Board Quality and Risk Disclosure: Evidence from Saudi Arabian Publicly Listed Companies

Abstract This paper investigates the effect of the board quality on risk reporting in specific social and cultural context of Saudi Arabia for a sample of 423 company-year observations over the period 2015-2018. The paper utilizes a comprehensive risk reporting index and self-constructed index of board quality to measure the main variables. Using pooled OLS regression models, our results suggest that there is a positive and significant relationship between the quality of the board of directors and risk reporting in Saudi non-financial firms. In addition, this finding is consistent with the disaggregation of the risk disclosure index into mandatory versus voluntary risk disclosures and the disclosure of financial and non-financial risk disclosures. Such findings suggest that the quality of the board of directors helps to eliminate information asymmetry and agency costs. Finally, the findings of this study can prove to be of great value to market regulators in their attempts to improve the corporate governance in Saudi Arabia and can be extended to include other countries in the MENA region

Reproductive Abuse and the Sterilization of Women of Color

Women of color have long suffered targeted and systematic racial discrimination and attempts to control their populations by the state. Well after eugenic rhetoric and policies’ prime in the 1930s and 1940s, and the Civil Rights movements of the mid-century, Chicana, Black, and Indigenous women continued to be victimized by state-sanctioned eugenic policy. This paper examines the way that eugenic rhetoric and policy evolved from the first sterilization laws in the nation passed in California that targeted criminality to later legislation and rhetoric that explicitly targeted racial minorities

Vega, Capital Ratios, and Real Estate Lending

The 2007 financial crisis revealed how excessive bank risk threatens financial system stability. This paper studies two aspects of the risk-taking incentives of banks– CEO compensation and capital. The vega of a bank executive’s equity compensation measures how compensation changes relative to the banks’ stock volatility. If CEO compensation vega is high, I expect the CEO to take more risk in areas where he exercises control. Conversely, if regulators demand that banks invest their own capital to encourage conservative behavior, then I expect risk-taking to be lower. This paper confirms that higher vega and lower capital ratios are associated with more real estate lending by bank holding companies in the U.S. between 2000 and 2014. The negative relation between capital ratios and real estate lending exists in almost all subsamples. However, the positive relation between vega and real estate lending is only significant among small well-capitalized banks, and after the financial crisis

Toward a Robust Sparse Data Representation for Wireless Sensor Networks

Compressive sensing has been successfully used for optimized operations in wireless sensor networks. However, raw data collected by sensors may be neither originally sparse nor easily transformed into a sparse data representation. This paper addresses the problem of transforming source data collected by sensor nodes into a sparse representation with a few nonzero elements. Our contributions that address three major issues include: 1) an effective method that extracts population sparsity of the data, 2) a sparsity ratio guarantee scheme, and 3) a customized learning algorithm of the sparsifying dictionary. We introduce an unsupervised neural network to extract an intrinsic sparse coding of the data. The sparse codes are generated at the activation of the hidden layer using a sparsity nomination constraint and a shrinking mechanism. Our analysis using real data samples shows that the proposed method outperforms conventional sparsity-inducing methods.Comment: 8 page

Study of Sorptivity of Self-Compacting Concrete with Different Chemical Admixtures

The influence of chemical admixtures on the properties of Self-Compacting Concrete (SCC) was investigated. All types of used admixtures were the same percentage of 1.4% according technical data. The water – cement ratio was maintained at 0.36 for all mixes [8] [9].The paper presents test results for acceptance characteristics of flow ability, resistance against segregation, and passing ability of self-compacting concrete in fresh state. Further, mechanical properties of hardened concrete such as compressive, tensile and flexural strength at the ages of 7 and 28 were also determined, and results of Absorption and sorptivity result are included here.The results indicate that Sika ViscoCrete 3425 and AddiCrete BVS 100 give better results for all tests

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

Rate-distortion Balanced Data Compression for Wireless Sensor Networks

This paper presents a data compression algorithm with error bound guarantee for wireless sensor networks (WSNs) using compressing neural networks. The proposed algorithm minimizes data congestion and reduces energy consumption by exploring spatio-temporal correlations among data samples. The adaptive rate-distortion feature balances the compressed data size (data rate) with the required error bound guarantee (distortion level). This compression relieves the strain on energy and bandwidth resources while collecting WSN data within tolerable error margins, thereby increasing the scale of WSNs. The algorithm is evaluated using real-world datasets and compared with conventional methods for temporal and spatial data compression. The experimental validation reveals that the proposed algorithm outperforms several existing WSN data compression methods in terms of compression efficiency and signal reconstruction. Moreover, an energy analysis shows that compressing the data can reduce the energy expenditure, and hence expand the service lifespan by several folds.Comment: arXiv admin note: text overlap with arXiv:1408.294

FLEXURAL BEHAVIOR OF RC BEAMS WITH OPENING

Providing an opening in beam develops cracks around the opening due to stress concentration. In this paper an experimental works conducted to study the behavior of RC beam with different shapes of opening with varying diameters at different locations. This paper presents the behavior of RC beam with opening unstrengthened by additional reinforcement. In this experimental study 27 beams were casted, one beam without opening as a control beam and the remaining beams were provided with opening. These beams were tested under four-point loading. The effect of size of opening with different locations was studied in terms of ultimate failure load, maximum deflection and failure mode. From the test results, it could be concluded that the ultimate load carrying capacity of the RC beam at shear zone with opening was maximum reduction but at flexure zone showed minimum reduction. Rectangular opening increased the ultimate load reduction than square opening by (4%), while the circular opening reduced the ultimate load reduction than square opening by (8%)