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1
Latha, Kunchaparthi Jyothsna, Markapudi Baburao, and Chaduvula Kavitha. "A Comparative study on Logit leaf model (LLM) and Support leaf model (SLM) for predicting the customer churn." International Journal of Computer Sciences and Engineering 7, no. 5 (May 31, 2019): 1628–32. http://dx.doi.org/10.26438/ijcse/v7i5.16281632.
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Lo, Venus, and Huseyin Topaloglu. "Omnichannel Assortment Optimization Under the Multinomial Logit Model with a Features Tree." Manufacturing & Service Operations Management 24, no. 2 (March 2022): 1220–40. http://dx.doi.org/10.1287/msom.2021.1001.
Анотація:
Problem definition: We consider the assortment optimization problem of a retailer that operates a physical store and an online store. The products that can be offered are described by their features. Customers purchase among the products that are offered in their preferred store. However, customers who purchase from the online store can first test out products offered in the physical store. These customers revise their preferences for online products based on the features that are shared with the in-store products. The full assortment is offered online, and the goal is to select an assortment for the physical store to maximize the retailer’s total expected revenue. Academic/practical relevance: The physical store’s assortment affects preferences for online products. Unlike traditional assortment optimization, the physical store’s assortment influences revenue from both stores. Methodology: We introduce a features tree to organize products by features. The nonleaf vertices on the tree correspond to features, and the leaf vertices correspond to products. The ancestors of a leaf correspond to features of the product. Customers choose among the products within their store’s assortment according to the multinomial logit model. We consider two settings; either all customers purchase online after viewing products in the physical store, or we have a mix of customers purchasing from each store. Results: When all customers purchase online, we give an efficient algorithm to find the optimal assortment to display in the physical store. With a mix of customers, the problem becomes NP-hard, and we give a fully polynomial-time approximation scheme. We numerically demonstrate that we can closely approximate the case where products have arbitrary combinations of features without a tree structure and that our fully polynomial-time approximation scheme performs remarkably well. Managerial implications: We characterize conditions under which it is optimal to display expensive products with underrated features and expose inexpensive products with overrated features.
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Coussement, Kristof, Minh Phan, Arno De Caigny, Dries F. Benoit, and Annelies Raes. "Predicting student dropout in subscription-based online learning environments: The beneficial impact of the logit leaf model." Decision Support Systems 135 (August 2020): 113325. http://dx.doi.org/10.1016/j.dss.2020.113325.
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Chiou, Yan-Shiang, Pei-Ing Wu, Je-Liang Liou, Ta-Ken Huang, and Chu-Wei Chen. "What Is the Willingness to Pay for a Basket of Agricultural Goods? Multi-Features of Organic, Animal Welfare-Based and Natural Products with No Additives." Agriculture 13, no. 9 (September 1, 2023): 1743. http://dx.doi.org/10.3390/agriculture13091743.
Анотація:
The purpose of this study is to construct a model by combining the theory of planned behavior (TPB) with conjoint analysis to evaluate baskets of agricultural goods. Each basket of agricultural goods contains various different products, including white rice and leaf vegetables are either organic or non-organic, hens’ eggs and chicken drumsticks obtained from chickens bred with and without due consideration for animal welfare, and soy sauce and jam with or without additives. The evaluation of these various features is innovative and in accordance with the shopping behavior of most consumers who, most of the time, concurrently evaluate these multi-features and multi-products. The price premium for each feature and the willingness to pay, the highest amount that a consumer is willing to pay, for a specific basket of agricultural goods is evaluated by using the multinomial logit model and the linear regression model. The relationship between essential factors in the TPB and the sociodemographic characteristics of consumers is examined. In general, the ranking of the price premium paid for products from the highest to the lowest is soy sauce, jam, chicken drumsticks, white rice, hens’ eggs, and leaf vegetables, respectively. The price premium for natural products with no additives is higher than that for organic and animal welfare-based products. The evaluation of these multi-features of agricultural goods allows us to observe the relative importance of an agricultural product through the price premium, with different combinations of other products. This indicates that the evaluation of the price premium for only a single product or for multiple products with a single feature might be either over-estimated or under-estimated.
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Nita, M., M. A. Ellis, and L. V. Madden. "Effects of Temperature, Wetness Duration, and Leaflet Age on Infection of Strawberry Foliage by Phomopsis obscurans." Plant Disease 87, no. 5 (May 2003): 579–84. http://dx.doi.org/10.1094/pdis.2003.87.5.579.
Анотація:
Temperature, leaf wetness, and leaflet age effects on infection of strawberry foliage by Phomopsis obscurans were examined in controlled-environment experiments. A mid-season (‘Honeoye’) and early-season (‘Earliglow’) cultivar were used. Tested temperatures were 10, 15, 20, 25, 30, and 35°C, and tested wetness periods were 5, 10, 15, 20, 25, and 35 h. Leaflets were labeled based on age: 0 to 1, 2 to 6, and 7 to 14 days old. Effects of temperature, wetness duration, and leaflet age on the logit of disease incidence and severity were quantified using a linear mixed model analysis of variance (ANOVA). Age, wetness duration, and their interaction significantly affected these measures of disease. Disease intensity decreased dramatically with increasing leaflet age at the time of infection, indicating a decrease in susceptibility with maturation of foliage, and increased with increasing wetness duration. Temperature only affected disease incidence with ‘Honeoye’. A prediction model was developed for leaflet infection based on ANOVA results. Coefficients of determination were approximately 0.8 for both cultivars and measures of disease (incidence and severity), indicating that disease could be described accurately based on environmental conditions and leaflet age.
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Redinbaugh, Margaret G., Julio E. Molineros, Jean Vacha, Sue Ann Berry, Ronald B. Hammond, Laurence V. Madden, and Anne E. Dorrance. "Bean pod mottle virus Spread in Insect-Feeding-Resistant Soybean." Plant Disease 94, no. 2 (February 2010): 265–70. http://dx.doi.org/10.1094/pdis-94-2-0265.
Анотація:
Bean pod mottle virus (BPMV) infection reduces yield and seed quality in soybean. To test the hypothesis that virus incidence and movement within plots would be reduced in soybean with resistance to feeding by the virus' bean leaf beetle (Cerotoma trifurcata) vector, BPMV spread was evaluated in five soybean genotypes at two inoculum levels over 2 years at two locations in Ohio. Soybean genotypes included two insect-feeding-susceptible genotypes (Williams 82 and Resnik), two insect-feeding-resistant, semidwarf genotypes (HC95-15 and HC95-24), and an insect-feeding-susceptible, semidwarf genotype (Troll). BPMV incidence was assessed in individual plants at growth stages R5/R6 and R7/R8 using enzyme-linked immunosorbent assay. Beetle feeding was visually assessed in 2004. Data for infection of individual plants were analyzed using a generalized linear mixed model, with a binomial distribution and logit-link. Within plots, BPMV incidence was highest in Resnik and Williams 82 and significantly lower in Troll. Incidence in HC95-15 was not significantly different than in Williams 82 and Resnik but incidence in HC95-24 was lower than in Resnik. BPMV incidence was also significantly (P < 0.05) affected by year, location, inoculum level and sampling date, with increasing incidence over time and higher incidence at the higher inoculum level. Beetle feeding damage was affected by the interaction of location–genotype. Significant spatial aggregation of infected plants was found for most plots but aggregation was independent of host genotype and inoculum level. Although the results indicate that BPMV infection varied by genotype, they do not support the hypothesis that insect-feeding resistance is sufficient to reduce the incidence and spread of BPMV.
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Muller, WJ, K. Helms, and PM Waterhouse. "National survey of viruses in pastures of subterranean clover. II. Statistical methodology for large scale quantitative ELISA." Australian Journal of Agricultural Research 44, no. 8 (1993): 1863. http://dx.doi.org/10.1071/ar9931863.
Анотація:
Statistical methodology was applied to a survey of time-course incidence of four viruses (alfalfa mosaic virus, clover yellow vein virus, subterranean clover mottle virus and subterranean clover red leaf virus) in improved pastures in southern regions of Australia, with samplings in each winter and spring over 3 years. The 100 samples per paddock collected at each time of sampling provided detection probabilities of 0.63 and 0.87 for 1% and 2% infection respectively. A microtitre plate design for ELISA was developed to include 60 field samples, 10 glasshouse-grown healthy control samples and 6 glasshouse-grown samples infected with the virus under examination. This design was used on 816 plates for each of the four viruses tested. The method used for identification of virus in sap of a plant sample from a particular paddock was that the ELISA reading was both significantly greater than healthy control readings, and an outlier in the distribution of readings of all sap samples from that paddock. It is argued that as the identification of uninfected samples as infected was highly unlikely, this double criterion method was superior to the use of each criterion separately. Use of significance above healthy control values as the sole criterion would have increased virus incidences by about 60%; use of outlier identification as the sole criterion would have increased virus incidences by about 30%. A generalized linear model with binomial errors and logit link was used for adjusting the virus incidences reported in the previous paper (Helms et al. 1993) for biases due to paddocks and/or districts not sampled on some occasions. This adjustment slightly increased overall incidences in all but one sampling and confirmed the time-course increase in incidence over the 3 years of the survey. The same model also proved to be the most appropriate for investigating the effects of year, season and district on virus incidence.
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Muller, WJ, K. Helms, and PM Waterhouse. "Corrigendum - National survey of viruses in pastures of subterranean clover. II. Statistical methodology for large scale quantitative ELISA." Australian Journal of Agricultural Research 44, no. 8 (1993): 1863. http://dx.doi.org/10.1071/ar9931863c.
Анотація:
Statistical methodology was applied to a survey of time-course incidence of four viruses (alfalfa mosaic virus, clover yellow vein virus, subterranean clover mottle virus and subterranean clover red leaf virus) in improved pastures in southern regions of Australia, with samplings in each winter and spring over 3 years. The 100 samples per paddock collected at each time of sampling provided detection probabilities of 0.63 and 0.87 for 1% and 2% infection respectively. A microtitre plate design for ELISA was developed to include 60 field samples, 10 glasshouse-grown healthy control samples and 6 glasshouse-grown samples infected with the virus under examination. This design was used on 816 plates for each of the four viruses tested. The method used for identification of virus in sap of a plant sample from a particular paddock was that the ELISA reading was both significantly greater than healthy control readings, and an outlier in the distribution of readings of all sap samples from that paddock. It is argued that as the identification of uninfected samples as infected was highly unlikely, this double criterion method was superior to the use of each criterion separately. Use of significance above healthy control values as the sole criterion would have increased virus incidences by about 60%; use of outlier identification as the sole criterion would have increased virus incidences by about 30%. A generalized linear model with binomial errors and logit link was used for adjusting the virus incidences reported in the previous paper (Helms et al. 1993) for biases due to paddocks and/or districts not sampled on some occasions. This adjustment slightly increased overall incidences in all but one sampling and confirmed the time-course increase in incidence over the 3 years of the survey. The same model also proved to be the most appropriate for investigating the effects of year, season and district on virus incidence.
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Hinz, Oliver Fast, Pablo Chilibroste, Gabriel Menegazzi, Matías Oborsky, Cristina Genro, Pablo Soca, and Diego A. Mattiauda. "PSXI-31 How is the ingestive behaviour of mid lactating Holstein cows grazing a fescue based pasture under two different defoliation intensities?" Journal of Animal Science 97, Supplement_3 (December 2019): 385–86. http://dx.doi.org/10.1093/jas/skz258.766.
Анотація:
Abstract An experiment was performed to study the effect of two contrasting defoliation intensities of a fescue based pasture on the ingestive behaviour. Treatments were two grazing intensities: lax treatment (TL) 12 cm and control treatment (TC) 6 cm, with four replicants of 0.3 ha each. The starting of the experiment was determined by the three leaf stage. Twenty-four mid lactating Holstein cows were blocked according to parity, body weight, body condition score and calving date. Each plot was grazed by three cows during as many days as necessary until the defoliation height of each treatment was achieved (TL: 6 d; TC: 8 d). The pasture mass was 2530 ± 180 kgDM/ha and animals had access from 8:00 to 16:00. Each cow received 7.4 kgDM of supplementation (17% Crude Protein; 2.81 Mcal/kgDM). After PM milking (17:00 h) animals remained separated in 8 pens, where they received 5.5 kgDM in individual troughs. The remaining supplement was provided in the AM milking (05:00 h). During the access to the pasture, grazing and ruminating times and bites rate (BT; bites/minute) were determined every 5 minutes by visual observation at the beginning, middle and end of the experiment. Daily ruminating (DR) was also logged by electronic recorders in 2h periods (Heatime®HR, SCR Dairy). The PROC GLIMMIX of SAS (SAS 9.2, 2010) with a binomial response distribution and with Logit as a link function, was used to determine the probability of the different events. DR and BR were analysed with a mixed model with block and treatment as fixed effects. The probability of cows grazing was greater for TC than TL and lower for ruminating and DR (Table 1). There was no effect of treatment on BR (55 ± 8.8 bites/min). The changes observed on ingestive behaviour were reflected on productive performance (companion abstract).
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ODUNTAN, TOLULOPE KIKELOMO, TEMITAYO OLAYEMI AJAYI, and JONES OLANREWAJU MOODY. "PHARMACOGNOSTIC STANDARDIZATION AND ANTIMICROBIAL EVALUATION OF BYRSOCARPUS COCCINEUS SCHUM. AND THONN. (CONNARACEAE)." African Journal of Pharmaceutical Research and Development 16, no. 2 (June 7, 2024): 35–50. http://dx.doi.org/10.59493/ajopred/2024.2.4.
Анотація:
The plant Byrsocarpus coccineus Schum and Thonn is used traditionally for treating bacterial and fungal illnesses. This study investigated the ethnobotanical use of B. coccineus, pharmacognostic standard procedures and the antimicrobial properties of the leaf. A semi-structured questionnaire was employed, following the Logit model. Microscopy, macroscopy, physical constants, phytochemical screening, thin layer chromatography and antimicrobial activities (using the agar diffusion and micro broth dilution assays on Bacillus subtilis, Staphylococcus aureus, Multi resistant Staphylococcus aureus (MRSA), Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumonia, Candida albicans and Tricophytum rubrum) were evaluated. The results showed that the ethnobotanical uses include treatment of typhoid, men impotency, gonorrhoea, dysentery, cancer and urinary problems (highest with 30%). Microscopy showed the presence of jigsaw-shaped epidermal cells with numerous anomocytic stomata. Phytochemical screening revealed the presence of carbohydrates, glycosides, alkaloids, saponins, tannins, flavonoids and terpenoids, but steroids were absent. Eight (8) spots were observed for the n-hexane and methanol extract development on TLC in a solvent mixture of n-hexane: ethyl acetate (4:1). All microorganisms were susceptible to n-hexane extract at all serial dilutions (12.5 -50 mg/mL), highest susceptibility to B. subtilis at the 16 mm inhibition zone with gentamicin (positive control) at 16 mm inhibition zone as well. Also found was the lowest minimum inhibitory activity (MIC) on P. aeruginosa (0.1953 mg/mL) and minimum bactericidal concentration (MBC) of 12.5 mg/mL, 6.25 mg/ml and 12.5 mg/mL against S. aureus, B. subtilis and E. coli, respectively, with gentamicin (positive control) having 5 µg/mL, 5 µg/mL and 10 µg/mL, in that order. The aqueous extract showed the highest susceptibility on S. aureus, E. coli and P. aeruginosa, the lowest MIC against B. subtilis (0.78125 mg/mL) and MBC against T. rubrum (12.5 mg/mL). The plant extract showed good antibacterial and antifungal activity and thus can be explored as a new antimicrobial agent or source for new drug discovery.
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Pachuau, Lalrinkimi, and Vanlalchhawna a. "LOGIT MODEL INTERPRETATION OF TRAVEL MODAL CHOICE/ MODAL SPLIT IN AIZAWL CITY." International Journal of Advanced Research 9, no. 02 (February 28, 2021): 990–99. http://dx.doi.org/10.21474/ijar01/12541.
Анотація:
The subject matter of this study pertains to the population of Aizawl city, Mizoram. The data is based on the usage of public or private transportation by individuals irrespective of their ownership of private vehicles. The sample includes respondents who are teachers,high-school and college teachers taken separately, of all age groups, different educational backgrounds, as also different income levels who are mobile, belonging to Aizawl city and around.The study examines only the demand side factors influencing travel decisions. The supply side aspects, relating to public transports are taken as given. A study of this kind is beneficial to many parties like the government in its policy implication and also to the private entities as it is directed towards reduced travel expense. Insight of the mechanisms of the travel decision process will benefit governments to formulate policies that better address consumers needs in transport. The study will also enable public transport managers to understand their consumers needs preference and psyche. Furthermore, since no study of this nature has been conducted for the city of Aizawl, the present study will contribute to the birth of a recorded empirical work. It will also lead to further, deeper, more significant research in the area.This study attempts to contribute to the understanding of how local public transport demand is affected by different factors. The focus of this study is to examine the cause of preference of public transportation over private or vice versa by passengers. Considering the increased use of public transportation by individuals and especially by those who also own private vehicles, it is important to understand what causes this preference of one means over the other and the personal benefits involved with it. Careful analysis also shows that the respondents prefer private transportation to public. The logit model shows that of the variables affecting transport mode choice by individual among high school teachers that is most significant is accessibility and flexibility of the private transportation. Also the variables affecting transport mode choice by individual among college teachers that is most significant is time issues secondly, accessibility and flexibility of the private transportation which was also observed in the preceding sections of the chapter The small sample size, with little variability across the quantitative variables could be the reason of the low significance, yet high odd ratios.
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Carrubba, Clifford J., Amy Yuen, and Christopher Zorn. "In Defense of Comparative Statics: Specifying Empirical Tests of Models of Strategic Interaction." Political Analysis 15, no. 4 (2007): 465–82. http://dx.doi.org/10.1093/pan/mpm008.
Анотація:
Beginning in 1999, Curtis Signorino challenged the use of traditional logits and probits analysis for testing discrete-choice, strategic models. Signorino argues that the complex parametric relationships generated by even the simplest strategic models can lead to wildly inaccurate inferences if one applies these traditional approaches. In their stead, Signorino proposes generating stochastic formal models, from which one can directly derive a maximum likelihood estimator. We propose a simpler, alternative methodology for theoretically and empirically accounting for strategic behavior. In particular, we propose carefully and correctly deriving one's comparative statics from one's formal model, whether it is stochastic or deterministic does not particularly matter, and using standard logit or probit estimation techniques to test the predictions. We demonstrate that this approach performs almost identically to Signorino's more complex suggestion.
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Schaak, Henning, and Oliver Mußhoff. "Public Preferences for Pasture Landscapes and the Role of Scale Heterogeneity." German Journal of Agricultural Economics 70, no. 3 (September 1, 2021): 182–91. http://dx.doi.org/10.30430/70.2021.3.182-191.
Анотація:
The paper investigates the influence of different model specifications for interpreting the results of discrete choice experiments when investigating heterogeneous public landscape preferences. Comparing model specifications based on the Mixed Multinomial Logit and the Generalized Multinomial Logit Model reveals that the parameter estimates appear qualitatively comparable. Still, a more in-depth investigation of the conditional estimate distributions of the sample show that parameter interactions in the Generalized Multinomial Logit Model lead to different interpretations compared to the Mixed Multinomial Logit Model. This highlights the potential impact of common model specifications in the results in landscape preference studies.
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Venema, Yde. "Cylindric modal logic." Journal of Symbolic Logic 60, no. 2 (June 1995): 591–623. http://dx.doi.org/10.2307/2275853.
Анотація:
AbstractTreating the existential quantification ∃νi as a diamond ♢i and the identity νi = νj as a constant δij, we study restricted versions of first order logic as if they were modal formalisms. This approach is closely related to algebraic logic, as the Kripke frames of our system have the type of the atom structures of cylindric algebras; the full cylindric set algebras are the complex algebras of the intended multidimensional frames called cubes.The main contribution of the paper is a characterization of these cube frames for the finite-dimensional case and, as a consequence of the special form of this characterization, a completeness theorem for this class. These results lead to finite, though unorthodox, derivation systems for several related formalisms, e.g. for the valid n-variable first order formulas, for type-free valid formulas and for the equational theory of representable cylindric algebras. The result for type-free valid formulas indicates a positive solution to Problem 4.16 of Henkin, Monk and Tarski [16].
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Kim, K. S., S. E. Taylor, and M. L. Gleason. "Development and validation of a leaf wetness duration model using a fuzzy logic system." Agricultural and Forest Meteorology 127, no. 1-2 (December 2004): 53–64. http://dx.doi.org/10.1016/j.agrformet.2004.07.006.
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Park, Seongmin, and Juneyoung Park. "Multilevel Mixed-Effects Models to Identify Contributing Factors on Freight Vehicle Crash Severity." Sustainability 14, no. 19 (September 20, 2022): 11804. http://dx.doi.org/10.3390/su141911804.
Анотація:
Freight vehicle crashes are more serious than regular vehicle crashes because they are likely to lead to major damage and injury once they occur; therefore, countermeasures are needed. The fatality rate from freight vehicle crashes is 1.5 times higher than that of all other accidents, and the death rate from expressway freight vehicle crashes continues to increase. In this study, the ten-freight-vehicle crash severity models (the ordered logit and probit model, the multinomial logit and probit model, mixed-effects logit and probit model, random-effects ordered logit and probit model, and multilevel mixed-effects ordered logit and probit model) are used to analyze the freight vehicle crash severity factors. The model was constructed using data collected from expressways over eight years, and 13 factors were derived to increase the severity of crashes and 7 factors to reduce the severity of crashes. As a result of comparing the 10 constructed models using AIC and BIC, the multilevel mixed-effects ordered probit model showed the best performance. It is expected that it can contribute to improving the safety of freight vehicles in the expressway section by utilizing factors related to the severity of crashes derived from this study.
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Peña-Orozco, Diego Leon, Jesus Gonzalez-Feliu, Leidy Tatiana Salazar-Aguirre, and Mayra Alejandra Arenas-Ruiz. "Sustainability Fruit Supply Chain Design in the Context of Decentralized Smallholders: Modelling Framework and Sensitivity Analysis." LOGI – Scientific Journal on Transport and Logistics 14, no. 1 (January 1, 2023): 43–54. http://dx.doi.org/10.2478/logi-2023-0005.
Анотація:
Abstract This paper aims to examine the sustainability of smallholders’ citrus supply chain characterized by low coordination and the need to reinforce producers’ welfare, through optimization-based decision support method in the field where logistics specialization and global sustainability are required by agricultural producers. More specifically, a mixed-objective and multi-objective linear programming model is developed to achieve a sustainable balance: at the economic level, to reduce the logistics costs associated with the production chain as well as to reduce the environmental impacts in the form of carbon dioxide emissions generated during transport, while at the social level, integration through job creation into a three-echelons fruit supply chain including producers, intermediaries and retailers. The model is applied to four scenarios, whose analyses determine the importance of supply chain costs that cannot be neglected but which lead to an optimum that also reduces environmental burden and increases social welfare. In conclusion, the integration of opposing approaches represented by this model enables the improvement of the performance of the supply chain studied.
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Munizaga, Marcela A., and Ricardo Alvarez-Daziano. "Testing Mixed Logit and Probit Models by Simulation." Transportation Research Record: Journal of the Transportation Research Board 1921, no. 1 (January 2005): 53–62. http://dx.doi.org/10.1177/0361198105192100107.
Анотація:
Discrete choice models with error structures that are not independent and identically distributed have received enormous attention in the recent literature. A detailed synthetic study tests this type of model in a controlled case. With mixed logit and probit models as the study objects, calibration was implemented with the use of software available on the Internet. The controlled situation was built as a simulation laboratory, which generated databases with known parameters. The effects of various elements were analyzed: number of repetitions of the simulation, number of observations in the database, and how the use of Halton sequences improves the mixed logit calibration. The scale effects on the different models are also discussed. The results obtained in this specific context lead to some recommendations for future users of these powerful modeling tools. In particular, flexible structures require large sample sizes to calibrate the elements of the covariance matrix.
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A., Abreu, and Calado J. M. F. "A Fuzzy Logic Model to Evaluate the Lean Level of an Organization." International Journal of Artificial Intelligence & Applications 8, no. 5 (September 30, 2017): 59–75. http://dx.doi.org/10.5121/ijaia.2017.8505.
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Sarifudin, M. S., M. A. Mansor, and W. Safiei. "Waste Simplification for Warehouse Using Boolean Logic." International Journal of Engineering Technology and Sciences 5, no. 1 (August 27, 2019): 44–52. http://dx.doi.org/10.15282/ijets.v5i1.2822.
Анотація:
Warehouse accumulates non-value added or wastes activities consist of inventory, waiting and transportation. The warehouse is a must to prevent any unforeseen events causing failures to implement the Just-In-Time concept. However, the existence of the warehouse will increase the operation expenditure and can lead to the profit losses. Therefore, the manufacturer needs to identify and eliminate the wastes to reduce the consumption of the resources and keep minimum requirement of the activities such as inventory, waiting and transportation in the warehouse. Value Stream Mapping is one of the Lean tools as an approach to eliminate the non-value added or wastes. This tool visualizes the information and material flow of the manufacturing activities. The development of a model based from Value Stream Mapping determined the current state of the wastes existed in the warehouse activities. The model is used to identify and eliminate the waste in the warehouse. From the information flow, the optimum combination of the wastes was determined through Boolean concept. The wastes are simplified and combined by passing through the Boolean operators consist of AND Gate and OR Gate. The expected outcome of this paper is to propose a conceptual model of new value stream mapping to identify and eliminate the waste in the warehouse. From the removal of wastes, the profit can be increased by reduction of the operation expenditure of the manufacturer.
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Ashok Kumar, Et al. "Automated Plant Disease Diagnosis Using Deep Learning Model." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 11 (November 30, 2023): 01–06. http://dx.doi.org/10.17762/ijritcc.v11i11.9066.
Анотація:
With the world's population growing, it is vital that food crops and medicinal plants are required to be developed in large quantity. A model that can help us understand the process more comprehensively will be explored. Based on a thorough understanding, we are exploring a model that will enable us to extract the precise information and in-depth knowledge we require. There are many plants that contract lethal diseases every year, including food plants. This reduces their output rates. We must employ automated methods to locate the issue inside the facility if we do not want manufacturing prices to rise. The detection of plant diseases can be automated through robotics and image processing. As a result of recent technological advancements, we now have the ability to simplify our artwork. A deep learning and image processing approach can increase the efficiency of detection processes. A great deal of progress has been made in diagnosing plant diseases. An artificial intelligence model was trained to assist in diagnosing flora disorders. Based on the photo information (leaf), the model can be controlled. Identifying the problem and discovering the condition in this study, we propose the use of computer vision technology combined with fuzzy logic to detect and grade leaf diseases. GLCM is performed to extract texture features, and fuzzy logic is applied to grade the disease. K-means clustering is applied for determining defected areas; GLCM is used to determine defected areas; and fuzzy logic is used for diagnosing diseases. About 70% of classifications are accurate according to the model. By using Speed Up Robust Features (SURF), DENSE, and Bag of Visual Words (BOVW) in addition to the global features, the accuracy of the system can be enhanced. A treatment program will help people better understand the illness if one is offered.
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Srinivasan, R. "Mahindra Powerol: powering entrepreneurial growth within a corporate group." Emerald Emerging Markets Case Studies 5, no. 4 (July 9, 2015): 1–13. http://dx.doi.org/10.1108/eemcs-09-2014-0235.
Анотація:
Subject area Corporate Strategy, Vertical integration, Diversification. Study level/applicability Graduate. Case overview The case discusses the evolution, decline and turnaround of Mahindra Powerol, a division inside the large Indian business group, Mahindra & Mahindra (M&M). The Powerol division had its genesis from the then Farm Equipment Sector, when they used the surplus capacity in the tractor manufacturing facilities to produce and sell power generators (Gensets). Powerol capitalized on the rapid growth of the Indian telecommunications sector and the need for power backup at remote locations for the mobile communication towers. Adopting a lean asset model, it transformed the industry ecosystem and grew rapidly. As the telecom opportunity saturated, Powerol performance declined, but quickly rebound as it diversified into other products. As Powerol continues its diversification journey, there are questions about how Powerol can leverage the lean asset model that was their source of competitive advantage in the Gensets market, into other businesses. Expected learning outcomes Introduce the fundamental logic of vertical integration. The case elucidates how and when a firm vertically integrates/outsources its operations. Supplementary materials Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request Teaching notes Instructional Note and Case consent form.
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Cai, Jing, Jianyou Zhao, Yusheng Xiang, Jing Liu, Gang Chen, Yueqi Hu, and Jianhua Chen. "Can I Trust You? Estimation Models for e-Bikers Stop-Go Decision before Amber Light at Urban Intersection." Journal of Advanced Transportation 2020 (December 23, 2020): 1–17. http://dx.doi.org/10.1155/2020/6678996.
Анотація:
Electric bike (e-bike) riders’ inappropriate go-decision, yellow-light running (YLR), could lead to accidents at intersection during the signal change interval. Given the high YLR rate and casualties in accidents, this paper aims to investigate the factors influencing the e-bikers’ go-decision of running against the amber signal. Based on 297 cases who made stop-go decisions in the signal change interval, two analytical models, namely, a base logit model and a random parameter logit model, were established to estimate the effects of contributing factors associated with e-bikers’ YLR behaviours. Besides the well-known factors, we recommend adding approaching speed, critical crossing distance, and the number of acceleration rate changes as predictor factors for e-bikers’ YLR behaviours. The results illustrate that the e-bikers’ operational characteristics (i.e., approaching speed, critical crossing distance, and the number of acceleration rate change) and individuals’ characteristics (i.e., gender and age) are significant predictors for their YLR behaviours. Moreover, taking effects of unobserved heterogeneities associated with e-bikers into consideration, the proposed random parameter logit model outperforms the base logit model to predict e-bikers’ YLR behaviours. Providing remarkable perspectives on understanding e-bikers’ YLR behaviours, the predicting probability of e-bikers’ YLR violation could improve traffic safety under mixed traffic and fully autonomous driving condition in the future.
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Li, Jiayao, Cheng Lin, Liwei Zhuang, Zhilong Xu, Zhenlin Liang, and Yuning Gao. "Research on glass type classification based on Logit model and K-Means clustering algorithm." Highlights in Science, Engineering and Technology 58 (July 12, 2023): 163–71. http://dx.doi.org/10.54097/hset.v58i.10056.
Анотація:
Glass artifacts have been important in human history and are often studied by archaeologists and art historians to understand the development of society, technological progress, and cultural exchange. However, the systematic classification of glass artifacts is a major challenge to their study, because glass artifacts excavated from archaeological excavations are often highly weathered, making it difficult to classify them, so a scientific and reliable method to analyze and systematically classify glass artifacts based on their detected chemical composition is of great importance to the study of human history and culture. In this paper, two methods, logit model classification and cluster analysis, were used to determine the key to distinguishing high-potassium glass from lead-barium glass by the content of PbO, SrO, SnO2, and CaO components. Next, a comparison of the three cluster analyses was used to determine the use of the k-means algorithm to further subdivide the high potassium class and the lead-barium glass artifacts into two subclasses each: high Al-Fe and high Cu-Zn; and high PbP and high Na-Zn. Finally, the sensitivity analysis of the model and the robustness of the model and the reasonableness of the results were analyzed using Pearson correlation coefficients.
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Sreedharan V., Raja, R. Raju, Vijaya Sunder M., and Jiju Antony. "Assessment of Lean Six Sigma Readiness (LESIRE) for manufacturing industries using fuzzy logic." International Journal of Quality & Reliability Management 36, no. 2 (February 4, 2019): 137–61. http://dx.doi.org/10.1108/ijqrm-09-2017-0181.
Анотація:
Purpose Many organizations have reported significant benefits after the implementation of Lean Six Sigma (LSS). Embracing LSS requires asking some important questions: How Lean Six Sigma Readiness (LESIRE) can be measured? How can an organization identify the barriers for LESIRE? Answers to these questions are critical to both academicians and practitioners. The paper aims to discuss this issue. Design/methodology/approach This study illustrates the development process of a Lean Six Sigma Readiness (LESIRE) evaluation model to assess an organization’s readiness for LSS deployment using the fuzzy approach. The model was developed from 4 enablers, 16 criteria and 46 attributes of LSS, identified through a literature review. Findings To demonstrate the efficiency of the model, this study testing the LESIRE evaluation model in three Indian SMEs. Using experts’ ratings and weight, the researchers calculated the Fuzzy Lean Six Sigma index (FLSS) which indicates the LESIRE level of an organization and the Fuzzy Performance Importance Index (FPII) that helps to identify the barriers for LESIRE. Research limitations/implications The main limitations of this study are that it did not consider the failure factors of LSS for model development and the LESIRE was only tested in manufacturing industries. Thus, future researchers could focus on developing a model with failure factors. The results obtained from the SMEs show that LESIRE is capable of assessing LESIRE in an industrial scenario and helps practitioners to measure LESIRE for the future decision making process. Practical implications The LESIRE model is easy to understand and use without much computation complexity. This simplicity makes the LESIRE evaluation model unique from other LSS models. Further, LESIRE was tested in three different SMEs, and it aided them to identify and improve their weak areas, thereby readying them for LSS deployment. Originality/value The main contribution of this study it proposes a LESIRE model that evaluates the organization for FLSS and FPII for LESIRE, which is essential for the organization embarking on an LSS journey. Further, it improves the readiness of the organization that is already practicing LSS.
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Renger, Ralph, Lewe Atkinson, Jessica Renger, Jirina Renger, and Gary Hart. "The connection between logic models and systems thinking concepts." Evaluation Journal of Australasia 19, no. 2 (June 2019): 79–87. http://dx.doi.org/10.1177/1035719x19853660.
Анотація:
This article examines the relationship between systems thinking concepts and the logic model. Two notable shortcomings of the logic model are illustrated: depicting the program theory linearly and failing to place the program in context. Both issues lead to an artificial depiction of reality making evaluation findings difficult to interpret. Systems thinking concepts are defined and how they address these shortcomings is discussed. This article then demonstrates how many systems thinking concepts are evident in the logic model; although in a limited way. This article concludes by noting the importance of using system concepts when answering evaluation questions related to system dynamics and interrelationships.
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M., Sivaram Chowdary, and Puviarasi R. "Accuracy Improvement in Disease Identification of Mango Leaf Using CNN Algorithm Compared with Fuzzy Algorithm." ECS Transactions 107, no. 1 (April 24, 2022): 11889–903. http://dx.doi.org/10.1149/10701.11889ecst.
Анотація:
Aim: The main aim of this work is to measure the accuracy in the identification of mango leaf diseases using Convolutional Neural Networks (CNN) compared with Fuzzy Logic. Materials and methods: The data set contains 10 images collected from the seed buzz website and these images are used for training and testing the predictive model in MATLAB. Statistical analysis is done using SPSS software. In the SPSS tool, the measured accuracy of CNN is compared with the Fuzzy model accuracy. Result: The proposed system using CNN achieved high accuracy of 95.2%, whereas the fuzzy mean algorithm gives an accuracy of 93.5 with the significance value 0.038 for accuracy and 0.073 for sensitivity. Conclusion: The outcome of the study confirms that the CNN-based model provides better results in enhancing the accuracy of disease identification in mango leaves.
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Shalack, Vladimir I. "A natural generalization of the Turing computability model." Logical Investigations 29, no. 2 (2023): 9–35. http://dx.doi.org/10.21146/2074-1472-2023-29-2-9-35.
Анотація:
The Turing computability model is a model of algorithmic symbolic transformations that can be performed by humans. The Church-Turing thesis is a statement about the completeness of their formalisms with respect to this model. Algorithmic transformations are applicable not only to symbols, but also to physical objects. Some of these transformations can be analyzed by means of Turing formalism by way of special character encoding. At the same time, there are physical algorithms that go far beyond the standard Turing model. Examples are recipes, medical procedures, technological processes, etc. Their common feature is not only the operation of physical objects, but also the appeal to external physical processes. The general definition of an algorithm, as prescriptions for a sequence of actions to obtain the desired result, is satisfied by well-known phenomena of goal-directed behavior. Symbolic calculations are a special case of goal-directed behavior. Models of combined temporal and dynamic logic can be used to analyze goal-directed behavior. Such an analysis allows us to conclude that there are at least three types of elementary rules underlying complex purposeful behavior: 1) passively-processual – "If there is a process P , then do nothing, but wait for it to lead you to the desired goal G "; 2) constructive – "If there is a C , perform action d , the immediate result of which is the desired goal G "; 3) constructively-processual – "If C takes place, perform action d so that its immediate result R initiates process P , which will lead to the desired goal G ". The combined logic allows you to determine the conditions for the correctness of these rules. Constructively-processual rules have the property of universality, since two other types of rules are reduced to them. In the paper we define a T-machine (teleological machine) that implements complex goal-directed behavior, and conduct a comparative analysis with Turing machines. It is shown that within the framework of the new algorithmic model there are functions that are computable in it, but not computable in Turing model. In the new model, algorithms have the status of laws of living nature related to the emergence of life and evolution. The algorithmic model of goal-directed behavior can be naturally applied to describe and analyze many phenomena of the social sphere.
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Thornton, Peter E., and Niklaus E. Zimmermann. "An Improved Canopy Integration Scheme for a Land Surface Model with Prognostic Canopy Structure." Journal of Climate 20, no. 15 (August 1, 2007): 3902–23. http://dx.doi.org/10.1175/jcli4222.1.
Анотація:
Abstract A new logical framework relating the structural and functional characteristics of a vegetation canopy is presented, based on the hypothesis that the ratio of leaf area to leaf mass (specific leaf area) varies linearly with overlying leaf area index within the canopy. Measurements of vertical gradients in specific leaf area and leaf carbon:nitrogen ratio for five species (two deciduous and three evergreen) in a temperate climate support this hypothesis. This new logic is combined with a two-leaf (sunlit and shaded) canopy model to arrive at a new canopy integration scheme for use in the land surface component of a climate system model. An inconsistency in the released model radiation code is identified and corrected. Also introduced here is a prognostic canopy model with coupled carbon and nitrogen cycle dynamics. The new scheme is implemented within the Community Land Model and tested in both diagnostic and prognostic canopy modes. The new scheme increases global gross primary production by 66% (from 65 to 108 Pg carbon yr−1) for diagnostic model simulations driven with reanalysis surface weather, with similar results (117 PgC yr−1) for the new prognostic model. Comparison of model predictions to global syntheses of observations shows generally good agreement for net primary productivity (NPP) across a range of vegetation types, with likely underestimation of NPP in tundra and larch communities. Vegetation carbon stocks are higher than observed in forest systems, but the ranking of stocks by vegetation type is accurately captured.
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Kim, K. S., M. L. Gleason, and S. E. Taylor. "Forecasting Site-Specific Leaf Wetness Duration for Input to Disease-Warning Systems." Plant Disease 90, no. 5 (May 2006): 650–56. http://dx.doi.org/10.1094/pd-90-0650.
Анотація:
Empirical models based on classification and regression tree analysis (CART model) or fuzzy logic (FL model) were used to forecast leaf wetness duration (LWD) 24 h into the future, using site-specific weather data estimates as inputs. Forecasted LWD and air temperature then were used as inputs to simulate performance of the Melcast and TOM-CAST disease-warning systems. Overall, the CART and FL models underpredicted LWD with a mean error (ME) of 2.3 and 3.9 h day-1, respectively. The CFL model, a corrected version of the FL model using a weight value, reduced ME in LWD forecasts to -1.1 h day-1. In the Melcast and TOM-CAST simulations, the CART and CFL models predicted timing of occurrence of action thresholds similarly to thresholds derived from on-site weather data measurements. Both models forecasted the exact spray dates for approximately 45% of advisories derived from measurements. When hindcast and forecast estimates derived from site-specific estimates provided by SkyBit Inc. were used as inputs, the CART and CFL models forecasted spray advisories within 3 days for approximately 70% of simulation periods for the Melcast and TOM-CAST disease-warning systems. The results demonstrate that these models substantially enhance the accuracy of commercial site-specific LWD estimates and, therefore, can enhance performance of disease-warning systems using LWD as an input.
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Nassif, Ali Bou, Mohammad Azzeh, Ali Idri, and Alain Abran. "Software Development Effort Estimation Using Regression Fuzzy Models." Computational Intelligence and Neuroscience 2019 (February 20, 2019): 1–17. http://dx.doi.org/10.1155/2019/8367214.
Анотація:
Software effort estimation plays a critical role in project management. Erroneous results may lead to overestimating or underestimating effort, which can have catastrophic consequences on project resources. Machine-learning techniques are increasingly popular in the field. Fuzzy logic models, in particular, are widely used to deal with imprecise and inaccurate data. The main goal of this research was to design and compare three different fuzzy logic models for predicting software estimation effort: Mamdani, Sugeno with constant output, and Sugeno with linear output. To assist in the design of the fuzzy logic models, we conducted regression analysis, an approach we call “regression fuzzy logic.” State-of-the-art and unbiased performance evaluation criteria such as standardized accuracy, effect size, and mean balanced relative error were used to evaluate the models, as well as statistical tests. Models were trained and tested using industrial projects from the International Software Benchmarking Standards Group (ISBSG) dataset. Results showed that data heteroscedasticity affected model performance. Fuzzy logic models were found to be very sensitive to outliers. We concluded that when regression analysis was used to design the model, the Sugeno fuzzy inference system with linear output outperformed the other models.
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Jacobs, Jules, Jonas Kastberg Hinrichsen, and Robbert Krebbers. "Deadlock-Free Separation Logic: Linearity Yields Progress for Dependent Higher-Order Message Passing." Proceedings of the ACM on Programming Languages 8, POPL (January 5, 2024): 1385–417. http://dx.doi.org/10.1145/3632889.
Анотація:
We introduce a linear concurrent separation logic, called LinearActris , designed to guarantee deadlock and leak freedom for message-passing concurrency. LinearActris combines the strengths of session types and concurrent separation logic, allowing for the verification of challenging higher-order programs with mutable state through dependent protocols. The key challenge is to prove the adequacy theorem of LinearActris, which says that the logic indeed gives deadlock and leak freedom “for free” from linearity. We prove this theorem by defining a step-indexed model of separation logic, based on connectivity graphs . To demonstrate the expressive power of LinearActris, we prove soundness of a higher-order (GV-style) session type system using the technique of logical relations. All our results and examples have been mechanized in Coq.
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Agrawal, Rohit, P. Asokan, and S. Vinodh. "Benchmarking fuzzy logic and ANFIS approaches for leanness evaluation in an Indian SME." Benchmarking: An International Journal 24, no. 4 (May 2, 2017): 973–93. http://dx.doi.org/10.1108/bij-06-2016-0083.
Анотація:
Purpose The purpose of this paper is to present a study that is focused on application of fuzzy logic and adaptive neuro-fuzzy inference system (ANFIS) approaches for leanness evaluation in an Indian small- and medium-size enterprise (SME). Design/methodology/approach Lean manufacturing concepts are being adopted by SMEs to sustain in the competitive manufacturing landscape. Performance of lean system needs to be assessed using appropriate methods. A model for measuring lean performance is proposed with five enablers, 30 criteria and 90 attributes. Leanness index is computed using fuzzy logic approach and benchmarked with ANFIS approach. Findings Leanness index computed using fuzzy logic approach is found to be (4.47, 5.97, 7.55) and that of ANFIS approach is found to be 5.84 to facilitate benchmarking of leanness evaluation. After finding weaker areas, certain improvement initiatives are being deployed. Research limitations/implications The developed model for leanness evaluation has been test implemented in an SME. In future, the model could be test implemented in several SMEs. Practical implications A case study conducted in an SME involved in heavy engineering fabrication is presented. Therefore, the inferences derived from the study has practical propensity. Originality/value The development of leanness evaluation model for SMEs and deployment in an industrial scenario are the original contributions of the authors.
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Bagloee, Saeed Asadi, Mohsen Asadi, and Cyrus Mohebbi. "A Model for Screening Vulnerability in the Loan Market in the Context of Credit Rationing." International Journal of Strategic Decision Sciences 5, no. 1 (January 2014): 59–75. http://dx.doi.org/10.4018/ijsds.2014010104.
Анотація:
The loan market has contributed to the success and failure of economies. Examples of such failures are the US subprime mortgage crisis as well as the global economic meltdown that followed. Many factors influence the loan market, making it volatile and vulnerable. As such, it is important to understand the extent of its vulnerability. Such uncertainties emerge from asymmetric information in the loan market that may lead to credit rationing. Many studies have been devoted to exploring theoretical aspects of the credit market. However, before delving into the theory, it is important to understand and analyze empirical data. Having said that, the literature has yet to provide reliable methodologies for analyzing the empirical data of the loan market. Therefore, given an empirical survey, this study provides a model describing borrowers' behavior in the loan markets. Borrowers are faced with a variety of loan contracts with different terms and conditions from different banks. Logit models can be used to capture the borrowers' choice of bank. Credit is not easily available rather it is rationed and borrowers compete to obtain their required credit via best suited banks offers. The competition is guaranteed by developing a mathematical programming formulation (an objective function subject to constraints) integrated with the logit models for which a solution algorithm using Successive Coordinate Descent was developed. Numerical results of the methodology are presented. Loan terms and conditions as well the borrowers characteristics and preferences are captured in the logit models as explanatory variables. The methodology allows sensitivity analysis on the explanatory variables demonstrating the fluctuation and vulnerability of credit flow.
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Wang, Quanhui, En Fan, and Pengfei Li. "Fuzzy-Logic-Based, Obstacle Information-Aided Multiple-Model Target Tracking." Information 10, no. 2 (February 2, 2019): 48. http://dx.doi.org/10.3390/info10020048.
Анотація:
Incorporating obstacle information into maneuvering target-tracking algorithms may lead to a better performance when the target when the target maneuver is caused by avoiding collision with obstacles. In this paper, we propose a fuzzy-logic-based method incorporating new obstacle information into the interacting multiple-model (IMM) algorithm (FOIA-MM). We use convex polygons to describe the obstacles and then extract the distance from and the field angle of these obstacle convex polygons to the predicted target position as obstacle information. This information is fed to two fuzzy logic inference systems; one system outputs the model weights to their probabilities, the other yields the expected sojourn time of the models for the transition probability matrix assignment. Finally, simulation experiments and an Unmanned Aerial Vehicle experiment are carried out to demonstrate the efficiency and effectiveness of the proposed algorithm.
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Sándor, Gáspár, Gábor Vajda, and Ede Martos. "Qualification of the results of aggregated lean KPIs along fuzzy logic." Multidiszciplináris kihívások, sokszínű válaszok, no. 2 (December 31, 2021): 2–27. http://dx.doi.org/10.33565/mksv.2021.02.01.
Анотація:
The application of lean management has become a fundamental competitive criterion in the operation of industrial enterprises in the 21st century. The use of tools and methods related to different lean management appears in a significant part of corporate functions. However, it is also important to mention that these lean tools and methods are used in addition to the mixed use of many other tools and methods that support non-lean goals. This problem is also a challenge for controlling. Because lean accounting methods do not necessarily measure the extent of lean effectively in such an environment, a number of other methods are used to monitor lean in both academic and business practice. Of these, lean evaluation models based on fuzzy logic should be highlighted. With the help of these models, it is possible to determine the lean performance of a company primarily along financial data. The disadvantage of the model, however, is that lean management also appears in a number of functional areas that cannot be assessed along financial ratios, but they clearly influence the operation of lean management.
In our research, we illustrated a complex set of lean controlling methods through an instrumental case study, which allows companies to evaluate the performance of lean management and to explore different points of intervention. Our research results make it possible to calculate the lean fuzzy index not only along financial data, and thus clarify the information content of the index. Along the methods and indicators formulated in our research, the effectiveness of lean methods and tools, as well as the processes and methods supporting lean goals, can be separated and measured. Our research goal is to create a generally applicable lean controlling conceptual model.
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Zhang, Tong, Mingyu Cui, and Nina He. "Classification and identification of glass artifacts based on fuzzy clustering and binary logit regression analysis." Highlights in Science, Engineering and Technology 22 (December 7, 2022): 299–306. http://dx.doi.org/10.54097/hset.v22i.3392.
Анотація:
This paper establishes a mathematical model based on the existing data of glass types, summarizes the classification rules of high potassium glass and lead-barium glass, and selects the appropriate chemical composition and subclasses for high potassium glass and lead-barium glass. And based on the classification law, the chemical composition data of the unknown category of glass artifacts are used to identify the type to which they belong.
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Abbes, Nedra, Néjib Sejri, Jun Xu, and Morched Cheikhrouhou. "New Lean Six Sigma readiness assessment model using fuzzy logic: Case study within clothing industry." Alexandria Engineering Journal 61, no. 11 (November 2022): 9079–94. http://dx.doi.org/10.1016/j.aej.2022.02.047.
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Patterson, Chris, and Heather M. Arthur. "A Model for Implementing Integrative Practice in Health Care Agencies." Integrative Medicine Insights 3 (January 2008): 117863370800300. http://dx.doi.org/10.4137/117863370800300001.
Анотація:
Over the last few years, there has been increased awareness and use of complementary/alternative therapies (CAM) in many countries without the health care infrastructure to support it. The National Centre for Complementary and Alternative Medicine referred to the combining of mainstream medical therapies and CAM as integrative medicine. The creation of integrative health care teams will definitely result in redefining roles, but more importantly in a change in how services are delivered. The purpose of this paper is to describe a model of the necessary health care agency resources to support an integrative practice model. A logic model is used to depict the findings of a review of current evidence. Logic models are designed to show relationships between the goals of a program or initiative, the resources to achieve desired outputs and the activities that lead to outcomes. The four major resource categories necessary for implementing integrative care are within the domains of a) professional and research development, b) health human resource planning, c) regulation and legislation and d) practice and management in clinical areas. It was concluded that the system outcomes from activities within these resource categories should lead to freedom of choice in health care; a culturally sensitive health care system and a broader spectrum of services for achieving public health goals.
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Özger, Mehmet, Ashok K. Mishra, and Vijay P. Singh. "Long Lead Time Drought Forecasting Using a Wavelet and Fuzzy Logic Combination Model: A Case Study in Texas." Journal of Hydrometeorology 13, no. 1 (February 1, 2012): 284–97. http://dx.doi.org/10.1175/jhm-d-10-05007.1.
Анотація:
Abstract Drought forecasting is important for drought risk management. Considering the El Niño–Southern Oscillation (ENSO) variability and persistence in drought characteristics, this study developed a wavelet and fuzzy logic (WFL) combination model for long lead time drought forecasting. The idea of WFL is to separate each predictor and predictand into their frequency bands and then reconstruct the predictand series by using its predicted bands. The strongest-frequency bands of predictors and predictand were determined from the average wavelet spectra. Applying this combination model to the state of Texas, it was found that WFL had a significant improvement over the fuzzy logic model that did not use wavelet banding. Comparison with an artificial neural network (ANN) model and a coupled wavelet and ANN (WANN) model showed that WFL was more accurate for drought forecasting. Also, it should be noted that the ENSO variability is not a global precursor of drought. For this reason, prior to an application of such a data-driven model in different regions, significant work is required to identify appropriate independent predictors. Drought forecasting with longer lead times and higher accuracy is of significant value in engineering applications.
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Janková, Zuzana, Dipak Kumar Jana, and Petr Dostál. "Investment Decision Support Based on Interval Type-2 Fuzzy Expert System." Engineering Economics 32, no. 2 (April 29, 2021): 118–29. http://dx.doi.org/10.5755/j01.ee.32.2.24884.
Анотація:
The decision-making process on investing in financial markets is a very complex and difficult task, mainly due to the chaotic behavior and high uncertainty in the development of the prices of investment instruments. For this reason, financial markets are increasingly using means of artificial intelligence, namely fuzzy logic, which is able to capture the nonlinear behavior.Fuzzy logic provides a way to draw definitive conclusions from vague, ambiguous, or inaccurate information.However, there are some drawbacks associated with type-1 fuzzy logic, so the type-2 fuzzy logic comes forward, which can work with greater uncertainty. Type-2 fuzzy logic works with a new third dimension fuzzy set that provides additional degrees of freedom and allows to model and process numerical and linguistic uncertainties directly. The paper applies type-2 fuzzy logic to the stock market with the aim to create a simple and understandable model for deciding on investing in investment instruments, which is important for investors in this area. The proposed type-2 fuzzy model uses return, risk, dividend and total expense ratio of ETF as input variables. The created system is able to generate aggregated models from a certain number of language rules, which allows the investor to understand the created financial model. Using type-2 fuzzy logic can lead to more realistic and accurate results than type-1 fuzzy logic.
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Kazmane, Jaouad. "Proposal and Analysis of a Model for Design and Development of Lean Supply Chain Strategy." International Journal of Engineering Research in Africa 37 (August 2018): 158–71. http://dx.doi.org/10.4028/www.scientific.net/jera.37.158.
Анотація:
In a highly competitive environment, cost reduction and optimization of the supply chain are more than ever a strategic issue for companies. In this work, we are going to propose and analyze a model of design and development of the Lean Supply Chain strategy. This model based on the results and the logic of the model proposed in the previous research work, and more precisely the way of the determination of Supply Chain strategies, whose aspect is operational excellence. This model serves as a decision support tool for business managers to design or develop Supply Chain strategies based on the Lean supply chain.
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Boisvert, Richard N., Nelson L. Bills, and Elizabeth Bailey. "A Model to Explain Participation in New York's Agricultural Districts and Use-Value Assessment Programs." Northeastern Journal of Agricultural and Resource Economics 17, no. 2 (October 1988): 167–77. http://dx.doi.org/10.1017/s0899367x0000180x.
Анотація:
Logit regression models are estimated to identify factors affecting decisions to enroll farmland in New York's agricultural districts program and participate in the use-value assessment program. The results suggest that the districts law is consistent with preserving the best farmland at the rural-urban fringe and that the decision to enroll in agricultural districts affects in a recursive fashion the decision to participate in the use-value assessment program. Short-term monetary gains are the overriding considerations in applying for use-value exemptions. This may lead to additional erosion of the tax base via tax preferences for agricultural land.
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Cheng, Jing, and Xiaowei Luo. "Analyzing the Land Leasing Behavior of the Government of Beijing, China, via the Multinomial Logit Model." Land 11, no. 3 (March 3, 2022): 376. http://dx.doi.org/10.3390/land11030376.
Анотація:
In this paper, the government behavior of leasing different land use rights in Beijing, China, is analyzed using data analysis based on the multinomial logit model. The factors that lead the government to lease different land use rights are considered from the aspects of the land features, geographical location of the land, district economic development, government finance and political tenure of the district head, etc. Considering the factors as the variables, the multinomial logit model is presented to analyze the factors that affect the district government behavior on leasing different land use rights. The data of the variables are obtained in Beijing at the district level from 2004 to 2015. From the results, we can see that the area and price of the land, gross domestic product, foreign direct investment, distance of the land from airport, distance of the land from city center, distance of the land from the nearest industrial park, government fiscal deficit and tenure of the district head all influence the district government behavior on leasing land. Finally, the policy implications are proposed. The results and implications can be referenced by other metropolises in China and other developing countries with public ownership of land.
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Ashok Kumar, Et al. "Deep Learning for Automated Diagnosis of Plant Diseases: A Technological Approach." Journal of Electrical Systems 20, no. 1 (January 25, 2024): 01–08. http://dx.doi.org/10.52783/jes.655.
Анотація:
- With the world's population growing, it is vital that food crops and medicinal plants are required to be developed in large quantity. A model that can help us understand the process more comprehensively will be explored. Based on a thorough understanding, we are exploring a model that will enable us to extract the precise information and in-depth knowledge we require. There are many plants that contract lethal diseases every year, including food plants. This reduces their output rates. We must employ automated methods to locate the issue inside the facility if we do not want manufacturing prices to rise. The detection of plant diseases can be automated through robotics and image processing. As a result of recent technological advancements, we now have the ability to simplify our artwork. A deep learning and image processing approach can increase the efficiency of detection processes. A great deal of progress has been made in diagnosing plant diseases. An artificial intelligence model was trained to assist in diagnosing flora disorders. Based on the photo information (leaf), the model can be controlled. Identifying the problem and discovering the condition in this study, we propose the use of computer vision technology combined with fuzzy logic to detect and grade leaf diseases. GLCM is performed to extract texture features, and fuzzy logic is applied to grade the disease. K-means clustering is applied for determining defected areas; GLCM is used to determine defected areas; and fuzzy logic is used for diagnosing diseases. About 70% of classifications are accurate according to the model. By using Speed Up Robust Features (SURF), DENSE, and Bag of Visual Words (BOVW) in addition to the global features, the accuracy of the system can be enhanced. A treatment program will help people better understand the illness if one is offered.
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Saier, Martin Christopher. "Going back to the roots of W.A. Shewhart (and further) and introduction of a new CPD cycle." International Journal of Managing Projects in Business 10, no. 1 (January 4, 2017): 143–66. http://dx.doi.org/10.1108/ijmpb-11-2015-0111.
Анотація:
Purpose Investigating the beginning of project management (app. 30 BC) with a focus on business models similar to the “PDCA” cycle, the purpose of this paper is to find an approach which could be used as a new standard procedure for the eradication of projects in Lean project management. Design/methodology/approach Based on literature research of models similar to Walter A. Shehwart’s three-step and Edward W. Deming’s four-step (PDC(A)) wheel, the investigated models are interconnected to form a new concept which represents an innovative cycle logic proposed to be applied in Lean project management. This new cycle logic is rolled out on three different levels, which are transferred from the Lean management hoshin kanri model to Lean project management. In addition to literature research, semi-structured interviews were performed to get an indication as to the integration of Lean management (with a focus on PDCA) in project management today. Findings It was found that the “Check Plan Do” cycle is a Lean variant of the “Plan Do Check Act” model that is already used in consulting projects in practice, partially appears in project management standards, in governance models of ambulance, fire services, human aid and military forces and in quality management models of Six Sigma, design for Six Sigma and an excellence model of the European Foundation for Quality Management. To ensure continuous improvement it was found that the new CPD cycle can be used on different “planning” levels in analogy to the hoshin kanri logic. Originality/value To the best of the author’s knowledge, a discussion as to how the PDCA cycle can be adapted to Lean project management, considering the implication of business models similar to the PDCA wheel, has not yet been conducted within the field of project management.
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Xu, Baowei, Boxun Li, and Siyu Tian. "Glass classification and identification based on lasso regression and K-means clustering." Highlights in Science, Engineering and Technology 40 (March 29, 2023): 80–88. http://dx.doi.org/10.54097/hset.v40i.6563.
Анотація:
Ancient glass is classified into two types, high potassium glass and lead-barium glass, which are highly susceptible to weathering by the burial environment. In order to protect the glass artifacts more safely, based on some data related to the chemical composition ratio of glass artifacts,by the lasso regression model based on the logit transformation, the classification rules of high potassium and lead-barium glass were analyzed, and the glass was divided into four subclasses based on the principal component analysis using K-means clustering, and sensitivity analysis was performed on the classification results. Finally, the validity of the model was verified by determining the type of glass to which a set of test data belonged.
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Ghorbel, Faiez, Wafik Hachicha, Younes Boujelbene, and Awad M. Aljuaid. "Linking Entrepreneurial Innovation to Effectual Logic." Sustainability 13, no. 5 (March 1, 2021): 2626. http://dx.doi.org/10.3390/su13052626.
Анотація:
The terms “innovation” and “effectuation” are frequently used but not in the same thought. In this order, publications linking innovation to effectuation are presented and discussed through a methodology based on the publish and perish tool. In the last two decades, effectuation has become an active criterion in entrepreneurship research. However, previous studies do not interconnect effectuation to the different innovation approaches. In order to overcome this gap, this paper focuses on studying innovation in an effectual context and linking different innovation approaches to effectual logic. Indeed, effectuation is a way of thinking that serves entrepreneurs in the processes of opportunity identification and new venture creation. Effectuation includes a set of decision-making principles expert entrepreneurs are observed to employ in situations of uncertainty (as defined in Society for Effectual Action). This article outlines the four most-studied innovation approaches from the date of their apparitions until January 2021: frugal innovation, disruptive innovation, lean start-up, and design thinking. In this context, effectuation as the essence of innovation must be clarified as a method that has similarities and differences with frugal and disruptive innovation, lean start-up, and design thinking. To validate the proposed theorical model, a bibliometrics tool, named “Harzing publish” or “perish”, is used. The main finding of this research affirms that the two most linked innovation approaches to effectuation are “lean start-up” and “design thinking”, compared to “frugal innovation” and “disruptive innovation”. In an entrepreneurial innovation context, design thinking and lean start-up are flexible tools that can stimulate and validate the effectual cycle.
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Chen, Shu-Ping, Wen-Pin Chang, Bryan Fleet, Santoch Rai, Steve Panteluk, Alberto Choy, and DeAnn Hunter. "Is a Forensic Cohabitation Program Recovery-Oriented? A Logic Model Analysis." International Journal of Environmental Research and Public Health 19, no. 1 (December 21, 2021): 9. http://dx.doi.org/10.3390/ijerph19010009.
Анотація:
Background. Recovery orientation is a movement in mental health practice. Although general mental health services have taken the lead in promoting recovery, forensic psychiatric systems have lagged behind because of the need to reconcile recovery principles with the complexities of legal mandates. Advocating recovery and making systemic changes can be challenging because they require seeking a balance between the competing duties to the patient and the public. This paper used a logic model framework to demonstrate a cohabitation program that placed a woman and her newborn infant in a secure forensic rehabilitation unit, and analyzed the key assumptions of recovery upon which it was based. Methods. This was a qualitative program evaluation. Data collection involved individual interviews with the woman, the infant’s father, five primary healthcare providers, and five system administrators, and 11 focus groups with unit staff and other patients. Content analysis was used to guide the data analysis and develop the critical components of the program logic model. Results. A logic model that consists of input (team building, program planning, staff and patient preparation, resource management), output (logistic activities, risk management, mental healthcare, staff/other patient support, discharge preparation), and outcome (individual, provider, system, and society) components was developed. Conclusions. This study demonstrates a recovery-oriented program for a woman cohabitating with her baby in a secure forensic psychiatric rehabilitation unit. The logic model provided a comprehensive understanding of the way the recovery principles, such as shared decision-making, positive risk-taking, informed choices, and relational security, were implemented.
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Zulkifle, Haneef, Fadhilah Yusof, and Siti Rohani Mohd Nor. "Comparison of Lee Carter Model and Cairns, Blake and Dowd Model in Forecasting Malaysian Higher Age Mortality." MATEMATIKA 35, no. 4 (December 31, 2019): 65–77. http://dx.doi.org/10.11113/matematika.v35.n4.1264.
Анотація:
Demographers and actuaries are very much conscious of the trend of mortality in their own country or in the world in general. This is because mortality is the basis for longevity risk evaluation. Mortality is showing a declining trend and it is expected to further decline in the future. This will lead to continuous increase in life expectancy. Several stochastic models have been developed throughout the years to capture mortality and its variability. This includes Lee Carter (LC) model which has been extended by various researchers. This paper will be focusing on comparing LC model and another mortality model proposed by Cairns, Blake and Dowd (CBD). The LC uses the log of central rate of mortality and CBD uses logit of the mortality odds as dependent variable. Analysis of comparison is done using a few techniques including Akaike information criteria (AIC) and Bayesian information criterion (BIC). From the overall results, there is no model better than the other in every aspect tested. We illustrate this via visual inspection and in sample and outof sample analysis usingMalaysianmortality data from 1980 to 2017.