Miracle-dz/UniFAR-FTUs huggingface dataset:
Signal Processing for Digital Beamforming FMCW SAR

According to the limitations of single channel Frequency Modulation Continuous Wave (FMCW) Synthetic Aperture Radar (SAR), Digital Beamforming (DBF) technology is introduced to improve system performance. Combined with multiple receive apertures, DBF FMCW SAR can obtain high resolution in low pulse repetition frequency, which can increase the processing gain and decrease the sampling frequency. The received signal model of DBF FMCW SAR is derived. The continuous antenna motion which is the main characteristic of FMCW SAR received signal is taken into account in the whole signal processing. The detailed imaging diagram of DBF FMCW SAR is given. A reference system is also demonstrated in the paper by comparing with a single channel FMCW SAR. The validity of the presented diagram is demonstrated with a point target simulation results.
How Project Manager–Project Owner Interaction Can Work within and Influence Project Risk Management

Inherent interest conflicts between a project management team and project owner are often neglected in project risk management. Risk management by the project management team basically focuses on project short-term survival, or project success toward handover to the customer, while for the project owner, strategic success should be more important. To see how this takes place in and influences real projects, seven large projects were studied, and interaction in project risk management between the project owners and project management team was examined for each project. The study revealed that the main focus in the studied projects was on operational risks, even within the project owner's set of high-priority risks.
Field and Laboratory Studies on High-Mast Lighting Towers in Iowa

Recent failures of high-mast lighting towers in several Midwestern states have raised questions as to the robustness and safety of the existing inventory of similar structures. Failure of these structures is very critical, as they are typically located adjacent to interstates or other high-speed highways. The potential exists for these fracture-critical structures to fall across multiple traffic lanes or adjacent property. Forensic studies on cracked poles in the state of Iowa and elsewhere have revealed fatigue to be the primary cause of the failures. Interestingly, there is little data on the actual response of these structures in terms of natural wind, longterm cyclic stresses, and general dynamic properties. Believed to be the first of its kind, the Iowa Department of Transportation has sponsored a comprehensive field testing and long-term remote monitoring program that has focused on two poles in near Clear Lake, Iowa. The results of the field studies suggest that additional fatigue cracking can be expected at other poles in the future. In order to address this issue, retrofit strategies have been developed and are currently going through static and fatigue tests to establish the fatigue resistance and long-term viability of the design. The laboratory tests, which have just begun, have been augmented with detailed finite element analytical studies on the base plate connection. This paper will report on the initial results of the field studies and provide suggested strategies for retrofit, inspection, and maintenance of these fracture-critical structures.
An orifice shape-based reduced order model of patient-specific mitral valve regurgitation

Mitral valve regurgitation (MR) is one of the most prevalent valvular heart diseases. Its quantitative assessment is challenging but crucial for treatment decisions. Using computational fluid dynamics (CFD), we developed a reduced order model (ROM) describing the relationship between MR flow rates, transvalvular pressure differences, and the size and shape of the regurgitant valve orifice. Due to its low computational cost, this ROM could easily be implemented into clinical workflows to support the assessment of MR. We reconstructed mitral valves of 43 patients from 3D transesophageal echocardiographic images and estimated the 3D anatomic regurgitant orifice areas using a shrink-wrap algorithm. The orifice shapes were quantified with three dimensionless shape parameters. Steady-state CFD simulations in the reconstructed mitral valves were performed to analyse the relationship between the regurgitant orifice geometry and the regurgitant hemodynamics. Based on the results, three ROMs with increasing complexity were defined, all of which revealed very good agreement with CFD results with a mean bias below 3% for the MR flow rate. Classifying orifices into two shape groups and assigning group-specific flow coefficients in the ROM reduced the limit of agreement predicting regurgitant volumes from 9.0 ml to 5.7 ml at a mean regurgitant volume of 57 ml.
PLATFORMS, PROBLEMS AND SOLUTIONS OF ONLINE ENGLISH LANGUAGE TEACHING AT VOCATIONAL HIGH SCHOOL

The study aimed to discover and to describe online learning platforms used, the problems faced and the solutions that offered by the English teacher in Vocational High School. The descriptive qualitative research was used as the research design in order to describe in detail the issues which had been discovered. The researcher selected 7 English teachers from each state vocational high school of Bengkulu city as the representative sample for this research. The instrument of this research was the interview guideline and data were collected by using the interview. After collecting the data, the researcher analyzed the data by using descriptive analysis. The result Google classroom and WhatsApp were effective platforms to have online English language teaching in the pandemic era, especially, for the students at the vocational high school. The problems of using the platforms were the internet connection, lack of students’ motivation, lack of students’ understanding, and inefficient teaching time. While the problems of teaching language skills through the use of platforms were miss understanding and lack motivation, in adequate time, lack of interaction, and overload the use of data plan. The solution that the teacher used for solving the use of platform were providing the extended time and offline module or having face to face class. However for solving the problems of teaching language skills, the teachers did Whatsapp discussion, peer feedback and having question and answer session in Whatsapp, decreasing listening activity and providing additional time for writing.
Genomic Variation across a Clinical Cryptococcus Population Linked to Disease Outcome

Infection outcomes for cryptococcosis, most commonly caused by C. neoformans, are influenced by host immune responses as well as by host and pathogen genetics. Infecting yeast isolates are genetically diverse; however, we lack a deep understanding of how this diversity impacts patient outcomes. ABSTRACT Cryptococcus neoformans is the causative agent of cryptococcosis, a disease with poor patient outcomes that accounts for approximately 180,000 deaths each year. Patient outcomes may be impacted by the underlying genetics of the infecting isolate; however, our current understanding of how genetic diversity contributes to clinical outcomes is limited. Here, we leverage clinical, in vitro growth and genomic data for 284 C. neoformans isolates to identify clinically relevant pathogen variants within a population of clinical isolates from patients with human immunodeficiency virus (HIV)-associated cryptococcosis in Malawi. Through a genome-wide association study (GWAS) approach, we identify variants associated with the fungal burden and the growth rate. We also find both small and large-scale variation, including aneuploidy, associated with alternate growth phenotypes, which may impact the course of infection. Genes impacted by these variants are involved in transcriptional regulation, signal transduction, glycosylation, sugar transport, and glycolysis. We show that growth within the central nervous system (CNS) is reliant upon glycolysis in an animal model and likely impacts patient mortality, as the CNS yeast burden likely modulates patient outcome. Additionally, we find that genes with roles in sugar transport are enriched in regions under selection in specific lineages of this clinical population. Further, we demonstrate that genomic variants in two genes identified by GWAS impact virulence in animal models. Our approach identifies links between the genetic variation in C. neoformans and clinically relevant phenotypes and animal model pathogenesis, thereby shedding light on specific survival mechanisms within the CNS and identifying the pathways involved in yeast persistence. IMPORTANCE Infection outcomes for cryptococcosis, most commonly caused by C. neoformans, are influenced by host immune responses as well as by host and pathogen genetics. Infecting yeast isolates are genetically diverse; however, we lack a deep understanding of how this diversity impacts patient outcomes. To better understand both clinical isolate diversity and how diversity contributes to infection outcomes, we utilize a large collection of clinical C. neoformans samples that were isolated from patients enrolled in a clinical trial across 3 hospitals in Malawi. By combining whole-genome sequence data, clinical data, and in vitro growth data, we utilize genome-wide association approaches to examine the genetic basis of virulence. Genes with significant associations display virulence attributes in both murine and rabbit models, demonstrating that our approach can identify potential links between genetic variants and patho-biologically significant phenotypes.
Optimal PID control of a nano-Newton CMOS-MEMS capacitive force sensor for biomedical applications

This paper presents closed loop simulation of a CMOS-MEMS force sensor for biomedical applications employing an optimal proportional-integral-derivative controller. Since the dynamic behavior of the sensor under investigation is nonlinear the iterative feedback tuning approach was proposed for optimal gains tuning of the proposed controller. Simulation results presented in this research illustrate that the proposed controller suppresses the undesired in-plane vibration induced by environment or gripper 40 times faster than the nonlinear controller proposed in the literature. To suppress the maximum input disturbance the maximum voltage was approximately 18 V which was less than the pull-in voltage of 30 V. The proposed controller is served to actuate two stator fingers adjacent to a rotor finger in order to provide both the attractive and repellent forces during manipulation. Employing the proposed mechanism not only resolves the drawbacks corresponding to the nonlinear controller presented in the literature but also improves its performance of the closed loop system by using the complete nonlinear dynamics of the force sensor. Also, applying complete non-linear dynamic of model improves the performance of controller and is one of superior features of proposed PID controller in comparison with the classical controller presented in literature.
Shear Strength Determination in RC Beams Using ANN Trained with Tabu Search Training Algorithm

The shear failure of reinforced concrete (RC) beams is a critical issue and has attracted the attention of researchers. The specific challenges of shear failure are the numerous factors affecting shear strength, the nonlinear behavior, and the nonlinear relationship between affecting parameters and the concrete properties. This study tackles this challenge by employing Artificial Neural Network (ANN) models. Since, according to No Free Lunch theorem, the performance of optimization algorithms is problem-dependent, this paper aims to assess the feasibility of modeling the shear strength of RC beams using ANNs trained with the Tabu Search Training (TST) algorithm. To this end, 248 experimental results were collected from the literature, and a feed-forward ANN model was employed to predict the shear strength. To assess its feasibility, the ANNs were also modeled using the Particle Swarm Optimization, and Imperialist Competitive Algorithms. As a traditional technique, the multiple regression model was also employed. The shear design equations of ACI-318-2019 were also investigated and compared with Tabu Search Trained ANN model. The analysis of results suggests the superiority of Tabu Search Trained ANNs in comparison to other suggested models in literature and the ACI-318-2019 design code.
Hourly Solar Radiation Forecast Based on k-NN Nonparametric Regression Model

It is hard to accurately predict solar radiation due to its very prominent nonlinear feature, so four major models based on the k-NN model, which have time, sunshine hours, temperature, wind speed and humidity as input data, are presented in the paper for hourly solar radiation forecasting. The models forecasting instantaneous solar radiation values in the Xining region have been created through experiments carried out in Qinghai University. The accuracy of the optimum model is up to 88.7% on average and 97.01% at most on the premise and the allowed absolute percentage error is lower than 20%.
Study of “Wave Type” Uneven Settlement and Reinforcing Method of Soft Clay Foundation

The deformation is the dominant factor of the quality of the road constructed on the soft soil foundation. Tianjin DongJiang port is located on the hydraulic filled soil foundation which is improved by using vacuum preloading method. Roads in this area often suffer wave type asymmetry settlement, which serious affects the usage of the road and causes damage to both vehicles and human being. It is found that the initial wave asymmetry deformation of the road on very soft soil foundation usually exists and will be developing continuously under the traffic load. The mechanism of the wavy failure of the road is discussed by establishing a mechanical model. The method of using geogrids to reduce the asymmetry deformation is proposed, the reinforce effect is analyzed using finite element method.
A Kind of Evolutionary Multi-Objective Optimization Algorithm Based on AIS

Problem of multi-objective optimization based on Artificial Immune System (AIS) is an important research area of current evolutionary computing. Starting from the intelligent information processing mechanism of immune theory and the immune system itself, a kind of evolutionary multi-objective optimization algorithm based on AIS is proposed. Clonal selection, scattered crossover and hypermutation based on the learning mechanism are characteristics of the algorithm. Algorithm implements clonal selection according to the distribution of individuals in the objective space, which benefit obtaining Pareto optimal boundary distributed more widely and speed up the convergence. Compared with the existing algorithms, the algorithm has been greatly improved in convergence, diversity, and distribution of solutions.
An extended dual decision-feedback equalizer for high-density perpendicular magnetic recording channels

Partial-response maximum-likelihood (PRML) systems are powerful and indispensable for high-density perpendicular magnetic recording channels. However, high-order partial-response (PR) targets must be considered because of severe intersymbol interference (ISI). On the other hand, decision feedback equalization (DFE) has very low complexity. DFE can be used with high code rate modulation codes, thanks to the fact that DFE does not use a minimum run constraint as a multilevel DFE (MDFE). At high recording densities, dual detection schemes such as dual DFE (DDFE) significantly improve performance and reduce error propagation. So, we compare DDFE detectors with PR(1221)ML and PR(12321)ML on 16/17 maximum transition run (MTR) (3,11)-coded perpendicular magnetic recording channels and propose an extended DDFE that represents a dual version of the DDFE. Simulation results show that the DDFE has a bit-error-rate (BER) performance comparable to that for PR(12321)ML. Our extended DDFE in turn shows a performance gain over DDFE and PR(12321)ML at the normalized recording densities 3 and 4.
Urban development in the context of extreme flooding events

Due to the rapid urban development and climate change, extreme meteorological events are occurring more frequently. The extreme meteorological events refer to the ‘natural’ disasters, such as storms, floods, droughts, temperature extremes and earthquakes, which are prominently rare, unexpected and severe in their consequences. Urban floods have been increasing in its intensity and frequency in recent decades. The proportion of the global population exposed to the threat of flooding has increased by nearly a quarter from 2000 to 2015, or 10 times of the previous estimation (i.e. 2.6%). Extreme urban floods can cause irreversible damages to lives and properties of urban citizens and pose a huge potential threat to the future development. Based on the Global Flood Database from 2000 to 2018, most urban floods took place in Asia (n1⁄4 398, China has 52 and India has 85), America (n1⁄4 223, 98 in the USA), Africa (n1⁄4 143), Europe (n1⁄4 92) and Oceania (n1⁄4 57). On 20 July 2021, more than 200mm of rain fell on the city of Zhengzhou in a single hour (denoted as ‘Zhengzhou flood’), in central China’s Henan province. The precipitation accumulated up to 552mm in 24 h (breaking the historical extreme records), while the worst-hit areas of Germany saw 154mm over 24 h. The Zhengzhou flood affected more than three million people with flooding death toll of 302 and 50 people missing. The direct economic loss was around ¥114.3 billion RMB ($17.7 billion US dollars), including infrastructure paralyses, collapsed buildings, washed-away cars, flooded facilities, outages of resources, etc. Moreover, the heavy rainfall also caused irreversible damages to historic heritages (e.g. museums, archaeological sites, Longmen Grottoes and Shaolin Temple). Figure 1. Urban flood in Zhenzhou, China. The reasons leading to Zhengzhou flood are multifolds. Zhengzhou is the largest city of Henan Province situated in the central part of China (112�–114�E, 34�N) with a 10.35 million population. When the airflow hits themountains in central China’sHenan province, it converged and flowed upwards, causing rain clouds to be accumulated. Moreover, the Typhoon ‘In-Fa’ brought abundant water vapour from Pacific Ocean. The stable atmospheric circulation also enhanced and extended the rainfall process. Although warnings have been broadcasted in advance regarding this heavy rainfall, instantaneous rain intensity prediction of a specific place is a worldwide challenge. In addition, the intensity of the strong rainfall exceeds the previous experience of local citizens. The public awareness and knowledge of flood prevention were unprepared for this extreme rainfall, causing serious property losses and casualties. Thus,mitigation strategies for such extrememeteorological events should be established on different aspects.
Computer aided process and design optimization for injection moulding

Abstract Sophisticated computer aided engineering (CAE) simulation tools for injection moulding have been available and are now widely used in industrial practices. As a result, the design and manufacturing of injection-moulded parts have been literally transformed from a ‘black art’ to an engineering discipline based on scientific principles. It is well recognized that computer simulation tools help engineers to gain process insight and to pinpoint blind spots and problems that are overlooked. Nevertheless, there remains a missing link in CAE, which lies in the ability to identify effectively the optimal design and process variables, as it is hampered by the sheer amount of computer-generated data and complex non-linear interactions among those input variables. This paper presents the system implementation and experimental verifications of an integrated CAE optimization tool that couples a process simulation program with optimization algorithms to determine intelligently and automatically the optimal design and process variables for injection moulding. In addition, this study enables evaluation and comparison of various local and global optimization algorithms in terms of computational efficiency and effectiveness for injection moulding, as presented in this paper.
Concept for the WWR-M Reactor Renovation

This paper presents the current status and feasibility of extended use of WWR-M research reactor; the extention of the reactor life depends strongly on the vessel condition. Generic information regarding works performed during reactor upgrade is also presented. In the present paper, the concept of the reactor renovation is proposed; and the key element is the replacement of the reactor vessel. Estimation of the technical implementation for such replacement is given. The concept schedule sequence is determined with forthcoming result of the reactor life-time extension for another 40-50 years.
Extrinsic and Intrinsic for online Classroom

The objectives of this research are 1) to examine how Thai youth in tertiary education feel about extrinsic and intrinsic rewards when studying online.2) to explore any similarities and differences between the two techniques. 3) to determine how students felt about the reward system used in this class. The samples in this research are 37 students. They are all the students who study in an online classroom for the whole semester during the COVID19 global pandemic (2019-2021). The questionnaire and the interview instruments were designed to clarify participants’ attitude and used a five point Likert scales and the entire reliability value is 0.80. The statistics used for data analysis were included descriptive statistics; and proportion and percentage, and inferential statistics such as multiple regression and Chi-square- test. The result disclose as follows : 1) The students showed that all of the four dimensions of this variables test of which one variables is extrinsic, have significant, positive relationships with satisfaction (r = .690, p < 0.01). 2) The results indicate that extrinsic and intrinsic variables had a negative effect on satisfaction (b = .051, p > 0.01), (b = .252, p > 0.01). 3) the results indicate that Feelings had a positive effect on satisfaction (β = .638, p < 0.01) and could predict satisfaction variables by 56.1 percent (adjusted R2 = 0.561), and extrinsic and intrinsic variables had a negative effect on satisfaction (p > 0.01).