This research aims to study the optical characteristics of semiconductor quantum dots (QDs) composed of CdTe and CdTe/CdSe core-shell structures. It utilizes the refluxed method to synthesize these nanoscale particles and aims to comprehend the growth process by monitoring their optical properties over varied periods of time and pH 12. Specifically, the optical evolution of these QDs is evaluated using photoluminescence (PL) and ultraviolet (UV) spectroscopy. For CdTe QDs, a consistent absorbance and peak intensity increase were observed across the spectrum over time. Conversely, CdTe/CdSe QDs displayed distinctive absorbance and peak intensity variations. These disparities might stem from irregularities in forming selenium (Se) layers a
... Show MoreIn this work we study the influence of the laser pulse energy and ablation time on the aluminum nanoparticles productivity during nanosecond laser ablation of bulk aluminum immersed in liquid.
Aluminum nanoparticles were synthesized by pulsed laser ablation of Al targets in ethanol for 3-8 minutes using the 1064 nm wavelength of a Nd:YAG laser with energies of 300-500 mJ per pulse.The laser energy was varied between 300 and 500 mJ/pulse, whereas the ablation time was set to 5 minutes. UV-Visible absorption spectra was used for the characterization and comparison of products.
It is difficult to perform real time object detection in Uncrewed Aerial Vehicle(UAV) based video surveillance because of the dynamic movement of camera, scale, occlusion, variation of illumination and limited power availability on-board of the computer. Purpose: In this paper of researches, the author suggests the proposed UAV Spatial-Temporal Network(UAV-STNet), which is a hybrid model of spatio-temporal deep learning model that is expected to improve the accuracy of the detection, balance of time, and real-time performance. Approaches: techniques: The proposed framework incorporates U-Net representing the system of total encoder involving extraction of multiscale space features mode, Transformer attention module which will involve global
... Show MoreSamples prepared by using carbon black as a filler material and phenolic resin as a binder. The samples were pressed in a (3) cm diameter cylindrical die to (250)MPa and treated thermally within temperature range of (600-1000)oC for two and three hours. Physical properties tests were performed, like density, porosity, and X-ray tests. Moreover vicker microhardness and electric resistivity tests were done. From the results, it can be concluded that density was increased while porosity was decreased gradually with increasing temperature and treating time. In microhardness test, it found that more temperature and treating time cause more hardness. Finally the resistivity was decreased in steps with temperature and treating time. It can be c
... Show MoreThin films of pure polycarbonate (PC) with anthracene doping PC films for different doping ratios (10, 20, 30, 40, 50 and 60 ml) were prepared by using a casting method. The influence of anthracene doping ratio on photo-fries rearrangement of polycarbonate was systematic investigated. Furthermore, pure PC and anthracene doping PC films were irradiated via UV light at a wavelength (254 nm) for different periods (5, 240, 288, and 360 hrs). The photo-fries rearrangement occurring in pure PC and anthracene doping PC films were monitored using UV and FTIR spectroscopies. The photo-fries rearrangement leads to scission the carbonate linkage and formation phenylsalicylate and dihydroxybenzophenes. The result of the UV spectrum confirms disappea
... Show MoreThe method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par
... Show MoreA robust video-bitrate adaptive scheme at client-aspect plays a significant role in keeping a good quality of video streaming technology experience. Video quality affects the amount of time the video has turned off playing due to the unfilled buffer state. Therefore to maintain a video streaming continuously with smooth bandwidth fluctuation, a video buffer structure based on adapting the video bitrate is considered in this work. Initially, the video buffer structure is formulated as an optimal control-theoretic problem that combines both video bitrate and video buffer feedback signals. While protecting the video buffer occupancy from exceeding the limited operating level can provide continuous video str
... Show MoreImproving the quality of health services in the health sector is an important and necessary matter that must be taken care of and improved, and this study seeks to demonstrate the role of quality costs in improving the quality of health services and achieving a high level of quality to satisfy the beneficiaries and to provide health services of good quality, and the research concluded that the main point of service provision Good health is the costs of prevention and evaluation (costs of quality conformity) and attention to it, and that technical competition contributes greatly to the development of the level of quality, as well as the use of health and medical staff with competent expertise, and that the costs of internal failure and th
... Show MoreAt the heart of every robust economy is a vital banking system. The functional banking system can effectively perform several functions such as mobilizing savings, allocating credit, monitoring managers, transforming risks, and facilitating the financial transactions. This paper aims to measure the impact of banking system development on economic growth in Iraq. Credit to private sector divided by GDP used as a proxy of banking development. Real per capita GDP used as a proxy of economic growth. By using Autoregressive Distributed Lag (ARDL) model, the paper finds that the undeveloped Iraqi banking system could not promote economic growth in the country. Therefore, a variety of policies need to be taken to spur the role of bankin
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