PurposeThe purpose of this study is to map the conceptual structure of the body of knowledge linking digital technologies and auditing, with the aim of contributing to a better understanding of this ...research stream.Design/methodology/approachThis research develops a bibliometric analysis of 256 articles following two steps. The analysis of descriptive performance indicators identifies the main traits of the community of scholars debating audit and technology in terms of publications, productive countries and authors, as well as the publication’s impact of the target journals concerning specific fields, number of citations per country and most cited articles in the data set. To analyse the conceptual structure of the data set, the study performs a co-word analysis adopting social network analysis tools.FindingsThe results highlight a growing academic interest in the research topic, especially in the past few years. The bibliometric analysis reveals three main topics concerning the use and application of technology in the audit profession: the adoption of continuous auditing and continuous monitoring in the auditing profession; the use of software tools in the audit profession; the connections between information systems and audit.Originality/valueThis paper contributes to the field by providing an examination of the current state of the art of research on the use and application of technology in the audit profession as well as identifying the current gaps in the literature and, most importantly, propose a research agenda for the field.
Identification of technology development trends is essential for supporting decision makers in forecasting and identifying related innovation activities and industrial growth. Different from the ...traditional technology development trends based on keyword-based quantitative methods, which usually predict trends by finding key technologies without showing how to develop them, our method allows the identification of future direction and industry goal for the technology domain and shows detailed paths for achieving them. Thus, our method has constructed technology roadmapping (TRM) with seven layers (material, technology, influencing factor, component, product, goal, and future direction) on the basis of subject–action–object analysis. The detailed paths for developing this as a trend can be shown by the interaction among these TRM elements. In addition, the method also sets three indicators as a discriminating standard to find key players that can support the trend by engaging technological innovation scenarios. The case of a dye-sensitized solar cell (DSSC) is exemplified to illustrate the detailed procedure of our method. The results reveal the development trends in the field of DSSCs, the detailed paths to achieve them, and key countries that support them.
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•We propose an SAO-based approach to identify technology development trend.•We propose a TRM with seven layers using SAO structures with significant information.•TRM displays the development trend of technology domain and detailed innovation paths.•We use subject–action–object (SAO) semantic analysis to mine significant information.
The two-dimensional structure map (atomic radius ratio R, d-electron total count DET) for prediction of the formation of the transition metal-transition metal Laves phases. Atomic radius ratio ...R>1.116 is valid for the transition metal-transition metal Laves phases forming through liquid phases. The parameter d-electron total count (DET) proposed for the first time can effectively describe the bonding features in transition metal-transition metal alloys, and the DET in the range of 5<DET<10 favors the formation of unsaturated covalent bonding which is assumed as the dominant bonding of the transition metal-transition metal Laves phases. Within the scope of transition metal-transition metal systems as defined in this paper, the formation of the Laves phases through liquid metals requires satisfying both the criteria of R and DET generally.
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•A structural map for prediction of transition-metal Laves phases is proposed.•The map uses atomic radius ratio and d-electron total count as coordinates.•d-electron total count can outline the bonding feature in transition-metal Laves.•The map effectively distinguishes the Laves and non-Laves.
Although it is well accepted that atomic size and electronic factors control the formation of transition-metal (TM) Laves phases, a geometrical description of the occurrence of the TM-TM Laves phases is lacking. In this paper, a two-dimensional structure map is proposed to predict the Laves phases using atomic radius ratio (R) and d-electron total count (DET) as coordinates, where DET is empirically developed to describe the bonding features in the TM-TM Laves phases. Within the structure map, the criterion R>1.116 is found for the formation of 16-coordinated Frank-Kasper polyhedra in TM-TM Laves phases through liquid alloys; while the narrowed range of 5<DET<10 may offer an empirical measurement on the formation tendency of unsaturated covalent bonds in the TM-TM systems. The existence of TM-TM Laves phases forming through liquid alloys defined in the present work satisfies both R>1.116and5<DET<10 simultaneously. The proposed two-dimensional structure map method provides a possible new strategy to predict the Laves phases in the TM-TM systems.
This work presents Satellite Style and Structure Generative Adversarial Network (SSGAN), a generative model of high resolution satellite imagery to support image segmentation. Based on spatially ...adaptive denormalization modules (SPADE) that modulate the activations with respect to segmentation map structure, in addition to global descriptor vectors that capture the semantic information in a vector with respect to Open Street Maps (OSM) classes, this model is able to produce consistent aerial imagery. By decoupling the generation of aerial images into a structure map and a carefully defined style vector, we were able to improve the realism and geodiversity of the synthesis with respect to the state-of-the-art baseline. Therefore, the proposed model allows us to control the generation not only with respect to the desired structure, but also with respect to a geographic area.
Bioinformatics approaches to carbohydrate research have recently begun using large amounts of protein and carbohydrate data. In this field called glycome informatics, the foremost necessity is a ...comprehensive resource for genome-scale bioinformatics analysis of glycan data. Although the accumulation of experimental data may be useful as a reference of biological and biochemical information on carbohydrates, this is insufficient for bioinformatics analysis. Thus, we have developed a glycome informatics resource (http://www.genome.jp/kegg/glycan/) in KEGG (Kyoto Encyclopedia of Genes and Genomes), an integrated knowledge base of protein networks, genomic information, and chemical information. This review describes three noteworthy features: (1) GLYCAN, a database of carbohydrate structures; (2) glycan-related pathways; and (3) Composite Structure Map (CSM), a map illustrating all possible variations of carbohydrate structures within organisms. GLYCAN includes two useful tools: an intuitive drawing tool called KegDraw, and an efficient glycan search and alignment tool called KEGG Carbohydrate Matcher (KCaM). KEGG's glycan biosynthesis and metabolism pathways, integrating carbohydrate structures, proteins, and reactions, are also a pivotal resource. CSM is constructed as a bridge between carbohydrate functions and structures. CSM is able to display, for example, expression data of glycosyltransferases in a compact manner. In all the KEGG resources, various objects including KEGG pathways, chemical compounds, as well as carbohydrate structures are commonly represented as graphs, which are widely studied and utilized in the computer science field.
This study maps the conceptual structure of the body of knowledge concerning bank risk to understand this research strand better. A bibliometric analysis including 671 publications from January 1978 ...to October 2022 was conducted to achieve the aim of the study. The analysis of descriptive indicators identifies the main traits of scholars debating bank risk in terms of the annual production of publications; most productive authors, countries, affiliations, and journals; and most cited articles in the dataset. This study performs a co-word analysis by adopting social network analysis tools to analyze the conceptual structure of the dataset. The results highlight growing academic interest in bank risk research topics, especially following the global financial crisis. The bibliometric analysis reveals three main topics concerning the consideration of bank risk: (1) the adoption of risk management and bank risk, (2) the use of bank risk during the financial crisis, and (3) the interrelations between corporate governance and bank risk.
In the last few years, huge amounts of progress have been made regarding remote sensing in the field of computer vision. This success and progress is mostly due to the effectiveness of deep learning ...(DL) algorithms. In addition, the remote sensing community has shifted its attention to DL, and DL algorithms have been used to achieve significant success in many image analysis tasks. However, with regard to remote sensing, a number of challenges caused by difficulties in data acquisition and annotation have not been fully solved yet. This reprint is a collection of novel developments in the field of remote sensing using computer vision, deep learning, and artificial intelligence. The articles published involve fundamental theoretical analyses as well as those demonstrating their application to real-world problems.
In the last few years, huge amounts of progress have been made regarding remote sensing in the field of computer vision. This success and progress is mostly due to the effectiveness of deep learning ...(DL) algorithms. In addition, the remote sensing community has shifted its attention to DL, and DL algorithms have been used to achieve significant success in many image analysis tasks. However, with regard to remote sensing, a number of challenges caused by difficulties in data acquisition and annotation have not been fully solved yet. This reprint is a collection of novel developments in the field of remote sensing using computer vision, deep learning, and artificial intelligence. The articles published involve fundamental theoretical analyses as well as those demonstrating their application to real-world problems.
We apply the Gromov–Hausdorff metric
d
G
for characterization of certain generalized manifolds. Previously, we have proven that with respect to the metric
d
G
,
generalized
n
-manifolds are limits of ...spaces which are obtained by gluing two topological
n
-manifolds by a controlled homotopy equivalence (the so-called 2-patch spaces). In the present paper, we consider the so-called
manifold-like
generalized
n
-manifolds
X
n
,
introduced in 1966 by Mardeić and Segal, which are characterized by the existence of
δ
-mappings
f
δ
of
X
n
onto closed manifolds
M
δ
n
,
for arbitrary small
δ
>
0
, i.e., there exist onto maps
f
δ
:
X
n
→
M
δ
n
such that for every
u
∈
M
δ
n
,
f
δ
-
1
(
u
)
has diameter less than
δ
. We prove that with respect to the metric
d
G
,
manifold-like generalized
n
-manifolds
X
n
are limits of topological
n
-manifolds
M
i
n
. Moreover, if topological
n
-manifolds
M
i
n
satisfy a certain local contractibility condition
M
(
ϱ
,
n
)
, we prove that generalized
n
-manifold
X
n
is resolvable.
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