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Relevant bibliographies by topics / Asymmetrical Factorial Design

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Academic literature on the topic 'Asymmetrical Factorial Design'

Author: Grafiati

Published: 8 September 2023

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Journal articles on the topic "Asymmetrical Factorial Design"

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KUMAR, PRAKASH, KRISHAN LAL, ANIRBAN MUKHERJEE, UPENDRA KUMAR PRADHAN, MRINMOY RAY, and OM PRAKASH. "Advanced row-column designs for animal feed experiments." Indian Journal of Animal Sciences 88, no. 4 (January 5, 2023): 499–503. http://dx.doi.org/10.56093/ijans.v88i4.78895.

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Inappropriate statistical designs may misinterpret results of animal feed experiments. Thus complete statistical designs can make animal feed research more appropriate and cost effective. Usually factorial row-column designs are used when the heterogeneity in the experimental material is in two directions and the experimenter is interested in studying the effect of two or more factors simultaneously. Attempts have been to develop the method of construction of balanced nested row column design under factorial setup. Factorial experiments are used in designs when two or more factors have same levels or different levels. The designs that are balanced symmetric factorials nested in blocks are called block designs with nested row-column balanced symmetric factorial experiments. These designs were constructed by using confounding through equation methods.Construction of confounded asymmetrical factorial experiments in row-column settings and efficiency factor of confounded effects was worked out. The design can be used in animal feed experiment with fewer resources by not compromising the test accuracy.

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Boguslavsky, Ilya, Slava Z. Brodsky, and Gena R. Ioffe. "Regular uniform main-effect designs derivable from geometric factorial designs in 2n runs." Model Assisted Statistics and Applications 15, no. 4 (December 25, 2020): 323–33. http://dx.doi.org/10.3233/mas-200504.

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The article introduces a general method of construction of asymmetrical regular factorial main-effect designs in 2n runs. It presents a collection of optimal designs constructed by this method in 32, 64, 128, and 256 runs. The method provides exploration of design structure and construction of designs with required properties. Construction of composite designs is given as an example of design structure exploration.

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Voinovich, D., B. Campisi, M. Moneghini, C. Vincenzi, and R. Phan-Tan-Luu. "Screening of high shear mixer melt granulation process variables using an asymmetrical factorial design." International Journal of Pharmaceutics 190, no. 1 (November 1999): 73–81. http://dx.doi.org/10.1016/s0378-5173(99)00278-1.

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Das, Dipa Rani, and Sanjib Ghosh. "An Alternative Method of Construction and Analysis of Asymmetrical Factorial Experiment of the type 6x2² in Blocks of Size 12." Chittagong University Journal of Science 40, no. 1 (June 28, 2018): 137–50. http://dx.doi.org/10.3329/cujs.v40i1.47920.

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This paper focuses on the construction and analysis of an extra ordinary type of asymmetrical factorial experiment which corresponds to fraction of a symmetrical factorial experiment as indicated by Das (1960). For constructing this design, we have used 3 choices and for each choice we have used 5 different cases. Finding the block contents for each case we have seen that there are mainly two different cases for each choice. In case of analysis of variance, we have seen that, for the case where the highest order interaction effect is confounded in 4 replications, the loss of information is same for all the choices. Again for the case where the highest order interaction effect is confounded in 3 replications, the loss of information is also same for all the choices and one effect which is confounded due to fractionation has the same loss of information for all the choices. The Chittagong Univ. J. Sci. 40 : 137-150, 2018

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Hund, E., Y. Vander Heyden, M. Haustein, D. L. Massart, and J. Smeyers-Verbeke. "Comparison of several criteria to decide on the significance of effects in a robustness test with an asymmetrical factorial design." Analytica Chimica Acta 404, no. 2 (January 2000): 257–71. http://dx.doi.org/10.1016/s0003-2670(99)00716-3.

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Luis Pérez, Carmelo J. "On the Application of a Design of Experiments along with an ANFIS and a Desirability Function to Model Response Variables." Symmetry 13, no. 5 (May 18, 2021): 897. http://dx.doi.org/10.3390/sym13050897.

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In manufacturing engineering, it is common to use both symmetrical and asymmetrical factorial designs along with regression techniques to model technological response variables, since the in-advance prediction of their behavior is of great importance to determine the levels of variation that lead to optimal response values to be obtained. For this purpose, regression techniques based on the response surface method combined with a desirability function for multi-objective optimization are commonly employed, since it is usual to find manufacturing processes that require simultaneous optimization of several variables, which exhibit in many cases an opposite behavior. However, these regression models are sometimes not accurate enough to predict the behavior of these response variables, especially when they have significant non-linearities. To deal with this drawback, soft computing techniques are very effective in overcoming the limitations of conventional regression models. This present study is focused on the employment of a symmetrical design of experiments along with a new desirability function, which is proposed in this study, and with soft computing techniques based on fuzzy logic. It will be shown that more accurate results than those obtained from regression techniques are obtained. Moreover, this new desirability function is analyzed in this study.

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Tiwari, Ankit, A. K. Tripathi, Jagannath Pathak, Gaurav Shukla, Aditya Shukla, and Shivam Singh. "Response of Spring Greengram (Vigna radiata L.) Cultivars to Integrated Nutrient Management in Bundelkhand Region of Uttar Pradesh." International Journal of Plant & Soil Science 35, no. 16 (June 23, 2023): 196–200. http://dx.doi.org/10.9734/ijpss/2023/v35i163145.

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A field experiment was conducted to study the effect of integrated nutrient management on growth and yield of spring mungbean (Vigna radiata (L.) Wilczek) cultivars in Bundelkhand region of Uttar Pradesh during season of 2019 at Banda University of Agriculture and Technology, Banda (Uttar Pradesh). The experiment was laid out in asymmetrical factorial randomized block design with 6 treatment combinations of integrated nutrient management practices with 2 varieties. Results revealed that cultivar “Shikha” suits to be the better over “Samrat” in respect of growth, yield attributes, seed yield and economics. Additionally, INM practices had better effect on growth, yield attributes compared to sole application of inorganic fertilizers and vermicompost treatments. 100% RDF + 100% vermicompost had highest seed yield (771kg/ha), closely followed by 75% RDF + 50% vermicompost (741 kg/ha) compared to rest of treatments. Among the INM treatments, application of 50% RDF blended with 50% vermicompost recorded at par values of growth, yield attributes and seed yield over the application of 100% RDF + 100% vermicompost and 75% RDF + 50% vermicompost. On an average, INM treatments noted 69.89, 14.07 and 43.39% higher net returns as well as 68.92, 21.2 and 51.57% more benefit: cost ratio over the control, 100% RDF and 100% vermicompost, respectively. Therefore, application of 50% RDF + 50% vermicompost (1.25 t/ha) was optimum under the existing condition of Bundelkhand.

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Agarwal, S. B., and M. N. Das. "Asymmetrical Factorial Type Switch over Designs." Calcutta Statistical Association Bulletin 35, no. 3-4 (September 1986): 149–56. http://dx.doi.org/10.1177/0008068319860304.

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In the present paper an attempt has been made to construct asymmetrical factorial type switch over designs having strip type arrangement of combination of the levels. To start with two factors at different levels have been considered. One factor has number of levels larger by one compared to the number of levels of other factor. The sequences of levels of second factor are associated with each level symbol of first factor. The situation is similar to strip plot designs in agricultural experiments. Method of construction along with analysis of these designs has been described in this paper.

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Gupta, V. K., Rajender Parsad, Lal Mohan Bhar, and Basudev Kole. "Supersaturated Designs for Asymmetrical Factorial Experiments." Journal of Statistical Theory and Practice 2, no. 1 (March 2008): 95–108. http://dx.doi.org/10.1080/15598608.2008.10411863.

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Zi, Xue-Min, Min-Qian Liu, and Run-Chu Zhang. "Asymmetrical Factorial Designs Containing Clear Effects." Metrika 65, no. 1 (April 14, 2006): 123–31. http://dx.doi.org/10.1007/s00184-006-0064-9.

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Book chapters on the topic "Asymmetrical Factorial Design"

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Kantamneni, S. Prasad, and Charles F. Hofacker. "Building Fractional Factorials: a Methodology for Symmetric and Asymmetric Designs." In Proceedings of the 1993 Academy of Marketing Science (AMS) Annual Conference, 345–49. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13159-7_79.

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"Confounding in Asymmetrical Factorial Designs." In Design and Analysis of Experiments, 466–506. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471709948.ch12.

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"Appendix D: Selected Asymmetrical Balanced Factorial Designs." In Design and Analysis of Experiments, 728–35. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471709948.app4.

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Venkatesha, Shashikiran, and Ranjani Parthasarathi. "Design of Low-Cost Reliable and Fault-Tolerant 32-Bit One Instruction Core for Multi-Core Systems." In Fault Tolerance [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.102823.

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Billions of transistors on a chip have led to integration of many cores leading to many challenges such as increased power dissipation, thermal dissipation, occurrence of faults in the circuits, and reliability issues. Existing approaches explore the usage of redundancy-based solutions for fault tolerance at core level, thread level, micro-architectural level, and software level. Core-level techniques improve the lifetime reliability of multi-core systems with asymmetric cores (large and small cores), which have gained momentum and focus among a large number of researchers. Based on the above implications, multi-core system using one instruction cores (MCS-OIC) factoring its features are proposed in this chapter. The MCS-OIC is an asymmetric multi-core architecture with MIPS core as the conventional core and OICs as the warm standby-redundant core. OIC executes only one instruction named ‘subleq _ subtract if less than or equal to zero’. When there is one of the functional units (i.e., ALU) of any conventional core fails, the opcode of the instruction is sent to the OIC. The OIC decodes the instruction opcode and emulates the faulty instruction by repeated execution of the ‘subleq’ instruction, thus providing fault tolerance. To evaluate the idea, the OIC is synthesized using ASIC and FPGA. Performance implications due to OICs at instruction and application level are evaluated. Yield analysis is estimated for various configurations of multi-core system using OICs.

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Conference papers on the topic "Asymmetrical Factorial Design"

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Han, L., M. Thornton, C. Chandrasekar, S. Maggs, and M. Shergold. "Effect of Specimen Dimensions on Mechanical Behavior of Resistant Spot Welded Aluminium Lap Joints." In ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2010. http://dx.doi.org/10.1115/esda2010-24289.

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A study was carried out to examine the effect of specimen dimensions on mechanical behavior of RSW welded joints. A full factorial Design of Experiment (DOE) approach was applied to the experimental process and analysis stages. Aluminium alloy AA5754 sheet in various thicknesses was used to form symmetrical and asymmetrical joints. Single lap shear test geometry with three dimensional changes; width, length and overlap at two-level, was tested throughout the project. The results demonstrated that for both symmetric and asymmetric stacks, the width of the specimen had a statistically significant effect on both failure mechanism and shear strength value of such joints; a strong interaction effect between length and overlap of the specimen on joint shear strength was observed. Although the strength variation is not substantial in engineering terms, the change in failure mechanism is significant and the results are useful in optimization of lap shear test standards and in comparison of joint strength obtained from different investigations with different specimen dimensions. It is also helpful in assisting structural and manufacturing engineers in design and development of RSW of aluminium for application.

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