Miracle-dz/UniFAR-FTUs huggingface dataset:
An Optimal Site Selection for Distributed Generation in the Distribution Network by QPSO Algorithm

Environmental concerns, technology improvement and deregulation of electricity markets have encouraged the use of Distributed Generation (DG) sources. An optimal site selection for DG placement can improve distribution system efficiency by minimizing network losses and improving system voltage. Finding an optimal place of DG for a distribution network is a complex optimization issue. In this paper, we have demonstrated the modified version of Particle Swarm Optimization (PSO) called Quantum Behaved PSO (QPSO) algorithm to determine optimal location of DG units for power loss minimization. A standard IEEE 33 and 69-node distribution network are used to validate the effectiveness of the demonstrated method. The simulation results are matched with the literature and it is established that the QPSO has better ability to minimize network losses and improve system voltage by finding more precise location for DG installation.
Amplifier Nonlinearities in an Antenna Array During Spatially-Multiplexed Transmissions

The effects of nonlinearities in radio frequency (RF) power amplifiers (PAs) driving a Nant element array antenna are investigated. Initially, it is assumed that only the phase of each antenna path is adjusted and that the phase shift between neighbouring elements is equal. The Nant phase shifts used is referred to as the precoding vector. It is shown that when two (or more) data streams are spatially-multiplexed using different precoding vectors, the PA nonlinearities intermodulate the precoding vectors. This creates IMD beams in directions following the linear beam directions, as well as additional IMD beams whose directions are determined by the spatial separation of the linear beams. This case is generalized to allow amplitude shifts that are distributed to create Gaussian shading (tapering) within the precoding vectors. Digital predistortion is applied to reduce the IMD beams in the dominant directions.
Mixing Pre-clinical and Clinical Medical Students in Full Patient Simulation: Impacts and Outcomes

Introduction: Full patient simulation is an accepted learning modality in the final years of undergraduate medical education. Less explored is its applicability to the pre-clinical stages of the medical curriculum or as a medium for peer learning. To investigate these issues we conducted a simulation study involving mixed teams of pre-clinical and clinical medical students. Methods: A sample of 52 medical students (27 year four, 25 year two) participated in one of six full patient simulation sessions. A mixed study design involving an online questionnaire and focus groups was used to assess the students’ perceptions regarding their recent simulation experience and the proposed addition of simulation into the preclinical stage of their medical curriculum. Results: Focus group thematic analysis identified three major themes: non-technical skills, learning opportunities during simulation and simulation in the medical curriculum. The opportunity to practise team working and communication between different year levels was identified as a particular advantage. Questionnaire responses demonstrated an overall positive perception of the mixed year simulation experience. Conclusion: This study demonstrates the unique peer learning opportunities created through combining pre-clinical and clinical undergraduates in full patient simulation. The positive impact of these sessions on students’ perceived acquisition of non-technical skills, specifically those of communication and team-working with colleagues of different skill levels, supports the incorporation of inter-year simulation into the undergraduate medical curriculum.
Ground subsidence monitoring of Shanghai Inner Viaduct by TerraSAR images

Shanghai is the central city of the Yangtze River Delta Urban Agglomeration and the second largest municipality in China. Shanghai has formed a three-dimensional transportation network consisting of ground roads, elevated roads, river crossing tunnels and bridges, as well as metros and elevated rail transit. As soft soil basement, monitoring ground subsidence of the Shanghai Inner Viaduct is very important for its safety and maintaining work. Multitemporal interferometric synthetic aperture radar (MT-InSAR) is a technology that uses high spatial resolution satellite images to detect high-precision surface variations. In this paper, we use 37 scenes of TerraSAR-X ascending images with a high resolution of 3 meters acquired from March 2009 to October 2012 to detect and process high coherence points along Shanghai Inner Viaduct. Then, we use the unsupervised classification method of K-means for the separation of elevated points and ground points. A total of 14,869 points are obtained along the viaduct, and 7,668 of them are on the viaduct. The average deformation rate of elevated points and ground points are 0.38 mm/year and −1.15 mm/year respectively. The result shows that high resolution SAR images can be used to monitor the deformation of the Shanghai inner viaduct efficiently and the settlement of the viaduct is more stable than its nearby ground.
Machine Learning-based Interference Detection in GPGPU Concurrent Kernel Execution

Recent advancements in GPU architectures have made it possible to run multiple kernels concurrently on a single GPU, to avoid under-utilization of its resources. Fine-grain sharing of streaming multiprocessors (SMs) allows thread blocks of multiple kernels to be assigned to GPU resources altogether. However, this may cause resource contention and performance degradation if both kernels try to access a shared resource at the same time. Detecting these interferences is essential especially in high-performance computing (HPC) systems, in which multiple applications may issue different kernels to available shared GPUs. This paper proposes a machine learning-based approach to characterize kernels and predict interference before their concurrent execution. Random forest classifier is used to classify interfering and noninterfering kernels. Experimental results show that the proposed method can detect interfering kernels with up to 91.7% accuracy.
An Adversarial Machine Learning Approach to Evaluate the Robustness of a Security Solution

Cyber-Security industry has always been a "cat and a mouse" game - whenever a new technology was developed it was shortly followed by the appearance of several techniques used by malware creators to avoid detection. It is no surprise that the developing of adversarial machine learning algorithms has provided a tool that can be used to avoid machine learning based detection mechanisms available in security products. This paper presents how the same algorithms can also be used to strengthen a security solution by identifying its weak points / features. We will also provide a method that can be used to fight Generative Adversarial Networks (GANs) with GANs, that is effective when a malware writer is using these methods to avoid detection.
A Robust, Iteration Dependent Variable Step-Size (RID-VSS) Least-Mean Square (LMS) Adaptive Algorithm

A robust variable step-size LMS algorithm is proposed. The variable step-size is a weighted running average of the squared error signal which varies as the square of the estimated error changes. The weighting factor ensures stability and convergence. Robustness of the algorithm is achieved through the step-size inherent bounded nature and independence from the initial condition. The algorithm is compared with two benchmark VSS algorithms. Convergence and steady-state behavior of the proposed adaptive filter are analyzed. Simulation for the system identification scenario is carried out and the performance of the proposed algorithm is compared.
Distributed Sub-gradient Algorithms with Limited Communications

We consider the distributed convex optimization scenario in which nodes in a network collectively find the minimum of a function utilizing only local communications and computations. Various sub-gradient algorithms have been developed for this optimization setting for the case in which the global function factorizes as the sum of local functions to be distributed to the nodes in network, including the distributed (i) online gradient descent, (ii) Nesterov gradient descent, and (iii) dual averaging algorithms. Generally speaking, these subgradient algorithms assume that, in each communication round, nodes can exchange messages of size comparable to that of the optimization variable. For many high-dimensional optimization problems, this communication requirement is beyond the capabilities of the communication network supporting the distributed optimization. For this reason, we propose a dimensionality reduction technique based on random projections to adapt these distributed optimization algorithms to networks with communication links of limited capacity. In particular, we analyze the performance of the proposed dimensionality reduction technique for the three algorithms above, i.e. (i)–(iii). Numerical simulations are presented that illustrate the performance of the proposed approach for these three algorithms.
A Parametric TDoA Technique in the IoT Localization Context

Internet of Things (IoT) has been scaling up over the last few years in multiple applications and due to the need for geolocation and tracking capabilities, the usage of traditional Time Difference of Arrival (TDOA) arises. In this paper, a novel methodology for localizing using TDoA is presented, after the detailed and complete description of the TDoA has been provided. This proposed method depends on the hyperbolic functions to localize the node on a hyperbola, rather than locating it in a free position in the space potentially suffering from the influence of the timestamp imperfections. Thus, the proposed approach is finding this location on a hyperbola at a point which has the minimum Euclidean distance to all the other hyperbolas. A comparison is performed investigating the attainable accuracies for localizing based on this parametric TDoA and the classical TDoA method, on a well-defined simulation environment. The simulator is based on a Poisson distribution approach for defining the gateways and the node topology, as well as a noise model for emulating the oscillator drift at the gateways. In the given results, the feasibility of the proposed technique is asserted by a drastic improvement over a wide range of drift variances and the number of gateways. This manifests the robustness of the contributed method to the outlier timestamps and its optimum rendering, especially when the number of gateways is expected to be increased in the future.
Reentrancy Vulnerability Identification in Ethereum Smart Contracts

Ethereum Smart contracts use blockchain to transfer values among peers on networks without central agency. These programs are deployed on decentralized applications running on top of the blockchain consensus protocol to enable people make agreements in a transparent and conflict free environment. The security vulnerabilities within those smart contracts are a potential threat to the applications and have caused huge financial losses to their users. In this paper, we present a framework that combines static and dynamic analysis to detect Reentrancy vulnerabilities in Ethereum smart contracts. This framework generates an attacker contract based on the ABI specifications of smart contracts under test and analyzes the contract interaction to precisely report Reentrancy vulnerability. We conducted a preliminary evaluation of our proposed framework on 5 modified smart contracts from Etherscan and our framework was able to detect the Reentrancy vulnerability in all our modified contracts. Our framework analyzes smart contracts statically to identify potentially vulnerable functions and then uses dynamic analysis to precisely confirm Reentrancy vulnerability, thus achieving increased performance and reduced false positives.
Short Range 3D MIMO mmWave Channel Reconstruction via Geometry-aided AoA Estimation

In some millimeter wave (mmWave) applications, such as wearables, the distance between the transceivers is relatively short. Further, the channel has significant angular spread in both azimuth and elevation domains even in line-of-sight (LoS). Under such conditions, hybrid mmWave architectures with multiple analog uniform planar arrays (UPAs) potentially allow spatial multiplexing even in LoS provided that the high rank structure of the channel is captured. The conventional far-field channel estimation methods are not generally suitable for these scenarios and perform poorly. We consider parametrized spatial channel estimation, where the known antenna array geometry is exploited to recover the angle-of-arrivals (AoAs) of the 3D multiple-input multiple-output (MIMO) channel. The channel is then reconstructed using these AoA estimates and the known geometry. We show that conventional maximum a posteriori (MAP) estimation of the channel parameters suffers from high computational complexity and may not be not applicable for low powered devices. To this end, we propose a lower complexity message passing algorithm for short range channel estimation. We show, by numerical examples, that the proposed technique achieves good performance with fewer pilot resources when compared to compressed sensing or antenna specific pilot based channel estimation.
Spinal and Pelvic Kinematics During Gait in People with Lower-Limb Amputation, with and without Low Back Pain: An Exploratory Study

Introduction Despite the high prevalence of chronic low back pain (LBP) in people with lower-limb amputation, it is not clear whether there are differences in spinal and pelvic motion in individuals with and without LBP. This exploratory study aimed to describe the spinal and pelvic kinematics during gait in people with transfemoral amputation (TFA) and transtibial amputation (TTA), with and without LBP. Methods Eighteen participants with traumatic amputation (6 TFA, 12 TTA) were grouped according to their amputation level and presence (or absence) of LBP. Three-dimensional thoracic, lumbar, and pelvic kinematics during walking were reported to identify movement patterns that may be indicative of LBP. Results The TFA-LBP group elevated the pelvis on the intact side and minimized lumbar lateral flexion to achieve the same trunk lateral flexion angle (Trendelenburg gait) as those with TFA-No LBP. Those with TFA-LBP kept the lumbar spine rotated toward the prosthetic limb throughout the gait cycle. There were no differences in the spinal and pelvic kinematics of people with TTA-LBP and TTA-No LBP. Conclusions This study provides preliminary evidence of differences in spinal and pelvic kinematics that may be associated with LBP in people with TFA.
What Motivates Learners' Intention to Use Blackboard Mobile Learning (BML)?: Evidence from Thailand

this research focuses on the factors motivate learners' intention to use blackboard mobile learning. The research objective is to investigate the main factors in terms of usefulness learning and individual characteristics in order to investigate the factors that affect blackboard mobile learning acceptance among university students in Thailand. Based on the quantitative research method this study obtained behavior intention score from undergraduate students in Thailand. The Partial Least Squares method, a statistical analysis technique based on the Structural Equation Model (SEM), was used to analyse the data. The results of 314 undergraduate students were found that mobile self-efficacy had the significant effect on perceived ease of use of blackboard mobile learning while convenience had the significant effect on perceived usefulness of blackboard mobile learning. In addition, the main variable from the technology acceptance model namely perceived ease of use and perceived usefulness had positively related to user intention to blackboard mobile learning.
AUTOIMMUNE THYROIDITIS AMONG IONIZING RADIATION EXPOSED WORKERS IN CARDIAC CATHETERIZATION UNITS.

Introduction: It is well known that ionizing radiation (IR) exposure increases the risk of thyroid cancer; however less is known about its role in development of autoimmune thyroiditis. Aim of work: to investigate the thyroid gland functions,level of anti TPO among interventional cardiology team members searching for an association between the level of their occupational exposure to ionizing radiation and the thyroid gland integrity. Materials and methods: This work was carried out in Cardiac Catheterization Unit in National Heart Institute Center. The study comprised two groups, an exposed group of 47 cardiac catheterization workers (19 physicians, 15 nurses and 13 technicians) and a control group of 47 workers matched with the exposed group as regards age and sex. The studied groups were subjected to a detailed questionnaire, full clinical examinations. laboratory investigations in the form of serum thyroid stimulating hormone (TSH), Triiodothyronine (T3), Thyroxine (T4) and antithyroxiperoxidase antibodies (anti-TPO). Radiation exposure was monitored by digital dosimeter. Results: Dosimeter readings were higher among physicians followed by nurses and technicians. Statistically significant higher level of serum TSH, anti-TPO along with statistically significant lower levels of T3, were found among the exposed compared to control groups (P<0.05). Significant positive correlation was detectedbetween the level of anti-TPO and TSH (r= 0.876 P<0.001). Moreover, a significant negative correlation was found between anti-TPO and each of T3 (r= -0.814 P<0.001) and T4 (r= -0.324 P<0.05). ANOVA and Post Hoc tests showed significantly higher level of anti-TPO with significantly lower levels of T3 among the physicians compared to control group. Conclusion: Autoimmune thyroiditis may be considered as one of the adverse health hazards of occupational exposure to ionizing radiation in cardiac catheterization units. Recommendations: We recommend the regular measurement of thyroid hormone especially TSH and anti-TPO to detect early affection of thyroid glandamong radiation exposed workers.
Hospital disaster emergency preparedness: A study of Onandjokwe Lutheran Hospital, Northern Namibia

This study explored disaster emergency preparedness at Onandjokwe Lutheran Hospital in Northern Namibia. It utilized quantitative and qualitative research methods, using a self-administered questionnaire, semi-structured key informant interviews, and a hospital disaster plan checklist. A stratified sample of 120 participants was used with a response rate of 75% and the sample included all staff categorises within the hospital. Five key informants were purposively selected from the management team. In addition, one environmental health officer was selected from non-managerial staff members. The key informants were members of the hospital emergency preparedness committee and command and control unit. The questionnaires were self-administered which enabled the respondents to respond freely and at their convenience. The questionnaire was pre-tested, adjusted and finalised. Face-to-face semi-structured key informant interviews allowed for clarifications and followup questions on overall disaster emergency preparedness process. Through the use of open-ended questions the respondents were encouraged to express their opinions and offer more information. The checklist was used to check and determine the components of the hospital’s disaster plan against the actual processes in the hospital. Most of the respondents were young females aged between 20 and 30 years. The results indicated a fair knowledge of the principled conduct and abilities to respond to emergencies including disease outbreaks. It was established that positive efforts in disaster preparedness were being effected. However, even though the hospital has a good draft disaster plan, more is to be done on training, revisions, and infrastructure alignments. Keywords: disaster emergency preparedness, hospitals, disaster, disaster management, Namibia
Determinants Of Utilization Of Maternal And Neonatal Healthcare Services By Mothers In Embakasi Sub-County, Nairobi, Kenya

xiv CHAPTER ONE:INTRODUCTION . 1 1.1 Background to the study . 1 1.2 Statement of the problem . 3 1.3 Purpose of the study . 4 1.4 Objectives of the study. 5 1.5 Research questions . 5 1.6 Significance of the Study . 5 1.7 Limitations of the study . 6 1.8 Delimitation of the Study . 6 1.9 Assumptions of the study . 7 1.10 Definitions of Significant Terms as Used in the Study . 7 1.11 Organization of the Study: . 8 CHAPTER TWO:LITERATURE REVIEW . 9 2.
Structural Cardiac Abnormalities in Children with Congenital Malformationsin Lagos

Background: Congenital heart disease has a great impact on a child’s morbidity and mortality as well as on the health systems cost. They represent the main cause of death among children with congenital malformations. Method: The study was prospective, cross-sectional involving consecutive subjects from two centers which were; a tertiary hospital, a private hospital and a major cardiology center. Children with congenital malformations had transthoracic echocardiography done by a cardiologist. Data was analyzed using Microsoft excel software supplemented with Statistical Package for Social Sciences (SPSS) version 20. Means of continuous variables were compared using the Student t test and proportions using Chi-square test. Level of significance set at p<0.05. Results: A total of 366 children with obvious congenital malformation were recruited in the study. The age range of the patients was between 1 day to 12 years with a mean age of about 6 + 508.03. Majority of the patients were neonates as shown in Table 1. Male to female ratio was 1.1:1. Up to 26.5% of the subjects had a structurally normal heart. The most common congenital heart defect observed observed was atrial septal defect (14.8%) followed by isolated ventricular septal defect (14.1%). Atrioventricular septal defect 13.7%, Patent ductus arteriosus 7.1%, tetralogy of Fallot 4.5%. Some of the patients had more than one cardiac defects. Conclusion: The prevalence of congenital heart defects among children with congenital malformation is very high. Routine screening for cardiac defects in any patients with congenital malformation is advocated to improve quality of life, reduce morbidity and mortality in these subjects.