Despite the importance of adopting SPM tools for supporting agile practices and the significance of usability as an essential component of human factors engineering, their usability evaluation was neglected in the lit...
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ISBN:
(数字)9798400712494
ISBN:
(纸本)9798331523169
Despite the importance of adopting SPM tools for supporting agile practices and the significance of usability as an essential component of human factors engineering, their usability evaluation was neglected in the literature. This study aims to identify the common usability issues in SPM tools and propose suggestions for enhancing their usability. Two of the most widely used SPM tools were selected as a case study for this study, namely Jira and Pivotal Tracker. Three independent evaluators participated in the usability evaluation, using two human factors techniques: Heuristic Evaluation and Cognitive Walkthrough. The results revealed a total frequency of 123 issues in both tools. Both tools had a nearly equal frequency of issues in each evaluation method but different severity levels. Learnability issues were the issues that were raised the most in the evaluation for both tools. Most of the issues had minor to major severity, with the following percentages of total issues: 41.33% and 46.67%, respectively, while only 13.33% were catastrophic. Considering the proposed solutions by designers and developers for this type of tool can help enhance the design of SPM tools, leading to increased user satisfaction and tool *** CONCEPTS• Human-centered computing → Heuristic evaluations; Walk-through evaluations; Usability testing.
It is reported that the first partial derivative of the phase distribution for a transparent object can be measured automatically by a personal computer with an image processor. The moire pattern is formed by superimp...
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Temporal planning methods usually focus on the objective of minimizing makespan. Unfortunately, this misses a large class of planning problems where it is important to consider a wider variety of temporal and non-temp...
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Using software components has become a widely used development technique for building large enterprise systems. However in practice, component applications are still primarily built using simple component models and a...
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Using software components has become a widely used development technique for building large enterprise systems. However in practice, component applications are still primarily built using simple component models and advanced component models offering valuable features like component nesting, multiple communication styles, behavior validation, etc. are omitted (by industry in particular). Based on our experience, such an omitting is mainly caused due to usually unbalanced semantics of these advanced features. In this paper, we present a "next-generation" component model SOFA 2.0, which in particular aims at a proper support of such advanced features.
The practice of getting competitive quotes from carriers to convey goods is known as shipment bidding. Currently, open bidding is handled manually, and prospective bidders are frequently disqualified from taking part ...
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ISBN:
(数字)9798350384369
ISBN:
(纸本)9798350384376
The practice of getting competitive quotes from carriers to convey goods is known as shipment bidding. Currently, open bidding is handled manually, and prospective bidders are frequently disqualified from taking part in the process. The system that is being proposed is designed to record every bidding procedure and make it cumulative in terms of monetary compensation. Real-time shipping tracking, feedback mechanisms, and bid evaluation tools are just a few of the features that the system offers. Shippers choose the best transportation company after weighing bids according to criteria including cost, level of service, and experience. In order to provide safe and effective financial operations, the proposed system also supports the payment and invoicing processes. Additionally, this application has analytical tools to produce reports and insights that help carriers cut costs.
In the Art Education studies, one of the most interesting trends - in terms of its theoretical foundations- is the phenomena of measuring aesthetic experiences [1],[2]. However, traditionally, the teaching of art has ...
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The Common Algebraic Specification Language (CASL) is an expressive language for the formal specification of functional requirements and modular design of software. It has been designed by COFI, the international Comm...
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Implicit feedback is widely used in collaborative filtering methods for recommendation. It is well known that implicit feedback contains a large number of values that are missing not at random (MNAR); and the missing ...
Implicit feedback is widely used in collaborative filtering methods for recommendation. It is well known that implicit feedback contains a large number of values that are missing not at random (MNAR); and the missing data is a mixture of negative and unknown feedback, making it difficult to learn users' negative preferences. Recent studies modeled exposure, a latent missingness variable which indicates whether an item is exposed to a user, to give each missing entry a confidence of being negative feedback. However, these studies use static models and ignore the information in temporal dependencies among items, which seems to be an essential underlying factor to subsequent missingness. To model and exploit the dynamics of missingness, we propose a latent variable named "user intent" to govern the temporal changes of item missingness, and a hidden Markov model to represent such a process. The resulting framework captures the dynamic item missingness and incorporate it into matrix factorization (MF) for recommendation. We also explore two types of constraints to achieve a more compact and interpretable representation of user intents. Experiments on real-world datasets demonstrate the superiority of our method against state-of-the-art recommender systems.
The McCracken et al. working group paper is often cited for the proposition that students can't program. In that study, students from four different institutions were each assigned to implement one of three versio...
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The accumulation of huge amount of biology data and their heterogeneity has become a bottleneck in the analysis of protein-protein interaction (PPI) networks, especially in the visualization of PPI networks. Because t...
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The accumulation of huge amount of biology data and their heterogeneity has become a bottleneck in the analysis of protein-protein interaction (PPI) networks, especially in the visualization of PPI networks. Because the format of the data generated from different experimental groups is diverse, and the databases for the storage and management of the data are different, network visualization of the heterogeneous data by integrating different derived data is challenging and is a key to comprehensively understanding the mechanism of biology system. To visualize the interactions of proteins, we first utilize the robot crawl technique to dynamically integrate the information of protein-protein interactions from all the related public databases such as Protein Interaction Database (PID), Human Protein Reference Database (HPRD) and Reactome. Second, we use a graph algorithm to partition the complex network into different sub-networks to discover the `Hub' proteins in the visualization protein-protein networks. Finally, we develop a protocol for the collaboration of different researchers based on the visualization of the PPI networks.
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