• International conference on construction engineering and project management
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• 2007.03a
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• pp.289-298
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• 2007

The development of construction industry has led to the increase in the number of criteria imposed by project clients for selecting contractors. For example, clients often request tenderers to satisfy various conditions such as tight programme, financial strength, managerial ability, relevant work experiences, technical strength, high workmanship standard, safety requirement, quality specification, and yet others. This trend has attracted research interests of devising various methods for helping project clients to assess contractors' bids. For example, in recent development, the Works Bureau of the Hong Kong Government has introduced two mechanisms in tender evaluation for various public work contracts, namely, the Marking Scheme effective from June 2002 and the Formula Approach effective from November 2002 [1], [2]. These approaches evaluate a contractor's tender by considering collectively its tender price and performance attributes, the latter including contractor experience, past performance, technical resources and technical content of his proposal. The tender with the highest combined price and performance score (CPPS) will be normally recommended for acceptance. It appears, however, that there is little existing research in helping contractors to identify a competition strategy that enables the contractor to offer his most competitive bid collectively taking into account his resource capacities and project client's multiple performance criteria. This paper examines the factors affecting contractor's competition strategy to compete for works in Hong Kong. The understanding about the factors will contribute to identifying effective competition strategy. The data used for the analysis were collected from Hong Kong construction industry. The research findings may provide valuable references for investigating effective competition strategies in other construction industries outside the region.

• Animal Bioscience
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• v.36 no.10
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• pp.1596-1603
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• 2023

Objective: Sous-vide cooking offers several advantages for poultry meat, including enhanced tenderness, reduced cooking loss, and improved product yield. However, in duck meat, there are challenges associated with using the sous-vide method. The prolonged cooking time at low temperatures can lead to unstable microbial and oxidative stabilities. Thus, we aimed to assess how varying sous-vide cooking temperatures and durations affect the physicochemical and microbial characteristics of duck breast meat, with the goal of identifying an optimal cooking condition. Methods: Duck breast meat (Anas platyrhynchos) aged 42 days and with an average weight of 1,400±50 g, underwent cooking under various conditions (ranging from 50℃ to 80℃) for either 60 or 180 min. Then, physicochemical, microbial, and microstructural properties of the cooked duck breast meat were assessed. Results: Different cooking conditions affected the quality attributes of the meat. The cooking loss, lightness, yellowness, Hue angle, whiteness, and thiobarbituric acid reactive substance (TBARS) values of the duck breast meat increased with the increase in cooking temperature and time. In contrast, the redness and chroma values decreased with the increase in cooking temperature and time. Cooking of samples higher than 60℃ increased the volatile basic nitrogen contents and TBARS. Microbial analysis revealed the presence of Escherichia coli and Coliform only in the samples cooked at 50℃ and raw meat. Cooking at lower temperature and shorter time increased the tenderness of the meat. Microstructure analysis showed that the contraction of myofibrils and meat density increased upon increasing the cooking temperature and time. Conclusion: Our data indicate that the optimal sous-vide method for duck breast meat was cooking at 60℃ for 60 min. This temperature and time conditions showed good texture properties and microbial stability, and low level of TBARS of the duck breast meat.

• Journal of Korean Clinical Nursing Research
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• v.29 no.3
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• pp.337-347
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• 2023

Purpose: The objectives of this study were to categorize the conflict management types of preceptor nurses and determine the effects of these types on preceptors' role perception and core competencies. Methods: Data was collected from 192 preceptor nurses with at least two years experiences in general hospitals, from July 1 to July 31, 2022. Conflict management type, preceptor role perception, and core competency were investigated using structured instruments. The data was analyzed using K-means cluster analysis, Independent samples t-test, One-way ANOVA with Scheffé's test, and multiple regression analysis. Results: The conflict management types were categorized into four types; comprehensive type (cluster 1), integrating, obliging, compromising type (cluster 2), undifferentiated type (cluster 3) and obliging, avoiding type (cluster 4). The effect of conflict management types on preceptors' role recognition occurred in the following order of cluster 2 (integrating/obliging/compromising type), cluster 1 (comprehensive type), and cluster 4 (obliging/avoiding type). Next, cluster 1 (comprehensive type), cluster 2 (integrating/obliging/compromising type), and cluster 4 (obliging/avoiding type) were shown in the order of the impact on the core competencies of the preceptor. Conclusion: When preceptor nurses use a mixture of various attributes of conflict management evenly, they have been shown to demonstrate effective preceptor role recognition and core competencies. Therefore, it is proposed that future development of conflict management training programs for preceptor nurses should begin with identifying their conflict management type, followed by creating a program that addresses any deficiencies.

• Advances in concrete construction
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• v.16 no.1
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• pp.69-78
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• 2023

This investigation delves into the adverse repercussions stemming from the impact of arsenic on steel pipes concealed within soil designated for rice cultivation. Simultaneously, the study aims to ascertain effective techniques for detecting arsenic in the soil and to provide strategies for mitigating the corrosion of steel pipes. The realm of nanotechnology presents promising avenues for addressing the intricate intersection of renewable energy, oil, and environmental pollution from a novel perspective. Nanostructured materials, characterized by distinct chemical and physical attributes, unveil novel pathways for pioneering materials that exert a substantial impact across diverse realms of food production, storage, packaging, and quality control. Within the scope of the food industry, the scope of nanotechnology encompasses processes, storage methodologies, packaging paradigms, and safeguards to ensure the safety of consumables. Of particular note, silver nanoparticles, in addition to their commendable antibacterial efficacy, boast anti-fungal and anti-inflammatory prowess, environmental compatibility, minimal irritability and allergenicity, resilience to microbial antagonism, thermal stability, and robustness. Confronting the pressing issue of arsenic contamination within both environmental settings and the food supply is of paramount importance to preserve public health and ecological equilibrium. In response, this study introduces detection kits predicated upon silver nanoparticles, providing an expeditious and economically feasible avenue for identifying arsenic concentrations ranging from 0.5 to 3 ppm within rice. Subsequent quantification employs Hydride Atomic Absorption Spectroscopy (HG-AAS), which features a detection threshold of 0.05 ㎍/l. A salient advantage inherent in the HG-AAS methodology lies in its capacity to segregate analytes from the sample matrix, thereby significantly reducing instances of spectral interference. Importantly, the presence of arsenic in the soil beneath rice cultivation establishes a causative link to steel pipe corrosion, with potential consequences extending to food contamination-an intricate facet embedded within the broader tapestry of renewable energy, oil, and environmental pollution.

• Journal of the Korean Society of Food Culture
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• v.38 no.6
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• pp.415-424
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• 2023

This study was undertaken to provide basic data to aid product development and marketing by identifying purchasing behaviors and performing Important Performance Analysis (IPA) according to the consumption values of rice cakes. This study was conducted on 426 consumers who purchased rice cakes. Analysis was performed to determine general characteristics, consumption behaviors, preference for rice cakes, material preferences for rice cake development, need for rice cake development, and importance and satisfaction when selecting rice cakes. Cluster analysis classified consumption values into three clusters. The high and middle consumption value groups contained the greatest proportions of consumers aged over fifty. The high and medium consumption value groups preferred rice cakes more than the low consumption value group. Higher rice cake consumption value was positively associated with the greater preference for rice cakes. Furthermore, the perceived need to develop rice cakes was greatest in the high consumption value group. In addition, importance and satisfaction were positively associated with consumption value. IPA analysis showed that the attributes that require continuous attention because of their contributions to importance and satisfaction were taste, quantity, and hygiene. Different rice cake marketing and product development strategies are required for different consumption values.

• Journal of Integrative Natural Science
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• v.16 no.4
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• pp.123-131
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• 2023

Breast cancer continues to pose a substantial worldwide health challenge, thereby requiring the development of innovative strategies to discover new therapeutic interventions. Signal Transducer and Activator of Transcription 3 (STAT-3) has been identified as a significant factor in the development of several types of cancer, including breast cancer. This is primarily attributed to its diverse functions in promoting tumour formation and conferring resistance to therapeutic interventions. This study presents an in silico drug repositioning approach that focuses on identifying specific inhibitors of STAT-3 for the purpose of treating breast cancer. We initially examined the structural and functional attributes of STAT-3, thereby elucidating its crucial involvement in cellular signalling cascades. A comprehensive virtual screening was performed on a diverse collection of drugs that have been approved by the FDA from zinc15 database. Various computational techniques, including molecular docking, cross docking, and cDFT analysis, were utilised in order to prioritise potential candidates. This prioritisation was based on their predicted binding energies and outer molecular orbital reactivity. The findings of our study have unveiled a Dihydroergotamine and Paritaprevir that have been approved by the FDA and exhibit considerable promise as selective inhibitors of STAT-3. In conclusion, the utilisation of our in silico drug repositioning approach presents a prompt and economically efficient method for the identification of potential compounds that warrant subsequent experimental validation as selective STAT-3 inhibitors in the context of breast cancer. The present study highlights the considerable potential of employing computational strategies to expedite the drug discovery process. Moreover, it provides valuable insights into novel avenues for targeted therapeutic interventions in the context of breast cancer treatment.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.493-513
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• 2014

With the development of related technologies, Location-Based Services (LBS) are growing fast and being used in many ways. Past LBS studies have focused on adoption of LBS because of the fact that LBS users have privacy concerns regarding revealing their location information. Meanwhile, the number of LBS users and revenues from LBS are growing rapidly because users can get some benefits by revealing their location information. Little research has been done on how LBS affects consumers' information search behavior in product purchase. The purpose of this paper is examining the effect of LBS information filtering on buyers' uncertainty and their information search behavior. When consumers purchase a product, they try to reduce uncertainty by searching information. Generally, there are two types of uncertainties - knowledge uncertainty and choice uncertainty. Knowledge uncertainty refers to the lack of information on what kinds of alternatives are available in the market and/or their important attributes. Therefore, consumers having knowledge uncertainty will have difficulties in identifying what alternatives exist in the market to fulfil their needs. Choice uncertainty refers to the lack of information about consumers' own preferences and which alternative will fit in their needs. Therefore, consumers with choice uncertainty have difficulties selecting best product among available alternatives.. According to economics of information theory, consumers narrow the scope of information search when knowledge uncertainty is high. It is because consumers' information search cost is high when their knowledge uncertainty is high. If people do not know available alternatives and their attributes, it takes time and cognitive efforts for them to acquire information about available alternatives. Therefore, they will reduce search breadth. For people with high knowledge uncertainty, the information about products and their attributes is new and of high value for them. Therefore, they will conduct searches more in-depth because they have incentive to acquire more information. When people have high choice uncertainty, people tend to search information about more alternatives. It is because increased search breadth will improve their chances to find better alternative for them. On the other hand, since human's cognitive capacity is limited, the increased search breadth (more alternatives) will reduce the depth of information search for each alternative. Consumers with high choice uncertainty will spend less time and effort for each alternative because considering more alternatives will increase their utility. LBS provides users with the capability to screen alternatives based on the distance from them, which reduces information search costs. Therefore, it is expected that LBS will help users consider more alternatives even when they have high knowledge uncertainty. LBS provides distance information, which helps users choose alternatives appropriate for them. Therefore, users will perceive lower choice uncertainty when they use LBS. In order to test the hypotheses, we selected 80 students and assigned them to one of the two experiment groups. One group was asked to use LBS to search surrounding restaurants and the other group was asked to not use LBS to search nearby restaurants. The experimental tasks and measures items were validated in a pilot experiment. The final measurement items are shown in Appendix A. Each subject was asked to read one of the two scenarios - with or without LBS - and use a smartphone application to pick a restaurant. All behaviors on smartphone were recorded using a recording application. Search breadth was measured by the number of restaurants clicked by each subject. Search depths was measured by two metrics - the average number of sub-level pages each subject visited and the average time spent on each restaurant. The hypotheses were tested using SPSS and PLS. The results show that knowledge uncertainty reduces search breadth (H1a). However, there was no significant correlation between knowledge uncertainty and search depth (H1b). Choice uncertainty significantly reduces search depth (H2b), but no significant relationship was found between choice uncertainty and search breadth (H2a). LBS information filtering significantly reduces the buyers' choice uncertainty (H4) and reduces the negative relationship between knowledge uncertainty and search breadth (H3). This research provides some important implications for service providers. Service providers should use different strategies based on their service properties. For those service providers who are not well-known to consumers (high knowledge uncertainty) should encourage their customers to use LBS. This is because LBS would increase buyers' consideration sets when the knowledge uncertainty is high. Therefore, less known services have chances to be included in consumers' consideration sets with LBS. On the other hand, LBS information filtering decrease choice uncertainty and the near service providers are more likely to be selected than without LBS. Hence, service providers should analyze geographically approximate competitors' strength and try to reduce the gap so that they can have chances to be included in the consideration set.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.99-118
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• 2015

Object-oriented programming languages have been widely selected for developing modern information systems. The use of concepts relating to object-oriented (OO, in short) programming has reduced efforts of reusing pre-existing codes, and the OO concepts have been proved to be a useful in interpreting system requirements. In line with this, we have witnessed that a modern conceptual modeling approach supports features of object-oriented programming. Unified Modeling Language or UML becomes one of de-facto standards for information system designers since the language provides a set of visual diagrams, comprehensive frameworks and flexible expressions. In a modeling process, UML users need to consider relationships between classes. Based on an explicit and clear representation of classes, the conceptual model from UML garners necessarily attributes and methods for guiding software engineers. Especially, identifying an association between a class of part and a class of whole is included in the standard grammar of UML. The representation of part-whole relationship is natural in a real world domain since many physical objects are perceived as part-whole relationship. In addition, even abstract concepts such as roles are easily identified by part-whole perception. It seems that a representation of part-whole in UML is reasonable and useful. However, it should be admitted that the use of UML is limited due to the lack of practical guidelines on how to identify a part-whole relationship and how to classify it into an aggregate- or a composite-association. Research efforts on developing the procedure knowledge is meaningful and timely in that misleading perception to part-whole relationship is hard to be filtered out in an initial conceptual modeling thus resulting in deterioration of system usability. The current method on identifying and classifying part-whole relationships is mainly counting on linguistic expression. This simple approach is rooted in the idea that a phrase of representing has-a constructs a par-whole perception between objects. If the relationship is strong, the association is classified as a composite association of part-whole relationship. In other cases, the relationship is an aggregate association. Admittedly, linguistic expressions contain clues for part-whole relationships; therefore, the approach is reasonable and cost-effective in general. Nevertheless, it does not cover concerns on accuracy and theoretical legitimacy. Research efforts on developing guidelines for part-whole identification and classification has not been accumulated sufficient achievements to solve this issue. The purpose of this study is to provide step-by-step guidelines for identifying and classifying part-whole relationships in the context of UML use. Based on the theoretical work on Meta-model Formalization, self-check forms that help conceptual modelers work on part-whole classes are developed. To evaluate the performance of suggested idea, an experiment approach was adopted. The findings show that UML users obtain better results with the guidelines based on Meta-model Formalization compared to a natural language classification scheme conventionally recommended by UML theorists. This study contributed to the stream of research effort about part-whole relationships by extending applicability of Meta-model Formalization. Compared to traditional approaches that target to establish criterion for evaluating a result of conceptual modeling, this study expands the scope to a process of modeling. Traditional theories on evaluation of part-whole relationship in the context of conceptual modeling aim to rule out incomplete or wrong representations. It is posed that qualification is still important; but, the lack of consideration on providing a practical alternative may reduce appropriateness of posterior inspection for modelers who want to reduce errors or misperceptions about part-whole identification and classification. The findings of this study can be further developed by introducing more comprehensive variables and real-world settings. In addition, it is highly recommended to replicate and extend the suggested idea of utilizing Meta-model formalization by creating different alternative forms of guidelines including plugins for integrated development environments.

• Management & Information Systems Review
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• v.30 no.1
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• pp.211-226
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• 2011

This study was intended to investigate the attributes of the Internet shopping mall and to examine the effects of each attribute on the consumer purchase intention. 279 valid responses of total 300 questionnaire were used for the analysis of this study. Both the exploratory factor analysis and reliability analysis were conducted to evaluate the conceptual validity and internal coherence of the determining variables and the use intention. The factor analysis resulted in identifying the five factors of the Internet shopping mall and on the multiple regression analysis, three of the five identified factors were found to affect significantly the purchase intention. According to the verified results interactivity(t=4.384) was found to affect positively the use intention, while privacy risk(t=-2.985) and delivery risk(t=-2.257) were found to affect negatively the purchase intention. Managerial suggestions are recommended as the results of analysis. It is urgently necessary for decreasing countermeasures delivery risk and privacy risk to enhance purchase intention of customers in internet shopping malls. Especially obtaining more information on consumers gives short-term advantages to marketers, perceived slackness in privacy will hinder purchase intention in internet shopping malls in the long run by causing distrust of consumers. Other limitations and future research directions are also mentioned.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.12
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• pp.1981-1989
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• 2008

Different people buy the same or similar products for different reasons. Benefit segmentation attempts to understand these differences by grouping together people who assign a similar level of importance to the same attributes. We focused on identifying market segments for knit fabrics by comparing the relative attribute preference for knit fabrics according to segmented clusters, and testing to establish if there were significant differences between the preferences of clusters. Three consumer segments emerged, and there were three clusters with different ideal knit profiles: a preferred wool group, a preferred acrylic group, and a preferred long stitch length group. The preferred wool group and the preferred acrylic group rated the mixture ratio as the main attribute that determined their preference, followed by the stitch length. The preferred long stitch length group considered stitch length as being the most important attribute, followed by the mixture ratio. The difference in the preferences for the mixture ratio and stitch length of knit fabrics was the highest between the three clusters, The preferred wool group preferred a knit fabric that has a greater wool mixture ratio and a short stitch length, and the preferred acrylic group and long stitch length group preferred a knit fabric that had a higher acrylic mixture ratio and a short stitch length.