Product Model Research Articles

Model Pengembangan Zakat Produktif Studi Komparatif di Indonesia dan Brunei Darussalam

This research examines the productive zakat development model in Indonesia and Brunei Darussalam through a comparative approach. Productive zakat is an effort to utilize zakat funds to improve the economic welfare of mustahik in a sustainable manner. In Indonesia, zakat is regulated by Law no. 23 of 2011 and managed by the National Amil Zakat Agency (BAZNAS) and various Amil Zakat Institutions (LAZ). Meanwhile, in Brunei Darussalam, zakat is managed by the Brunei Islamic Religious Council (MUIB) based on sharia law. This study found that the two countries have different approaches but both focus on empowering the mustahik economy through programs such as providing business capital, skills training and assistance with production equipment. Indonesia shows diversity in program implementation with extensive collaboration between various institutions, while Brunei Darussalam utilizes full government support for more focused and effective program implementation. Challenges facing Indonesia include unequal distribution and weak supervision, while Brunei faces challenges in economic diversification. However, both countries have great opportunities to increase the effectiveness of productive zakat programs through technological innovation and closer collaboration between the public and private sectors. This study provides insight into best practices and lessons that can be drawn from each country to improve the welfare of mustahik in a sustainable manner. The conclusion of this research emphasizes the importance of strengthening the legal and institutional framework, as well as increasing transparency and accountability in the management of productive zakat.

Eye Tracking and Semantic Evaluation for Ceramic Teapot Product Modeling

In addition to their practical and aesthetic qualities, ceramic teapots are highly decorative and stylish. Based on the theory of perceptual engineering, this study employs eye-tracking technology and semantic-difference methods to investigate user preferences for ceramic teapot shapes. Using eye-movement experiments, the study first determines users’ visual attention to different morphological regions. Using the orthogonal alignment method, nine styling samples were developed by combining expert classification of classic and traditional teapot styling elements. By combining a semantic perception questionnaire with a satisfaction questionnaire, the study evaluated users’ visual attention to these samples and their satisfaction with them. It was found that shapes characterized by classic, rounded, and proportional coordination were more in line with consumers’ aesthetic preferences despite the differences in semantic evaluations among consumers of different genders and ages, which led to relatively consistent consumer satisfaction. The purpose of this study is not only to provide a scientific basis for styling ceramic teapots but also to assist designers in grasping the laws of consumer preference in order to create better products.

Design optimization of vibration amplitude reduction based on virtual prototype and machine learning

The traditional design optimization of vibration amplitude reduction mainly has the disadvantages of low modeling and prediction accuracy as well as low optimization efficiency. Therefore, this paper presents a design optimization method for vibration amplitude reduction based on virtual prototyping and machine learning, which combines the high accuracy of numerical calculations with the efficiency of machine learning, overcoming the shortcomings of traditional methods. Firstly, sample points are collected through the design of experiments and virtual prototype simulation. Then, based on the sampled data, a prediction model for the relationship between the design parameters and the amplitude of the product is established using Genetic Algorithm-Support Vector Regression (GA-SVR). On the basis of the GA-SVR prediction model, a multi-objective optimization model of product is established, and Multiple Objectives Particle Swarm Optimization -entropy weight- Technique for Order Preference by Similarity to Ideal Solution (MOPSO-entropy weight-TOPSIS) is used to solve for the optimal design parameters. Finally, the washing machine suspension system is used as an example to verify the effectiveness of the model. The results show that, compared with the original design scheme, the design scheme obtained by the model can reduce the amplitude of the washing machine suspension system by 12.68%, and reduce the total weight of the counterweight by 7.35%. This method is conducive to the intelligent and efficient design optimization of vibration amplitude reduction, and is of great significance to product life cycle design.

Industrial Sufficiency: A Conceptual Methodological Framework

Implementing sustainability strategies is essential for the future viability of companies. While companies have been focusing intensively on the operationalization of efficiency and consistency for quite some time, sufficiency approaches are rare. As a result, there is a lack of fundamental understanding of the concept, its inherent potential, as well as a lack of basic implementation concepts for strategies, management systems, and product and process development. Based on a literature review using Scopus and Web of Science according to the PRISMA approach, this paper develops a definition for the concept of industrial sufficiency and presents three general industrial sufficiency strategies (frugality, longevity, and specificity) regarding three distinct business determinants (product, production, and business model). The investigation shows that not only can there be overlaps between the three general sustainability strategies (efficiency, consistency, and sufficiency) but that individual measures are also mutually dependent at different levels. In addition, significant conflicts of objectives for implementation in industrial practice are revealed.

Identification of feature selection techniques for software defect prediction by using BCF-WASPAS methodology based on Einstein operators

PurposeThis research focuses on a very important research question of determining the appropriate feature selection methods for software defect prediction. The study is centered on the creation of a new method that would enable the identification of both positive and negative selection criteria and the handling of ambiguous information in the decision-making process.Design/methodology/approachTo do so, we develop an improved method by extending the WASPAS assessment in the context of bipolar complex fuzzy sets, which leads to the bipolar complex fuzzy WASPAS method. The approach also uses Einstein operators to increase the accuracy of aggregation and manage complicated decision-making parameters. The methodology is designed for the processing of multi-criteria decision-making problems where criteria have positive and negative polarities as well as other ambiguous information.FindingsIt is also shown that the proposed methodology outperforms the traditional weighted sum or product models when assessing feature selection methods. The incorporation of bipolar complex fuzzy sets with WASPAS improves the assessment of selection criteria by taking into account both positive and negative aspects of the criteria, which contributes to more accurate feature selection for software defect prediction. We investigate a case study related to the identification of feature selection techniques for software defect prediction by using the bipolar complex fuzzy WASPAS methodology. We compare the proposed methodology with certain prevailing ones to reveal the supremacy and the requirements of the proposed theory.Originality/valueThis research offers the first integrated framework for handling bipolarity and uncertainty in feature selection for software defect prediction. The combination of Einstein operators with bipolar complex fuzzy sets improves the DM process, which will be useful for software engineers and help them select the best feature selection techniques. This work also helps to enhance the overall performance of software defect prediction systems.

Investigation on the Effect of Water Quenching to Microstructure, Crystal Structure, Hardness, and Wear of Gray Iron

Gray cast iron has been one of the most widely used engineering materials since a long time ago. However, the development of casting techniques and methods to produce various models of cast iron products for the domestic market is not followed by improvements in product quality. The intriguing aspect of gray iron products is the diverse morphologies that graphite can assume, leading to distinct variations in mechanical and physical properties. Quenching is a typical heat treatment procedure performed to improve the mechanical properties of a material that entails the rapid cooling of the material from a high temperature to a low temperature. The aim of this study is to investigate the effect of water quenching effects on microstructure, crystal structure, hardness, and wear of gray iron, which undergoes quenching from the austenitizing temperature. Gray cast iron was obtained from the local foundry industry, then thermally treated at 900°C, held for 15 minutes, and rapidly quenched by water. The quenching procedure induces a significant alteration in the overall microstructure, where transition of most dendrite arms to the eutectic phase microstructure is observed. Moreover, the quenching process is attributed to the reduction of crystal size and growth of carbon crystal. The average crystal size of the sample was reduced from 47.833 nm to 17.97 nm, hence improving the hardness from 16.375 HRC to 48.04 HRC, which in turn improved wear resistance under high loading condition from 0.014 g/sec to 0.00042 g/sec.

Integrating Symmetry in Attribute-Based Sentiment Modeling with Enhanced Hesitant Fuzzy Scoring for Personalized Online Product Recommendations

Online product reviews provide valuable insights on user experiences and product qualities. However, issues such as information overload and the limited utilization of review features persist, particularly in personalized rankings for popular items like movies. To address these challenges—information overload in online reviews, limited review feature utilization, and personalized decision-making for high-demand products like movies—we introduce a personalized online decision-making framework that integrates a sentiment model for product attributes with an enhanced hesitant fuzzy scoring function. This framework incorporates the concept of symmetry in sentiment analysis. It employs feature words, sentiment terms, and modifiers to assess user sentiments within a hesitant fuzzy setting, utilizing symmetrical relationships between positive and negative sentiments. The improved fuzzy score function efficiently quantifies sentiment values for product features by considering the symmetrical balance of user opinions. Additionally, review quality assessment incorporates both content and reviewer characteristics, resulting in final attribute evaluations. An attribute weighting system, tailored to diverse product types, further captures product specifics and user inclinations, leveraging symmetry to balance varying user preferences. Validation through multi-genre movie sorting demonstrates the method’s capacity to handle review data across varied products and user tastes, offering a robust tool for enhancing online decision quality, especially for high-demand items.

FUZZY PRODUCTION MODEL WITH FUZZY VALUED DEMAND WITH NONLINEAR SELLING PRICE, WARRANTY, AND LEVEL OF GREENNESS OF THE PRODUCT UNDER FUZZY DETERMINATION RATE

Many studies on manufacturing and inventory management for increasingly problematic commodities have focused on how quality, greenness, product warranties, and environmental concerns might be incorporated into industrial operations. However, comparatively few articles have integrated these two themes. To close this knowledge gap and advance practice, these two decaying object criteria must be included in the study. The following assumptions are used to create a warranty-based, sustainable production inventory model for green products. In this article, we look at how greenness, product assurances, and reducing carbon emissions technologies impact overall profit to assist those making decisions to make better choices regarding pricing and replenishment. Due to the consideration of fuzzy valued inventory parameters along with the objective function's nonlinearity and the presence of five decision variables, we have addressed this problem with the help of the Lingo 18 software along with the defuzzification technique. The mathematical formula is quantitatively demonstrated in one experiment, and a sensitivity analysis is performed to determine the effects of various factors on overall profit and management insights.

Development of a fully integrated hydrological fate and transport model for plant protection products: incorporating groundwater, tile drainage, and runoff

IntroductionPlant protection products (PPPs) such as pesticides and herbicides are experiencing increased use worldwide. In the context of PPP authorization and registration, water exposure assessments (drinking water and aquatic exposure) use numerical modeling to simulate relevant hydrological processes and exposure pathways. A common practice for estimating PPP leaching to groundwater, PPP loading onto surface water via tile drainage, or PPP transport via runoff utilizes multiple one-dimensional models, each representing a separate exposure pathway. Separate analysis of individual exposure pathways can result in disparate assumptions being made that represent relative worst-case scenarios for each pathway, rather than an integrated reasonable worst-case scenario for all pathways.MethodsThe interplay between PPP degradation, leaching to groundwater, transport in tile drainage, and runoff is well-suited for simulation using an integrated surface–subsurface hydrologic and chemical fate and transport model. This study presents functionality added to HydroGeoSphere (HGS), a three-dimensional, fully integrated, surface–subsurface hydrologic model. HGS was verified against other recognized models: PRZM, HYDRUS, PEARL, PELMO, and MACRO. Added features include automatic irrigation, non-linear adsorption, temperature and soil water content-dependent degradation, and solute uptake by plant roots.Results and DiscussionHGS results for leaching of PPP mass to groundwater showed the highest correlation, lowest error, and lowest bias relative to PEARL model results. Simulation of macropore flow to tile drains in HGS produced an intermittent tile drain flow in summer that resulted in generally lower peak effluent concentrations compared to the MACRO model. Simulation of runoff in HGS produced a higher total runoff compared to the PRZM model, attributed to lower evapotranspiration in HGS. Use of the integrated HGS model resulted in a greater agreement in water balance components relative to using multiple models to simulate individual hydrologic pathways.

Agroforestry Systems: A Pathway to Resilient and Productive Landscapes

Agroforestry, the integration of trees, crops, and livestock on the same land, offers a sustainable approach to enhancing agricultural productivity while mitigating environmental challenges. This review highlights the important role agroforestry systems play in promoting resilient and productive landscapes, particularly in the face of climate change, land degradation, and biodiversity loss. Agroforestry systems, including alley cropping, silvopasture, and home gardens, provide significant ecological benefits such as carbon sequestration, reduced greenhouse gas emissions, improved soil health, water conservation, and enhanced biodiversity. These systems not only stabilize microclimates and reduce soil erosion but also improve soil fertility and water infiltration, making them vital for climate adaptation. Socio-economically, agroforestry diversifies income sources for smallholder farmers by generating products like timber, fruits, and fodder, while contributing to food security through year-round crop availability and improved nutrition. Despite these benefits, the adoption of agroforestry faces substantial barriers, including socio-cultural resistance, knowledge gaps, inadequate policy support, and limited access to markets and credit. High initial costs, perceived risks, and competition for resources between trees and crops further impede its widespread implementation. Addressing these challenges requires enhancing extension services, policy reforms, financial incentives, and market access to support smallholder farmers. Future directions emphasize integrating agroforestry into national agricultural policies and climate action plans, supported by research on optimizing species selection, pest management, and sustainable resource use. By the synergies between agroforestry, regenerative agriculture, and Sustainable Development Goals, agroforestry presents a viable pathway for transforming agricultural systems into more resilient, productive, and sustainable models. Scaling up agroforestry can help restore degraded lands, sequester carbon, and enhance the livelihoods of rural communities, contributing to global efforts to combat climate change and promote sustainable development.

Exploring the Relationship Between Upper Ocean States and the Falling Ice Radiative Effects using ECCO Product and Global Climate Models

Abstract This study seeks to explore the relationship between upper ocean current (UOC) anomalies (above 200 meters) and surface wind stress (TAU), focusing on the influence of falling ice (snow) radiative effects (FIREs) over the tropical and subtropical Pacific regions. To achieve this, we conducted sensitivity experiments with the CESM1-CAM5 model, using the Coupled Model Intercomparison Project phase 5 (CMIP5) historical run setting, with FIREs turned off (NOS) and on (SON). The monthly ocean current and temperature of the ocean reanalysis from the NASA Estimating the Circulation and Climate of the Ocean (ECCO) project, which assimilates satellite and in situ measurements, serve as a reference for this study. The spatial patterns of the horizontal UOC anomaly (UOCA) differences between the NOS and SON experiments show a strong correlation with the TAU patterns across the studied domain. When compared to the experiments with NOS, the experiments with SON demonstrate an improvement in the annual mean UOC. The improvement in UOC can be attributed to the enhancements in TAU, specifically in the trade-wind regions. The enhancements in TAU play a significant role in influencing the UOCA patterns and contribute to the overall improvement observed in the experiments with SON. In SON, the average absolute bias of simulated UOCA over the study area is reduced by up to 30% compared to NOS against ECCO. 
Although biases in UOC are present over the southern and northern flanks of the equator in SON, the improvements in annual mean ocean currents are closely related to enhancements in TAU driven by the inclusion of FIREs. Notably, stronger ocean current magnitudes correspond to more significant changes in TAU due to Coriolis forces. When evaluating the ensemble mean absolute biases of UOC from the CMIP5 models, similarities to NOS, however, are limited over the South Pacific region.

COLOR VISUALIZATION OF 3D-MODELS FOR ENHANCED PREPARATION OF ADDITIVE MANUFACTURING PROCESSES

The main aspects of color visualization of triangulated models of industrial products are presented. The implementation of visualization capabilities is based on RGB and HSV color models. The structure and key features of the software implementation of color visualization and the export of the displayed image in PLY, and AMF formats are discussed. Methods for transformations between RGB and HSV color models are described, as well as an algorithm for coloring the triangular faces of the model based on specified color ranges. The developed algorithms allow for a sufficiently informative representation of the desired areas of the product's surfaces by significantly altering one color component while minimally changing the other two. This is achieved by directing the assignment of functional dependencies and value ranges for each component of the color model. Examples of various methods for color shading of vertices and/or edges and/or faces of the model are provided. The visualization subsystem enables the analysis of the geometric characteristics of the polygonal model during the preparation phase of additive manufacturing processes. Significant advantages of these approaches to color visualization are evident when adapting the product design to technological requirements (design preparation) and when solving optimization tasks in technological preparation. The developed software is integrated into the technological preparation system for manufacturing enterprises in the machine engineering sector. This research was developed at the Department of "Integrated Technologies of Mechanical Engineering" named after M. Semko of NTU "KhPI".

Development of a Methodology for Obtaining Solid Models of Products That Are Objects of Reverse Engineering Using the Example of the Capstone Micro-GTU C 65

Currently, about a thousand micro gas turbine units of small and medium capacity are in operation in the Russian Federation, which are used as an autonomous power source at critical infrastructure facilities. During long-term operation, the component parts of the micro GTU may fail and require replacement or repair. The lack of spare parts and design documentation for their production makes it impossible to operate. As a way to solve the problem, the reverse engineering process can be used to produce components. One of the stages of reverse engineering is to determine the geometric parameters of the object. The fastest and most accurate way to obtain geometric characteristics in the reverse engineering process is 3D scanning. Three-dimensional scanning technology is used to obtain a solid 3D model of the prototype surface, based on which design documentation is subsequently developed. This article presents the results of a study of the influence of the parameters of the distance between polygonal grid points and the scanner exposure on the detailing of the outer surface and the geometric parameters of the resulting polygonal model. As a result of this study, the dependence of the final file size and the time spent on scanning and processing on the distance between the points of the polygonal grid and the model was established. Based on the dependence of the parameters, recommendations were obtained for choosing the distance between the points of the polygonal grid of laser 3D scanning. Also, after performing the stages of reverse engineering, the methodology for creating solid models and design documentation of parts of power equipment units using 3D scanning technology was improved.

Polymer Concretes Based on Various Resins: Modern Research and Modeling of Mechanical Properties

This review is devoted to experimental studies and modeling in the field of mechanical and physical properties of polymer concretes and polymer-modified concretes. The review analyzes studies carried out over the past two years. The paper examines the properties of polymer concretes based on various polymer resins and presents the advantages and disadvantages of various models developed to predict the mechanical properties of materials. Based on data in the literature, the most promising polymers for use in the field of road surface repair are polymer concretes with poly(meth)acrylic resins. It was found that the most adequate and productive models are the deep machine learning model—using several hidden layers that perform calculations based on input parameters—and the extreme gradient boosting model. In particular, the extreme gradient boosting model showed high R2 values in forecasting (in the range of 0.916–0.981) when predicting damping coefficient and ultimate compressive strength. In turn, among the additives to Portland cement concrete, the most promising are natural polymers, such as mammalian gelatin and cold fish gelatin, and superabsorbent polymers. These additives allow for an improvement in compressive strength of 200% or more. The review may be of interest to engineers specializing in building construction, materials scientists involved in the development and implementation of new materials into production, as well as researchers in the interdisciplinary fields of chemistry and technology.

A Geography of Agrarian Structures in Argentina: Productive Models, Socioenvironmental Impacts and Neodevelopmentalism

En 2022, la Unión de Trabajadores de laTierra propuso por cuarta vez al Congreso argentino su Ley de Acceso a la Tierra. Esta propuesta siguió a la publicación de los resultados del censo agropecuario de 2018, publicado en 2021, que fue el primer censo agropecuario válido desde 2002. En este artículo, comparamos los resultados del censo de 2018 con los de 2002 a través de dos temas distintos: a) la concentración y distribución de la tierra; y b) los cultivos y la aplicación de agroquímicos. Encontramos que los productores de pequeña escala han disminuido drásticamente tanto en unidades como en hectáreas de cobertura en los últimos veinte años, debido principalmente a la expansión de los monocultivos, que forman parte de un modelo de agricultura que se caracteriza por una aplicación intensificada de agroquímicos y el cultivo de organismos genéticamente modificados. Aunque los gobiernos posneoliberales enfatizan la importancia de los pequeños agricultores, han impulsado en vez de detenido la expansión de los agronegocios a costa de la agricultura de pequeña escala.

Estimation of the Reaction Rate in Models of Processes and Products

Estimation of the Reaction Rate in Models of Processes and Products

PT19 Emerging Trends in the Adoption of Alternative Financing Models for Advanced Therapy Medicinal Products: A Scoping Review

PT19 Emerging Trends in the Adoption of Alternative Financing Models for Advanced Therapy Medicinal Products: A Scoping Review

Optimal Warranty Period Design for New Products Subject to Degradation and Environmental Shocks Considering Imperfect Maintenance

For new products, manufacturers usually aim to set a reasonable warranty period before market launch to maximize future profits. However, the lack of historical warranty claim records makes it challenging to optimize the warranty period effectively. This paper proposes a new framework to optimize the warranty period for new products based on laboratory data, considering degradation-shock competing failures and imperfect maintenance. First, a degradation-shock competing failure model for the new products is established based on laboratory accelerated degradation data. Next, the impact of imperfect maintenance on warranty costs is quantified using the maintenance improvement factor model. Then, an optimization model for the warranty period is established with the aim of maximizing the manufacturer's profit. Finally, a case study is carried out to verify the validity and applicability of the proposed model. The numerical results clearly indicate that the frequency and magnitude of shock failures significantly impact the optimal warranty period for the product. Moreover, as the mean value of the imperfect maintenance factor increases from 0.5 to 0.9, the optimal warranty period first rises from 6.49 to 7.79, then drops to 7.42, which means strategically relaxing maintenance requirements can lead to higher profit margins for manufacturers.

Identification Risks in Road Construction Projects Using Weighted Product Model: Iraq as a Case Study

One of the challenges that developing countries is the necessity to properly manage the risks involved in road construction projects. For that, the present work developed a dissension method to specify effective risk factors in a wide range of approaches and protocols to achieve its objectives. The Influence of Risk Road Implementation on Performance Indicators The initial sets of outcomes were derived from computing the average risk estimate. Subsequently, the second results group was established by assessing the relative importance index (RII) effects. In the RII method and mean results the workers and machinery insurance is the most important. The identical data that had been collected from the weighted product model (WPM) methodology ultimately determined that the essential resources such as staff and equipment must be accessible through all stages of activity. In road construction, machines represent a major effective factor that can help to project success with a rank of 0.868. Also, the worker conditions and skills represent another strategy in projects with 0.547 rank. The weighted product model results yelled a more accurate and practical output.

A143: Integrating Stakeholder Theory and SWOT Analysis to Examine COVID-19 Outbreak Impact on Fitness Programs

Background/Purpose: The fitness industry has been an important segment in the sports-related global market (SFIA, 2020). The U.S. Bureau of Labor Statistics Occupations Projection (2016-2026) indicated there would be an 18.70% annual occupational employment percentage increase in the need for athletic trainers (CareerOneStop, 2019). The U.S. 71394 Gym, Health & Fitness Clubs Report revealed a 1%–6% revenue increase each year since 2012. This projection indicated that the fitness market uptrend would continue in the next decade. However, the COVID-19 outbreak had a significant impact on the fitness market, and it was projected to have a 10% revenue decline in 2020 (IBISWorld, 2020). This study examined the challenges that fitness programs faced during the COVID-19 pandemic. Marketing strategies and fitness program redesigns were proposed. Methods: This case study’s subjects were the fitness programs. Stakeholder Theory was employed as it concerns participants serving as its primary stakeholders. Supplementing with SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis, strengths and weaknesses identified internal factors that directly and indirectly affect fitness programs’ operation during the COVID-19 pandemic, while opportunities and threats examined the external factors. Results: Based on SWOT analysis, internal strengths that impact fitness programs’ operations were: 1) Fitness training could still be operated via an online format and keep participants safely and actively engaged during the crisis; 2) Online training can be globally distributed with no charge via its application platform; 3) Recorded and standardized daily training can be done at any time without limits. Weaknesses were: 1) Limited exercises available and no trainers’ in-person interaction to demonstrate and correct participants’ exercises; 2) Technology application and internet requirements may opt out participants who may not favor technology or have access to the internet. External opportunities were: 1) During a crisis like COVID-19, health-oriented outcomes were of great need; 2) The service-oriented business model would win out over the tangible products model due to the major economic and social impact. Threats were: 1) Online application consumption has not been a major trend like studio membership purchases; 2) COVID-19 lockdown led to significant financial impact and emotional disorders for fitness participants; 3) More interruptions from family routines would affect people’s fitness participation. Conclusions: To survive in a global pandemic such as COVID-19, fitness programs need to consider shifting traditional studio membership sales to technology-assisted services purchases in order to boost their revenues. Collaboration with local community health care providers to facilitate real-time interaction and post-family training activities would further strengthen fitness programs’ involvement and the primary stakeholders’ attachment.