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Numerical Modeling of a Pile Group Subjected to Seismic Loading Using the Hypoplasticity Model
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Various simple and complicated models have been utilized to simulate the stress-strain behavior of the soil. These models are used in Finite Element Modeling (FEM) for geotechnical engineering applications and analysis of dynamic soil-structure interaction problems. These models either can't adequately describe some features, such as the strain-softening of dense sand, or they require several parameters that are difficult to gather by conventional laboratory testing. Furthermore, soils are not completely linearly elastic and perfectly plastic for the whole range of loads. Soil behavior is quite difficult to comprehend and exhibits a variety of behaviors under various circumstances. As a result, a more realistic constitutive model is needed, one that can represent the key aspects of soil behavior using simple parameters. In this regard, the powerful hypoplasticity model is suggested in this paper. It is classified as a non-linear model in which the stress increment is stated in a tonsorial form as a function of strain increment, actual stress, and void ratio. Eight material characteristics are needed for the hypoplastic model. The hypoplastic model has a unique way to keep the state variables and material parameters separated. Because of this property, the model can implement the behavior of soil under a variety of stresses and densities while using the same set of material properties.

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
A Novel System for Confidential Medical Data Storage Using Chaskey Encryption and Blockchain Technology
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Secure 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

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Publication Date
Fri Feb 01 2019
Journal Name
Environmental Technology & Innovation
Cadmium removal using a spiral-wound woven wire meshes packed bed rotating cylinder electrode
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Publication Date
Sun Sep 29 2024
Journal Name
International Journal Of Corrosion And Scale Inhibition
Using expired pharmaceutical Clotrimazole as a corrosion inhibitor for stainless steel in acidic media
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Publication Date
Thu Jun 27 2024
Journal Name
Journal Of Image And Graphics
ALL-FABNET: Acute Lymphocytic Leukemia Segmentation Using a Flipping Attention Block Decoder-Encoder Network
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Melanoma, a highly malignant form of skin cancer, affects individuals of all genders and is associated with high mortality rates, especially in advanced stages. The use of tele-dermatology has emerged as a proficient diagnostic approach for skin lesions and is particularly beneficial in rural areas with limited access to dermatologists. However, accurately, and efficiently segmenting melanoma remains a challenging task due to the significant diversity observed in the morphology, pigmentation, and dimensions of cutaneous nevi. To address this challenge, we propose a novel approach called DenseUNet-169 with a dilated convolution encoder-decoder for automatic segmentation of RGB dermascopic images. By incorporating dilated convolution,

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Publication Date
Mon Nov 01 2021
Journal Name
Energies
Solidification Enhancement in a Triple-Tube Latent Heat Energy Storage System Using Twisted Fins
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This work evaluates the influence of combining twisted fins in a triple-tube heat exchanger utilised for latent heat thermal energy storage (LHTES) in three-dimensional numerical simulation and comparing the outcome with the cases of the straight fins and no fins. The phase change material (PCM) is in the annulus between the inner and the outer tube, these tubes include a cold fluid that flows in the counter current path, to solidify the PCM and release the heat storage energy. The performance of the unit was assessed based on the liquid fraction and temperature profiles as well as solidification and the energy storage rate. This study aims to find suitable and efficient fins number and the optimum values of the Re and the inlet tem

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Publication Date
Fri Feb 01 2019
Journal Name
Environmental Technology & Innovation
Cadmium removal using a spiral-wound woven wire meshes packed bed rotating cylinder electrode
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The effect of electrolysis operating parameters on the removal efficiency of cadmium from a simulated wastewater was studied by adopting response surface methodology combined with Box–Behnken Design. As a new electrode design, spiral-wound woven wire mesh rotating cylinder electrode was used for cadmium removal. Current (240–400 mA), rotation speed (200–1000 rpm), initial cadmium concentration (200–600ppm), and cathode mesh number (30–60) were chosen as independent variables while the removal efficiency of cadmium was considered as a response function. The results revealed that the rotation speed has the major effect on the removal efficiency of cadmium. Regression analysis showed good fit of the experimental data to the second-or

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
A study on predicting crime rates through machine learning and data mining using text
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Abstract<p>Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o</p> ... Show More
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Publication Date
Wed Dec 27 2017
Journal Name
Al-khwarizmi Engineering Journal
A New Structure for Cascaded Single-Stage Distributed Amplifier Using Proposed Active Inductor Loads
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A modification to cascaded single-stage distributed amplifier (CSSDA) design by using active inductor is proposed. This modification is shown to render the amplifier suitable for high gain operation in small on-chip area. Microwave office program simulation of the Novel design approach shows that it has performance compatible with the conventional distributed amplifiers but with smaller area. The CSSDA is suitable for optical and satellite communication systems.

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
Digital Data Encryption Using a Proposed W-Method Based on AES and DES Algorithms
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This 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

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Publication Date
Mon Apr 20 2026
Journal Name
International Journal Of Intelligent Engineering And Systems
A Robust Base-layer Design for Hierarchical IoT Intrusion Detection Using Hybrid Deep Learning
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The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines

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