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"This book discusses what is currently known about software engineering, based on an analysis of all the publicly available data. This aim is not as ambitious as it sounds, because there is not a great deal of data publicly available.
The intent is to provide material that is useful to professional developers working in industry; until recently researchers in software engineering have been more interested in vanity work, promoted by ego and bluster.
The material is organized in two parts, the first covering software engineering and the second the statistics likely to be needed for the analysis of software engineering data." |
In this article, we examine the accuracy and bias of market valuations in the U.S. commercial real estate sector using properties included in the NCREIF Property Index (NPI) between 1997 and 2021 and assess the potential of machine learning algorithms (i.e., boosting trees) to shrink the deviations between market values and subsequent transaction prices. Under consideration of 50 covariates, we find that these deviations exhibit structured variation that boosting trees can capture and further explain, thereby increasing appraisal accuracy and eliminating structural bias. The understanding of the models is greatest for apartments and industrial properties, followed by office and retail buildings. This study is the first in the literature to extend the application of machine learning ... |
With the explosive growth of artificial intelligence (AI) and big data, it has become vitally important to organize and represent the enormous volume of knowledge appropriately. As graph data, knowledge graphs accumulate and convey knowledge of the real world. It has been well-recognized that knowledge graphs effectively represent complex information; hence, they rapidly gain the attention of academia and industry in recent years. Thus to develop a deeper understanding of knowledge graphs, this paper presents a systematic overview of this field. Specifically, we focus on the opportunities and challenges of knowledge graphs. We first review the opportunities of knowledge graphs in terms of two aspects: (1) AI systems built upon knowledge graphs; (2) potential application fields of kn... |
The first two of the twenty-three unsolved problems that David Hilbert famously proposed at the 1900 International Congress of Mathematicians (ICM) in 1900 dealt with issues associated with the real number continuum. The first problem concerned Cantor’s continuum hypothesis, whereas the second dealt with Hilbert’s attempt to establish the existence of the continuum by proving the consistency of his axioms for characterizing its properties. Few have noted, however, that Hilbert himself linked the larger goals of Cantor’s theory of transfinite arithmetic with those of his own program for axiomatization. |
This paper examines the critical role of Mega Infrastructure Projects in sustainable urban and peripheral development by presenting a Sustainable Infrastructure Serum Analysis supported by primary field research. In the Athens Metro case study, we examined the project's impact on sustainable development by analysing the opinions of the project's users. As a result, the Athens Metro serves as a case study to help us better understand sustainable infrastructure as a framework for green growth from the standpoint of society. The three pillars of sustainable development are inextricably linked. |
We consider a lot-sizing problem with set-ups where the demands are uncertain, and propose a novel approach to evaluate the inventory costs. An interval uncertainty is assumed for the demands. Between two consecutive production periods, the adversary chooses to set the demand either to its higher value or to its lower value in order to maximize the inventory (holding or backlog) costs. A mixed-integer model is devised and a column-and-row generation algorithm is proposed. Computational tests based on random generated instances are conducted to evaluate the model, the decomposition algorithm, and compare the structure of the solutions from the robust model with those from the deterministic model. |
We model civil litigation as a simultaneous contest between a plaintiff and a defendant who have monetary and emotional preferences. The litigants’ emotional variables capture a non-monetary joy of winning and relational emotions toward each other. A contest success function (CSF) describes the litigants’ respective probabilities of success based on their endogenous litigation expenses and exogenous relative advantages. The model does not specify a functional form for the CSF. Instead, it accommodates any CSF that satisfies general and intuitive assumptions, which capture frequently-used functional forms. A cost-shifting rule allows the winner to recover an exogenous proportion of her litigation expenses from the loser. |
The use of algorithmic management systems is rapidly changing organizational models and practices, as millions of workers in multiple sectors worldwide are managed by computer software. Despite receiving increasing academic interest, little summarizing literature exist on the ways algorithmic systems are used in management. This article aims to fill this gap by systematically reviewing and qualitatively analyzing 172 articles on the topic. Our research contributes to the existent algorithmic management literature in three ways. First, we provide a descriptive overview of algorithmic management as a field of research. Second, we identify and synthesize the discussion on the key concepts of the topic, namely how algorithmic management: (1) simultaneously restrains and enables workers’... |
Accurate and informative hand-object collision feedback is of vital importance for hand manipulation in virtual reality (VR). However, to our best knowledge, the hand movement performance in fully-occluded and confined VR spaces under visual collision feedback is still under investigation. In this paper, we firstly studied the effects of several popular visual feedback of hand-object collision on hand movement performance. To test the effects, we conducted a within-subject user study (n=18) using a target-reaching task in a confined box. Results indicated that users had the best task performance with see-through visualization, and the most accurate movement with the hybrid of proximity-based gradation and deformation. |
The influence of personality traits on educational outcomes has been widely recognized and studied. Research has explored its effects on factors such as student satisfaction, academic anxiety, and dishonesty, particularly during the COVID-19 pandemic. However, there has been a lack of studies comparing the learning behaviors and performance of students with different personality traits during the pre, during, and post-COVID-19 lockdown periods. This study fills this gap by analyzing the differences in academic metrics, such as class grades and assignment submissions, among students with varying personality traits during different lockdown periods. Our research, based on a dataset of 282 graduate students in the USA, identified correlations and patterns between lockdown periods, pers... |
