Many geophysical methods have been applied to locate groundwater in Nigeria’s rural and urban villages. Locating groundwater in low permeability formations like shales and siltstones is even more challenging due to the difficulty of mapping fracture zones within these formations. The fracture zones serve as potential aquifers in low permeability formations and have been the object of groundwater search in shales, siltstones and other low permeability formations. The electrical resistivity method has proven helpful in fracture mapping within low permeability formations due to the existing resistivity contrast usually observed between the fractured and non-fractured sections in the Shales and Siltstones. Three vertical electrical geosounding datasets (VES 1, VES 2 and VES 3) were acquired in the Schlumberger configuration, using a maximum current electrode spacing of 200m to delineate the fracture zones based on their electrical resistivities. The acquired datasets were processed and modelled using IP12 Win software, while the processed datasets were correlated with local geology to estimate the depths of the fractured shales in the area. Results show five modelled geo-electric layers with depths to the fractured shales ranging from 17-25m, while aquifer thicknesses range from 7 to 12m. Aquifer resistivities range from 58 - 115 ohm-m. The curves are primarily of the QH type. One of the Vertical Electrical Sounding Data points (VES 2) encountered an anomalously low resistivity zone at a depth range of 5 to 8m which was interpreted as a galena lode. The low resistivity zone has been confirmed through exploratory drilling to tie with Lead-Zinc lodes at a depth of 8m.
Mersing is one of the places that have the potential for wind power development in Malaysia. Researchers often suggest it as an ideal place for generating electricity from wind power. However, before a location is chosen, several factors need to be considered. By analyzing the location ahead of time, resource waste can be avoided and maximum profitability to various parties can be realized. For this study, the focus is to identify the distribution of the wind speed of Mersing and to determine the optimal average of wind speed. This study is critical because the wind speed data for any region has its distribution. It changes daily and by season. Moreover, no determination has been made regarding selecting the average wind speed used for w
... Show MoreThe study investigates the water quality of the Orontes River, which is considered one of the important water recourses in Syria, as it is used for drinking, irrigation, swimming and industrial needs. A database of 660 measurements for 13 parameters concentrations used, were taken from 11 monitoring points distributed along the Orontes River for a period of five years from 2015-2019, and to study the correlation between parameters and their impact on water quality, statistical analysis was applied using (SPSS) program. Cluster analysis was applied in order to classify the pollution areas along the river, and two groups were given: (low pollution - high pollution), where the areas were classified according to the sources of pollution to w
... Show MoreThis paper proposes a new encryption method. It combines two cipher algorithms, i.e., DES and AES, to generate hybrid keys. This combination strengthens the proposed W-method by generating high randomized keys. Two points can represent the reliability of any encryption technique. Firstly, is the key generation; therefore, our approach merges 64 bits of DES with 64 bits of AES to produce 128 bits as a root key for all remaining keys that are 15. This complexity increases the level of the ciphering process. Moreover, it shifts the operation one bit only to the right. Secondly is the nature of the encryption process. It includes two keys and mixes one round of DES with one round of AES to reduce the performance time. The W-method deals with
... Show MoreSecure storage of confidential medical information is critical to healthcare organizations seeking to protect patient's privacy and comply with regulatory requirements. This paper presents a new scheme for secure storage of medical data using Chaskey cryptography and blockchain technology. The system uses Chaskey encryption to ensure integrity and confidentiality of medical data, blockchain technology to provide a scalable and decentralized storage solution. The system also uses Bflow segmentation and vertical segmentation technologies to enhance scalability and manage the stored data. In addition, the system uses smart contracts to enforce access control policies and other security measures. The description of the system detailing and p
... Show MoreThe type of groundwater in the studied area is slightly brackish. In general, the dominant water type is calcium-sulfate. The reasons behind these different chemical groundwater types can be referred to the active ion exchange between the groundwater of the Dammam aquifer and Rus Formation. The groundwater of the Dammam unconfined aquifer is not suitable for human drinking in all the parameters properties. The groundwater class is fair in the Qasir Al-Ukhaider area, while the Shebcha area and Al-Salman area are poor class except the eastern part of Al-Salman area is very poor.
Background: Low birth weight (LBW) is the main leading cause of infant death. It is contributing to a variety of short and long term poor health outcomes. Determination of risk factors associated with LBW is important to select a suitable action to prevent or reduce this outcome. Studies on LBW and maternal risk factors in the Kurdistan region of Iraq are scarce.
Objectives: This study aimed to determine risk factors associated with Low birth weight in Sulaimania city, Kurdistan region of Iraq.
Cases and Methods: This study was carried out in the Maternity Hospital in Sulaimania from first of July, 2019 to first of February, 2020. Participants were 300 randomly selected mothers who gave a live birth. The questionnaire form, which c
Image classification can be defined as one of the most important tasks in the area of machine learning. Recently, deep neural networks, especially deep convolution networks, have participated greatly in end-to-end learning which reduce need for human designed features in the image recognition like Convolution Neural Network. It is offers the computation models which are made up of several processing layers for learning data representations with several abstraction levels. In this work, a pre-trained deep CNN is utilized according to some parameters like filter size, no of convolution, pooling, fully connected and type of activation function which includes 300 images for training and predict 100 image gender using probability measures. Re
... Show MoreThe Elliptic Curve Cryptography (ECC) algorithm meets the requirements for multimedia encryption since the encipher operation of the ECC algorithm is applied at points only and that offer significant computational advantages. The encoding/decoding operations for converting the text message into points on the curve and vice versa are not always considered a simple process. In this paper, a new mapping method has been investigated for converting the text message into a point on the curve or point to a text message in an efficient and secure manner; it depends on the repeated values in coordinate to establish a lookup table for encoding/ decoding operations. The proposed method for mapping process is&
... Show MoreThe purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be
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