• Journal of Information Processing Systems
• /
• v.17 no.3
• /
• pp.441-452
• /
• 2021

Federated learning provides an efficient integrated model for distributed data, allowing the local training of different data. Meanwhile, the goal of multi-task learning is to simultaneously establish models for multiple related tasks, and to obtain the underlying main structure. However, traditional federated multi-task learning models not only have strict requirements for the data distribution, but also demand large amounts of calculation and have slow convergence, which hindered their promotion in many fields. In our work, we apply the rank constraint on weight vectors of the multi-task learning model to adaptively adjust the task's similarity learning, according to the distribution of federal node data. The proposed model has a general framework for solving optimal solutions, which can be used to deal with various data types. Experiments show that our model has achieved the best results in different dataset. Notably, our model can still obtain stable results in datasets with large distribution differences. In addition, compared with traditional federated multi-task learning models, our algorithm is able to converge on a local optimal solution within limited training iterations.

• Journal of Broadcast Engineering
• /
• v.13 no.6
• /
• pp.962-965
• /
• 2008

2-D shape descriptors, which are vectors representing characteristics of shapes, enable comparison and classification of shapes and are mainly applied to image and 3-D model retrieval. Existing descriptors have limitations that they only describe shapes of single closed contours or lack in precision, making it difficult to be applied to shapes with multiple contours. Therefore, in this paper, we propose a new shape descriptor called Multi-Curvature-Scale Space that can be applied to shapes with multiple contours. Specifically, we represent the topology of the sub-contours in the multi-contour along with Curvature-Scale Space descriptors to represent the shapes of each sub-contours. Also, by allowing the weight of each component to be controlled when computing the distance between descriptors the weight, we deal with ambiguities in measuring similarity between shapes. Results of various experiments that prove the effectiveness of proposed descriptor are presented.

• Structural Engineering and Mechanics
• /
• v.41 no.4
• /
• pp.495-508
• /
• 2012

The strength theory of concrete is significant to structure design and nonlinear finite element analysis of concrete structures because concrete utilized in engineering is usually subject to the action of multi-axial stress. Experimental results have revealed that lightweight aggregate (LWA) concrete exhibits plastic flow plateau under high compressive stress and most of the lightweight aggregates are crushed at this stage. For the purpose of safety, therefore, in the practical application the strength of LWA concrete at the plastic flow plateau stage should be regarded as the ultimate strength under multi-axial compressive stress state. With consideration of the strength criterion, the ultimate strength surface of LWA concrete under multi-axial stress intersects with the hydrostatic stress axis at two different points, which is completely different from that of the normal weight concrete as that the ultimate strength surface is open-ended. As a result, the strength criteria aimed at normal weight concrete do not fit LWA concrete. In the present paper, a multi-axial strength criterion for LWA concrete is proposed based on the Unified Twin-Shear Strength (UTSS) theory developed by Prof Yu (Yu et al. 1992), which takes into account the above strength characteristics of LWA under high compressive stress level. In this strength criterion model, the tensile and compressive meridians as well as the ultimate strength envelopes in deviatoric plane under different hydrostatic stress are established just in terms of a few characteristic stress states, i.e., the uniaxial tensile strength $f_t$, the uniaxial compressive strength $f_c$, and the equibiaxial compressive $f_{bc}$. The developed model was confirmed to agree well with experimental data under different stress ratios of LWA concrete.

• Asia pacific journal of information systems
• /
• v.18 no.3
• /
• pp.1-20
• /
• 2008

Based on the multi-attribute utility theory (MAUT), we present a survey method to measure consumer preferences. The multi-attribute utility theory has been used to make decisions in OR/MS field; however, we show that the method can be effectively used to estimate the demand for new services by measuring individual level utility function. Because conjoint method has been widely used to measure consumer preferences for new products and services, we compare the pros and cons of two consumer preference survey methods. Further, we illustrate how swing weighing method can be effectively used to elicit customer preferences especially for new telecommunications services, Multi-attribute utility theory is a compositional approach for modeling customer preference, in which researchers calculate overall service utility by summing up the evaluation results for each attribute. On the contrary, conjoint method is a decompositional approach, which requires holistic evaluations for profiles. Partworth for each attribute is derived or estimated based on the evaluation, and finally consumer preferences for each profile are calculated. However, if the profiles are quite new and unfamiliar to the survey respondents, they will find it very difficult to accurately evaluate the profiles. We believe that the multi-attribute utility theory-based survey method is more appropriate than the conjoint method, because respondents only need to assess attribute level preferences and not holistic assessment. We chose swing weighting method among many weight assessment methods in multi-attribute utility theory, because it is designed to perform in a simple and fast manner. As illustrated in Clemen and Reilly (2001), to assess swing weights, the first step is to create the worst possible outcome as a benchmark by setting the worst level on each of the attributes. Then, each of the succeeding rows "swings" one of the attributes from worst to best. Upon constructing the swing table, respondents rank order the outcomes (rows). The next step is to rate the outcomes in which the rating for the benchmark is set to be 0 and the rating for the best outcome to be 100, and the ratings for other outcomes are determined in the ranges between 0 and 100. In calculating weight for each attribute, ratings are normalized by the total sum of all ratings. To demonstrate the applicability of the approach, we elicited and analyzed individual-level customer preference for new telecommunication services-WiBro and HSDPA. We began with a randomly selected 800 interviewees, and reduced them to 432 because other remaining ones were related to the people who did not show strong intention for subscription to new telecommunications services. For each combination of content and handset, number of responses which favored WiBro and HSDPA were counted, respectively. It was assumed that interviewee favors a specific service when expected utility is greater than that of competing service(s). Then, the market share of each service was calculated by normalizing the total number of responses which preferred each service. Holistic evaluation of new and unfamiliar service is a tough challenge for survey respondents. We have developed a simple and easy method to assess individual level preference by estimating weight of each attribute. Swing method was applied for this purpose. We believe that estimating individual level preference will be quite flexibly used to predict market performance of new services in many different business environments.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.16 no.1
• /
• pp.175-180
• /
• 2008

Due to the global environment problems and the consumer's need for higher vehicle performance, it becomes very important for the global car makers to reduce vehicle weight. To reduce vehicle weight, many car makers have tried to use lightweight materials, for example, aluminum, magnesium, and plastics, for the vehicle structures and components. Especially, the ASF(aluminum space frame) is known for the excellent concept of the vehicle to satisfy structural rigidity, safety performance and weight reduction. In this research, the design of experiments and the multi-disciplinary optimization technique were utilized to meet the weight and structural rigidity target of the ASF. For the structural performance of the ASF, the locations and the size of aluminum extruded frames, aluminum cast nodes, and the aluminum sheets were optimized. As a result, the optimization design procedure has been set up to meet both structural and weight target of the ASF, and the assembled ASF showed good structural performance and weight reduction.

• Proceedings of the IEEK Conference
• /
• 2000.07b
• /
• pp.1041-1044
• /
• 2000

The enhancement to the back-propagation algorithm presented in this paper has resulted from the need to extract sparsely connected networks from networks employing product terms. The enhancement works in conjunction with the back-propagation weight update process, so that the actions of weight zeroing and weight stimulation enhance each other. It is shown that the error measure, can also be interpreted as rate of weight change (as opposed to ${\Delta}W_{ij}$), and consequently used to determine when weights have reached a stable state. Weights judged to be stable are then compared to a zero weight threshold. Should they fall below this threshold, then the weight in question is zeroed. Simulation of such a system is shown to return improved learning rates and reduce network connection requirements, with respect to the optimal network solution, trained using the normal back-propagation algorithm for Multi-Layer Perceptron (MLP), Higher Order Neural Network (HONN) and Sigma-Pi networks.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.16 no.3
• /
• pp.37-43
• /
• 2007

Recent technological developments in machine tools have been focused on high speed, low vibration machining and high precision machining. And the concern with multi-functional machining has been increased for the last several years. Multi-tasking machines are widely used in machine tool industries. Laser multi-tasking machine has been developed for high precision and fewer vibration machining. The purpose of this study is to evaluate the effects of structural reinforcement on Laser multi-tasking machine which is comprehensively combined turning center and laser machine. Up to date, for the structural stability evaluation of a multi-tasking machine, the analysis model has been considered only the weight of the upper parts. The positions of upper parts on multi-tasking machine have not been considered in the model. So, the results of the present FE model have revealed some difference with measurement data in case of multi-tasking machine. Design of the machine and structural analysis is carried out by FEM simulation using the commercial software CATIA V5. In the result of the structural analysis, effectiveness of reinforcement of the bed was confirmed.

• Korean Journal of Agricultural Science
• /
• v.46 no.1
• /
• pp.1-10
• /
• 2019

The objective of this study was to determine the effect of multi-enzyme supplementation in a corn and soybean meal-based diet on the growth performance, apparent nutrient digestibility, blood profile, fecal microbes and noxious gas emission in growing pigs. A total of 80 crossbred [(Landrace ${\times}$ Yorkshire) ${\times}$ Duroc] growing pigs with an average body weight (BW) of $25.04{\pm}1.44kg$ were used in a 6-week experiment. The experimental treatments were as follows: CON, basal diet and; T1, basal diet + 100 mg/kg multi-enzyme. During the experiment, the pigs fed the diet with multi-enzyme supplementation had a higher gain to feed ratio (G/F) (p < 0.05) than the pigs fed the diet without multi-enzyme supplementation. On day 42, the pigs fed the diet with multi-enzyme supplementation had decreased $H_2S$ and $NH_3$ emissions (p < 0.05) than the pigs fed the diet without multi-enzyme supplementation. However, no effect was observed on nutrient digestibility, blood profiles and fecal microbes among the treatments (p > 0.05). In conclusion, it is suggested that multi-enzyme supplementation in a corn and soybean meal based diet can partly improve the growth performance and noxious gas emission of growing pigs.

• IEIE Transactions on Smart Processing and Computing
• /
• v.5 no.1
• /
• pp.22-28
• /
• 2016

Multi-loop control of a boost converter needs a current-sensing circuit to detect the inductor current. Current sensorless multi-loop control reduces the cost, size and weight of the converter. The Luenberger observer (LO) is widely used to estimate the inductor current for current sensorless control of a switching converter. However, the design of the LO-based sensorless multi-loop control has not been well presented, so far. In this paper, a closed-loop characteristics evaluation method is proposed to design an LO-based current sensorless multi-loop control for boost converters. Simulations show evaluations of the closed-loop characteristics. Practical experiments on a digital processor confirm the simulations.

• Proceedings of the Korean Society For Composite Materials Conference
• /
• 2000.04a
• /
• pp.143-148
• /
• 2000

In this article, we presents multi-objective design optimization of laminated composite beam using Fuzzy programming method. At first, the two design objectives are minimizing the structural weight and maximizing the buckling load respectively. Fuzzy multi-optimization problem can be formulated based on results of single optimizations. Due to different relative importance of design objectives, membership functions are constructed by adding exponential parameters for different objective's weights. Finite element analysis of composite beam for buckling behavior are carried by Natural mode method proposed by J.Argyris and computational time of analysis can be reduced. With this scheme, a designer can conveniently obtain a compromise optimal solution of a multi-objective optimization problem only by providing some exponential parameters corresponding to the importance of the objective functions.