Search results for: correlated k(CK) model

Authors: P. Singh, R. M. Banik

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Artificial neural network (ANN) was employed to optimize assay parameters viz., time, temperature, pH of reaction mixture, enzyme volume and substrate concentration of L-glutaminase from Bacillus cereus MTCC 1305. ANN model showed high value of coefficient of determination (0.9999), low value of root mean square error (0.6697) and low value of absolute average deviation. A multilayer perceptron neural network trained with an error back-propagation algorithm was incorporated for developing a predictive model and its topology was obtained as 5-3-1 after applying Levenberg Marquardt (LM) training algorithm. The predicted activity of L-glutaminase was obtained as 633.7349 U/l by considering optimum assay parameters, viz., pH of reaction mixture (7.5), reaction time (20 minutes), incubation temperature (35˚C), substrate concentration (40mM), and enzyme volume (0.5ml). The predicted data was verified by running experiment at simulated optimum assay condition and activity was obtained as 634.00 U/l. The application of ANN model for optimization of assay conditions improved the activity of L-glutaminase by 1.499 fold.

Keywords: Bacillus cereus, L-glutaminase, assay parameters, artificial neural network

Procedia PDF Downloads 422

Authors: Buket Metin

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Buildings cause a variety of loads on the environment due to activities performed at each stage of the building life cycle. Construction is the first stage that affects both the natural and built environments at different steps of the process, which can be defined as transportation of materials within the construction site, formation and preparation of materials on-site and the application of materials to realize the building subsystems. All of these steps require the use of technology, which varies based on the facilities that contractors and subcontractors have. Hence, environmental consequences of the construction process should be tackled by focusing on construction technology options used in every step of the process. This paper presents an environmental decision-making model for assessing on-site performances of subcontractors based on the construction technology options which they can supply. First, construction technologies, which constitute information, tools and methods, are classified. Then, environmental performance criteria are set forth related to resource consumption, ecosystem quality, and human health issues. Finally, the model is developed based on the relationships between the construction technology components and the environmental performance criteria. The Fuzzy Analytical Hierarchy Process (FAHP) method is used for weighting the environmental performance criteria according to environmental priorities of decision-maker(s), while the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is used for ranking on-site environmental performances of subcontractors using quantitative data related to the construction technology components. Thus, the model aims to provide an insight to decision-maker(s) about the environmental consequences of the construction process and to provide an opportunity to improve the overall environmental performance of construction sites.

Keywords: construction process, construction technology, decision making, environmental performance, subcontractor

Procedia PDF Downloads 236

Authors: S. Mezghani, E. Perrin, J. L. Bodnar, J. Marthe, B. Cauwe, V. Vrabie

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Non contact evaluation of the thickness of paint coatings can be attempted by different destructive and nondestructive methods such as cross-section microscopy, gravimetric mass measurement, magnetic gauges, Eddy current, ultrasound or terahertz. Infrared thermography is a nondestructive and non-invasive method that can be envisaged as a useful tool to measure the surface thickness variations by analyzing the temperature response. In this paper, the thermal quadrupole method for two layered samples heated up with a pulsed excitation is firstly used. By analyzing the thermal responses as a function of thermal properties and thicknesses of both layers, optimal parameters for the excitation source can be identified. Simulations show that a pulsed excitation with duration of ten milliseconds allows to obtain a substrate-independent thermal response. Based on this result, an experimental setup consisting of a near-infrared laser diode and an Infrared camera was next used to evaluate the variation of paint coating thickness between 60 µm and 130 µm on two samples. Results show that the parameters extracted for thermal images are correlated with the estimated thicknesses by the Eddy current methods. The laser pulsed thermography is thus an interesting alternative nondestructive method that can be moreover used for non conductive substrates.

Keywords: non destructive, paint coating, thickness, infrared thermography, laser, heterogeneity

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Authors: Olfa Kaabia, Ilyes Abid, Khaled Guesmi

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This pioneer paper studies whether and how Bitcoin shocks are transmitted to the U.S economy. We employ a new methodology: TVP FAVAR model with stochastic volatility. We use a large dataset of 111 major U.S variables from 1959:m1 to 2016:m12. The results show that Bitcoin shocks significantly impact the U.S. economy. This significant impact is pronounced in a volatile and increasing U.S economy. The Bitcoin has a positive relationship on the U.S real activity, and a negative one on U.S prices and interest rates. Effects on the Monetary Policy exist via the inter-est rates and the Money, Credit and Finance transmission channels.

Keywords: bitcoin, US economy, FAVAR models, stochastic volatility

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Authors: Jussi Horelli, Salla Niittymäki

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In this acceleratingly developing world, it will be crucial for our students to not only to adapt to continuous change, but to be the driving force of it. This raises the question of how can the educational processes motivate and encourage the students to learn the perhaps most important skill there for their further work career: the ability to learn and absorb more by themselves. In engineering education, the learning contents and methods have traditionally been very substance oriented and teacher-centered. In Häme University of Applied Sciences (HAMK), the pedagogical model has been completely renewed during the past few years. Terms like phenomenon or skills-based learning and collaborative teaching are things which have not very often been related to engineering education, but are now the foundation of HAMK’s pedagogical model in all disciplines, even in engineering studies. In this paper, a new flexible way of executing engineering studies will be introduced. The paper will summarize three years’ experiences and observations of a process where traditional teacher-centric mechanical engineering teaching was converted into a model where teachers work collaboratively in teams supporting the students’ learning processes.

Keywords: team teaching, collaborative learning, engineering education, new pedagogy

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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The aim of this study was to improve the effects of human body 3D reconstruction. The MvP algorithm was adopted to obtain key point information from multiple perspectives. This algorithm allowed the capture of human posture and joint positions from multiple angles, providing more comprehensive and accurate data. The study also incorporated the SMPL-X model, which has been widely used for human body modeling, to achieve more accurate 3D reconstruction results. The use of the MvP algorithm made it possible to observe the reconstructed object from multiple angles, thus reducing the problems of blind spots and missing information. This algorithm was able to effectively capture key point information, including the position and rotation angle of limbs, providing key data for subsequent 3D reconstruction. Compared with traditional single-view methods, the method of multi-view fusion significantly improved the accuracy and stability of reconstruction. By combining the MvP algorithm with the SMPL-X model, we successfully achieved better human body 3D reconstruction effects. The SMPL-X model is highly scalable and can generate highly realistic 3D human body models, thus providing more detail and shape information.

Keywords: 3D human reconstruction, multi-view, joint point, SMPL-X

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Authors: Elyes Zarrouk, Yassine Benayed, Faiez Gargouri

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This paper presents a new hybrid model for isolated Arabic words recognition. To do this, we apply Support Vectors Machine (SVM) as an estimator of posterior probabilities within the Dynamic Bayesian networks (DBN). This paper deals a comparative study between DBN and SVM/DBN systems for multi-dialect isolated Arabic words. Performance using SVM/DBN is found to exceed that of DBNs trained on an identical task, giving higher recognition accuracy for four different Arabic dialects. In fact, the average of recognition rates for the four dialects with SVM/DBN was 87.67% while 83.01% with DBN.

Keywords: dynamic Bayesian networks, hybrid models, supports vectors machine, Arabic isolated words

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Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

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An estimating equation technique is an alternative method of the widely used maximum likelihood methods, which enables us to ease some complexity due to the complex characteristics of time-varying covariates. In the situations, when both the time-varying covariates and left-truncation are considered in the model, the maximum likelihood estimation procedures become much more burdensome and complex. To ease the complexity, in this study, the modified estimating equations those have been given high attention and considerations in many researchers under semiparametric transformation model was proposed. The purpose of this article was to develop the modified estimating equation under flexible and general class of semiparametric transformation models for left-truncated and right censored survival data with time-varying covariates. Besides the commonly applied Cox proportional hazards model, such kind of problems can be also analyzed with a general class of semiparametric transformation models to estimate the effect of treatment given possibly time-varying covariates on the survival time. The consistency and asymptotic properties of the estimators were intuitively derived via the expectation-maximization (EM) algorithm. The characteristics of the estimators in the finite sample performance for the proposed model were illustrated via simulation studies and Stanford heart transplant real data examples. To sum up the study, the bias for covariates has been adjusted by estimating density function for the truncation time variable. Then the effect of possibly time-varying covariates was evaluated in some special semiparametric transformation models.

Keywords: EM algorithm, estimating equation, semiparametric transformation models, time-to-event outcomes, time varying covariate

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Authors: Wilhelmina van den Berg

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Through intentionally developing the Register Continuum and the Functional Model of Language in the secondary history classroom, teachers can effectively build a teaching and learning cycle geared towards literacy improvement and EAL differentiation. Developing an understanding of and engaging students in the field, tenor, and tone of written and spoken language, allows students to build the foundation for greater academic achievement due to integrated literacy skills in the history classroom. Building a variety of scaffolds during lessons within these models means students can improve their academic language and communication skills.

Keywords: academic language, EAL, functional model of language, international baccalaureate, literacy skills

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Authors: Jiajun Wang, Xiaoge Li

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The purpose of the aspect-level sentiment analysis task is to identify the sentiment polarity of aspects in a sentence. Currently, most methods mainly focus on using neural networks and attention mechanisms to model the relationship between aspects and context, but they ignore the dependence of words in different ranges in the sentence, resulting in deviation when assigning relationship weight to other words other than aspect words. To solve these problems, we propose a new aspect-level sentiment analysis model that combines a multi-channel convolutional network and graph convolutional network (GCN). Firstly, the context and the degree of association between words are characterized by Long Short-Term Memory (LSTM) and self-attention mechanism. Besides, a multi-channel convolutional network is used to extract the features of words in different ranges. Finally, a convolutional graph network is used to associate the node information of the dependency tree structure. We conduct experiments on four benchmark datasets. The experimental results are compared with those of other models, which shows that our model is better and more effective.

Keywords: aspect-level sentiment analysis, attention, multi-channel convolution network, graph convolution network, dependency tree

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Authors: Bishakha Majumdar, Ranjeet Nambudiri

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Considerable dichotomy exists in research regarding the role of optimism and self-efficacy in work and career outcomes. Optimism and self-efficacy are related to performance, commitment and engagement, but also are implicated in seeing opportunities outside the firm and switching jobs. There is absence of research capturing these opposing strands of findings in the same model and providing a holistic understanding of how the expectancy beliefs operate in case of the working professional. We attempt to bridge this gap by proposing that career-decision self-efficacy and career outcome expectations affect intention to quit through the competitive mediation pathways of internal and external marketability. This model provides a holistic picture of the role of career expectancy beliefs on career outcomes, by considering perceived career opportunities both inside and outside one’s present organization. The understanding extends the application of career expectancy beliefs in the context of career decision-making by the employed individual. Further, it is valuable for reconsidering the effectiveness of hiring and retention techniques used by a firm, as selection, rewards and training programs need to be supplemented by interventions that specifically strengthen the stability pathway.

Keywords: career decision self-efficacy, career outcome expectations, marketability, intention to quit, job mobility

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Authors: Sulastriningsih Djumingin

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This study has some objectives. It aims at describing the ability of the second-grade students to write review text without applying the Lesson Study model at SMPN 18 Makassar. Second, it seeks to describe the ability of the second-grade students to write review text by applying the Lesson Study model at SMPN 18 Makassar. Third, it aims at testing the effectiveness of the Lesson Study model in writing review text at SMPN 18 Makassar. This research was true experimental design with posttest Only group design involving two groups consisting of one class of the control group and one class of the experimental group. The research populations were all the second-grade students at SMPN 18 Makassar amounted to 250 students consisting of 8 classes. The sampling technique was purposive sampling technique. The control class was VIII2 consisting of 30 students, while the experimental class was VIII8 consisting of 30 students. The research instruments were in the form of observation and tests. The collected data were analyzed using descriptive statistical techniques and inferential statistical techniques with t-test types processed using SPSS 21 for windows. The results shows that: (1) of 30 students in control class, there are only 14 (47%) students who get the score more than 7.5, categorized as inadequate; (2) in the experimental class, there are 26 (87%) students who obtain the score of 7.5, categorized as adequate; (3) the Lesson Study models is effective to be applied in writing review text. Based on the comparison of the ability of the control class and experimental class, it indicates that the value of t-count is greater than the value of t-table (2.411> 1.667). It means that the alternative hypothesis (H1) proposed by the researcher is accepted.

Keywords: application, lesson study, review text, writing

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Authors: Andrea Ghermandi

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Constructed wetlands have long been recognized as sources of ancillary benefits such as support for recreational activities. To date, there is a lack of quantitative understanding of the extent and welfare impact of such benefits. Here, it is shown how geotagged, passively crowdsourced data from online social networks (e.g., Flickr and Panoramio) and Geographic Information Systems (GIS) techniques can: (1) be used to infer annual recreational visits to 273 engineered wetlands worldwide; and (2) be integrated with non-market economic valuation techniques (e.g., travel cost method) to infer the monetary value of recreation in these systems. Counts of social media photo-user-days are highly correlated with the number of observed visits in 62 engineered wetlands worldwide (Pearson’s r = 0.811; p-value < 0.001). The estimated, mean willingness to pay for access to 115 wetlands ranges between $5.3 and $374. In 50% of the investigated wetlands providing polishing treatment to advanced municipal wastewater, the present value of such benefits exceeds that of the capital, operation and maintenance costs (lifetime = 45 years; discount rate = 6%), indicating that such systems are sources of net societal benefits even before factoring in benefits derived from water quality improvement and storage. Based on the above results, it is argued that recreational benefits should be taken into account in the design and management of constructed wetlands, as well as when such green infrastructure systems are compared with conventional wastewater treatment solutions.

Keywords: constructed wetlands, cultural ecosystem services, ecological engineering, social media

Procedia PDF Downloads 118

Authors: Ciolomic Ioana Andreea, Farcas Teodora, Tiron-Tudor Adriana

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Investments in research and innovation are widely acknowledged as being crucial drivers for economic growth, for job-creation and to secure social and economic welfare. The aim of this article is to disseminate the results of a Leonardo da Vinci Innovation Transfer project, AdapTykes Adaptation of trainings based up on the Finnish Workplace Development Programme. This project aims to analyses the adaptability of the Finnish model to the economic and political environment of the two emergent countries Romania and Hungary, in order to develop workplace innovation. The focus of this paper is to present the adaptability of the Finnish model to the Romanian context.

Keywords: innovation, human resources, education, tools

Procedia PDF Downloads 511

Authors: Antonello Troncone, Luigi Pugliese, Andrea Parise, Enrico Conte

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The present study deals with the landslides periodically reactivated by groundwater level fluctuations owing to rainfall. The main type of movement which generally characterizes these landslides consists in sliding with quite small-displacement rates. Another peculiar characteristic of these landslides is that soil deformations are essentially concentrated within a thin shear band located below the body of the landslide, which, consequently, undergoes an approximately rigid sliding. In this context, a simple method is proposed in the present study to forecast the movements of this type of landslides owing to rainfall. To this purpose, the landslide body is schematized by means of a two-block model. Some analytical solutions are derived to relate rainfall measurements with groundwater level oscillations and these latter, in turn, to landslide mobility. The proposed method is attractive for engineering applications since it requires few parameters as input data, many of which can be obtained from conventional geotechnical tests. To demonstrate the predictive capability of the proposed method, the application to a well-documented landslide periodically reactivated by rainfall is shown.

Keywords: rainfall, water level fluctuations, landslide mobility, two-block model

Procedia PDF Downloads 111

Authors: G. Nyongombe, Guy L. Kabongo, B. M. Mothudi, M. S. Dhlamini

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A series of Transition Metals Oxides (TMOs) doped graphene were synthesized and successfully used as supercapacitor electrode materials. The as-synthesized materials exhibited exceptional electrochemical properties owing to the combined properties of its constituents; high surface area and good conductivity were achieved. Several analytical characterization techniques were employed to investigate the morphology, crystal structure atomic arrangement and elemental chemical state in the materials for which scanning electron microscopy (SEM), X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) were conducted, respectively. Moreover, the electrochemical properties of the as-synthesized materials were examined by performing cyclic voltammetry (CV), galvanostatic charge-discharge (GCD) and electrochemical impedance spectroscopy (EIS) measurements. Furthermore, the effect of doping concentration on the interlayer distance of the graphene materials and the charge transfer resistance are investigated and correlated to the exceptional current density which was multiplied by a factor of ~80 after TMOs doping in graphene. Finally, the resulting high capacitance obtained confirms the contribution of grapheme exceptional electronic conductivity and large surface area on the electrode materials. Such good-performing electrode materials are highly promising for supercapacitors and other energy storage devices.

Keywords: energy density, graphene, supercapacitors, TMOs

Procedia PDF Downloads 243

Authors: K. G. Sorokozherdyev, E. A. Efimov

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The socio-economic development of regions and countries is an important research issue. Today, in the face of many negative events in the global and regional economies, it is especially important to identify those areas that can serve as sources of economic growth and the basis for the well-being of the population. This study aims to identify the most important sectors of the economy of the Arkhangelsk region that can contribute to the socio-economic development of the region as a whole. For research, the Arkhangelsk region was taken as one of the typical Russian regions that do not have significant reserves of hydrocarbons nor there are located any large industrial complexes. In this regard, the question of possible origins of economic growth seems especially relevant. The basis of this study constitutes the distributed lag regression model (ADL model) developed by the authors, which is based on quarterly data on the socio-economic development of the Arkhangelsk region for the period 2004-2016. As a result, we obtained three equations reflecting the dynamics of three indicators of the socio-economic development of the region -the average wage, the regional GRP, and the birth rate. The influencing factors are the shares in GRP of such sectors as agriculture, mining, manufacturing, construction, wholesale and retail trade, hotels and restaurants, as well as the financial sector. The study showed that the greatest influence on the socio-economic development of the region is exerted by such industries as wholesale and retail trade, construction, and industrial sectors. The study can be the basis for forecasting and modeling the socio-economic development of the Arkhangelsk region in the short and medium term. It also can be helpful while analyzing the effectiveness of measures aimed at stimulating those or other industries of the region. The model can be used in developing a regional development strategy.

Keywords: regional economic development, regional sectoral structure, ADL model, Arkhangelsk region

Procedia PDF Downloads 90

Authors: Diqin Qi, Jiaming Li, Siman Li

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Based on the use of the three-point smoothing method for selectively processing original data columns, this paper establishes a group of grey GM(1,1) models to predict the concentration ranges of four major air pollutants in Shanghai from 2023 to 2024. The results indicate that PM₁₀, SO₂, and NO₂ maintain the national Grade I standards, while the concentration of PM₂.₅ has decreased but still remains within the national Grade II standards. Combining the forecast results, recommendations are provided for the Shanghai municipal government's efforts in air pollution prevention and control.

Keywords: atmospheric pollutant prediction, Grey GM(1, 1), model group, three-point smoothing method

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Authors: Francesco Angelucci, Katerina Veverova, Alžbeta Katonová, Lydia Piendel, Martin Vyhnalek, Jakub Hort

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Alzheimer's disease (AD) is a central nervous system (CNS) disease characterized by loss of memory, cognitive functions and neurodegeneration. Plasmin is an enzyme degrading many plasma proteins. In the CNS, plasmin may reduce the accumulation of A, and have other actions relevant to AD pathophysiology. Brain plasmin synthesis is regulated by two enzymes: one activating, the tissue plasminogen activator (tPA), and the other inhibiting, the plasminogen activator inhibitor-1 (PAI-1). We investigated whether tPA and PAI-1 serum levels in AD and amnestic mild cognitive impairment (aMCI) patients are altered compared to cognitively healthy controls. Moreover, we examined the PAI-1/tPA ratio in these patient groups. 40 AD, 40 aMCI and 10 healthy controls were recruited. Venous blood was collected and PAI-1 and tPA serum concentrations were quantified by sandwich ELISAs. The results showed that PAI-1 levels increased in AD and aMCI patients. This increase negatively correlated with cognitive deficit measured by MMSE. Similarly, the ratio between tPA and PAI-1 gradually increases in aMCI and AD patients. This study demonstrates that AD and aMCI patients have altered PAI-1 serum levels and PAI-1/tPA ratio. Since these enzymes are CNS regulators of plasmin, PAI-1 serum levels could be a marker reflecting a cognitive decline in AD.

Keywords: Alzheimer disease, amnestic mild cognitive impairment, plasmin, tissue-type plasminogen activator

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Authors: Ivo Zution Goncalves, Christopher M. U. Neale, Hiran Medeiros, Everardo Mantovani, Natalia Souza

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Multispectral and thermal infrared imagery from satellite sensors coupled with climate and soil datasets were used to estimate evapotranspiration and biomass in center pivots planted to maize in Brazil during the 2016 season. The hybrid remote sensing based model named Spatial EvapoTranspiration Modelling Interface (SETMI) was applied using multispectral and thermal infrared imagery from the Landsat Thematic Mapper instrument. Field data collected by the IRRIGER center pivot management company included daily weather information such as maximum and minimum temperature, precipitation, relative humidity for estimating reference evapotranspiration. In addition, soil water content data were obtained every 0.20 m in the soil profile down to 0.60 m depth throughout the season. Early season soil samples were used to obtain water-holding capacity, wilting point, saturated hydraulic conductivity, initial volumetric soil water content, layer thickness, and saturated volumetric water content. Crop canopy development parameters and irrigation application depths were also inputs of the model. The modeling approach is based on the reflectance-based crop coefficient approach contained within the SETMI hybrid ET model using relationships developed in Nebraska. The model was applied to several fields located in Minas Gerais State in Brazil with approximate latitude: -16.630434 and longitude: -47.192876. The model provides estimates of real crop evapotranspiration (ET), crop irrigation requirements and all soil water balance outputs, including biomass estimation using multi-temporal satellite image inputs. An interpolation scheme based on the growing degree-day concept was used to model the periods between satellite inputs, filling the gaps between image dates and obtaining daily data. Actual and accumulated ET, accumulated cold temperature and water stress and crop water requirements estimated by the model were compared with data measured at the experimental fields. Results indicate that the SETMI modeling approach using data assimilation, showed reliable daily ET and crop water requirements for maize, interpolated between remote sensing observations, confirming the applicability of the SETMI model using new relationships developed in Nebraska for estimating mainly ET and water requirements in Brazil under tropical conditions.

Keywords: basal crop coefficient, irrigation, remote sensing, SETMI

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Authors: Hamid Goharnejad, Milad Sadeghpoor Moalem, Mahmood Zakeri Niri, Leili Sadeghi Khalegh Abadi

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While there are many benefits to using reservoir dams, their break leads to destructive effects. From the viewpoint of International Committee of Large Dams (ICOLD), dam break means the collapse of whole or some parts of a dam; thereby the dam will be unable to hold water. Therefore, studying dam break phenomenon and prediction of its behavior and effects reduces losses and damages of the mentioned phenomenon. One of the most common types of reservoir dams is embankment dam. Overtopping in embankment dams occurs because of flood discharge system inability in release inflows to reservoir. One of the most important issues among managers and engineers to evaluate the performance of the reservoir dam rim when sliding into the storage, creating waves is large and long. In this study, the effects of floods which caused the overtopping of the dam have been investigated. It was assumed that spillway is unable to release the inflow. To determine outflow hydrograph resulting from dam break, numerical model using Flow-3D software and empirical equations was used. Results of numerical models and their comparison with empirical equations show that numerical model and empirical equations can be used to study the flood resulting from dam break.

Keywords: embankment dam break, empirical equations, Taleghan dam, Flow-3D numerical model

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Authors: Norfadilah Kamaruddin

Abstract:

This paper introduces a new proposed framework for the development process of interface design for Malaysian interactive courseware by exploring four established model in the recent research literature, existing Malaysian government guidelines and Malaysian developers practices. In particular, the study looks at the stages and practices throughout the development process. Significant effects of each of the stages are explored and documented, and significant interrelationships among them suggested. The results of analysis are proposed as potential model that helps in establishing and designing a new version of Malaysian interactive courseware.

Keywords: development processes, interaction with interface, interface design, social sciences

Procedia PDF Downloads 371

Authors: Atinkut Atinafu Yilma, Eyob Messele Sefene

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Anomaly detection is one of the essential mechanisms to control and reduce production loss, especially in today's smart manufacturing. Quick anomaly detection aids in reducing the cost of production by minimizing the possibility of producing defective products. However, developing an anomaly detection model that can rapidly detect a production change is challenging. This paper proposes Gated Recurrent Unit (GRU) combined with Random Forest (RF) to detect anomalies in the production process in real-time quickly. The GRU is used as a feature detector, and RF as a classifier using the input features from GRU. The model was tested using various synthesis and real-world datasets against benchmark methods. The results show that the proposed GRU-RF outperforms the benchmark methods with the shortest time taken to detect anomalies in the production process. Based on the investigation from the study, this proposed model can eliminate or reduce unnecessary production costs and bring a competitive advantage to manufacturing industries.

Keywords: anomaly detection, multivariate time series data, smart manufacturing, gated recurrent unit network, random forest

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Authors: Vichada Chokesikarin

Abstract:

The study aims to determine which factors account for customer satisfaction and to investigate the relationship between entrepreneurial orientation and business success, in particular, context of the information understanding of hostel business in Pranakorn district, Bangkok and the significant element of entrepreneurship in tourism industry. This study covers 352 hostels customers and 61 hostel owners/managers nearby Khao San Road. Data collection methods were used by survey questionnaire and a series of hypotheses were developed from services marketing literature. The findings suggest the customer satisfaction most influenced by image, service quality, room quality and price accordingly. Furthermore the findings revealed that significant relationships exist between entrepreneurial orientation and business success; while competitive aggressiveness was found unrelated. The ECSI model’s generic measuring customer satisfaction was found partially mediate the business success. A reconsideration of other variables applicable should be supported with the model of hostel business. The study provides context and overall view of hostel business while discussing from the entrepreneurial orientation to customer satisfaction, thereby reducing decision risk on hostel investment.

Keywords: customer satisfaction, ECSI model, entrepreneurial orientation, small hotel, hostel, business performance

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Authors: Krisztina Szegedi, Gyula Fülöp, Ádám Bereczk

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The shared goal of social entrepreneurship, corporate social responsibility and social innovation is the advancement of society. The business model of social enterprises is characterized by unique strategies based on the competencies of the entrepreneurs, and is not aimed primarily at the maximization of profits, but rather at carrying out goals for the benefit of society. Corporate social responsibility refers to the active behavior of a company, by which it can create new solutions to meet the needs of society, either on its own or in cooperation with other social stakeholders. The objectives of this article are to define concepts, describe and integrate relevant theoretical models, develop a model and introduce some examples of international practice that can inspire initiatives for social development.

Keywords: corporate social responsibility, CSR, social innovation, social entrepreneurship

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Authors: Pierluigi Gallo, Francesco Randazzo, Ignazio Gallo

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In recent years, many new and interesting models of successful online business have been developed. Many of these are based on the competition between users, such as online auctions, where the product price is not fixed and tends to rise. Other models, including group-buying, are based on cooperation between users, characterized by a dynamic price of the product that tends to go down. There is not yet a business model in which both sellers and buyers are grouped in order to negotiate on a specific product or service. The present study investigates a new extension of the group-buying model, called fair, which allows aggregation of demand and supply for price optimization, in a cooperative manner. Additionally, our system also aggregates products and destinations for shipping optimization. We introduced the following new relevant input parameters in order to implement a double-side aggregation: (a) price-quantity curves provided by the seller; (b) waiting time, that is, the longer buyers wait, the greater discount they get; (c) payment time, which determines if the buyer pays before, during or after receiving the product; (d) the distance between the place where products are available and the place of shipment, provided in advance by the buyer or dynamically suggested by the system. To analyze the proposed model we implemented a system prototype and a simulator that allows studying effects of changing some input parameters. We analyzed the dynamic price model in fairs having one single seller and a combination of selected sellers. The results are very encouraging and motivate further investigation on this topic.

Keywords: auction, aggregation, fair, group buying, social buying

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Authors: Siti Indati Mustapa, Hussain Ali Bekhet

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Transportation sector represents more than 40% of total energy consumption in Malaysia. This sector is a major user of fossils based fuels, and it is increasingly being highlighted as the sector which contributes least to CO2 emission reduction targets. Considering this fact, this paper attempts to investigate the problem of reducing CO2 emission using linear programming approach. An optimization model which is used to investigate the optimal level of CO2 emission reduction in the road transport sector is presented. In this paper, scenarios have been used to demonstrate the emission reduction model: (1) utilising alternative fuel scenario, (2) improving fuel efficiency scenario, (3) removing fuel subsidy scenario, (4) reducing demand travel, (5) optimal scenario. This study finds that fuel balancing can contribute to the reduction of the amount of CO2 emission by up to 3%. Beyond 3% emission reductions, more stringent measures that include fuel switching, fuel efficiency improvement, demand travel reduction and combination of mitigation measures have to be employed. The model revealed that the CO2 emission reduction in the road transportation can be reduced by 38.3% in the optimal scenario.

Keywords: CO2 emission, fuel consumption, optimization, linear programming, transportation sector, Malaysia

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Authors: Khadijah B. Alziyadi, Khawlh A. Alzubaidi, Amor M. Alsayari

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Recently, GaMnAs diluted magnetic semiconductors(DMSs) have received considerable attention because they combine semiconductor and magnetic properties. GaMnAs has been used as a model DMS and as a test bed for many concepts and functionalities of spintronic devices. In this paper, a theoretical study on the band structure ofGaMnAswill be presented. The model that we used in this study is the 8-band k.p methodwherespin-orbit interaction, spin splitting, and strain are considered. The band structure of GaMnAs will be calculated in different directions in the reciprocal space. The effect of manganese content on the GaMnAs band structure will be discussed. Also, the influence of strain, which varied continuously from tensile to compressive, on the different bands will be studied.

Keywords: band structure, diluted magnetic semiconductor, k.p method, strain

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Authors: Seyed Abbas Tabatabaei, Marjan Naderan Tahan, Arman Kadkhodai

Abstract:

An efficient optimization approach, called feasible gate (FG), is developed to enhance the computation efficiency and solution quality of the previously developed highway alignment optimization (HAO) model. This approach seeks to realistically represent various user preferences and environmentally sensitive areas and consider them along with geometric design constraints in the optimization process. This is done by avoiding the generation of infeasible solutions that violate various constraints and thus focusing the search on the feasible solutions. The proposed method is simple, but improves significantly the model’s computation time and solution quality. On the other, highway alignment optimization through Feasible Gates, eventuates only economic model by considering minimum design constrains includes minimum reduce of circular curves, minimum length of vertical curves and road maximum gradient. This modelling can reduce passenger comfort and road safety. In most of highway optimization models, by adding penalty function for each constraint, final result handles to satisfy minimum constraint. In this paper, we want to propose a safety-function solution by introducing gift function.

Keywords: safety, highway geometry, optimization, alignment

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Authors: Bekim Berisha, Sebastian Hirsiger, Pavel Hora

Abstract:

Advanced material models involving several sets of model parameters require a big experimental effort. As models are getting more and more complex like e.g. the so called “Homogeneous Anisotropic Hardening - HAH” model for description of the yielding behavior in the 2D/3D stress space, the number and complexity of the required experiments are also increasing continuously. In the context of sheet metal forming, these requirements are even more pronounced, because of the anisotropic behavior or sheet materials. In addition, some of the experiments are very difficult to perform e.g. the plane stress biaxial compression test. Accordingly, tensile tests in at least three directions, biaxial tests and tension-compression or shear-reverse shear experiments are performed to determine the parameters of the macroscopic models. Therefore, determination of the macroscopic model parameters based on virtual experiments is a very promising strategy to overcome these difficulties. For this purpose, in the framework of multiscale material modeling, a dislocation density based crystal plasticity model in combination with a FFT-based spectral solver is applied to perform virtual experiments. Modeling of the plastic behavior of metals based on crystal plasticity theory is a well-established methodology. However, in general, the computation time is very high and therefore, the computations are restricted to simplified microstructures as well as simple polycrystal models. In this study, a dislocation density based crystal plasticity model – including an implementation of the backstress – is used in a spectral solver framework to generate virtual experiments for three deep drawing materials, DC05-steel, AA6111-T4 and AA4045 aluminum alloys. For this purpose, uniaxial as well as multiaxial loading cases, including various pre-strain histories, has been computed and validated with real experiments. These investigations showed that crystal plasticity modeling in the framework of Representative Volume Elements (RVEs) can be used to replace most of the expensive real experiments. Further, model parameters of advanced macroscopic models like the HAH model can be determined from virtual experiments, even for multiaxial deformation histories. It was also found that crystal plasticity modeling can be used to model anisotropic hardening more accurately by considering the backstress, similar to well-established macroscopic kinematic hardening models. It can be concluded that an efficient coupling of crystal plasticity models and the spectral solver leads to a significant reduction of the amount of real experiments needed to calibrate macroscopic models. This advantage leads also to a significant reduction of computational effort needed for the optimization of metal forming process. Further, due to the time efficient spectral solver used in the computation of the RVE models, detailed modeling of the microstructure are possible.

Keywords: anisotropic hardening, crystal plasticity, micro structure, spectral solver

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