Miracle-dz/UniFAR-FTUs huggingface dataset:
Teaching the Hajj Using Virtual Simulation Technology with Middle School Students in Saudi Arabia

Islamic education in Saudi Arabia is often taught using teacher-centered traditional education methods, which adversely affects students‘ motivation for learning, hence their achievement level. This project presents a technology-based method for teaching Islamic education, especially the Hajj. Virtual simulation technology has the capacity to enhance students‘ motivation to learn, to increase their engagement level, and to give them an opportunity to learn by exploring in a safe environment that is very similar to reality. Teaching the Hajj through virtual simulation technology is the key to a better understanding of the Hajj
Modeling of Creep Behavior of an Argillaceous Rock by Numerical Homogenization Method

This paper is devoted to modeling the creep behavior of argillaceous rock and a comparison with experimental and numerical results from literature. The proposed time dependent modeling is based on a numerical homogenization method, matrix-inclusion material microstructure and a creep micromechanical model. The nonlinear viscosity of the argillaceous matrix is described by the creep model “Modified Time Hardening”, while classical linear elasticity is applied for the calcite and quartz inclusions. The simulation accuracy was analyzed under single and multistage creep test. A satisfactory agreement between the simulation and the experimental results are obtained by assuming the main mineral phases of the Callovo-Oxfordian argillite. It was found that better agreements could be obtained when the multi-scale modeling is performed on sample with a given mineralogical composition and much more precisely volume fraction. The results show how numerical homogenization method is capable of effectively modelling macroscopic creep deformation.
Effects of Dietary Wakame Undaria penatifida and Ascophyllum nodosum Supplements on Growth, Feed Efficiency, and Proximate Compositions of Liver and Muscle of Red Sea Bream*1

In order to investigate Che nutritional value of seaweed as a dietary supplement, red sea bream Chrysophrys major were fed on the control diet without seaweed and on the diets supplemented with Wakame or Ascophyllum at a level of 5% or 10% to the control diet for 10 weeks. The growth and feed efficiency were best in the 5% Wakame diet group, followed by the 5% Ascophyl- lum, the 10% Wakame, the control, and the 10% Ascophyllum diet group. Besides this, the muscle lipid content was slightly higher in the 5% Wakame, the 5% Ascophyllum and the 10 % Wakame diet groups, compared with the control and the 10% Ascophyllum diet groups.
Evaluation of inverter reliability performance due to negative bias temperature instability (NBTI) effects in advance CMOS technology nodes

Negative bias temperature instability (NBTI) is the most concern issue CMOS devices with the scaling down of the CMOS technologies. NBTI effect contributes to P-MOSFET device degradation which later reduce the performance and reliability of CMOS circuits. This paper presents a reliability simulation study based on R-D model on CMOS inverter circuit. HSPICE MOSRA model together with the Predictive Technology Model (PTM) was used as to incorporate the NBTI model in the circuit reliability simulation study for different technology nodes. PTM of High Performance (HP) models of 16nm, 22nm, 32nm and 45nm were used in this simulation study. The atomic hydrogen based model was integrated in the simulation. The results show that in a CMOS inverter circuit, the threshold voltage shift of p-MOSFET under NBTI stressing increased as the year progressed. The threshold voltage shift was observed to increase up to 45.1% after 10 years of operation. The time exponent, n ~ 0.232 of the threshold voltage shift observed indicates that the defect mechanism contributed to the degradation is atomic hydrogen. The propagation delay increased to 19.5% over a 10-year period. s up to 19.5% from the zero year of operation until 10 years of the operation. In addition, the time propagation delay increased as year increased when the technology nodes smaller. The finding is important for understanding reliability issues related to advanced technology nodes in CMOS circuits study.
A Decentralized Reputation Management System for Securing the Internet of Vehicles

The evolution of the Internet of Vehicles (IoV) paradigm has recently attracted a lot of researchers and industries. Vehicular Ad Hoc Networks (VANET) is the networking model that lies at the heart of this technology. It enables the vehicles to exchange relevant information concerning road conditions and safety. However, ensuring communication security has been and still is one of the main challenges to vehicles’ interconnection. To secure the interconnected vehicular system, many cryptography techniques, communication protocols, and certification and reputation-based security approaches were proposed. Nonetheless, some limitations are still present, preventing the practical implementation of such approaches. In this paper, we first define a set of locally-perceived behavioral reputation parameters that enable a distributed evaluation of vehicles’ reputation. Then, we integrate these parameters into the design of a reputation management system to exclude malicious or faulty vehicles from the IoV network. Our system can help in the prevention of several attacks on the VANET environment such as Sybil and Denial of Service attacks, and can be implemented in a fully decentralized fashion.
Group-Based Key Exchange for Medical IoT Device-to-Device Communication (D2D) Combining Secret Sharing and Physical Layer Key Exchange

Proximity based D2D communication is expected to be an essential part of the Internet of Things (IoT) in the future cellular networks as it will reduce the packet transmission delay for the ultra-low latency communication scenarios in addition to the higher bandwidth and significant Quality of Service (QoS). This will provide an opportunity for health monitoring devices to have a direct cellular D2D communication capability so that the data can be transmitted between the medical devices in short range, without using the data transmission through the base station (BS) from the cellular infrastructure. However, secure communication between these devices could be a major challenge to resist a variety of attack as the security procedures will no longer be assisted by the base station. The establishment of a secure communication link between these devices requires an authenticated key exchange protocol especially in a group-based communication scenario where designing a secure group based key exchange technique is still an open research issue. Therefore, this paper proposes an information-theoretically secure key management protocol suitable for the low-constrained IoT D2D communication. The focus of this research is to design a group key exchange protocol that integrates the physical layer key exchange technique (PLKE) with the cryptographic secret sharing approach that enables a reduction in computational complexity of the proposed protocol. It also aims to design an RF fingerprinting Intrusion detection system that can extract, and process features from the communicating signals to generate a fingerprint for each medical IoT device during the key exchange process in a D2D communication scenario to prevent device spoofing attacks. Ambient Assisted Living (AAL) fall detection is considered as a reference scenario for group-based communication in which devices might need to communicate to avoid any false positives and to detect the actual state of the patient.
A Comprehensive Study of Low Frequency and High Frequency Channel Correlation

To meet the increasing throughput demand due to the proliferation of data-hungry services and applications, 5G technologies are adopting innovative solutions, such as using high frequency (HF) bands from 20 to 300GHz. While these bands provide more bandwidth and thus higher data rates, this comes at the price of higher propagation and penetration losses, making reliable communication more challenging in some scenarios. The characteristics of low frequency (LF) and HF bands are complementary, and multiband systems that combine the advantages of both types of bands are highly promising. In such a case, estimating the channel of one band given an prior channel measurement of the other band helps to reduce channel measurement overhead, provided the bands are correlated. In this work, we present a detailed study of the correlation between HF and LF bands. The existence of this correlation makes possible to reduce the overhead of expensive operations such as millimeter-wave beam steering to one third of its original time with an average loss rate SNR of less than 3dB.
Two-Stage Deep Learning Approach to the Classification of Fine-Art Paintings

Due to the digitization of fine art collections, pictures of fine art objects stored at museums and art galleries became widely available to the public. It created a demand for efficient software tools that would allow rapid retrieval and semantic categorization of art. This paper introduces a new, two-stage image classification approach aiming to improve the style classification accuracy. At the first stage, the proposed approach divides the input image into five patches and applies a deep convolutional neural network (CNN) to train and classify each patch individually. At the second stage, the outcomes from the individual five patches are fused in the decision-making module, which applies a shallow neural network trained on the probability vectors given by the first-stage classifier. While the first stage categorizes the input image based on the individual patches, the second stage infers the final decision label categorizing the artistic style of the analyzed input image. The key factor in improving the accuracy compared to the baseline techniques is the fact that the second stage is trained independently on the first stage using probability vectors instead of images. This way, the second stage is effectively trained to compensate for the potential mistakes made during the first stage. The proposed method was tested using six different pre-trained CNNs (AlexNet, VGG-16, VGG-19, GoogLeNet, ResNet-50, and Inceptionv3) as the first-stage classifiers, and a shallow neural network as a second-stage classifier. The experiments conducted using three standard art classification datasets indicated that the proposed method presents a significant improvement over the existing baseline techniques.
Image Captioning with Word Gate and Adaptive Self-Critical Learning

: Although the policy-gradient methods for reinforcement learning have shown signiﬁcant improvement in image captioning, how to achieve high performance during the reinforcement optimizing process is still not a simple task. There are at least two difﬁculties: (1) The large size of vocabulary leads to a large action space, which makes it difﬁcult for the model to accurately predict the current word. (2) The large variance of gradient estimation in reinforcement learning usually causes severe instabilities in the training process. In this paper, we propose two innovations to boost the performance of self-critical sequence training (SCST). First, we modify the standard long short-term memory (LSTM)based decoder by introducing a gate function to reduce the search scope of the vocabulary for any given image, which is termed the word gate decoder. Second, instead of only considering current maximum actions greedily, we propose a stabilized gradient estimation method whose gradient variance is controlled by the difference between the sampling reward from the current model and the expectation of the historical reward. We conducted extensive experiments, and results showed that our method could accelerate the training process and increase the prediction accuracy. Our method was validated on MS COCO datasets and yielded state-of-the-art performance. the inference can lower the variance of the gradients and improve the training procedure. FC is the full connected layer which projects the image vector to the word dictionary probabilities. CIDEr is an image captioning evaluation method proposed in [5]. method with β set to 0.8, and the h represent different hyper-parameters for the history factor. We found that with longer history reward information, better performance was obtained. In practice, β set to be 0.8 and h set to be more than 2500 iterations could help our model to yield better performance.
Placement Delivery Array Design via Attention-Based Sequence-to-Sequence Model With Deep Neural Network

Recently, coded caching scheme was proposed as the ability of alleviating the load of networks. Especially, the placement delivery array (PDA) used for characterizing the coded caching scheme has attracted vast attention. In this letter, a deep neural architecture is first proposed to learn the construction of PDAs for reducing the computational complexity. The problem of variable size of PDAs is solved using mechanism of neural attention and reinforcement learning. Different from previous works using combined optimization algorithms to get PDAs, our proposed deep neural architecture uses sequence-to-sequence model to learn construct PDAs. Numerical results are given to demonstrate that the proposed method can effectively implement coded caching meanwhile reducing the computational complexity.
A Procedure for Modeling Photovoltaic Arrays under Any Configuration and Shading Conditions

Photovoltaic (PV) arrays can be connected following regular or irregular connection patterns to form regular configurations (e.g., series-parallel, total cross-tied, bridge-linked, etc.) or irregular configurations, respectively. Several reported works propose models for a single configuration; hence, making the evaluation of arrays with different configuration is a considerable time-consuming task. Moreover, if the PV array adopts an irregular configuration, the classical models cannot be used for its analysis. This paper proposes a modeling procedure for PV arrays connected in any configuration and operating under uniform or partial shading conditions. The procedure divides the array into smaller arrays, named sub-arrays, which can be independently solved. The modeling procedure selects the mesh current solution or the node voltage solution depending on the topology of each sub-array. Therefore, the proposed approach analyzes the PV array using the least number of nonlinear equations. The proposed solution is validated through simulation and experimental results, which demonstrate the proposed model capacity to reproduce the electrical behavior of PV arrays connected in any configuration.
Data processing procedure using distribution of slopes of phase differences for broadband VHF interferometer

The upgraded VHF digital interferometer (VHF DITF) system is introduced which can continuously sample the radiation associated with lightning. A new processing technique was implemented which uses the distribution of slopes of the phase difference versus frequency to locate the radiation source. By using this technique, frequency components which are not due to lightning can be excluded and low as well as high amplitude sources are located. As a result, both positive breakdown and negative breakdown are located, and negative recoil leaders (recoil leaders) are visualized in great detail. The recoil leaders which continue into the positive charge region are seen to slow their propagation and dim their radiation as they cross the flash initiation region. Analysis of the relative received power of the different breakdown types, negative leaders, recoil leaders, and positive leaders, also can be made. In both the intracloud and cloud‐to‐ground flash, the modes of the distributions of received power for negative leaders, recoil leaders, and positive leaders were approximately the same. The brightest emissions seen from the positive leader were substantially lower than the brightest emission seen from the negative leader. The results also indicate that positive leaders as well as lower elevation negative leader emit more low frequency radiation than recoil leaders and high‐elevation negative leaders. By continuously sampling the VHF waveform, the upgraded VHF DITF locates many weak sources which the previous system was not capable of locating.
Evaluating the Usability of Unity Game Engine from Developers' Perspective

While usability evaluation studies consider the end users' perspectives, there are not many studies regarding the developers' usability perspectives on their own software development environments. Usability evaluation of Unity game engine was conducted in this study. Seven software developers have participated. Participants were given 26 tasks to complete with Unity. Task completion rates and times were recorded. Results revealed that there were no major problems that would prevent its use completely. However, there are some issues that disturb its users. It is thought that eliminating these issues would contribute to improving the system.
Computational of the wind velocity effect on infiltration rates in an individual building using multi-zone airflow model

ABSTRACT This paper presents and discusses numerical simulation of the wind velocity's effect on infiltration rates in an individual building using multi-zone modelling. The governing equations are expressed in terms of unknown pressures at points where flow paths connect. Their implementation was achieved using an advanced numerical model, which was developed via the MATLAB environment. Such a numerical approach has been validated through available results. A good agreement has been observed between available data and our study's results. Moreover, the model implemented allows to determine the reference pressure in each zone to compute the air infiltration rate by each connection. To perform this, a large range of input data is needed. These include leakage characteristics of airflow elements, wind pressure coefficients, and ventilation system characteristics. To sum up, it is found that the wind velocity increase produces a strongly variation on computed infiltration rates.
Distributed feedback InGaN/GaN laser diodes

We have realised InGaN/GaN distributed feedback laser diodes emitting at a single wavelength in the 42X nm wavelength range. Laser diodes based on Gallium Nitride (GaN) are useful devices in a wide range of applications including atomic spectroscopy, data storage and optical communications. To fully exploit some of these application areas there is a need for a GaN laser diode with high spectral purity, e.g. in atomic clocks, where a narrow line width blue laser source can be used to target the atomic cooling transition. Previously, GaN DFB lasers have been realised using buried or surface gratings. Buried gratings require complex overgrowth steps which can introduce epi-defects. Surface gratings designs, can compromise the quality of the p-type contact due to dry etch damage and are prone to increased optical losses in the grating regions. In our approach the grating is etched into the sidewall of the ridge. Advantages include a simpler fabrication route and design freedom over the grating coupling strength.Our intended application for these devices is cooling of the Sr+ ion and for this objective the laser characteristics of SMSR, linewidth, and power are critical. We investigate how these characteristics are affected by adjusting laser design parameters such as grating coupling coefficient and cavity length.
Performance Analysis of a Biomass Gasifier Genset at Varying Operating Conditions

An All Power Labs PP20 gasifier generation set (Berkeley, Calif.) was tested to evaluate its suitability for powering biomass conversion technologies (BCT) at remote forest operations sites. Feedstock of the species tanoak (Notholithocarpus densiflorus), coast redwood (Sequoia sempervirens), and Douglas fir (Pseudotsuga menziesii) were tested at moisture contents of 15% and 25% (wet basis). The PP20 was connected to a load bank with five different load profiles designed to simulate possible BCT loads. Two parameters of power quality, voltage variability, and frequency deviation, were determined to be within acceptable limits. The unit also successfully powered a remote biochar operation in Branscomb, California. Emissions of the PP20, when compared to diesel generator regulations, would meet non-methane hydrocarbons (NMHC) and NOX requirements but exceed the CO emissions limits by a factor of ten. The CO emissions could be reduced by adding a catalytic converter. The results indicate that it is possible to use a PP20 unit to provide electric power for the highly variable loads of a BCT system.
Measuring the structural impact of mutations on cytochrome P450 21A2, the major steroid 21-hydroxylase related to congenital adrenal hyperplasia

Abstract Congenital adrenal hyperplasia is an inherited autosomal recessive disorder related to deficient cortisol synthesis. The deficiency of steroid 21-hydroxylase (cytochrome P450 21A2), an enzyme involved in cortisol synthesis, is responsible for ∼95% of cases of congenital adrenal hyperplasia. This metabolic disease exhibits three clinical forms: salt-wasting, simple virilizing, and non-classical form, which are divided according to the degree of severity. In the present study, structural and mutational analyses were performed in order to identify the structural impact of mutations on cytochrome P450 21A2 and correlate them with patient clinical severity. The following mutations were selected: arginine-356 to tryptophan (R356W), proline-30 to leucine (P30L), isoleucine-172 to asparagine (I172N), valine-281 to leucine (V281L), and the null mutation glutamine-318 (Q318X). Our computational approach mapped the location of residues on P450 and identified their implications on enzyme electrostatic potential mapping to progesterone and heme binding pockets. Using molecular dynamics simulations, we analyzed the structural stability of ligand binding and protein structure, as well as possible conformational changes at the catalytic pocket that leads to impairment of enzymatic activity. Our study sheds light on the impact structural mutations have over steroid 21-hydroxylase structure-function in the cell. Communicated by Ramaswamy H. Sarma