Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi Wideband Hexagonal-Spiral Microstrip Band-Pass Filter for Wireless Applications

In this communication, multi-wideband micro-strip Hexagonal-Spiral (HS)band-passfilter is presented. The proposed multiband band-pass filterconsists of four spiral shunt quarter-wavelength short-circuited stubs separated by connecting lines with length of $\boldsymbol{\lambda}\mathbf{g}/2$ and $\boldsymbol{\lambda}\mathbf{g}/4$, respectively. Appropriate transmission zeros are generated to isolate the bands of proposed band-pass filter, as desired. From the simulated results, the offered wide bandwidth observed for dual band-pass filter is 240 MHz (0.8 GHz to 1.04 GHz) and 250 MHz (1.18 GHz to 1.43 GHz). The bandwidth for the proposed triple band pass filter are 220 MHz (0.64 GHz to 0.86 GHz), 100 MHz (1.38 GHz to 1.48 GHz), and 400 MHz (2.31 GHz to 2.71 GHz). The triple band HS filter is fabricated and tested with network analyzer. The measured results are in good agreement with the simulation results. These filters are suitable for GSM 900 MHz and WLAN (2.4 GHz) applications.
The Effect of Final Consonants in the Cognitive Process of Thai Language

Written nature of Thai language does not have spaces in a sentence like English and does not have Kanji characters as in Japanese. Words will be written continuously until the end of the sentence the judgement for separate words depends on human decisions. Therefore, cognitive processing is very important to separate words in the Thai language. This research studied the cognitive processing and influence of final consonants in the Thai language by using word identification tasks to verify the difference in time spent answering and correcting data, as there is no direct measurement. Therefore, the time spent on selected word and correctness ratio was the most important variable in the cognitive processing test. The differences of average duration for selected words were analyzed by ANOVA and t-test that is statistical analysis. The results showed that final consonants work as the space in English is used for separating words and sentences and can make the Thai language easier for detect words in Thai language and also reduce the confusion when separating words in the long run on sentences. It works as the accelerator of competency in cognition of Thai language and helps learners to receive more precise and faster information.
Real-time mobile video compression and streaming: live video from mobile devices over cell phone networks

The limited computing resources on mobile phones, the demands of real-time requirements, and the variable and error-prone nature of the bandwidth of cell phone networks make the task of streaming live video from cell phones very challenging. As such, computational simplicity and efficiency are a requirement for video encoders on mobile devices. This research presents core components of a mobile video compression algorithm that has been developed in this project to compress real-time video from cell phones. This work shows how the careful selection of video compression components can be used to strike a delicate balance between the computationally complex nature of video compression and the efficient utilization of the limited computing resources available on cell phones. Although optimality is never claimed, a method for compressing and streaming real-time video of 15 frames per second has been developed. The video encoder uses 5-3 wavelet transformation and a new subband aligned integer run-length encoding technique to compress video in real-time on mobile devices. The wavelet video encoder is adaptive, highly scalable, and can gracefully adjust video compression levels to match changing cell phone network bandwidth conditions. Further, because of the variability of the bandwidth of cell phone networks, the efficient streaming of real-time video over cell phone networks requires the ability to adapt the quality and amount of video being streamed to the available bandwidth. This research shows that without such adaptability, video frames will be dropped. Experiments presented herein show that without an adaptive framework over 50% of the video frames can be dropped. In response to this challenge, this research implements an application layer framework for the control of real-time streaming video originating from mobile devices to better utilize available bandwidth. The approach taken here aims to align the quality and transmission rate of live streaming video with the capabilities of cell phone networks. Using decision making and feedback from the receiving video decoder, this real-time mobile streaming video framework is able to sense network conditions and effectively predict the available bandwidth. This adaptive framework utilizes the scalable wavelet video encoder for video compression. In conjunction with the wavelet video encoder on the mobile device, the framework adapts in real-time the video quality and video frames transmitted per second to achieve a near 100% delivery rate. This work provides a thorough description of this framework along with numerous experimental results. Presented is a detailed examination of the features of the adaptive framework and how they relate to cell phone network conditions, the video being streamed, and the mobile computing resources available on the mobile device.
Analysis, measurement and cancellation of the bandwidth and amplitude dependence of intermodulation distortion in RF power amplifiers

The main emphasis in modern RF power amplifier (PA) research is on improving linearity while at the same time maintaining reasonably good efficiency, for which purpose external linearization in the form of feedforward or predistortion is often used. Linearity and linearization can be considered from both a fundamental signal (amplitude and phase conversions, AM-AM & AM-PM) and an intermodulation distortion (IMD) regeneration point of view, and since a study of intermodulation gives more information on the behaviour of an amplifier, linearity is studied in this thesis by analysing the amplitude and phase of IM components under varying signal conditions, i.e. as functions of temperature, modulation bandwidth and amplitude. To study the behaviour of IM components analytically, a Volterra model including electrothermal distortion mechanisms is developed and a simulation technique is introduced to determine how easily the amplifier can be linearized. An S-parameter characterization method for extracting the Volterra model and the simulation model is developed, and the amplitude and phase dependences of the IM components are shown by means of measurements performed by a novel technique developed here. The results show that the behaviour of IM components is more complicated than had commonly been expected. Three techniques are developed for eliminating the frequency dependence of IM components, impedance optimization, envelope filtering and envelope injection. In the envelope injection technique, a low frequency envelope signal is added to the input of the amplifier in order to improve both the bandwidth and amplitude range of the memoryless predistortion. The functionality of envelope injection is demonstrated by Volterra calculations, simulations and measurements, and the technique is applied to 1W, 1.8 GHz common-emitter BJT and common-source MESFET amplifiers. IM cancellation better than 20 dB is achieved over a wide range of bandwidths and amplitudes. It is concluded that an inherently linear amplifier is not necessarily easy to linearize any further using external techniques, but that the part of the distortion that varies with bandwidth and amplitude can be cancelled out using envelope injection and the remaining memoryless distortion by means of a simple polynomial RF predistorter. This results in good cancellation of distortion, and since both envelope injection and RF predistortion consume little power, both good efficiency and linearity can be achieved.
CuMF: scale matrix factorization using just ONE machine with GPUs

Matrix factorization (MF) is widely used in recommendation systems. We present cuMF, a highly-optimized matrix factorization tool with supreme performance on graphics processing units (GPUs) by fully utilizing the GPU compute power and minimizing the overhead of data movement. Firstly, we introduce a memoryoptimized alternating least square (ALS) method by reducing discontiguous memory access and aggressively using registers to reduce memory latency. Secondly, we combine data parallelism with model parallelism to scale to multiple GPUs. Results show that with up to four GPUs on one machine, cuMF can be up to ten times as fast as those on sizable clusters on large scale problems, and has impressively good performance when solving the largest matrix factorization problem ever reported.
Effects of Bias-Correcting Climate Model Data on the Projection of Future Changes in High Flows

Bias-correction methods are commonly applied to climate model data in hydrological climate impact studies. This is due to the often large deviations between simulated and observed climate variables. These biases may cause unrealistic simulation results when directly using the climate model data as input for hydrological models. Our analysis of the EURO-CORDEX (Coordinated Downscaling Experiment for Europe) data for the Northwestern part of Germany showed substantial biases for all climatological input variables needed by the hydrological model PANTA RHEI. The sensitivity for climatological input data demonstrated that changes in only one climate variable significantly affect the simulated average discharge and mean annual peak flow. The application of bias correction methods of different complexity on the climate model data improved the plausibility of hydrological modeling results for the historical period 1971–2000. The projections for the future period 2069–2099 for high flows indicate on average small changes for representative concentration pathway (RCP) 4.5 and an increase of approximately 10% for RCP8.5 when applying non-bias corrected climate model data. These values significantly differed when applying bias correction. The bias correction methods were evaluated in terms of their ability to (a) maintain the change signal for precipitation and (b) the goodness of fit for hydrological parameters for the historical period. Our results for this evaluation indicated that no bias correction method can explicitly be preferred over the others.
DE-IDENTIFICATION OF PROTECTED HEALTH INFORMATION PHI FROM FREE TEXT IN MEDICAL RECORDS

Medical health records often contain clinical investigations results and critical information regarding patient health conditions. In these medical records, along with patient health information, patient Protected Health Information (PHI) such as names, locations and date information can co-exist. As per Health Insurance Portability and Accountability Act (HIPAA), before sharing the medical records with researchers and others, all types of PHI information needs to be de-identified. Manual de-identification through human annotators is laborious and error prone, hence, a reliable automated de-identification system is need of the hour. In this work, various state of the art techniques for de-identification of patient notes in electronic health records were analyzed for their performance, based on the performance quoted in the literature, NeuroNER was selected to de-identify Indian Radiology reports. NeuroNER is a named-entity recognition text de-identification tool developed by Massachusetts Institute of Technology (MIT). This tool is based on the Artificial Neural Networks written in Python and uses Tensorflow machine-learning framework and it comes with five pre-trained models. To test the NeuroNER models on Indian context data such as name of the person and place, 3300 medical records were simulated. Medical records were simulated by extracting clinical findings, remarks from MIMIC-III data set. For collection of all the relevant Indian data, various websites were scraped to include Indian names, Indian locations (all towns and cities), and Indian Hospital and unit names. During the testing of NeuroNER system, we observed that some of the Indian data such as name, location, etc. were not de-identified satisfactorily. To improve the performance of NeuroNER on Indian context data, along with the existing NeuroNER pre-trained model, a new pre-trained model was added to handle Indian medical reports. Medical dictionary lookup was used to reduce number of misclassifications. Results from all four pre-trained models and the model trained on Indian simulated data were concatenated and final PHI token list was generated to anonymize the medical records to obtain de-identified records. Using this approach, we improved the applicability of the NeuroNER system to Indian data and improved its efficiency and reliability. 2000 simulated reports were used for transfer learning as training set, 1000 reports were used for test set and 300 reports were used for validation (unseen) set.
Network-enabled monitoring and stable control of dynamic systems

The integration of computers, communication, and control in modern distributed systems such as intelligent transit systems and industrial facilities has garnered a great deal of attention in recent years. This thesis presents an investigation into basic research, technology development, and implementation of monitoring and control strategies for networked-enabled dynamical systems. In view of the hierarchical nature of these systems, the thesis focuses on two important system layers; namely, networked control systems within the direct-control (servo) layer, and remote monitoring and supervisory control within the supervisory-layer. In the present work, a networked control system (NCS) comprises the traditional components of a control system such as a plant, sensors, actuators, controllers, and signal conditioning and modification devices, but may be geographically distributed and linked through a communication network. In particular, in an N C S , the traditional feedback control loops are closed through a real-time communication network. A primary objective of the present thesis is to investigate, analyze, develop, implement and test stable control strategies to overcome the transmission problems between sensors, actuators, and controllers in an N C S ; specifically, non-deterministic delay, losses, vacant sampling, and mis-synchronization of data/information. The term networked control is used in this thesis to mean the control of a networked system, and a networked system with a controller as an integral part is an N C S . In this thesis, a new networked control strategy is developed which takes advantage of the potential capability of constrained Model Predictive Control ( M P C ) to compensate for anticipated data transmission problems. The constructive and computationally inexpensive strategy, which is developed here, uses predictions of future control actions and estimations of possibly erroneous sensory signals, to maintain good performance and stability of a closed-loop N C S , through an innovative method of information buffering. Network and computational loads are effectively minimized by incorporating variable prediction horizons. Performance is further improved through adaptive weight sequencing enhancements. The analytical issues of system stability of the new networked control strategy are rigorously treated in the thesis. The analysis is carried out in two stages. In the first stage, prefect state measurement is assumed to develop the necessary and sufficient conditions for guaranteeing closed-loop asymptotic stability while utilizing predicted future control actions
Penyelesaian Numerik Hamburan Kuantum Potensial Sentral Dengan Metode Runge-Kutta

Telah dilakukan perhitungan tampang lintang total hamburan dengan metode gelombang parsial. Dalam metode ini, besaran yang menjadi kunci adalah geser fasa δl diperoleh dengan menyelesaikan persamaan diferensial bagian radial hamburan kuantum dengan dan tanpa potensial penghambur. Perhitungan Numerik yang dipilih adalah metode Runge-Kutta karena kemudahan aplikasi dan akurasi tinggi. Potensial hamburan yang digunakan adalah potensial Coulomb tertirai (Screened-Coulomb) yang telah diketahui parameter-parameter potensialnya sebagaimana telah disajikan oleh Salvat (Salvat et al, 1987) melalui metode variasi medan konsisten. Hamburan yang dimaksud adalah hamburan elektron-atom.
Laser Behavior of (E, E)-2, 5-Bis [2-(1-Methyl-1H-Pyrrole-2-Yl] Pyrazine (BMPP) Dye Hybridized with CdS Quantum Dots (QDs) in Sol-Gel Matrix and Various Hosts

The emission of a dye can be adjusted utilizing NPs and quenching or enhancement of photoluminescence of a dye by NPs dependent on the separation between dye molecule and NPs and mechanism of energy transfer [2]. There are of three kids of quenching tasks: static, dynamic and by electron / energy transfer. In static quenching, the dropping in emission intensity is a result of adsorption of the probe on the surface of QDs, activity a non-fluorescent complex among the fluorophore and quencher QDs, however, in dynamic quenching, the lowering of emission intensity is brought about by collision of the excited fluorophore with a quencher over the excited state lifetime. The third kind of quenching is because of radiative and non-radiative energy transfer among the dye molecule and QDs [3]. The fluorescence quenching is improved at shorter separations and it is relegated to proficient non-radiative energy transfer between a dye and the NPs [3]. ABSTRACT
A Review on Human-exoskeleton Coordination towards Lower limb robotic exoskeleton Systems

The study of lower extremity exoskeleton robots has been pursued for many years and is now receiving significant attention. A number of review articles have focused on describing the mechanical design of exoskeleton robots, their control methods, human–exoskeleton robot interfaces, and so on. None, however, have focused on the coordination of control between humans and these kinds of robots. In this paper, we examine the research regarding human–exoskeleton robot coordinated control to capture the current state-of-the-art. One hundred and fifty six relevant articles were collected and screened from the Web of science, and classified into six categories, based on human neurobiology and exoskeleton robots’ assistive effects. These categories were further subdivided according to their perspective on human–exoskeleton robots coordinated control. The paper extensively reviews various control methods we uncovered and how they are coordinated between wearer and exoskeleton robot.
Kalman Filter Applied to Ultrassonic-Based Level Sensoring

The following project suggests the use of a Kalman Filter for conditioning wave height signals, acquired from ultrasonic sensors present in the new wave basin of TPN ("Tanque de Provas Numerico", Portuguese for "Numeric Offshore Tank”), recently constructed in University of Sao Paulo – USP, named Hydrodynamic Calibrator (CH-TPN). The sensors are mounted on the frontal face of each of the 148 flaps present in the tank, and are responsible for the incident wave height measurements. These measurements are directly used in the active wave absorption algorithm, which is the great advantage of the tank. Currently, the wave height signals present noise and distortion, mainly due to mechanical problems that occurred during the sensors installation, which lead to spurious ultrasonic echoes and inaccurate wave height measurements. A low pass filter is being used to attenuate the signal noise together with a sensor mapping which exclude the worse sensors, but this configuration has three main disadvantages in this application: it delays the signal, which compromises severely the absorption control; presents a significant loss in wave height signal when the noise is more intense; and worsens multi-directional waves absorption. Aiming to have a better signal on each flap, it is suggested the use of the Kalman Filter, which is an “intelligent” filter, since it takes into count the system dynamic model and estimates the measurements weighting between the predictions and the values acquired by the sensors themselves. Another interesting feature of this kind of filter is that it allows sensor fusion, that is, it allows the use of more than one sensor to evaluate the same measurement, thus improving the estimation. The project involved designing the Kalman Filter to work with two different kinds of waves: regular waves, which have a constant and unique frequency; and irregular waves, which have a wide frequency spectrum. With the use of the Kalman Filter, it was expected that the wave re-reflection coefficient would be reduced from about 15% to about 5%, which is the value originally expected in the wave basin design. The project was divided in five basic phases: theoretical study, offline implementation, online implementation, tests and data acquisition, and finally, documentation of results. After implementation and tests, it was confirmed that the use of Kalman Filter applied to the wave height sensors enabled great improvement in both signal quality and absorption. However, it was not possible to utilize the Filter simultaneously in all 148 sensors due to little time available to perform its calculations. Still, it was possible to run the absorption algorithm and the Kalman filter for a full wall of the tank (39 flaps simultaneously). Several trials were held to evaluate objectively the performance improvement using the Filter. The expected reduction in the re-reflection coefficient, of about 5% to 10%, was achieved in most of the trials, proving the Filter’s efficiency and thus providing a new component in the CH-TPN software library.
C-LARSP: Developing a Chinese Grammatical Profile for Clinical Assessment in Malaysia

Lixian Jin from Speech and Language Therapy has published a chapter with collaborators based on her PMI2 research project completed in 2010. This research uses the fundamental principles of assessing grammatical development of young children for clinical language profiling, which originated from the research developed by British clinical linguists and now used in many countries around the world which adopt the principle to develop this clinical linguistic tool for their native languages. This Chinese version is one of the 12 languages included in the first book of such a collection. Future volumes will publish more languages using this principle.
Disaster Vulnerability and Social Capitals in the Gulf Coast and Flint, Michigan

v Introduction.1 Chapter 1. Risk Perceptions, Place Attachment, and Natural Resource Employment: Predicting Willingness to Move from a Threatened Coastline.4 Chapter 2. Predicting Self-Rated Physical and Mental Health Before and After the Announcement of the Flint Water Crisis.30 Chapter 3. Social Support, Religious Ecology, and Alcohol Misuse in the Gulf Coast.51 Bibliography.66 Vita.78