Search results for: normal and inverse Weibull models

Authors: Abolfazl Hosseinkhani, Sepehr Sanaye

Abstract:

Different approaches have been used to predict the performance of the vertical axis wind turbines (VAWT), such as experimental, computational fluid dynamics (CFD), and analytical methods. Analytical methods, such as momentum models that use streamtubes, have low computational cost and sufficient accuracy. The double multiple streamtube (DMST) is one of the most commonly used of momentum models, which divide the rotor plane of VAWT into upwind and downwind. In fact, results from the DMST method have shown some discrepancy compared with experiment results; that is because the Darrieus turbine is a complex and aerodynamically unsteady configuration. In this study, analytical-experimental-based corrections, including dynamic stall, streamtube expansion, and finite blade length correction are used to improve the DMST method. Results indicated that using these corrections for a SANDIA 17-m VAWT will lead to improving the results of DMST.

Keywords: Vertical axis wind turbine, analytical, double multiple streamtube, streamtube expansion model, dynamic stall model, finite blade length correction.

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Authors: Sacide Güzin Mazman, Yasemin Koçak Usluel

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Possible advantages of technology in educational context required the defining boundaries of formal and informal learning. Increasing opportunity to ubiquitous learning by technological support has revealed a question of how to discover the potential of individuals in the spontaneous environments such as social networks. This seems to be related with the question of what purposes in social networks have been being used? Social networks provide various advantages in educational context as collaboration, knowledge sharing, common interests, active participation and reflective thinking. As a consequence of these, the purpose of this study is composed of proposing a new model that could determine factors which effect adoption of social network applications for usage in educational context. While developing a model proposal, the existing adoption and diffusion models have been reviewed and they are thought to be suitable on handling an original perspective instead of using completely other diffusion or acceptance models because of different natures of education from other organizations. In the proposed model; social factors, perceived ease of use, perceived usefulness and innovativeness are determined four direct constructs that effect adoption process. Facilitating conditions, image, subjective norms and community identity are incorporated to model as antecedents of these direct four constructs.

Keywords: Adoption of innovation, educational context, social networks.

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Authors: M. S. Mahmoud

Abstract:

This study was conducted to evaluate the manganese removal from aqueous solution using Banana peels activated carbon (BPAC). Batch experiments have been carried out to determine the influence of parameters such as pH, biosorbent dose, initial metal ion concentrations and contact times on the biosorption process. From these investigations, a significant increase in percentage removal of manganese 97.4% is observed at pH value 5.0, biosorbent dose 0.8 g, initial concentration 20 ppm, temperature 25 ± 2°C, stirring rate 200 rpm and contact time 2h. The equilibrium concentration and the adsorption capacity at equilibrium of the experimental results were fitted to the Langmuir and Freundlich isotherm models; the Langmuir isotherm was found to well represent the measured adsorption data implying BPAC had heterogeneous surface. A raw groundwater samples were collected from Baharmos groundwater treatment plant network at Embaba and Manshiet Elkanater City/District-Giza, Egypt, for treatment at the best conditions that reached at first phase by BPAC. The treatment with BPAC could reduce iron and manganese value of raw groundwater by 91.4% and 97.1%, respectively and the effect of the treatment process on the microbiological properties of groundwater sample showed decrease of total bacterial count either at 22°C or at 37°C to 85.7% and 82.4%, respectively. Also, BPAC was characterized using SEM and FTIR spectroscopy.

Keywords: Biosorption, banana peels, isothermal models, manganese.

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Authors: N. P. Tsephe, S. D. Eyono Obono

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Rural tourism is usually associated with rural development because it has strong linkages to rural resources; but it remains underdeveloped compared to urban tourism. This underdevelopment of rural tourism serves as a motivation for this study whose aim is to examine the factors affecting the perceived satisfaction of rural tourists. The objectives of this study are: to identify and design theories and models on rural tourism satisfaction, and to empirically validate these models and theories through a survey of tourists from the Malealea Lodge which is located in the Mafeteng District, in the Mountain Kingdom of Lesotho. Data generated by the collection of questionnaires used by this survey was analyzed quantitatively using descriptive statistics and correlations in SPSS after checking the validity and the reliability of the questionnaire. The main hypothesis behind this study is the relationship between the demographics of rural tourists, their motivation, and their satisfaction, as supported by existing literature; except that motivation is measured in this study according to three dimensions: push factors, pull factors, and perceived usefulness of ICTs in the rural tourism experience. Findings from this study indicate that among the demographics factors, continent of origin and marital status influence the satisfaction of rural tourists; and their occupation affects their perceptions on the use of ICTs in rural tourism. Moreover, only pull factors were found to influence the satisfaction of rural tourists.

Keywords: Digital world, Motivation, Rural tourism, Satisfaction.

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Authors: T. P. Athira, Gibin Chacko George

Abstract:

This paper proposes a dual tree complex wavelet transform (DT-CWT) based directional interpolation scheme for noisy images. The problems of denoising and interpolation are modelled as to estimate the noiseless and missing samples under the same framework of optimal estimation. Initially, DT-CWT is used to decompose an input low-resolution noisy image into low and high frequency subbands. The high-frequency subband images are interpolated by linear minimum mean square estimation (LMMSE) based interpolation, which preserves the edges of the interpolated images. For each noisy LR image sample, we compute multiple estimates of it along different directions and then fuse those directional estimates for a more accurate denoised LR image. The estimation parameters calculated in the denoising processing can be readily used to interpolate the missing samples. The inverse DT-CWT is applied on the denoised input and interpolated high frequency subband images to obtain the high resolution image. Compared with the conventional schemes that perform denoising and interpolation in tandem, the proposed DT-CWT based noisy image interpolation method can reduce many noise-caused interpolation artifacts and preserve well the image edge structures. The visual and quantitative results show that the proposed technique outperforms many of the existing denoising and interpolation methods.

Keywords: Dual-tree complex wavelet transform (DT-CWT), denoising, interpolation, optimal estimation, super resolution.

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Authors: S. Areerachakul

Abstract:

Nowadays, several techniques such as; Fuzzy Inference System (FIS) and Neural Network (NN) are employed for developing of the predictive models to estimate parameters of water quality. The main objective of this study is to compare between the predictive ability of the Adaptive Neuro-Fuzzy Inference System (ANFIS) model and Artificial Neural Network (ANN) model to estimate the Biochemical Oxygen Demand (BOD) on data from 11 sampling sites of Saen Saep canal in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage, Bangkok Metropolitan Administration, during 2004-2011. The five parameters of water quality namely Dissolved Oxygen (DO), Chemical Oxygen Demand (COD), Ammonia Nitrogen (NH3N), Nitrate Nitrogen (NO3N), and Total Coliform bacteria (T-coliform) are used as the input of the models. These water quality indices affect the biochemical oxygen demand. The experimental results indicate that the ANN model provides a higher correlation coefficient (R=0.73) and a lower root mean square error (RMSE=4.53) than the corresponding ANFIS model.

Keywords: adaptive neuro-fuzzy inference system, artificial neural network, biochemical oxygen demand, surface water.

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Authors: Mohammad Reza Ayatollahzadeh Shirazi, Pooya Jaferian, Golnaz Elahi, Hamid Baghi, Babak Sadeghian

Abstract:

The world is moving rapidly toward the deployment of information and communication systems. Nowadays, computing systems with their fast growth are found everywhere and one of the main challenges for these systems is increasing attacks and security threats against them. Thus, capturing, analyzing and verifying security requirements becomes a very important activity in development process of computing systems, specially in developing systems such as banking, military and e-business systems. For developing every system, a process model which includes a process, methods and tools is chosen. The Rational Unified Process (RUP) is one of the most popular and complete process models which is used by developers in recent years. This process model should be extended to be used in developing secure software systems. In this paper, the Requirement Discipline of RUP is extended to improve RUP for developing secure software systems. These proposed extensions are adding and integrating a number of Activities, Roles, and Artifacts to RUP in order to capture, document and model threats and security requirements of system. These extensions introduce a group of clear and stepwise activities to developers. By following these activities, developers assure that security requirements are captured and modeled. These models are used in design, implementation and test activitie

Keywords:

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Authors: Sushovan Sarkar, Debabrata Mazumder

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Hybrid bioreactor having both suspended-growth and attached-growth bacteria is found a novel and excellent bioreactor system for treating the municipal wastewater containing inhibitory substrates too. In this reactor a fraction of substrate is used by suspended biomass and the remaining by attached biomass resulting in the competition between the two growths for the substrate. The combination of suspended and attached growth provides the system with enhanced biomass concentration and sludge age more than those in ASP. Similar to attached growth system, the hybrid bioreactor ensures considerable efficiency for treating toxic and refractory substances in wastewater. For the process design of hybrid bioreactor a suitable mathematical model is required. Although various mathematical models were developed on hybrid bioreactor in due course of time in earlier research works, none of them was found having a specific simplified solution of the corresponding models and without having any drawback. To overcome this drawback authors already developed a simplified mathematical model for process design of a hybrid bioreactor. The present paper briefly highlights on the various aspects of process design of an aerobic hybrid bioreactor for the treatment of municipal wastewater.

Keywords: Hybrid bioreactor, mathematical model, process design, application, municipal wastewater.

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Authors: P. van Tonder, C. C. Kruger

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Concrete structures deteriorate over time and degradation escalates due to various factors. The rate of deterioration can be complex and unpredictable in nature. Such deteriorations may be located beneath the surface of the concrete at high elevations. This emphasizes the need for an efficient method of finding such defects to be able to assess the severity thereof. Current methods using thermography to find defects require equipment to reach higher elevations. This could become costly and time consuming not to mention the risks involved in having personnel scaffold or abseiling at such heights. Accordingly, by combining the thermal camera needed for thermography and a remotely piloted aerial system (Drone/RPAS), it could be used to alleviate some of the issues mentioned. Images can be translated into a 3D temperature model to aid concrete diagnostics and with further research can relate back to the mechanical properties of the structure but will not be dealt with in this paper. Such diagnostics includes finding delamination, similar to finding delamination on concrete decks, which resides beneath the surface of the concrete before spalling can occur. Delamination can be caused by reinforcement eroding and causing expansion beneath the concrete surface. This could lead to spalling, where concrete pieces start breaking off from the main concrete structure.

Keywords: Concrete, diagnostic, infrared thermography, 3D thermal models.

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Authors: J. Mizuno, S. Takahashi

Abstract:

In this paper, design and fabrication of an actuated parallel-plate mirror based on a 3D-printer is described. The mirror and electrode layers are fabricated separately and assembled thereafter. The alignment is performed by dowel pin-hole pairs fabricated on the respective layers. The electrodes are formed on the surface of the electrode layer by Au ion sputtering using a suitable mask, which is also fabricated by a 3D-printer.For grounding the mirror layer, except the contact area with the electrode paths, all the surface is Au ion sputtered. 3D-printers are widely used for creating 3D models or mock-ups. The authors have recently proposed that these models can perform electromechanical functions such as actuators by suitably masking them followed by metallization process. Since the smallest possible fabrication size is in the order of sub-millimeters, these electromechanical devices are named by the authors as SMEMS (Sub-Milli Electro-Mechanical Systems) devices. The proposed mirror described in this paper which consists of parallel-plate electrostatic actuators is also one type of SMEMS devices. In addition, SMEMS is totally environment-clean compared to MEMS (Micro Electro-Mechanical Systems) fabrication processes because any hazardous chemicals or gases are utilized.

Keywords: MEMS, parallel-plate mirror, SMEMS, 3D-printer.

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Authors: Taru Hakanen, Mervi Murtonen

Abstract:

This study aims to increase understanding of the transition of business models in servitization. The significance of service in all business has increased dramatically during the past decades. Service-dominant logic (SDL) describes this change in the economy and questions the goods-dominant logic on which business has primarily been based in the past. A business model canvas is one of the most cited and used tools in defining end developing business models. The starting point of this paper lies in the notion that the traditional business model canvas is inherently goods-oriented and best suits for product-based business. However, the basic differences between goods and services necessitate changes in business model representations when proceeding in servitization. Therefore, new knowledge is needed on how the conception of business model and the business model canvas as its representation should be altered in servitized firms in order to better serve business developers and interfirm co-creation. That is to say, compared to products, services are intangible and they are co-produced between the supplier and the customer. Value is always co-created in interaction between a supplier and a customer, and customer experience primarily depends on how well the interaction succeeds between the actors. The role of service experience is even stronger in service business compared to product business, as services are co-produced with the customer. This paper provides business model developers with a service business model canvas, which takes into account the intangible, interactive, and relational nature of service. The study employs a design science approach that contributes to theory development via design artifacts. This study utilizes qualitative data gathered in workshops with ten companies from various industries. In particular, key differences between Goods-dominant logic (GDL) and SDLbased business models are identified when an industrial firm proceeds in servitization. As the result of the study, an updated version of the business model canvas is provided based on service-dominant logic. The service business model canvas ensures a stronger customer focus and includes aspects salient for services, such as interaction between companies, service co-production, and customer experience. It can be used for the analysis and development of a current service business model of a company or for designing a new business model. It facilitates customer-focused new service design and service development. It aids in the identification of development needs, and facilitates the creation of a common view of the business model. Therefore, the service business model canvas can be regarded as a boundary object, which facilitates the creation of a common understanding of the business model between several actors involved. The study contributes to the business model and service business development disciplines by providing a managerial tool for practitioners in service development. It also provides research insight into how servitization challenges companies’ business models.

Keywords: Boundary object, business model canvas, managerial tool, service-dominant logic.

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Authors: M. Tufekci, C. Guven

Abstract:

In Automotive Industry, sliding door systems that are also used as body closures are safety members. Extreme product tests are realized to prevent failures in design process, but these tests realized experimentally result in high costs. Finite element analysis is an effective tool used for design process. These analyses are used before production of prototype for validation of design according to customer requirement. In result of this, substantial amount of time and cost is saved. Finite element model is created for geometries that are designed in 3D CAD programs. Different element types as bar, shell and solid, can be used for creating mesh model. Cheaper model can be created by selection of element type, but combination of element type that was used in model, number and geometry of element and degrees of freedom affects the analysis result. Sliding door system is a good example which used these methods for this study. Structural analysis was realized for sliding door mechanism by using FE models. As well, physical tests that have same boundary conditions with FE models were realized. Comparison study for these element types, were done regarding test and analyses results then optimum combination was achieved.

Keywords: Finite Element Analysis, Sliding Door Mechanism, Element Type, Structural Analysis.

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Authors: Marzhan Baimurzayeva, Alibek Utyanov, Gulnar Shabdarbaeva, Damir Khussainov

Abstract:

This article introduces the actual problem that is а study of proposed by the authors Hydrocele ointment in amino acids’ metabolism of cows’ blood in inflammation of traumatic origin. Hydrocele ointment has shown a positive effect on inflammatory process and amino acids’ metabolism of animals treated with the drug. Amino acid levels reached physiological parameters on the 10th day after treatment; in the control group this parameter was higher than normal.

Keywords: Amino acids, blood protein, Hydrocele ointment, inflammation, repair.

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Authors: Y. Zheng, W. Sun

Abstract:

This paper describes a new approach which can be used to interpret the experimental creep deformation data obtained from miniaturized thin plate bending specimen test to the corresponding uniaxial data based on an inversed application of the reference stress method. The geometry of the thin plate is fully defined by the span of the support, l, the width, b, and the thickness, d. Firstly, analytical solutions for the steady-state, load-line creep deformation rate of the thin plates for a Norton’s power law under plane stress (b→0) and plane strain (b→∞) conditions were obtained, from which it can be seen that the load-line deformation rate of the thin plate under plane-stress conditions is much higher than that under the plane-strain conditions. Since analytical solution is not available for the plates with random b-values, finite element (FE) analyses are used to obtain the solutions. Based on the FE results obtained for various b/l ratios and creep exponent, n, as well as the analytical solutions under plane stress and plane strain conditions, an approximate, numerical solutions for the deformation rate are obtained by curve fitting. Using these solutions, a reference stress method is utilised to establish the conversion relationships between the applied load and the equivalent uniaxial stress and between the creep deformations of thin plate and the equivalent uniaxial creep strains. Finally, the accuracy of the empirical solution was assessed by using a set of “theoretical” experimental data.

Keywords: Bending, Creep, Miniature Specimen, Thin Plate.

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Authors: Sandipan Chakroborty, Anindya Roy, Goutam Saha

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A state of the art Speaker Identification (SI) system requires a robust feature extraction unit followed by a speaker modeling scheme for generalized representation of these features. Over the years, Mel-Frequency Cepstral Coefficients (MFCC) modeled on the human auditory system has been used as a standard acoustic feature set for SI applications. However, due to the structure of its filter bank, it captures vocal tract characteristics more effectively in the lower frequency regions. This paper proposes a new set of features using a complementary filter bank structure which improves distinguishability of speaker specific cues present in the higher frequency zone. Unlike high level features that are difficult to extract, the proposed feature set involves little computational burden during the extraction process. When combined with MFCC via a parallel implementation of speaker models, the proposed feature set outperforms baseline MFCC significantly. This proposition is validated by experiments conducted on two different kinds of public databases namely YOHO (microphone speech) and POLYCOST (telephone speech) with Gaussian Mixture Models (GMM) as a Classifier for various model orders.

Keywords: Complementary Information, Filter Bank, GMM, IMFCC, MFCC, Speaker Identification, Speaker Recognition.

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Authors: Hadia Abdel Aziz, Raghda El Ebrashi

Abstract:

Business models are shaped by their design space or the environment they are designed to be implemented in. The rapidly changing economic, technological, political, regulatory and market external environment severely affects business logic. This is particularly true for social enterprises whose core mission is to transform their environments, and thus, their whole business logic revolves around the interchange between the enterprise and the environment. The context in which social business operates imposes different business design constraints while at the same time, open up new design opportunities. It is also affected to a great extent by the impact that successful enterprises generate; a continuous loop of interaction that needs to be managed through a dynamic capability in order to generate a lasting powerful impact. This conceptual research synthesizes and analyzes literature on social enterprise, social enterprise business models, business model innovation, business model design, and the open system view theory to propose a new business model design process for social enterprises that takes into account the critical role of environmental factors. This process would help the social enterprise develop a dynamic capability that ensures the alignment of its business model to its environmental context, thus, maximizing its probability of success.

Keywords: Social enterprise, business model, business model design.

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Authors: S. K. Tomar, R. Prasad, S. Panda, C. Ardil

Abstract:

Reduction of Single Input Single Output (SISO) discrete systems into lower order model, using a conventional and an evolutionary technique is presented in this paper. In the conventional technique, the mixed advantages of Modified Cauer Form (MCF) and differentiation are used. In this method the original discrete system is, first, converted into equivalent continuous system by applying bilinear transformation. The denominator of the equivalent continuous system and its reciprocal are differentiated successively, the reduced denominator of the desired order is obtained by combining the differentiated polynomials. The numerator is obtained by matching the quotients of MCF. The reduced continuous system is converted back into discrete system using inverse bilinear transformation. In the evolutionary technique method, Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example.

Keywords: Discrete System, Single Input Single Output (SISO), Bilinear Transformation, Reduced Order Model, Modified CauerForm, Polynomial Differentiation, Particle Swarm Optimization, Integral Squared Error.

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Authors: Kazeem K. Adewole, Julia M. Race, Steve J. Bull

Abstract:

The fracture performance of steel wires for civil engineering applications remains a major concern in civil engineering construction and maintenance of wire reinforced structures. The need to employ approaches that simulate micromechanical material processes which characterizes fracture in civil structures has been emphasized recently in the literature. However, choosing from the numerous micromechanics-based fracture models, and identifying their applicability and reliability remains an issue that still needs to be addressed in a greater depth. Laboratory tensile testing and finite element tensile testing simulations with the shear, ductile and Gurson-Tvergaard-Needleman’s micromechanics-based models conducted in this work reveal that the shear fracture model is an appropriate fracture model to predict the fracture performance of steel wires used for civil engineering applications. The need to consider the capability of the micromechanics-based fracture model to predict the “cup and cone” fracture exhibited by the wire in choosing the appropriate fracture model is demonstrated.

Keywords: Fracture performance, FE simulation, Shear fracture model, Ductile fracture model, Gurson-Tvergaard-Needleman fracture model, Wires.

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Authors: Hamid Goharnejad, Amir Hossein Eghbali

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Recent investigations have demonstrated the global sea level rise due to climate change impacts. In this study, climate changes study the effects of increasing water level in the strait of Hormuz. The probable changes of sea level rise should be investigated to employ the adaption strategies. The climatic output data of a GCM (General Circulation Model) named CGCM3 under climate change scenario of A1b and A2 were used. Among different variables simulated by this model, those of maximum correlation with sea level changes in the study region and least redundancy among themselves were selected for sea level rise prediction by using stepwise regression. One of models (Discrete Wavelet artificial Neural Network) was developed to explore the relationship between climatic variables and sea level changes. In these models, wavelet was used to disaggregate the time series of input and output data into different components and then ANN was used to relate the disaggregated components of predictors and input parameters to each other. The results showed in the Shahid Rajae Station for scenario A1B sea level rise is among 64 to 75 cm and for the A2 Scenario sea level rise is among 90 t0 105 cm. Furthermore, the result showed a significant increase of sea level at the study region under climate change impacts, which should be incorporated in coastal areas management.

Keywords: Climate change scenarios, sea-level rise, strait of Hormuz, artificial neural network, fuzzy logic.

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Authors: Iosif-Viorel Onut, Bin Zhu, Ali A. Ghorbani

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We propose a novel graphical technique (SVision) for intrusion detection, which pictures the network as a community of hosts independently roaming in a 3D space defined by the set of services that they use. The aim of SVision is to graphically cluster the hosts into normal and abnormal ones, highlighting only the ones that are considered as a threat to the network. Our experimental results using DARPA 1999 and 2000 intrusion detection and evaluation datasets show the proposed technique as a good candidate for the detection of various threats of the network such as vertical and horizontal scanning, Denial of Service (DoS), and Distributed DoS (DDoS) attacks.

Keywords: Anomaly Visualization, Network Security, Intrusion Detection.

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Authors: Suphat Rittirat, Sutha Klaocheed, Kanchit Thammasiri

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The effects of thidiazuron (TDZ) and benzyladenine (BA) on protocorm-like bodies (PLBs) induction from leaf explants was investigated. It was found that TDZ was superior to BA. The highest percentage and number of PLBs per leaf explant at 30 and 5.3, respectively were obtained on ½ MS medium supplemented with 9µM TDZ. The regenerated plantlets were potted and acclimatized in the greenhouse. These plants grew well and developed into normal plants after 3 month of transplantation. The 100% survival of plantlets was achieved when planted on pots containing sphagnum moss. 

Keywords: Orchid, PLBs, sphagnum moss, thidiazuron.

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Authors: S. Kulsri, M. Jaroensutasinee, K. Jaroensutasinee

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We developed a new method based on quasimolecular modeling to simulate the cavity flow in three cavity shapes: rectangular, half-circular and bucket beer in cgs units. Each quasi-molecule was a group of particles that interacted in a fashion entirely analogous to classical Newtonian molecular interactions. When a cavity flow was simulated, the instantaneous velocity vector fields were obtained by using an inverse distance weighted interpolation method. In all three cavity shapes, fluid motion was rotated counter-clockwise. The velocity vector fields of the three cavity shapes showed a primary vortex located near the upstream corners at time t ~ 0.500 s, t ~ 0.450 s and t ~ 0.350 s, respectively. The configurational kinetic energy of the cavities increased as time increased until the kinetic energy reached a maximum at time t ~ 0.02 s and, then, the kinetic energy decreased as time increased. The rectangular cavity system showed the lowest kinetic energy, while the half-circular cavity system showed the highest kinetic energy. The kinetic energy of rectangular, beer bucket and half-circular cavities fluctuated about stable average values 35.62 x 103, 38.04 x 103 and 40.80 x 103 ergs/particle, respectively. This indicated that the half-circular shapes were the most suitable shape for a shrimp pond because the water in shrimp pond flows best when we compared with rectangular and beer bucket shape.

Keywords: Quasi-molecular modelling, particle modelling, lid driven cavity flow.

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Authors: Rafayel A. Azizyan, Aram E. Gevorgyan, Valeri B. Arakelyan, Emil S. Gevorgyan

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Currently, mathematical and computer modeling are widely used in different biological studies to predict or assess behavior of such a complex systems as a biological are. This study deals with mathematical and computer modeling of bi-substrate enzymatic reactions, which play an important role in different biochemical pathways. The main objective of this study is to represent the results from in silico investigation of bi-substrate enzymatic reactions in the presence of uncompetitive inhibitors, as well as to describe in details the inhibition effects. Four models of uncompetitive inhibition were designed using different software packages. Particularly, uncompetitive inhibitor to the first [ES₁] and the second ([ES₁S₂]; [FS₂]) enzyme-substrate complexes have been studied. The simulation, using the same kinetic parameters for all models allowed investigating the behavior of reactions as well as determined some interesting aspects concerning influence of different cases of uncompetitive inhibition. Besides, it has been shown that uncompetitive inhibitors exhibit specific selectivity depending on mechanism of bi-substrate enzymatic reaction. 

Keywords: Mathematical modeling, bi-substrate enzymatic reactions, sequential mechanism, ping-pong mechanism, uncompetitive inhibition.

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Authors: R.Abbaszadeh, A.Rajabipour, M.Delshad, M.J.Mahjub, H.Ahmadi

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It is difficult to judge ripeness by outward characteristics such as size or external color. In this paper a nondestructive method was studied to determine watermelon (Crimson Sweet) quality. Responses of samples to excitation vibrations were detected using laser Doppler vibrometry (LDV) technology. Phase shift between input and output vibrations were extracted overall frequency range. First and second were derived using frequency response spectrums. After nondestructive tests, watermelons were sensory evaluated. So the samples were graded in a range of ripeness based on overall acceptability (total desired traits consumers). Regression models were developed to predict quality using obtained results and sample mass. The determination coefficients of the calibration and cross validation models were 0.89 and 0.71 respectively. This study demonstrated feasibility of information which is derived vibration response curves for predicting fruit quality. The vibration response of watermelon using the LDV method is measured without direct contact; it is accurate and timely, which could result in significant advantage for classifying watermelons based on consumer opinions.

Keywords: Laser Doppler vibrometry, Phase shift, Overallacceptability, Regression model , Resonance frequency, Watermelon

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Authors: Yingguo Li

Abstract:

In this paper, we consider a discrete Gompertz model with time delay. Firstly, the stability of the equilibrium of the system is investigated by analyzing the characteristic equation. By choosing the time delay as a bifurcation parameter, we prove that Neimark- Sacker bifurcations occur when the delay passes a sequence of critical values. The direction and stability of the Neimark-Sacker are determined by using normal forms and centre manifold theory. Finally, some numerical simulations are given to verify the theoretical analysis.

Keywords: Gompertz system, Neimark-Sacker bifurcation, stability, time delay.

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Authors: Mehdi Seifbarghy, Sajjad Jalali, Seyed Habib A. Rahmati

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Recently studies in area of supply chain network (SCN) have focused on the disruption issues in distribution systems. Also this paper extends the previous literature by providing a new biobjective model for cost minimization of designing a three echelon SCN across normal and failure scenarios with considering multi capacity option for manufacturers and distribution centers. Moreover, in order to solve the problem by means of LINGO software, novel model will be reformulated through a branch of LP-Metric method called Min-Max approach.

Keywords: Scenario programming, Distribution, Multi-echelon supply chain design, Reliable facility

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Authors: Yi Chao Ma, Cheng Siong Chin, Wai Lok Woo

Abstract:

Since the last decade, there has been a rapid growth in digital multimedia, such as high-resolution media files and threedimentional movies. Hence, there is a need for large digital storage such as Hard Disk Drive (HDD). As such, users expect to have a quieter HDD in their laptop. In this paper, a jury test has been conducted on a group of 34 people where 17 of them are students who are the potential consumer, and the remaining are engineers who know the HDD. A total 13 HDD sound samples have been selected from over hundred HDD noise recordings. These samples are selected based on an agreed subjective feeling. The samples are played to the participants using head acoustic playback system, which enabled them to experience as similar as possible the same environment as have been recorded. Analysis has been conducted and the obtained results have indicated different group has different perception over the noises. Two neural network-based acoustic annoyance models are established based on back propagation neural network. Four psychoacoustic metrics, loudness, sharpness, roughness and fluctuation strength, are used as the input of the model, and the subjective evaluation results are taken as the output. The developed models are reasonably accurate in simulating both training and test samples.

Keywords: Hard disk drive noise, jury test, neural network model, psychoacoustic annoyance.

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Authors: Siddhant Rao

Abstract:

Studies estimate that there will be 266,120 new cases of invasive breast cancer and 40,920 breast cancer induced deaths in the year of 2018 alone. Despite the pervasiveness of this affliction, the current process to obtain an accurate breast cancer prognosis is tedious and time consuming. It usually requires a trained pathologist to manually examine histopathological images and identify the features that characterize various cancer severity levels. We propose MITOS-RCNN: a region based convolutional neural network (RCNN) geared for small object detection to accurately grade one of the three factors that characterize tumor belligerence described by the Nottingham Grading System: mitotic count. Other computational approaches to mitotic figure counting and detection do not demonstrate ample recall or precision to be clinically viable. Our models outperformed all previous participants in the ICPR 2012 challenge, the AMIDA 2013 challenge and the MITOS-ATYPIA-14 challenge along with recently published works. Our model achieved an F- measure score of 0.955, a 6.11% improvement in accuracy from the most accurate of the previously proposed models.

Keywords: Object detection, histopathology, breast cancer, mitotic count, deep learning, computer vision.

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi

Abstract:

This study was designed to find the best stochastic model (using of time series analysis) for annual extreme streamflow (peak and maximum streamflow) of Karkheh River at Iran. The Auto-regressive Integrated Moving Average (ARIMA) model used to simulate these series and forecast those in future. For the analysis, annual extreme streamflow data of Jelogir Majin station (above of Karkheh dam reservoir) for the years 1958–2005 were used. A visual inspection of the time plot gives a little increasing trend; therefore, series is not stationary. The stationarity observed in Auto-Correlation Function (ACF) and Partial Auto-Correlation Function (PACF) plots of annual extreme streamflow was removed using first order differencing (d=1) in order to the development of the ARIMA model. Interestingly, the ARIMA(4,1,1) model developed was found to be most suitable for simulating annual extreme streamflow for Karkheh River. The model was found to be appropriate to forecast ten years of annual extreme streamflow and assist decision makers to establish priorities for water demand. The Statistical Analysis System (SAS) and Statistical Package for the Social Sciences (SPSS) codes were used to determinate of the best model for this series.

Keywords: Stochastic models, ARIMA, extreme streamflow, Karkheh River.

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Authors: Cristian Păuna

Abstract:

In the first decades of the 21st century, in the electronic trading environment, algorithmic capital investments became the primary tool to make a profit by speculations in financial markets. A significant number of traders, private or institutional investors are participating in the capital markets every day using automated algorithms. The autonomous trading software is today a considerable part in the business intelligence system of any modern financial activity. The trading decisions and orders are made automatically by computers using different mathematical models. This paper will present one of these models called Price Prediction Line. A mathematical algorithm will be revealed to build a reliable trend line, which is the base for limit conditions and automated investment signals, the core for a computerized investment system. The paper will guide how to apply these tools to generate entry and exit investment signals, limit conditions to build a mathematical filter for the investment opportunities, and the methodology to integrate all of these in automated investment software. The paper will also present trading results obtained for the leading German financial market index with the presented methods to analyze and to compare different automated investment algorithms. It was found that a specific mathematical algorithm can be optimized and integrated into an automated trading system with good and sustained results for the leading German Market. Investment results will be compared in order to qualify the presented model. In conclusion, a 1:6.12 risk was obtained to reward ratio applying the trigonometric method to the DAX Deutscher Aktienindex on 24 months investment. These results are superior to those obtained with other similar models as this paper reveal. The general idea sustained by this paper is that the Price Prediction Line model presented is a reliable capital investment methodology that can be successfully applied to build an automated investment system with excellent results.

Keywords: Algorithmic trading, automated investment system, DAX Deutscher Aktienindex.

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