This study was carried out to investigate the effects of magnetized water on accumulated infiltration depth. A test rig was designed and constructed for this purpose was installed at the water tests laboratory of the Department of Water Resources Engineering at the University of aghdad. The investigation was carried out by using two types of soil, different flow velocities throughout magnetizing device and different configuration of magnets over and under the water passage of the magnetizing device. The soils that were used in the experiments are clayey and sandy soils. Six different flow velocities throughout magnetizing device ranged between 0.29 to 1.19 cm/s and ten configurations of arranging the magnets over and under the water passage of the magnetizing device were used. The magnates are sintered neodymium-iron-boron type. Tests results obtained with magnetized water were compared with those of untreated water. Results showed that magnetizing water increases the accumulated infiltration depth for the two types of soil. The highest increase in the accumulated infiltration depth is achieved under low flow velocity throughout the magnetizing device and with ten magnets. This highest increase for the clayey and sandy soils was 98.2% and 34.2%, respectively.
Future generations of wireless communications systems are expected to evolve toward allowing massive ubiquitous connectivity and achieving ultra-reliable and low-latency communications (URLLC) with extremely high data rates. Massive multiple-input multiple-output (m-MIMO) is a crucial transmission technique to fulfill the demands of high data rates in the upcoming wireless systems. However, obtaining a downlink (DL) training sequence (TS) that is feasible for fast channel estimation, i.e., meeting the low-latency communications required by future generations of wireless systems, in m-MIMO with frequency-division-duplex (FDD) when users have different channel correlations is very challenging. Therefore, a low-complexity solution for
... Show MoreObjective: This study aimed to evaluate the effect of coating titanium (Ti) dental implant with polyether ketone ketone (PEKK) polymer using magnetron sputtering on osseointegration, trying to overcome some of the problems associated with Ti alloys. Material and Methods: Implants were prepared from grade (II) commercially pure titanium (CP Ti), then laser was used to induce roughness on the surface of Ti. PEKK was deposited on the surface of Ti implants by radiofrequency (RF) magnetron sputtering technique. The implants were divided in to three groups: without coating (Ls), with PEKK coating using argon (Ar) as sputtering gas (Ls-PEKK-Ar), and with PEKK coating using nitrogen (N) as sputtering gas (Ls-PEKK-N). All the implants were implante
... Show MoreKinetic analysis has received great importance in the fields of sports and biomedicine, as it provides accurate data about the motor performance of athletes and helps in improving performance and preventing injuries, and among the technological tools currently available, artificial intelligence applications such as the (on form) application, which works to analyze performance directly and indirectly and has several advantages where direct analysis of performance is possible and reduce time and costs without referring to the video and analyzing it with analysis programs such as the (kenovea) program, which needs more time and greater experience by the person analyzing it, The research aimed at a comparative study to measure some mechanical v
... Show MoreWireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregati
... Show MoreThe research seeks to identify the dimensions of creative thinking and its impact on the re-engineering of hotel service operations by analyzing the correlation and impact between research variables as well as comparing the research sample The importance of the research comes from the need to motivate managers the importance of creative thinking among workers in the researched hotels because it is an essential part in the re-engineering of hotel services. To achieve this a questionnaire was designed containing (33) items that include the independent research variables (creative thinking) and the accredited (re-engineering the hotel service) and distributed to a sample of (50) individuals represented by (Commissioner Director, Dep
... Show MoreCorrosion experiments were carried out to investigate the effect of several operating parameters on the corrosion rate and corrosion potential of carbon steel in turbulent flow conditions in the absence and presence of sodium benzoate inhibitor using electrochemical polarization technique. These parameters were rotational velocity (0 - 1.57 m/s), temperature (30oC – 50oC), and time. The effect of these parameters on the corrosion rate and inhibition efficiency were investigated and discussed. It was found that the corrosion rate represented by limiting current increases considerably with increasing velocity and temperature and that it decreased with time due to the formation of corrosion product layer. The corrosion potential shifted t
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
Seawater might serve as a fresh‐water supply for future generations to help meet the growing need for clean drinking water. Desalination and waste management using newer and more energy intensive processes are not viable options in the long term. Thus, an integrated and sustainable strategy is required to accomplish cost‐effective desalination via wastewater treatment. A microbial desalination cell (MDC) is a new technology that can treat wastewater, desalinate saltwater, and produce green energy simultaneously. Bio‐electrochemical oxidation of wastewater organics creates power using this method. Desalination and the creation of value‐added by‐products are expected because of this ionic mov