Miracle-dz/UniFAR-FTUs huggingface dataset:
Landmark Prediction of Survival

Recent advancement in technology has lead to a wide range of genetic and biological markers that hold great potential in improving the prediction of survival outcomes. Although such new markers promise better disease prognosis, the accuracy in identifying short term and long term survivors remains unsatisfactory for most complex diseases. It has often been argued that short term clinical outcomes may have potential in predicting long term outcomes. In this paper, we propose to develop and evaluate conditional prognostic rules for the prediction of long term outcomes based on baseline marker information along with short term outcome status at an earlier landmark time. When there are multiple markers available, we construct an optimal composite score by fitting a proportional hazards working model for the conditional survival distribution. We also provide inference procedures for evaluating the incremental value of new markers in landmark prediction. The accuracy of the score is evaluated non-parametrically based on inverse probability weighting. Resampling procedures are proposed to derive estimation procedures for the accuracy measures. With a real example and numerical studies, we demonstrate that the proposed procedures perform well in finite samples.
Comprehensive Study on the Impact of Sternotomy Wires on UWB WBAN Channel Characteristics on the Human Chest Area

This paper presents a comprehensive study on the impact of the sternotomy wires on the characteristics of ultra wideband (UWB) radio propagation channel in the human chest area. The study is conducted using two simulation models: a planar layer model and a three-dimensional elliptical layer model. The study includes antennas designed for on-body and in-body communications. Furthermore, the measured data and propagation path calculations are presented to verify the simulation results. The main purpose is to show how the steel wires affect the on-body channel characteristics and in-body propagation within the tissues when the monitoring antennas are located in close vicinity of the human body. The study is conducted by evaluating: 1) channel characteristics in both frequency and time domains; 2) 2D power flow figures; and 3) Poynting vector values. Furthermore, the impact of the fat layer thickness on the visibility of sternotomy wires is studied. Moreover, the impact of sternotomy wires is studied for the case of the recently operated patient, for which the sternotomy wires are on the sternum bone surface, as well as for the case where the sternotomy wires are embedded into the sternum bone. It is found that sternotomy wires have a clear impact on the channel. The strength of the impact depends on the antenna types used by the monitoring devices, the thickness of the fat layer in the sternum area, and whether the sternotomy wires are on the sternum surface or whether they have already been embedded on the sternum as it happens with time.
Providing a Four-layer Method Based on Deep Belief Network to Improve Emotion Recognition in Electroencephalography in Brain Signals

Background: One of the fields of research in recent years that has been under focused is emotion recognition in electroencephalography (EEG) signals. This study provides a four-layer method to improve people's emotion recognition through these signals and deep belief neural networks. Methods: In this study, using DEAP dataset, a four-layer method is established, which includes (1) preprocessing, (2) extracting features, (3) dimension reduction, and (4) emotion identification and estimation. To find the optimal choice in some of the steps of these layers, three different tests have been conducted. The first is finding the perfect window in feature extraction section that resulted in superiority of Hamming window to the other windows. The second is choosing the most appropriate number of filter bank and the best result was 26. The third test was also emotion recognition that its accuracy was 92.93 for arousal dimension, 92.64 for valence dimension, 93.14 for dominance dimension in two-class experiment and 76.28 for the arousal, 74.83 for the valence, and 75.64 for dominance in three-class experiment. Results: The results of this method show an improvement of 12.34% and 7.74% in two- and three-class levels in the arousal dimension. This improvement in the valence is 12.77 and 8.52, respectively. Conclusion: The results show that the proposed method can be used to improve the accuracy of emotion recognition.
Analyzing Personality Traits and External Factors for Stem Education Awareness using Machine Learning

The purpose of the paper is to present the personality traits and the factors that influence a student to pursue STEM education using machine learning techniques. STEM courses have high regard because they play a vital role in global technology, inventions and the economy. Educational Data Mining helps us to identify patterns and relationships in a large educational database. On the other hand, Machine Learning facilitates decision making process by enabling learning from the dataset. A survey comprising of an extensive variety of questions regarding STEM education was conducted and the opinions of students from various backgrounds and disciplines were collected. A dataset was generated based on the responses from students. Machine Learning algorithms (one class-SVM and KNN) applied on this dataset emphasizes variety of courses offered, research-oriented learning, problem-solving approach, a good career with high paying job are some of the factors which may influence a student to choose STEM course.
Development of a Customized High-Speed Delta Robot

The Robot industry is playing one of the key roles of global market and economic development of Taiwan. In recent years, the Taiwan official is inspired and has encouraged the development of the emerging industry. This study focuses on developing the industrial 3-axis Delta parallel robot system due to its advantages of high-precision, high-speed, high repeatability, long life span, and stable mechanism. For shortening the product development time, different geometric design software, Solidworks and RecurDyn, are employed to accomplish the key components design, simulation, and analysis. The practical implementation uses the Taiwan-made key components including servo motor, actuator, transmission elements, and various controllers. It is hopefully expected that Taiwan can keep up with the torrent of the global 4th industry revolution and develop the cutting-edge robot system which will create drastic profits for Taiwan.
Select-and-Fill-in Concept Map Scores as a Measure of Undergraduate Students' Connected Understanding of Introductory Astronomy.

This study was designed to explore the validity of scores from a select-and-fill-in (SAFI) concept map assessment as a measure of 130 undergraduate students' connected understanding of introductory astronomy. Scores from SAFI maps created for this purpose possessed high internal consistency and showed large mean increases from the beginning to the end of the astronomy course. The SAFI map scores exhibited large relationships with scores from direct-instruction multiple-choice examinations and with scores from a relatedness ratings measure, taken together and separately, for students overall and when examined separately by gender. Results provide initial evidence of the validity of scores from SAFI maps as measures of connected understanding of introductory astronomy in ethnically diverse undergraduate students. (Contains 26 references.) (Author/SLD) ******************************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. ********************************************************************************
T-COUNT OPTIMIZATION OF QUANTUM CARRY LOOK-AHEAD ADDER

OF THESIS T-COUNT OPTIMIZATION OF QUANTUM CARRY LOOK-AHEAD ADDER With the emergence of quantum physics and computer science in the 20 century, a new field was born which can solve very difficult problems in a much faster rate or problems that classical computing just can’t solve. In the 21 century, quantum computing needs to be used to solve tough problems in engineering, business, medical, and other fields that required results not today but yesterday. To make this dream come true, engineers in the semiconductor industry need to make the quantum circuits a reality. To realize quantum circuits and make them scalable, they need to be fault tolerant, therefore Clifford+T gates need to be implemented into those circuits. But the main issue is that in the Clifford+T gate set, T gates are expensive to implement. Carry Look-Ahead addition circuits have caught the interest of researchers because the number of gate layers encountered by a given qubit in the circuit (or the circuit’s depth) is logarithmic in terms of the input size n. Therefore, this thesis focuses on optimizing previous designs of out-of-place and in-place Carry Look-Ahead Adders to decrease the T-count, sum of all T and T Hermitian transpose gates in a quantum circuit.
Generating Affixed Words from a Root Word and Getting Lemma from Affixed Word in Bahasa: Indonesian Language

Previously, there were morphological analyzer and lemmatization method for Bahasa: Indonesian language, yet they have not handled all occurred cases. Therefore, we develop an algorithm which combines two tasks; they are to generate affixed words from a root word and vice versa. The current morphological analyzer to generate affixed words has not covered in analyzing two words, whilst the current lemmatization method cannot find out the lemma from an affixed word which has confix and reduplication. Hence, we will cover these issues in order to enhance the current methods. The algorithm concerns only in Bahasa. The algorithm to generate affixed word is based on the two-level morphological analyzer, while refinement of lemmatization method is based on rule precedence and token checking. After implementing the algorithms, we find out that affixed word produced is 12.63% productive words, 86.98% non-productive words, and 0.39% incorrect words for the affixed word, whilst lemmatization can achieve 96.11% accuracy.
Performance Analysis of Low-Cost Infrared Sensors for Multi-Robot Localization and Communication

In this paper, we produced a study for choosing a suitable environment for indoor localization and communication among several robots by using low-cost infrared sensors. This study is used to compare the performance of the infrared sensors for measuring the distances and the range of communication among robots at indoor environments. This environment is tested under the influence of the sun and the fluorescent lights and with different angles of viewing among these sensors. Practical circuits for these infrared sensor are built and tested in different environments with different angles of view to choose a suitable performance of these sensors.
Simulation and Position Control of a Quadrotor UAV

The aim of this project was to produce a simulation of the School of Engineering and Information Technology’s recently purchased AscTec Pelican Quadrotor (QRT) and subsequently determine if an inner loop (attitude) – outer loop (position) control architecture would stabilise the system in hover. The motivation to perform this work is to enable further research into UAV control by producing an accurate simulation of the QRT’s dynamics. Simulations produced for other aircraft in SEIT were used as inspiration in development. The simulation developed is accurate due to the implementation of two key factors. The first is the use of helicopter aerodynamic theory to model the contribution of the rotors to the applied forces and moments. The numerical solution of the non-linear rotor thrust problem appears to be a first in QRT simulation. Secondly, the response of the aircraft is then determined using the exact non-linear 6 degree-of-freedom rigid body dynamics. All simulated aerodynamics are dependent on the relative wind vector and therefore the simulation promises to be accurate for flight conditions other than hover, such as forwards/rearwards, up/down and sideward flight. Other aerodynamic and dynamic effects were investigated but discarded due to either the nature of the particular system precluding their manifestation and/or as an order of magnitude analysis proved their relative contribution minimal. The simulation’s aerodynamics were validated by analysing figures of the generated forces/moments and the dynamics were validated by sanity checking open loop responses. An inner loop – outer loop cascading control system was then applied to attempt to stabilise the system in the presence of wind turbulence and sensor noise that would be experienced in actual flight. Importantly, the simulation includes finite controller update rates and approximate motor/rotor response and sensor noise models to further replicate actual operation of the QRT. The simulation predicts that the control system is able to stabilise the QRT in the presence of winds of at least 50 kilometres per hour. It is observed that sensor noise significantly reduces the QRT’s stability. In all cases the controllers were tuned by trial and error. By demonstration of sufficient response to operating conditions, it is determined that the proposed control architecture performs satisfactorily for future implementation on the QRT.
CREW Revisited in 2007 the Year of Women in Engineering: An Update on Women's Progress in the Australian Engineering Workforce

This report revisits a study that was carried out in 1999, the Careers Review of Engineering Women (CREW). The original review showed that women engineers were generally less happy with their career than their male counterparts, and were more inclined to leave the profession. The 2007 report show that this has improved slightly (for men as well), however problems of sexual harassment, workplace-bullying (of men and women) and discrimination are still big concerns.
Myth and reality: uncovering and discovering the nurses of St George's Hospital, London 1850-1900

The history of 19th century nursing reforms has focussed almost entirely on the activities and lives of nurse leaders, to the exclusion of the ordinary nurses. The lives of such nurses at one London hospital, St George's, have been investigated using a methodology based on prosopographical techniques. It was found that by the end of the century, far from becoming the exclusive preserve of middle class women, as some historians have argued, the Nursing Department at this particular hospital had become a melting pot of social classes. Appointment and promotion depended on ability rather than social position, and many women at the Hospital viewed nursing as a career, rather than a stop-gap before marriage. Evidence has also been accumulated which challenges the image of late 19th century nurses as being meek and docile women. The nurses at St George's were prepared to challenge the authorities to gain recognition for their various causes. Between 1850 and 1900, the Hospital Managers focussed increasingly on improving conditions of employment (including wages, accommodation and holidays) as a means of achieving stability within the Nursing Department, and of attracting a 'better quality' of woman. Nursing training was introduced during the fifty years of this study, although this was a slow process compared to its introduction at other hospitals. Financial considerations appeared to play a greater role in the development of probationer schemes, than a desire to improve the quality of nursing within the Hospital. The study of a group of Victorian nurses, such as this, provides insight into the development of nursing during the period, and reveals details which contradict the writings of nurse reformers. It also aids in the understanding of wider issues, including the changing role of women in Victorian society, and in particular their increasing participation in the labour market.
SDNizing the Wireless LAN - A Practical Approach

The emerging Internet of Things (IoT) paradigm and a plethora of diverse applications provision more ﬂexi-ble network management. Software Deﬁned Networking (SDN) occupies the pivotal role in realizing such ﬂexible network management. However, the gain of this potential panacea is still unmeasurable in a real sense especially when wireless medium is part of the equation, as the validation frameworks mostly skip capturing realistic system dynamics. In this paper, we study the performance gain of SDN control implemented in a physical testbed comprising of a virtualized core and a WLAN access network. With this contribution, we aim at realizing a more realistic environment where the impact of system dynamics on the stakeholders (users and operators) may be studied. We developed a mechanism to map the logical wireless channels over the physical wireless interface of the access point. SDN (OpenDaylight) control application for mobility management, the mapper tool, a visualization and con-trol GUI, and Android applications are amongst the main contribution of this work.
Performance Optimization Over Wireless Links With Operating Constraints

PERFORMANCE OPTIMIZATION OVER WIRELESS LINKS WITH OPERATING CONSTRAINTS Shiny Abraham Old Dominion University, 2012 Director: Dr. Dimitrie C. Popescu Wireless communication is one of the most active areas of technological inno­ vations and groundbreaking research ranging from simple cellular phones to highly complex military monitoring devices. The emergence of radios with cognitive capabil­ ities like software defined radios has revolutionized modern communication systems by providing transceivers which can vary their output waveforms as well as their demodulation methods. This adaptability plays a pivotal role in efficient utilization of radio spectrum in an intelligent way while simultaneously not interfering with other radio devices operating on the same frequency band. Thus, it is safe to say that current and future wireless systems and networks depend on their adaptation capability which in turn presents many new technical challenges in hardware and protocol design, power management, interference metrics, distributed algorithms, Quality of Service (QoS) requirements and security issues. Transmitter adaptation methods have gained importance, and numerous transmitter optimization algorithms have been proposed in recent years. The main idea behind these algorithms is to optimize the transmitted signals according to the patterns of interference in the op­ erating environment such that some specific criterion is optimized. In this context, the objective of this dissertation is to propose transmitter adaptation algorithms in conjunction with power control for wireless systems focusing on performance opti­ mization based on operating constraints. Specifically, this dissertation achieves joint transmitter adaptation and power control in the uplink and downlink of wireless sys­ tems with applications to Multiple-Input-Multiple-Output(MIMO) wireless systems and cognitive radio networks. In addition, performance of the proposed algorithms are evaluated in the context of fading channels, taking into consideration the timevarying nature of wireless channels.
Ensemble learning based Architecture Vulnerability Factor calculation using partial feature set in processors

With the scaling technology, soft error induced bit upsets are increasingly threatening the processor reliability. Processor designers require effective tools or methodologies to estimate the often-used metric Architectural Vulnerability Factor (AVF). This paper presents an ensemble learning based AVF calculation methodology for fast reliability assessment. Instead of the entire feature set, only partial non-critical attributes are selected to build the predictive model so that many performance counters can be removed or shut down for saving memory space and power consumption. Millions of data collected from a cycle-accurate simulator sim-SODA, are trained by the latest learning methods in Tensorflow. The SPEC2000 results demonstrate the instanced ensemble learning-random forest and Ada-boost perform nearly perfect accuracy, better than linear regression, and neural network.
Towards Unconstrained Face Recognition Using 3D Face Model

Over the last couple of decades, many commercial systems are available to identify human faces. However, face recognition is still an outstanding challenge against different kinds of real world variations especially facial poses, non-uniform lightings and facial expressions. Meanwhile the face recognition technology has extended its role from biometrics and security applications to human robot interaction (HRI). Person identity is one of the key tasks while interacting with intelligent machines/robots, exploiting the non intrusive system security and authentication of the human interacting with the system. This capability further helps machines to learn person dependent traits and interaction behavior to utilize this knowledge for tasks manipulation. In such scenarios acquired face images contain large variations which demands an unconstrained face recognition system.
Source coding with channel, distortion, and complexity constraints

Data compression methods have progressed from coding a simple alphabet according to known probabilities to a multistage process involving breaking down complex data structures, estimating conditional probabilities, and producing an output data stream. A variety of methods exist for converting alphabet symbols with known or estimated probabilities into a compressed bit stream. Arithmetic coding is one method that allows great efficiency and generality for describing the data. This dissertation presents a generalization of arithmetic coding which allows data compression to be performed onto constrained channels. This is a natural endeavor since compressed data must be stored or transmitted and some constraints typically exist on these processes. This generalization allows the compressed data stream to automatically meet constraints such as a run length limited constraint, a trellis code error correction constraint, or even a Morse code channel constraint. In addition, a simple implementation is presented using finite state machines. Results show that under certain circumstances simple finite state machines can perform compression as efficiently as the QM-coder used in the JPEG and JBIG international standards. In addition, discrete channel modulation can be performed more efficiently than currently employed fixed rate encoders, although error propagation is increased. Joint compression and modulation operations can be more efficient and less complex than separate operations. In this dissertation probability estimation and modeling aspects of a data compression system are discussed. Transform coders are analyzed in some detail, leading to a prediction of bit rate and distortion for a class of encoders including the JPEG standard. A three-way trade-off between computation and bit rate and distortion is investigated. Lastly, a brief examination of minimum entropy quantization is made in the context of images compression with a maximum error criterion.
Emoji and Chernoff - A Fine Balancing Act or are we Biased?

We seek to answer the question on whether different geometrical attributes within a glyph can bias interpretation of data. We focus on a specific visual encoding, the Emoji, and evaluate its effectiveness at encoding multidimensional features. Given the anthropomorphic nature of the encoding we seek to quantify the amount of bias the encoding itself introduces, and use this to balance the Emoji glyph to remove that bias. We perform our analysis by comparing Emoji with Chernoff faces, of which they can be seen as direct descendant. Results shed light on how this new approach of feature-tuning in glyph design can influence overall effectiveness of novel multidimensional encodings.