• Title/Summary/Keyword: Behavior Inference

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A Study on the Expert System for Food Wastes Reduction using MFA (물질흐름분석(MFA)을 활용한 주방 음식물쓰레기 저감 전문가시스템)

  • Kim, Kwang-Man
    • Journal of the Korea Safety Management & Science
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    • v.15 no.4
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    • pp.245-251
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    • 2013
  • In this paper, the expert system to reduce the amount of food waste is proposed. The method of material flow analysis (MFA) is applied. Proper handling of waste beyond the terms of the need for proactive research been mentioned before, but actually cause the waste generator research focuses on consumer behavior and the business community to analyze the flow of materials within the study are insufficient. In this paper, the type of food consumption and food waste, look at the relationship between the occurrence of secondary schools in the diet is provided for students to examine the preferences of the target model diet expert system was reconfigured. Preference for leaving the food in the diet leads to the important information that is Each diet recipes that make up the target material flow analysis (MFA) was constructed to perform all the database. This database is currently being generated from the rain while cooking diet edible plants and materials to reflect the self-esteem following the recommended diet is used to create. Reducing food waste is actually being used currently in research knowledge to the knowledge base was constructed. Future Home Smart System was developed in conjunction with the system to the user, by providing guidelines for the utilization can be expected.

Game Character Growing System using Player Type Analysis based on Petri-Net (페트리네트 기반 플레이어 타입 분석을 이용한 게임 캐릭터 성장 시스템)

  • Lee, Sinku;Kang, Minsu;Lee, Sangjun
    • Journal of Korea Game Society
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    • v.15 no.6
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    • pp.131-140
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    • 2015
  • The character is one of most important interest-element in role playing game genres since it shows the individuality. In general cases, game players allocate points to talent clauses that they choose. However, it is not easy to provide the suitable character-growing to players in generic system since the cases are too simple and based on just humans choices. In this paper, we propose the character growing system based on the player type inference module. Growth morphology is determined by player's behavior or type. The determination is based on petri-net. Our experimental results and analysis show that our proposed approach is suitable for character-growing system.

Application of Market Basket Analysis to Personalized advertisements on Internet Storefront (인터넷 상점에서 개인화 광고를 위한 장바구니 분석 기법의 활용)

  • 김종우;이경미
    • Korean Management Science Review
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    • v.17 no.3
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    • pp.19-30
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    • 2000
  • Customization and personalization services are considered as a critical success factor to be a successful Internet store or web service provider. As a representative personalization technique, personalized recommendation techniques are studied and commercialized to suggest products or services to a customer of Internet storefronts based on demographics of the customer or based on an analysis of the past purchasing behavior of the customer. The underlining theories of recommendation techniques are statistics, data mining, artificial intelligence, and/or rule-based matching. In the rule-based approach for personalized recommendation, marketing rules for personalization are usually collected from marketing experts and are used to inference with customers data. however, it is difficult to extract marketing rules from marketing experts, and also difficult to validate and to maintain the constructed knowledge base. In this paper, we proposed a marketing rule extraction technique for personalized recommendation on Internet storefronts using market basket analysis technique, a well-known data mining technique. Using marketing basket analysis technique, marketing rules for cross sales are extracted, and are used to provide personalized advertisement selection when a customer visits in an Internet store. An experiment has been performed to evaluate the effectiveness of proposed approach comparing with preference scoring approach and random selection.

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Children's Personalized Inferences when Reasoning about Other's Emotion or Behavior (타인의 정서 및 행동 추론 시 아동의 개인화된 추론)

  • Chung Ha-Na;Yi Soon-Hyung
    • Journal of Families and Better Life
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    • v.24 no.2 s.80
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    • pp.15-26
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    • 2006
  • The purposes of this study were (1) to investigate children's personalized inferences of characters emotional reactions depending on character's personality trait, emotional situation, children's age and gender, (2) to investigate children's personalized inferences of character's behavioral reactions depending on character's personality trait, emotional situation, children's age and gender, (3) to investigate differences between children's personalized inferences of character's emotional reaction and that of character's behavioral reactions. The subjects were 103 children from three age groups (thirty-four 3-year-olds, thirty-three 5-year-olds and thirty-six 7-year-olds). The statistical methods adopted for the data analysis were frequency, percentile, mean, standard deviation, repeated measure ANOVA and paired t-test. The result showed that there were significant differences in children's personalized inferences of character's emotional reaction depending on character's personality trait, emotional situation and their age. There were significant differences in children's personalized inferences of character's behavioral reaction depending on children's age and gender. There were significant differences between personalized inferences of character's emotional reaction and behavioral reactions.

Store Patronage Mix Behavior between Fashion Outlet and Department Store Consumers (패션아웃렛과 백화점 이용 소비자의 점포혼합애고행동)

  • Kim, Hyun-Sik
    • The Korean Journal of Community Living Science
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    • v.18 no.2
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    • pp.265-276
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    • 2007
  • The purpose of this study was 1) to find out the consumer patronage mix of department and fashion outlet stores, 2) to compare the clothing and price attitudes among store patronage groups and 3) to compare the importance of the stores' attributes among the store patronage groups. The subjects were 381 female consumers in the Seoul and Gyeonggi areas. Questionnaires were used to collect the data. The data was analyzed by frequency, factor analysis, ANOVA, Duncan's Multiple Range Test and Cronbach's Alpha. The results were as follows. First, clothing purchasing attitudes of the total respondents were classified by three factors: fashion/confident oriented, appearance oriented, and brand-name oriented. Also, clothing price attitudes were composed of three factors: price/quality-prestige inference, discount/low price pursuit and benefit/value pursuit. In addition, the importance of the store's attributes was composed of five factors: convenience/service, concern of fashion outlet store, brand-name/fashionability, awareness of fashion outlet store, and practical advantage of the store. Second, the department store patronage group was significantly different from the fashion outlet store patronage group in clothing attitude, price attitude, and the importance of the store attribute. Third, the responses of the department store patronage group were significantly different from those of the fashion outlet store patronage group in product reliability and awareness of the fashion outlet store.

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Compressive strength estimation of concrete containing zeolite and diatomite: An expert system implementation

  • Ozcan, Giyasettin;Kocak, Yilmaz;Gulbandilar, Eyyup
    • Computers and Concrete
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    • v.21 no.1
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    • pp.21-30
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    • 2018
  • In this study, we analyze the behavior of concrete which contains zeolite and diatomite. In order to achieve the goal, we utilize expert system methods. The utilized methods are artificial neural network and adaptive network-based fuzzy inference systems. In this respect, we exploit seven different mixes of concrete. The concrete mixes contain zeolite, diatomite, mixture of zeolite and diatomite. All seven concrete mixes are exposed to 28, 56 and 90 days' compressive strength experiments with 63 specimens. The results of the compressive strength experiments are used as input data during the training and testing of expert system methods. In terms of artificial neural network and adaptive network-based fuzzy models, data format comprises seven input parameters, which are; the age of samples (days), amount of Portland cement, zeolite, diatomite, aggregate, water and hyper plasticizer. On the other hand, the output parameter is defined as the compressive strength of concrete. In the models, training and testing results have concluded that both expert system model yield thrilling medium to predict the compressive strength of concrete containing zeolite and diatomite.

A Study on Policing Mechanism in ATM Network using Fuzzy Control (퍼지 제어를 이용한 ATM망에서 PM에 관한 연구)

  • 신관철;박세준;양태규
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.5 no.5
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    • pp.931-940
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    • 2001
  • In this paper, I propose Fuzzy Policing Mechanism(FPM) over ATM networks for the control of traffic which is unpredictable and bursty source. The FPM is consist of counter, subtracter and Fuzzy Logic Controller(FLC). The FLC is divided to fuzzifier, inference engine and defuzzifer The output of FLC inputs to the subtractor and it controls the counter. The counter works as a switch in transmission of cells. In simulation, I compared the FPM with the Leaky Bucket algorithm(LBM) in cell loss probability and performance characteristics. As a result, FPM gives lower cell loss probability than that of LBM and has good response behavior The FPM efficiently controls the transmission of packets which are variable traffic source and, it also has good selectivity.

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Prediction of curvature ductility factor for FRP strengthened RHSC beams using ANFIS and regression models

  • Komleh, H. Ebrahimpour;Maghsoudi, A.A.
    • Computers and Concrete
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    • v.16 no.3
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    • pp.399-414
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    • 2015
  • Nowadays, fiber reinforced polymer (FRP) composites are widely used for rehabilitation, repair and strengthening of reinforced concrete (RC) structures. Also, recent advances in concrete technology have led to the production of high strength concrete, HSC. Such concrete due to its very high compression strength is less ductile; so in seismic areas, ductility is an important factor in design of HSC members (especially FRP strengthened members) under flexure. In this study, the Adaptive Neuro-Fuzzy Inference System (ANFIS) and multiple regression analysis are used to predict the curvature ductility factor of FRP strengthened reinforced HSC (RHSC) beams. Also, the effects of concrete strength, steel reinforcement ratio and externally reinforcement (FRP) stiffness on the complete moment-curvature behavior and the curvature ductility factor of the FRP strengthened RHSC beams are evaluated using the analytical approach. Results indicate that the predictions of ANFIS and multiple regression models for the curvature ductility factor are accurate to within -0.22% and 1.87% error for practical applications respectively. Finally, the effects of height to wide ratio (h/b) of the cross section on the proposed models are investigated.

Optimization of shear connectors with high strength nano concrete using soft computing techniques

  • Sedghi, Yadollah;Zandi, Yosef;Paknahad, Masoud;Assilzadeh, Hamid;Khadimallah, Mohamed Amine
    • Advances in nano research
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    • v.11 no.6
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    • pp.595-606
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    • 2021
  • This paper conducted mainly for forecasting the behavior of the shear connectors in steel-concrete composite beams based on the different factors. The main goal was to analyze the influence of variable parameters on the shear strength of C-shaped and L-shaped angle shear connectors. The method of ANFIS (adaptive neuro fuzzy inference system) was applied to the data in order to select the most influential factors for the mentioned shear strength forecasting. Five inputs are considered: height, length, thickness of shear connectors together with concrete strength and respective slip of the shear connectors after testing. The ANFIS process for variable selection was also implemented in order to detect the predominant factors affecting the forecasting of the shear strength of C-shaped and L-shaped angle shear connectors. The results show that the forecasting methodology developed in this research is useful for enhancing the multiple performances characterizing in the shear strength prediction of C and L shaped angle shear connectors analyzing.

A STUDY OF USING CKKS HOMOMORPHIC ENCRYPTION OVER THE LAYERS OF A CONVOLUTIONAL NEURAL NETWORK MODEL

  • Castaneda, Sebastian Soler;Nam, Kevin;Joo, Youyeon;Paek, Yunheung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.05a
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    • pp.161-164
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    • 2022
  • Homomorphic Encryption (HE) schemes have been recently growing as a reliable solution to preserve users' information owe to maintaining and operating the user data in the encrypted state. In addition to that, several Neural Networks models merged with HE schemes have been developed as a prospective tool for privacy-preserving machine learning. Those mentioned works demonstrated that it is possible to match the accuracy of non-encrypted models but there is always a trade-off in the computation time. In this work, we evaluate the implementation of CKKS HE scheme operations over the layers of a LeNet5 convolutional inference model, however, owing to the limitations of the evaluation environment, the scope of this work is not to develop a complete LeNet5 encrypted model. The evaluation was performed using the MNIST dataset with Microsoft SEAL (MSEAL) open-source homomorphic encryption library ported version on Python (PyFhel). The behavior of the encrypted model, the limitations faced and a small description of related and future work is also provided.