component Analysis (PCA) and factor analysis were applied to deduce the result. Cation concentration for Ca²⁺ > Mg²⁺ > Na⁺ > K⁺ in the meltwater for both the years can be arranged in the order as Ca²⁺ > Mg²⁺ > Na⁺ > K⁺. Study showed that Ca²⁺ and HCO₃⁻ found to be dominant on the both melting period. Carbonate weathering identified as the dominant process controlling the dissolved ion chemistry of meltwater due to the high ratios of (Ca²⁺ + Mg²⁺) versus TZ+ and (Ca²⁺ + Mg²⁺) versus (Na⁺ + K⁺) in the study area. The cation denudation rate of the Shaune Garnag catchment is 3412.2 m⁻² a⁻¹, i.e. higher than the other glacierised catchment in the Himalaya, indicating intense chemical erosion in this catchment.

Keywords: Shaune Garang glacier, Hydrochemistry, chemical composition, cation denudation rate, carbonate weathering

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Authors: Mohan Li

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Nowadays, intelligent research technology is more and more important than traditional research methods in urban research work, and this proportion will greatly increase in the next few decades. Frequently such analyzing work cannot be carried without some software engineering knowledge. And here, domain models of urban research will be necessary when applying software engineering knowledge to urban work. In many urban plan practice projects, making rational models, feeding reliable data, and providing enough computation all make indispensable assistance in producing good urban planning. During the whole work process, domain models can optimize workflow design. At present, human beings have entered the era of big data. The amount of digital data generated by cities every day will increase at an exponential rate, and new data forms are constantly emerging. How to select a suitable data set from the massive amount of data, manage and process it has become an ability that more and more planners and urban researchers need to possess. This paper summarizes and makes predictions of the emergence of technologies and technological iterations that may affect urban research in the future, discover urban problems, and implement targeted sustainable urban strategies. They are summarized into seven major domain models. They are urban and rural regional domain model, urban ecological domain model, urban industry domain model, development dynamic domain model, urban social and cultural domain model, urban traffic domain model, and urban space domain model. These seven domain models can be used to guide the construction of systematic urban research topics and help researchers organize a series of intelligent analytical tools, such as Python, R, GIS, etc. These seven models make full use of quantitative spatial analysis, machine learning, and other technologies to achieve higher efficiency and accuracy in urban research, assisting people in making reasonable decisions.

Keywords: big data, domain model, urban planning, urban quantitative analysis, machine learning, workflow design

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Authors: Pia Ulvenblad, Henrik Barth, Jennie Cederholm BjöRklund, Maya Hoveskog, Per-Ola Ulvenblad

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The importance of business model innovation (BMI) is widely recognized. This is also valid for firms in the agri-food industry, closely connected to global challenges. Worldwide food production will have to increase 70% by 2050 and the United Nations’ sustainable development goals prioritize research and innovation on food security and sustainable agriculture. The firms of the agri-food industry have opportunities to increase their competitive advantage through BMI. However, the process of BMI is complex and the implementation of new business models is associated with high degree of risk and failure. Thus, managers from all industries and scholars need to better understand how to address this complexity. Therefore, the research presented in this paper (i) explores different categories of barriers in research literature on business models in the agri-food industry, and (ii) illustrates categories of barriers with empirical cases. This study is addressing the rather limited understanding on barriers for BMI in the agri-food industry, through a systematic literature review (SLR) of 570 peer-reviewed journal articles that contained a combination of ‘BM’ or ‘BMI’ with agriculture-related and food-related terms (e.g. ‘agri-food sector’) published in the period 1990-2014. The study classifies the barriers in several categories and illustrates the identified barriers with ten empirical cases. Findings from the literature review show that barriers are mainly identified as outcomes. It can be assumed that a perceived barrier to growth can often be initially exaggerated or underestimated before being challenged by appropriate measures or courses of action. What may be considered by the public mind to be a barrier could in reality be very different from an actual barrier that needs to be challenged. One way of addressing barriers to growth is to define barriers according to their origin (internal/external) and nature (tangible/intangible). The framework encompasses barriers related to the firm (internal addressing in-house conditions) or to the industrial or national levels (external addressing environmental conditions). Tangible barriers can include asset shortages in the area of equipment or facilities, while human resources deficiencies or negative willingness towards growth are examples of intangible barriers. Our findings are consistent with previous research on barriers for BMI that has identified human factors barriers (individuals’ attitudes, histories, etc.); contextual barriers related to company and industry settings; and more abstract barriers (government regulations, value chain position, and weather). However, human factor barriers – and opportunities - related to family-owned businesses with idealistic values and attitudes and owning the real estate where the business is situated, are more frequent in the agri-food industry than other industries. This paper contributes by generating a classification of the barriers for BMI as well as illustrating them with empirical cases. We argue that internal barriers such as human factors barriers; values and attitudes are crucial to overcome in order to develop BMI. However, they can be as hard to overcome as for example institutional barriers such as governments’ regulations. Implications for research and practice are to focus on cognitive barriers and to develop the BMI capability of the owners and managers of agri-industry firms.

Keywords: agri-food, barriers, business model, innovation

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Authors: Kalpana Jamdhade, Anita Chorey, Bharti Tijare, V. M. Bhale

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A field experiment was conducted during summer season of 2011 at Agronomy research farm, Dr. PDKV, Akola, to study the effect of irrigation regime and nitrogen levels on growth and productivity of summer sesame. The experiment was laid out in split plot Design in which three irrigation scheduling on the basis of IW/CPE ratio viz., irrigation at 0.6, 0.8 and 1.0 IW/CPE ratios (I1, I2 and I3, respectively) and one irrigation scheduling based on critical growth stages of sesame (I4), in main plot and three nitrogen levels 0, 30 and 60 kg N ha-1 (N0, N1 and N2, respectively) in subplot. The result showed that plant height, number of leaves plant-1, leaf area and dry matter accumulation were maximum in irrigation scheduling at 1.0 IW/CPE ratio, which significantly superior over 0.6 IW/CPE ratio and irrigation at critical growth stages but were statistically at par with irrigation at 0.8 IW/CPE ratio. Nitrogen levels, application of 60 kg N ha-1 was recorded significantly superior all growth parameters over treatment 30 kg N ha-1 and 0 kg N ha-1. In case of yield attributes viz., No. of capsules plant-1, Test wt., grain yield and Stalk yield (qha-1) were maximum in irrigation scheduling at 1.0 IW/CPE ratio and were significantly superior over 0.8 IW/CPE ratio, 0.6 IW/CPE ratio and irrigation at critical growth stages. Application of 60 kg N ha-1 increased all yield attributing characters over application of 30 and 0 kg N ha-1. In case of economics of crop same trend was found and the highest B:C ration was obtained in irrigation scheduling at 1.0 IW/CPE ratio. Whereas, application of 30 kg N ha-1 was recorded highest B:C ration over application of 60 and 0 kg N ha-1. Interaction effect of irrigation and nitrogen levels were found to be non significant in summer season.

Keywords: irrigation regimes, nitrogen levels, summer sesame, agricultural technology

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Authors: Ilsun Pang, Kwanghun Kim, Sungsun Baik

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Large diameter Si wafer is used as semiconductor substrate. Large diameter Si crystal ingot should be needed in order to increase wafer size. To make convection of large silicon melt stable, magnetic field is normally applied, but magnetic field is expensive and it is not proper to stabilize the large Si melt. To solve the problem, we propose a continuous Czochralski process which can be applied to small melt without magnetic field. We used granule poly, which has size distribution of 1~3 mm and is easily supplied in double crucible during silicon ingot growth. As the result, we produced 420 mm diameter ingot. In this paper, we describe an experimental study on crystal growth of large diameter silicon by Continuous Czochralski process.

Keywords: Czochralski, ingot, silicon crystal, wafer

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Authors: Qasim Munye, Juned Islam, Haseeb Qureshi, Syed Jung

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Lung nodules are commonly identified in computed tomography (CT) scans by experienced radiologists at a relatively late stage. Early diagnosis can greatly increase survival. We propose using a pix2pix conditional generative adversarial network to generate realistic images simulating early-stage lung nodule growth. We have applied deep images prior to 2341 slices from 895 computed tomography (CT) scans from the Lung Image Database Consortium (LIDC) dataset to generate pseudo-healthy medical images. From these images, 819 were chosen to train a pix2pix network. We observed that for most of the images, the pix2pix network was able to generate images where the nodule increased in size and intensity across epochs. To evaluate the images, 400 generated images were chosen at random and shown to a medical student beside their corresponding original image. Of these 400 generated images, 384 were defined as satisfactory - meaning they resembled a nodule and were visually similar to the corresponding image. We believe that this generated dataset could be used as training data for neural networks to detect lung nodules at an early stage or to improve the accuracy of such networks. This is particularly significant as datasets containing the growth of early-stage nodules are scarce. This project shows that the combination of deep image prior and generative models could potentially open the door to creating larger datasets than currently possible and has the potential to increase the accuracy of medical classification tasks.

Keywords: medical technology, artificial intelligence, radiology, lung cancer

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Authors: Arlene López-Sampson, Tony Page, Betsy Jackes

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Aquilaria genus produces a highly valuable fragrant oleoresin known as agarwood. Agarwood forms in a few trees in the wild as a response to injure or pathogen attack. The resin is used in perfume and incense industry and medicine. Cultivation of Aquilaria species as a sustainable source of the resin is now a common strategy. Physiological traits are frequently used as a proxy of crop and tree productivity. Aquilaria species growing in Queensland, Australia were studied to investigate relationship between leaf-productivity traits with tree growth. Specifically, 28 trees, representing 12 plus trees and 16 trees from yield plots, were selected to conduct carbon isotope analysis (δ13C) and monitor six leaf attributes. Trees were grouped on four diametric classes (diameter at 150 mm above ground level) ensuring the variability in growth of the whole population was sampled. Model averaging technique based on the Akaike’s information criterion (AIC) was computed to identify whether leaf traits could assist in diameter prediction. Carbon isotope values were correlated with height classes and leaf traits to determine any relationship. In average four leaves per shoot were recorded. Approximately one new leaf per week is produced by a shoot. Rate of leaf expansion was estimated in 1.45 mm day-1. There were no statistical differences between diametric classes and leaf expansion rate and number of new leaves per week (p > 0.05). Range of δ13C values in leaves of Aquilaria species was from -25.5 ‰ to -31 ‰ with an average of -28.4 ‰ (± 1.5 ‰). Only 39% of the variability in height can be explained by δ13C in leaf. Leaf δ13C and nitrogen content values were positively correlated. This relationship implies that leaves with higher photosynthetic capacities also had lower intercellular carbon dioxide concentrations (ci/ca) and less depleted values of 13C. Most of the predictor variables have a weak correlation with diameter (D). However, analysis of the 95% confidence of best-ranked regression models indicated that the predictors that could likely explain growth in Aquilaria species are petiole length (PeLen), values of δ13C (true13C) and δ15N (true15N), leaf area (LA), specific leaf area (SLA) and number of new leaf produced per week (NL.week). The model constructed with PeLen, true13C, true15N, LA, SLA and NL.week could explain 45% (R2 0.4573) of the variability in D. The leaf traits studied gave a better understanding of the leaf attributes that could assist in the selection of high-productivity trees in Aquilaria.

Keywords: 13C, petiole length, specific leaf area, tree growth

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Authors: M. A. Hafiz, P. T. Matevenga

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Micro-level machining of metals is a developing field which has shown to be a prospective approach to produce features on the parts in the range of a few to a few hundred microns with acceptable machining quality. It is known that the mechanics (i.e. the material removal mechanism) of micro-machining and conventional machining have significant differences due to the scaling effects associated with tool-geometry, tool material and work piece material characteristics. Shape memory alloys (SMAs) are those metal alloys which display two exceptional properties, pseudoelasticity and the shape memory effect (SME). Nickel-titanium (NiTi) alloys are one of those unique metal alloys. NiTi alloys are known to be difficult-to-cut materials specifically by using conventional machining techniques due to their explicit properties. Their high ductility, high amount of strain hardening, and unusual stress–strain behaviour are the main properties accountable for their poor machinability in terms of tool wear and work piece quality. The motivation of this research work was to address the challenges and issues of micro-machining combining with those of machining of NiTi alloy which can affect the desired performance level of machining outputs. To explore the significance of range of cutting conditions on surface roughness and tool wear, machining tests were conducted on NiTi. Influence of different cutting conditions and cutting tools on surface and sub-surface deformation in work piece was investigated. Design of experiments strategy (L9 Array) was applied to determine the key process variables. The dominant cutting parameters were determined by analysis of variance. These findings showed that feed rate was the dominant factor on surface roughness whereas depth of cut found to be dominant factor as far as tool wear was concerned. The lowest surface roughness was achieved at the feed rate of equal to the cutting edge radius where as the lowest flank wear was observed at lowest depth of cut. Repeated machining trials have yet to be carried out in order to observe the tool life, sub-surface deformation and strain induced hardening which are also expecting to be amongst the critical issues in micro machining of NiTi. The machining performance using different cutting fluids and strategies have yet to be studied.

Keywords: nickel titanium, micro-machining, surface roughness, machinability

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Authors: Shienna Marie Esteban

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The economic growth experience of the Philippines is one of the fastest in Asia. However, the said growth has not yet trickled down to every Filipino. This is evident to agricultural-dependent population. Moreover, the contribution of the agriculture sector to GDP has been dwindling while large number of labor force is still dependent on a relatively small share of GDP. As a result, poverty incidence worsened among rural poor causing hunger and malnutrition. Therefore, the existing agricultural policies in the Philippines are pushing to achieve greater food production and productivity to alleviate poverty and food insecurity. Through a review of related literature and collection and analysis of secondary data from DA, DBM, BAS - CountrySTAT, PSA, NSCB, PIDS, IRRI, UN-FAO, IFPRI, and World Bank among others, the study revealed that Philippines is still far from its goals of poverty reduction and food security. In addition, the agricultural sector is underperforming. The productivity growth of the sector comes out mediocre. The common observation is that weakness is attributed to the failures of policy and institutional environments of the agriculture sector. The policy environment failed to create a structure appropriate for the rapid growth of the sector due to institutional and governance weaknesses. A recommendation is to go through institutional and policy reforms through legislative or executive mandates should take form to improve the implementation and enforcement of existing policies.

Keywords: agriculture, food security, policy, poverty

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Authors: Gokhan Erkal, Gulsen Aydin, Muge Yuce, Lokman Sahin

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This study aims to analyze the impacts of involving in mediation of conflicts in the Middle East from the perspective of the economic growth of the mediators. The Middle East is a highly volatile region of the world with rampant crises whose affects spill beyond its borders. Therefore, management and resolution of the conflicts in the region are of great significance. Mediation is an instrument used for abating violence and settling dispute. The recourse to mediation has grown to an important degree in recent years. However, for mediators, it is a daunting task to involve in the mediation of the deadlocks in the Middle East. This study tries to shed light on the positive correlation between economic growth of the mediator and the successful outcome of the mediation process to provide motivation for mediators. To this end, first, it briefly introduces the conflicts ongoing in the region and their negative impacts. Second, the methodology, time series analysis, and the data to be used, International Crisis Behavior Project Data, are presented. Third, the empirical test is carried out and the findings are evaluated. The conclusion highlights the benefits of successful mediation for the economic growth of the mediators of Middle Eastern crises.

Keywords: international crises, mediation, Middle East, times series analysis

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Authors: M. Kadela

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The load caused by the traffic movement should be transferred in the road constructions in a harmless way to the pavement as follows: − on the stiff upper layers of the structure (e.g. layers of asphalt: abrading and binding), and − through the layers of principal and secondary substructure, − on the subsoil, directly or through an improved subsoil layer. Reliable description of the interaction proceeding in a system “road construction – subsoil” should be in such case one of the basic requirements of the assessment of the size of internal forces of structure and its durability. Analyses of road constructions are based on: − elements of mechanics, which allows to create computational models, and − results of the experiments included in the criteria of fatigue life analyses. Above approach is a fundamental feature of commonly used mechanistic methods. They allow to use in the conducted evaluations of the fatigue life of structures arbitrarily complex numerical computational models. Considering the work of the system “road construction – subsoil”, it is commonly accepted that, as a result of repetitive loads on the subsoil under pavement, the growth of relatively small deformation in the initial phase is recognized, then this increase disappears, and the deformation takes the character completely reversible. The reliability of calculation model is combined with appropriate use (for a given type of analysis) of constitutive relationships. Phenomena occurring in the initial stage of the system “road construction – subsoil” is unfortunately difficult to interpret in the modeling process. The classic interpretation of the behavior of the material in the elastic-plastic model (e-p) is that elastic phase of the work (e) is undergoing to phase (e-p) by increasing the load (or growth of deformation in the damaging structure). The paper presents the essence of the calibration process of cooperating subsystem in the calculation model of the system “road construction – subsoil”, created for the mechanistic analysis. Calibration process was directed to show the impact of applied constitutive models on its deformation and stress response. The proper comparative base for assessing the reliability of created. This work was supported by the on-going research project “Stabilization of weak soil by application of layer of foamed concrete used in contact with subsoil” (LIDER/022/537/L-4/NCBR/2013) financed by The National Centre for Research and Development within the LIDER Programme. M. Kadela is with the Department of Building Construction Elements and Building Structures on Mining Areas, Building Research Institute, Silesian Branch, Katowice, Poland (phone: +48 32 730 29 47; fax: +48 32 730 25 22; e-mail: m.kadela@ itb.pl). models should be, however, the actual, monitored system “road construction – subsoil”. The paper presents too behavior of subsoil under cyclic load transmitted by pavement layers. The response of subsoil to cyclic load is recorded in situ by the observation system (sensors) installed on the testing ground prepared for this purpose, being a part of the test road near Katowice, in Poland. A different behavior of the homogeneous subsoil under pavement is observed for different seasons of the year, when pavement construction works as a flexible structure in summer, and as a rigid plate in winter. Albeit the observed character of subsoil response is the same regardless of the applied load and area values, this response can be divided into: - zone of indirect action of the applied load; this zone extends to the depth of 1,0 m under the pavement, - zone of a small strain, extending to about 2,0 m.

Keywords: road structure, constitutive model, calculation model, pavement, soil, FEA, response of soil, monitored system

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Authors: Torchane Lazhar

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In this work, our task consists in optimizing the nitriding treatment at low-temperature of the steel 32CrMoV13 by the way of the mixtures of ammonia gas, nitrogen and hydrogen to improve the mechanical properties of the surface (good wear resistance, friction and corrosion), and of the diffusion layer of the nitrogen (good resistance to fatigue and good tenacity with heart). By limiting our work to the pure iron and to the alloys iron-chromium and iron-chrome-carbon, we have studied the various parameters which manage the nitriding: flow rate and composition of the gaseous phase, the interaction chromium-nitrogen and chromium-carbon by the help of experiments of nitriding realized in the laboratory by thermogravimetry. The acquired knowledge have been applied by the mastery of the growth of the combination layer on the diffusion layer in the case of the industrial steel 32CrMoV13.

Keywords: diffusion of nitrogen, gaseous nitriding, layer growth kinetic, steel

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Authors: Mojtaba Farzaneh, Majid Baghaei Nejad

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This article proposes a new Flexible Capacitive Tactile Sensors based on paper sheets. This method combines the parameters of sensor's material and dielectric, and forms a new model of flexible capacitive sensors. The present article tries to present a practical explanation of this method's application and advantages. With the use of this new method, it is possible to make a more flexibility and accurate sensor in comparison with the current models. To assess the performance of this model, the common capacitive sensor is simulated and the proposed model of this article and one of the existing models are assessed. The results of this article indicate that the proposed model of this article can enhance the speed and accuracy of tactile sensor and has less error in comparison with the current models. Based on the results of this study, it can be claimed that in comparison with the current models, the proposed model of this article is capable of representing more flexibility and more accurate output parameters for touching the sensor, especially in abnormal situations and uneven surfaces, and increases accuracy and practicality.

Keywords: capacitive sensor, paper sheets, flexible, tactile, uneven

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Authors: Mosima M. Mabitsela

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Groundnut is preferably grown on light textured soils. Most of these light textured soils tend to be highly weathered and characterized by high soil acidity and low nutrient status. One major soil factor associated with infertility of acidic soils that can negatively depress groundnut yield is aluminium (Al) toxicity. In plants Al toxicity damages root cells, leading to inhibition of root growth as a result of the suppression of cell division, cell elongation and cell expansion in the apical meristem cells of the root. The end result is that roots become stunted and brittle, root hair development is poor, and the root apices become swollen. This study was conducted to determine the effects of aluminium (Al) toxicity on a range of groundnut varieties. Fifteen cultivars were tested in incremental aluminum (Al) supply in an ebb and flow solution culture laid out in a randomized complete block design. There were six aluminium (Al) treatments viz. 0 µM, 1 µM, 5.7 µM, 14.14 µM, 53.18 µM, and 200 µM. At 1 µM there was no inhibitory effect on the growth of groundnut. The inhibition of groundnut growth was noticeable from 5.7 µM to 200 µM, where the severe effect of aluminium (Al) stress was observed at 200 µM. The cultivars varied in their response to aluminium (Al) supply in solution culture. Groundnuts are one of the most important food crops in the world, and its supply is on a decline due to the light-textured soils that they thrive under as these soils are acidic and can easily solubilize aluminium (Al) to its toxic form. Consequently, there is a need to develop groundnut cultivars with high tolerance to soil acidity.

Keywords: aluminium toxicity, cultivars, reduction, root growth

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Authors: Stephen Olusanmi Akintayo, Ilesanmi Fadahunsi

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The ability of Lactic acid bacteria (LAB) to grow and survive in milk is being exploited in industrial and biotechnological applications. Although considerable studies have been reported on the fermentation of milk, however, not so much work has been documented on the selection of LAB strains from milk of the Nigerian local cattle breeds for their starter culture potentials. A total of 110 LAB were isolated from raw milk of Sokoto gudali cattle breed. The isolates were screened for their proteolytic activities on skimmed milk media with isolates A07, F06 and A01 showing the highest zone of clearance of 18.5mm, 18.5mm, and 18.0mm respectively and were selected for the studies of their growth in different constituents of milk. A01, F06, and A07 were identified as Pediococcus acidilactici, Lactococcus raffinolactis, and Leuconostoc mesenteriodes respectively using cultural, biochemical, physiological and molecular characterization techniques. Leuconostoc mesenteriodes showed the highest growth in all the milk components that were used in this study. The three LAB species selected showed a growth range of 6.46 log cfu/ml to 10.91 log cfu/ml in lactose with Leuconostoc mesenteriodes showing the highest growth of 10.91 log cfu/ml while Pediococcus acidilactici recorded the lowest growth of 9.78 log cfu/ml. In medium containing leucine as the only amino acid, the viable counts of Pediococcus acidilactici, Lactococcus raffinolactis and Leuconostoc mesenteriodes in log cfu/ml at zero hour were 6.39, 6.36 and 6.38 respectively which increased to 9.31 log cfu/ml, 9.21 log cfu/ml, 9.92 log cfu/ml respectively after 24 hours. Similarly, in all other substrates (casein, lysine, glutamic acid, aspartic acid, stearic acid and oleic acid ) tested in this study, Leuconostoc mesenteriodes showed the highest growth. It was observed that the highest quantity of lactic acid (15.31mg/ml) was produced by Leuconostoc mesenteriodes. The same trend was also observed in the production of diacetyl and hydrogen peroxide by the three tested microorganisms. Due to its ability to grow maximally in milk components, Leuconostoc mesenteriodes shows potential as starter culture for milk fermentation.

Keywords: Leuconostoc mesenteriodes, lactic acid bacteria, Sokoto gudali, starter culture

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Authors: Mohamed Yusuf

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Aim: The growth promoting the effect of the blue-green filamentous alga Spirulina platensis (SP) was observed on meat type Japanese quail with antibiotic growth promoter alternative and immune enhancing power. Materials and Methods: This study was conducted on 180 Japanese quail chicks for 4 weeks to find out the effect of diet type (vegetarian protein diet [VPD] and fish meal protein diet [FMPD])- Spirulina dose interaction (1 or 2 g/kg diet) on growth performance, gut microbiota, and sensory meat quality of growing Japanese quails (1-5 weeks old). Results: Data revealed improvement (p<0.05) of weight gain, feed conversion ratio, and European efficiency index due to 1, 2 g (SP)/kg VPD, and 2 g (SP)/kg FMPD, respectively. There was a significant decrease of ileum mean pH value by 1 g(SP)/kg VPD. Concerning gut microbiota, there was a trend toward an increase in Lactobacilli count in both 1; 2 g (SP)/kgVPD and 2 g (SP)/kg FMPD. It was concluded that 1 or 2 g (SP)/kg vegetarian diet may enhance parameters of performance without obvious effect on both meat quality and gut microbiota. Moreover, 1 and/or 2 g (SP) may not be invited to share fishmeal based diet for growing Japanese quails. Conclusion: Using of SP will support the profitable production of Japanese quails fed vegetable protein diet.

Keywords: isocaloric, isonitrogenous, meat quality, performances, quails, spirulina, spirulina

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Authors: Bi-Huei Tsai

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Previous studies on financial distress prediction choose the conventional failing and non-failing dichotomy; however, the distressed extent differs substantially among different financial distress events. To solve the problem, “non-distressed”, “slightly-distressed” and “reorganization and bankruptcy” are used in our article to approximate the continuum of corporate financial health. This paper explains different financial distress events using the two-stage method. First, this investigation adopts firm-specific financial ratios, corporate governance and market factors to measure the probability of various financial distress events based on multinomial logit models. Specifically, the bootstrapping simulation is performed to examine the difference of estimated misclassifying cost (EMC). Second, this work further applies macroeconomic factors to establish the credit cycle index and determines the distressed cut-off indicator of the two-stage models using such index. Two different models, one-stage and two-stage prediction models, are developed to forecast financial distress, and the results acquired from different models are compared with each other, and with the collected data. The findings show that the two-stage model incorporating financial ratios, corporate governance and market factors has the lowest misclassification error rate. The two-stage model is more accurate than the one-stage model as its distressed cut-off indicators are adjusted according to the macroeconomic-based credit cycle index.

Keywords: Multinomial logit model, corporate governance, company failure, reorganization, bankruptcy

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Authors: Sarisha Devnath, Oluwatosin A. Ijabadeniyi

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In recent years milk contamination has become a major problem in households; due to the likely occurrence of bacteria, even after the milk has been processed. One such genus of bacteria causing unwanted growth is Bacillus. This research project looks at the presence of spore formers in processed milk from household refrigerators and the effect of pasteurization and high temperature on Bacillus spores activation. 24 samples each of UHT milk and pasteurised milk from 24 households were sampled for the presence of spore formers. While anaerobic spore formers were not found in any of the samples, the average aerobic spore formers in UHT milk and pasteurized milk however were 5.77 cfu/ml and 5.88 cfu/ml respectively. After sequencing, it was detected that the mixed culture contained Bacillus cereus, for both pasteurised and UHT milk samples. For the activation study, raw milk samples were collected and subjected to four different temperatures; 65˚C, 72˚C, 80˚C, 100˚C respectively. Samples were stored for 7 days at 5˚C and 10˚C and analysed daily. The average aerobic spore formers in raw milk for samples stored at 5˚C range between 4.67-6.00 cfu/ml while it ranges between 4.84-6.00 cfu/ml at 10˚C, signifying that the high temperatures could have resulted in germination of dominant spores. Statistical analysis conducted on these results indicated a significant difference between the numbers of colonies present at the different treatment temperatures the bacterium was exposed to. This work showed that household milk may constitute public health risk furthermore; pasteurization and higher temperatures may not be effective to remove aerobic spore formers because of Bacillus spores activation.

Keywords: sporeformers, bacillus, spores, activation, milk

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Authors: Felix Schumann, Giorgia Carratta, Tobias Dauth, Liv Jaeckel

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In the last few decades, the rapid growth of the use and disposal of plastic items has led to their overaccumulation in the environment. As a result, plastic pollution has become a subject of global concern. Today plastics are used as raw materials in almost every industry. While the recognition of the ecological, social, and economic impact of plastics in academic research is on the rise, the potential role of the ‘plastic industry’ in dealing with such issues is still largely underestimated. Therefore, the literature on sustainable plastic management is still nascent and fragmented. Working towards sustainability requires a fundamental shift in the way companies employ plastics in their day-to-day business. For that reason, the applicability of the business model concept has recently gained momentum in environmental research. Business model innovation is increasingly recognized as an important driver to re-conceptualize the purpose of the firm and to readily integrate sustainability in their business. It can serve as a starting point to investigate whether and how sustainability can be realized under industry- and firm-specific circumstances. Yet, there is no comprehensive view in the plastic industry on how firms start refining their business models to embed sustainability in their operations. Our study addresses this gap, looking primarily at the industrial sectors responsible for the production of the largest amount of plastic waste today: plastic packaging, consumer goods, construction, textile, and transport. Relying on the archetypes of sustainable business models and applying them to the aforementioned sectors, we try to identify companies’ current strategies to make their business models more sustainable. Based on the thematic clustering, we can develop an integrative framework for the plastic industry. The findings are underpinned and illustrated by a variety of relevant plastic management solutions that the authors have identified through a systematic literature review and analysis of existing, empirically grounded research in this field. Using the archetypes, we can promote options for business model innovations for the most important sectors in which plastics are used. Moreover, by linking the proposed business model archetypes to the plastic industry, our research approach guides firms in exploring sustainable business opportunities. Likewise, researchers and policymakers can utilize our classification to identify best practices. The authors believe that the study advances the current knowledge on sustainable plastic management through its broad empirical industry analyses. Hence, the application of business model archetypes in the plastic industry will be useful for shaping companies’ transformation to create and deliver more sustainability and provides avenues for future research endeavors.

Keywords: business models, environmental economics, plastic management, plastic pollution, sustainability

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Authors: Alexandros Pournaras, Anastasia Papadopoulou, Serafim Kontos, Anastasios Karakostas

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The air quality of modern cities is an important concern, as poor air quality contributes to human health and environmental issues. Reliable air quality forecasting has, thus, gained scientific and governmental attention as an essential tool that enables authorities to take proactive measures for public safety. In this study, the potential of Machine Learning (ML) models to forecast PM2.5 at local scale is investigated in the city of Thessaloniki, the second largest city in Greece, which has been struggling with the persistent issue of air pollution. ML models, with proven ability to address timeseries forecasting, are employed to predict the PM2.5 concentrations and the respective Air Quality Index 5-days ahead by learning from daily historical air quality and meteorological data from 2014 to 2016 and gathered from two stations with different land use characteristics in the urban fabric of Thessaloniki. The performance of the ML models on PM2.5 concentrations is evaluated with common statistical methods, such as R squared (r²) and Root Mean Squared Error (RMSE), utilizing a portion of the stations’ measurements as test set. A multi-categorical evaluation is utilized for the assessment of their performance on respective AQIs. Several conclusions were made from the experiments conducted. Experimenting on MLs’ configuration revealed a moderate effect of various parameters and training schemas on the model’s predictions. Their performance of all these models were found to produce satisfactory results on PM2.5 concentrations. In addition, their application on untrained stations showed that these models can perform well, indicating a generalized behavior. Moreover, their performance on AQI was even better, showing that the MLs can be used as predictors for AQI, which is the direct information provided to the general public.

Keywords: Air Quality, AQ Forecasting, AQI, Machine Learning, PM2.5

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Authors: Ashish Kumar, Tejendra Dixit, I. A. Palani, Vipul Singh

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Zinc oxide, with its interesting properties such as large band gap (3.37eV), high exciton binding energy (60 meV) and intense UV absorption has been studied in literature for various applications viz. optoelectronics, biosensors, UV-photodetectors etc. The performance of ZnO devices is highly influenced by morphologies, size, crystallinity of the ZnO active layer and processing conditions. Recently, our group has shown the influence of the in situ addition of KMnO4 in the precursor solution during the hydrothermal growth of ZnO nanorods (NRs) on their near band edge (NBE) emission. In this paper, we have investigated the effect of post-growth annealing on the variations in NBE and deep level (DL) emissions of as grown ZnO nanorods. These observed results have been explained on the basis of X-ray Diffraction (XRD) and Raman spectroscopic analysis, which clearly show that improved crystalinity and quantum confinement in ZnO nanorods.

Keywords: ZnO, nanorods, hydrothermal, KMnO4

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Authors: M. Ouassaf, S. Belaid

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A series of quinoline derivatives with antimalarial activity were subjected to two-dimensional quantitative structure-activity relationship (2D-QSAR) studies. Three models were implemented using multiple regression linear MLR, a regression partial least squares (PLS), nonlinear regression (MNLR), to see which descriptors are closely related to the activity biologic. We relied on a principal component analysis (PCA). Based on our results, a comparison of the quality of, MLR, PLS, and MNLR models shows that the MNLR (R = 0.914 and R² = 0.835, RCV= 0.853) models have substantially better predictive capability because the MNLR approach gives better results than MLR (R = 0.835 and R² = 0,752, RCV=0.601)), PLS (R = 0.742 and R² = 0.552, RCV=0.550) The model of MNLR gave statistically significant results and showed good stability to data variation in leave-one-out cross-validation. The obtained results suggested that our proposed model MNLR may be useful to predict the biological activity of derivatives of quinoline.

Keywords: antimalarial, quinoline, QSAR, PCA, MLR , MNLR, MLR

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Authors: Jung-Il Kang, Jeon Eon Park, Yu-Jin Moon, Young-Seok Ahn, Eun-Sook Yoo, Hee-Kyoung Kang

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This study was conducted to evaluate the effect of Undariopsis peterseniana, a seaweed native to Jeju Island, Korea, on the growth of hair. The dermal papilla cells (DPCs) have known to regulate hair growth cycle and length of hair follicle through interact with epithelial cells. When immortalized vibrissa DPCs were treated with the U. peterseniana extract, the U. peterseniana extract significantly increased the proliferation of DPCs. The effect of U. peterseniana extract on the growth of vibrissa follicles was also examined. U. peterseniana extract significantly increased the hair-fiber lengths of the vibrissa follicles. Hair loss is partly caused by dihydrotestosterone (DHT) binding to androgen receptor in hair follicles, and the inhibition of 5α-reductase activity can prevent hair loss through the decrease of DHT level. The U. peterseniana extract inhibited 5α-reductase activity. Minoxidil, a potent hair-growth agent, can induce proliferation in NIH3T3 fibroblasts by opening KATP channels. We thus examined the proliferative effects of U. peterseniana extract in NIH3T3 fibroblasts. U. peterseniana extract significantly increased the proliferation of NIH3T3 fibroblasts. Tetraethylammonium chloride (TEA), a K+ channel blocker, inhibited U. peterseniana-induced proliferation in NIH3T3 fibroblasts. These results suggest that U. peterseniana could have the potential to treat alopecia through the proliferation of DPCs, the inhibition of 5α-reductase activity and the opening of KATP channels. [Acknowledgement] This research was supported by The Leading Human Resource Training Program of Regional Neo industry through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT and future Planning (2016H1D5A1908786).

Keywords: hair growth, Undariopsis peterseniana, vibrissa follicles, dermal papilla cells, 5α-reductase, KATP channels

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Authors: Xiongxiong You, Zhanwen Niu

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Choosing an appropriate surrogate model plays an important role in surrogates-assisted evolutionary algorithms (SAEAs) since there are many types and different kernel functions in the surrogate model. In this paper, an adaptive selection of the best suitable surrogate model method is proposed to solve different kinds of expensive optimization problems. Firstly, according to the prediction residual error sum of square (PRESS) and different model selection strategies, the excellent individual surrogate models are integrated into multiple ensemble models in each generation. Then, based on the minimum root of mean square error (RMSE), the best suitable surrogate model is selected dynamically. Secondly, two methods with dynamic number of models and selection strategies are designed, which are used to show the influence of the number of individual models and selection strategy. Finally, some compared studies are made to deal with several commonly used benchmark problems, as well as a rotor system optimization problem. The results demonstrate the accuracy and robustness of the proposed method.

Keywords: adaptive selection, expensive optimization, rotor system, surrogates assisted evolutionary algorithms

Procedia PDF Downloads 137