Search results for: Cross Entropy Method

Authors: Yulina E. Riany, Divna Haslam, Matthew Sanders

Abstract:

This cross-cultural study aims to compare the level of parental depression and stress, parenting style use, and child emotional and behavioural problems between parents in Australia as an example of a Western country and parents in Indonesia as an example of Asian culture. A series of hierarchical regressions were undertaken to determine two models examining the factors that predict child problems residing in Australia (Model 1) and in Indonesia (Model 2). The online survey was completed by 179 parents in Australia and 448 parents in Indonesia. Results indicated that Australian parents reported higher levels of depression, authoritative parenting and higher levels of child misbehaviours compared to Indonesian parents. In comparison, Indonesian parents reported higher authoritarian parenting. Analyses performed to examine Model 1 and 2 revealed that parental negative emotional states and parenting style predicted child emotional and behavioural problems in both countries.

Keywords: cross-cutural study, parental stress, parenting, child misbehaviour

Procedia PDF Downloads 99

Authors: Tien-Ching Yao, Ching-Ching Lu

Abstract:

Understanding human language processing is one of the main challenges of current cognitive neuroscience. The aims of the present study were to use a sentence decision task combined with event-related potentials to investigate the psychological reality of "cross-sentence patterns." Therefore, we take the math word problems the experimental materials and use the ERPs' P600 component to verify. In this study, the experimental material consisted of 200 math word problems with three different conditions were used ( multiplication word problems、division word problems type 1、division word problems type 2 ). Eighteen Mandarin native speakers participated in the ERPs study (14 of whom were female). The result of the grand average waveforms suggests a later posterior positivity at around 500ms - 900ms. These findings were tested statistically using repeated measures ANOVAs at the component caused by the stimulus type of different questions. Results suggest that three conditions present significant (P < 0.05) on the Mean Amplitude, Latency, and Peak Amplitude. The result showed the characteristic timing and posterior scalp distribution of a P600 effect. We interpreted these characteristic responses as the psychological reality of "cross-sentence patterns." These results provide insights into the sentence processing issues in linguistic theory and psycholinguistic models of language processing and advance our understanding of how people make sense of information during language comprehension.

Keywords: language processing, sentence comprehension, event-related potentials, cross-sentence patterns

Procedia PDF Downloads 128

Authors: Kishor Bhagwat, Gayatri Vyas

Abstract:

Construction industry is earmarked with complex processes depending on the nature and scope of the project. In recent years, developments in this sector are remarkable and have resulted in both positive and negative impacts on the environment and human being. Sustainable construction can be looked upon as one of the solution to overcome the negative impacts since sustainable construction is a vast concept, which includes many parameters, and sometimes the use of multi-criteria decision making [MCDM] tools becomes necessary. The main objective of this study is to determine the weightage of sustainable building parameters with the help of MCDM tools. Questionnaire survey was conducted to examine the perspective of respondents on the importance of weights of the criterion, and the respondents were architects, green building consultants, and civil engineers. This paper presents an overview of research related to Indian and international green building rating systems and MCDM. The results depict that economy, environmental health, and safety, site selection, climatic condition, etc., are important parameters in sustainable construction.

Keywords: green building, sustainability, multi-criteria decision making method [MCDM], analytical hierarchy process [AHP], technique for order preference by similarity to an ideal solution [TOPSIS], entropy

Procedia PDF Downloads 71

Authors: Atish Bagchi, Siva Chandrasekaran

Abstract:

Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

Procedia PDF Downloads 126

Authors: Oussema Tabbabi, Mondher Laabidi, Fethi Choubani, J. David

Abstract:

This study presents a miniaturized antenna based on chiral metamaterials slotted ground plane. To decrease resonant frequency while keeping the antennas physical dimensions the same, we propose a two novel patch antennas with double Z and cross slots on the ground plane. The length of the each type of slot are also altered to investigate the effect on miniaturization performance. Resonance frequency reduction has been achieved nearly to 30% and 23% as well as size reduction of almost 28% and 22% for the double Z and the cross shape respectively.

Keywords: chiral metamaterials, miniaturized antenna, miniaturization, resonance frequency

Procedia PDF Downloads 440

Authors: Vinod B. Suryawanshi, Ajit D. Kelkar

Abstract:

Glass fiber reinforced composites materials, due their unique properties such as high mechanical strength to weight ratio, corrosion resistance, and impact resistance have huge potential as structural materials in automotive, construction and transportation applications. However, these properties often come at higher cost owing to complex design methods, difficult manufacturing processes and raw material cost. In this paper, a cost effective design and manufacturing approach for a composite cantilever beam structure is presented. A constant stress (variable cross section) beam concept has been used to design and optimize the shape of composite cantilever beam and thus obtain the reduction in material used. The variable cross section beam was fabricated from the glass epoxy prepregs using cost effective out of autoclave process. The drop ply technique has been successfully used to obtain the variation in the cross section along the span of the beam. In order to test the beam and validate the design, the beam was subjected to different end loads. Strain gauges were mounted along the length of the beam to obtain strains in the beam at different sections and loads. The strain values were used to calculate the flexural strength and bending stresses in the beam. The stresses obtained through strain measurements from the experiment were found to be uniform along the span of the beam, and thus validates the design. Finally, the finite element model for the constant stress beam was developed using commercial finite element simulation software. It was observed that the simulation results agreed very well with the experimental results.

Keywords: beams, composites, constant cross-section, structures

Procedia PDF Downloads 325

Authors: Elvis Adam Alhassan, Kaiyu Tian, Akos Konadu, Ernest Zamanah, Michael Jackson Adjabui, Ibrahim Justice Musah, Esther Agyeiwaa Owusu, Emmanuel K. A. Agyeman

Abstract:

In this paper, how to solve simultaneous equations using the Elvis improved method is shown. The Elvis improved method says; to make one variable in the first equation the subject; make the same variable in the second equation the subject; equate the results and simplify to obtain the value of the unknown variable; put the value of the variable found into one equation from the first or second steps and simplify for the remaining unknown variable. The difference between our Elvis improved method and the substitution method is that: with Elvis improved method, the same variable is made the subject in both equations, and the two resulting equations equated, unlike the substitution method where one variable is made the subject of only one equation and substituted into the other equation. After describing the Elvis improved method, findings from 100 secondary students and the views of 5 secondary tutors to demonstrate the effectiveness of the method are presented. The study's purpose is proved by hypothetical examples.

Keywords: simultaneous equations, substitution method, elimination method, graphical method, Elvis improved method

Procedia PDF Downloads 102

Authors: A. Dehghani, S. Shirin

Abstract:

We propose in this article a new configuration of quantum states, |α, β> := |α>×|β>. Which are composed of vector products of two different copies of spin coherent states, |α> and |β>. Some mathematical as well as physical properties of such states are discussed. For instance, it has been shown that the cross products of two coherent vectors remain coherent again. They admit a resolution of the identity through positive definite measures on the complex plane. They represent packets similar to the true coherent states, in other words we would not expect to take spin squeezing in any of the field quadratures Lˆx, Lˆy and Lˆz. Depending on the particular choice of parameters in the above scenarios, they can be converted into the so-called Dicke states which minimize the uncertainty relations of each pair of the angular momentum components.

Keywords: vector (Cross-)products, minimum uncertainty, angular momentum, measurement, Dicke states

Procedia PDF Downloads 388

Authors: Amy Gooden, Meshandren Naidoo

Abstract:

Genetic research and transfers of big data are not confined to a particular jurisdiction, but there is a lack of clarity regarding the legal requirements for importing and exporting such data. Using direct-to-consumer genetic testing (DTC-GT) as an example, this research assesses the status of data sharing into and out of South Africa (SA). While SA laws cover the sending of genetic data out of SA, prohibiting such transfer unless a legal ground exists, the position where genetic data comes into the country depends on the laws of the country from where it is sent – making the legal position less clear.

Keywords: cross-border, data, genetic testing, law, regulation, research, sharing, South Africa

Procedia PDF Downloads 110

Authors: Rahal Nacer, Beghdad Houda, Tehami Mohamed, Souici Abdelaziz

Abstract:

Although the shrinkage of the concrete causes undesirable parasitic effects to the structure, it can then harm the resistance and the good appearance of the structure. Long term behaviourmodelling of steel-concrete composite beams requires the use of the time variable and the taking into account of all the sustained stress history of the concrete slab constituting the cross section. The work introduced in this article is a theoretical study of the behaviour of composite beams with respect to the phenomenon of concrete shrinkage. While using the theory of the linear viscoelasticity of the concrete, and on the basis of the rate of creep method, in proposing an analytical model, made up by a system of two linear differential equations, emphasizing the effects caused by shrinkage on the resistance of a steel-concrete composite beams. Results obtained from the application of the suggested model to a steel-concrete composite beam are satisfactory.

Keywords: composite beams, shrinkage, time, rate of creep method, viscoelasticity theory

Procedia PDF Downloads 503

Authors: Zehui Du, Chaiwat Prapainainar, Paisan Kongkachuichay, Paweena Prapainainar

Abstract:

The aim of this work was to obtain small crystalline size and high crystallinity of mordenites and analcimes, by modifying the aging time, agitation, water content, crystallization temperature and crystallization time. Two different hydrothermal methods were studied. Both methods used Na2SiO3 as the silica source, NaAlO2 as the aluminum source, and NaOH as the alkali source. The first method used HMI as the template while the second method did not use the template. Mordenite crystals with spherical shape and bimodal in size of about 1 and 5 µm were obtained from the first method using conditions of 24 hr aging time, 170°C and 24 hr crystallization. Modernites with high crystallinity were formed using agitation system in the crystallization process. It was also found that the aging time of 2 hr and 24 hr did not much affect the formation of mordenite crystals. Analcime crystals were formed in spherical shape and facet on surface with the size between 13-15 µm by the second method using the conditions of 30 minutes aging time, 170°C and 24 hr crystallization without calcination. By increasing water content, the crystallization process was slowed down and resulted in smaller analcime crystals. Larger size of analcime crystals were observed when the samples were calcined at 300°C and 580°C. Higher calcination temperature led to higher crystal growth and resulted in larger crystal size. Finally, mordenite and analcime was used as fillers in zeolite/Nafion composite membrane to solve the fuel cross over problem in direct alcohol fuel cell.

Keywords: analcime, hydrothermal synthesis, mordenite, zeolite

Procedia PDF Downloads 244

Authors: N. J. Nawarathna, N. R. Kmarasinghe, D. Chandrasekara, B. M. R. S. Balasooriya, R. A. A. Shaminda, R. J. K. Senevirathne

Abstract:

Introduction: Thyroid malignancy associated with hyperthyroidism is considered rare. Retrospective studies have shown the incidence of thyroid malignancy in hyperthyroid patients to be low (0.7-8.5%). To assess the clinical relevance of this association, thyroid status in a cohort of patients with thyroid malignancy were analyzed. Method: Thyroid malignancies diagnosed histologically in 56 patients, over a 18 month period beginning from April 2013, in a single surgical unit at Teaching Hospital Kandy were included. Preoperative patient details and progression of thyroid status were asessed with Thyroid Stimulating Hormone, free Thyroxin and free Triiodothyronine levels. Results: Amongst 56 patients Papillary carcinoma was diagnosed in 44(78.6%), follicular carcinomas in 7(12.5%) and 5(8.9%) with medullary and anaplastic carcinomas. 12(21.4%) were males and 44(78.6%) were females. 20(35.7%) were less than 40years, 29(51.8%) were between 40 to 59years and 7(12.5%) were above 59years. Cross tabulation of Type of carcinoma with Gender revealed likelihood ratio of 6.908, Significance p = 0.032. Biochemically 12(21.4%) were hyperthyroid. Out of them 5(41.7%) had primary hyperthyroidism and 7(58.3%) had secondary hyperthyroidism. Mean age of euthyroid patients was 43.77years (SD 10.574) and hyperthyroid patients was 53.25years(SD 16.057). Independent Samples Test t is -2.446, two tailed significance p =0.018. When cross tabulate thyroid status with Age group Likelihood Ratio was 9.640, Significance p = 0.008. Conclusion: Papillary carcinoma is seen more among females. Among the patients with thyroid carcinomas, those with biochemically proven hyperthyroidism were more among the older age group than those who were euthyroid. Hence careful evaluation of elderly hyperthyroid patients to select the most suitable therapeutic approach is justified.

Keywords: age, hyperthyroidism, thyroid malignancy, thyroid status

Procedia PDF Downloads 380

Authors: Adam M. Yates, Julie E. Byles

Abstract:

Hypertension has been identified as a prominent co-morbidity of obesity. To improve clinical intervention of hypertension, it is critical to identify metrics that most accurately reflect risk for increased morbidity. Two of the most relevant and accurate measures for increased risk of hypertension due to excess adipose tissue are Body Mass Index (BMI) and Waist-Height Ratio (WHtR). Previous research has examined these measures in cross-national and cross-ethnic studies, but has most often relied on secondary means such as meta-analysis to identify and evaluate the efficacy of individual body mass measures. In this study, we instead use cross-sectional analysis to assess the cross-ethnic discriminative power of BMI and WHtR to predict risk of hypertension. Using the WHO SAGE survey, which collected anthropometric and biometric data from respondents in six middle-income countries (China, Ghana, India, Mexico, Russia, South Africa), we implement logistic regression to examine the discriminative power of measured BMI and WHtR with a known population of hypertensive and non-hypertensive respondents. We control for gender and age to identify whether optimum cut-off points that are adequately sensitive as tests for risk of hypertension may be different between groups. We report results for OR, RR, and ROC curves for each of the six SAGE countries. As seen in existing literature, results demonstrate that both WHtR and BMI are significant predictors of hypertension (p < .01). For these six countries, we find that cut-off points for WHtR may be dependent upon gender, age and ethnicity. While an optimum omnibus cut-point for WHtR may be 0.55, results also suggest that the gender and age relationship with WHtR may warrant the development of individual cut-offs to optimize health outcomes. Trends through multiple countries show that the optimum cut-point for WHtR increases with age while the area under the curve (AUROC) decreases for both men and women. Comparison between BMI and WHtR indicate that BMI may remain more robust than WHtR. Implications for public health policy are discussed.

Keywords: hypertension, obesity, Waist-Height ratio, SAGE

Procedia PDF Downloads 454

Authors: Mingde Du, Dong Han

Abstract:

A low profile, dual polarized, slot coupled patch antenna is designed and developed in this paper. The antenna has a measured bandwidth of 17.2% for return loss > 15 dB and pair ports isolation >23 dB. The gain of the antenna is over 10 dBi and the half power beam widths (HPBW) of the antenna are 80±3^o in the horizontal plane and 39±2^o in the vertical plane. The cross polarization discrimination (XPD) is less than 20 dB in HPBW. Within the operating band, the performances of good impedance match, high ports isolation, low cross polarization, and stable radiation patterns are achieved.

Keywords: dual polarized, patch antenna, slot coupled, base station antenna

Procedia PDF Downloads 428

Authors: Maria Zinnia Bardas Hoffmann

Abstract:

Contrastive Analysis (CA) is the systematic comparison between two languages. It stems from the notion that errors are caused by interference of the L1 system in the acquisition process of an L2. CA represents a useful tool to understand the nature of learning and acquisition. Also, this particular method promises a path to un-derstand the nature of underlying cognitive processes, even when other factors such as intrinsic motivation and teaching strategies were found to best explain student’s problems in acquisition. CA study is justified not only from the need to get a deeper understanding of the nature of SLA, but as an invaluable source to provide clues, at a cognitive level, for those general processes involved in rule formation and abstract thought. It is relevant for cross disciplinary studies and the fields of Computational Thought, Natural Language processing, Applied Linguistics, Cognitive Linguistics and Math Theory. That being said, this paper intends to address here as well its own set of constraints and limitations. Finally, this paper: (a) aims at identifying some of the difficulties students may find in their learning process due to the nature of their specific variety of L1, Rio de la Plata Spanish (RPS), (b) represents an attempt to discuss the necessity for specific models to approach CA.

Keywords: second language acquisition, applied linguistics, contrastive analysis, applied contrastive analysis English language department, meta-linguistic rules, cross-linguistics studies, computational thought, natural language processing

Procedia PDF Downloads 118

Authors: Rajaian Hoonejani Mohammad, Eshraghi Pegah, Zomorodian Zahra Sadat, Tahsildoost Mohammad

Abstract:

Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

Procedia PDF Downloads 42

Authors: P. M. Keshtiban, M. Zdshakoyan, G. Faragi

Abstract:

Different severe plastic deformation (SPD) methods are the most successful ways to build nano-structural materials from coarse grain samples without changing the cross-sectional area. One of the most widely used methods in the SPD process is equal channel angler pressing (ECAP). In this paper, ECAP process on Al1050 sheets was evaluated at room temperature by both experiments and finite element method. Since, one of the main objectives of SPD processes is to achieve high equivalent plastic strain (PEEQ) in one cycle, the values of PEEQ obtained by finite element simulation. Also, force-displacement curve achieved by FEM. To study the changes of mechanical properties, micro-hardness tests were conducted on samples and improvement in the mechanical properties were investigated. Results show that there is the good proportion between FEM, theory and experimental results.

Keywords: AL1050, experiments, finite element method, severe plastic deformation

Procedia PDF Downloads 391

Authors: Gunasekaran Raja, Ramkumar Jayaraman

Abstract:

In this paper, we consider CCL-N (Cooperative Cross Layer Network) topology based on the cross layer (both centralized and distributed) environment to form network communities. Various performance metrics related to the IEEE 802.16 networks are discussed to design CCL-N Topology. In CCL-N topology, nodes are classified as master nodes (Master Base Station [MBS]) and serving nodes (Relay Station [RS]). Nodes communities are organized based on the networking terminologies. Based on CCL-N Topology, various simulation analyses for both transparent and non-transparent relays are tabulated and throughput efficiency is calculated. Weighted load balancing problem plays a challenging role in IEEE 802.16 network. CoTS (Concurrent Transmission Scheduling) Scheme is formulated in terms of three aspects – transmission mechanism based on identical communities, different communities and identical node communities. CoTS scheme helps in identifying the weighted load balancing problem. Based on the analytical results, modularity value is inversely proportional to that of the error value. The modularity value plays a key role in solving the CoTS problem based on hop count. The transmission mechanism for identical node community has no impact since modularity value is same for all the network groups. In this paper three aspects of communities based on the modularity value which helps in solving the problem of weighted load balancing and CoTS are discussed.

Keywords: cross layer network topology, concurrent scheduling, modularity value, network communities and weighted load balancing

Procedia PDF Downloads 235

Authors: Arezoo Hakimi, Afshin Farahbakhsh

Abstract:

Herein, we comparison synthesized Fe3O4 using, hydrothermal method, Mechanochemical processes and solvent thermal method. The Hydrothermal Technique has been the most popular one, gathering interest from scientists and technologists of different disciplines, particularly in the last fifteen years. In the hydrothermal method Fe3O4 microspheres, in which many nearly monodisperse spherical particles with diameters of about 400nm, in the mechanochemical method regular morphology indicates that the particles are well crystallized and in the solvent thermal method Fe3O4 nanoparticles have good properties of uniform size and good dispersion.

Keywords: Fe3O4 nanoparticles, hydrothermal method, mechanochemical processes, solvent thermal method

Procedia PDF Downloads 334

Authors: Autcha Araveeporn

Abstract:

This paper presents a study about a nonparametric regression model consisting of a smoothing spline method and a penalized spline regression method. We also compare the techniques used for estimation and prediction of nonparametric regression model. We tried both methods with crude oil prices in dollars per barrel and the Stock Exchange of Thailand (SET) index. According to the results, it is concluded that smoothing spline method performs better than that of penalized spline regression method.

Keywords: nonparametric regression model, penalized spline regression method, smoothing spline method, Stock Exchange of Thailand (SET)

Procedia PDF Downloads 410

Authors: V. Lukášová, P. Peukert, V. Votrubec

Abstract:

Thermal conductivity in the x, y and z-directions was measured on a pultruded profile that was manufactured by the technology of pulling from glass fibers and a polyester matrix. The results of measurements of thermal conductivity showed considerable variability in different directions. The caused variability in thermal conductivity was expected due fraction variations. The cross-section of the pultruded profile was scanned. An image analysis illustrated an uneven distribution of the fibers and the matrix in the cross-section. The distribution of these inequalities was processed into a Voronoi diagram in the observed area of the pultruded profile cross-section. In order to verify whether the variation of the fiber volume fraction in the pultruded profile can affect its thermal conductivity, the numerical simulations in the ANSYS Fluent were performed. The simulation was based on the geometry reconstructed from image analysis. The aim is to quantify thermal conductivity numerically. Above all, images with different volume fractions were chosen. The results of the measured thermal conductivity were compared with the calculated thermal conductivity. The evaluated data proved a strong correlation between volume fraction and thermal conductivity of the pultruded profile. Based on presented results, a modification of production technology may be proposed.

Keywords: pultrusion profile, volume fraction, thermal conductivity, numerical simulation

Procedia PDF Downloads 323

Authors: Ravi Sheshala, Annie Lee, Ai Lin Ong, Ling Ling Cheu, Thiagarajan Madheswaran, Thankur R. R. Singh

Abstract:

The objectives of the present research work were to develop and characterize biodegradable controlled release photo cross-linked implants of Triamcinolone Acetonide (TA) for the treatment of chronic ocular diseases. The photo cross-linked implants were prepared using film casting technique by mixing TA (2.5%) polyethylene glycol diacrylate (PEGDA 700), pore formers (mannitol, maltose, and gelatin) and the photoinitiator (Irgacure 2959). The resulting mixture was injected into moulds using 21 G and subjected to photocrosslinking at 365 nm. Scanning electron microscopy results demonstrated that more pores were formed in the films with the increase in the concentration of pore formers from 2%-10%. The maximum force required to break the films containing 2-10% of pore formers were determined in both dry and wet conditions using texture analyzer and found that films in a dry condition required a higher force to break compared to wet condition and blank films. In vitro drug release from photo cross-linked films were determined by incubating samples in 50 ml PBS pH 7.4 at 37 C and the samples were analyzed for drug release by HPLC. The films demonstrated a biphasic release profile i.e. an initial burst release (<20%) on the first day followed by a constant and continuous drug release in a controlled manner for 42 days. The drug release from all formulations followed the first-order release pattern and the combination of diffusion and erosion release mechanism. In conclusion, the developed formulations were able to provide controlled drug delivery to treat the chronic ocular diseases.

Keywords: controlled release, ophthalmic, PEGDA, photocrosslinking, pore formers

Procedia PDF Downloads 383

Authors: Jun Ying Lin, Tzu Hsiang Yen, Cha'o Kuang Chen

Abstract:

Nowadays, the great majority believe that there is great potentiality in hydrogen storage alloy storing hydrogen by physical and chemical absorption. However, the hydrogen storage alloy is limited by high operation temperature. Scientists find that adding transition elements can improve the properties of hydrogen storage alloy. In this research, outstanding improvements of kinetic and thermal properties are given by the addition of Palladium and Titanium hydride to Magnesium-based hydrogen storage alloy. Magnesium-based alloy is the main material, into which TiH2 / Pd are added separately. Following that, materials are milled by a Planetary Ball Miller at 650 rpm. TGA/DSC and PCT measure the capacity, spending time and temperature of abs/des-orption. Additionally, SEM and XRD analyze the structures and components of material. It is clearly shown that Pd is beneficial to kinetic properties. 2MgH2-0.1Pd has the highest capacity of all the alloys listed, approximately 5.5 wt%. Secondly, there are not any new Ti-related compounds found from XRD analysis. Thus, TiH2, considered as the catalyst, leads to the condition of 2MgH2-TiH2 and 2MgH2-TiH2-0.1Pd efficiently absorbing hydrogen in low temperature. 2MgH2-TiH2 can reach roughly 3.0 wt% in 82.4 minutes at 50°C and 8 minutes at 100°C, while2MgH2-TiH2-0.1Pd can reach 2.0 wt% in 400 minutes at 50°C and in 48 minutes at 100°C. The lowest temperature of 2MgH2-0.1Pd and 2MgH2-TiH2 is similar (320°C), otherwise the lowest temperature of 2MgH2-TiH2-0.1Pd decrease by 20°C. From XRD, it can be observed that PdTi2 and Pd3Ti are produced by mechanical alloying when adding Pd as well as TiH2 into MgH2. Due to the synergistic effects between Pd and TiH2, 2MgH2-TiH2-0.1Pd owns the lowest dehydrogenation temperature. Furthermore, the Pressure-Composition-Temperature (PCT) curve of 2MgH2-TiH2-0.1Pd is measured at different temperature, 370°C, 350°C, 320°C and 300°C separately. The plateau pressure is given form the PCT curves above. In accordance to different plateau pressures, enthalpy and entropy in the Van’t Hoff equation can be solved. In 2MgH2-TiH2-0.1Pd, the enthalpy is 74.9 KJ/mol and the entropy is 122.9 J/mol. Activation means that hydrogen storage alloy undergoes repeat abs/des-orpting processes. It plays an important role in the abs/des-orption. Activation shortens the abs/des-orption time because of the increase in surface area. From SEM, it is clear that the grain size and surface become smaller and rougher

Keywords: hydrogen storage materials, magnesium hydride, abs-/des-orption performance, Plateau pressure

Procedia PDF Downloads 237

Authors: Samar Akef, Ahdab M. K. El-Morshedy, Mohamed M. Samy, Ahmed M. Emam

Abstract:

This paper presents a safe and realistic design for the proposed high voltage direct current grounding grid for the converter station at Badr City in Egypt. The outcomes show that the estimated results for touch and step voltages are below the safe limits for humans in monopolar operation and fault conditions. The cross-section area of earthing conductor is computed using IEC TS 62344. The results show that touch voltage in monopolar and fault conditions are 46.6 V and 167.68 V, respectively. The optimum number of required earthing rods is obtained by an analytical method. The step voltages are 12.9 and 43 V in monopolar operation and fault conditions. In addition, this paper presents an experimental case study to verify the simulation work executed using CYMGrd software (finite element method based). The percentage error between the measured and simulated surface potential is below 15.9%.

Keywords: grounding, monopolar, fault conditions, step potential, touch potential, CYMGrd, finite element method, experimental case study

Procedia PDF Downloads 47

Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

Abstract:

Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: artificial immune system, breast cancer diagnosis, Euclidean function, Gaussian function

Procedia PDF Downloads 417

Authors: Xin Zhao

Abstract:

The project aims to expand the notion of narrative learning and address the importance of learning by reflection in our learning and teaching context at a British university. Drawing on the key concepts such as development ZPD, transition and reflection-in and –on-action, this project analyses the learning experiences of a small sample of Chinese postgraduate students in a British University, who use part-time job experience to develop cross-cultural communication skills. The project adopts a mixed methods approach. Questionnaires and focus group interviews are used to examine the way in which students adapt (or not adapt) to the culture of learning in a British university and develop a renewed sense of self in transitions from one culture to the other. The project also looks at how the students appropriate opportunities for learning not just from classrooms but outside classrooms from everyday encounters. The project aims to address the implication of learning by reflection as development in transition. Time in and for learning, or duration, is taken for granted in theorising narrative learning. The project shall explore this very issue of time in relation to learning by reflection in considering time in/of/for learning as duration.

Keywords: cross-cultural competence, learning by refection, international student transition, part-time work experience

Procedia PDF Downloads 166

Authors: Surita Maini, Sanjay Dhanka

Abstract:

Machine learning (ML) involves developing algorithms and statistical models that enable computers to learn and make predictions or decisions based on data without being explicitly programmed. Because of its unlimited abilities ML is gaining popularity in medical sectors; Medical Imaging, Electronic Health Records, Genomic Data Analysis, Wearable Devices, Disease Outbreak Prediction, Disease Diagnosis, etc. In the last few decades, many researchers have tried to diagnose Breast Cancer (BC) using ML, because early detection of any disease can save millions of lives. Working in this direction, the authors have proposed a hybrid ML technique RBF SVM, to predict the BC in earlier the stage. The proposed method is implemented on the Breast Cancer UCI ML dataset with 569 instances and 32 attributes. The authors recorded performance metrics of the proposed model i.e., Accuracy 98.24%, Sensitivity 98.67%, Specificity 97.43%, F1 Score 98.67%, Precision 98.67%, and run time 0.044769 seconds. The proposed method is validated by K-Fold cross-validation.

Keywords: breast cancer, support vector classifier, machine learning, hyper parameter tunning

Procedia PDF Downloads 53

Authors: Eyup Dogan

Abstract:

One criticism of the energy-growth-environment literature, to the best of our knowledge, is that only a few studies analyze the influence of tourism on CO₂ emissions even though tourism sector is closely related to the environment. The other criticism is the selection of methodology. Panel estimation techniques that fail to consider both heterogeneity and cross-sectional dependence across countries can cause forecasting errors. To fulfill the mentioned gaps in the literature, this study analyzes the impacts of real GDP, renewable energy and tourism on the levels of carbon dioxide (CO₂) emissions for the top 10 most-visited countries around the world. This study focuses on the top 10 touristic (most-visited) countries because they receive about the half of the worldwide tourist arrivals in late years and are among the top ones in 'Renewables Energy Country Attractiveness Index (RECAI)'. By looking at Pesaran’s CD test and average growth rates of variables for each country, we detect the presence of cross-sectional dependence and heterogeneity. Hence, this study uses second generation econometric techniques (cross-sectionally augmented Dickey-Fuller (CADF), and cross-sectionally augmented IPS (CIPS) unit root test, the LM bootstrap cointegration test, and the DOLS and the FMOLS estimators) which are robust to the mentioned issues. Therefore, the reported results become accurate and reliable. It is found that renewable energy mitigates the pollution whereas real GDP and tourism contribute to carbon emissions. Thus, regulatory policies are necessary to increase the awareness of sustainable tourism. In addition, the use of renewable energy and the adoption of clean technologies in tourism sector as well as in producing goods and services play significant roles in reducing the levels of emissions.

Keywords: air pollution, tourism, renewable energy, income, panel data

Procedia PDF Downloads 167

Authors: Yaolin Tian, Shanxiong Chen, Fujia Zhao, Xiaoyu Lin, Hailing Xiong

Abstract:

Ancient books are significant culture inheritors and their background textures convey the potential history information. However, multi-style texture recovery of ancient books has received little attention. Restricted by insufficient ancient textures and complex handling process, the generation of ancient textures confronts with new challenges. For instance, training without sufficient data usually brings about overfitting or mode collapse, so some of the outputs are prone to be fake. Recently, image generation and style transfer based on deep learning are widely applied in computer vision. Breakthroughs within the field make it possible to conduct research upon multi-style texture recovery of ancient books. Under the circumstances, we proposed a network of layout analysis and image fusion system. Firstly, we trained models by using Deep Convolution Generative against Networks (DCGAN) to synthesize multi-style ancient textures; then, we analyzed layouts based on the Position Rearrangement (PR) algorithm that we proposed to adjust the layout structure of foreground content; at last, we realized our goal by fusing rearranged foreground texts and generated background. In experiments, diversified samples such as ancient Yi, Jurchen, Seal were selected as our training sets. Then, the performances of different fine-turning models were gradually improved by adjusting DCGAN model in parameters as well as structures. In order to evaluate the results scientifically, cross entropy loss function and Fréchet Inception Distance (FID) are selected to be our assessment criteria. Eventually, we got model M8 with lowest FID score. Compared with DCGAN model proposed by Radford at el., the FID score of M8 improved by 19.26%, enhancing the quality of the synthetic images profoundly.

Keywords: deep learning, image fusion, image generation, layout analysis

Procedia PDF Downloads 131

Authors: Amit Kumar, Amanpreet Chander, Ashish Sahani

Abstract:

This paper presents our recent work on real-time human activity detection based on the media pipe pipeline and machine learning algorithms. The proposed system can detect human activities, including running, jumping, squatting, bending to the left or right, and standing still. This is a robust solution for developing a yoga, dance, metaverse, and fitness application that checks for the correction of the pose without having any additional monitor like a personal trainer. MediaPipe solution offers an open-source cross-platform which utilizes a two-step detector-tracker ML pipeline for live detection of key landmarks on our body which can be used for motion data collection. The prediction of real-time poses uses a variety of machine learning techniques and different types of analysis. Without primarily relying on powerful desktop environments for inference, our method achieves real-time performance on the majority of contemporary mobile phones, desktops/laptops, Python, or even the web. Experimental results show that our method outperforms the existing method in terms of accuracy and real-time capability, achieving an accuracy of 99.92% on testing datasets.

Keywords: human activity detection, media pipe, machine learning, metaverse applications

Procedia PDF Downloads 151