Data quality requirements analysis and modeling

Reprint. "1063-6382/93 $03.00 1993 IEEE."--P. 670. "April 1993."Includes bibliographical references (p. 676).Supported by the Productivity From Information Technology (PROFIT) Research Initiative at MIT.Richard Wang, Henry Kon, Stuart Madnick

Food Quality Standards in Equilibrium Models: A Discussion of Current Modeling Approaches

Throughout recent year food quality standards have become a ubiquitous phenomenon that nationally and globally influences agri-food markets. With equilibrium models commonly used in the quantitative analysis of market and trade effects, we review possible approaches to modeling standards existent in the literature, elaborate the reasoning behind them and discuss their suitability to reflect "real world" situations. While the modeling approaches identified may respectively depict a specific situation, they may not be appropriate in others. That is they capture certain effects of standards only. With increasing ability to account for the various effects of standards, the modeling approaches become more complex and the data requirements increase.food quality, standards, modeling approaches, equilibrium models, Food Consumption/Nutrition/Food Safety, F1, C6, Q18,

Pengaruh Kualitas Produk Kualitas Pelayanan Terhadap Kepuasan Konsumen Pada Home Industry Tempe Di Desa Putra Buyut Gunung Sugih Lampung Tengah

ABSTRAK Penelitian ini bertujuan untuk menganalisis pengaruh kualitas produk, kualitas pelayanan terhadap kepuasan konsumen. Dalam penelitian ini menggunakan data primer yang dikumpulkan dengan metode explanatory survey dan teknik pengambilan sampel berupa accidental sampling terhadap 80 orang responden menggunakan kuesioner dengan skala likert. Pengujian persyaratan instrumen yang digunakan meliputi uji validitas dan uji reliabilitas. Uji normalitas, uji homogenitas, uji linieritas dan keberartian regresi sebagai pengujian persyaratan analisis SEM (Structural Equation Modeling), dan teknik analisis data yang digunakan adalah analisis SEM (Structural Equation Modeling). Berdasarkan hasil penelitian dengan menggunakan analisis SEM (Structural Equation Modeling) diperoleh kualitas produk berpengaruh terhadap kualitas pelayanan, kualitas produk berpengaruh terhadap kepuasan konsumen, dan kualitas pelayanan berpengaruh terhadap kepuasan konsumen. Kata kunci :Kualitas Produk, Kualitas Pelayanan, Kepuasan Konsumen.   ABSTRACT Yuda Fernanda. 2021. “The Influence Of Product Quality Service Quality On Consumer Satisfaction at Home IndustryTempe Putra Buyut Gunung Sugih Lampung Tengah for Management Study Program, Faculty of Economics and Business, Muhammadiyah Metro University. Supervisor (I) Dr. Suharto, S. E., M.M. Supervisor (II) Fitriani S. E., M.M. This study aims to analyze the effect of product quality service quality on costumer satisfaction. In this study using primary data collected by explanatory survey methods and sampling techniques in the form of accidental sampling of 80 respondents using a questionnaire with a Likert scale. Testing the instrument requirements used include validity and reliability testing. Normality test, homogeneity test, linearity test and significance of regression as testing requirements for SEM (Structural Equation Modeling) analysis, and data analysis techniques used are SEM (Structural Equation Modeling) analysis. Based on research results using SEM (Structural Equation Modeling) analysis, product quality haan effect on service quality. Product quality affects customer satisfaction, and service quality affects customer satisfaction. Keywords: Product Quality, Service Quality, Customer satisfactio

NTP comparison process

The systems engineering process for the concept definition phase of the program involves requirements definition, system definition, and consistent concept definition. The requirements definition process involves obtaining a complete understanding of the system requirements based on customer needs, mission scenarios, and nuclear thermal propulsion (NTP) operating characteristics. A system functional analysis is performed to provide a comprehensive traceability and verification of top-level requirements down to detailed system specifications and provides significant insight into the measures of system effectiveness to be utilized in system evaluation. The second key element in the process is the definition of system concepts to meet the requirements. This part of the process involves engine system and reactor contractor teams to develop alternative NTP system concepts that can be evaluated against specific attributes, as well as a reference configuration against which to compare system benefits and merits. Quality function deployment (QFD), as an excellent tool within Total Quality Management (TQM) techniques, can provide the required structure and provide a link to the voice of the customer in establishing critical system qualities and their relationships. The third element of the process is the consistent performance comparison. The comparison process involves validating developed concept data and quantifying system merits through analysis, computer modeling, simulation, and rapid prototyping of the proposed high risk NTP subsystems. The maximum amount possible of quantitative data will be developed and/or validated to be utilized in the QFD evaluation matrix. If upon evaluation of a new concept or its associated subsystems determine to have substantial merit, those features will be incorporated into the reference configuration for subsequent system definition and comparison efforts

Styles in business process modeling: an exploration and a model

© 2013, The Author(s).Business process models are an important means to design, analyze, implement, and control business processes. As with every type of conceptual model, a business process model has to meet certain syntactic, semantic, and pragmatic quality requirements to be of value. For many years, such quality aspects were investigated by centering on the properties of the model artifact itself. Only recently, the process of model creation is considered as a factor that influences the resulting model’s quality. Our work contributes to this stream of research and presents an explorative analysis of the process of process modeling (PPM). We report on two large-scale modeling sessions involving 115 students. In these sessions, the act of model creation, i.e., the PPM, was automatically recorded. We conducted a cluster analysis on this data and identified three distinct styles of modeling. Further, we investigated how both task- and modeler-specific factors influence particular aspects of those modeling styles. Based thereupon, we propose a model that captures our insights. It lays the foundations for future research that may unveil how high-quality process models can be established through better modeling support and modeling instruction

Applying model-based systems engineering in search of quality by design

2022 Spring.Includes bibliographical references.Model-Based System Engineering (MBSE) and Model-Based Engineering (MBE) techniques have been successfully introduced into the design process of many different types of systems. The application of these techniques can be reflected in the modeling of requirements, functions, behavior, and many other aspects. The modeled design provides a digital representation of a system and the supporting development data architecture and functional requirements associated with that architecture through modeling system aspects. Various levels of the system and the corresponding data architecture fidelity can be represented within MBSE environment tools. Typically, the level of fidelity is driven by crucial systems engineering constraints such as cost, schedule, performance, and quality. Systems engineering uses many methods to develop system and data architecture to provide a representative system that meets costs within schedule with sufficient quality while maintaining the customer performance needs. The most complex and elusive constraints on systems engineering are defining system requirements focusing on quality, given a certain set of system level requirements, which is the likelihood that those requirements will be correctly and accurately found in the final system design. The focus of this research will investigate specifically the Department of Defense Architecture Framework (DoDAF) in use today to establish and then assess the relationship between the system, data architecture, and requirements in terms of Quality By Design (QbD). QbD was first coined in 1992, Quality by Design: The New Steps for Planning Quality into Goods and Services [1]. This research investigates and proposes a means to: contextualize high-level quality terms within the MBSE functional area, provide an outline for a conceptual but functional quality framework as it pertains to the MBSE DoDAF, provides tailored quality metrics with improved definitions, and then tests this improved quality framework by assessing two corresponding case studies analysis evaluations within the MBSE functional area to interrogate model architectures and assess quality of system design. Developed in the early 2000s, the Department of Defense Architecture Framework (DoDAF) is still in use today, and its system description methodologies continue to impact subsequent system description approaches [2]. Two case studies were analyzed to show proposed QbD evaluation to analyze DoDAF CONOP architecture quality. The first case study addresses the analysis of DoDAF CONOP of the National Aeronautics and Space Administration (NASA) Joint Polar Satellite System (JPSS) ground system for National Oceanic and Atmospheric Administration (NOAA) satellite system with particular focus on the Stored Mission Data (SMD) mission thread. The second case study addresses the analysis of DoDAF CONOP of the Search and Rescue (SAR) navel rescue operation network System of Systems (SoS) with particular focus on the Command and Control signaling mission thread. The case studies help to demonstrate a new DoDAF Quality Conceptual Framework (DQCF) as a means to investigate quality of DoDAF architecture in depth to include the application of DoDAF standard, the UML/SysML standards, requirement architecture instantiation, as well as modularity to understand architecture reusability and complexity. By providing a renewed focus on a quality-based systems engineering process when applying the DoDAF, improved trust in the system and data architecture of the completed models can be achieved. The results of the case study analyses reveal how a quality-focused systems engineering process can be used during development to provide a product design that better meets the customer's intent and ultimately provides the potential for the best quality product

A Data Annotation Process for Human Activity Recognition in Public Places

Behavior analysis of individuals in crowds or groups of people in public places through surveillance cameras gains importance for several different actors. Automatically detecting and understanding pedestrians in real-world uncooperative scenarios is very challenging. Common issues such as limited annotated data, unreliable data and annotation quality, and appropriate use of this data for supervised learning often originate in steps preceding the modeling of specialized neural network architectures. In this report, the necessity and requirements for designing a reliable data annotation process are presented. Some precise ideas for automation through neural networks are discussed in a conceptual manner

Emission inventories and modeling requirements for the development of air quality plans. Application to Madrid (Spain)

Modeling is an essential tool for the development of atmospheric emission abatement measures and air quality plans. Most often these plans are related to urban environments with high emission density and population exposure. However, air quality modeling in urban areas is a rather challenging task. As environmental standards become more stringent (e.g. European Directive 2008/50/EC), more reliable and sophisticated modeling tools are needed to simulate measures and plans that may effectively tackle air quality exceedances, common in large urban areas across Europe, particularly for NO2. This also implies that emission inventories must satisfy a number of conditions such as consistency across the spatial scales involved in the analysis, consistency with the emission inventories used for regulatory purposes and versatility to match the requirements of different air quality and emission projection models. This study reports the modeling activities carried out in Madrid (Spain) highlighting the atmospheric emission inventory development and preparation as an illustrative example of the combination of models and data needed to develop a consistent air quality plan at urban level. These included a series of source apportionment studies to define contributions from the international, national, regional and local sources in order to understand to what extent local authorities can enforce meaningful abatement measures. Moreover, source apportionment studies were conducted in order to define contributions from different sectors and to understand the maximum feasible air quality improvement that can be achieved by reducing emissions from those sectors, thus targeting emission reduction policies to the most relevant activities. Finally, an emission scenario reflecting the effect of such policies was developed and the associated air quality was modeled