• Asia-Pacific Journal of Business
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• v.6 no.1
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• pp.17-25
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• 2015

In this study, we identified the various mechanisms through which entrepreneurial orientation impacts firm performance. We proposed that entrepreneurial orientation assists organizations in building cultural, structural, human and technical knowledge capabilities, which in turn lead to sustainable competitive advantage. We tested our proposed hypothesis using data collected from 76 managers of small entrepreneurial firms. We found that cultural knowledge capabilities are the strongest mediators of entrepreneurial orientation and firm performance relationship. By bringing in knowledge capabilities in the literature of entrepreneurial orientation, we open new directions for research. Our findings have implications for theory as well as practice.

• Advanced Industrial SCIence
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• v.2 no.2
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• pp.1-8
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• 2023

The goal of the study is to describe blockchain technology as it relates to enhancing supply chains in the retail sector in order to achieve sustainability. This study offers a critical analysis of the possible applications of blockchain technology and smart contracts to supply chain management. This paper explains how Blockchain technology may be used by customers and merchants in a variety of retail business operations to great advantage. By adopting a modified version of the UTUAT model, this study validates the possibility of using blockchain for supply chain management in the retail industry. The study found a significant and positive correlation between behavioral intention and acceptance toward employing block networks in supply chain management in the retail business. The behavior intention (BI) to adopt blockchain technology is significantly influenced by performance expectations, effect expectations, subjective standards, and enabling variables. The performance and effort expectations have a considerable impact on the BI to adopt blockchain in supply chain management.

• Honam Mathematical Journal
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• v.39 no.1
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• pp.1-25
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• 2017

In this paper, we introduce a new scheme namely: CUIA-iterative scheme and utilize the same to prove a strong convergence theorem for quasi contractive mappings in Banach spaces. We also establish the equivalence of our new iterative scheme with various iterative schemes namely: Picard, Mann, Ishikawa, Agarwal et al., Noor, SP, CR etc for quasi contractive mappings besides carrying out a comparative study of rate of convergences of involve iterative schemes. The present new iterative scheme converges faster than above mentioned iterative schemes whose detailed comparison carried out with the help of different tables and graphs prepared with the help of MATLAB.

• Advances in Computational Design
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• v.7 no.3
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• pp.253-279
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• 2022

This study investigated and predicted the Marshall stability of glass-fiber asphalt mix, carbon-fiber asphalt mix and glass-carbon-fiber asphalt (hybrid) mix by using machine learning techniques such as Artificial Neural Network (ANN), Support Vector Machine (SVM) and Random Forest(RF), The data was obtained from the experiments and the research articles. Assessment of results indicated that performance of the Artificial Neural Network (ANN) based model outperformed applied models in training and testing datasets with values of indices as; coefficient of correlation (CC) 0.8492 and 0.8234, mean absolute error (MAE) 2.0999 and 2.5408, root mean squared error (RMSE) 2.8541 and 3.3165, relative absolute error (RAE) 48.16% and 54.05%, relative squared error (RRSE) 53.14% and 57.39%, Willmott's index (WI) 0.7490 and 0.7011, Scattering index (SI) 0.4134 and 0.3702 and BIAS 0.3020 and 0.4300 for both training and testing stages respectively. The Taylor diagram also confirms that the ANN-based model outperforms the other models. Results of sensitivity analysis show that Carbon fiber has a major influence in predicting the Marshall stability. However, the carbon fiber (CF) followed by glass-carbon fiber (50GF:50CF) and the optimal combination CF + (50GF:50CF) are found to be most sensitive in predicting the Marshall stability of fibrous asphalt concrete.

• Advances in materials Research
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• v.11 no.1
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• pp.75-90
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• 2022

In this paper, functionality of soft computing algorithms such as Group method of data handling (GMDH), Random forest (RF), Random tree (RT), Linear regression (LR), M5P, and artificial neural network (ANN) have been looked out to predict the compressive strength of concrete mixed with marble powder. Assessment of result suggests that, the overall performance of ANN based model gives preferable results over the different applied algorithms for the estimate of compressive strength of concrete. The results of coefficient of correlation were maximum in ANN model (0.9139) accompanied through RT with coefficient of correlation (CC) value 0.8241 and minimum root mean square error (RMSE) value of ANN (4.5611) followed by RT with RMSE (5.4246). Similarly, other evaluating parameters like, Willmott's index and Nash-sutcliffe coefficient value of ANN was 0.9458 and 0.7502 followed by RT model (0.8763 and 0.6628). The end result showed that, for both subsets i.e., training and testing subset, ANN has the potential to estimate the compressive strength of concrete. Also, the results of sensitivity suggest that the water-cement ratio has a massive impact in estimating the compressive strength of concrete with marble powder with ANN based model in evaluation with the different parameters for this data set.

• Journal of Crop Science and Biotechnology
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• v.10 no.3
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• pp.167-174
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• 2007

Spongy Alphonso mangoes were found to be infected with Staphylococcus bacteria. A Gram positive Staphylococcus strain was isolated from spongy pulp and identified from CABI Bioscience, UK, by partial 16S rDNA sequence analysis and by morphological and biochemical characterization through IMTECH, Chandigarh, India. Although identification by both of these methods indicated the organism belonged to same genus, different species names were given. Changes in total phenolics, reducing, and non-reducing sugars, respiration rate, total carotenoids, peroxidase(POX), and catalase activities were monitored during ripening of these fruits. The climacteric rise in spongy fruits was marked by an increase in respiration rate and a decrease in sugar content. Total phenolics content increased in spongy fruits as compared to ripe non-spongy fruits. Development of corky white tissue in spongy fruits was associated with about a 2.5-fold reduction in total carotenoids and a concomitant increase in lipoxygenase-mediated, $\beta$-carotene co-oxidation. A marked decrease in soluble protein content and about a 1.5-fold increase in POX activity was observed. Maximum POX activity was confined to 50-70%$(NH_4)_2SO_4$ fraction. The intense dark bands visible after POX specific substrate staining of the Native gel indicated a high expression of isoenzymes of POX in spongy fruits. Similarly, changes in levels of catalase activity were also observed in spongy fruits. The results suggest that infection of Alphonso mangoes with Staphylococcus bacteria affects the normal ripening processes of the fruit interfering with the carbohydrate and carotenoid metabolism. Also, the studies indicate the expression of POX and catalase enzymes as a plant defense response to microbial invasion.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5229-5252
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• 2016

With proliferation of diverse network access technologies, users demands are also increasing and service providers are offering a Quality of Service (QoS) to satisfy their customers. In roaming, a mobile node (MN) traverses number of available networks in the heterogeneous wireless networks environment and a single operator is not capable to fulfill the demands of user. It is crucial task for MN for selecting a best network from the list of networks at any time anywhere. A MN undergoes a network selection situation frequently when it is becoming away from the home network. Multiple Attribute Group Decision (MAGD) method will be one of the best ways for selecting target network in heterogeneous wireless networks (4G). MAGD network selection process is predominantly dependent on two steps, i.e., attribute weight, decision maker's (DM's) weight and aggregation of opinion of DMs. This paper proposes Multi-Attribute Intuitionistic Fuzzy Group Decision Method (MAIFGDM) using TOPSIS for the selection of the suitable candidate network. It is scalable and is able to handle any number of networks with large set of attributes. This is a method of lower complexity and is useful for real time applications. It gives more accurate result because it uses Intuitionistic Fuzzy Sets (IFS) with an additional parameter intuitionistic fuzzy index or hesitant degree. MAIFGDM is simulated in MATLAB for its evaluation. A comparative study of MAIFDGM is also made with TOPSIS and Fuzzy-TOPSIS in respect to decision delay. It is observed that MAIFDGM have low values of decision time in comparison to TOPSIS and Fuzzy-TOPSIS methods.

• Korean Institute of Interior Design Journal
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• v.15 no.6 s.59
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• pp.213-220
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• 2006

Le Corbusier (1887-1965) is known as a great architect ranking with such master architects as Frank Lloyd Wright and Mies van der Rohe who produced great architectural achievements in an era from the dawning to the maturity of the modem architecture. His works are marked for their peculiarity in expressing his architectural concept as perceived through his artistic sensibility. He has brought the form of his architecture to perfect through the influence of Purism. His architectural concept has instigated him to construct the relations between structure, form and the notion of space through the 'Dom-ino' structural system and the 'Five Principles of the Modem Architecture.' As a result, he has become such an architect as has ripened his works by adopting the 'Modulor' for human measurement. During the decade from 1929 to 1939, he made public the 'Museum of Unlimited Growth' programs in an attempt to give a concrete form to his concept of 'unlimited space' spreading to all directions, which was actually visualized by the constructions of three art museums, located Ahmedabad and Chandigarh in India and Tokyo in Japan. Although a number of researches have so far been publicized on the works and the architectural ideas of Le Corbusier, no systematic research has yet been released on the idea of 'Museum of Unlimited Growth' as a matter of fact. Therefore, this study has set its purpose to grasp the peculiarities of his exhibition space design through an analysis on the characteristics of the 'Museum of Unlimited Growth' so designed as to reflect the concept of a space, which is centrifugally growing. With this purpose in mind, this research is also to suggest how the design of the 'Museum of Unlimited Growth' would influence the modem museum exhibit space. The contents of this study comprise the consideration on the early ideas of Le Corbusier, the typical features of the growing museum and the analysis as well as the integration of his works.

• Advances in environmental research
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• v.9 no.4
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• pp.275-284
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• 2020

We provide the first study on the occurrence of microplastics in Dal lake, Kashmir, India. Microplastics act as catastrophe that trigger many environmental problems. The key origins of microplastics are larger plastics, which split into smaller plastics after UV light disintegration. There is relatively little work carried out on the existence of microplastics. The present work has been undertaken on the occurrence of microplastics at four pre-selected sites (surface water) in Dal lake, Kashmir. The samples were taken to the laboratory to dissolve organic matter by using H2O2 (6%). To speed up the organic digestion; the treated mixture was heated on a hot plate at 70℃. The mixture was then subjected to density separation. The supernatant obtained was observed under the microscope (10X) and measurements were taken. At site-I, the microplastics ranged from 2-3 mm, site-II 5-6 mm, site-III 3-4 mm, site-IV 4-5 mm in thickness, indicating the presence of microplastics in the lake. The presence of microplastics indicated that the lake has undergone an anthropogenic change over a period of time. Our research highlights the value of enhancing the quality of the drainage system and sewage disposal. This work can be helpful to recognize successful microplastic control management techniques and possible threats associated with the Dal lake. So far, no such data on the presence of microplastics in Kashmir lakes is available.

• Composite Materials and Engineering
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• v.3 no.3
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• pp.201-220
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• 2021

In this study, potential of three machine learning techniques i.e., M5P, Support vector machines and Gaussian processes were evaluated to find the best algorithm for the prediction of flexural strength of concrete mix with steel fibre. The study comprises the comparison of results obtained from above-said techniques for given dataset. The dataset consists of 124 observations from past research studies and this dataset is randomly divided into two subsets namely training and testing datasets with (70-30)% proportion by weight. Cement, fine aggregates, coarse aggregates, water, super plasticizer/ high-range water reducer, steel fibre, fibre length and curing days were taken as input parameters whereas flexural strength of the concrete mix was taken as the output parameter. Performance of the techniques was checked by statistic evaluation parameters. Results show that the Gaussian process technique works better than other techniques with its minimum error bandwidth. Statistical analysis shows that the Gaussian process predicts better results with higher coefficient of correlation value (0.9138) and minimum mean absolute error (1.2954) and Root mean square error value (1.9672). Sensitivity analysis proves that steel fibre is the significant parameter among other parameters to predict the flexural strength of concrete mix. According to the shape of the fibre, the mixed type performs better for this data than the hooked shape of the steel fibre, which has a higher CC of 0.9649, which shows that the shape of fibers do effect the flexural strength of the concrete. However, the intricacy of the mixed fibres needs further investigations. For future mixes, the most favorable range for the increase in flexural strength of concrete mix found to be (1-3)%.