Miracle-dz/UniFAR-FTUs huggingface dataset:
Advanced control system for stand-alone diesel engine driven-permanent magnetic generator sets

The main focus is on the development of an advanced control system for variable speed standalone diesel engine driven generator systems. An extensive literature survey reviews the historical development and previous relevant research work in the fields of diesel engines, electrical machines, power electronic converters, power and electronic systems. Models are developed for each subsystem from mathematical derivations with necessary simplifications made to reduce complexity while retaining the required accuracy. Initially system performance is investigated using simulation models in Matlab/Simulink. The AC/DC/AC power electronic conversion system used employs a voltage controlled dc link. The ac voltage is maintained at constant magnitude and frequency by using a dc-dc converter and a fixed modulation ratio VSI PWM inverter. The DC chopper provides fast control of the output voltage by dealing efficiently with transient conditions. A Variable Speed Fuzzy Logic Core (VSFLC) controller is combined with a classical control method to produce a novel hybrid controller. This provides an innovative variable speed control that responds to both load and speed changes. A new power balance based control strategy is proposed and implemented in the speed controller. Subsequently a novel overall control strategy is proposed to co-ordinate the hybrid variable speed controller and chopper controller to provide overall control for both fast and slow variations of system operating conditions. The control system is developed and implemented in hardware using Xilinx Foundation Express. The VHDL code for the complete control system design is developed and the designs are synthesised and analysed within the Xilinx environment. The controllers are implemented with XC95108-PC84 and XC4010-PC84 to provide a compact and cheap control system. A prototype experimental system is described and test results are obtained that show the combined control strategy to be very effective. The research work makes contributions in the areas of automatic control systems for diesel engine generator sets and CPLD/FPGA application that will benefit manufacturers and consumers.
Gains from Markowitz Optimization: Evidence from Reoptimization of Mutual Fund Holdings

Prior studies have challenged the practical usefulness of Markowitz portfolio optimization in improving the return–risk trade-off in portfolio management. The authors approach this question from a unique angle by examining whether one can improve the performance of a large sample of actual mutual fund portfolios by reoptimizing the holdings using simple mean–variance optimization methods. The analyses produce compelling evidence of the benefits of Markowitz optimization. Simple portfolio optimization improves mutual fund portfolios’ risk-adjusted performance despite noisy expected return estimates inferred from mutual fund portfolio weights. Several alternative optimization strategies, including the risk-parity portfolio, minimum variance portfolio, mean–variance portfolio, and Sharpe ratio maximization portfolio, all outperform actual mutual fund portfolios in terms of the Sharpe ratio and other risk-adjusted performance measures. Moreover, the results are robust to subsamples partitioned on various dimensions. In contrast to the findings of DeMiguel et al. (2009), the authors find that the 1/N portfolio performs the worst.
Radiomics approach to quantify shape irregularity from crowd-based qualitative assessment of intracranial aneurysms

ABSTRACT The morphological assessment of anatomical structures is clinically relevant, but often falls short of quantitative or standardised criteria. Whilst human observers are able to assess morphological characteristics qualitatively, the development of robust shape features remains challenging. In this study, we employ psychometric and radiomic methods to develop quantitative models of the perceived irregularity of intracranial aneurysms (IAs). First, we collect morphological characteristics (e.g. irregularity, asymmetry) in imaging-derived data and aggregated the data using rank-based analysis. Second, we compute regression models relating quantitative shape features to the aggregated qualitative ratings (ordinal or binary). We apply our method for quantifying perceived shape irregularity to a dataset of 134 IAs using a pool of 179 different shape indices. Ratings given by 39 participants show good agreement with the aggregated ratings (Spearman rank correlation ). The best-performing regression model based on quantitative shape features predicts the perceived irregularity with
Performance of a calculator for diagnosing the cause of liver damage

Introduction/Objective. Making a calculator that would recognize patterns of abnormal liver function tests and link them to the most probable etiology could help clinicians in their initial orientation towards a definitive diagnosis in patients with liver damage. The aim of our study was to design, construct, and validate a calculator that based on a pattern of abnormalities in liver function tests of a patient with liver damage would propose the most probable etiology. Methods. Patterns of abnormal liver function tests for certain etiology of liver damage were extracted from distributions of actual values taken from reports in medical literature about patients whose etiology of liver damage was proven by reliable diagnostic tests. After setting up the calculator with the patterns extracted, its diagnostic value was checked under real-life conditions, on a sample of patients with liver damage whose etiology was established by the gold standard of diagnostics (biopsy or else). The calculator validation study was carried out at the Military Medical Academy in Belgrade during a two-year period (2015? 2016). Results. For all tested diagnoses, the calculator demonstrated a highly significant difference between the area under the receiver-operator curves? values and the value of 0.5 (p < 0.001), and high level of sensitivity (more than 90%, except for the model for chronic hepatitis) as well as relatively high specificity (more than 75%) were noted, indicating good ability of the calculator to detect etiology of liver damage. Conclusion. New calculators showed satisfactory sensitivity and specificity for revealing major liver damage etiologies.
Facial Feminization Surgery: The Ethics of Gatekeeping in Transgender Health

The lack of access to gender-affirming surgery represents a significant unmet health care need within the transgender community, frequently resulting in depression and self-destructive behavior. While some transgender people may have access to gender reassignment surgery (GRS), an overwhelming majority cannot afford facial feminization surgery (FFS). The former may be covered as a “medical necessity,” but FFS is considered “cosmetic” and excluded from insurance coverage. This demarcation between “necessity” and “cosmetic” in transgender health care based on specific body parts is in direct opposition to the scientific community’s understanding of gender dysphoria and professional guidelines for transgender health. GRS affects one’s ability to function in an intimate relationship, while FFS has the same impact on social interactions an, therefore may have a far greater implication for one’s quality of life. FFS is a cost-effective intervention that needs to be covered by insurance policies. The benefits of such coverage far exceed the insignificant costs.
Platform verification and secure program execution in embedded devices

Recently, hardware manufacturers are increasingly outsourcing their production process into countries with lower cost structure. Although this reduces the cost of hardware production, it also creates opportunity for attackers to hack into the supply chain and change the original design of the hardware components. Such changes could range from short circuiting a module (for instance random number generators) to inserting parasite circuits and new masks (such as hardware Trojan circuits). These kind of intrusions are difficult to detect through pure functional testing. Furthermore, attacks on runtime program attributes (eg. fault injection attacks) are increasing in number and sophistication. In this thesis we propose techniques for platform verification and secure program execution that can be used in low-end to medium-end embedded systems. Our design incorporates a pre-deployment device verification and dedicated security module that monitors the program’s properties during execution. Both our predeployment and runtime verification methods constitute compile and execution time computations to reduce the time required for security checks during runtime. In the core of this thesis, we analyse the current threats to the embedded systems platform and programs. This leads to two major contributions spanning the pre and post integration of embedded systems into the larger electronic equipment. We propose side channel based pre-deployment platform verification techniques. In our techniques we use instruction and basic block level side channel templates to identify anomalies within the target platform. Our approach does not require prior detailed knowledge of the inner workings of the program or the platform under test. Furthermore, we also propose the design of a generic runtime secure program execution architecture. Our proposal protects the target program’s runtime data, instructions and control flow jumps during its execution. To achieve this goal without affecting the performance of the main processor we introduce a dedicated hardware module. Finally, we provide the test implementations of our proposals along with their performance measures.
Machine Learning Algorithms for Optic Pathway Disease Diagnostics: A Review

Most of people are unaware that some of the indicators of optic pathway diseases such as stroke or tumor can be detected from the loss part of human vision, or referred as visual field defect. Ophthalmologist will manually examine the site, size and margin of the lesion from patient’s visual field points mapped by Humphrey Field Analyzer. Different site, size and margin of lesion indicates different type of defects and disease that associated with it. Therefore, an effective automated detection mechanism of multi class visual field defect is in demand to help decision making by ophthalmologist. In this paper, we review multiple techniques of supervised and unsupervised learning method for detection of optic pathway disease.
Vehicular ad hoc routing protocol with link expiration time (VARP-LET) information

This thesis presents a vehicular ad hoc routing protocol that uses link expiration time (LET) information in selection of routes. The proposed protocol is named as VARP-LET, which uses LET information to increase reliability and stability of the routes. LET information is used selectively in the route discovery mechanism to reduce the routing control overhead. In addition to LET a Route Break Indicator (RBI) message is introduced. RBI is generated when a link breakage is about to occur. A source node on receiving the RBI signal preemptively stops sending data packets through a route before it breaks. This provision decreases the packet loss. The effectiveness of LET and RBI is tested via network simulations with NS-2. These simulations show that VARP-LET protocol increases packet delivery ratio by 20.7% in street section mobility model and by 30% in highway mobility scenario compared to regular AODV protocol. It is also shown that the protocol significantly reduces frequent route failure and routing overhead.
Process Heuristics: Extraction, Analysis, and Repository Considerations

The motivation for this article is to present a method for extracting heuristics from a team of mission architects, referred to in this article as “designers” at NASA's Jet Propulsion Laboratory (JPL). The method for this study includes both focus group and individual interviews, as well as artifact analysis. The interviews led to insights about the role of heuristics within a design team and how documenting those heuristics can be of value to the team. The heuristics generated allowed for an overview of how designers at JPL perceived their own process heuristics. It was found that most heuristics were comprised a single, positively framed step to be carried out within the team, not just by an individual. Participants were also able to produce mainly informal actions they take, rather than formalized textbook approaches to design. It is hypothesized that the process heuristics generated are universal enough to be transferred out of the mission design domain and into another, if desired.
AutoMAP: Diagnose Your Microservice-based Web Applications Automatically

The high complexity and dynamics of the microservice architecture make its application diagnosis extremely challenging. Static troubleshooting approaches may fail to obtain reliable model applies for frequently changing situations. Even if we know the calling dependency of services, we lack a more dynamic diagnosis mechanism due to the existence of indirect fault propagation. Besides, algorithm based on single metric usually fail to identify the root cause of anomaly, as single type of metric is not enough to characterize the anomalies occur in diverse services. In view of this, we design a novel tool, named AutoMAP, which enables dynamic generation of service correlations and automated diagnosis leveraging multiple types of metrics. In AutoMAP, we propose the concept of anomaly behavior graph to describe the correlations between services associated with different types of metrics. Two binary operations, as well as a similarity function on behavior graph are defined to help AutoMAP choose appropriate diagnosis metric in any particular scenario. Following the behavior graph, we design a heuristic investigation algorithm by using forward, self, and backward random walk, with an objective to identify the root cause services. To demonstrate the strengths of AutoMAP, we develop a prototype and evaluate it in both simulated environment and real-work enterprise cloud system. Experimental results clearly indicate that AutoMAP achieves over 90% precision, which significantly outperforms other selected baseline methods. AutoMAP can be quickly deployed in a variety of microservice-based systems without any system knowledge. It also supports introduction of various expert knowledge to improve accuracy.
A Hardware Implementation of Neuro-PMD Model classifier based FPGA

A classifier (polarization mode dispersion) has been introduced in this article. The suggested NeuroPMD classifier uses various types of fiber optics, and it’s deviation effect properties to handle light transmission using Polarization Mode Desperation (PMD). The suggested classifier receives an unspecified signal with many percentage points, classifies it base on stored signals and shows the reliability of the received signal. The proposed system is built using VHDL, modeled by the Xilinx package (ISE 9.2i), the proposed NeuroPMD is implemented on the Spartan-3A XC3S700A kit. simulation and Implementation behavioral results demonstrate that the proposed model satisfies the specified operational requirements and gives solutions to overcome the scattering problems in the optical systems.
Deep learning-aided CBCT image reconstruction of interventional material from four x-ray projections

Interventional guidance aims at providing the radiologist with detailed information about the location and orientation of interventional tools such as guide wires and stents. Most commonly, this is done by acquiring fluoroscopic images using an interventional C-arm system. Due to its projective nature, fluoroscopy is restricted to provide information from two spatial dimensions, preventing an exact 3D localization of the interventional tools. Analogous to computed tomography for diagnostic imaging, four-dimensional (three spatial dimensions plus the temporal dimension) interventional guidance has the potential to drastically improve both the speed and accuracy of such interventions, but is currently impractical due to the excessively high dose that would be necessary for continuous cone-beam CT (CBCT) scanning at high frame rates. In this work we develop a novel deep learning-based approach to reconstruct interventional tools from only four x-ray projections. We train and test this deep tool reconstruction (DTR) network on simulated data. Only small deviations from the ground truth (GT) reconstruction of the tools were observed, both quantitatively and qualitatively, showing that deep learning-based four-dimensional interventional guidance has the potential to overcome the drawbacks of conventional interventional guidance in the future.
Retracted Article: Key technologies of cloud computing-based IoT data mining

We, the Editor and Publisher of the International Journal of Computers and Applications, have retracted the following article which was part of the Special Issue on Advanced Security Techniques for Cloud Computing and Big Data - New Directions: Rongqing Zhuo & Zhongxian Bai (2020) Key technologies of cloud computing-based IoT data mining, International Journal of Computers and Applications, DOI: 10.1080/1206212X.2020. 1738665 Since publication, it came to our attention that the articles published in this Special Issue were not reviewed fully in line with the journal's peer review standards and policy. We did not find any evidence of misconduct by the authors. However, in order to ensure full assessment has been conducted, we sought expert advice on the validity and quality of the published articles from independent peer reviewers. Following this post publication peer review, the Editor has determined that the articles do not meet the required scholarly standards to remain published in the journal, and therefore has taken the decision to retract. The concerns raised have been shared with the authors and they have been given the opportunity to respond. The authors have been informed about the retraction of the article. We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions. The retracted articles will remain online to maintain the scholarly record, but they will be digitally watermarked on each page as ‘Retracted’.
Review of Environmental Safety Research Based on Systematic Mapping Study: Taking CNKI Database as an Example

This paper applies the Systematic Mapping Study (SMS) to the review of environmental safety research in China. Different from the traditional systematic literature review, this study focuses on the classification and analysis of related literatures to form a number of quantitative, systematic visualization images to identify the current status and gaps in the research field. The paper follows the SMS analysis steps, takes the literature related to environmental safety research in recent 3 years from CNKI database as the analysis sample. SMS method is used to systematically analyze the publication trends, research types and research contributions, which offers a visual summary map of the field. The research results show that the SMS method can reflect the status quo of environmental safety research and identify research gaps efficiently and accurately, and can put forward targeted opinions accordingly.
Problem‐solving strategies used in anatomical multiple‐choice questions

Multiple‐choice questions (MCQ) in the anatomical sciences are often perceived to be targeting recall of facts and regurgitation of trivial details. Moving away from this assumption requires the design of purposeful multiple‐choice questions that focus on higher‐order cognitive functions as opposed to rote memorization. In order to develop such questions, it was important to first understand the strategies that students use in solving multiple‐choice questions. Using the think‐aloud protocol, this study seeks to understand strategies students use in solving multiple‐choice questions. Specifically, it seeks to uncover patterns in the reasoning process and tactics used when solving higher and lower order MCQ in anatomy. The research also provides insights onto how these strategies influence the student's probability of answering questions correctly.
A survey on engineering approaches for self-adaptive systems (extended version)

The complexity of information systems is increasing in recent years, leading to increased effort for maintenance and configuration. Self-adaptive systems (SASs) address this issue. Due to new computing trends, such as pervasive computing, miniaturization of IT leads to mobile devices with the emerging need for context adaptation. Therefore, it is beneficial that devices are able to adapt context. Hence, we propose to extend the definition of SASs and include context adaptation. This paper presents a taxonomy of self-adaptation and a survey on engineering SASs. Based on the taxonomy and the survey, we motivate a new perspective on SAS including context adaptation.
6 channels Velodyne versus planar LiDARs based perception system for Large Scale 2D-SLAM

The ability of self-localization is a basic requirement for an autonomous vehicle, and a prior reconstruction of the environment is usually needed. This paper analyses the performances of two typical hardware architectures that we evaluate in our 2D Simultaneous Localization and Mapping (2D-SLAM) system for large scale scenarios. In particular, the selected configurations are supposed to guarantee the possibility of integrating at a later stage mobile objects tracking capabilities without modifying the hardware architecture. The choice of the perception system plays a vital role for building a reliable and simple architecture for SLAM. Therefore we analyse two common configurations: one based on three planar LiDARs Sick LMS151 and the other based on a Velodyne 3D LiDAR VLP-16. For each of the architectures we identify advantages and drawbacks related to system installation, calibration complexity and robustness, quantifying their respective accuracy for local-ization purposes. The conclusions obtained tip the balance to the side of using a Velodyne-like sensor facilitating the process of hardware implementation, keeping a lower cost and without compromising the accuracy of the localization. From the point of view of perception, additional advantages arise from the fact of having 3D information available on the system for other purposes.