Search results for: fuzzy network project
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9836

Search results for: fuzzy network project

3086 Distribution Urban Public Spaces Among Riyadh Residential Neighborhoods

Authors: Abdulwahab Alalyani, Mahbub Rashid

Abstract:

Urban Open Space (UOS) a central role to promotes community health, including daily activities, but these resources may not available, accessible enough, and or equitably be distributed. This paper measures and compares spatial equity of the availability and accessibility UOS among low, middle, and high-income neighborhoods in Riyadh city. The measurement mothdulgy for the UOSavailability was by calculating the total of UOS with respect to the population total (m2/inhabitant) and the accessibility indicted by using walking distance of a 0.25 mi (0.4 km) buffering streets network.All UOS were mapped and measured using geographical information systems. To evaluate the significant differences in UOS availability and accessibility across low, medium, and high-income Riyadh neighborhoods, we used a One-way ANOVA analysis of covariance to test the differences.The findings are as follows; finding, UOSavailability was lower than global standers. Riyadh has only 1.13 m2 per capita of UOS, and the coverage accessible area by walking distance to UOS was lower than 50%. The final finding, spatial equity of the availability and accessibility, were significantly different among Riyadh neighborhoods based on socioeconomic status. The future development of UOS should be focused on increasing Urban park availability and should be given priority to those low-income and unhealthy communities.

Keywords: distribution urban open space, urban open space accessibility, spatial equity, riyadh city

Procedia PDF Downloads 90
3085 Speech and LanguageTherapists’ Advices for Multilingual Children with Developmental Language Disorders

Authors: Rudinë Fetahaj, Flaka Isufi, Kristina Hansson

Abstract:

While evidence shows that in most European countries’ multilingualism is rising, unfortunately, the focus of Speech and Language Therapy (SLT) is still monolingualism. Furthermore, there is sparse information on how the needs of multilingual children with language disorders such as Developmental Language Disorder (DLD) are being met and which factors affect the intervention approach of SLTs when treating DLD. This study aims to examine the relationship and correlation between the number of languages SLTs speak, years of experience, and length of education with the advice they give to parents of multilingual children with DLD regarding which language to be spoken. This is a cross-sectional study where a survey was completed online by 2608 SLTs across Europe and data has been used from a 2017 COST-action project. IBM-SPSS-28 was used where descriptive analysis, correlation and Kruskal-Wallis test were performed.SLTs mainly advise the parents of multilingual children with DLD to speak their native language at home. Besides years of experience, language status and the level of education showed to have no association with the type of advice SLTs give. Results showed a non-significant moderate positive correlation between SLTs years of experience and their advice regarding the native language, whereas language status and length of education showed no correlation with the advice SLTs give to parents.

Keywords: quantitative study, developmental language disorders, multilingualism, speech and language therapy, children, European context

Procedia PDF Downloads 73
3084 A Smart Monitoring System for Preventing Gas Risks in Indoor

Authors: Gyoutae Park, Geunjun Lyu, Yeonjae Lee, Jaheon Gu, Sanguk Ahn, Hiesik Kim

Abstract:

In this paper, we propose a system for preventing gas risks through the use of wireless communication modules and intelligent gas safety appliances. Our system configuration consists of an automatic extinguishing system, detectors, a wall-pad, and a microcomputer controlled micom gas meter to monitor gas flow and pressure as well as the occurrence of earthquakes. The automatic fire extinguishing system checks for both combustible gaseous leaks and monitors the environmental temperature, while the detector array measures smoke and CO gas concentrations. Depending on detected conditions, the micom gas meter cuts off an inner valve and generates a warning, the automatic fire-extinguishing system cuts off an external valve and sprays extinguishing materials, or the sensors generate signals and take further action when smoke or CO are detected. Information on intelligent measures taken by the gas safety appliances and sensors are transmitted to the wall-pad, which in turn relays this as real time data to a server that can be monitored via an external network (BcN) connection to a web or mobile application for the management of gas safety. To validate this smart-home gas management system, we field-tested its suitability for use in Korean apartments under several scenarios.

Keywords: gas sensor, leak, gas safety, gas meter, gas risk, wireless communication

Procedia PDF Downloads 407
3083 Using SMS Mobile Technology to Assess the Mastery of Subject Content Knowledge of Science and Mathematics Teachers of Secondary Schools in Tanzania

Authors: Joel S. Mtebe, Aron Kondoro, Mussa M. Kissaka, Elia Kibga

Abstract:

Sub-Saharan Africa is described as the second fastest growing mobile phone penetration in the world more than in the United States or the European Union. Mobile phones have been used to provide a lot of opportunities to improve people’s lives in the region such as in banking, marketing, entertainment, and paying various bills such as water, TV, and electricity. However, the potential of using mobile phones to enhance teaching and learning has not been explored. This study presents an experience of developing and delivering SMS quizzes questions that were used to assess mastery of the subject content knowledge of science and mathematics secondary school teachers in Tanzania. The SMS quizzes were used as a follow up support mechanism to 500 teachers who participated in a project to upgrade subject content knowledge of science and mathematics subjects. Quizzes of 10-15 questions were sent to teachers each week for 8 weeks and the results were analyzed using SPSS. The results showed that chemistry and biology had better performance compared to mathematics and physics. Teachers reported some challenges that led to poor performance, invalid answers, and non-responses and they are presented. This research has several practical implications for those who are implementing or planning to use mobile phones for teaching and learning especially in rural secondary schools in sub-Saharan Africa.

Keywords: mobile learning, elearning, educational technolgies, SMS, secondary education, assessment

Procedia PDF Downloads 272
3082 Forecasting 24-Hour Ahead Electricity Load Using Time Series Models

Authors: Ramin Vafadary, Maryam Khanbaghi

Abstract:

Forecasting electricity load is important for various purposes like planning, operation, and control. Forecasts can save operating and maintenance costs, increase the reliability of power supply and delivery systems, and correct decisions for future development. This paper compares various time series methods to forecast 24 hours ahead of electricity load. The methods considered are the Holt-Winters smoothing, SARIMA Modeling, LSTM Network, Fbprophet, and Tensorflow probability. The performance of each method is evaluated by using the forecasting accuracy criteria, namely, the mean absolute error and root mean square error. The National Renewable Energy Laboratory (NREL) residential energy consumption data is used to train the models. The results of this study show that the SARIMA model is superior to the others for 24 hours ahead forecasts. Furthermore, a Bagging technique is used to make the predictions more robust. The obtained results show that by Bagging multiple time-series forecasts, we can improve the robustness of the models for 24 hours ahead of electricity load forecasting.

Keywords: bagging, Fbprophet, Holt-Winters, LSTM, load forecast, SARIMA, TensorFlow probability, time series

Procedia PDF Downloads 86
3081 Optimization in Locating Firefighting Stations Using GIS Data and AHP Model; A Case Study on Arak City

Authors: Hasan Heydari

Abstract:

In recent decades, locating urban services is one of the significant discussions in urban planning. Among these considerations, cities require more accurate planning in order to supply citizen needs, especially part of urban safety. In order to gain this goal, one of the main tasks of urban planners and managers is specifying suitable sites to locate firefighting stations. This study has been done to reach this purpose. Therefore effective criteria consist of coverage radius, population density, proximity to pathway network, land use (compatible and incompatible neighborhood) have been specified. After that, descriptive and local information of the criteria was provided and their layers were created in ArcGIS 9.3. Using Analytic Hierarchy Process (AHP) these criteria and their sub-criteria got the weights. These layers were classified regarding their weights and finally were overlaid by Index Overlay Model and provided the final site selection map for firefighting stations of Arak city. The results gained by analyzing in GIS environment indicate the existing fire station don’t cover the whole city sufficiently and some of the stations have established on the unsuitable sites. The output map indicates the best sites to locate firefighting stations of Arak.

Keywords: site-selection, firefighting stations, analytic hierarchy process (AHP), GIS, index overlay model

Procedia PDF Downloads 340
3080 Prevalence and the Results of the Czech Nationwide Survey and Personality Traits of Adolescence Playing Computer Games

Authors: Jaroslava Sucha, Martin Dolejs, Helena Pipova, Panajotis Cakirpaloglu

Abstract:

The paper introduces the research project which is focused on evaluating the level of pathological relation towards computer or video games playing (including any games played by using a screen such as a mobile or a tablet). The study involves representative sample of the Czech adolescents between ages 11 and 19. This poster presents the psychometric indicators of the new psychologic assessment method (mean, standard deviation, reliability, validity) which will be able to detect an acceptable level of games’ playing and at the same time will detect and describe the level of gaming which might be potentially risky. The prevalence of risky computer game playing at Czech adolescents in age 11 to 19 will be mentioned. The research study also aims to describe the personality profile of the problematic players with respect to the digital games. The research area will encompass risky behaviour, aggression, the level of self-esteem, impulsivity, anxiety and depression. The contribution will introduce a new test method for the assessment of pathological playing computer games. The research will give the first screening information of playing computer games in the Czech Republic by adolescents between 11-19 years. The results clarify what relationship exists between playing computer games and selected personality characteristics (it will describe personality of the gamer, who is in the category of ‘pathological playing computer games’).

Keywords: adolescence, computer games, personality traits, risk behaviour

Procedia PDF Downloads 227
3079 A Quality Improvement Project to Assess the Impact of Orthognathic Surgery on the Quality of Life of Patients: Pre-Operatively versus Post-Operatively

Authors: Fiona Lourenco, William Allen

Abstract:

Dentofacial deformities are primarily surgically treated via orthognathic surgery. Health-related quality of life is concerned with aspects of quality of life that relate specifically to an individual’s health. Design and Setting: Retrospective analysis of patients who had orthognathic surgery from January 2018 - December 2022 at the trust using the previously validated Orthognathic Quality of Life questionnaire (OQoL). Materials and Methods: 32 Patient questionnaires (which included pre-operative and post-operative separate sections) were obtained via telephone survey. The data was analysed using the two-tailed paired t-test and Wilcoxon signed-rank test. Results: The change in perception post-surgery was highly significant (both tests resulted in p<0.001 for overall analysis as well as for each domain). Overall, a 74% improvement in QoL was seen following orthognathic surgery. Reports of improvement in each domain were as follows: 71% in the social aspect of the deformity domain, 76% in facial aesthetics, 60% in function, and 57% improvement in awareness of facial deformity. Conclusion: The assessment of QoL is becoming progressively imperative in clinical research. The above data shows that orthognathic surgery has a significant improvement in the QoL of patients post-operatively. The results demonstrate improvement in all domains, with perceptions in facial aesthetics seeing the highest change post-operatively.

Keywords: dentofacial, oral, facial asymmetry, orthognathic surgery, quality of life

Procedia PDF Downloads 68
3078 A Methodology for Investigating Public Opinion Using Multilevel Text Analysis

Authors: William Xiu Shun Wong, Myungsu Lim, Yoonjin Hyun, Chen Liu, Seongi Choi, Dasom Kim, Kee-Young Kwahk, Namgyu Kim

Abstract:

Recently, many users have begun to frequently share their opinions on diverse issues using various social media. Therefore, numerous governments have attempted to establish or improve national policies according to the public opinions captured from various social media. In this paper, we indicate several limitations of the traditional approaches to analyze public opinion on science and technology and provide an alternative methodology to overcome these limitations. First, we distinguish between the science and technology analysis phase and the social issue analysis phase to reflect the fact that public opinion can be formed only when a certain science and technology is applied to a specific social issue. Next, we successively apply a start list and a stop list to acquire clarified and interesting results. Finally, to identify the most appropriate documents that fit with a given subject, we develop a new logical filter concept that consists of not only mere keywords but also a logical relationship among the keywords. This study then analyzes the possibilities for the practical use of the proposed methodology thorough its application to discover core issues and public opinions from 1,700,886 documents comprising SNS, blogs, news, and discussions.

Keywords: big data, social network analysis, text mining, topic modeling

Procedia PDF Downloads 283
3077 Urban Areas Management in Developing Countries: Analysis of the Urban Areas Crossed with Risk of Storm Water Drains, Aswan-Egypt

Authors: Omar Hamdy, Schichen Zhao, Hussein Abd El-Atty, Ayman Ragab, Muhammad Salem

Abstract:

One of the most risky areas in Aswan is Abouelreesh, which is suffering from flood disasters, as heavy deluge inundates urban areas causing considerable damage to buildings and infrastructure. Moreover, the main problem was the urban sprawl towards this risky area. This paper aims to identify the urban areas located in the risk areas prone to flash floods. Analyzing this phenomenon needs a lot of data to ensure satisfactory results; however, in this case the official data and field data were limited, and therefore, free sources of satellite data were used. This paper used ArcGIS tools to obtain the storm water drains network by analyzing DEM files. Additionally, historical imagery in Google Earth was studied to determine the age of each building. The last step was to overlay the urban area layer and the storm water drains layer to identify the vulnerable areas. The results of this study would be helpful to urban planners and government officials to make the disasters risk estimation and develop primary plans to recover the risky area, especially urban areas located in torrents.

Keywords: risk area, DEM, storm water drains, GIS

Procedia PDF Downloads 448
3076 Surface Roughness of Al-Si/10% AlN MMC Material in Milling Operation Using the Taguchi Method

Authors: M. S. Said, J. A. Ghani, Izzati Osman, Z. A. Latiff, S. A .F. Syed Mohd

Abstract:

Metal matrix composites have demand for light-weight structural and functional materials. MMCs have been shown to offer improvements in strength, rigidity, temperature stability, wear resistance, reliability and control of physical properties such as density and coefficient of thermal expansion, thereby providing improved engineering performance in comparison to the un-reinforced matrix. Experiment were conducted at various cutting speed, feed rate and difference cutting tools according to Taguchi method using a standard orthogonal array L9. The volume of AlN reinforced particle was 10% in MMC. The milling process was carried out under dry cutting condition using uncoated carbide, TiN and TiCN tool insert. The parameters used were the cutting speed of (230,300,370 m/min) the federate used were (0.4, 0.6, 0.8 mm/tooth) while the depth of cut is constant (0.3 mm). The tool diameter is 20mm. From the project, the surface roughness mechanism was investigated in detail using Mitutoyo portable surface roughness measurements surftest SJ-310. This machining will be fabricated on MMC with 150mm length, 100mm width and 30mm thick. The results showed using S/N ratio, concluded that a combination of low cutting speed, medium feed rate and uncoated insert give a remarkable surface finish. From the ANOVA result showed the feed rate was major contributing factor (43.76%) following type of insert (40.89%).

Keywords: MMC, milling operation and surface roughness, Taguchi method

Procedia PDF Downloads 523
3075 Effect of Antioxidants Addition in Combination with Milk Re Pasteurization on the Physical, Chemical and Sensory Properties of Condensed Yoghurt

Authors: Mahmoud Abu-Ghoush, Murad Al Holy

Abstract:

Our main goal in this project is to study the causes and finding solutions for both the hydrolytic and the oxidative rancidity that can be produced during condensed yoghurt production. The re pasteurization of the pasteurized milk and the addition of different types of antioxidants (ascorbic acid and propyl gallate) were used to achieve this goal. Chemical, physical, microbial and sensory tests were done to evaluate the product. It was found that there were significant differences between the different treatments and the control regarding the peroxide value. This means that the addition of both types of antioxidants have a positive effect in decreasing the rancidity value. However, it was found that there were some samples have hydrolytic rancidity flavour without any type of oxidative rancidity (low peroxide value). To overcome this problem the re pasteurization step was used to destroy all the vegetative form of microbes. It was found that this treatment was very useful in controlling the rancidity flavour according to the sensory evaluation of the condensed yoghurt products for several batches. The best condensed yoghurt which contains 0.25% ascorbic acid exhibited the highest sensory properties values. Also, it has the ability in lowering the oxidative rancidity in the combination with the re pasteurization step of the pasteurized milk. This suggests that a higher quality and stable condensed yoghurt can be obtained upon using this combination. These results may help producers in selecting the best treatment methods to overcome the rancidity flavor in this type of condensed yoghurt.

Keywords: antioxidants, condensed yoghurt, repasturization, condensed milk

Procedia PDF Downloads 279
3074 Two-Phase Sampling for Estimating a Finite Population Total in Presence of Missing Values

Authors: Daniel Fundi Murithi

Abstract:

Missing data is a real bane in many surveys. To overcome the problems caused by missing data, partial deletion, and single imputation methods, among others, have been proposed. However, problems such as discarding usable data and inaccuracy in reproducing known population parameters and standard errors are associated with them. For regression and stochastic imputation, it is assumed that there is a variable with complete cases to be used as a predictor in estimating missing values in the other variable, and the relationship between the two variables is linear, which might not be realistic in practice. In this project, we estimate population total in presence of missing values in two-phase sampling. Instead of regression or stochastic models, non-parametric model based regression model is used in imputing missing values. Empirical study showed that nonparametric model-based regression imputation is better in reproducing variance of population total estimate obtained when there were no missing values compared to mean, median, regression, and stochastic imputation methods. Although regression and stochastic imputation were better than nonparametric model-based imputation in reproducing population total estimates obtained when there were no missing values in one of the sample sizes considered, nonparametric model-based imputation may be used when the relationship between outcome and predictor variables is not linear.

Keywords: finite population total, missing data, model-based imputation, two-phase sampling

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3073 Persistent Bacteremia in Cases of Endodontic Re-Treatments

Authors: Ilma Robo, Manola Kelmendi, Kleves Elezi, Nevila Alliu

Abstract:

The most important stage in deciding whether to re-treat or not endodontically is to find the reason for the clinical in-success. Therefore, endodontic re-treatment aims to eliminate the etiology of the pathology, where the main ones are the bacteria remaining in the inter-radicular spaces or the presence of other irritants that can be not only bacterial toxins but also the elements that keep the batteries fixed or extra-canal toxins such as extraction outside the apex of the canal filling. Shortcomings of endodontic treatment can be corrected, if possible, only with endodontic re-treatment that is initially attempted orthograde, and if clinical endodontic success is not achieved again, it can be performed retrograde or surgically. The elements that do not help in this direction are the anatomical deformations in the canal network of the tooth roots, in the presence of the delta at the apex of the tooth root, in the isthmuses present, all of which can be explained by the endodontic canal anatomical morphology. Actually, even if the causative endodontic bacteria remains isolated and without an exit in the healthy periodontal tissues, then this can also be a clinical endodontic success, regardless of the fact that the endodontic isolation occurred only in the exits such as the apex or the accessory canals. Clinical endodontic in-success occurs only when bacterial residues emerge or provide an exit in the healthy periradicular tissues or along the entire length of the canal where the accessory canals exit.

Keywords: endodontic success, E. foecalis, nanoparticles, laser diode, antibacterial, antiseptic

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3072 Production and Characterization of Ce3+: Si2N2O Phosphors for White Light-Emitting Diodes

Authors: Alparslan A. Balta, Hilmi Yurdakul, Orkun Tunckan, Servet Turan, Arife Yurdakul

Abstract:

Si2N2O (Sinoite) is an inorganic-based oxynitride material that reveals promising phosphor candidates for white light-emitting diodes (WLEDs). However, there is now limited knowledge to explain the synthesis of Si2N2O for this purpose. Here, to the best of authors’ knowledge, we report the first time the production of Si2N2O based phosphors by CeO2, SiO2, Si3N4 from main starting powders, and Li2O sintering additive through spark plasma sintering (SPS) route. The processing parameters, e.g., pressure, temperature, and sintering time, were optimized to reach the monophase Si2N2O containing samples. The lattice parameter, crystallite size, and amount of formation phases were characterized in detail by X-ray diffraction (XRD). Grain morphology, particle size, and distribution were analyzed by scanning and transmission electron microscopes (SEM and TEM). Cathodoluminescence (CL) in SEM and photoluminescence (PL) analyses were conducted on the samples to determine the excitation, and emission characteristics of Ce3+ activated Si2N2O. Results showed that the Si2N2O phase in a maximum 90% ratio was obtained by sintering for 15 minutes at 1650oC under 30 MPa pressure. Based on the SEM-CL and PL measurements, Ce3+: Si2N2O phosphor shows a broad emission summit between 400-700 nm that corresponds to white light. The present research was supported by TUBITAK under project number 217M667.

Keywords: cerium, oxynitride, phosphors, sinoite, Si₂N₂O

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3071 The Epidemiology of Hospital Maternal Deaths, Haiti 2017-2020

Authors: Berger Saintius, Edna Ariste, Djeamsly Salomon

Abstract:

Background: Maternal mortality is a preventable global health problem that affects developed, developing, and underdeveloped countries alike. Globally, maternal mortality rates have declined since 1990, but 830 women die every day from pregnancy and childbirth-related causes that are often preventable. Haiti, with a number of 529 maternal deaths per 100,000 live births, is one of the countries with the highest maternal mortality rate in the Caribbean. This study consists of analyzing maternal death surveillance data in Haiti from 2017-2020. Method : A descriptive study was conducted; data were extracted from the National Epidemiological Surveillance Network of maternal deaths from 2017 to 2020. Sociodemographic variables were analyzed. Excel and Epi Info 7.2 were used for data analysis. Frequency and proportion measurements were calculated. Results: 756 deaths were recorded for the study period: 42 (6%) in 2017, 168 (22%) in 2018, 265 (35%) in 2019, and 281 (37%) in 2020. The North Department recorded the highest number of deaths, 167 (22%). 83(11%) in Les Cayes. 96% of these deaths are people aged between 15 and 49. Conclusion. Maternal mortality is a major health problem in Haiti. Mobilization, participation, and involvement of communities, increase in obstetric care coverage and promotion of Family Planning are among the strategies to fight this problem.

Keywords: epidemiology, maternal death, hospital, Haiti

Procedia PDF Downloads 80
3070 NR/PEO Block Copolymer: A Chelating Exchanger for Metal Ions

Authors: M. S. Mrudula, M. R. Gopinathan Nair

Abstract:

In order to utilize the natural rubber for developing new green polymeric materials for specialty applications, we have prepared natural rubber and polyethylene oxide based polymeric networks by two shot method. The polymeric networks thus formed have been used as chelating exchanger for metal ion binding. Chelating exchangers are, in general, coordinating copolymers containing one or more electron donor atoms such as N, S, O, and P that can form coordinate bonds with metals. Hydrogels are water- swollen network of hydrophilic homopolymer or copolymers. They acquire a great interest due to the facility of the incorporation of different chelating groups into the polymeric networks. Such polymeric hydrogels are promising materials in the field of hydrometallurgical applications and water purification due to their chemical stability. The current study discusses the swelling response of the polymeric networks as a function of time, temperature, pH and [NaCl] and sorption studies. Equilibrium swelling has been observed to depend on both structural aspects of the polymers and environmental factors. Metal ion sorption shows that these polymeric networks can be used for removal, separation, and enrichment of metal ions from aqueous solutions and can play an important role for environmental remediation of municipal and industrial wastewater.

Keywords: block copolymer, adsorption, chelating exchanger, swelling study, polymer, metal complexes

Procedia PDF Downloads 333
3069 Numerical Analysis of a Pilot Solar Chimney Power Plant

Authors: Ehsan Gholamalizadeh, Jae Dong Chung

Abstract:

Solar chimney power plant is a feasible solar thermal system which produces electricity from the Sun. The objective of this study is to investigate buoyancy-driven flow and heat transfer through a built pilot solar chimney system called 'Kerman Project'. The system has a chimney with the height and diameter of 60 m and 3 m, respectively, and the average radius of its solar collector is about 20 m, and also its average collector height is about 2 m. A three-dimensional simulation was conducted to analyze the system, using computational fluid dynamics (CFD). In this model, radiative transfer equation was solved using the discrete ordinates (DO) radiation model taking into account a non-gray radiation behavior. In order to modelling solar irradiation from the sun’s rays, the solar ray tracing algorithm was coupled to the computation via a source term in the energy equation. The model was validated with comparing to the experimental data of the Manzanares prototype and also the performance of the built pilot system. Then, based on the numerical simulations, velocity and temperature distributions through the system, the temperature profile of the ground surface and the system performance were presented. The analysis accurately shows the flow and heat transfer characteristics through the pilot system and predicts its performance.

Keywords: buoyancy-driven flow, computational fluid dynamics, heat transfer, renewable energy, solar chimney power plant

Procedia PDF Downloads 249
3068 The Regulation of the Pro-inflammatory Cytokine Interleukin 6 (IL6) by Epstein-Barr Virus (EBV)

Authors: Liu Xiaohan

Abstract:

Epstein–Barr virus (EBV) is a human herpesvirus and is closely related to many malignancies of lymphocyte and epithelial origins, such as gastric cancer, Burkitt’s lymphoma, and nasopharyngeal carcinoma (NPC). NPC is a malignant epithelial tumor which is 100% associated with EBV latent infection. Most of the NPC cases are densely populated in southern China, especially in Guangdong and Hong Kong. To our knowledge, overexpression of pro-inflammatory cytokines may result in a loss of balance of the immune system and cause damage to human bodies. Interleukin-6 (IL6) is a pro-inflammatory cytokine which plays an important role in tumor progression. In addition, gene expression is regulated by both transcriptional and post-transcriptional pathways, while post-transcriptional regulation is an important mechanism to modulate the mature mRNA level in mammalian cells. AU-rich element binding factor 1 (AUF1)/heterogeneous nuclear RNP D (hnRNP D) is known for its function in destabilizing mRNAs, including cytokines and cell cycle regulators. Previous studies have found that overexpression of hnRNP D would lead to tumorigenesis. In this project, our aim is to determine the role played by hnRNP D in EBV-infected cells and how our anti-EBV agents can affect the function of hnRNP D. The results of this study will provide a new insight into how the pro-inflammatory cytokine expression can be regulated by EBV.

Keywords: interleukin 6 (IL6), epstein-barr virus (EBV), nasopharyngeal carcinoma (NPC, epstein-barr nuclear antigen-1 (EBNA1)

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3067 The Impact of Artificial Intelligence on Spare Parts Technology

Authors: Amir Andria Gad Shehata

Abstract:

Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenanceneural network, LSTM, MLP, forecasting demand, inventory management

Procedia PDF Downloads 46
3066 User Selections on Social Network Applications

Authors: C. C. Liang

Abstract:

MSN used to be the most popular application for communicating among social networks, but Facebook chat is now the most popular. Facebook and MSN have similar characteristics, including usefulness, ease-of-use, and a similar function, which is the exchanging of information with friends. Facebook outperforms MSN in both of these areas. However, the adoption of Facebook and abandonment of MSN have occurred for other reasons. Functions can be improved, but users’ willingness to use does not just depend on functionality. Flow status has been established to be crucial to users’ adoption of cyber applications and to affects users’ adoption of software applications. If users experience flow in using software application, they will enjoy using it frequently, and even change their preferred application from an old to this new one. However, no investigation has examined choice behavior related to switching from Facebook to MSN based on a consideration of flow experiences and functions. This investigation discusses the flow experiences and functions of social-networking applications. Flow experience is found to affect perceived ease of use and perceived usefulness; perceived ease of use influences information ex-change with friends, and perceived usefulness; information exchange influences perceived usefulness, but information exchange has no effect on flow experience.

Keywords: consumer behavior, social media, technology acceptance model, flow experience

Procedia PDF Downloads 349
3065 Computer Aided Analysis of Breast Based Diagnostic Problems from Mammograms Using Image Processing and Deep Learning Methods

Authors: Ali Berkan Ural

Abstract:

This paper presents the analysis, evaluation, and pre-diagnosis of early stage breast based diagnostic problems (breast cancer, nodulesorlumps) by Computer Aided Diagnosing (CAD) system from mammogram radiological images. According to the statistics, the time factor is crucial to discover the disease in the patient (especially in women) as possible as early and fast. In the study, a new algorithm is developed using advanced image processing and deep learning method to detect and classify the problem at earlystagewithmoreaccuracy. This system first works with image processing methods (Image acquisition, Noiseremoval, Region Growing Segmentation, Morphological Operations, Breast BorderExtraction, Advanced Segmentation, ObtainingRegion Of Interests (ROIs), etc.) and segments the area of interest of the breast and then analyzes these partly obtained area for cancer detection/lumps in order to diagnosis the disease. After segmentation, with using the Spectrogramimages, 5 different deep learning based methods (specified Convolutional Neural Network (CNN) basedAlexNet, ResNet50, VGG16, DenseNet, Xception) are applied to classify the breast based problems.

Keywords: computer aided diagnosis, breast cancer, region growing, segmentation, deep learning

Procedia PDF Downloads 81
3064 Predictive Analytics in Traffic Flow Management: Integrating Temporal Dynamics and Traffic Characteristics to Estimate Travel Time

Authors: Maria Ezziani, Rabie Zine, Amine Amar, Ilhame Kissani

Abstract:

This paper introduces a predictive model for urban transportation engineering, which is vital for efficient traffic management. Utilizing comprehensive datasets and advanced statistical techniques, the model accurately forecasts travel times by considering temporal variations and traffic dynamics. Machine learning algorithms, including regression trees and neural networks, are employed to capture sequential dependencies. Results indicate significant improvements in predictive accuracy, particularly during peak hours and holidays, with the incorporation of traffic flow and speed variables. Future enhancements may integrate weather conditions and traffic incidents. The model's applications range from adaptive traffic management systems to route optimization algorithms, facilitating congestion reduction and enhancing journey reliability. Overall, this research extends beyond travel time estimation, offering insights into broader transportation planning and policy-making realms, empowering stakeholders to optimize infrastructure utilization and improve network efficiency.

Keywords: predictive analytics, traffic flow, travel time estimation, urban transportation, machine learning, traffic management

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3063 Digital Curriculum Preservation Planning, Actions, and Challenges

Authors: Misook Ahn

Abstract:

This study examined the Digital Curriculum Repository (DCR) project initiated at Defense Language Institute Foreign Language Center (DLIFLC). The purpose of the DCR is to build a centralized curriculum infrastructure, preserve all curriculum materials, and provide academic service to users (faculty, students, or other agencies). The DCR collection includes core language curriculum materials developed by each language school—foreign language textbooks, language survival kits, and audio files currently in or not in use at the schools. All core curriculum materials with audio and video files have been coded, collected, and preserved at the DCR. The DCR website was designed with MS SharePoint for easy accessibility by the DLIFLC’s faculty and students. All metadata for the collected curriculum materials have been input by language, code, year, book type, level, user, version, and current status (in use/not in use). The study documents digital curriculum preservation planning, actions, and challenges, including collecting, coding, collaborating, designing DCR SharePoint, and policymaking. DCR Survey data is also collected and analyzed for this research. Based on the finding, the study concludes that the mandatory policy for the DCR system and collaboration with school leadership are critical elements of a successful repository system. The sample collected items, metadata, and DCR SharePoint site are presented in the evaluation section.

Keywords: MS share point, digital preservation, repository, policy

Procedia PDF Downloads 151
3062 Developing a Web-Based Workflow Management System in Cloud Computing Platforms

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
3061 Seasonal Variability of Aerosol Optical Properties and Their Radiative Effects over Indo-Gangetic Plain in India

Authors: Kanika Taneja, V. K. Soni, S. D. Attri, Kafeel Ahmad, Shamshad Ahmad

Abstract:

Aerosols represent an important component of earth-atmosphere system and have a profound impact on the global and regional climate. With the growing population and urbanization, the aerosol load in the atmosphere over the Indian region is found to be increasing. Several studies have reported that the aerosol optical depth over the northern part of India is higher as compared to the southern part. The northern India along the Indo-Gangetic plain is often influenced with dust transported from the Thar Desert in northwestern India and from Arabian Peninsula during the pre-monsoon season. Seasonal variations in aerosol optical and radiative properties were examined using data retrieved from ground based multi-wavelength Prede Sun/sky radiometer (POM-02) over Delhi, Rohtak, Jodhpur and Varanasi for the period April 2011-April 2013. These stations are part of the Skynet-India network of India Meteorological Department. The Sun/sky radiometer (POM-02) has advantage over other instruments that it can be calibrated on-site. These aerosol optical properties retrieved from skyradiometer observations are further used to analyze the Direct Aerosol Radiative Forcing (DARF) over the study locations.

Keywords: aerosol optical properties, indo- gangetic plain, radiative forcing, sky radiometer

Procedia PDF Downloads 538
3060 The Influence of Ligands Molecular Structure on the Antibacterial Activity of Some Metal Complexes

Authors: Sanja O. Podunavac-Kuzmanović, Lidija R. Jevrić, Strahinja Z. Kovačević

Abstract:

In last decade, metal-organic complexes have captured intensive attention because of their wide range of biological activities such as antibacterial, antifungal, anticancerous, antimicrobial and antiHIV. Therefore, it is of great importance for the development of coordination chemistry to explore the assembly of functional organic ligands with metal ion and to investigate the relationship between the structure and property. In view of our studies, we reasoned that benzimidazoles complexed to metal ions could act as a potent antibacterial agents. Thus, we have bioassayed the inhibitory potency of benzimidazoles and their metal salts (Co or Ni) against Gram negative bacteria Escherichia coli. In order to validate our in vitro study, we performed in silico studies using molecular docking software’s. The investigated compounds and their metal complexes (Co, Ni) showed good antibacterial activity against Escherichia coli. In silico docking studies of the synthesized compounds suggested that complexed benzimidazoles have a greater binding affinity and enhanced antibacterial activity in comparison with noncomplexed ligands. In view of their enhanced inhibitory properties we propose that the studied complexes can be used as potential pharmaceuticals. This study is financially supported by COST action CM1306 and the project No. 114-451-347/2015-02, financially supported by the Provincial Secretariat for Science and Technological Development of Vojvodina.

Keywords: benzimidazoles, complexes, antibacterial, Escherichia coli, metal

Procedia PDF Downloads 307
3059 Power Quality Improvement Using UPQC Integrated with Distributed Generation Network

Authors: B. Gopal, Pannala Krishna Murthy, G. N. Sreenivas

Abstract:

The increasing demand of electric power is giving an emphasis on the need for the maximum utilization of renewable energy sources. On the other hand maintaining power quality to satisfaction of utility is an essential requirement. In this paper the design aspects of a Unified Power Quality Conditioner integrated with photovoltaic system in a distributed generation is presented. The proposed system consist of series inverter, shunt inverter are connected back to back on the dc side and share a common dc-link capacitor with Distributed Generation through a boost converter. The primary task of UPQC is to minimize grid voltage and load current disturbances along with reactive and harmonic power compensation. In addition to primary tasks of UPQC, other functionalities such as compensation of voltage interruption and active power transfer to the load and grid in both islanding and interconnected mode have been addressed. The simulation model is design in MATLAB/ Simulation environment and the results are in good agreement with the published work.

Keywords: distributed generation (DG), interconnected mode, islanding mode, maximum power point tracking (mppt), power quality (PQ), unified power quality conditioner (UPQC), photovoltaic array (PV)

Procedia PDF Downloads 497
3058 Seismic Hazard Prediction Using Seismic Bumps: Artificial Neural Network Technique

Authors: Belkacem Selma, Boumediene Selma, Tourkia Guerzou, Abbes Labdelli

Abstract:

Natural disasters have occurred and will continue to cause human and material damage. Therefore, the idea of "preventing" natural disasters will never be possible. However, their prediction is possible with the advancement of technology. Even if natural disasters are effectively inevitable, their consequences may be partly controlled. The rapid growth and progress of artificial intelligence (AI) had a major impact on the prediction of natural disasters and risk assessment which are necessary for effective disaster reduction. The Earthquakes prediction to prevent the loss of human lives and even property damage is an important factor; that is why it is crucial to develop techniques for predicting this natural disaster. This present study aims to analyze the ability of artificial neural networks (ANNs) to predict earthquakes that occur in a given area. The used data describe the problem of high energy (higher than 10^4J) seismic bumps forecasting in a coal mine using two long walls as an example. For this purpose, seismic bumps data obtained from mines has been analyzed. The results obtained show that the ANN with high accuracy was able to predict earthquake parameters; the classification accuracy through neural networks is more than 94%, and that the models developed are efficient and robust and depend only weakly on the initial database.

Keywords: earthquake prediction, ANN, seismic bumps

Procedia PDF Downloads 118
3057 Extraction of Road Edge Lines from High-Resolution Remote Sensing Images Based on Energy Function and Snake Model

Authors: Zuoji Huang, Haiming Qian, Chunlin Wang, Jinyan Sun, Nan Xu

Abstract:

In this paper, the strategy to extract double road edge lines from acquired road stripe image was explored. The workflow is as follows: the road stripes are acquired by probabilistic boosting tree algorithm and morphological algorithm immediately, and road centerlines are detected by thinning algorithm, so the initial road edge lines can be acquired along the road centerlines. Then we refine the results with big variation of local curvature of centerlines. Specifically, the energy function of edge line is constructed by gradient feature and spectral information, and Dijkstra algorithm is used to optimize the initial road edge lines. The Snake model is constructed to solve the fracture problem of intersection, and the discrete dynamic programming algorithm is used to solve the model. After that, we could get the final road network. Experiment results show that the strategy proposed in this paper can be used to extract the continuous and smooth road edge lines from high-resolution remote sensing images with an accuracy of 88% in our study area.

Keywords: road edge lines extraction, energy function, intersection fracture, Snake model

Procedia PDF Downloads 331