Thermal properties of soils are important in buried structures contact problems. Although laboratory is distinctly advantageous in measuring the thermal conductivity of soil under ideal condition, given the ability to simulate relatively large-scale in place of soil bed, the field thermal conductivity of soil is not yet commonly used in many types of research. The use of only a laboratory experiment to estimate thermal conductivity may be the key reason for overestimation or underestimation it. In this paper, an intensive site investigation including field thermal conductivity tests for six different subsoil strata were performed using a thermal probe method (TLS-100) to systematically understanding the effects of field dry density, water content and soil type. Results were obtained from the alluvial plain lands in the middle part of Iraq, in an attempt to find a correlation between different soil characteristics and the thermal conductivity. It is shown that clayey soil generally had lower thermal conductivity than sandy soil. Thermal conductivity can potentially be affected by the proposed soil low or high plasticity. It is evident that in general, the measured field thermal conductivity value for the lean (low plasticity) silty clay increases with an increase in depth due to the increase of the degree of saturation; however, decreases with an increase in depth for the fat (high plasticity) silty clay. The field water content of the soil in the study obtained here increases so does the thermal conductivity of the soil for most the sites. Further investigations are required, to understand the effects of other environmental conditions with the seasons. This is especially helpful to the future of geotechnical engineering when designing geothermal systems. © 2021 Elsevier Ltd. All rights reserved.
The consensus algorithm is the core mechanism of blockchain and is used to ensure data consistency among blockchain nodes. The PBFT consensus algorithm is widely used in alliance chains because it is resistant to Byzantine errors. However, the present PBFT (Practical Byzantine Fault Tolerance) still has issues with master node selection that is random and complicated communication. The IBFT consensus technique, which is enhanced, is proposed in this study and is based on node trust value and BLS (Boneh-Lynn-Shacham) aggregate signature. In IBFT, multi-level indicators are used to calculate the trust value of each node, and some nodes are selected to take part in network consensus as a result of this calculation. The master node is chosen
... Show MoreThe results of the analysis showed that there is a correlation between ISO 9001 and the competitive advantage, which shows that the implementation of ISO 9001 in the private colleges achieves a competitive advantage through its ability to employ the entrance of quality systems management according to ISO 9001, By focusing on improving the quality of its educational services in accordance with a clear and understandable policy for all and its ability to meet the expectations, expectations and wishes of students and beneficiaries, which leads to lower costs of operations compared to other colleges and achieve a higher level of reliability and quality and value of services provided and rapid respon
... Show MoreMany oil and gas processes, including oil recovery, oil transportation, and petroleum processing, are negatively impacted by the precipitation and deposition of asphaltene. Screening methods for determining the stability of asphaltenes in crude oil have been developed due to the high cost of remediating asphaltene deposition in crude oil production and processing. The colloidal instability index, the Asphaltene-resin ratio, the De Boer plot, and the modified colloidal instability index were used to predict the stability of asphaltene in crude oil in this study. The screening approaches were investigated in detail, as done for the experimental results obtained from them. The factors regulating the asphaltene precipitation are different fr
... Show MoreProblem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
... Show MoreThe research aims to test the two characteristics of the relationship between accounting profits and the stock returns, to find out the suitability of both of them in explaining the relationship between accounting profits and stock returns for joint stock companies registered in the Baghdad Stock Exchange, also aims to reaching the most appropriate specification for the relationship between the two variables of the company’s stock dealing in the Baghdad Stock Exchange, and get a set of results, the most important of which are: the ability of changing for both of these variables in the profits share and the stock level of the profits does not explain more than 9,9% of the market returns of the Iraqi Joint Stock Companies registered i
... Show MoreBP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.
Laboratory studies were conducted at the biological control unit, college of Agriculture, University of Baghdad to evaluate some biological aspects of the predator Chilocorus bipustulatus (Coleoptera: Coccinellidae), which is considered one of the most important predators on many insect pests, especially the scale insect, Parlatoria blanchardi, (Homoptera: Diaspididae) on date palms. The results showed that biological parameters of the predator were varied according to different degree of temperature. Egg incubation period was significantly different and reached to 7.5 and 5.44 day at 25 and 30°C respectively, Fertility was the same 100% at both temperature degrees. Larval growth periods were 17.41 and 16.12 day as well as the mortality
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