The current pandemic (COVID-19) currently is great importance at all levels due to its comprehensiveness in its impact on the global economy, as well as it has displaced a number of companies from positions that have always occupied this decline as a result of improper practices and poor management, and the pandemic was the main driver of the market in financial fluctuations. It is expected that it will affect production and sales and, as a result, the expected profits, and then on the credibility of the financial statements and the exposure of companies to bankruptcy, and it will be the opposite of what was disclosed in those statements. Therefore, some accounting treatments should be carried out and some financial instruments derived therefrom, and working on finding an accounting framework that uses some types of contracts The research aims to analyze the risks facing companies, exposure to different and appropriate accounting approaches and treatments, and knowledge search to carry out reforms in accordance with international financial reporting standards and enable it to control risks effectively and successfully, and that the application of the framework helps to Risk Management and Reducing its Consequences The researchers followed the case study on a sample of service companies (Baghdad Transport and Real Estate Investment Company). It was reached to strengthen the financial position by acquiring financial assets as a result of accounting treatments for derivatives and employing gains with hedged financial assets that enhance their ability to continue and address risks before they occur. Controlling risks using these modern derivative tools is an essential issue for companies based on the returns of these tools, such as controlling regular financial flows, achieving capital gains and reducing risks. Risk and ensure its continuity and then rise to competition.
Background Viscoelastic soluble polymeric additives have been used successfully for a long time as drag reducers in pipelines carrying commercial liquids like crude oil. Most of these polymers suffer from irreversible degradation when exposed to high shearing zones as in valves, elbows, and pumps which reduces, or eliminates, its flow enhancement effect. Insoluble additives were proven to be an effective drag reducer that overcomes the degradation drawback of soluble additives. On the other hand, insoluble additives suffer from the lack of viscoelasticity which limits their use as flow enhancers. The creation of complexes from soluble and insoluble additives is a field of research that is rarely explored despite its importance in introducing new flow enhancement methods for a higher drag reduction performance. The present work introduces a new surfactant–solid complex as a drag-reducing agent for turbulent flow in pipelines. Results The surfactant, solid, and their complexes’ drag reduction performance was tested in a closed-loop turbulent flow liquid circulation system, while rheological characteristics of the soluble additives were tested using a standard rheometer. All the surfactant solutions showed non-Newtonian shear thinning behavior in all the investigated concentrations that ranged between 500 and 1300 wppm. The initial experimental result indicated that the surfactant solution's drag reduction performance was higher than that of the solid suspensions. On the other hand, the drag reduction performance was enhanced by 52% when creating a 1300 wppm surfactant–2000 wppm solid complex. This improvement in the drag reduction performance is due to the formation of surfactant–solid-enforced aggregates with high resistance to shear forces and high turbulence suppression efficiency. Conclusions The present work introduces a new drag reduction solid–surfactant complex by creating aggregates combining the viscoelastic properties of surfactants with the resistance to high shear forces exerted by the solid particles. The polar nature of the surfactant micelles that form in single-phase flow systems contributed significantly to trapping the solid's micro-particles as enforcement to resist the shearing forces applied by the turbulent flow system.
Gallium nitride (GaN) thin film was grown by Nd: YAG pulsed laser ablation with two laser ablation energies. The optical band gaps and crystallinities of the specimens were studied to determine the optimal energy applied. The obtained results ensure that the physical properties of the prepared samples are directly related to the used laser energy. The XRD result exhibited three peaks of hexagonal GAN (h-GaN) nano-particles at 2θ = 34.54°, 37.49° and 48.19 from the (002), (100) and (200) planes, respectively. The ablation energy of 1600 mJ showed a high peak intensity. The samples fabricated at laser energy of 1400 mJ showed the maximum energy bandgap of 3.62 eV at room temperature. High-performance GaN/Si photo-detector was prepared using a drop casting. The spectral response was approximately 2.34 Am/W, and device detectivity was approximately 557.887 × 10¹² cm Hz1/2 W⁻¹ in the UV spectral region.
In the process of this work, the Pulsed Laser Deposition (PLD) technique was used to deposit nanoparticles of pure titanium oxide (TiO2) onto a glass substrate at temperatures ranging from 100 to 400 degrees Celsius. This experiment made use of a Nd: YAG laser that had its frequency-doubled. The laser had a wavelength of 532 nanometers and an average laser strength of 800 millijoules. To explore the optical properties, transmittance spectrometry measurements were carried out for both visible and ultraviolet wavelengths. These measurements were carried out. The results of the optical transmittance test showed that it was more than 80 percent, which indicates that it is suitable for use in applications involving solar cells. The research was conducted on a number of optical constants, including the refractive index, the absorption coefficient, and the attenuation coefficient, and the values of these optical constants were determined. The value of the refractive index was found to be 2.49 when measured at a temperature of 400 degrees Celsius and a wavelength of 550 nanometers. Additionally, it was feasible to calculate the density of the titanium dioxide coating, which came out to be 3.6881 grams per cubic centimeter after the calculation was complete. The use of a numerical equation was utilized to ascertain the connection that exists between density and base temperature. It is an empirical equation that may be employed in the process of calculating the density of the components that are being used, and it has the potential to do so successfully. This equation is one of a kind since it was produced via the use of a theoretical computer program, and it is specific to the results that were obtained from the research.
Recently, most of the researchers focused on provide lower greenhouse gas emissions that emitted from diesel engines by using renewable fuels to be good alternative to the conventional diesel fuel. Ethanol can be derived from renewable sources such as sugar cane, corn, timber and dates. In the current study, the ethanol fuel used in the tests was derived from the dates. The effects of using exhaust gas recirculation (EGR) diesel-ethanol blend (E10) with on engine performance and emissions characteristics have been studied in diesel engine under various engine loads. This study focused the use of oxygen in the bio-ethanol composition to compensate for the decrease occurred by the addition of EGR, which improves the engine performance and reduces its emissions. In this experiment, the ratios of EGR were 10%, 20% and 30% as well as 10% ratio of ethanol was blended into the diesel fuel blend under fixed engine speed. A traditional (without additional systems to reduce emissions) four cylinders direct injection (DI) diesel engine was used for all tests. The brake specific fuel consumption (BSFC) increased with increasing the EGR ratio by 10%, 20% and 30% by 18.7%, 22.4% and 37.4%, respectively. The thermal efficiency decreased under variable conditions of engine load for different ethanol blends. Furthermore, the emissions of NOX decreased when fuelled B10 into the engine in comparison with diesel under low engine load. Significant reduction in the NOx emissions were found when applied EGR in the tests than to the absence EGR for E10 blend and diesel. The NOx reduction rate was 12.3%, 30.6% and 43.4% when EGR rate was 10%, 20% and 30%, respectively. In addition, the concentrations of HC and CO emissions decreased more by 8.23% and 6.4%, respectively, when using E10 in comparison with the diesel for various engine loads. It is indicated that the oxygen reduction by EGR effect was compensated from ethanol blend combustion. The results showed that the combination use of E10 and EGR leads to significant reduction in engine emissions accompanied with partial reduction in the engine performance.
The fuel combustion in diesel engines can be improved by adding nanomaterials to the fuel which result in an reduction in pollutant emissions and enhance the quality of fuel combustion. The engine performance and soot nanoparticles characteristics were evaluated in this study with adding nanoparticles of copper oxide (CuO2) to the rapeseed methyl ester (RME) and diesel under variable engine speeds. The addition of CuO2 to the RME significantly improve brake thermal efficiency (BTE) and decline the brake specific fuel consumption (BSFC) by 23.6% and 7.6%, respectively, compared to the neat RME and diesel fuel. The inclusion CuO2 nanoparticles into the RME and diesel led to decrease the concentration and number of particulate matter (PM)by 33% and 17% in comparison with neat RME and diesel without nano additives, respectively. Moreover, PM is significantly decreased by 31.5% during the RME combustion in comparison with neat RME and diesel under various engine speeds. It was also obtained that the number of emitted particles (npo) reduced by 23.5% with adding nanoparticles to the RME in comparison with diesel, while the diameter of soot nanoparticles (dpo) increased by 8.6% in comparison with diesel. Furthermore, the addition CuO2 to the RME decreased the size and number of particles more than to the diesel fuel.
This study is geared toward generating highly stabilized partially premixed flames at various levels of turbulence and partially premixing. Therefore, with the help of the laser-induced breakdown spectroscopy (LIBS) technique, a new burner was constructed and employed to quantitatively estimate the mixture equivalence ratio (Φ) within the flame. Two turbulence generator disks, five degrees of partial premixing, and two fuels were used to assess the flame stability. Natural gas (NG) and liquefied petroleum gas (LPG) were used as fuels. The LIBS spectrum's most common atomic emission lines which include hydrogen, nitrogen, oxygen, and carbon, were chosen to establish the correlation between emission lines' intensity and the flame's mixture equivalence ratio. The results showed that the stability of NG flame was less sensitive to the variation of the partially premixing levels. In contrast, the LPG flames were more susceptible to the variation of the mixing degree. At a lower level of partially premixing, NG flames were more stable, and as the mixing degree increased, the stability of NG flames was reduced compared to LPG flames. In addition, the results showed that the equivalence ratio radial profiles are more homogeneous and have lower RMS fluctuation for the wider slot of the turbulence generator disc. Furthermore, the larger turbulence generator disk's higher turbulent intensity contributed in posting the mixing process and enhancing mixture homogeneity over even shorter recess distances than the smaller disk generator.
Zn doped and Sn:Zn co‒doped CdS semiconductor nanostructured have been fabricated by chemical reaction, then thin film samples have been deposited by pulsed laser method. The coated films have a hexagonal phase as demonstrated by X‒ray (XRD) diffraction with fine Nano-crystallites with crystallite size between (2.6–2.85 nm). The UV–visible test showed good transmittance and obtained energy gap increased for Zn:CdS (3.30 eV) compared to bulk CdS. Electrical examination revealed that some samples have an enhancement in current with increased applied voltage in Sn ions adding to the Zn:CdS composition might be due to adding sub-levels electronic transitions. Morphology characterization was examined by atomic force (AFM) microscopy and was declared that the samples were quite smooth and increased roughness with increased co‒doping ions.
Most of the energy consumption in a hot and dry area is used for the air‐conditioning systems. This study aims to investigate the possibility of reducing the electricity consumption in air conditioners using ground cold energy to cool the hot fluid in the pipes. Several experiments were carried out to investigate the performance of the proposed system to be used in the weather conditions of Baghdad city (i.e., hot and dry). Two configurations of ground source heat exchangers (GSHEs) were developed and constructed. The first configuration comprised coil type with two different materials (copper and polyvinyl chloride [PVC]). The second configuration was the 3U type, which was made from copper, PVC, and galvanized. Three water flow rates were considered (5, 10, and 15 L/min) with water inlet temperatures (80°C, 70°C, and 60°C). The experiments' results showed that the type of material of the pipe has a significant influence on both the heat transfer effectiveness and the system performance. Copper tubes were the best type of heat exchanger (type coil) to be used in this regard. The highest recorded values of the heat exchange rate were 5.81, 4.81, 2.72, 1.60, and 1.32 kW with an inlet temperature of 80°C and a flow rate of 5 L/min for the case of copper coil, copper 3U, galvanized 3U, PVC profile, and PVC 3U, respectively. These findings can be used as a guideline for future studies of GSHEs, particularly for the applications fixed in unsaturated soils.
Seven all-optical logic gates based on hybrid plasmonic squared-shaped nanoring resonators and strips are proposed, designed, and numerically analyzed using finite element method with COMSOL software package version 5.5. Constructive and destructive interferences between the input port(s) and the control port(s) are the main operating principles used to produce the proposed gates. The ratio of output optical power to the input power at a single port which is called the transmission threshold is selected to be 30% and the resonance wavelength is 1310 nm. All the hybrid plasmonic logic gates are performed in a single structure of 400 nm × 400 nm dimensions and the performance is measured according to the values of transmission at the output port versus a wavelength range from 800 to 2000 nm, contrast ratio, modulation depth, and insertion loss. The transmission exceeds 100% in five gates, 146% at NOT and NAND gates, 202.3% at OR, AND, and XNOR gates. The modulation depth scores are 99.75% at the XNOR gate, 98.5% at the NOR gate, 97.67% at OR, AND, NOT, and NAND gates, and 95.29% for the XOR gate.
Batch adsorption treatment using Iraqi bentonite as a natural adsorbent was adopted in this study to decontaminate actual ¹³⁷ Cs radioactive wastewater from the Al-Tuwaitha Nuclear Research Center, located south of Baghdad. The bentonite characterization was applied before and after treatment, using chemical compositions analyses, X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), Brunauer–Emmett–Teller (BET) surface area analysis and Fourier-transform infrared spectroscopy (FT-IR). The batch adsorption mode was applied with the initial radioactivity concentration (1440.5 Bq/L), solid/liquid ratio (1 g/L), pH (6–8), contact time (1.5 h), and temperature (298°K). The adsorption experiments showed a decontamination removal efficiency of about 95.66% of ¹³⁷ Cs. A Freundlich adsorption isotherm model was approved for the adsorption of ¹³⁷ Cs, with a coefficient of determination R ² = 0.998. A pseudo-second-order model fitted well with the adsorption of ¹³⁷ Cs, with R ² = 0.983. The positive value of ΔH° in the thermodynamic results indicated that the adsorption process was endothermic physisorption (ΔH° = 15.01 kJ mol ⁻¹ ), spontaneous and favorable (ΔG° = −7.66 kJ mol ⁻¹ K ⁻¹ ), with a very low degree of disorder (ΔS° = 0.076 kJ mol ⁻¹ K ⁻¹ ).
Congestion control plays an essential role on the internet to manage overload, which affects data transmission performance. The random early detection (RED) algorithm belongs to active queue management (AQM), which is used to manage internet traffic. The RED is used to eliminate weakness in default control of the Transport Control Protocol (TCP) drop-tail mechanism. The drawback of RED is parameter tuning, while adaptive RED (ARED) automatically adjusts these parameters. In this study, the suggested algorithm, the Markov decision process RED (MDPRED) uses the Markov decision process (MDP) to suitably adapt values for queue weight in the RED algorithm based on average queue length to enhance the performance of the traditional RED during TCP Slow Startup phase. This study is conducted based on fluctuations among the rate of service, queuing weight, and the mean queue length by using open-source network simulator NS3. The study shows efficient results by fluctuating end-to-end packet throughput and fast response to the inception of congestion in the network. The modified algorithm achieves a low level of drop packets by evaluating the results with other five algorithms, which is done by increasing the algorithm’s response when the average queue size becomes close to the maximum queue length threshold.
The Vehicular Cloud Environment (VCE) is a brand-new study field in cloud and vehicular network.It gives cars networking and sensor capabilities for V2I or V2V communication with roadside infrastructure. Cloud applications are frequently used in traffic control and road safety. A hybrid technical solution that utilises vehicle resources, cloud infrastructure, and Internet of Things (IoT) settings is needed for effective vehicular communication networking. VCE is a smart vehicular communication architecture that promotes system security, enhanced vehicle control, and self-driving cars. Due to the integration of unknown vehicles and infrastructure via the public network, security and privacy seem to be significant challenges with VCE. In this regard, we propose a PSEBVC, which is a provably secure elliptic curve cryptography (ECC) and biometric based authentication system for VCE employing smartphones. In the face of active and passive adversaries, the offered framework obtains the majority of security features and properties for secure communication. We also propose and prove a formal security model based on the random oracle concept. We also demonstrate the security analysis using the Scyther tool. In the same scenario, we evaluate the performance of our protocol against that of other frameworks. The proposed system, according to our findings, is both secure and efficient in terms of communication and processing overhead. The proposed architecture, according to our findings, provides all needed security criteria while also permitting effective communication.
The automated sorting systems are used in the industrial sectors to increase the rate of production. This research developed the sorting system by using a vision machine to detect the matching of capturing image with the storage base image. The system will be matching and sorting in real-time with 5 cm/s conveyor belt speed. The vision system is based on three stages to arrive at the sorting decision. The first stage is to covert the capturing image to a binary image, the second stage is applying edge detection of the product, and the third stage is matching this result with the base image. The system was successful to sort any product with complexity in shape and with high efficiency. The system sorting can be detected and sorted any product/machine element at any position or orientation. The system uses real-time analysis in order to provide the required results. The results arrived at the sorting gate at the end conveyer belt of the system if open that means the product matching. Three different products were selected in order to investigate the response and the accuracy of the results. It was found that the maximum of error to detect the product is not exceeding 2% for all cases.
Since early 2020, Coronavirus Disease 2019 (COVID-19) has spread widely around the world. COVID-19 infects the lungs, leading to breathing difficulties. Early detection of COVID-19 is important for the prevention and treatment of pandemic. Numerous sources of medical images (e.g., Chest X-Rays (CXR), Computed Tomography (CT), and Magnetic Resonance Imaging (MRI)) are regarded as a desirable technique for diagnosing COVID-19 cases. Medical images of coronavirus patients show that the lungs are filled with sticky mucus that prevents them from inhaling. Today, Artificial Intelligence (AI) based algorithms have made a significant shift in the computer aided diagnosis due to their effective feature extraction capabilities. In this survey, a complete and systematic review of the application of Machine Learning (ML) methods for the detection of COVID-19 is presented, focused on works that used medical images. We aimed to evaluate various ML-based techniques in detecting COVID-19 using medical imaging. A total of 26 papers were extracted from ACM, ScienceDirect, Springerlink, Tech Science Press, and IEEExplore. Five different ML categories to review these mechanisms are considered, which are supervised learning-based, deep learning-based, active learning-based, transfer learning-based, and evolutionary learning-based mechanisms. A number of articles are investigated in each group. Also, some directions for further research are discussed to improve the detection of COVID-19 using ML techniques in the future. In most articles, deep learning is used as the ML method. Also, most of the researchers used CXR images to diagnose COVID-19. Most articles reported accuracy of the models to evaluate model performance. The accuracy of the studied models ranged from 0.84 to 0.99. The studies demonstrated the current status of AI techniques in using AI potentials in the fight against COVID-19.
Purpose Pollution from oil operations; exploration, drilling, transfer, transport, refinery and distribution reduce soil quality, and results in the removal of a large amount of soil from annual utilization cycles. Soil quality is an essential asset of sustainable development and is negatively affected by erosion and anthropogenic activity. Co-composting is a biological technique used in the bioremediation of soils, which was investigated in this study. Materials and methods This study focused on the remediation of 1200 m³ of saline contaminated soil from an oil-polluted operational area in Iran. The initial total petroleum hydrocarbon (TPH) content of the soil was between 6.9 and 17.1 g kg⁻¹ and was contaminated with heavy oil. Initial water repellency of the soil was between 1500 and 12,500 S. The remediation procedure commenced with trials in which organic waste of a local sugarcane sugar factory, mixed urea, sugar, and compost mixtures was added to contaminated soils. Results After irrigation and aeration of piles of organic materials and soil over 3 months of operation, the TPH reduced from 4.86, 6.52, and 9.89 to 0.068, 0.080, and 0.109 g kg⁻¹, in the moderately, highly, and very highly polluted soil piles respectively. At the end of the remediation project, following gas chromatography analysis of contaminant content, and in accordance with governmental authorities, recovered soils were added to the surrounding environment to the support growth of the natural ecosystem. Conclusion Soil recovery and remediation utilizing valorization and complimentary local industries have a transferable quality that may be adapted to additional vulnerable sites in droughted and variable edaphic and climatic conditions.
[This corrects the article DOI: 10.1007/s11042-022-12952-7.].
In this work, a high purity FAU-type zeolite catalyst was prepared from shale rock and modiﬁed as a heterogeneous efﬁcient catalyst for biodiesel production from sunﬂower oil. The characterization prop- erties for both of the prepared catalysts were determined using X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDAX), Brunauer–Emmett–Teller (BET), and Fourier-transform infrared spectroscopy (FTIR). The incipient wetness impregnation method was adopted for loading the catalyst with three base precursors: NaOH, KOH, and Ca(OH)3. Different factors affecting transesteriﬁcation reaction onto modiﬁed Na-K-Ca-FAU zeolite were investigated such as; temperature (35, 45, 55, and 65 �C), catalyst concentrations (2, 3,4, 5, and 6 wt%) and the molar ratio of methanol to sunﬂower oil (3:1, 6:1, 9:1 and 12:1). The optimum conditions of transesteriﬁcation reactions were obtained for reaction time (4 h) and agitation rate (700 rpm) in a batch reactor at 65 �C reaction temper- ature, 5% catalyst concentration, and a 9:1 M ratio of methanol to oil. The experimental results showed that the conversion of triglyceride in sunﬂower oil to fatty acid methyl ester (FIME) increased from 48.62 to 91.6% when the FAU zeolite was loaded with 15 wt% of the three bases. The properties of the produced biodiesel were evaluated within the standard performance ASTM D-6751. This study shows that the three base precursors (i.e., NaOH, KOH, and Ca(OH)3) were successfully loaded onto support FAU zeolite and functioned as excellent catalysts for biodiesel production. Theoretical considerations for kinetic modeling in the heterogeneous transesteriﬁcation reaction were investigated using MATLAB programming. The experimental and theoretical considerations for kinetic modeling were ﬁtted well.
Pulsed laser deposition (PLD) is a commonly utilized technology for growing thin films in academia and industry. Compared to alternative deposition processes, the PLD offers more excellent benefits such as adaptability, control over the growth rate, stoichiometric transfer, and an infinite degree of freedom in the ablation geometry. This investigation collected data from five reputable academic databases, including Science Direct, IEEE Xplore, Scopus, Web of Science, and Google Scholar. In this review, we analyzed and summarized 20 empiricals on the impact of pulsed laser deposition on the production nanostructure, including laser wavelength, laser fluence, repetition rate and pulse length of the laser pulse, pulse shaping of the laser spot, plasma generation, distance between substrates and target, angular position of the material, substrate temperature, gas composition, and target material properties. Finally, we show this field's advantages, challenges, and viewpoints and focus on the strengths and weaknesses that can improve the deposition of nanostructure properties for various applications. Therefore, provide fascinating insights into the interaction of these processes in different fields.
In this work, the performance of wavelength division multiplexing based radio over free space optics (WDM-RoFSO) communication system is investigated utilizing OptiSystem 0.7 software. Four weather conditions are adopted in this paper, namely, clear, haze, rain and fog with attenuation losses of 0.2 dB/km, 2.3 dB/km, 4.3 dB/km and 8 dB/km, respectively In addition, a high radio frequency of 30 GHz with high bit rate of 160 Gbps is modulated and carried on optical signal for fifth generation (5G) applications. The dual channel technique is employed in order to enhance the performance parameters of proposed WDM-RoFSO communication system. The enhancement in the link range is about; 46.1%, 35%, 29.4% and 25.9% for clear, haze, rain and fog, respectively.
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