Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of small-scale deep learning architectures in Thai speech recognition

This paper presents a performance evaluation study for small-scale deep learning neural network for Thai speech recognition task. Convolutional neural network and long short term memory networks were built with a relatively small size dataset and small constructs. The aim of this study is to determine which method would be suitable for a small-scale deep learning study. Relatively small speech corpus was used to build deep-learning neural networks with two different architectures, including convolutional neural network (CNN) model and long short term memory (LSTM) model. Models were evaluated using cross validation technique and compare to one another. The result shows that CNN outperformed LSTM for a small-scale deep learning. This suggests that with the limited dataset and small-scale architecture CNN is a more suitable choice in the speech recognition study.
SIMO RSS measurement in Bluetooth low power indoor positioning system

This paper deals with the study of received signal strength (RSS) as an input reference used in Bluetooth Low Energy (BLE) Indoor Positioning System (IPS) for location estimation. In the IPS where there are fixed scanners and portable advertisers which are sending no additional data, the RSS is the only reference for location process. Therefore, it is important to suppress RSS fluctuation caused by fading. The proposed method uses spatial diversity (SIMO approach) in combination with frequency diversity. Two different distances between four antennas were tested and for a quarter of the wavelength additional arrangement using back-side reflector was taken.
Multiband 2×1 annular ring microstrip antenna with defected ground structure for c and ku band

A Multiband 2×1 annular ring microstrip antenna with Defected ground structure is proposed and investigated. A DGS is a defected etched periodic or non-periodic configuration in a ground plane of a microstrip antenna. To achieve band stop characteristics and to suppress higher order harmonics and mutual coupling between adjacent array elements and to minimize cross polarization DGS concept has been used. A single radiator antenna is not good enough to give required radiation characteristics while use of an antenna arrays offer improved directivity and efficiency compared to single element. Effect of the variation in the radiation characteristics by changing parameters of two different circular radios (R1 andR2) are studied in this work. A Multiband 2×1 annular ring microstrip antenna with Defected ground structure provides multiple bands for 5 GHz, 10 GHz and 13 GHz for different structure meanwhile it exhibits excellent radiation patterns with improved bandwidth and linear polarization. Major results are consistent with the simulation from IE3d simulator.
Real time controlling algorithm for vehicle to grid system under price uncertainties

Multi-directional flow of electricity can be possible by the implementation of vehicle-to-grid system (V2G), this system allows the two side flow of electricity. The stored energy in EV batteries can be sold back to the electric grid in peak hours for load and frequency management. Therefore, a control algorithm is required to enable frequency regulation services and control the EVs charging and discharging according to grid situation. Due to price uncertainties V2G control has become more complicated, because the electricity price changes for every hour. This paper consists of a V2G controlling algorithm, which helps to counter the price uncertainties in real time. By using the Markov chain technique a controlling algorithm has been formulated, with the unidentified switching probabilities, entitled as a Morkov decision process (MDP). Inherent assessment is featured in this model to find out the long term profits of current controlling operation with dynamic electricity price. To enhance the profit margin of EV owners a Q-learning algorithm is adopted for control purposes. The proposed algorithm is then evaluated under different pricing scenarios. The results proved that, the proposed algorithm can provide better frequency regulation services, as well as increase the profits for EV owners, as compared to conventional EV charging schemes.
High-Performance QCM Humidity Sensors Using Acidized-Multiwalled Carbon Nanotubes as Sensing Film

A series of high-performance quartz crystal microbalance humidity sensors were fabricated by using acidized-multiwalled carbon nanotubes (MWCNTs) as sensing film. The detection process is carried out in the static humidity generator at room temperature. The material characteristics of the thin films were analyzed by Raman spectra, X-ray photoelectron spectroscopy, FT-IR spectroscopy, and transmission electron microscopy. The experimental results manifested that acidized-MWCNTs exerted high-excellent dynamic response sensitivity (frequency shift reached -21037 Hz at 95%RH), fast response-recovery time (49s/6s), logarithmic linear relationship, small humidity Hysteresis, and outstanding reproducibility and reversibility. Furthermore, the adsorption dynamics of water vapor molecules mechanism was also analyzed.
Wireless energy and information transfer in networks with hybrid ARQ

In this paper, we consider a class of wireless powered communication devices using hybrid automatic repeat request (HARQ) protocol to ensure reliable communications. In particular, we analyze the trade-off between accumulating mutual information and harvesting RF energy at the receiver of a point-to-point link over a time-varying independent and identically distributed (i.i.d.) channel. The transmitter is assumed to have a constant energy source while the receiver relies, solely, on the RF energy harvested from the received signal. At each time slot, the incoming RF signal is split between information accumulation and energy accumulation with the objective of minimizing the expected number of re-transmissions. A major finding of this work is that the optimal policy minimizing the expected number of re-transmissions utilizes the incoming RF signal to either exclusively harvest energy or to accumulate mutual information. This finding enables achieving an optimal solution in feasible time by converting a two dimensional uncountable state Markov decision process (MDP) with continuous action space into a countable state MDP with binary decision space.
Hydrogels for Atopic Dermatitis and Wound Management: A Superior Drug Delivery Vehicle

Wound management, in addition to presenting a significant burden to patients and their families, also contributes significantly to a country’s healthcare costs. Treatment strategies are numerous, but in most cases not ideal. Hydrogels, three-dimensional polymeric materials that can withstand a great degree of swelling without losing structural integrity, are drawing great attention for their use as topical wound management solutions in the form of films and as vehicles for drug delivery, due to their unique properties of high water content, biocompatibility, and flexibility. Hydrogels, both naturally and synthetically derived, can be tuned to respond to specific stimuli such as pH, temperature and light and they are ideally suited as drug delivery vehicles. Here we provide a brief overview of the history and characteristics of hydrogels, assess their uses in wound management and drug delivery, and compare them with other types of common drug delivery vehicle.
Design of a Framework for Knowledge Analytics

With access to Internet and Open Data initiatives, large amounts of data are available for analysis. Data Analytics has grown over the years delivering insights from data in a variety of forms ranging from structured to highly unstructured data. With the development of Semantic Web, many applications generate semantic data in significant amounts. Semantic data exist in the form of Resource Description Framework (RDF) triples, Ontologies and Simple Knowledge Organization System (SKOS). Semantic data are knowledge structures in the form of graphs with well defined hierarchies of both concepts and relations in ontology of the domain. Analyzing such knowledge structures requires different methods as they are fundamentally different from a regular graph and regular analytical operations on knowledge structures may misinterpret the actual data. We define new analytical operators which consider the semantic constraints on data to deliver meaningful insights. In this paper, we present the design of an analytical framework for knowledge structures.
Solving dynamic multi-objective optimization problems via support vector machine

Dynamic Multi-objective Optimization Problems (DMOPs) refer to optimization problems that objective functions will change with time. Solving DMOPs implies that the Pareto Optimal Set (POS) at different moments can be accurately found, and this is a very difficult job due to the dynamics of the optimization problems. The POS that have been obtained in the past can help us to find the POS of the next time more quickly and accurately. Therefore, in this paper we present a Support Vector Machine (SVM) based Dynamic Multi-Objective Evolutionary optimization Algorithm, called SVM-DMOEA. The algorithm uses the POS that has been obtained to train a SVM and then take the trained SVM to classify the solutions of the dynamic optimization problem at the next moment, and thus it is able to generate an initial population which consists of different individuals recognized by the trained SVM. The initial populuation can be fed into any population based optimization algorithm, e.g., the Nondominated Sorting Genetic Algorithm II (NSGA-II), to get the POS at that moment. The experimental results show the validity of our proposed approach.
Accurate Recovery of Internet Traffic Data Under Variable Rate Measurements

The inference of the network traffic matrix from partial measurement data becomes increasingly critical for various network engineering tasks, such as capacity planning, load balancing, path setup, network provisioning, anomaly detection, and failure recovery. The recent study shows it is promising to more accurately interpolate the missing data with a 3-D tensor as compared with the interpolation methods based on a 2-D matrix. Despite the potential, it is difficult to form a tensor with measurements taken at varying rate in a practical network. To address the issues, we propose a Reshape-Align scheme to form the regular tensor with data from variable rate measurements, and introduce user-domain and temporal-domain factor matrices which take full advantage of features from both domains to translate the matrix completion problem to the tensor completion problem based on CANDECOMP/PARAFAC decomposition for more accurate missing data recovery. Our performance results demonstrate that our Reshape-Align scheme can achieve significantly better performance in terms of several metrics: error ratio, mean absolute error, and root mean square error.
Four quadrant operation of BLDC motor suitable for DC micro grid for elevator application

This paper presents a four quadrant operation of BLDC motor suitable for DC micro grid for Elevator application. The various advantages such as high torque to current ratio, high power density and higher efficiency of BLDC motor make it possible for using it in cranes, elevator system and many other industries. In this paper the four quadrant operation of BLDC motor worked out to control the elevator system and the, the motor is controlled without the loss of energy; instead regeneration of power is taken in account. The entire simulated system consists of a BLDC motor drive fed with an inverter where the DC bus feeds the drive. FPGA controller is used to provide the control signals to the inverter.
Enhanced multi-user beamforming protocol for millimeter wave wireless local area networks

MmWave in the unlicensed 60GHz band is highly discussed due to the rapid growth of wireless communication services. The utilization of microwave spectrum below 10 GHz is almost reaching its limit. Beamforming (BF) has become an essential technique to compensate the high path loss phenomenon of mmWave. IEEE 802.11ad and 802.11ay standardization task group institute directional multi-gigabit (DMG) wireless local area networks (WLANs) supporting mmWave techniques. With wireless devices explosively increasing, the limited number of BF slots in conventional DMG protocols leads to high packet collision probability, which potentially degrades the system performance. Most of the existing research does not take the multi-user BF contention problem into consideration. In this paper, we design a non-slotted association beamforming training (A-BFT) frame structure for multi-users without separating A-BFT slots in order to alleviate packet collisions due to the shortage of contention and training frames. This new proposed structure allows collisions with useful information left in remaining non-collided slots or frames in order to leverage the insufficiency of BF training for multiple devices. Furthermore, in order to further reduce BF collision probability, we propose two multiuser beamforming training mechanisms, including the time-based distributed coordination function (TDCF) and time-based beam-collision avoidance (TBCA) schemes. Simulation results demonstrate that our new proposed frame structure along with proposed TDCF and TBCA mechanisms outperforms 802.11ad protocol.
Comparative analysis of electrical braking performance for induction motor drive

Electric Braking in application to traction system is a promising aspect in the present day research and development. This in turn is also essential for significant improvements in the working of electric vehicles towards the development of efficiency of performance, utilization of energy and reduction of polluting emissions. Due to its ruggedness, the induction machine (IM) is usually preferred for electric drive in traction industry with additional advantages of dynamic modeling and similar torque-speed characteristics with that of the traction characteristics. Considering the braking performance of the IM, although regenerative braking is quite efficient in the context of energy regeneration but it has poor braking time performance. On the other hand plug braking is highly efficient in terms of fastness of braking but without any regeneration of kinetic energy being wasted during this process. In the present context a comparative analysis has been made between the performance of plug braking and regenerative braking, in order to develop an algorithm to utilize the advantages of both plug braking and regenerative braking simultaneously.
Towards a dynamic behavioral profile: A diachronic study of polysemous sentir in Spanish

Abstract This study examines the diachronic evolution of the polysemy of the Spanish verb sentir (‘to feel’) by means of a corpus-based dynamic behavioral profile (BP) analysis. Methodologically, it presents the first application of the BP approach to historical data and proposes some methodological innovations not only within the current body of research in historical semantics but also with regard to previous applications of the BP approach. First, whereas the majority of existing studies in quantitative historical semantics are largely based on observed frequencies or percentages of collocational co-occurrence, our study leverages more complex historical data that are based on the similarities of vectors. Second, this study also provides an extension of the methodological apparatus of the BP approach by complementing the traditional hierarchical agglomerative cluster analysis (HAC) with a dynamic BP approach derived from multidimensional scaling maps (MDS). Theoretically, this methodology contributes to a comprehensive perspective on the process of Constructionalization and the nature of networks, which is illustrated on the basis of the development of the Discourse Marker (DM) lo siento (‘I’m sorry’).
Cyber security of unmanned aircraft system traffic management (UTM)

Millions of small Unmanned Aircraft System (sUAS) aircraft of various shapes and capabilities will soon fly at low altitudes in urban environments for ambitious applications. It is critical to ensure these remotely piloted aircraft fly safely, predictably, and efficiently in this challenging airspace, without endangering themselves and other occupants sharing that airspace or in proximity. Concepts, technologies, processes, and policies to solve this hard problem of UAS Traffic Management (UTM) are being explored. But, cyber security considerations are largely missing. This paper bridges this gap and addresses UTM cyber security needs and issues. It contributes a comprehensive framework to understand, identify, classify, and assess security threats to UTM, including those resulting from sUAS vulnerabilities. Promising threat mitigations, major challenges, and research directions are discussed to secure UTM.
Contribution of Forest Biomass to Atmosphere

Rapid population growth, deterioration of natural resources and adverse impact of industrialization have caused global climate change and global warming problems. Forests are important terrestrial ecosystems for reducing carbon dioxide in the atmosphere. Forests increase their biomass by producing organic matter through photosynthesis, also produce oxygen. In this study, biomass quantities, carbon contents and the amount of oxygen were determined for various tree species by using biomass models. Red pine (Pinus brutia Ten.), Scots pine (Pinus silvestris L.), black pine (Pinus nigra Arn.), Cedar (Cedrus libani L.) and fir (Abies bornmülleriana Matff.) are important species of Turkey forests and the production quantities of these species were calculated assuming that they made a 1 cm diameter increase in the middle of 15-20-25 cm in different sizes. Average values for the biomass expected to occur when the 20 cm diameter of this specieses reaches 21 cm are calculated as as 18. 18 ton / ha, 47.26 ton / ha, 29.58 ton / ha, 19.55 ton / ha and 22.60 ton / ha, respectively in the middle site index.
Radar detection of small-size UAVs

The task of detection of ultra-small low-velocity objects by radar aids is discussed in the paper. Results of real tests of the prototype of wideband Ku-band radar with resolution of 12 cm in range are considered with reference to this task. Detection channel of the prototype uses the time-of-phase compensator and Doppler processor of reflected signal.
YebC controls virulence by activating T3SS gene expression in the pathogen Edwardsiella piscicida

Edwardsiella piscicida is an infectious Gram-negative bacterium that causes great losses to the aquaculture industry worldwide. Based on pattern analysis of conditional essentiality (PACE), a new method for transposon insertion sequencing (Tn-seq) data analysis, we investigated the genome-wide genetic requirements during the dynamic process of infection and colonization in turbot in this study. As a result, disruption of ETAE_1437 was discovered to lead to substantially reduced colonization, which was similar to the in vivo dynamic patterns of the mutants of T3SS or T6SS. Bioinformatics analysis indicated that ETAE_1437 is a YebC/PmpR family regulator. Moreover, we found that ETAE_1437 not only regulated quorum sensing by directly binding to the edwR promoter region but also activated T3SS expression by directly binding to the promoter region of the T3SS gene ETAE_0873. In addition, ETAE_1437 mutants exhibited substantial colonization defects and significantly decreased virulence in turbot. Overall, this study identified ETAE_1437 as a novel virulence regulator in E. piscicida and enriched our understanding of the pathogenesis of E. piscicida in fish. We thus reannotated ETAE_1437 as YebC.
Dispersion reduced SIW leaky-wave antenna by loading metasurface prism

Leaky-wave antennas (LWAs) are well-known for the high directivity, wide impedance bandwidth, and the beam-scanning performance with frequency. However, in the system that requires high-speed data transfer, wide system band and high directivity, LWAs are struggling with their beam squint effect in the radiation patterns, which limits their applications. In this paper, a dispersive metasurface prism is loaded to a dispersive LWA, reducing the LWA's dispersion, to make the LWA wide band radiating at a specific direction. A substrate integrated waveguide (SIW) LWA is taken to demonstrate the proposed concept with metasurface prism implemented by metallic vias. Full-wave simulation results show that the proposed low-dispersive SIW LWA has the main radiating direction at φ=24°, with half-power beamwidth of 8°, steers only ±0.5° from 33 to 38 GHz.
Correlation between multi-detector CT findings and angiography reported stenosis in symptomatic coronary artery disease patients: Pilot study

The objective of this study was to correlate stenosis assessment results using multi-detector Computed Tomography (MDCT) in both Coronary Computed Tomography Angiography (CCTA) and Computed Tomography Calcium Score (CTCS) examinations with results of Invasive Coronary Angiography (ICA). A total of 24 symptomatic Coronary Artery Disease (CAD) patients who underwent CCTA and/or CTCS following ICA were retrospectively analyzed. Mean age of the cohort was 62.3± 9.5 years. The diagnostic accuracy of CCTA was compared with ICA over three levels; segment-based, vessel-based and patient-based. CCTA correctly identified 30% of the segments with significant (=50%) stenosis. For the vessel-based evaluation, 80% of Left Main (LM) arteries were correctly identified as well as 93% of Left Anterior Descending (LAD), 87%o of Left Circumflex (LCX) and 87% of Right Coronary Artery (RCA). For the patient-based analysis, the area under receiver-operating characteristic (ROC) curve was 0.990 for 50% stenosis threshold and 0.974 for 70%o stenosis threshold. CTCS area under ROC curve was lower than that of CCTA (0.976). 19% of the vessels reported with 0 calcium score by CTCS were shown to contain a certain level of stenosis when compared with ICA. Herein, MDCT was found to be a reliable method in detecting and accurately ruling out significant stenosis by CCTA examinations. However due to the inaccuracy of CTCS in reporting vessels with 0 calcium score as stenosis-free, CTCS would be better in detecting significant stenosis than excluding stenosis.
Conversations about Death and Dying with Older People: An Ethnographic Study in Nursing Homes

Nursing homes are often places where older persons “come to die. ” Despite this, death and dying are seldom articulated or talked about. The aim of this study was to explore assistant nurses’ experiences of conversations about death and dying with nursing home residents. This study is part of an implementation project through a knowledge-based educational intervention based on palliative care principles. An ethnographic study design was applied in seven nursing homes, where eight assistant nurses were interviewed and followed in their daily assignments through participant observations. The assistant nurses stated that they had the knowledge and tools to conduct such conversations, even though they lacked the time and felt that emotional strain could be a hinder for conversations about death and dying. The assistant nurses used the strategies of distracting, comforting, and disregarding either when they perceived that residents’ reflections on death and dying were part of their illness and disease or when there was a lack of alignment between the residents’ contemplations and the concept of dying well. They indicated that ambivalence and ambiguity toward conversations about death and dying should be taken into consideration in future implementations of knowledge-based palliative care that take place in nursing homes after this project is finalized.