Search results for: acoustic emission signal

Authors: Steven D. P. Moore

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An electrical discharge in the air induces an electromagnetic (EM) wave capable of wireless transfer, reception, and conversion back into electrical discharge at a distant location. Following Norton’s ground wave principles, EM wave radiation (EMR) runs parallel to the Earth’s surface. Energy in an EMR wave can move through the air and be focused to create a spark at a distant location, focused by a receiver to generate a local electrical discharge. This local discharge can be amplified and stored but also has the propensity to initiate another EMR wave. In addition to typical EM waves, lightning is also associated with atmospheric events, trans-ionospheric pulse pairs, the most powerful natural EMR signal on the planet. With each lightning strike, regardless of global position, it generates naturally occurring pulse-pairs that are emitted towards space within a narrow cone. An EMR wave can self-propagate, travel at the speed of light, and, if polarized, contain vector properties. If this reflective pulse could be directed by design through structures that have increased probabilities for lighting strikes, it could theoretically travel near the surface of the Earth at light speed towards a selected receiver for local transformation into electrical energy. Through research, there are several influencing parameters that could be modified to model, test, and increase the potential for adopting this technology towards the goal of developing a global grid that utilizes natural sources of energy.

Keywords: electricity, sparkgap, wireless, electromagnetic

Procedia PDF Downloads 185

Authors: Kemal Efe Eseller, Göktuğ Yazici

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Laser-induced breakdown spectroscopy (LIBS) is a rapid optical atomic emission spectroscopy which is used for material identification and analysis with the advantages of in-situ analysis, elimination of intensive sample preparation, and micro-destructive properties for the material to be tested. LIBS delivers short pulses of laser beams onto the material in order to create plasma by excitation of the material to a certain threshold. The plasma characteristics, which consist of wavelength value and intensity amplitude, depends on the material and the experiment’s environment. In the present work, medicine samples’ spectrum profiles were obtained via LIBS. Medicine samples’ datasets include two different concentrations for both paracetamol based medicines, namely Aferin and Parafon. The spectrum data of the samples were preprocessed via filling outliers based on quartiles, smoothing spectra to eliminate noise and normalizing both wavelength and intensity axis. Statistical information was obtained and principal component analysis (PCA) was incorporated to both the preprocessed and raw datasets. The machine learning models were set based on two different train-test splits, which were 70% training – 30% test and 80% training – 20% test. Cross-validation was preferred to protect the models against overfitting; thus the sample amount is small. The machine learning results of preprocessed and raw datasets were subjected to comparison for both splits. This is the first time that all supervised machine learning classification algorithms; consisting of Decision Trees, Discriminant, naïve Bayes, Support Vector Machines (SVM), k-NN(k-Nearest Neighbor) Ensemble Learning and Neural Network algorithms; were incorporated to LIBS data of paracetamol based pharmaceutical samples, and their different concentrations on preprocessed and raw dataset in order to observe the effect of preprocessing.

Keywords: machine learning, laser-induced breakdown spectroscopy, medicines, principal component analysis, preprocessing

Procedia PDF Downloads 86

Authors: Bayar Shahab

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The fast development of technology that has advanced neuroscience and human interaction with computers has enabled solutions to various problems, and issues of this new era have been found and are being found like no other time in history. Brain-computer interface so-called BCI has opened the door to several new research areas and have been able to provide solutions to critical and important issues such as supporting a paralyzed patient to interact with the outside world, controlling a robot arm, playing games in VR with the brain, driving a wheelchair or even a car and neurotechnology enabled the rehabilitation of the lost memory, etc. This review work presents state-of-the-art methods and improvements of canonical correlation analyses (CCA), which is an SSVEP-based BCI method. These are the methods used to extract EEG signal features or, to be said in a different way, the features of interest that we are looking for in the EEG analyses. Each of the methods from oldest to newest has been discussed while comparing their advantages and disadvantages. This would create a great context and help researchers to understand the most state-of-the-art methods available in this field with their pros and cons, along with their mathematical representations and usage. This work makes a vital contribution to the existing field of study. It differs from other similar recently published works by providing the following: (1) stating most of the prominent methods used in this field in a hierarchical way (2) explaining pros and cons of each method and their performance (3) presenting the gaps that exist at the end of each method that can open the understanding and doors to new research and/or improvements.

Keywords: BCI, CCA, SSVEP, EEG

Procedia PDF Downloads 143

Authors: Rahman Mofidi, Sina Rahimi, Farnoosh Darban

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Communication plays a key role in today’s world, and to support it, the quality of service has the highest priority. It is very important to differentiate between traffic based on priority level. Some traffic classes should be a higher priority than other classes. It is also necessary to give high priority to customers who have more payment for better service, however, without influence on other customers. So to realize that, we will require effective quality of service methods. To ensure the optimal performance of the network in accordance with the quality of service is an important goal for all operators in the mobile network. In this work, we propose an algorithm based on control parameters which it’s based on user feedback that aims at minimizing the access to system transmit power and thus improving the network key performance indicators and increasing the quality of service. This feedback that is known as channel quality indicator (CQI) indicates the received signal level of the user. We aim at proposing an algorithm in control parameter criterion to study improving the quality of service and throughput in a cellular network at the simulated environment. In this work we tried to parameter values have close to their actual level. Simulation results show that the proposed algorithm improves the system throughput and thus satisfies users' throughput and improves service to set up a successful call.

Keywords: quality of service, key performance indicators, control parameter, channel quality indicator

Procedia PDF Downloads 201

Authors: Chaohong Pan

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Through public diplomacy on social media, governments have attempted to influence foreign public opinion. What is the impact of digital public diplomacy? Public diplomacy research often relies on content analysis to study the strategies employed by communicators but has rarely examined its actual impact on the audience. In addition, we do not know if giving a communicator an explicit label, as Twitter does with “government account”, would change the effects of the messages. Can the government label reduce the percussiveness of public diplomacy messages by sending a warning signal? Using a 2 × 2 survey experiment, the present paper contributes to the study of public diplomacy by randomly exposing American participants to four types of tweets from Chinese diplomats. The stimulus materials vary in terms of the tweets’ content (“positive-china” vs. “negative-US) and Twitter government labels (with vs. without the labels). I found that positive tweets about China have a significant positive effect on Americans’ attitudes toward China, whereas negative tweets about the US have little effect on their opinions. Furthermore, positive-China tweets are effective only on China-related issues, which indicates that Chinese diplomats’ tweets have limited effects on shaping a foreign audience’s attitudes toward their own country. Lastly, I find that labels largely have no impact on a diplomatic tweet’s effect. These results contribute to our understanding of the effects of public diplomacy in the digital age.

Keywords: public diplomacy, china, foreign public opinion, twitter

Procedia PDF Downloads 191

Authors: Ahmed El-Fiqi, Hae-Won Kim

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Incorporation of therapeutic elements such as Sr, Cu and Co into bioglass structure and their release as ions is considered as one of the promising approaches to enhance cellular responses, e.g., osteogenesis and angiogenesis. Here, cobalt as angiogenesis promoter has been incorporated (at 0, 1 and 4 mol%) into sol-gel derived calcium silicate mesoporous bioglass nanoparticles. The composition and structure of cobalt-free (CFN) and cobalt-doped (CDN) mesoporous bioglass nanoparticles have been analyzed by X-ray fluorescence (XRF), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and Fourier-Transform Infra-red spectroscopy (FT-IR). The physicochemical properties of CFN and CDN have been investigated using high-resolution transmission electron microscopy (HR-TEM), Selected area electron diffraction (SAED), and Energy-dispersive X-ray (EDX). Furthermore, the textural properties, including specific surface area, pore-volume, and pore size, have been analyzed from N²⁻sorption analyses. Surface charges of CFN and CDN were also determined from surface zeta potential measurements. The release of ions, including Co²⁺, Ca²⁺, and SiO₄⁴⁻ has been analyzed using inductively coupled plasma atomic emission spectrometry (ICP-AES). Loading and release of diclofenac as an anti-inflammatory drug model were explored in vitro using Ultraviolet-visible spectroscopy (UV-Vis). XRD results ensured the amorphous state of CFN and CDN whereas, XRF further confirmed that their chemical compositions are very close to the designed compositions. HR-TEM analyses unveiled nanoparticles with spherical morphologies, highly mesoporous textures, and sizes in the range of 90 - 100 nm. Moreover, N²⁻ sorption analyses revealed that the nanoparticles have pores with sizes of 3.2 - 2.6 nm, pore volumes of 0.41 - 0.35 cc/g and highly surface areas in the range of 716 - 830 m²/g. High-resolution XPS analysis of Co 2p core level provided structural information about Co atomic environment and it confirmed the electronic state of Co in the glass matrix. ICP-AES analysis showed the release of therapeutic doses of Co²⁺ ions from 4% CDN up to 100 ppm within 14 days. Finally, diclofenac loading and release have ensured the drug/ion co-delivery capability of 4% CDN.

Keywords: mesoporous bioactive glass, nanoparticles, cobalt ions, release

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Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

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In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

Procedia PDF Downloads 42

Authors: A. Ghodbane, M. Saad, J. F. Boland, C. Thibeault

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Historically, actuators’ redundancy was used to deal with faults occurring suddenly in flight systems. This technique was generally expensive, time consuming and involves increased weight and space in the system. Therefore, nowadays, the on-line fault diagnosis of actuators and accommodation plays a major role in the design of avionic systems. These approaches, known as Fault Tolerant Flight Control systems (FTFCs) are able to adapt to such sudden faults while keeping avionics systems lighter and less expensive. In this paper, a (FTFC) system based on the Geometric Approach and a Reconfigurable Flight Control (RFC) are presented. The Geometric approach is used for cosmic ray fault reconstruction, while Sliding Mode Control (SMC) based on Lyapunov stability theory is designed for the reconfiguration of the controller in order to compensate the fault effect. Matlab®/Simulink® simulations are performed to illustrate the effectiveness and robustness of the proposed flight control system against actuators’ faulty signal caused by cosmic rays. The results demonstrate the successful real-time implementation of the proposed FTFC system on a non-linear 6 DOF aircraft model.

Keywords: actuators’ faults, fault detection and diagnosis, fault tolerant flight control, sliding mode control, geometric approach for fault reconstruction, Lyapunov stability

Procedia PDF Downloads 417

Authors: Sree Vennela P., V. Samyuktha Bhardwaj

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Hyponatremia is an electrolyte disturbance in which the sodium ion concentration in the serum is lower than normal. Sodium is the dominant extracellular cation (positive ion) and cannot freely cross from the interstitial space through the cell membrane, into the cell. Its homeostasis (stability of concentration) inside the cell is vital to the normal function of any cell. Normal serum sodium levels are between 135 and 145 mEq/L. Hyponatremia is defined as a serum level of less than 135 mEq/L and is considered severe when the serum level is below 125 mEq/L. In the vast majority of cases, Hyponatremia occurs as a result of excess body water diluting the serum sodium (salt level in the blood). Hyponatremia is often a complication of other medical illnesses in which excess water accumulates in the body at a higher rate than can be excreted (for example in congestive heart failure, syndrome of inappropriate antidiuretic hormone, SIADH, or polydipsia). Sometimes it may be a result of over-hydration (drinking too much water).Lack of sodium (salt) is very rarely the cause of Hyponatremia, although it can promote Hyponatremia indirectly. In particular, sodium loss can lead to a state of volume depletion (loss of blood volume in the body), with volume depletion serving as a signal for the release of ADH (anti-diuretic hormone). As a result of ADH-stimulated water retention (too much water in the body), blood sodium becomes diluted and Hyponatremia results.

Keywords: Tolvaptan, hyponatremia, syndrome of insufficient anti diuretic hormone (SIADH), euvolemic hyponatremia

Procedia PDF Downloads 258

Authors: Leah Lee

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This paper examines the correlation between deep learning models and emotions with noises to see whether or not noises mask emotions. The deep learning models used are plain convolutional neural networks (CNN), auto-encoder, long short-term memory (LSTM), and Visual Geometry Group-16 (VGG-16). Emotion datasets used are Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), Crowd-sourced Emotional Multimodal Actors Dataset (CREMA-D), Toronto Emotional Speech Set (TESS), and Surrey Audio-Visual Expressed Emotion (SAVEE). To make it four times bigger, audio set files, stretch, and pitch augmentations are utilized. From the augmented datasets, five different features are extracted for inputs of the models. There are eight different emotions to be classified. Noise variations are white noise, dog barking, and cough sounds. The variation in the signal-to-noise ratio (SNR) is 0, 20, and 40. In summation, per a deep learning model, nine different sets with noise and SNR variations and just augmented audio files without any noises will be used in the experiment. To compare the results of the deep learning models, the accuracy and receiver operating characteristic (ROC) are checked.

Keywords: auto-encoder, convolutional neural networks, long short-term memory, speech emotion recognition, visual geometry group-16

Procedia PDF Downloads 74

Authors: Anamarel Medina-Hernandez, Teresa Ponce-Noyola, Ileana Vera-Reyes, Ana C. Ramos-Valdivia

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Somatic embryos reproduce original seed characteristics and could be implemented in biotechnological studies. Jatropha curcas L. is an important plant for biodiesel production, but also is used in traditional medicine. Seeds from J. curcas are toxic because contain diterpenoids called phorbol esters, but in Mexico exist a non-toxic variety. Therefore, somatic embryos suspension cultures from non-toxic J. curcas variety were induced. In order to investigate the characteristics of somatic embryos, a differential proteomic analysis was made between pre-globular and globular stages by 2-D gel electrophoresis. 108 spots were differentially expressed (p<0.02), and 20 spots from globular somatic embryos were sequenced by MALDI-TOF-TOF mass spectrometry. A comparative analysis of terpenoids production between the two stages was made by RP-18 TLC plates. The sequenced proteins were related to energy production (68%), protein destination and storage (9%), secondary metabolism (9%), signal transduction (5%), cell structure (5%) and aminoacid metabolism (4%). Regarding terpenoid production, in pre-globular and globular somatic embryos were identified sterols and triterpenes of pharmacological interest (alpha-amyrin and betulinic acid) but also it was found compounds that were unique to each stage. The results of this work are the basis to characterize at different levels the J. curcas somatic embryos so that this system can be used efficiently in biotechnological processes.

Keywords: Jatropha curcas, proteomics, somatic embryo, terpenoids

Procedia PDF Downloads 250

Authors: Ahmed A. D. Sarhan, Hong Wan Ping, M. Sayuti

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In this current era of competitive machinery productions, the industries are designed to place more emphasis on the product quality and reduction of cost whilst abiding by the pollution-preventing policy. In attempting to delve into the concerns, the industries are aware that the effectiveness of existing lubrication systems must be improved to achieve power-efficient and pollution-preventing machining processes. As such, this research is targeted to study on a plausible solution to the issue in grinding titanium alloy (Ti-6Al-4V) by using nanolubrication, as an alternative to flood grinding. The aim of this research is to evaluate the optimum condition of grinding force and surface roughness using MQL lubricating system to deliver nano-oil at different level of weight concentration of Silicon Dioxide (SiO2) mixed normal mineral oil. Taguchi Design of Experiment (DoE) method is carried out using a standard Taguchi orthogonal array of L16(43) to find the optimized combination of weight concentration mixture of SiO2, nozzle orientation and pressure of MQL. Surface roughness and grinding force are also analyzed using signal-to-noise(S/N) ratio to determine the best level of each factor that are tested. Consequently, the best combination of parameters is tested for a period of time and the results are compared with conventional grinding method of dry and flood condition. The results show a positive performance of MQL nanolubrication.

Keywords: grinding, MQL, precision grinding, Taguchi optimization, titanium alloy

Procedia PDF Downloads 274

Authors: Mearg Berhe Gebregziabher

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Wire-cut electric discharge machining (WEDM) is one of the advanced machining processes. Due to the development of the current manufacturing sector, there has been no research work done before about the optimization of the process parameters based on the availability of the workpiece of the Steel St-37 material in Ethiopia. Material Removal Rate (MRR) is considered as the experimental response of WCEDM. The main objective of this work is to investigate and optimize the process parameters on machining quality that gives high MRR during machining of Steel St-37. Throughout the investigation, Pulse on Time (TON), Pulse off Time (TOFF) and Velocities of Wire Feed (WR) are used as variable parameters at three different levels, and Wire tension, flow rate, type of dielectric fluid, type of the workpiece and wire material and dielectric flow rate are keeping as constants for each experiment. The Taguchi methodology, as per Taguchi‟ 's standard L9 (3^3) Orthogonal Array (OA), has been carried out to investigate their effects and to predict the optimal combination of process parameters over MRR. Signal to Noise ratio (S/N) and Analysis of Variance (ANOVA) were used to analyze the effect of the parameters and to identify the optimum cutting parameters on MRR. MRR was measured by using the Electronic Balance Model SI-32. The results indicated that the most significant factors for MRR are TOFF, TON and lastly WR. Taguchi analysis shows that, the optimal process parameters combination is A2B2C2, i.e., TON 6μs, TOFF 29μs and WR 2 m/min. At this level, the MRR of 0.414 gram/min has been achieved.

Keywords: ANOVA, MRR, parameter, Taguchi Methode

Procedia PDF Downloads 40

Authors: Jiun-Horng Tsai, Shi-Jie, Nieh

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Fine particulate matter (PM₂.₅) has become an important issue all over the world over the last decade. Annual mean PM₂.₅ concentration has been over the ambient air quality standard of PM₂.₅ (annual average concentration as 15μg/m³) which adapted by Taiwan Environmental Protection Administration (TEPA). TEPA, therefore, has developed a number of air pollution control measures to improve the ambient concentration by reducing the emissions of primary fine particulate matter and the precursors of secondary PM₂.₅. This study investigated the potential improvement of ambient PM₂.₅ concentration by the TEPA program and the other scenario for further emission reduction on various sources. Four scenarios had been evaluated in this study, including a basic case and three reduction scenarios (A to C). The ambient PM₂.₅ concentration was evaluated by Community Multi-scale Air Quality modelling system (CMAQ) ver. 4.7.1 along with the Weather Research and Forecasting Model (WRF) ver. 3.4.1. The grid resolutions in the modelling work are 81 km × 81 km for domain 1 (covers East Asia), 27 km × 27 km for domain 2 (covers Southeast China and Taiwan), and 9 km × 9 km for domain 3 (covers Taiwan). The result of PM₂.₅ concentration simulation in different regions of Taiwan shows that the annual average concentration of basic case is 24.9 μg/m³, and are 22.6, 18.8, and 11.3 μg/m³, respectively, for scenarios A to C. The annual average concentration of PM₂.₅ would be reduced by 9-55 % for those control scenarios. The result of scenario C (the emissions of precursors reduce to allowance levels) could improve effectively the airborne PM₂.₅ concentration to attain the air quality standard. According to the results of unit precursor reduction contribution, the allowance emissions of PM₂.₅, SOₓ, and NOₓ are 16.8, 39, and 62 thousand tons per year, respectively. In the Kao-Ping air basin, the priority for reducing precursor emissions is PM₂.₅ > NOₓ > SOₓ, whereas the priority for reducing precursor emissions is PM₂.₅ > SOₓ > NOₓ in others area. The result indicates that the target pollutants that need to be reduced in different air basin are different, and the control measures need to be adapted to local conditions.

Keywords: airborne PM₂.₅, community multi-scale air quality modelling system, control measures, weather research and forecasting model

Procedia PDF Downloads 138

Authors: Ahmed Eid, Amita Gupta

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Abstract: Background: Background Medical gases are estimated to contribute to 5% of the carbon footprints produced by hospitals, Desflurane has the largest impact, but all increase significantly when used with N2O admixture. Climate Change Act 2008, we must reduce our carbon emission by 80% of the 1990 baseline by 2050.NHS carbon emissions have reduced by 18.5% (2007-2017). The NHS Long Term Plan has outlined measures to achieve this objective, including a 2% reduction by transforming anaesthetic practices. FGF is an important variable that determines the utilization of inhalational agents and can be tightly controlled by the anaesthetist. Aims and Objectives Environmental safety, Identification of areas of high N20 and different anaesthetic agents used across the St Helier operating theatres and consider improvising on the current practice. Methods: Data was collected from St Helier operating theatres and retrieved daily from Care Station 650 anaesthetic machines. 60 cases were included in the sample. Collected data (average flow rate, amount and type of agent used, duration of surgery, type of surgery, duration, and the total amount of Air, O2 and N2O used. AAGBI impact anaesthesia calculator was used to identify the amount of CO2 produced and also the cost per hour for every pt. Communication via reminder emails to staff emphasized the significance of low-flow anaesthesia and departmental meeting presentations aimed at heightening awareness of LFA, Distribution of AAGBI calculator QR codes in all theatres enables the calculation of volatile anaesthetic consumption and CO2e post each case, facilitating informed environmental impact assessment. Results: A significant reduction in the flow rate use in the 2nd sample was observed, flow rate usage between 0-1L was 60% which means a great reduction of the consumption of volatile anaesthetics and also Co2e. By using LFA we can save money but most importantly we can make our lives much greener and save the planet.

Keywords: low flow anesthesia, sustainability project, N₂0, Co2e

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Authors: Andre Wittenborn, Jarek Krajewski

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Trauma-related sadness in speech can alter the voice in several ways. The generation of non-linear aerodynamic phenomena within the vocal tract is crucial when analyzing trauma-influenced speech production. They include non-laminar flow and formation of jets rather than well-behaved laminar flow aspects. Especially state-space reconstruction methods based on chaotic dynamics and fractal theory have been suggested to describe these aerodynamic turbulence-related phenomena of the speech production system. To extract the non-linear properties of the speech signal, we used the time delay embedding method to reconstruct from a scalar time series (reconstructed phase space, RPS). This approach results in the extraction of 7238 Features per .wav file (N= 47, 32 m, 15 f). The speech material was prompted by telling about autobiographical related sadness-inducing experiences (sampling rate 16 kHz, 8-bit resolution). After combining these features in a support vector machine based machine learning approach (leave-one-sample out validation), we achieved a correlation of r = .41 with the well-established, self-report ground truth measure (RATS) of post-traumatic stress disorder (PTSD).

Keywords: non-linear dynamics features, post traumatic stress disorder, reconstructed phase space, support vector machine

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Authors: Anna S. Tolkacheva, Sergey N. Shkerin, Kirill G. Zemlyanoi, Olga G. Reznitskikh, Pavel D. Khavlyuk

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Calcium oxovanadates with garnet related structure are multifunctional oxides in various fields like photoluminescence, microwave dielectrics, and magneto-dielectrics. For example, vanadate garnets are self-luminescent compounds. They attract attention as RE-free broadband excitation and emission phosphors and are candidate materials for UV-based white light-emitting diodes (WLEDs). Ca₅M₄(VO₄)₆ (M = Mg, Zn, Co, Ni, Mn) compounds are also considered promising for application in microwave devices as substrate materials. However, the relation between their structure, composition and physical/chemical properties remains unclear. Given the above-listed observations, goals of this study are to synthesise Ca₅M₄(VO₄)₆ (M = Mg, Zn, Ni) and to study their thermal and electrical properties. Solid solutions Ca₅Mg₄₋ₓMₓ(VO₄)₆ (0 ≤ x ≤ 4) where M is Zn and Ni have been synthesized by sol-gel method. The single-phase character of the final products was checked by powder X-ray diffraction on a Rigaku D/MAX-2200 X-ray diffractometer using Cu Kα radiation in the 2θ range from 15° to 70°. The dependence of thermal properties on chemical composition of solid solutions was studied using simultaneous thermal analyses (DSC and TG). Thermal analyses were conducted in a Netzch simultaneous analyser STA 449C Jupiter, in Ar atmosphere, in temperature range from 25 to 1100°C heat rate was 10 K·min⁻¹. Coefficients of thermal expansion (CTE) were obtained by dilatometry measurements in air up to 800°C using a Netzsch 402PC dilatometer; heat rate was 1 K·min⁻¹. Impedance spectra were obtained via the two-probe technique with an impedance meter Parstat 2273 in air up to 700°C with the variation of pH₂O from 0.04 to 3.35 kPa. Cation deficiency in Ca and Mg sublattice under the substitution of MgO with ZnO up to 1/6 was observed using Rietveld refinement of the crystal structure. Melting point was found to decrease with x changing from 0 to 4 in Ca₅Mg₄₋ₓMₓ(VO₄)₆ where M is Zn and Ni. It was observed that electrical conductivity does not depend on air humidity. The reported study was funded by the RFBR Grant No. 17–03–01280. Sample attestation was carried out in the Shared Access Centers at the IHTE UB RAS.

Keywords: garnet structure, electrical conductivity, thermal expansion, thermal properties

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Authors: Saud Al Taj

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Employer branding is considered as a useful tool for addressing the global-local problem facing complex organisations that have operations scattered across the globe and face challenges of dealing with the local environment alongside. Despite being an established field of study within the Western developed world, there is little empirical evidence concerning the relevance of employer branding to global companies that operate in the under-developed economies. This paper fills this gap by gaining rich insight into the implementation of employer branding programs in a foreign multinational operating in Pakistan dealing with the global-local problem. The study is qualitative in nature and employs semi-structured and focus group interviews with senior/middle managers and local frontline employees to deeply examine the phenomenon in case organisation. Findings suggest that authenticity is required in employer brands to enable them to respond to the local needs thereby leading to the resolution of the global-local problem. However, the role of signaling theory is key to the development of authentic employer brands as it stresses on the need to establish an efficient and effective signaling environment wherein signals travel in both directions (from signal designers to receivers and backwards) and facilitate firms with the global-local problem. The paper also identifies future avenues of research for the employer branding field.

Keywords: authenticity, counter-signals, employer branding, global-local problem, signaling theory

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Authors: Cristina Costa-Lobo, Carla B. Vestena, Filomena E. Ponte

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Creativity and intelligence are concepts that have aroused very expressive interest in the field of educational sciences and the field of psychological science since the middle of the last century since they have a great impact on the potential and well-being of individuals. However, due to progress in cognitive and positive psychology, there has been a growing interest in the psychoeducational domain of intelligence and creativity in the last decade. In this theoretical work, are analyzed comparatively the theoretical models that relate the intelligence and the creativity, are analyzed several psychoeducational intervention programs that have been implemented with a view to the promotion of creativity and signal possibilities, realities and ironies around the psychological evaluation of intelligence and creativity. In order to reach a broad perspective on creativity, the evidence is presented that points the need to evaluate different psychological domains. The psychoeducational intervention programs addressed have, with a common characteristic, the full stimulation of the creative potential of the participants, assumed as a highly valued capacity at the present time. The results point to the systematize that all interventions in the ambit of creativity have two guiding principles: all individuals can be creative, and creativity is a capacity that can be stimulated. This work refers to the importance of stimulus creativity in educational contexts, to the usefulness and pertinence of the creation, the implementation, and monitoring of flexible curricula, adapted to the educational needs of students, promoting a collaborative work among teachers, parents, students, psychologists, managers and educational administrators.

Keywords: creativity, intelligence, psychoeducational intervention programs, psychological evaluation, educational contexts

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Authors: Fernanda Laureti T. Ferreira, Kazuo Nishimoto

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This paper presents a summary of the experience on videoconferencing tools that have been used to teach regular classes during this pandemic period in educational institutions in São Paulo, which tools and applications are most used and the challenges related to this mode of delivery. At this moment, the massive online education is not a choice of students or a structured development of education system, but a solution that emerged to attend urgent needs and it presents the opportunity to teach and learning available for the most students in this single time of social isolation that forced among others, this significant change for education, students, teachers, institutions and families. Distance education enables synchronous and asynchronous mode classes, and even though the current circumstances generate discomfort and uncertainty, on the other hand, there is a chance to promote a 'learning to learn'. The videoconference is a preferred choice of schools because synchronous mode to give more interaction between a group of students and teachers, but this mode requires specifics teacher competencies and skills, in addition to equipment and provision of adequate internet signal for all participants of the process. The approach is making use of known technical information about video conference tools and the results of search answered by a group of students, teachers, schools, and parents. The results presented refer to the perspectives of students and parents as respondents.

Keywords: distance education, interaction on education, online classes, synchronous e-learning, videoconference

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Authors: Khadra Ahmed, Khaled Kheireldin

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In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: planktons, diversity indices, water quality index, water ways

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Authors: Venkataraman Sivasankar, Kiyoshi Omine, Hideaki Sano

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The leaching of fluoride from Plaster Board Waste (PBW) is quite feasible in soil and water environments. The Ministry of Environment, Japan recommended the standard limit of 0.8 mgL⁻¹ or less for fluoride. Although the utilization of PBW as a substitute for cement is rather meritorious, its fluoride leaching behavior deteriorates the quality of soil and water and therefore envisaged as a demerit. In view of this fluoride leaching problem, the present research is focused on immobilizing fluoride in PBW. The immobilization experiments were conducted with four chemical systems operated by DAHP (diammonium hydrogen phosphate) and phosphoric acid carbonization of bamboo mass coupled with certain inorganic reactions using reagents such as calcium hydroxide, sodium hydroxide, and aqueous ammonia. The fluoride immobilization was determined after shaking the reactor contents including the plaster board waste for 24 h at 25˚C. In the DAHP system, the immobilization of fluoride was evident from the leaching of fluoride in the range 0.071-0.12 mgL⁻¹, 0.026-0.14 mgL⁻¹ and 0.068-0.12 mgL⁻¹ for the reaction temperatures at 30˚C, 50˚C, and 90˚C, respectively, with final pH of 6.8. The other chemical systems designated as PACCa, PACAm, and PACNa could immobilize fluoride in PBW, and the resulting solution was analyzed with the fluoride less than the Japanese environmental standard of 0.8 mgL⁻¹. In the case of PACAm and PACCa systems, the calcium concentration was found undetectable and witnessed the formation of phosphate compounds. The immobilization of fluoride was found inversely proportional to the increase in the volume of leaching solvent and dose of PBW. Characterization studies of PBW and the solid after fluoride immobilization was done using FTIR (Fourier transform infrared spectroscopy), Raman spectroscopy, FE-SEM ( Field Emission Scanning Electron Microscopy) with EDAX (Energy Dispersive Spectroscopy), XRD (X-ray diffraction), and XPS (X-ray photoelectron spectroscopy). The results revealed the formation of new calcium phosphate compounds such as apatite, monetite, and hydroxylapatite. The participation of such new compounds in fluoride immobilization seems indispensable through the exchange mechanism of hydroxyl and fluoride groups. Acknowledgment: First author thanks to Japanese Society for the Promotion of Science (JSPS) for the award of the fellowship (ID No. 16544).

Keywords: characterization, fluoride, immobilization, plaster board waste

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Authors: João Madureira, Ricardo Lagido, Inês Sousa, Fraunhofer Portugal

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Surf is an increasingly popular sport and its performance evaluation is often qualitative. This work aims at using a smartphone to collect and analyze the GPS and inertial sensors data in order to obtain quantitative metrics of the surfing performance. Two approaches are compared for detection of wave rides, computing the number of waves rode in a surfing session, the starting time of each wave and its duration. The first approach is based on computing the velocity from the Global Positioning System (GPS) signal and finding the velocity thresholds that allow identifying the start and end of each wave ride. The second approach adds information from the Inertial Measurement Unit (IMU) of the smartphone, to the velocity thresholds obtained from the GPS unit, to determine the start and end of each wave ride. The two methods were evaluated using GPS and IMU data from two surfing sessions and validated with similar metrics extracted from video data collected from the beach. The second method, combining GPS and IMU data, was found to be more accurate in determining the number of waves, start time and duration. This paper shows that it is feasible to use smartphones for quantification of performance metrics during surfing. In particular, detection of the waves rode and their duration can be accurately determined using the smartphone GPS and IMU.

Keywords: inertial measurement unit (IMU), global positioning system (GPS), smartphone, surfing performance

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Authors: Yun Sun, Meng Xun, Jingtao Zhou, Ming Li, Qiang Kan, Zhi Jin, Xinyu Liu, Dexin Wu

Abstract:

Higher speed short-wavelength vertical-cavity surface-emitting lasers (VCSELs) working at high temperature are required for future optical interconnects. In this work, the high-speed 850 nm VCSELs are designed, fabricated and characterized. The temperature dependent static and dynamic performance of devices are investigated by using current-power-voltage and small signal modulation measurements. Temperature-stable high-speed properties are obtained by employing highly strained multiple quantum wells and short cavity length of half wavelength. The temperature dependent photon lifetimes and carrier radiative times are determined from damping factor and resonance frequency obtained by fitting the intrinsic optical bandwidth with the two-pole transfer function. In addition, an analytical theoretical model including the strain effect is development based on model-solid theory. The calculation results indicate that the better high temperature performance of VCSELs can be attributed to the strong confinement of holes in the quantum wells leading to enhancement of the carrier transit time.

Keywords: vertical cavity surface emitting lasers, high speed modulation, optical interconnects, semiconductor lasers

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Authors: Usha Kiran, M. Z. Abdin

Abstract:

Osmotin is an abundant cationic multifunctional protein discovered in cells of tobacco (Nicotiana tabacum L. var Wisconsin 38) adapted to an environment of low osmotic potential. It provides plants protection from pathogens, hence placed in the PRP family of proteins. The osmotin induced proline accumulation has been reported in plants including transgenic tomato and strawberry conferring tolerance against both biotic and abiotic stresses. The exact mechanism of induction of proline by osmotin is however, not known till date. These observations have led us to hypothesize that osmotin induced proline accumulation could be due to its involvement as transcription factor and/or cell signal pathway modulator in proline biosynthesis. The present investigation was therefore, undertaken to analyze the osmotin protein as transcription factor /cell signalling modulator using bioinformatics tools. The results of available online DNA binding motif search programs revealed that osmotin does not contain DNA-binding motifs. The alignment results of osmotin protein with the protein sequence from DATF showed the homology in the range of 0-20%, suggesting that it might not contain a DNA binding motif. Further to find unique DNA-binding domain, the superimposition of osmotin 3D structure on modeled Arabidopsis transcription factors using Chimera also suggested absence of the same. We, however, found evidence implicating osmotin in cell signaling. With these results, we concluded that osmotin is not a transcription factor but regulating proline biosynthesis and accumulation through cell signaling during abiotic stresses.

Keywords: osmotin, cell signaling modulator, bioinformatic tools, protein

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Authors: Almalki M., Alajmi M., Qadrouh Y., Alzahrani E., Sulaiman A., Aleid M., Albaiji A., Alfaifi H., Alhadadi A., Almotairy H., Alrasheed R., Alhafedh Y.

Abstract:

High-resolution marine seismic survey is a well-established technique that commonly used to characterize near-surface sediments and geological structures at shallow water. We conduct single channel seismic survey to provide high quality seismic images for near-surface sediments upto 100m depth at Jubal costal area, Arabian Gulf. Eight hydrophones streamer has been used to collect stacked seismic traces alone 5km seismic line. To reach the required depth, we have used spark system that discharges energies above 5000 J with expected frequency output span the range from 200 to 2000 Hz. A suitable processing flow implemented to enhance the signal-to-noise ratio of the seismic profile. We have found that shallow sedimentary layers at the study site have complex pattern of reflectivity, which decay significantly due to amount of source energy used as well as the multiples associated to seafloor. In fact, the results reveal that single channel marine seismic at shallow water is a cost-effective technique that can be easily repeated to observe any possibly changes in the wave physical properties at the near surface layers

Keywords: shallow marine single-channel data, high resolution, frequency filtering, shallow water

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Authors: Manisha Choudhary, Sudarsan Neogi

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Malachite green (MG), an organic basic dye, has been widely used for the dyeing purpose, as well as a fungicide and antiseptic in aquaculture industry to control fish parasites and disease. However, MG has now turned out to be an extremely controversial compound due to its adverse impact on living beings. Due to high toxicity, proper treatment of wastewater containing MG is utmost important. Among different available technologies, adsorption process is one of the most efficient and cost-effective treatment method due to its simplicity of design, ease of operation and regeneration of used materials. Nonetheless, commercial activated carbon is expensive leading the researchers to focus on utilizing natural resources. In the present work, a species of cactus, Opuntia ficus-indica (OFI), was used to develop a highly efficient, low-cost powdered activated carbon by chemical activation using NaOH. The biosorbent was characterized by Fourier-transform infrared spectroscopy, field emission scanning electron microscope, energy-dispersive X-ray spectroscopy, Brunauer–Emmett–Teller (BET) and X-ray diffraction analysis. Batch adsorption studies were performed to remove MG from an aqueous solution as a function of contact time, initial solution pH, initial dye concentration, biosorbent dosages, the presence of salt and temperature. By increasing the initial dye concentration from 100 to 500 mg/l, adsorption capacity increased from 165.45 to 831.58 mg/g. The adsorption kinetics followed the pseudo-second-order model and the chemisorption mechanisms were revealed. The electrostatic attractions and chemical interactions were observed between amino and hydroxyl groups of the biosorbent and amine groups of the dye. The adsorption was solely controlled by film diffusion. Different isotherm models were used to fit the adsorption data. The excellent recovery of adsorption efficiency after the regeneration of biosorbent indicated the high potential of this adsorbent to remove MG from aqueous solution and an excellent cost-effective biosorbent for wide application in wastewater treatment.

Keywords: adsorption, biosorbent, cactus, malachite green

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Authors: Rabab M. Ramadan, Elaraby A. Elgallad

Abstract:

With extensive application, the performance of unimodal biometrics systems has to face a diversity of problems such as signal and background noise, distortion, and environment differences. Therefore, multimodal biometric systems are proposed to solve the above stated problems. This paper introduces a bimodal biometric recognition system based on the extracted features of the human palm print and iris. Palm print biometric is fairly a new evolving technology that is used to identify people by their palm features. The iris is a strong competitor together with face and fingerprints for presence in multimodal recognition systems. In this research, we introduced an algorithm to the combination of the palm and iris-extracted features using a texture-based descriptor, the Scale Invariant Feature Transform (SIFT). Since the feature sets are non-homogeneous as features of different biometric modalities are used, these features will be concatenated to form a single feature vector. Particle swarm optimization (PSO) is used as a feature selection technique to reduce the dimensionality of the feature. The proposed algorithm will be applied to the Institute of Technology of Delhi (IITD) database and its performance will be compared with various iris recognition algorithms found in the literature.

Keywords: iris recognition, particle swarm optimization, feature extraction, feature selection, palm print, the Scale Invariant Feature Transform (SIFT)

Procedia PDF Downloads 233

Authors: Qais M. Yousef, Yasmeen A. Alshaer

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Over the last few years, the amount of data available on the globe has been increased rapidly. This came up with the emergence of recent concepts, such as the big data and the Internet of Things, which have furnished a suitable solution for the availability of data all over the world. However, managing this massive amount of data remains a challenge due to their large verity of types and distribution. Therefore, locating the required file particularly from the first trial turned to be a not easy task, due to the large similarities of names for different files distributed on the web. Consequently, the accuracy and speed of search have been negatively affected. This work presents a method using Electroencephalography signals to locate the files based on their contents. Giving the concept of natural mind waves processing, this work analyses the mind wave signals of different people, analyzing them and extracting their most appropriate features using multi-objective metaheuristic algorithm, and then classifying them using artificial neural network to distinguish among files with similar names. The aim of this work is to provide the ability to find the files based on their contents using human thoughts only. Implementing this approach and testing it on real people proved its ability to find the desired files accurately within noticeably shorter time and retrieve them as a first choice for the user.

Keywords: artificial intelligence, data contents search, human active memory, mind wave, multi-objective optimization

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Authors: M. A. Grigoryev, A. N. Shishkov, D. A. Sychev

Abstract:

The article defines the necessity of choosing the optimal power circuits scheme of the electric drive with field regulated reluctance machine. The specific weighting factors are calculation, the linear regression dependence of specific losses in semiconductor frequency converters are presented depending on the values of the rated current. It is revealed that with increase of the carrier frequency PWM improves the output current waveform, but increases the loss, so you will need depending on the task in a certain way to choose from the carrier frequency. For task of optimization by criterion of the minimum electrical losses regression dependence of the electrical losses in the frequency converter circuit at a frequency of a PWM signal of 0 Hz. The surface optimization criterion is presented depending on the rated output torque of the motor and number of phases. In electric drives with field regulated reluctance machine with at low output power optimization criterion appears to be the worst for multiphase circuits. With increasing output power this trend hold true, but becomes insignificantly different optimal solutions for three-phase and multiphase circuits. This is explained to the linearity of the dependence of the electrical losses from the current.

Keywords: field regulated reluctance machine, the electrical losses, multiphase power circuit, the surface optimization criterion

Procedia PDF Downloads 293