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Journal articles on the topic 'Model transfer approach'

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Published: 10 December 2022

Last updated: 28 January 2023

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1

KAYA, TUNCER, and MURAT ARIK. "REDUCED TRANSFER MATRIX APPROACH FOR ISING MODEL." International Journal of Modern Physics B 25, no. 21 (August 20, 2011): 2895–903. http://dx.doi.org/10.1142/s0217979211101235.

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In this work, we present a simple approximate transfer matrix method for 2D and 3D Ising ferromagnet to calculate spontaneous magnetization of the system. The critical coupling strength Kc of 2D and 3D Ising models in reduced transfer matrix approximation is obtained quite accurately by simple improvements over the mean field theory. The important physical effect we include is the some of the fluctuations effects of the systems directly with help of this method. We predict from the spontaneous magnetization curve that the critical coupling strength Kc=J/kBT = 0.401 and 0.245 for two-dimensional (2D) and three-dimensional (3D) systems, respectively.

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Braylan, Alexander, and Risto Miikkulainen. "Object-Model Transfer in the General Video Game Domain." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 12, no. 1 (June 25, 2021): 136–42. http://dx.doi.org/10.1609/aiide.v12i1.12870.

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A transfer learning approach is presented to address the challenge of training video game agents with limited data. The approach decomposes games into objects, learns object models, and transfers models from known games to unfamiliar games to guide learning. Experiments show that the approach improves prediction accuracy over a comparable control, leading to more efficient exploration. Training of game agents is thus accelerated by transferring object models from previously learned games.

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KAYA, TUNCER. "CORRELATED REDUCED TRANSFER MATRIX APPROACH FOR ISING MODEL." International Journal of Modern Physics B 26, no. 14 (May 16, 2012): 1250085. http://dx.doi.org/10.1142/s0217979212500853.

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In this paper we present a simple approximate transfer matrix method for 2D and 3D hyper cubic nearest neighbor Ising models with various coordination number z to calculate the corresponding critical coupling strengths Kc. The critical coupling strengths of the Ising ferromagnets are obtained quite accurately by simple improvements over the self-consistent correlated field (SCCF) approximation. The important physical effect included in this work is some of the fluctuation effects of the systems by the help of a reduced transfer matrix method. When used in combination with the accuracy of the average magnetization obtained from the SCCF approximation, this reduced transfer matrix method leads to estimate of Kc more accurate than those obtained from the Bethe–Peierls–Weiss approximation and also SCCF approximation. Therefore, we believe that the approach we refer to as the correlated reduced transfer matrix method is potentially very useful scheme for obtaining approximate values of the critical coupling strengths of the Ising models with a mathematically easy meaner.

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Hien, Ngo Le Huy, Luu Van Huy, and Nguyen Van Hieu. "Artwork style transfer model using deep learning approach." Cybernetics and Physics, Volume 10, 2021, Number 3 (October 30, 2021): 127–37. http://dx.doi.org/10.35470/2226-4116-2021-10-3-127-137.

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Art in general and fine arts, in particular, play a significant role in human life, entertaining and dispelling stress and motivating their creativeness in specific ways. Many well-known artists have left a rich treasure of paintings for humanity, preserving their exquisite talent and creativity through unique artistic styles. In recent years, a technique called ’style transfer’ allows computers to apply famous artistic styles into the style of a picture or photograph while retaining the shape of the image, creating superior visual experiences. The basic model of that process, named ’Neural Style Transfer,’ has been introduced promisingly by Leon A. Gatys; however, it contains several limitations on output quality and implementation time, making it challenging to apply in practice. Based on that basic model, an image transform network was proposed in this paper to generate higher-quality artwork and higher abilities to perform on a larger image amount. The proposed model significantly shortened the execution time and can be implemented in a real-time application, providing promising results and performance. The outcomes are auspicious and can be used as a referenced model in color grading or semantic image segmentation, and future research focuses on improving its applications.

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Nakawaki, Darrell E., Sangwan Joo, and Fumio Miyazaki. "Skill transfer improved with a multi-model approach." Advanced Robotics 14, no. 5 (January 2000): 371–75. http://dx.doi.org/10.1163/156855300741654.

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Mat Said, Noor Azura, Siti Mariam Bujang, Nor Aishah Buang, Harlina Harlizah Siraj @ Ramli, and Mohd Nasri Awang Besar. "CONCEPTUALIZING CRITICAL THINKING LEARNING TRANSFER MODEL: A QUALITATIVE APPROACH." Malaysian Journal of Learning and Instruction 18, Number 1 (January 31, 2021): 111–30. http://dx.doi.org/10.32890/mjli2021.18.1.5.

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Purpose – Although there is a growing interest in Critical Thinking Learning Transfer (CTLT), previous studies have presented less detailed information regarding the transfer. Besides, a few pieces of literature have been focusing on medical contexts. In Malaysia, there are small number of reviews regarding the concept compared to other countries. This issue raises the question: How do the medical undergraduates in Malaysia transfer their critical thinking learning? Thus, the authors sought to explore CTLT process among medical undergraduates in Malaysia. Then, the authors synthesized the CTLT model which presented the types of CTLT. Methodology – This study adopted a qualitative case study approach. Eight medical undergraduates in Universiti Kebangsaan Malaysia were selected using two sampling strategies under the purposive sampling. Data obtained using in-depth interviews. Data were analysed using thematic analysis. Findings – The findings showed three types of CTLT, namely near transfer, far transfer, and integrated transfer. Each types of the transfer were specified into components. In summary, the medical undergraduates’ conceptions on the CTLT process led to the development of a model. The model presented the types of CTLT that provide a better understanding about the extension of occurrence of CTLT among the medical undergraduates. Significance – The CTLT model presented extra value to the description of the CTLT process. This model led to a better understanding of the extension of critical thinking learning transfer occurrence among students especially in the context of early clinical year medical programme. Besides, the model may influence the future development of critical thinking pedagogies. Keywords: Conceptualization, critical thinking, learning transfer, extension of occurrence, medical undergraduates, qualitative case study.

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Eshratifar, Amir Erfan, Mohammad Saeed Abrishami, David Eigen, and Massoud Pedram. "A Meta-Learning Approach for Custom Model Training." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 9937–38. http://dx.doi.org/10.1609/aaai.v33i01.33019937.

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Transfer-learning and meta-learning are two effective methods to apply knowledge learned from large data sources to new tasks. In few-class, few-shot target task settings (i.e. when there are only a few classes and training examples available in the target task), meta-learning approaches that optimize for future task learning have outperformed the typical transfer approach of initializing model weights from a pretrained starting point. But as we experimentally show, metalearning algorithms that work well in the few-class setting do not generalize well in many-shot and many-class cases. In this paper, we propose a joint training approach that combines both transfer-learning and meta-learning. Benefiting from the advantages of each, our method obtains improved generalization performance on unseen target tasks in both few- and many-class and few- and many-shot scenarios.

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Acharya, Sanjaya, Marcello Signorelli, Borut Vojinovic, and Žan Jan Oplotnik. "Alternative Approach to Economic Restructuring to Benefit the Poor – Sam Multipliers Analysis as Alternative Approach." Annals of the Alexandru Ioan Cuza University - Economics 60, no. 1 (July 1, 2013): 182–201. http://dx.doi.org/10.2478/aicue-2013-0016.

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Abstract Many economic reforms in developing economies are, in fact, price deregulation in the product markets and trade liberalisation, concerning whether the growth of exports accelerates. This paper, however, attempts to offer a new flavour in the policy reforms using fixed price model to study the growth impact of different sectoral investments and transfers to households. We used Social Accounting Matrix (SAM) multipliers to analyse the flow structure and distributional effects of sectoral investments and transfers in a typical developing economy. Using the case of Nepal we simulate the effects of additional demand creations to sectors and transfer earning growth to households and measure their effects and conclude that in the given flow structure, the additional sector demand and transfer growth in the economy benefit the middle income groups more; whereas the benefit to the poorest is only modest. We examine the effects of potential pro-poor economic restructuring measures especially with regard to the improvements of efficiency parameters and redirection of factor endowments. Consequently, poor households transfer towards those activities which have higher multiplier effects of additional demand and transfer earning. Furthermore, redirection of factor endowments requires undergoing with the skill upgrade of poor labour to be conducive with higher economic growth.

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Audit, P. "Transfer matrix approach to the three-dimensional Ising model." Journal of Physics A: Mathematical and General 20, no. 8 (June 1, 1987): 2187–97. http://dx.doi.org/10.1088/0305-4470/20/8/031.

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Bao, W., J. Zhao, J. Chang, and Y. Qi. "Robust dynamic bumpless transfer: an exact model matching approach." IET Control Theory & Applications 6, no. 10 (July 5, 2012): 1341–50. http://dx.doi.org/10.1049/iet-cta.2011.0231.

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Bayman, B. F. "A Glauber-model approach to one-nucleon transfer reactions." Physics Reports 264, no. 1-5 (January 1996): 39–45. http://dx.doi.org/10.1016/0370-1573(95)00025-9.

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Nelson, Donald W., and Udo von Toussaint. "Radiometric Scale Transfer Using Bayesian Model Selection." Proceedings 33, no. 1 (February 3, 2020): 32. http://dx.doi.org/10.3390/proceedings2019033032.

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The key input quantity to climate modelling and weather forecasts is the solar beam irradiance, i.e., the primary amount of energy provided by the sun. Despite its importance the absolute accuracy of the measurements are limited—which not only affects the modelling but also ground truth tests of satellite observations. Here we focus on the problem of improving instrument calibration based on dedicated measurements. A Bayesian approach reveals that the standard approach results in inferior results. An alternative approach method based on monomial based selection of regression functions, combined with model selection is shown to yield superior estimations for a wide range of conditions. The approach is illustrated on selected data and possible further enhancements are outlined.

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Mukhlif, Abdulrahman Abbas, Belal Al-Khateeb, and Mazin Abed Mohammed. "Incorporating a Novel Dual Transfer Learning Approach for Medical Images." Sensors 23, no. 2 (January 4, 2023): 570. http://dx.doi.org/10.3390/s23020570.

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Recently, transfer learning approaches appeared to reduce the need for many classified medical images. However, these approaches still contain some limitations due to the mismatch of the domain between the source domain and the target domain. Therefore, this study aims to propose a novel approach, called Dual Transfer Learning (DTL), based on the convergence of patterns between the source and target domains. The proposed approach is applied to four pre-trained models (VGG16, Xception, ResNet50, MobileNetV2) using two datasets: ISIC2020 skin cancer images and ICIAR2018 breast cancer images, by fine-tuning the last layers on a sufficient number of unclassified images of the same disease and on a small number of classified images of the target task, in addition to using data augmentation techniques to balance classes and to increase the number of samples. According to the obtained results, it has been experimentally proven that the proposed approach has improved the performance of all models, where without data augmentation, the performance of the VGG16 model, Xception model, ResNet50 model, and MobileNetV2 model are improved by 0.28%, 10.96%, 15.73%, and 10.4%, respectively, while, with data augmentation, the VGG16 model, Xception model, ResNet50 model, and MobileNetV2 model are improved by 19.66%, 34.76%, 31.76%, and 33.03%, respectively. The Xception model obtained the highest performance compared to the rest of the models when classifying skin cancer images in the ISIC2020 dataset, as it obtained 96.83%, 96.919%, 96.826%, 96.825%, 99.07%, and 94.58% for accuracy, precision, recall, F1-score, sensitivity, and specificity respectively. To classify the images of the ICIAR 2018 dataset for breast cancer, the Xception model obtained 99%, 99.003%, 98.995%, 99%, 98.55%, and 99.14% for accuracy, precision, recall, F1-score, sensitivity, and specificity, respectively. Through these results, the proposed approach improved the models’ performance when fine-tuning was performed on unclassified images of the same disease.

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Fomina, Olena, Olena Moshkovska, Svitlana Luchyk, Yulia Manachynska, and Olena Androsenko. "Managing the capital force impulse of the agrarian enterprise: transfer approach." Problems and Perspectives in Management 18, no. 3 (October 6, 2020): 373–91. http://dx.doi.org/10.21511/ppm.18(3).2020.31.

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In the current conditions of globalization and European integration trends, domestic agricultural companies use the transfer pricing mechanism when exporting agricultural products, which on one hand allows owners to increase the efficiency of internal management, and on the other to hide real profits and reflect unprofitable production in financial statements. At the same time, traditional double-entry bookkeeping and financial reporting (including those prepared in accordance with IFRS) are unable to show the real power momentum of domestic agricultural enterprises profitability (their return on capital). This narrows the circle of potential investors when making decisions on the feasibility of investing financial resources in the development of Ukrainian agricultural sector. The purpose of the study is to develop a 3D-form of the Actuarial Report on Capital Force Impulse (3D - ARCFI), which informational content will provide an objective assessment of the capital force impulse of an agricultural enterprise and help to attract investment in its development. The object of the study is the process of actuarial accounting and 3D reporting as information subsystems for controlling the capital power momentum at domestic agricultural enterprises. The research methodology is based on the application of 3D-recording method and classical mechanics methods in displaying information from the actuarial accounting system on 3D-force accounts to develop a model of power momentum management of an agricultural entity return on capital as an alternative approach to transfer pricing based on informational filling of 3D-ARCFI with the help of net profit method. The study results showed dependence of domestic agricultural enterprises investment attractiveness on the qualitative informational filling of the actuarial management reporting in 3D format. The practical value of the results received confirmed the effectiveness of the proposed 3D-model of profit power momentum management within the transfer approach based on accounting-informational basis of 3D-ARCFI, which will contribute to an objective perspective assessment of agricultural companies return on equity power momentum and increase their market investment attractiveness. AcknowledgmentThe article has been prepared within the research project “Business Value Management” (state registration No. 0118U000131) implemented in the Kyiv National University of Trade and Economics.

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Zhou, Qianwen, Xiaopeng Deng, Bon-Gang Hwang, and Miao Yu. "System dynamics approach of knowledge transfer from projects to the project-based organization." International Journal of Managing Projects in Business 15, no. 2 (January 12, 2022): 324–49. http://dx.doi.org/10.1108/ijmpb-06-2021-0142.

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PurposeAlthough knowledge transfer in the context of projects and project-based organizations (PBOs) has gained increasing attention from academia and industry, it is not clear how knowledge transfers from projects to their parent PBOs. This research aims to explore the main factors influencing knowledge transfer from projects to their parent PBOs, and analyze how these factors integrate the transfer process as system components using the system dynamics (SD) method.Design/methodology/approachBased on the literature review, investigation and interview, this paper adopts the event analysis to obtain the influencing factors from historical cases and establishes a conceptual model of knowledge transfer from five dimensions, which simultaneously considers the knowledge sender, knowledge receiver and the relationship between the knowledge sender and receiver, knowledge features and transfer context. Then, the relationships between variables in the qualitative model were clarified, and a quantitative model including seven feedback loops was established using the SD model. Lastly, the system simulation and sensitivity analysis of the main parameters were realized in Vensim PLE software.FindingsThe simulation analysis results show that the model can simulate the knowledge transfer process from projects to the PBO to a certain extent. This research fully demonstrates the impact of variables from five dimensions on knowledge transfer and incorporates the knowledge gap and transfer threshold in the research category. Moreover, the rationality of seven feedback loops proposed in the model was verified. And the effects of various factors on the amount of knowledge transferred and the PBO's knowledge stock were examined through sensitivity analysis. Furthermore, recommendations for developing an integrated knowledge transfer mechanism of PBOs and projects to enhance transfer effect are offered.Research limitations/implicationsThis research provides other researchers with a systematic understanding of transfer process from projects to PBOs, and insight for further research on knowledge transfer in project and organization contexts. Furthermore, this study guides researchers to focus on the causal processes that constitute knowledge transfer and explores the expected and unexpected phenomena generated over time. However, some variables involved in the transfer process are simplified, and the establishment of a more complex dynamic model needs further research and discussion.Practical implicationsBy establishing a simulation model for knowledge transfer from projects to their parent PBOs, this study helps project teams and PBOs grasp the overall picture of the transfer process. Especially, this paper provides target-oriented recommendations for project and PBO managers to implement effective knowledge transfer practices, which have certain practical values for knowledge cultivation, coordination, reuse and innovation in the organization.Originality/valueThis study contributes to knowledge management and project management literature by simulating the knowledge transfer process from projects to their parent PBOs. Additionally, this paper provides a reference for PBO and project managers to establish an integrated knowledge-transfer mechanism in the work process and comprehensively implement effective knowledge transfer practices.

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Li, Zhigang, Shining He, Jing Ning, Zhen Liu, Jingwei Zhang, and Xin Du. "Business model transfer mechanism." Nankai Business Review International 11, no. 1 (November 25, 2019): 44–68. http://dx.doi.org/10.1108/nbri-06-2019-0021.

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Purpose Starting from corporate entrepreneurship, spin-off entrepreneurship and business model theory, this paper aims to examine the key influential factors and inherent mechanism in the process of business model transfer from parent enterprise to spin-off start-ups. Design/methodology/approach Grounded theory method is fit for constructing theoretical models, which can discover and interpret phenomenon and activities. According to the guidance of theoretical sampling and other core principles in grounded theory, this study extracts two parent enterprises named Haier and Phnix and lots of spin-offs derived from them. Findings This paper presents the theoretical framework that business models transfer from parents to spin-offs and probes into the embedding logic and connection relationship between factors and categories in this process, such as preconditions, incubation veins, business model elements, stripping mechanism and independent operations. Research limitations/implications Although this study is focused on the manufacturing industry, the main characteristics, comparative advantages, governance rules summarized from transfer activities of business model in spin-off entrepreneurship can also bring inspirations to both parent enterprises and spin-off start-ups. Originality/value Excavates process and mechanism of business model transfer from internal to external, extends the theoretical perspectives about existing related theories such as corporate entrepreneurship, spin-off entrepreneurship and business model theory and reveals new approaches and methods on business model design, which is different from the past way.

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Ali, W., and S. Kolyubin. "EMG-Based Grasping Force Estimation for Robot Skill Transfer Learning." Nelineinaya Dinamika 18, no. 5 (2022): 0. http://dx.doi.org/10.20537/nd221221.

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In this study, we discuss a new machine learning architecture, the multilayer preceptron-random forest regressors pipeline (MLP-RF model), which stacks two ML regressors of different kinds to estimate the generated gripping forces from recorded surface electromyographic activity signals (EMG) during a gripping task. We evaluate our proposed approach on a publicly available dataset, putEMG-Force, which represents a sEMG-Force data profile. The sEMG signals were then filtered and preprocessed to get the features-target data frame that will be used to train the proposed ML model. The proposed ML model is a pipeline of stacking 2 different natural ML models; a random forest regressor model (RF regressor) and a multiple layer perceptron artificial neural network (MLP regressor). The models were stacked together, and the outputs were penalized by a Ridge regressor to get the best estimation of both models. The model was evaluated by different metrics; mean squared error and coefficient of determination, or $r^{2}$ score, to improve the model prediction performance. We tuned the most significant hyperparameters of each of the MLP-RF model components using a random search algorithm followed by a grid search algorithm. Finally, we evaluated our MLP-RF model performance on the data by training a recurrent neural network consisting of 2 LSTM layers, 2 dropouts, and one dense layer on the same data (as it is the common approach for problems with sequential datasets) and comparing the prediction results with our proposed model. The results show that the MLP-RF outperforms the RNN model.

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Xie, Chengqing, Wenfu Xu, Gang Zhang, and Yingchun Zhang. "Patched shaping approach to low-thrust multi-revolution transfer design." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, no. 7 (June 29, 2018): 2663–72. http://dx.doi.org/10.1177/0954410018785236.

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This paper proposes a patched shaping approach method for the problem of low-thrust multi-revolution transfers between coplanar elliptic orbits. A simple shape is proposed to solve the multi-revolution transfers between coplanar coaxial elliptic orbits with the same eccentricity. The cosine inverse polynomial shape is used to transfer between coplanar noncoaxial elliptic orbits with different eccentricities using three revolutions or less. Finally, the low-thrust multi-revolution trajectory between arbitrary coplanar elliptic orbits can be achieved by means of the patched shaping approximation, which is composed of the proposed shape and the cosine inverse polynomial shape, considering thrust magnitude constraints at patched points. The proposed shape, based on the equation of the radial component, which uses a Fourier expansion of the semimajor axis, can effectively model the low-thrust multi-revolution transfers. And the closed-form solutions of the Fourier series coefficients are determined by the boundary conditions and the trajectory safety constraints. Compared with only a single shape method, numerical results show that the proposed approach of patched shaping can be used with a shorter-transfer-time and lower cost to implement the design of low-thrust multi-revolution transfers.

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Thoméo, J. C., and J. T. Freire. "Heat transfer in fixed bed: a model non-linearity approach." Chemical Engineering Science 55, no. 12 (June 2000): 2329–38. http://dx.doi.org/10.1016/s0009-2509(99)00465-0.

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Hardy, Anne, Oskaras Vorobjovas-Pinta, and Richard Eccleston. "Enhancing knowledge transfer in tourism: An Elaboration Likelihood Model approach." Journal of Hospitality and Tourism Management 37 (December 2018): 33–41. http://dx.doi.org/10.1016/j.jhtm.2018.09.002.

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Yoshioka, Takuya, and Tomohiro Nakatani. "Noise Model Transfer: Novel Approach to Robustness Against Nonstationary Noise." IEEE Transactions on Audio, Speech, and Language Processing 21, no. 10 (October 2013): 2182–92. http://dx.doi.org/10.1109/tasl.2013.2272513.

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Khan, Javed, Abid Haleem, and Zafar Husain. "Barriers to technology transfer: a total interpretative structural model approach." International Journal of Manufacturing Technology and Management 31, no. 6 (2017): 511. http://dx.doi.org/10.1504/ijmtm.2017.089075.

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Husain, Zafar, Javed Khan, and Abid Haleem. "Barriers to technology transfer: a total interpretative structural model approach." International Journal of Manufacturing Technology and Management 31, no. 6 (2017): 511. http://dx.doi.org/10.1504/ijmtm.2017.10010078.

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Andrade, R. F. S. "Potts model on the Sierpínski gasket: A transfer-matrix approach." Physical Review B 48, no. 21 (December 1, 1993): 16095–98. http://dx.doi.org/10.1103/physrevb.48.16095.

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Hampton, Tracy. "Modified Gene Transfer Approach Evaluated in Model of Brain Disease." JAMA 315, no. 1 (January 5, 2016): 19. http://dx.doi.org/10.1001/jama.2015.16891.

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Mishra, Bishwas, and Abhishek Samanta. "Quantum Transfer Learning Approach for Deepfake Detection." Sparklinglight Transactions on Artificial Intelligence and Quantum Computing 02, no. 01 (2022): 17–27. http://dx.doi.org/10.55011/staiqc.2022.2103.

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Deepfake image manipulation has achieved great attention in the previous year’s owing to brings solemn challenges from the public self-confidence. Forgery detection in face imaging has made considerable developments in detecting manipulated images. However, there is still a need for an efficient deepfake detection approach in complex background environments. This paper applies the state-of-the-art quantum transfer learning approach for classifying deepfake images from original face images. The proposed model comprises classical pre-trained ResNet-18 and quantum neural network layers that provide efficient features extraction to learn the different patterns of the deepfake face images. The proposed model is validated on a real-world deepfake dataset created using commercial software. An accuracy of 96.1 % was obtained.

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Leitnaker, Mary G., and Peter Purdue. "Compartmental models with transfer delays: a semi-Markov approach." Journal of Applied Probability 22, no. 3 (September 1985): 570–82. http://dx.doi.org/10.2307/3213861.

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Compartmental models for which transfer from one compartment to another takes a non-negligible time have been studied in the deterministic case. These models rely on the use of differential equations with delayed arguments. In this paper we show how the well-known structure of the semi-Markov process can be used to analyse stochastic compartmental models with transfer delays. Evaluation of the limiting behavior is much simpler in the stochastic model than in previous deterministic formulations. In addition, time-dependent behavior can be analysed using numerical quadrature methods.

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Leitnaker, Mary G., and Peter Purdue. "Compartmental models with transfer delays: a semi-Markov approach." Journal of Applied Probability 22, no. 03 (September 1985): 570–82. http://dx.doi.org/10.1017/s0021900200029338.

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Compartmental models for which transfer from one compartment to another takes a non-negligible time have been studied in the deterministic case. These models rely on the use of differential equations with delayed arguments. In this paper we show how the well-known structure of the semi-Markov process can be used to analyse stochastic compartmental models with transfer delays. Evaluation of the limiting behavior is much simpler in the stochastic model than in previous deterministic formulations. In addition, time-dependent behavior can be analysed using numerical quadrature methods.

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Rachmawati, Ani Wahyu. "Socialization Model of Tacit-Tacit Transfer Knowledge through Appreciative Inquiry Approach." International Journal of Management, Entrepreneurship, Social Sciences, and Humanities 1, no. 1 (April 20, 2018): 14. http://dx.doi.org/10.31098/ijmesh.v1i1.14.

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The aims of study is to describe combination of two big theory between Socialization model of tacit-tacit transfer knowledge and appreciative inquiry approach conceptually. This research idea comes to find better ways in tacit-tacit transfer of knowledge in knowledge management theory. This research is conceptual research and the limitation is about empirical study itself. The result of conceptual paper combine the process of tacit-tacit tansfer knowledge and appreciate inquiry in mental model, creative dialogue and develop mutual trust. Appreciative inquiry as a method to increase positive sense in tranfer knowlegde can be applied in tacit-tacit transfer knowledge phase in SECI Model.

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Rachmawati, Ani Wahyu. "Socialization Model of Tacit-Tacit Transfer Knowledge through Appreciative Inquiry Approach." International Journal of Management, Entrepreneurship, Social Science and Humanities 1, no. 1 (June 27, 2017): 7–14. http://dx.doi.org/10.31098/ijmesh.v1i1.4.

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The aims of study is to describe combination of two big theory between Socialization model of tacit-tacit transfer knowledge and appreciative inquiry approach conceptually. This research idea comes to find better ways in tacit-tacit transfer of knowledge in knowledge management theory. This research is conceptual research and the limitation is about empirical study itself. The result of conceptual paper combine the process of tacit-tacit tansfer knowledge and appreciate inquiry in mental model, creative dialogue and develop mutual trust. Appreciative inquiry as a method to increase positive sense in tranfer knowlegde can be applied in tacit-tacit transfer knowledge phase in SECI Model.

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Ligot, Gauthier, Philippe Balandier, Benoît Courbaud, and Hugues Claessens. "Forest radiative transfer models: which approach for which application?" Canadian Journal of Forest Research 44, no. 5 (May 2014): 391–403. http://dx.doi.org/10.1139/cjfr-2013-0494.

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Radiation is fundamental in forest ecosystem ecology as it drives plant photosynthesis, morphogenesis, and fluxes of carbon, water, and energy between soil, vegetation, and the atmosphere. Though all approaches of forest radiative transfer models (FRTM) share general properties, they differ greatly in terms of calibration parameters, required assumptions, and model objectives. They use different precision levels of canopy description (from one to three dimensions) and different mathematical relationships to model the attenuation of radiation through the canopy. To date, no general guideline has been given to help the modeler choose the approach that best suits his needs. We therefore reviewed evaluation, sensitivity, and performance of FRTMs recently reported in the literature. We quantified FRTM uncertainty and identified the most sensitive parameters relative to the modeling choices. Their advantages and drawbacks are discussed, and recommendations are made relative to application potential.

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Gaultney, Larry D., Miroslaw J. Skibniewski, and Gavriel Salvendy. "A Systematic Approach to Industrial Technology Transfer: A Conceptual Framework and a Proposed Methodology." Journal of Information Technology 4, no. 1 (March 1989): 7–16. http://dx.doi.org/10.1177/026839628900400102.

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This paper presents a new concept of modelling successful transfers of technological innovations across the boundaries of traditionally defined areas of industry. A summary review of work in the related topics is conducted. The proposed model of technological transfer includes a provision for the development of a new taxonomy of work tasks targeted for technology applications. The model also incorporates a matrix framework for representing a match between the generic components of work tasks, typical engineering projects, generic components of technology, and specific self-contained technologies. A validation procedure for application within an industry targeted for technology transfer is outlined.

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Jothe, Jaswant Singh, and Punit Kumar Johari. "COVID-19 CT SCAN IMAGE SEGMENTATION USING TRANSFER LEARNING APPROACH." International Research Journal of Computer Science 8, no. 8 (August 30, 2021): 200–208. http://dx.doi.org/10.26562/irjcs.2021.v0808.008.

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The Computer tomography Scan imaging technique becomes an alternative approach of RTPCR test in COVID-19 diagnosis, disease staging and monitoring of treatment response evolution. The sensitivity of RTPCT is low neat about 70% with compare to the sensitivity of chest CT Scan images technique up to 98%. In this work, COVID-19 CT Scan image segmentation has been performed. The UNET Model has been selected as the baseline model for CT Scan Image Segmentation. The CT Scan Image segmentation performance of the deep learning models has been improved using the transfer learning approach. The IoU values have been improved from 86.94 to 88.90, 93.56, 94.34 using MobileNet as an encoder, DenseNet201 as an encoder, DenseNet169 as an encoder in Baseline UNET Models respectively.

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Sevillya, Gur, Daniel Doerr, Yael Lerner, Jens Stoye, Mike Steel, and Sagi Snir. "Horizontal Gene Transfer Phylogenetics: A Random Walk Approach." Molecular Biology and Evolution 37, no. 5 (December 23, 2019): 1470–79. http://dx.doi.org/10.1093/molbev/msz302.

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Abstract The dramatic decrease in time and cost for generating genetic sequence data has opened up vast opportunities in molecular systematics, one of which is the ability to decipher the evolutionary history of strains of a species. Under this fine systematic resolution, the standard markers are too crude to provide a phylogenetic signal. Nevertheless, among prokaryotes, genome dynamics in the form of horizontal gene transfer (HGT) between organisms and gene loss seem to provide far richer information by affecting both gene order and gene content. The “synteny index” (SI) between a pair of genomes combines these latter two factors, allowing comparison of genomes with unequal gene content, together with order considerations of their common genes. Although this approach is useful for classifying close relatives, no rigorous statistical modeling for it has been suggested. Such modeling is valuable, as it allows observed measures to be transformed into estimates of time periods during evolution, yielding the “additivity” of the measure. To the best of our knowledge, there is no other additivity proof for other gene order/content measures under HGT. Here, we provide a first statistical model and analysis for the SI measure. We model the “gene neighborhood” as a “birth–death–immigration” process affected by the HGT activity over the genome, and analytically relate the HGT rate and time to the expected SI. This model is asymptotic and thus provides accurate results, assuming infinite size genomes. Therefore, we also developed a heuristic model following an “exponential decay” function, accounting for biologically realistic values, which performed well in simulations. Applying this model to 1,133 prokaryotes partitioned to 39 clusters by the rank of genus yields that the average number of genome dynamics events per gene in the phylogenetic depth of genus is around half with significant variability between genera. This result extends and confirms similar results obtained for individual genera in different manners.

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Myers, Scott, and Troi Carleton. "Tonal transfer in Chichewa." Phonology 13, no. 1 (May 1996): 39–72. http://dx.doi.org/10.1017/s095267570000018x.

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What happens to tone when a form is reduplicated in a tone language? In Marantz's (1982) model of reduplication, it is only segmental melody that is copied from the base. This approach predicts that no tones of the base will appear on the reduplicant. In other models, the whole base is copied, including prosody (Steriade 1988; McCarthy & Prince 1988, forthcoming). This approach predicts that the tone of the base will always appear on the reduplicant, i.e. there will be ‘transfer’ of the tone (Clements 1985).

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Leoncini, Giovanni, Roger A. Pielke, and Philip Gabriel. "From Model-Based Parameterizations to Lookup Tables: An EOF Approach." Weather and Forecasting 23, no. 6 (December 1, 2008): 1127–45. http://dx.doi.org/10.1175/2008waf2007033.1.

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Abstract The goal of this study is to transform the Harrington radiation parameterization into a transfer scheme or lookup table, which provides essentially the same output (heating rate profile and short- and longwave fluxes at the surface) at a fraction of the computational cost. The methodology put forth here does not introduce a new parameterization simply derived from the Harrington scheme but, rather, shows that given a generic parameterization it is possible to build an algorithm, largely not based on the physics, that mimics the outcome of the parent parameterization. The core concept is to compute the empirical orthogonal functions (EOFs) of all of the input variables of the parent scheme, run the scheme on the EOFs, and express the output of a generic input sounding exploiting the input–output pairs associated with the EOFs. The weights are based on the difference between the input and EOFs water vapor mixing ratios. A detailed overview of the algorithm and the development of a few transfer schemes are also presented. Results show very good agreement (r > 0.91) between the different transfer schemes and the Harrington radiation parameterization with a very significant reduction in computational cost (at least 95%).

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Secundo, Giustina, Christle De Beer, and Giuseppina Passiante. "Measuring university technology transfer efficiency: a maturity level approach." Measuring Business Excellence 20, no. 3 (August 15, 2016): 42–54. http://dx.doi.org/10.1108/mbe-03-2016-0018.

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Purpose The process of innovation in developing countries is different from that of developed countries, with mature technologies often being adopted with limited success. Universities are increasingly being viewed by policymakers as engines of innovation through the technology transfer office (TTO). However, with the adoption of various new intellectual property right legislation, university TTOs in developing countries have had an inefficient approach to technology transfer. Framed in the above premises, this study aims to develop a Maturity Model to measure, through non-monetary indicators, the efficiency of TTOs. Design/methodology/approach The Maturity Model is inspired by the Berkley (PM)2 Model which allows an organization to determine strengths and weaknesses and to focus on weak practices to achieve higher maturity. Fuzzy analytical hierarchy process is adopted to determine the priorities and weights of the non-monetary indicators because they are ambiguous. Findings The Maturity Model to measure the efficiency of TTO cover the following efficiency areas: intellectual property strategy and policy; organization design and structure; human resource; technology; industry links; and networking. The model provides a theoretical continuum along which the process of maturity can be developed incrementally in TTO from one level to the next, moving from awareness, defined, managed, integrated and sustained stage. Research limitations/implications The Maturity Model needs to be tested and applied in TTOs in developing countries. Practical implications The Maturity Model provides a means to sustain the decision-making process more effectively, especially in those countries considered as an inefficient innovator. Originality/value The findings inform the design of a customizable solution to barriers to the success of technology transfer and highlight weaknesses within each institution or TTOs efficiency.

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Kimura, Nobuaki, Ikuo Yoshinaga, Kenji Sekijima, Issaku Azechi, and Daichi Baba. "Convolutional Neural Network Coupled with a Transfer-Learning Approach for Time-Series Flood Predictions." Water 12, no. 1 (December 26, 2019): 96. http://dx.doi.org/10.3390/w12010096.

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East Asian regions in the North Pacific have recently experienced severe riverine flood disasters. State-of-the-art neural networks are currently utilized as a quick-response flood model. Neural networks typically require ample time in the training process because of the use of numerous datasets. To reduce the computational costs, we introduced a transfer-learning approach to a neural-network-based flood model. For a concept of transfer leaning, once the model is pretrained in a source domain with large datasets, it can be reused in other target domains. After retraining parts of the model with the target domain datasets, the training time can be reduced due to reuse. A convolutional neural network (CNN) was employed because the CNN with transfer learning has numerous successful applications in two-dimensional image classification. However, our flood model predicts time-series variables (e.g., water level). The CNN with transfer learning requires a conversion tool from time-series datasets to image datasets in preprocessing. First, the CNN time-series classification was verified in the source domain with less than 10% errors for the variation in water level. Second, the CNN with transfer learning in the target domain efficiently reduced the training time by 1/5 of and a mean error difference by 15% of those obtained by the CNN without transfer learning, respectively. Our method can provide another novel flood model in addition to physical-based models.

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Halás, Miroslav, Ülle Kotta, and Claude H. Moog. "Transfer Function Approach to the Model Matching Problem of Nonlinear Systems." IFAC Proceedings Volumes 41, no. 2 (2008): 15197–202. http://dx.doi.org/10.3182/20080706-5-kr-1001.02570.

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Khohlova, Svetlana S., Valentina A. Mikhailova, and Anatoly I. Ivanov. "Three-centered model of ultrafast photoinduced charge transfer: Continuum dielectric approach." Journal of Chemical Physics 124, no. 11 (March 21, 2006): 114507. http://dx.doi.org/10.1063/1.2178810.

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Leimbach, Michael. "Learning transfer model: a research‐driven approach to enhancing learning effectiveness." Industrial and Commercial Training 42, no. 2 (March 16, 2010): 81–86. http://dx.doi.org/10.1108/00197851011026063.

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Wu, Wei, and Wen-Li Zhu. "Heat transfer in a nonequilibrium spin-boson model: A perturbative approach." Annals of Physics 418 (July 2020): 168203. http://dx.doi.org/10.1016/j.aop.2020.168203.

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Arabi, Mazdak, Jennifer S. Stillman, and Rao S. Govindaraju. "A process-based transfer function approach to model tile-drain hydrographs." Hydrological Processes 20, no. 14 (2006): 3105–17. http://dx.doi.org/10.1002/hyp.6153.

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Talmoudi, Samia, and Moufida Lahmari. "The multi-model approach for fractional-order systems modelling." Transactions of the Institute of Measurement and Control 40, no. 1 (July 13, 2016): 331–40. http://dx.doi.org/10.1177/0142331216655396.

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Currently, fractional-order systems are attracting the attention of many researchers because they present a better representation of many physical systems in several areas, compared with integer-order models. This article contains two main contributions. In the first one, we suggest a new approach to fractional-order systems modelling. This model is represented by an explicit transfer function based on the multi-model approach. In the second contribution, a new method of computation of the validity of library models, according to the frequency [Formula: see text], is exposed. Finally, a global model is obtained by fusion of library models weighted by their respective validities. Illustrative examples are presented to show the advantages and the quality of the proposed strategy.

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Adebayo, Segun, Halleluyah Oluwatobi Aworinde, Akinwale O. Akinwunmi, Adebamiji Ayandiji, and Awoniran Olalekan Monsir. "Convolutional neural network-based crop disease detection model using transfer learning approach." Indonesian Journal of Electrical Engineering and Computer Science 29, no. 1 (January 1, 2022): 365. http://dx.doi.org/10.11591/ijeecs.v29.i1.pp365-374.

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Crop diseases disrupt the crop's physiological constitution by affecting the crop's natural state. The physical recognition of the symptoms of the various diseases has largely been used to diagnose cassava infections. Every disease has a distinct set of symptoms that can be used to identify it. Early detection through physical identification, however, is quite difficult for a vast crop field. The use of electronic tools for illness identification then becomes necessary to promote early disease detection and control. Convolutional neural networks (CNN) were investigated in this study for the electronic identification and categorization of photographs of cassava leaves. For feature extraction and classification, the study used databases of cassava images and a deep convolutional neural network model. The methodology of this study retrained the models' current weights for visual geometry group (VGG-16), VGG-19, SqueezeNet, and MobileNet. Accuracy, loss, model complexity, and training time were all taken into consideration when evaluating how well the final layer of CNN models performed when trained on the new cassava image datasets.

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Chong, P. Pete, Ye-Sho Chen, and James M. Pruett. "Information Technology Transfer in Econometric Forecasting: A Pictorial Approach." Journal of Information Technology 8, no. 1 (March 1993): 3–13. http://dx.doi.org/10.1177/026839629300800102.

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Successful information technology transfer requires effective communication and clear, concise information exchange. This paper, using the Louisiana econometric model as a case study, proposes a pictorial approach to present and manage complex factors essential to information technology transfer. The approach utilizes multi-layer entity-relationship diagrams to provide a meaningful framework for the entire forecasting process, provide clarity to ensure better model maintenance when changes in social/economic structures require reformulations, and provide a procedural and data dictionary for clear documentation. The pictorial approach is both intuitive and readable, capable of serving as a task management tool, a model implementation aid, and a system maintenance resource.

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Blasiak, Slawomir. "Heat Transfer Analysis for Non-Contacting Mechanical Face Seals Using the Variable-Order Derivative Approach." Energies 14, no. 17 (September 3, 2021): 5512. http://dx.doi.org/10.3390/en14175512.

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This article presents a variable-order derivative (VOD) time fractional model for describing heat transfer in the rotor or stator in non-contacting mechanical face seals. Most theoretical studies so far have been based on the classical equation of heat transfer. Recently, constant-order derivative (COD) time fractional models have also been used. The VOD time fractional model considered here is able to provide adequate information on the heat transfer phenomena occurring in non-contacting face seals, especially during the startup. The model was solved analytically, but the characteristic features of the model were determined through numerical simulations. The equation of heat transfer in this model was analyzed as a function of time. The phenomena observed in the seal include the conduction of heat from the fluid film in the gap to the rotor and the stator, followed by convection to the fluid surrounding them. In the calculations, it is assumed that the working medium is water. The major objective of the study was to compare the results of the classical equation of heat transfer with the results of the equations involving the use of the fractional-order derivative. The order of the derivative was assumed to be a function of time. The mathematical analysis based on the fractional differential equation is suitable to develop more detailed mathematical models describing physical phenomena.

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Oh, JeongRim, JongJin Park, ChangSoo Ok, ChungHun Ha, and Hong-Bae Jun. "A Study on the Wind Power Forecasting Model Using Transfer Learning Approach." Electronics 11, no. 24 (December 10, 2022): 4125. http://dx.doi.org/10.3390/electronics11244125.

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Recently, wind power plants that generate wind energy with electricity are attracting a lot of attention thanks to their smaller installation area and cheaper power generation costs. In wind power generation, it is important to predict the amount of generated electricity because the power system would be unstable due to uncertainty in supply. However, it is difficult to accurately predict the amount of wind power generation because the power varies due to several causes, such as wind speed, wind direction, temperature, etc. In this study, we deal with a mid-term (one day ahead) wind power forecasting problem with a data-driven approach. In particular, it is intended to solve the problem of a newly completed wind power generator that makes it very difficult to predict the amount of electricity generated due to the lack of data on past power generation. To this end, a deep learning based transfer learning model was proposed and compared with other models, such as a deep learning model without transfer learning and Light Gradient Boosting Machine (LGBM). As per the experimental results, when the proposed transfer learning model was applied to a similar wind power complex in the same region, it was confirmed that the low predictive performance of the newly constructed generator could be supplemented.

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Alzubaidi, Laith, Muthana Al-Amidie, Ahmed Al-Asadi, Amjad J. Humaidi, Omran Al-Shamma, Mohammed A. Fadhel, Jinglan Zhang, J. Santamaría, and Ye Duan. "Novel Transfer Learning Approach for Medical Imaging with Limited Labeled Data." Cancers 13, no. 7 (March 30, 2021): 1590. http://dx.doi.org/10.3390/cancers13071590.

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Deep learning requires a large amount of data to perform well. However, the field of medical image analysis suffers from a lack of sufficient data for training deep learning models. Moreover, medical images require manual labeling, usually provided by human annotators coming from various backgrounds. More importantly, the annotation process is time-consuming, expensive, and prone to errors. Transfer learning was introduced to reduce the need for the annotation process by transferring the deep learning models with knowledge from a previous task and then by fine-tuning them on a relatively small dataset of the current task. Most of the methods of medical image classification employ transfer learning from pretrained models, e.g., ImageNet, which has been proven to be ineffective. This is due to the mismatch in learned features between the natural image, e.g., ImageNet, and medical images. Additionally, it results in the utilization of deeply elaborated models. In this paper, we propose a novel transfer learning approach to overcome the previous drawbacks by means of training the deep learning model on large unlabeled medical image datasets and by next transferring the knowledge to train the deep learning model on the small amount of labeled medical images. Additionally, we propose a new deep convolutional neural network (DCNN) model that combines recent advancements in the field. We conducted several experiments on two challenging medical imaging scenarios dealing with skin and breast cancer classification tasks. According to the reported results, it has been empirically proven that the proposed approach can significantly improve the performance of both classification scenarios. In terms of skin cancer, the proposed model achieved an F1-score value of 89.09% when trained from scratch and 98.53% with the proposed approach. Secondly, it achieved an accuracy value of 85.29% and 97.51%, respectively, when trained from scratch and using the proposed approach in the case of the breast cancer scenario. Finally, we concluded that our method can possibly be applied to many medical imaging problems in which a substantial amount of unlabeled image data is available and the labeled image data is limited. Moreover, it can be utilized to improve the performance of medical imaging tasks in the same domain. To do so, we used the pretrained skin cancer model to train on feet skin to classify them into two classes—either normal or abnormal (diabetic foot ulcer (DFU)). It achieved an F1-score value of 86.0% when trained from scratch, 96.25% using transfer learning, and 99.25% using double-transfer learning.

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Losher, Tobias, Thomas Kleiner, Simon Hill, Nadin Sarajlic, Sebastian Rehfeldt, and Harald Klein. "Comparison of the Generalized Species Transfer Model with a Two‐Field Approach for Interfacial Mass Transfer." Chemical Engineering & Technology 43, no. 12 (November 13, 2020): 2576–82. http://dx.doi.org/10.1002/ceat.202000259.

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