Miracle-dz/UniFAR-FTUs huggingface dataset:
An Automated Approximation Methodology for Arithmetic Circuits

Arithmetic circuits like adders and multipliers are key workforces of many error resilient applications. Prior efforts on approximating these arithmetic circuits mainly focused on manual circuit level functional modifications. These manual approaches need high design time and effort. Due to this only a limited no. of approximate design points can be generated from the original circuit leading to a sparsely occupied pareto front. This work proposes an automated approximation methodology for arithmetic circuits. Proposed method approximates the gate level standard cell library and uses these approximate standard cells to modify the netlist of the original circuit. A heuristic design space exploration methodology is proposed to speed-up the design process. We integrate this methodology with traditional ASIC flow and validate our results using adders and multipliers of different bitwidths. We show that our methodology improves on existing state-of-the-art manual as well as automated design techniques by generating non-dominant pareto-fronts. An application case study (sobel edge detection) is shown using approximate arithmetic circuits generated by our methodology. In case of sobel edge detector, we show upto 50% energy improvements for hardly any quality degradation (PSNR ≥ 20dB).
A Compact THz Quasi TDS System for Mobile Scenarios

In this paper, a compact and affordable approach for terahertz spectroscopy is proposed. A quasi time-domain spectroscope, based on a multimode laser diode, is combined with a data acquisition setup consisting of an Arduino microcontroller platform and a Raspberry Pi single-board computer. The measurement results are verified with common laboratory equipment. A bandwith of more than 1 THz was achieved.
Energy Efficient Performance Analysis of NOMA for Wireless Down-link in Heterogeneous Networks under Imperfect SIC

In this paper, we analyze the performance of non- orthogonal multiple access (NOMA) for the down-link transmission of a Base-Band Unit (BBU) pool to multiple Radio Remote Heads (RRH) serving multiple types of cells (e.g., macro, micro, pico, and even femto) in a heterogeneous cloud radio access networks (H-CRAN). Our analytic model is intended for NOMA with imperfect successive interference cancellation (SIC) implementation for the wireless down-link in an H-CRAN. We conduct extensive numerical experiments to investigate the performance of the NOMA with imperfect SIC implementation taking into account power consumption levels at the remote radio head (RRH) of different cell types and front-hauling power. The numerical results reveal an interesting fact that increasing the imperfect SIC factor will degrade the energy efficiency (EE) of multi-cell cellular networks significantly.
Efficient Weight Reuse for Large LSTMs

Long Short-Term Memory (LSTM) networks have been deployed in speech recognition, natural language processing and financial calculations in recent years, and are beginning to be used in systems where low latency and low power are required. To meet such requirements, we propose a stall-free hardware architecture by reorganising the order of operations in an LSTM system and develop a unique blocking-batching strategy to reuse the LSTM weights fetched from external memory to optimise the benefits of on-chip memory with a limited size for a large machine learning model. Evaluation results show that our architecture can achieve up to 20.8 GOPS/W, which would be among the highest for FPGA designs targeting LSTM systems with weights stored in off-chip memory. Comparing to the state-of-the-art design using off-chip memory to store the weights, we achieve 1.65 times higher performance-per-watt efficiency and 1.60 times higher performance-per-DSP efficiency. When compared with CPU and GPU implementation, our novel hardware architecture is 23.7 and 1.3 times faster while consuming 208 and 19.2 times lower energy respectively, which shows that our approach contributes to high performance and low power FPGA-based LSTM systems.
A software-in-the-loop implementation of adaptive formation control for fixed-wing UAVs

This paper discusses the design and software-in-the-loop implementation of adaptive formation controllers for fixed-wing unmanned aerial vehicles ( UAVs ) with parametric uncertainty in their structure, namely uncertain mass and inertia. In fact, when aiming at autonomous flight, such parameters cannot assumed to be known as they might vary during the mission ( e.g. depending on the payload ). Modelingg and autopilot design for such autonomous fixed-wing UAVs are presented. The modeling is implemented in Matlab, while the autopilot is based on ArduPilot, a popular open-source autopilot suite. Specifically, the ArduPilot functionalities are emulated in Matlab according to the Ardupilot documentation and code, which allows us to perform software-in-the-loop simulations of teams of UAVs embedded with actual autopilot protocols. An overview of realtime path planning, trajectory tracking and formation control resulting from the proposed platform is given. The software-in-the-loop simulations show the capability of achieving different UAV formations while handling uncertain mass and inertia.
Multimodal Detection of Parkinson Disease based on Vocal and Improved Spiral Test

Previous studies have used data related to either voice or spiral drawing to detect Parkinson disease (PD). However, different people experience different symptoms and different levels of severity of PD. This paper proposes a multimodal approach combining voice and image test to enhance the reliability of detecting PD patients. To substantiate this idea, we have evaluated both voice and spiral test data using various machine learning models. The results based on the two types of dataset demonstrate an excellent level of accuracy for PD identification. Pairwise correlation and k-means clustering techniques are used to extract features from the vocal dataset. In this classification problem, the highest accuracy of 95.89% is obtained using an ensemble of 3 classification models. The Pearson's correlation is used to extract features from the image dataset. The best accuracy of 99.6% is achieved using the k-Nearest Neighbors classifier in the Dynamic Spiral Test (DST). An accuracy of 98.8% and 94.9% are achieved using the Logistic Regression classifier and the Adaptive Boosting classifier on the Static Spiral Test (SST) and Stability Test on Certain Point (STCP), respectively. A second ensemble making use of results from DST, SST, and STCP will provide the overall result of the spiral test. We also implement the multi-modal approach into a touch-enabled smartphone-based application to carry out preliminary PD tests conveniently, without the need of supervision of additional medical personnel or any specialized equipment. The final ensemble for the application makes use of the results of the respective ensemble from the vocal and spiral tests.
Driving in the Fog: Latency Measurement, Modeling, and Optimization of LTE-based Fog Computing for Smart Vehicles

Fog computing has been advocated as an enabling technology for computationally intensive services in connected smart vehicles. Most existing works focus on analyzing and optimizing the queueing and workload processing latencies, ignoring the fact that the access latency between vehicles and fog/cloud servers can sometimes dominate the end-to-end service latency. This motivates the work in this paper, where we report a five-month urban measurement study of the wireless access latency between a connected vehicle and a fog computing system supported by commercially available multi-operator LTE networks. We propose AdaptiveFog, a novel framework for autonomous and dynamic switching between different LTE operators that implement fog/cloud infrastructure. The main objective here is to maximize the service confidence level, defined as the probability that the tolerable latency threshold for each supported type of service can be guaranteed. AdaptiveFog has been implemented on a smart phone app, running on a moving vehicle. The app periodically measures the round-trip time between the vehicle and fog/cloud servers. An empirical spatial statistic model is established to characterize the spatial variation of the latency across the main driving routes of the city. To quantify the performance difference between different LTE networks, we introduce the weighted Kantorovich-Rubinstein (K-R) distance. An optimal policy is derived for the vehicle to dynamically switch between LTE operators’ networks while driving. Extensive analysis and simulation are performed based on our latency measurement dataset. Our results show that AdaptiveFog achieves around 30% and 50% improvement in the confidence level of fog and cloud latency, respectively.
Multi-step estimation of Multivariate GARCH models

Estimation of large time varying covariance matrices has proven difficult since the original multivariate volatility models were introduced. In this paper, we develop the empirical properties of a new class of MV-GARCH models capable of estimating large time-varying covariance matrices. We show that the problem of multivariate conditional variance estimation can be reduced to a series of univariate GARCH processes plus an additional conditional correlation estimator. We use the model to estimate a conditional covariance of up to 100 assets using S&P 500 Sector Indies and Dow Jones Industrial Average stocks. This new estimator demonstrates very strong performance especially considering the estimators easy of implementation.
On Some Examples of Quadratic Functionals of Brownian Motion

During the last few years, several variants of P. Levy's formula for the stochastic area of complex Brownian motion have been obtained, and are of interest in various domains of applied probability, particularly in relation with polymer studies. The method used by most authors is the diagonalisation procedure of Paul Levy. In our paper, we derive one such variant of Levy's formula, due to Chan, Dean, Jansons and Rogers, via a change of probability method, which reduces the computation of Laplace transforms of Brownian quadratic functionals to the computations of the means and variances of some adequate Gaussian variables. We then show that with the help of linear algebra and invanrance properties of the distribution of Brownian motion, we are able to derive simply three other variants of Levy's formula.
Linking ITCZ Migrations to the AMOC and North Atlantic/Pacific SST Decadal Variability

We examine the link between migrations in the intertropical convergence zone (ITCZ) and changes in the Atlantic meridional overturning circulation (AMOC), Atlantic multidecadal variability (AMV), and Pacific decadal oscillation (PDO). We use a coupled climate model that allows us to integrate over climate noise and assess underlying mechanisms. We use an ensemble of ten 300-yr-long simulations forced by a 50-yr oscillatory North Atlantic Oscillation (NAO)-derived surface heat flux anomaly in the North Atlantic, and a 4000-yr-long preindustrial control simulation performed with GFDL CM2.1. In both setups, an AMV phase change induced by a change in the AMOC’s cross-equatorial heat transport forces an atmospheric interhemispheric energy imbalance that is compensated by a change in the cross-equatorial atmospheric heat transport due to a meridional ITCZ shift. Such linkages occur on decadal time scales in the ensemble driven by the imposed forcing, and internally on multicentennial time scales in the control. Regional precipitation anomalies differ between the ensemble and the control for a zonally averaged ITCZ shift of similar magnitude, which suggests a dependence on time scale. Our study supports observational evidence of an AMV–ITCZ link in the twentieth century and further links it to the AMOC, whose long-time-scale variability can influence the phasing of ITCZ migrations. In contrast to the AMV, our calculations suggest that the PDO does not drive ITCZ migrations, because the PDO does not modulate the interhemispheric energy balance.
Combination of Example-based and SMT-based Approaches in a Chat-oriented Dialog System

This paper compares and contrasts example-based and statistical machine translation (SMT) approaches for building a chat-oriented dialog system, and investigates a combined method that addresses the advantages and disadvantages of both approaches. In particular, we compare two example-based (EBDM) techniques: syntactic-semantic similarity retrieval and TF-IDF based cosine similarity retrieval, as well as response generation using phrase-based SMT. Experiments utilize both movie and Twitter scripts, and performance was evaluated based on objective metrics (syntactic-semantic similarity and TF-IDF based cosine similarity evaluation metrics) and human subjective evaluation. Experimental results shows that the combined system provide the best performance. It may indicate that by combining both approaches, we could overcome the shortcomings of each approach.
WORK EMPOWERMENT AS AN ANTECEDENT OF ORGANIZATIONAL COMMITMENT IN THE HONG KONG QUANTITY SURVEYING PROFESSION

There is a widespread belief that empowerment of members of the workforce is a universal desirable. The rationale relates to problems of ‘command and control’ within larger and diverse organisations as well as the expectation that empowerment leads to greater commitment by employees to the organisation and, thereby, results in enhanced performance. This paper reports a pilot study of the relationship between empowerment and organisational commitment amongst quantity surveyors in four different types of construction industry organisations in Hong Kong. Organisational commitment comprises dimensions of affectiveness and continuance. Although analyses demonstrate that perceived empowerment does correlate with organisational commitment, further, more detailed study on affective and continuance commitment is recommended.
Authentic Leadership and Organizational Effectiveness : The Roles of Hope , Grit , and Growth Mindset

The study was to determine moderated mediation effects of hope, grit, and growth mindset on the relationship between authentic leadership and organizational effectiveness of office workers. Data were analyzed using SPSS PC+ Win. Ver. 21 and Process MACRO for SPSS. Results are as follows. First, correlations among authentic leadership, hope, growth mindset, grit and organizational effectiveness were all significant and positive. Second, growth mindset and grit had a moderating mediation effect on the relationship between authentic leadership and organizational effectiveness through hope. This study discussed ways to improve organizational effectiveness not only through authentic leadership, but also through hope, growth mindset, and grit.
Productivity to IT Woman Employees : The Rolesof Perceived Organizational Support

This study aims to examine empirically the effect of perceived organizational support on work productivity to IT woman employees. This study uses a quantitative method, data collection form questionnaire containing demographic data, scale perceived organizational support with an alpha value of 0.97 and work productivity scale with an alpha value of 0.942. The sampling technique uses purposive sampling. Respondents of this study were 73 IT woman employees. The data analysis technique in this study used regression analysis tests. The results showed that there was an effect of perceived organizational support on work productivity to IT woman employees at 16.6% and the residual is influenced by other factors.
ION-EXCHANGE, AND SORPTION PROPERTIES OF SELECTED CENTRAL EUROPEAN COALS

Several types of young brown coals from significant deposits in Central Europe were examined as potential materials for environmental applications. The chemical composition, ion-exchange properties, and sorption abilities of oxihumolites (weathered brown coals) from the North-Bohemian Coal Basin (Czech Republic) and lignites from the South-Moravian and West-Slovakian Coal Fields (belonging to the Vienna Basin) were measured. These low-rank coals contained high amounts of active organic constituents (humic acids), in some cases exceeding 80%. Thus, these coals are valuable as raw materials for non-energetic applications. Due to the presence of various cationexchange sites (primarily carboxylic and phenolic functional groups), the young brown * Corresponding author: Tel. : +420-475 284 148; fax: +420-475 284 158. E-mail address: pavel.janos@ujep.cz (P. Janoš) The exclusive license for this PDF is limited to personal website use only. No part of this digital document may be reproduced, stored in a retrieval system or transmitted commercially in any form or by any means. The publisher has taken reasonable care in the preparation of this digital document, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained herein. This digital document is sold with the clear understanding that the publisher is not engaged in rendering legal, medical or any other professional services. Pavel Janoš, Lucia Závodská, Juraj Lesný et al. 72 coals were very efficient in retaining heavy metal cations from aqueous solutions, with a metal binding capacity ranging typically from ca. 0.20 to 0.70 mmol/g. This was shown for the Cu, Zn, and Co ions. However, it was demonstrated that these coals also are capable of retaining ionogenic organic compounds (both basic as well as acidic dyes, such as Methylene Blue and Egacid Orange), and less polar organic contaminants (such as chlorophenols). It was shown that the young brown coals contain rather low concentrations of dangerous radionuclides, heavy metals, and other potentially hazardous elements, at levels that do not significantly exceed the average values in the Earth‘s crust. This favours their applications in various remediation technologies.
Synthesis , Characterization and Anti-prostatic Hyperplasia Activity of 1-( 5-Hydroxy-3-methyl-1-phenyl-1 H-pyrazol-4-yl ) Octadecan-1-One

Novel ligand, 1-(5-hydroxy-3-methyl-1-phenyl-1h-pyrazol-4-yl) octadecan-1-one (HMPPO) was synthesized by the reaction between 3-methyl-1-phenylpyrazol-5-one and octadecanoyl. HMPPO was characterized based on elemental analysis, IR, 1 HNMR and 13 CNMR spectroscopy. Physical properties such as colour, melting points and solubility profile were also determined for HMPPO. Spectroscopic analysis showed that HMPPO existed in the enol form. The solubility data showed that HMPPO was hydrophobic. Furthermore the biological activities of the HMPPO against benign Prostatic Hyperplasia (BPH) cells were studied. HMPPO reduced prostate specific antigen (PSA) significantly (P<0.05) relative to the hormone control ‘HC’ group. The reduction in PSA concentration may have been as a result of decrease in proliferation of prostatic cells in the test groups since PSA level is known to elevate in prostatic lesion due to cellular proliferation. HMPPO arrested growth of prostatic cells in the test groups leading to decreased secretion of prostatic acid phosphatase in the prostatic cells. There was significant increase (P<0.05) in relative prostate weight of ‘HC’ group compared to the test group HMPPO and Finasteride group. The result of this study showed that HMPPO have inhibitory effect on the development of benign prostatic hyperplasia.
Vibration Analysis of an Embedded Actuator Based UAV

This paper presents the results of a Finite Element based vibration analysis of a solar powered Unmanned Aerial Vehicle (UAV). The purpose of this paper was to quantify the free vibration, forced vibration response due to differing point inputs in order to predict the relative response magnitudes and frequencies at various wing locations of vibration induced power generators (magnet in coil) excited by gust and/or control surface pulse-decays used to help power the flight of the electric UAV. A Fluid Structure Interaction (FSI) study was performed in order to ascertain pertinent design stresses and deflections as well as aerodynamic parameters of the UAV airfoil. The 3.048 m (10 ft) span airfoil is modeled using Mylar as the primary material. Results show that the free mode in bending is 3.0 Hz while the first forced bending mode is on range of 16.2 to 16.7 Hz depending on the location of excitation. The free torsional bending mode is 28.3 Hz, and the first forced torsional mode is range of 26.4 to 27.8 Hz, depending on the location of excitation. A case study regarding the optimal placement of the embedded actuators was also carried out and results are summarized herein. A Fluid Structure Interaction (FSI) analysis was also carried out which showed the coefficients of aerodynamic drag and lift of to be 0.0052 and 0.077, respectively.
Revisiting the Contribution of Input and Output in the Improvement of Speaking Fluency of Iranian EFL Speakers

Fatemeh Shahamirian Department of Foreign Languages and linguistics, Shiraz University Iran ABSTRACT The present qualitative research, using an open interview, intended to identify the proportion of contribution of input and output and each of four language skills in improvement of English language speaking fluency of the most fluent EFL speakers who have picked up fluency in their own country. To accomplish this, 17 participants (7 females and 10 males) including 11 EFL learners in B.A. and M.A. degree and 6 EFL teachers (holding B.A. and M.A. degree) in English language institutes in Shiraz, Iran were purposefully selected. The number of participants, with age range of 19 to 55, depended on data saturation. The criterion for selecting the fluent speakers, besides the instructors and colleagues‟ knowledge of the participants‟ speaking fluency, was the Speaking Rubric scale chosen from the Common European Framework of Reference for Languages (2001). The results revealed that both input and output had impact on their fluency. However, the role of input was by far more pivotal. Moreover, although all language skills collaborated in the development of speaking fluency, the role of listening was by a great deal more appealing. Huge amounts of listening helped learners speak effortlessly. From the participants‟ viewpoints, it can be concluded that for enhancing speaking fluency, listening skill should become an inseparable part of the learners‟ daily schedule. The findings may make all the stakeholders aware to put more emphasis on listening as an input receptive skill which may have the greatest impact on improving speaking fluency.