280 research outputs found
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
Investigating Digital Corporate Reporting from an Upper Echelons Theory Perspective: Evidence from the Arab Middle East
Utilising the insights of Upper Echelons Theory (UET) and bounded rationality assumption, this original study aimed to investigate the association between corporate leaders’ characteristics and both the extent and readability of Digital Corporate Reporting (DCR). Content analysis of corporate websites of 122 publicly listed Jordananian firms has been carried out. The logistics regression analysis revealed that maintaining a functioning corporate website is inversely associated with CEO age. This indicates that younger CEOs are more likely to retain a web presence for the firm than their older counterparts. The OLS regression analysis revealed that CEOs’ education and tenure were negatively associated with the extent of DCR. Moreover, it was found that Corporate Governance (CG) moderating variables hardly lessen this relationship. The results confirm the current thoughts regarding the rise of CEO effects in corporations with unique evidence from the Arab Middle East (AME). Building on the previous evidence, the study also aimed at uncovering the association between chairman characteristics and the readability of the digital version of the chairman’s Letter to Shareholders (LTS). A hand-built dataset from a sample of 379 LTS from 101 publicly listed firms in 7 AME countries over five years (2014 – 2018) were employed to achieve this objective. Focusing on the clarity of DCR, the results of this second part of this study emphasizes the potential of UET to provide incremental plausible explanations of the variance in the levels of readability of LTS. The clustered regression results of the panel data demonstrate that older and less educated chairpersons are associated with more readable disclosures. Such findings on disclosure styles demonstrate the power of individuals in positions of authority as a consequence of higher education and tenure. Such findings contribute to the evolving inquiry on the significance of readability for enhancing corporate disclosure transparency and have implications for improving the DCR extent and readability
LIPIcs, Volume 261, ICALP 2023, Complete Volume
LIPIcs, Volume 261, ICALP 2023, Complete Volum
Understanding water chemistry in biofilters using chemometric methods
Biological activated carbon filtration operating in slow flowing mode is a compromise between slow sand filtration and rapid-rate biological activated carbon filtration. It brings together the benefits of both systems: good control of microbial pathogens and dissolved organic matter removal. In this thesis the change in water chemistry in such biofilters was studied as a possible alternative for small-scale decentralised water treatment in Scotland.
Change in chemical water quality was monitored in the influent, effluent, and pore water of labscale biofilters of varying lengths. Also, the effect of pore water chemistry on carbon processing by microbial communities from various filter depths was studied by batch experiment. Finally the effect of spatial and temporal water quality variation in Scotland on biofilter performance was studied via a metadata study.
Results showed that dissolved organic matter was removed via multistage adsorption with filter length having a positive impact on the removal efficiency in apparent steady state. Applying the biofilters to other Scottish fresh waters with lower DOM concentrations will increase their performance. Within the filters, different ecological niches were formed. The community at the top processed the easily available low molecular weight acids, the community at the bottom was able to degrade the more recalcitrant humic substances. This indicates that specific microbes inhabit this bottom niche and are able to survive on the limited choice of DOM species.
These research findings contribute to further optimisation of the biofilter design and for the scientific community to further understand biofilter stratification and its impact on DOM removal
A survey of parameterized algorithms and the complexity of edge modification
The survey is a comprehensive overview of the developing area of parameterized algorithms for graph modification problems. It describes state of the art in kernelization, subexponential algorithms, and parameterized complexity of graph modification. The main focus is on edge modification problems, where the task is to change some adjacencies in a graph to satisfy some required properties. To facilitate further research, we list many open problems in the area.publishedVersio
LIPIcs, Volume 274, ESA 2023, Complete Volume
LIPIcs, Volume 274, ESA 2023, Complete Volum
Remote Sensing Data Compression
A huge amount of data is acquired nowadays by different remote sensing systems installed on satellites, aircrafts, and UAV. The acquired data then have to be transferred to image processing centres, stored and/or delivered to customers. In restricted scenarios, data compression is strongly desired or necessary. A wide diversity of coding methods can be used, depending on the requirements and their priority. In addition, the types and properties of images differ a lot, thus, practical implementation aspects have to be taken into account. The Special Issue paper collection taken as basis of this book touches on all of the aforementioned items to some degree, giving the reader an opportunity to learn about recent developments and research directions in the field of image compression. In particular, lossless and near-lossless compression of multi- and hyperspectral images still remains current, since such images constitute data arrays that are of extremely large size with rich information that can be retrieved from them for various applications. Another important aspect is the impact of lossless compression on image classification and segmentation, where a reasonable compromise between the characteristics of compression and the final tasks of data processing has to be achieved. The problems of data transition from UAV-based acquisition platforms, as well as the use of FPGA and neural networks, have become very important. Finally, attempts to apply compressive sensing approaches in remote sensing image processing with positive outcomes are observed. We hope that readers will find our book useful and interestin
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