Search results for: performance parameters

Authors: Ana L. Martins, Rita S. Saraiva, João C. Ferreira

Abstract:

Much effort has been placed on the assessment of perceived service quality. Several models can be found in literature, but these are mainly focused on business-to-consumer (B2C) relationships. Literature on how to assess perceived quality in business-to-business (B2B) contexts is scarce both conceptually and in terms of its application. This research aims at filling this gap in literature by applying INDSERV to a case study situation. Under this scope, this research aims at analyzing the adequacy of the proposed assessment tool to other context besides the one where it was developed and by doing so analyzing the perceive quality of the advertisement service provided by a specific television network to its B2B customers. The INDSERV scale was adopted and applied to a sample of 33 clients, via questionnaires adapted to interviews. Data was collected in person or phone. Both quantitative and qualitative data collection was performed. Qualitative data analysis followed content analysis protocol. Quantitative analysis used hypotheses testing. Findings allowed to conclude that the perceived quality of the television service provided by television network is very positive, being the Soft Process Quality the parameter that reveals the highest perceived quality of the service as opposed to Potential Quality. To this end, some comments and suggestions were made by the clients regarding each one of these service quality parameters. Based on the hypotheses testing, it was noticed that only advertisement clients that maintain a connection to the television network from 5 to 10 years do show a significant different perception of the TV advertisement service provided by the company in what the Hard Process Quality parameter is concerned. Through the collected data content analysis, it was possible to obtain the percentage of clients which share the same opinions and suggestions for improvement. Finally, based on one of the four service quality parameter in a B2B context, managerial suggestions were developed aiming at improving the television network advertisement perceived quality service.

Keywords: B2B, case study, INDSERV, perceived service quality

Procedia PDF Downloads 201

Authors: Jaime Carpio-García, Elena Blanco-Fernández, Jorge Rodríguez-Hernández, Daniel Castro-Fresno

Abstract:

Geosynthetic mechanical behavior vs temperature or vs aging has been widely studied independently during the last years, both in laboratory and in outdoor conditions. This paper studies this behavior deeper, considering that geosynthetics have to perform adequately at different outdoor temperatures once they have been subjected to a certain degree of aging, and also considering the different geosynthetic structures made of the same material. This combining effect has been not considered so far, and it is important to ensure the performance of geosynthetics, especially where high temperatures are expected. In order to fill this gap, six commercial geosynthetics with different internal structures made of polypropylene (PP), high density polyethylene (HDPE), bitumen and polyvinyl chloride (PVC), or even a combination of some of them have been mechanically tested at mild temperature (20ºC or 23ºC) and at warm temperature (45ºC) before and after specific exposition to air at standardized high temperature in order to simulate 25 years of aging due to oxidation. Besides, for 45ºC tests, an innovative heating system during test for high deformable specimens is proposed. The influence of the combining effect of aging, structure and temperature in the product behavior have been analyzed and discussed, concluding that internal structure is more influential than aging in the mechanical behavior of a geosynthetic versus temperature.

Keywords: geosynthetics, mechanical behavior, temperature, aging, internal structure

Procedia PDF Downloads 62

Authors: Shahriar Farzam, Maryam Rastgarpour

Abstract:

Image denoising plays extremely important role in digital image processing. Enhancement of clinical image research based on Curvelet has been developed rapidly in recent years. In this paper, we present a method for image contrast enhancement for cone beam CT (CBCT) images based on fast discrete curvelet transforms (FDCT) that work through Unequally Spaced Fast Fourier Transform (USFFT). These transforms return a table of Curvelet transform coefficients indexed by a scale parameter, an orientation and a spatial location. Accordingly, the coefficients obtained from FDCT-USFFT can be modified in order to enhance contrast in an image. Our proposed method first uses a two-dimensional mathematical transform, namely the FDCT through unequal-space fast Fourier transform on input image and then applies thresholding on coefficients of Curvelet to enhance the CBCT images. Consequently, applying unequal-space fast Fourier Transform leads to an accurate reconstruction of the image with high resolution. The experimental results indicate the performance of the proposed method is superior to the existing ones in terms of Peak Signal to Noise Ratio (PSNR) and Effective Measure of Enhancement (EME).

Keywords: curvelet transform, CBCT, image enhancement, image denoising

Procedia PDF Downloads 288

Authors: Ayliana Dharmawan, Heng Yong Sheng, Zhang Xiaojin, Tan Thai Lian

Abstract:

To facilitate discharge planning, doctors are presently required to assign an Estimated Discharge Date (EDD) for each patient admitted to the hospital. This assignment of the EDD is largely based on the doctor’s judgment. This can be difficult for cases which are complex or relatively new to the doctor. It is hypothesized that a data-driven approach would be able to facilitate the doctors to make accurate estimations of the discharge date. Making use of routinely collected data on inpatient discharges between January 2013 and May 2016, a predictive model was developed using machine learning techniques to predict the Length of Stay (and hence the EDD) of inpatients, at the point of admission. The predictive performance of the model was compared to that of the clinicians using accuracy measures. Overall, the best performing model was found to be able to predict EDD with an accuracy improvement in Average Squared Error (ASE) by -38% as compared to the first EDD determined by the present method. It was found that important predictors of the EDD include the provisional diagnosis code, patient’s age, attending doctor at admission, medical specialty at admission, accommodation type, and the mean length of stay of the patient in the past year. The predictive model can be used as a tool to accurately predict the EDD.

Keywords: inpatient, estimated discharge date, EDD, prediction, data-driven

Procedia PDF Downloads 163

Authors: Alirıza Kaleli, M. Akif Ceviz, Erdoğan Güner, Köksal Erentürk

Abstract:

The cyclic variations in spark ignition engines occurring especially under specific engine operating conditions make the maximum pressure variable for successive in-cylinder pressure cycles. Minimization of cyclic variations has a great importance in effectively operating near to lean limit, or at low speed and load. The cyclic variations may reduce the power output of the engine, lead to operational instabilities, and result in undesirable engine vibrations and noise. In this study, spark timing is controlled in order to reduce the cyclic variations in spark ignition engines. Firstly, an ARMAX model has developed between spark timing and maximum pressure using system identification techniques. By using this model, the maximum pressure of the next cycle has been predicted. Then, self-tuning minimum variance controller has been designed to change the spark timing for consecutive cycles of the first cylinder of test engine to regulate the in-cylinder maximum pressure. The performance of the proposed controller is illustrated in real time and experimental results show that the controller has a reliable effect on cycle to cycle variations of maximum cylinder pressure when the engine works under low speed conditions.

Keywords: cyclic variations, cylinder pressure, SI engines, self tuning controller

Procedia PDF Downloads 471

Authors: Zhijun Ren, Zhang Lin, Zhao Ye, Zuo Xiangyu, Mei Dongxing

Abstract:

As a pretreatment process of ballast water treatment, the performance of high gradient magnetic separation (HGMS) technology for the removal of particulates and microorganisms was studied. The results showed that HGMS process could effectively remove suspended particles larger than 5 µm and had ability to resist impact load. Microorganism could also be effectively removed by HGMS process, and the removal effect increased with increasing magnetic field strength. The maximum removal rates for Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) were 4016.1% and 9675.3% higher, respectively, than without the magnetic field. In addition, the superoxide dismutase (SOD) activity of the microbes decreased by 32.2% when the magnetic field strength was 15.4 mT for 72 min. The microstructure of the stainless steel wool was investigated, and the results showed that particle removal by HGMS has common function by the magnetic force of the high-strength, high-gradient magnetic field on weakly magnetic particles in the water, and on the stainless steel wool.

Keywords: HGMS, particulates, superoxide dismutase (SOD) activity, steel wool magnetic medium

Procedia PDF Downloads 442

Authors: Valeriu Mihai But, Sorana Daniela Bolboacă, Adriana Elena Bulboacă

Abstract:

The nutraceutical compound Curcumin (Curcuma longa L.) is known for its anti-inflammatory, anti-cancer, and antioxidant effects. This study aimed to evaluate the antioxidative and analgesic effects of Curcumin (CC) compared to Tramadol (T) in chemical-induced nociceptive pain in rats. Thirty-five rats were randomly divided into five groups of seven rats each and were treated as follows: C group (control group): treated with saline solution 0.9%, (1 ml, i.p. administration), ethanoic acid (EA) group: pretreated with saline solution 0.9% - 30 min before EA nociceptive pain induction, (1 ml, i.p. administration), T group: pretreated with Tramadol, 10 mg/kg body weight (bw), i.p. administration - 30 min before EA nociceptive pain induction, CC1-group: pretreated with 1 mg/100g bw Curcumin i.p. administration - 2 days before EA pain induction and CC2-group: pretreated with Curcumin 2 mg/100g bw i.p. administration - 2 days before EA nociceptive pain induction. The following oxidative stress parameters were assessed: malondialdehyde (MDA), nitric oxide (NOx), total oxidative status (TOS), total antioxidative capacity (TAC), and thiol (Th). The antalgic activity was measured by the ethanoic acid writhing test. Treatment with Curcumin, both 1 mg/100g bw, and 2 mg/100g bw, showed significant differences as compared with the control group (p<0.001) regarding malondialdehyde (MDA), nitric oxide (NOx), and total oxidative status (TOS) oxidative biomarkers. Pretreatment with 2 mg/100g bw of Curcumin presented a significant decrease in MDA values compared with Tramadol (p<0.001). The TAC significantly increased in pretreatment with Curcumin compared with group control. (p<0.001) The nociceptive response to EA was significantly reduced in Curcumin and Tramadol groups. Treatment with Curcumin at a higher concentration was more effective. In an experimental pain model, this study demonstrates an important antioxidant and antinociceptive activity of Curcumin comparable with Tramadol treatment.

Keywords: curcumin, nociception, oxidative stress, pain

Procedia PDF Downloads 102

Authors: Ajish K. Abraham

Abstract:

Hearing aid is the most fundamental technology employed towards rehabilitation of persons with sensory neural hearing impairment. Hearing in noise is still a matter of major concern for many hearing aid users and thus continues to be a challenging issue for the hearing aid designers. Several techniques are being currently used to enhance the speech at the hearing aid output. Most of these techniques, when implemented, result in reduction of intelligibility of the speech signal. Thus the dissatisfaction of the hearing aid user towards comprehending the desired speech amidst noise is prevailing. Multichannel Wiener Filter is widely implemented in binaural hearing aid technology for noise reduction. In this study, Wiener filter based noise reduction approach is experimented for a single microphone based hearing aid set up. This method checks the status of the input speech signal in each frequency band and then selects the relevant noise reduction procedure. Results showed that the Wiener filter based algorithm is capable of enhancing speech even when the input acoustic signal has a very low Signal to Noise Ratio (SNR). Performance of the algorithm was compared with other similar algorithms on the basis of improvement in intelligibility and SNR of the output, at different SNR levels of the input speech. Wiener filter based algorithm provided significant improvement in SNR and intelligibility compared to other techniques.

Keywords: hearing aid output speech, noise reduction, SNR improvement, Wiener filter, speech enhancement

Procedia PDF Downloads 240

Authors: Ana Serafimovic, Karthik Devarajan

Abstract:

Non-negative matrix factorization approximates a high dimensional non-negative matrix V as the product of two non-negative matrices, W and H, and allows only additive linear combinations of data, enabling it to learn parts with representations in reality. It has been successfully applied in the analysis and interpretation of high dimensional data arising in neuroscience, computational biology, and natural language processing, to name a few. The objective of this paper is to assess a hybrid algorithm for non-negative matrix factorization with multiplicative updates. The method aims to minimize the symmetric version of Kullback-Leibler divergence known as intrinsic information and assumes that the noise is signal-dependent and that it originates from an arbitrary distribution from the exponential family. It is a generalization of currently available algorithms for Gaussian, Poisson, gamma and inverse Gaussian noise. We demonstrate the potential usefulness of the new generalized algorithm by comparing its performance to the baseline methods which also aim to minimize symmetric divergence measures.

Keywords: non-negative matrix factorization, dimension reduction, clustering, intrinsic information, symmetric information divergence, signal-dependent noise, exponential family, generalized Kullback-Leibler divergence, dual divergence

Procedia PDF Downloads 240

Authors: Fei Gao, Rodolfo C. Raga Jr.

Abstract:

This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

Procedia PDF Downloads 62

Authors: Wang Shuen-Tai, Lin Yu-Ching, Chang Hsi-Ya

Abstract:

Cloud computing is the innovative and leading information technology model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort. In this paper, we aim at the development of workflow management system for cloud computing platforms based on our previous research on the dynamic allocation of the cloud computing resources and its workflow process. We took advantage of the HTML 5 technology and developed web-based workflow interface. In order to enable the combination of many tasks running on the cloud platform in sequence, we designed a mechanism and developed an execution engine for workflow management on clouds. We also established a prediction model which was integrated with job queuing system to estimate the waiting time and cost of the individual tasks on different computing nodes, therefore helping users achieve maximum performance at lowest payment. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for cloud computing platform. This development also helps boost user productivity by promoting a flexible workflow interface that lets users design and control their tasks' flow from anywhere.

Keywords: web-based, workflow, HTML5, Cloud Computing, Queuing System

Procedia PDF Downloads 300

Authors: Y. Zhang, J. Perez, S. Marnier

Abstract:

To date, no study on goaltending butterfly motion has been completed in real conditions, during an ice hockey game or training practice, to the author's best knowledge. This motion, performed to save score, is unnatural, intense, and repeated. The target of this research activity is to identify representative biomechanical criteria for this goaltender-specific movement pattern. Determining specific physical parameters may allow to will identify the risk of hip and groin injuries sustained by goaltenders. Four professional or academic goalies were instrumented during ice hockey training practices with five inertial measurement units. These devices were inserted in dedicated pockets located on each thigh and shank, and the fifth on the lumbar spine. A camera was also installed close to the ice to observe and record the goaltenders' activities, especially the butterfly motions, in order to synchronize the captured data and the behavior of the goaltender. Each data recorded began with a calibration of the inertial units and a calibration of the fully equipped goaltender on the ice. Three butterfly motions were recorded out of the training practice to define referential individual butterfly motions. Then, a data processing algorithm based on the Madgwick filter computed hip and knee joints joint range of motion as well as angular specific angular velocities. The developed algorithm software automatically identified and analyzed all the butterfly motions executed by the four different goaltenders. To date, it is still too early to show that the analyzed criteria are representative of the trauma generated by the butterfly motion as the research is only at its beginning. However, this descriptive research activity is promising in its ecological assessment, and once the criteria are found, the tools and protocols defined will allow the prevention of as many injuries as possible. It will thus be possible to build a specific training program for each goalie.

Keywords: biomechanics, butterfly motion, human motion analysis, ice hockey, inertial measurement unit

Procedia PDF Downloads 119

Authors: Mourad Makhlouf Sabrina Bouriche, Zoubir Benmaamar, Didier Villemin

Abstract:

Background: The increasing presence of electromagnetic interference (EMI) requires the development of effective protection solutions. Intelligent textiles offer a promising approach due to their wear ability and the possibility of integration into everyday clothing. In this study, the use of graphene and polyaniline for EMI shielding on cotton fabrics was examined. Methods: In this study, the continuous dyeing of recycled graphite-derived graphene and polyaniline was examined. Bottom-reforming technology was adopted to improve adhesion and achieve uniform distribution of conductive material on the fiber surface. The effect of material weight ratio on fabric performance and X-band EMI shielding effectiveness (SE) was evaluated. Significant Findings: The dyed cotton fabrics incorporating graphene, polyaniline, and their combination exhibited improved conductivity. Notably, these fabrics achieved EMI SE values ranging from 9 to 16 dB within the X-band frequency range (8-9 GHz). These findings demonstrate the potential of this approach for developing intelligent textiles with effective EMI shielding capabilities. Additionally, the utilization of recycled materials contributes to a more sustainable shielding solution.

Keywords: Intelligent textiles, graphene, polyaniline, electromagnetic shielding, conductivity, recycling

Procedia PDF Downloads 23

Authors: Anthony Quansah, Tresor Ntaryamira, Shula Mushota

Abstract:

Models for geotechnical centrifuge testing are usually made from re-formed soil, allowing for comparisons with naturally occurring soil deposits. However, there is a fundamental omission in this process because the natural soil is deposited in layers creating a unique structure. Nonlinear dynamics of clay material deposit is an essential part of changing the attributes of ground movements when subjected to solid seismic loading, particularly when diverse intensification conduct of speeding up and relocation are considered. The paper portrays a review of axis shaking table tests and numerical recreations to explore the offshore clay deposits subjected to seismic loadings. These perceptions are accurately reenacted by DEEPSOIL with appropriate soil models and parameters reviewed from noteworthy centrifuge modeling researches. At that point, precise 1-D site reaction investigations are performed on both time and recurrence spaces. The outcomes uncover that for profound delicate clay is subjected to expansive quakes, noteworthy increasing speed lessening may happen close to the highest point of store because of soil nonlinearity and even neighborhood shear disappointment; nonetheless, huge enhancement of removal at low frequencies are normal in any case the forces of base movements, which proposes that for dislodging touchy seaward establishments and structures, such intensified low-recurrence relocation reaction will assume an essential part in seismic outline. This research shows centrifuge as a tool for creating a layered sample important for modelling true soil behaviour (such as permeability) which is not identical in all directions. Currently, there are limited methods for creating layered soil samples.

Keywords: seismic analysis, layered modeling, terotechnology, finite element modeling

Procedia PDF Downloads 148

Authors: Khaled M. Alhawiti

Abstract:

This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: speech recognition, acoustic phonetic, artificial intelligence, hidden markov models (HMM), statistical models of speech recognition, human machine performance

Procedia PDF Downloads 468

Authors: Ahmed Chetouani

Abstract:

Corrosion is a natural occurring process where it can be defined as the deterioration of materials properties due to its interaction with its environment. Corrosion can lead to failures in plant infrastructure and machines which are usually costly to repair. In terms of loss of contaminated products which will cause environmental damage and possibly costly in terms of human health. The driving force that causes metals to corrode is due to the natural consequence of their temporary existence in metallic form. There is a growing trend in utilizing plant extracts and pharmaceutical compounds as corrosion inhibitors. Exquisite identification of the essential oil of aerial parts of Pelargonium was obtained using hydrodistillation and identification using GC (gas chromatography) and GC/MS (gas chromatography-mass spectrometry). The oil was predominated by Citronellol (22.8%). The inhibitory effect of essential oil and extract of Pelargonium was estimated on the corrosion of mild steel in 1M hydrochloric acid (HCl) using weight loss, Electrochemical Impedance Spectroscopy (EIS) and Tafel polarization curves. Inhibition was found to increase with increasing concentration of the essential oil and extract of Pelargonium. The effect of temperature on the corrosion behaviour of mild steel in 1M HCl with addition of essential oil and extract was also studied and the thermodynamic parameters were determined and discussed. Values of inhibition efficiency were calculated from weight loss, Tafel polarization curves, and EIS. All results are in good agreement. Polarization curves showed that essential oil and extract of Pelargonium behave as mixed type inhibitors in hydrochloric acid. The results obtained showed that the essential oil and extract of Pelargonium could serve as an effective inhibitor of the corrosion of mild steel in Hydrochloric acid solution. To avoid any surprise of toxicity, the majority compounds have been studied by using POM analyses.

Keywords: corrosion inhibition, mild steel, pelargonium oil, extract, electrochemical system, hydrodistillation, side effects, POM Analyses

Procedia PDF Downloads 394

Authors: Fathi Kallel, Ahmed Ben Hamida, Christian Berger-Vachon

Abstract:

In this paper, a Speech Enhancement Algorithm based on Multi-Band Spectral Subtraction (MBSS) principle is evaluated for Bilateral Cochlear Implant (BCI) users. Specifically, dual-channel noise power spectral estimation algorithm using Power Spectral Densities (PSD) and Cross Power Spectral Densities (CPSD) of the observed signals is studied. The enhanced speech signal is obtained using Dual-Channel Multi-Band Spectral Subtraction ‘DC-MBSS’ algorithm. For performance evaluation, objective speech assessment test relying on Perceptual Evaluation of Speech Quality (PESQ) score is performed to fix the optimal number of frequency bands needed in DC-MBSS algorithm. In order to evaluate the speech intelligibility, subjective listening tests are assessed with 3 deafened BCI patients. Experimental results obtained using French Lafon database corrupted by an additive babble noise at different Signal-to-Noise Ratios (SNR) showed that DC-MBSS algorithm improves speech understanding for single and multiple interfering noise sources.

Keywords: speech enhancement, spectral substracion, noise estimation, cochlear impalnt

Procedia PDF Downloads 540

Authors: Ali Osman Güney, Bahattin Kanber

Abstract:

In this work, the effect of material type, diameter, orientation and closeness of fibers on the general performance of reinforced vulcanized rubbers are investigated using finite element method with experimental verification. Various fiber materials such as hemp, nylon, polyester are used for different fiber diameters, orientations and closeness. 3D finite element models are developed by considering bonded contact elements between fiber and rubber sheet interfaces. The fibers are assumed as linear elastic, while vulcanized rubber is considered as hyper-elastic. After an experimental verification of finite element results, the developed models are analyzed under prescribed displacement that causes tension. The normal stresses in fibers and shear stresses between fibers and rubber sheet are investigated in all models. Large deformation of reinforced rubber sheet also represented with various fiber conditions under incremental loading. A general assessment is achieved about best fiber properties of reinforced rubber sheets for tension-load conditions.

Keywords: reinforced vulcanized rubbers, fiber properties, out of plane loading, finite element method

Procedia PDF Downloads 336

Authors: Anucha Wittayakorn-Puripunpinyoo

Abstract:

The research objectives were 1) to study the situation and its trend of agricultural product export of Thailand 2) to study the impact of agricultural product export on income of Thai economy 3) the impact of agricultural product export on employment of Thai economy and 4) to find out the recommendations of agricultural product export policy of Thailand. In this research, secondary data were collected as yearly time series data from 1990 to 2016 accounted for 27 years. Data were collected from the Bank of Thailand database. Primary data were collected from the steakholders of agricultural product export policy of Thailand. Data analysis was applied descriptive statistics such as arithmetic mean, standard deviation. The forecasting of agricultural product was applied Mote Carlo Simulation technique as well as time trend analysis. In addition, the impact of agricultural product export on income and employment by applying econometric model while the estimated parameters were utilized the ordinary least square technique. The research results revealed that 1) agricultural product export value of Thailand from 1990 to 2016 was 338,959.5 Million Thai baht with its growth rate of 4.984 percent yearly, in addition, the forecasting of agricultural product export value of Thailand has increased but its growth rate has been declined 2) the impact of agricultural product export has positive impact on income in Thai economy, increasing in agricultural product export of Thailand by 1 percent would lead income increased by 0.0051 percent 3) the impact of agricultural product export has positive impact on employment in Thai economy, increasing in agricultural product export of Thailand by 1 percent would lead income increased by 0.079 percent and 4) in the future, agricultural product export policy would focused on finished or semi-finished agricultural product instead of raw material by applying technology and innovation in to make value added of agricultural product export. The public agricultural product export policy would support exporters in private sector in order to encourage them as agricultural exporters in Thailand.

Keywords: agricultural product export, income, employment, Thai economy

Procedia PDF Downloads 297

Authors: Amirhossein Mohajerzadeh, Abolghasem Mohajerzadeh

Abstract:

In this paper, target parameter is estimated with desirable precision in hierarchical wireless sensor networks (WSN) while the proposed algorithm also tries to prolong network lifetime as much as possible, using efficient data collecting algorithm. Target parameter distribution function is considered unknown. Sensor nodes sense the environment and send the data to the base station called fusion center (FC) using hierarchical data collecting algorithm. FC builds underlying phenomena based on collected data. Considering the aggregation level, x, the goal is providing the essential infrastructure to find the best value for aggregation level in order to prolong network lifetime as much as possible, while desirable accuracy is guaranteed (required sample size is fully depended on desirable precision). First, the sample size calculation algorithm is discussed, second, the average queue length based on M/M[x]/1/K queue model is determined and it is used for energy consumption calculation. Nodes can decrease transmission cost by aggregating incoming data. Furthermore, the performance of the new algorithm is evaluated in terms of lifetime and estimation accuracy.

Keywords: aggregation, estimation, queuing, wireless sensor network

Procedia PDF Downloads 180

Authors: Sara Patricia Ibarra-Zavaleta, Rabindranarth Romero-Lopez, Rosario Langrave, Annie Poulin, Gerald Corzo, Mathias Glaus, Ricardo Vega-Azamar, Norma Angelica Oropeza

Abstract:

The progressive change in climatic conditions worldwide has increased frequency and severity of extreme hydrometeorological events (EHE). Mexico is an example; this has been affected by the presence of EHE leaving economic, social and environmental losses. The objective of this research was to apply a Canadian distributed hydrological model (DHM) to tropical conditions and to evaluate its capacity to predict flows in a basin in the central Gulf of Mexico. In addition, the DHM (once calibrated and validated) was used to calculate the theoretical hydraulic power and the performance to predict streamflow before the presence of an EHE. The results of the DHM show that the goodness of fit indicators between the observed and simulated flows in the calibration process (NSE=0.83, RSR=0.021 and BIAS=-4.3) and validation: temporal was assessed at two points: point one (NSE=0.78, RSR=0.113 and BIAS=0.054) and point two (NSE=0.825, RSR=0.103 and BIAS=0.063) are satisfactory. The DHM showed its applicability in tropical environments and its ability to characterize the rainfall-runoff relationship in the study area. This work can serve as a tool for identifying vulnerabilities before floods and for the rational and sustainable management of water resources.

Keywords: HYDROTEL, hydraulic power, extreme hydrometeorological events, streamflow

Procedia PDF Downloads 332

Authors: Rahma Goussi, Walid Derbali, Arafet Manaa, Simone Cantamessa, Graziella Berta, Chedly Abdelly, Roberto Barbato

Abstract:

Salinity is one of the most important abiotic affecting plant growth and productivity worldwide. Photosynthesis, together with cell growth, is among the primary processes to be affected by salinity. Here, we report the effects of salinity stress on the primary processes of photosynthesis in a model halophyte Thellungiella Salsuginea. Plants were cultivated in hydroponic system with different NaCl concentrations (0, 100, 200 and 400 mM) during 2 weeks. The obtained results showed an obvious change in the photosynthetic efficiency of photosystem I (PSI) and phostosytem II (PSII), related to NaCl concentration supplemented to the medium and the stress duration considered. With moderate salinity (100 and 200 mM NaCl), no significant variation was observed in photosynthetic parameters of PSI and PSII and Chl fluorescence whatever the time of stress application. Also, the photosynthesis apparatus Fo, Fm and Fv fluorescence, as well as Fv/Fm were not affected by salt stress. While a significant decrease was observed on quantum yields Y(I), Y(II) and electron transport rate ETR(I), ETR(II) under high salt treatment (400 mM NaCl) with prolonged period (15 days). This reduction is quantitatively compensated by a corresponding increase of energy dissipation Y(NPQ) and a progressive decrease in Fv/Fm under salt treatment. The intensity of the OJIP fluorescence transient decreased with increase in NaCl concentration, with a major effect observed during prolonged period of salt stress. Ultrastructural analysis with Light Microscopy and Transmission Electron Microscopy of T. salsuginea chloroplasts showed some cellular changes, such as the shape of the mesophyll cells and number of chloroplast/cell only under higher NaCl concentration. Salt-stress caused the swelling of thylakoids in T. Salsuginea mesophyll with more accumulation of starch as compared to control plant.

Keywords: fluorescence, halophyte, photosynthesis, salt stress

Procedia PDF Downloads 365

Authors: A. Yongsheng Guo, B. Obedat. Abdulazeez, C. Xiaoxian Zhu

Abstract:

This study aimed to identify the barriers to the development of small and medium-sized enterprises (SMEs) in China and build a theoretical framework to evaluate the support provided by the authorities and institutions. A grounded theory approach was adopted to collect and analyze data. 32 interviews were conducted with SME managers, and open, axial and selective coding was utilized to develop themes. Based on institutional theory, grounded theory models were used to present findings. The findings showed that the main barriers in the business environment were defaulting on contracts, bureaucracy in procedures, lack of financial and legal support, limited intermediaries and channels, and poor quality of products and services. This study found that many programs were provided to support SMEs. A theoretical framework was developed to evaluate the performance of the programs from the managers’ perspective. The concepts of economy, efficiency and effectiveness were used to evaluate the perceived value of the programs. This study suggests that specialized programs are needed to suit sector-specific requirements, and creative packages are helpful in supporting SMEs' growth.

Keywords: business support, public economics, public programme, SME

Procedia PDF Downloads 31

Authors: Arthur D. Wiedemann, Christopher Fuller, Kyle A. Pascioni

Abstract:

With the introduction of electric motors, small unmanned aerial vehicle designers have to consider trade-offs between acoustic noise and thrust generated. Currently, there are few low-computational tools available for predicting acoustic noise emitted by a propeller into the far-field. Artificial neural networks offer a highly non-linear and adaptive model for predicting isolated and interactive tonal noise. But neural networks require large data sets, exceeding practical considerations in modeling experimental results. A methodology known as physics guided machine learning has been applied in this study to reduce the required data set to train the network. After building and evaluating several neural networks, the best model is investigated to determine how the network successfully predicts the acoustic waveform. Lastly, a post-network transfer function is developed to remove discontinuity from the predicted waveform. Overall, methodologies from physics guided machine learning show a notable improvement in prediction performance, but additional loss functions are necessary for constructing predictive networks on small datasets.

Keywords: aeroacoustics, machine learning, propeller, rotor, neural network, physics guided machine learning

Procedia PDF Downloads 212

Authors: Patrick T. Aquino, Jimwel B. Balunday, Cephas Olivier V. Cabatit, Mary Grace Q. Razonable

Abstract:

In 2023, the Philippine Department of Energy (PDOE) published the National Energy Efficiency and Conservation Plan (NEECP) and Roadmap 2023-2050 to be the basis of a comprehensive program for the efficient supply and economical use of energy. The building sector, as one of the most energy-intensive sectors, shall conform to the energy-conserving design to reduce the use of energy. The concept of Net-Zero Energy Building (NZEB), and its definitions promote to improve energy efficiency of the buildings. The PDOE partnered with Meralco Power Academy to survey and conduct focus group discussions to establish the readiness into NZE-aspiring buildings of government entities. This paper outlines important NZEB principles, best practices from other countries, issues and gaps relating to energy management program, and the recommendations on the development of a framework for NZEB under government building in the Philippines. Results revealed the limitation on specific data to establish a baseline building energy efficiency performance index and significant energy uses; the need to update the Guidelines for Energy Conservation Design of Buildings, including NZEB definition and requirements; appropriate enabling infrastructures and programs to transition government buildings into NZE-aspiring buildings to Nearly Zero Energy Buildings by 2050.

Keywords: NZEB, energy efficiency, buildings, Philippines

Procedia PDF Downloads 79

Authors: Halkiopoulos Constantinos, Gkintoni Evgenia, Koutsopoulou Ioanna, Antonopoulou Hera

Abstract:

E-sports and e-gaming have emerged in recent years since the increase in internet use have become universal and e-gamers are the new reality in our homes. The excessive involvement of young adults with e-sports has already been revealed and the adverse consequences have been reported in researches in the past few years, but the issue has not been fully studied yet. The present research is conducted in Greece and studies the psychological profile of video game players and provides information on personality traits, habits and emotional status that affect online gamers’ behaviors in order to help professionals and policy makers address the problem. Three standardized self-report questionnaires were administered to participants who were young male and female adults aged from 19-26 years old. The Profile of Mood States (POMS) scale was used to evaluate people’s perceptions of their everyday life mood; the personality features that can trace back to people’s habits and anticipated reactions were measured by Eysenck Personality Questionnaire (EPQ), and the Trait Emotional Intelligence Questionnaire (TEIQue) was used to measure which cognitive (gamers’ beliefs) and emotional parameters (gamers’ emotional abilities) mainly affected/ predicted gamers’ behaviors and leisure time activities?/ gaming behaviors. Data mining techniques were used to analyze the data, which resulted in machine learning algorithms that were included in the software package R. The research findings attempt to designate the effect of personality traits, emotional status and emotional intelligence influence and correlation with e-sports, gamers’ behaviors and help policy makers and stakeholders take action, shape social policy and prevent the adverse consequences on young adults. The need for further research, prevention and treatment strategies is also addressed.

Keywords: e-sports, e-gamers, personality traits, POMS, emotional intelligence, data mining, R

Procedia PDF Downloads 222

Authors: Ebenezer O. Olaniyi, Oyebade K. Oyedotun, Khashman Adnan

Abstract:

In the food industry high quality production is required within a limited time to meet up with the demand in the society. In this research work, we have developed a model which can be used to replace the human operator due to their low output in production and slow in making decisions as a result of an individual differences in deciding the defective and healthy banana. This model can perform the vision attributes of human operators in deciding if the banana is defective or healthy for food production based. This research work is divided into two phase, the first phase is the image processing where several image processing techniques such as colour conversion, edge detection, thresholding and morphological operation were employed to extract features for training and testing the network in the second phase. These features extracted in the first phase were used in the second phase; the classification system phase where the multilayer perceptron using backpropagation neural network was employed to train the network. After the network has learned and converges, the network was tested with feedforward neural network to determine the performance of the network. From this experiment, a recognition rate of 97% was obtained and the time taken for this experiment was limited which makes the system accurate for use in the food industry.

Keywords: banana, food processing, identification system, neural network

Procedia PDF Downloads 461

Authors: Khue Nguyen Dinh, Loi Nguyen Van, Thanh Nguyen Nhu

Abstract:

In this paper, we propose an adaptive method to resolve ambiguities and a ghost target removal process to extract targets detected by a ground-based pulse-Doppler radar using medium pulse repetition frequency (PRF) waveforms. The ambiguity resolution method is an adaptive implementation of the coincidence algorithm, which is implemented on a two-dimensional (2D) range-velocity matrix to resolve range and velocity ambiguities simultaneously, with a proposed clustering filter to enhance the anti-error ability of the system. Here we consider the scenario of multiple target environments. The ghost target removal process, which is based on the power after Doppler processing, is proposed to mitigate ghosting detections to enhance the performance of ground-based radars using a short PRF schedule in multiple target environments. Simulation results on a ground-based pulsed Doppler radar model will be presented to show the effectiveness of the proposed approach.

Keywords: ambiguity resolution, coincidence algorithm, medium PRF, ghosting removal

Procedia PDF Downloads 141

Authors: Larissa Negris de Souza, Ana Regina Mizrahy Cuperschmid, Daniel de Carvalho Moreira

Abstract:

Augmented Reality (AR) alters the elaboration of the architectural project, which relates to project cognition: representation, visualization, and perception of information. Understanding these features from the earliest stages of the design can facilitate the study of relationships, zoning, and overall dimensions of the forms. This paper’s goal was to explore a new approach for information visualization during the early stages of architectural design using Augmented Reality (AR). A three-dimensional marker inspired by the Rubik’s Cube was developed, and its performance, evaluated. This investigation interwovens the acquired knowledge of traditional briefing methods and contemporary technology. We considered the concept of patterns (Alexander et al. 1977) to outline geometric forms and associations using visual programming. The Design Science Research was applied to develop the study. An SDK was used in a game engine to generate the AR app. The tool's functionality was assessed by verifying the readability and precision of the reconfigurable 3D marker. The results indicated an inconsistent response. To use AR in the early stages of architectural design the system must provide consistent information and appropriate feedback. Nevertheless, we conclude that our framework sets the ground for looking deep into AR tools for briefing design.

Keywords: augmented reality, cuboid marker, early design stages, graphic representation, patterns

Procedia PDF Downloads 90

Authors: Zayneb Kthiri, Walid Hamada

Abstract:

The application of organic fertilizers is generally known to be useful to sustain soil fertility and plant growth, especially in poor soils, with less than 1% of organic matter, as it is very common in our Tunisian fields. Therefore, we focused on evaluating the effect of a new released liquid organic fertilizer named Solorga (with 5% of organic matter) compared to a reference product (Espartan: Kimitec, Spain) on tomato plant growth and physiology. Both fertilizers, derived from plant decomposition, were applied at an early stage in hydroponic system and under greenhouse. In hydroponic system, after 14 days of their application by root feeding, a significant difference was observed between treatments. Indeed, Solorga improved shoots and roots length, as well as the biomass respectively, by 45%, 27%, and 27.8% increase rate, while compared to control plants. However, Espartan induced less the measured parameters while compared to untreated control. Moreover, Solorga significantly increased the chlorophyll content by 42% compared to control and by 32% compared to Espartan. In the greenhouse, after 20 days of treatments, the results showed a significant effect of both fertilizers on SPAD index and the number of flowers blossom. Solorga increased the amount of chlorophyll present in the leaf by 7% compared to Espartan as well as the plant height under greenhouse. Moreover, the number of flowers blossom increased by 15% in plants treated with Solorga while compared to Espartan. Whereas, there is no notable difference between both organic fertilizers on the fruits blossom and the number of fruits per blossom. In conclusion, even though there is a difference in the organic matter between both fertilizers, Solorga improved better the plant growth in controlled conditions in hydroponic system while compared to Espartan. Altogether the obtained results are encouraging for the use of Solorga as a soil enriching source of organic matter to help plants to boost their growth and help them to overcome abiotic stresses linked to soil fertility.

Keywords: tomato, plant growth, organic fertilizer, hydroponic system, greenhouse

Procedia PDF Downloads 126