Effect of Water pH on Domestic Machine Washing Performance of Delicate Textiles

Abstract In order to investigate the effect of washing water pH on textile damage for delicate garments, the study was conducted such that a customer survey was first applied to randomly selected users to analyze domestic washing machine using habits of Turkish consumers. Based on the findings of the survey, the experimental study was designed in two successive phases to investigate the dimensional and mechanical behavior of certain types of delicate textiles against varying washing conditions by taking in particular, water properties, namely pH, hardness, and temperature into account, and accordingly to determine the optimized washing conditions for such textiles. Firstly, tergotometer was employed as a washing machine simulator. Within the light of the results obtained, the experimental work of the second phase of the study was conducted, which involved a domestic washing machine as a real-life scenario. All of the results, including the correlation between the data sets obtained from the tergotometer and domestic washing machine trials, were statistically analyzed using Minitab 17. The study produced some important findings regarding the effect of washing water pH on delicate textiles, in addition to an algorithm for improving the present washing program, minimizing textile damage for mainly wool and silk garments.

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The Hitman Study

European Psychologist ◽

10.1027/1016-9040/a000010 ◽

2010 ◽

Vol 15 (2) ◽

pp. 99-108 ◽

Cited By ~ 76

Author(s):

Christopher J. Ferguson ◽

Stephanie M. Rueda

Keyword(s):

Experimental Study ◽

Young Adults ◽

Aggressive Behavior ◽

Video Game ◽

Real Life ◽

Mood Management ◽

Video Game Play ◽

Video Game Playing ◽

Violent Video Game ◽

The Social

This article explores commonly discussed theories of violent video game effects: the social learning, mood management, and catharsis hypotheses. An experimental study was carried out to examine violent video game effects. In this study, 103 young adults were given a frustration task and then randomized to play no game, a nonviolent game, a violent game with good versus evil theme (i.e., playing as a good character taking on evil), or a violent game in which they played as a “bad guy.” Results indicated that randomized video game play had no effect on aggressive behavior; real-life violent video game-playing history, however, was predictive of decreased hostile feelings and decreased depression following the frustration task. Results do not support a link between violent video games and aggressive behavior, but do suggest that violent games reduce depression and hostile feelings in players through mood management.

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Enhancing statistical literacy skills through real life activities enriched with gamification elements: An experimental study

E-Learning and Digital Media ◽

10.1177/2042753020987016 ◽

2021 ◽

pp. 204275302098701

Author(s):

Ünal Çakıroğlu ◽

Mustafa Güler

Keyword(s):

Experimental Study ◽

Experimental Design ◽

Positive Impact ◽

Real Life ◽

Literacy Skills ◽

Statistical Literacy ◽

Instructional Process ◽

Post Test ◽

Quasi Experimental ◽

Teaching Statistics

This study attempts to determine whether gamification can be used as a pedagogical technique to overcome the challenges in teaching statistics. A post-test quasi-experimental design was carried out in gamified and non-gamified groups in order to reveal the effect of gamification elements in cultivating students’ statistical literacy skills. Students in gamified group were also interviewed to understand the function of gamification process. The results suggest that; although gamifying the instructional process had a positive impact on developing students’ statistical literacy in medium and high score students; surprisingly the influence of the gamification to the low- achieved scores were not positive. The positive impact was discussed in accordance with the gradual structure of statistical literacy and suggestions for successful gamification applications due to the context were included.

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EXPERIMENTAL STUDY ON FLAME PROPAGATION IN A STRAIGHT PIPE

Jurnal Teknologi ◽

10.11113/jt.v78.9568 ◽

2016 ◽

Vol 78 (8-3) ◽

Author(s):

Siti Zubaidah Sulaiman ◽

Rafiziana Md Kasmani ◽

A. Mustafa

Keyword(s):

Experimental Study ◽

Flame Propagation ◽

Experimental Work ◽

Diameter Ratio ◽

Straight Pipe ◽

Pipe Length ◽

Operating Condition ◽

Consistent Trend ◽

Length To Diameter Ratio

Flame propagation in a closed pipe with diameter 0.1 m and 5.1 m long, as well as length to diameter ratio (L/D) of 51, was studied experimentally. Hydrogen/air, acetylene/air and methane/air with stoichiometric concentration were used to observe the trend of flame propagation throughout the pipe. Experimental work was carried out at operating condition: pressure 1 atm and temperature 273 K. Results showed that all fuels are having a consistent trend of flame propagation in one-half of the total pipe length in which the acceleration is due to the piston-like effect. Beyond the point, fuel reactivity and tulip phenomenon were considered to lead the flame being quenched and decrease the overpressures drastically. The maximum overpressure for all fuels are approximately 1.5, 7, 8.5 barg for methane, hydrogen, and acetylene indicating that acetylene explosion is more severe.

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An Interoperability Platform Enabling Reuse of Electronic Health Records for Signal Verification Studies

BioMed Research International ◽

10.1155/2016/6741418 ◽

2016 ◽

Vol 2016 ◽

pp. 1-18 ◽

Cited By ~ 5

Author(s):

Mustafa Yuksel ◽

Suat Gonul ◽

Gokce Banu Laleci Erturkmen ◽

Ali Anil Sinaci ◽

Paolo Invernizzi ◽

...

Keyword(s):

Real Life ◽

Case Series ◽

Background Information ◽

Data Sets ◽

Local Data ◽

Lombardy Region ◽

Common Information ◽

Spontaneous Reports ◽

Wide Range ◽

Common Information Model

Depending mostly on voluntarily sent spontaneous reports, pharmacovigilance studies are hampered by low quantity and quality of patient data. Our objective is to improve postmarket safety studies by enabling safety analysts to seamlessly access a wide range of EHR sources for collecting deidentified medical data sets of selected patient populations and tracing the reported incidents back to original EHRs. We have developed an ontological framework where EHR sources and target clinical research systems can continue using their own local data models, interfaces, and terminology systems, while structural interoperability and Semantic Interoperability are handled through rule-based reasoning on formal representations of different models and terminology systems maintained in the SALUS Semantic Resource Set. SALUS Common Information Model at the core of this set acts as the common mediator. We demonstrate the capabilities of our framework through one of the SALUS safety analysis tools, namely, the Case Series Characterization Tool, which have been deployed on top of regional EHR Data Warehouse of the Lombardy Region containing about 1 billion records from 16 million patients and validated by several pharmacovigilance researchers with real-life cases. The results confirm significant improvements in signal detection and evaluation compared to traditional methods with the missing background information.

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Moral Decision Making in Business: A Phase-Model

Business Ethics Quarterly ◽

10.2307/3857833 ◽

2000 ◽

Vol 10 (4) ◽

pp. 773-803 ◽

Cited By ~ 18

Author(s):

Aviva Geva

Keyword(s):

Decision Making ◽

Ethical Decision ◽

Ethical Decision Making ◽

Ethical Problem ◽

Real Life ◽

Phase Model ◽

Second Phase ◽

Illustrative Case ◽

Moral Decision ◽

Ethical Problems

Abstract:The traditional model of ethical decision making in business suggests applying an initial set of principles to a concrete problem and if they conflict the decision maker may attempt to balance them intuitively. The centrality of the ethical conflict in the accepted notion of “ethical problem” has diverted the attention of moral decision modelers from other ethical problems that real-world managers must face—e.g., compliance problems, moral laxity, and systemic problems resulting from the structures and practices of the business organization. The present article proposes a new model for ethical decision making in business—the Phase-model—designed to meet the full spectrum of business-related ethical problems. Drawing on the dominant moral theories in business literature, the model offers additional strategies for tackling ethical issues beyond the traditional cognitive operations of deductive application of principles to specific cases and the balancing of ethical considerations. Its response to the problems of moral pluralism in the context of decision making lies in its structural features. The model distinguishes between three phases of the decision-making process, each having a different task and a different theoretical basis. After an introductory stage in which the ethical problem is defined, the first phase focuses on a principle-based evaluation of a course of action; the second phase provides a virtue-based perspective of the situation and strategies for handling unsettled conflicts and compliance problems; and the third phase adapts the decision to empirical accepted norms. An illustrative case demonstrates the applicability of the model to business real life.

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Self-Adaptive K-Means Based on a Covering Algorithm

Complexity ◽

10.1155/2018/7698274 ◽

2018 ◽

Vol 2018 ◽

pp. 1-16 ◽

Cited By ~ 1

Author(s):

Yiwen Zhang ◽

Yuanyuan Zhou ◽

Xing Guo ◽

Jintao Wu ◽

Qiang He ◽

...

Keyword(s):

Large Scale ◽

Clustering Algorithm ◽

Real Data ◽

Second Phase ◽

Data Sets ◽

Number Of Clusters ◽

Large Scale Data ◽

Long Time ◽

Two Phases ◽

Selection Of

The K-means algorithm is one of the ten classic algorithms in the area of data mining and has been studied by researchers in numerous fields for a long time. However, the value of the clustering number k in the K-means algorithm is not always easy to be determined, and the selection of the initial centers is vulnerable to outliers. This paper proposes an improved K-means clustering algorithm called the covering K-means algorithm (C-K-means). The C-K-means algorithm can not only acquire efficient and accurate clustering results but also self-adaptively provide a reasonable numbers of clusters based on the data features. It includes two phases: the initialization of the covering algorithm (CA) and the Lloyd iteration of the K-means. The first phase executes the CA. CA self-organizes and recognizes the number of clusters k based on the similarities in the data, and it requires neither the number of clusters to be prespecified nor the initial centers to be manually selected. Therefore, it has a “blind” feature, that is, k is not preselected. The second phase performs the Lloyd iteration based on the results of the first phase. The C-K-means algorithm combines the advantages of CA and K-means. Experiments are carried out on the Spark platform, and the results verify the good scalability of the C-K-means algorithm. This algorithm can effectively solve the problem of large-scale data clustering. Extensive experiments on real data sets show that the accuracy and efficiency of the C-K-means algorithm outperforms the existing algorithms under both sequential and parallel conditions.

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Evaluation of General Correlations for Heat Transfer During Boiling of Saturated Liquids in Tubes and Annuli

Heat Transfer: Volume 2 ◽

10.1115/ht2005-72025 ◽

2005 ◽

Cited By ~ 2

Author(s):

M. Mohammed Shah

Keyword(s):

Heat Transfer ◽

Experimental Study ◽

Large Deviations ◽

Boiling Heat Transfer ◽

Mean Deviation ◽

Data Sets ◽

Vapor Quality ◽

Dimensional Parameters ◽

Vertical Tubes ◽

Reduced Pressures

Six of the most verified correlations for boiling heat transfer were compared to data for horizontal and vertical tubes and annuli. The correlations evaluated were: Chen (1966), Shah (1982), Gungor and Winterton (1986), Liu & Winterton (1991), Kandlikar (1990), and Steiner and Taborek (1992). The database used to evaluate these correlations included 29 fluids: water, refrigerants, cryogens, organic and inorganic chemicals. The data cover reduced pressures from 0.005 to 0.783, mass flux from 28 to 11071 kg/m2s, vapor quality from 0 to 0.95, and boiling number from 0.000026 to 0.00742. The correlations of Shah and Gungor & Winterton gave the best agreement with data with a mean deviation of about 17.5%, only a couple of data sets showing large deviations. The paper presents and discusses the results of this study. Included are tables giving the range of dimensional and non-dimensional parameters covered by each experimental study.

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