Wyniki wyszukiwania - BazTech

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Exploring key quality indicators (KQIS) in green office buildings through Pareto analysis

Halicioglu Fahriye Hilal, Demirkapi Hande Betul, Gurel Kubra, Kasul Nurdan

Architecture Civil Engineering Environment

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2023

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Vol. 16, no. 2

15--27

EN

Ensuring higher user satisfaction while reducing building energy consumption is one of the challenges faced by the green building industry since quality comes into view at the level of responding to the environmental and sustainable expectations, health, and comfort needs of green building users. The main objective of this study is to explore the quality indicators in green office buildings. It attempts to answer the question: What are the key quality indicators in evaluating user satisfaction during the operational stage of green office buildings? To that end, a systematic case study review and Pareto analysis are used as a methodological approach. Firstly, a literature review was conducted to determine the quality indicators. Following that, the Pareto analysis was used to find key quality indicators in the literature dataset according to their occurrence frequencies. Finally, the study identified a total of 37 quality indicators and concluded by presenting 23 key quality indicators (kQIs) affecting satisfaction in green office buildings. This study draws attention to the fact that user-oriented quality improvement by getting feedback from the user experiences is inevitable for achieving sustainability goals in green office buildings. It contributes to understanding quality indicators for assessing and enhancing user satisfaction in green office buildings and fills the knowledge gap in the quality improvement of green office buildings.

2

Preferences of modern mobile app users

Kasztelan Kamil, Smołka Jakub

Journal of Computer Sciences Institute

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2022

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Vol. 23

71--76

PL

Celem artykułu jest ocena przydatności funkcji aplikacji mobilnych według preferencji współczesnych użytkowników. Każda grupa odbiorców posiada swoje preferencje, co do aplikacji mobilnych. Przeprowadzono ankietę w powiecie włodawskim w pierwszym kwartale 2020 roku. Wzięło w niej udział 150 przypadkowych osób. Zauważono że życie z urządzeniem mobilnym w ręku stało się już przyzwyczajeniem. Najbardziej popularną grupą aplikacji, jaką wybierają badani są aplikacje społecznościowe. Użytkownicy chętniej i częściej korzystają z pomocy urządzeń mobilnych podczas zakupów, szukając informacji o produkcie i promocjach. Zaobserwowano, że badani zwracają szczególną uwagę na zabezpieczenia aplikacji, chcą więc mieć pewność, że ich dane są bezpieczne. Mała grupa osób jest gotowa zrezygnować z urządzenia mobilnego i zacząć korzystać z tradycyjnych metod.

EN

Each user group has its own preferences for mobile applications. A better app will increase the satisfaction of existing users and encourage new people to download it. People are used to it that it's hard to get rid of them. A survey was conducted in the Włodawa district in the first quarter of 2020, in which 150 random people took part. It has been noticed that life with a mobile device in hand has become a habit. Users more willingly and more often use the help of mobile devices during shopping while looking for product information and promotions. It has been observed that users pay more attention to application security, wanting to be sure that their data is safe. A small group of people would give up their mobile device and start using traditional methods

3

Evaluation of Reliability of Mobile ICT Services

Kowalewski Marian, Kobus Ryszard, Sędek Tomasz

Journal of Telecommunications and Information Technology

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2021

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nr 1

37--42

EN

This article discusses common problems with reliability and availability of ICT services, mainly in mobile networks. Internet access-related services have been examined and traditional service quality assessment methods have been compared with the proposed solutions, with the primary focus placed on availability and reliability of mobile services. The required parameter values describing reliability and quality levels have been defined and proposed.

4

Predicting Aggregated User Satisfaction in Software Projects

Radliński Ł.

Foundations of Computing and Decision Sciences

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2018

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Vol. 43, No. 4

335--357

EN

User satisfaction is an important feature of software quality. However, it was rarely studied in software engineering literature. By enhancing earlier research this paper focuses on predicting user satisfaction with machine learning techniques using software development data from an extended ISBSG dataset. This study involved building, evaluating and comparing a total of 15,600 prediction schemes. Each scheme consists of a different combination of its components: manual feature preselection, handling missing values, outlier elimination, value normalization, automated feature selection, and a classifier. The research procedure involved a 10-fold cross-validation and separate testing, both repeated 10 times, to train and to evaluate each prediction scheme. Achieved level of accuracy for best performing schemes expressed by Matthews correlation coefficient was about 0.5 in the cross-validation and about 0.5–0.6 in the testing stage. The study identified the most accurate settings for components of prediction schemes.

5

Preliminary evaluation of schemes for predicting use satisfaction with the ability of system to meet stated objectives

Radliński Ł.

Journal of Theoretical and Applied Computer Science

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2015

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Vol. 9, nr 2

32--50

EN

In software engineering literature two most commonly investigated targets for prediction are development effort and software quality. This study follows the methodological advances of these studies but focuses on predicting user satisfaction in software project. Specific outcome variable investigated in prediction is user satisfaction with the ability of system to meet stated objectives (MSO). A total number of 288 prediction schemes have been evaluated in the ability to predict MSO. These schemes have been built as different combinations of their components, i.e. feature pre-selection, elimination of missing values, automated feature selection, and a classifier. Two best performing schemes achieved the accuracy measured as Matthews correlation coefficient of 0.71 in test subset. These schemes involved W-LMT and W-SimpleLogistic classifiers. Significant differences have been observed between different classifiers and selected other components, depending on the dataset (validation or test). Discussed results may serve as guidelines to design a scheme to predict user satisfaction.