The sustainable development according to the United Nation, listed firms throughout globally now routinely provide sustainability data. However, there is not enough information on Sustainability Performance Quality (SPQ) in the majority of emerging economies, including Malaysia. This study looks at how the SPQ of the top 100 Malaysian-listed businesses is affected by factors as connected with corporate governance (e.g., board meeting, board size, and board ethnic diversity). Utilizing 500 firm-year data, a longitudinal sample of 500 nonfinancial firms on the Bursa Malaysia for 2015-2019 is employed in this study. The findings from the analysis using the panel regression demonstrated that: ethnic diversity and board siz

The Russian foreign policy of the post-cold-war era faced dilemmas in the light of the international and regional realities of the disintegration of the Soviet Union and the formation of a new unipolar international order led by the United States of America. Thus, Russian foreign policy-making was divided over the nature of the foreign policy to be followed. The achievement of the Russian goals, especially as the objectives of Russian foreign policy have been set within the framework of trying to regain the status and leading role, as well as the establishment of some fundamental changes to be consistent with the new international situation of the post-one The Russian Federation has adopted in the sphere of its foreign policy to the vari

Numerous regions in the city of Baghdad experience the congestion and traffic problems. Due to the religious and economic significance, Al-Kadhimiya city (inside the metropolitan range of Baghdad) was chosen as study area. The data gathering stage was separated into two branches: the questionnaire method which is utilized to estimate the traffic volumes for the chosen roads and field data collection method which included video recording and manual counting for the volumes entering the selected signal intersections. The stage of analysis and evaluation for the seventeen urban roads, one highway, and three intersections was performed by HCS-2000 software.The presented work plots a system for assessing the level of service

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

In this paper, the system of the power plant has been investigated as a special type of industrial systems, which has a significant role in improving societies since the electrical energy has entered all kinds of industries, and it is considered as the artery of modern life.

   The aim of this research is to construct a programming system, which could be used to identify the most important failure modes that are occur in a steam type of power plants. Also the effects and reasons of each failure mode could be analyzed through the usage of this programming system reaching to the basic events (main reasons) that causing each failure mode. The construction of this system for FMEA is dependi

Carbon nanotubes were prepared by an arc-discharge method,
under different values of pressure of oxygen gas. The structure of
multi-walled carbon nanotubes powders has been characterized by
low-angle X-ray diffraction .The morphology of carbon nanotube
powder was examined by transmission electron microscope. The
capacitance-voltage and current- voltage (dark and illumination
current) characterization were measured under different values of
pressure (10-3, 10-4, 10-5) mbar of oxygen gas

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.