Search results for: “User acceptance of computer technology:A comparison of two theoretical models ”

Authors: Abdulqader Almasabe, Stephanie Ludi, Mohammed Alenazi

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Governments around the world have been increasingly introducing e-government services in order to make processes more efficient and accessible for their citizens. The government of Saudi Arabia has adopted E-Government for the effective delivery of services. However, the adoption rate of these services remains low in many countries. This paper aims to explore the determinants of citizens' intention to adopt and use e-government services, focusing on a model of factors influencing the adoption and utilization of e-government services (MFIAUEGS) that has been specially developed for this purpose. By analyzing the factors that influence citizens' decisions to use e-government services we hope to provide insights that help to increase adoption rates and improve the overall effectiveness of these services. In this paper, 562 valid responses were collected and analyzed to shed light on the issue. The results of the research showed that each of the proposed factors in the MFIAUEGS model played a significant role in influencing citizens' intentions to adopt and use e-government services.

Keywords: e-government, model acceptance, influencing factors, TAM

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Authors: Tripta Dixit, Smita Sahu, William Selvamurthy, Sadhana Srivastava

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The translation of healthcare technologies is an expensive, complex affair, current healthcare challenges in Asian countries and their efforts to meet Millennium Development Goals (MDGs), necessitates continuous technology advancement to save countless lives, improve the quality of life and for socio-economic development. India’s consistently improving global innovation index (57) demonstrates its innovation potential, but access to health care is asymmetric and lacks priority in India. Therefore, there is utmost need of a robust translation system for point-of-care (POC) solutions, inexpensive, low-maintenance, reliable, and easy-to-use diagnostic technologies. Few cases of POC technologies viz. Elisa based diagnostic kits for regional viral disease, a device for detection of cancerous lesions were studied to understand the process and challenges involved in their translation. Accordingly, the entire translation ecosystem was summarized proposing a nexus of various actors such as technology developer, technology transferor technology receiver, funding entities, government/regulatory bodies and their effect on translation of different medical technologies. This study highlights the role and concerns pertaining to these actors for POC such as unsystematic and unvalidated research roadmap, low profit preposition, unfocused approach of up-scaling, low market acceptability and multiple window regulatory framework, etc. This provides an opportunity to devise solutions to overcome problem areas in translation path.

Keywords: healthcare technologies, point-of-care solutions, public health, translation

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Authors: Chen-Yin Kuo, Yung-Hsin Lee

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Previous studies applying residual income valuation (RIV) model generally use panel data and single-equation model to forecast stock prices. Unlike these, this paper uses Taiwan longitudinal data to estimate multi-equation time-series models such as Vector Autoregressive (VAR), Vector Error Correction Model (VECM), and conduct out-of-sample forecasting. Further, this work assesses their forecasting performance by two instruments. In favor of extant research, the major finding shows that VECM outperforms other three models in forecasting for three stock sectors over entire horizons. It implies that an error correction term containing long-run information contributes to improve forecasting accuracy. Moreover, the pattern of composite shows that at longer horizon, VECM produces the greater reduction in errors, and performs substantially better than VAR.

Keywords: residual income valuation model, vector error correction model, out of sample forecasting, forecasting accuracy

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Authors: Talal Al-Bazali

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Air drilling has recently received increasing acceptance by the oil and gas industry due to its unique advantages. The main advantages of air drilling include the higher rate of penetration, less formation damage, lower risk of loss of circulation. However, these advantages cannot be fully realized if thermal effects in air drilling are not well understood and minimized. Due to its high frictional coefficient, low heat conductivity, and high compressibility, air can impact the temperature distribution of bit and thus affect its bit performances. Based on energy and mass balances, a transient thermal model that predicts bit temperature is presented along with numerical solutions in this paper. In addition, several important parameters that influence bit temperature distribution are analyzed. Simulation results show that the bit temperature increases with increasing weight on bit and rotary speed but decreases as the standpipe pressure and flow rate increase. These results can be used to optimize drilling operations and flow parameters for an improved bit performance as shown in this paper.

Keywords: air drilling, rate of penetration, temperature, rotary speed

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Authors: Sourabh Jain, Parul Madan

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Traffic noise pollution has become a challenging problem for all metro cities of India due to rapid urbanization, growing population and rising number of vehicles and transport development. In Delhi the prime source of noise pollution is vehicular traffic. In Delhi it is found that the ambient noise level (Leq) is exceeding the standard permissible value at all the locations. Noise barriers or enclosures are definitely useful in obtaining effective deduction of traffic noise disturbances in urbanized areas. US’s Federal Highway Administration Model (FHWA) and Calculation of Road Traffic Noise (CORTN) of UK are used to develop spread sheets for noise prediction. Spread sheets are also developed for evaluating effectiveness of existing boundary walls abutting houses in mitigating noise, redesigning them as noise barriers. Study was also carried out to examine the changes in noise level due to designed noise barrier by using both models FHWA and CORTN respectively. During the collection of various data it is found that receivers are located far away from road at Rithala and Moolchand sites and hence extra barrier height needed to meet prescribed limits was less as seen from calculations and most of the noise diminishes by propagation effect.On the basis of overall study and data analysis, it is concluded that FHWA and CORTN models under estimate noise levels. FHWA model predicted noise levels with an average percentage error of -7.33 and CORTN predicted with an average percentage error of -8.5. It was observed that at all sites noise levels at receivers were exceeding the standard limit of 55 dB. It was seen from calculations that existing walls are reducing noise levels. Average noise reduction due to walls at Rithala was 7.41 dB and at Panchsheel was 7.20 dB and lower amount of noise reduction was observed at Friend colony which was only 5.88. It was observed from analysis that Friends colony sites need much greater height of barrier. This was because of residential buildings abutting the road. At friends colony great amount of traffic was observed since it is national highway. At this site diminishing of noise due to propagation effect was very less.As FHWA and CORTN models were developed in excel programme, it eliminates laborious calculations of noise. There was no reflection correction in FHWA models as like in CORTN model.

Keywords: IFHWA, CORTN, Noise Sources, Noise Barriers

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Authors: Lubna Azmi, Ila Shukla, Shyam Sundar Gupta, Padam Kant, C. V. Rao

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Elvitegravir is the mainstay of anti-HIV combination therapy in most endemic countries presently. However, it cannot be used alone owing to its long onset time of action. 2-(3,4-dihydroxyphenyl)-3,5,7-trihydroxychromen-4-one (Quercetin: QU) is a polyphenolic compound obtained from Argeria speciosa Linn (Family: Convolvulaceae), an anti-HIV candidate. In the present study, a sensitive, simple and rapid high-performance liquid chromatography coupled with positive ion electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) method was developed for the simultaneous determination elvitegravir and Quercetin, in rat plasma. The method was linear over a range of 0.2–500 ng/ml. All validation parameters met the acceptance criteria according to regulatory guidelines. LC–MS/MS method for determination of Elvitegravir and Quercetin was developed and validated. Results show the potential of drug–drug interaction upon co-administration this marketed drugs and plant derived secondary metabolite.

Keywords: anti-HIV resistance, extraction, HPLC-ESI-MS-MS, validation

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Authors: Miho Tsukamoto

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Since the initial creation of the Barbie doll in 1959, it became a symbol of US society. Likewise, the Licca-chan, a Japanese doll created in 1967, also became a Japanese symbolic doll of Japanese society. Prior to the introduction of Licca-chan, Barbie was already marketed in Japan but their sales were dismal. Licca-chan (an actual name: Kayama Licca) is a plastic doll with a variety of sizes ranging from 21.0 cm to 29.0 cm which many Japanese girls dream of having. For over 35 years, the manufacturer, Takara Co., Ltd. has sold over 48 million dolls and has produced doll houses, accessories, clothes, and Licca-chan video games for the Nintendo DS. Many First-generation Licca-chan consumers still are enamored with Licca-chan, and go to Licca-chan House, in an amusement park with their daughters. These people are called Licca-chan maniacs, as they enjoy touring the Licca-chan’s factory in Tohoku or purchase various Licca-chan accessories. After the successful launch of Licca-chan into the Japanese market, a mixed-like doll from the US and Japan, a doll, JeNny, was later sold in the same Japanese market by Takara Co., Ltd. in 1982. Comparison of these cultural iconic dolls, Barbie and Licca-chan, are analyzed in this paper. In fact, these dolls have concepts of girls’ dreams. By using concepts of mythology of Jean Baudrillard, these dolls can be represented idealized images of figures in the products for consumers, but at the same time, consumers can see products with different perspectives, which can cause controversy.

Keywords: Barbie, dolls, JeNny, idealization, Licca-chan

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Authors: Eva Nedeliakova, Juraj Camaj, Jaroslav Masek

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This contribution is focused on the methodology for identifying levels of quality and improving quality through new logistics model in railway transport. It is oriented on the application of dynamic quality models, which represent an innovative method of evaluation quality services. Through this conception, time factor, expected, and perceived quality in each moment of the transportation process within logistics chain can be taken into account. Various models describe the improvement of the quality which emphases the time factor throughout the whole transportation logistics chain. Quality of services in railway transport can be determined by the existing level of service quality, by detecting the causes of dissatisfaction employees but also customers, to uncover strengths and weaknesses. This new logistics model is able to recognize critical processes in logistic chain. It includes service quality rating that must respect its specific properties, which are unrepeatability, impalpability, their use right at the time they are provided and particularly changeability, which is significant factor in the conditions of rail transport as well. These peculiarities influence the quality of service regarding the constantly increasing requirements and that result in new ways of finding progressive attitudes towards the service quality rating.

Keywords: logistics model, quality, railway transport

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Authors: Edgar Teixeira, Eurico Carrapatoso

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As 3D displays become increasingly affordable, while production techniques and computational resources to create stereoscopic content being ever more accessible, a new dimension is literally introduced along with new expressive and immersive potentialities in support of designing for the screen. Prospective design visionaries have already at the reach of their hands an innovative and powerful visualization technology, which enables them to actively envision future trends and vanguardist directions. This paper explores the aesthetic and informational potentialities of stereoscopic motion graphics, providing insight on the application of 3D displays in design practice, proposing strategies to investigate stereoscopic communication, discussing potential repercussions to extant theory and impacts on audience.

Keywords: design, visual communication, technology, stereoscopy, 3D media

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Authors: Raúl Bajo-Buenestado

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This paper studies the impact of the intensity of market competition on firms' willingness to adopt green technologies —which has become particularly relevant in the light of the debate on whether competition policies should be relaxed to achieve certain environmental targets. We exploit the staggered rollout of different rail-hailing platforms (most notably, Uber) across different metropolitan areas in Spain as a natural experiment that provides time and city-specific exogenous variation in the intensity of competition to study the impact on taxi drivers' decisions to purchase “green” or “dirty” vehicles. It was shown that the entry of these platforms significantly increased the takeout of green vehicles among professional drivers in incumbent (dominant) conventional taxi companies and decreased that of dirty vehicles. The exact opposite effect is observed in the cities where these platforms were extremely unlikely to enter. Back of the envelope calculations suggest that the entry of Uber is associated with an extra green vehicle purchase in every four among taxi drivers, resulting in a substantial drop in the level of emissions from the taxi fleet —still mostly dominated diesel vehicles.

Keywords: technological change, green technology adoption, market competition, diffusion of technology, environmental externalities

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Authors: Francesca Risplendi, Li-Chiang Lin, Jeffrey C. Grossman, Giancarlo Cicero

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Desalination is one of the most employed approaches to supply water in the context of a rapidly growing global water shortage. However, the most popular water filtration method available is the reverse osmosis (RO) technique, still suffers from important drawbacks, such as a large energy demands and high process costs. In addition some serious limitations have been recently discovered, among them, the boron problem seems to have a critical meaning. Boron has been found to have a dual effect on the living systems on Earth and the difference between boron deficiency and boron toxicity levels is quite small. The aim of this project is to develop a new generation of RO membranes based on porous graphene or reduced graphene oxide (rGO) able to remove salts from seawater and to reduce boron concentrations in the permeate to the level that meets the drinking or process water requirements, by means of a theoretical approach based on density functional theory and classical molecular dynamics. Computer simulations have been employed to investigate the relationship between the atomic structure of nanoporous graphene or rGO monolayer and its membrane properties in RO applications (i.e. water permeability and resilience at RO pressures). In addition, an emphasis has been given to multilayer nanoporous rGO and rGO flakes based membranes. By means of non-equilibrium MD simulations, we investigated the water transport mechanism permeating through such multilayer membrane focusing on the effect of slit widths and sheet geometries. These simulations allowed us to establish the implications of these graphene based materials as promising membrane properties for desalination plants and as boron filtration.

Keywords: boron filtration, desalination, graphene membrane, reduced graphene oxide membrane

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Authors: Maryam Zarabian, Hector Guzman, Pedro Pereira-Almao, Abraham Fapojuwo

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Dry reforming of methane (DRM) has sparked significant industrial and scientific interest not only as a viable alternative for addressing the environmental concerns of two main contributors of the greenhouse effect, i.e., carbon dioxide (CO₂) and methane (CH₄), but also produces syngas, i.e., a mixture of hydrogen (H₂) and carbon monoxide (CO) utilized by a wide range of downstream processes as a feedstock for other chemical productions. In this study, we develop an AI-enable syngas production model to tackle the problem of achieving an equivalent H₂/CO ratio [1:1] with respect to the most efficient conversion. Firstly, the unsupervised density-based spatial clustering of applications with noise (DBSAN) algorithm removes outlier data points from the original experimental dataset. Then, random forest (RF) and deep neural network (DNN) models employ the error-free dataset to predict the DRM results. DNN models inherently would not be able to obtain accurate predictions without a huge dataset. To cope with this limitation, we employ reusing pre-trained layers’ approaches such as transfer learning and greedy layer-wise pretraining. Compared to the other deep models (i.e., pure deep model and transferred deep model), the greedy layer-wise pre-trained deep model provides the most accurate prediction as well as similar accuracy to the RF model with R² values 1.00, 0.999, 0.999, 0.999, 0.999, and 0.999 for the total outlet flow, H₂/CO ratio, H₂ yield, CO yield, CH₄ conversion, and CO₂ conversion outputs, respectively.

Keywords: artificial intelligence, dry reforming of methane, artificial neural network, deep learning, machine learning, transfer learning, greedy layer-wise pretraining

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Authors: Michael Moeti, Khuliso Sigama, Thapelo Samuel Matlala

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One of the principal challenges that the world is confronted with is insecurity. The crime rate is increasing exponentially, and protecting our physical assets especially in the motorist industry, is becoming impossible when applying our own strength. The need to develop technological solutions that detect and report theft without any human interference is inevitable. This is critical, especially for vehicle owners, to ensure theft detection and speedy identification towards recovery efforts in cases where a vehicle is missing or attempted theft is taking place. The vehicle theft detection system uses Convolutional Neural Network (CNN) to recognize the driver's face captured using an installed mobile phone device. The location identification function uses a Global Positioning System (GPS) to determine the real-time location of the vehicle. Upon identification of the location, Global System for Mobile Communications (GSM) technology is used to report or notify the vehicle owner about the whereabouts of the vehicle. The installed mobile app was implemented by making use of python as it is undoubtedly the best choice in machine learning. It allows easy access to machine learning algorithms through its widely developed library ecosystem. The graphical user interface was developed by making use of JAVA as it is better suited for mobile development. Google's online database (Firebase) was used as a means of storage for the application. The system integration test was performed using a simple percentage analysis. Sixty (60) vehicle owners participated in this study as a sample, and questionnaires were used in order to establish the acceptability of the system developed. The result indicates the efficiency of the proposed system, and consequently, the paper proposes the use of the system can effectively monitor the vehicle at any given place, even if it is driven outside its normal jurisdiction. More so, the system can be used as a database to detect, locate and report missing vehicles to different security agencies.

Keywords: CNN, location identification, tracking, GPS, GSM

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Authors: Giorgio Bertolazzi, Panayiotis Benos, Michele Tumminello, Claudia Coronnello

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MicroRNAs are small non-coding RNAs that post-transcriptionally regulate the expression levels of messenger RNAs. MicroRNA regulation activity depends on the recognition of binding sites located on mRNA molecules. ComiR (Combinatorial miRNA targeting) is a user friendly web tool realized to predict the targets of a set of microRNAs, starting from their expression profile. ComiR incorporates miRNA expression in a thermodynamic binding model, and it associates each gene with the probability of being a target of a set of miRNAs. ComiR algorithms were trained with the information regarding binding sites in the 3’UTR region, by using a reliable dataset containing the targets of endogenously expressed microRNA in D. melanogaster S2 cells. This dataset was obtained by comparing the results from two different experimental approaches, i.e., inhibition, and immunoprecipitation of the AGO1 protein; this protein is a component of the microRNA induced silencing complex. In this work, we tested whether including coding region binding sites in the ComiR algorithm improves the performance of the tool in predicting microRNA targets. We focused the analysis on the D. melanogaster species and updated the ComiR underlying database with the currently available releases of mRNA and microRNA sequences. As a result, we find that the ComiR algorithm trained with the information related to the coding regions is more efficient in predicting the microRNA targets, with respect to the algorithm trained with 3’utr information. On the other hand, we show that 3’utr based predictions can be seen as complementary to the coding region based predictions, which suggests that both predictions, from 3'UTR and coding regions, should be considered in a comprehensive analysis. Furthermore, we observed that the lists of targets obtained by analyzing data from one experimental approach only, that is, inhibition or immunoprecipitation of AGO1, are not reliable enough to test the performance of our microRNA target prediction algorithm. Further analysis will be conducted to investigate the effectiveness of the tool with data from other species, provided that validated datasets, as obtained from the comparison of RISC proteins inhibition and immunoprecipitation experiments, will be available for the same samples. Finally, we propose to upgrade the existing ComiR web-tool by including the coding region based trained model, available together with the 3’UTR based one.

Keywords: AGO1, coding region, Drosophila melanogaster, microRNA target prediction

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Authors: Kim H. K. Choy, Oliva H. K. Chu, W. Y. Keung, B. Lim, Winnie P. Y. Tang

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Background: Health care providers have been identified as an at-risk group for obesity. Mobile health technology can be used to motivate lifestyle behavioral changes. The aim of this study was to investigate hospital-based health care providers’ perceptions of mHealth Workplace Nutrition Wellness Program. Methods: This qualitative study was conducted at a regional hospital in Hong Kong. Ten health care providers were purposively selected for the study. Qualitative data was collected by individual face-to-face semi-structured interviews which were audio-taped, transcribed verbatim and analyzed by thematic analysis. Results: Four themes were identified: (1) mobile health technology motivates lifestyle changes, (2) self-perceived body weight initiates health behavioral changes, (3) organizational support promotes healthy behavior, (4) lack of self-confidence hinders lifestyle modification. The health care providers’ perceptions of mobile health technology, barriers, and facilitators to participation in the mHealth Workplace Nutrition Wellness Program were discussed in the study. Conclusions: Barriers, facilitators, self-perceived body weight and experiences of mobile health technology were associated with intention of participation in mHealth Workplace Nutrition Wellness Program. The knowledge generated from the study could be used to guide the design and implementation of effective interventions, strategies and policies of workplace wellness programs to promote participation for hospital’s employees.

Keywords: workplace wellness program, mobile health, barriers, facilitators, qualitative

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Authors: Arjun, Gautam, Sanjeev Naval

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Concrete technology has been changing rapidly and constantly since its discovery. Concrete is the most widely used man-made construction material, versatility of making concrete is the 2nd largest consumed material on earth. In this paper an effort has been made to use metal aggregates in concrete has been discussed, the metal aggregates has been named as “BAUT” which had outstandingly qualities to resist shear, tension and compression forces. In this paper, COARSE BAUT AGGREGATES (C.B.A.) 10mm & 20mm and FINE BAUT AGGREGATES (F.B.A.) 3mm were divided and used for making high performance concrete (H.P.C). This “BAUT” had cutting edge technology through draft and design by the use of Auto CAD, ANSYS software can be used effectively In this research paper we study high performance concrete (H.P.C) with “BAUT” and consider the grade of M65 and finally we achieved the result of 90-95 Mpa (high compressive strength) for mega structures and irregular structures where center of gravity (CG) is not balanced. High Performance BAUT Concrete is the extraordinary qualities like long-term performance, no sorptivity by BAUT AGGREGATES, better rheological, mechanical and durability proportion that conventional concrete. This high strength BAUT concrete using “BAUT” is applied in the construction of mega structure like skyscrapers, dam, marine/offshore structures, nuclear power plants, bridges, blats and impact resistance structures. High Performance BAUT Concrete which is a controlled concrete possesses invariable high strength, reasonable workability and negligibly permeability as compare to conventional concrete by the mix of Super Plasticizers (SMF), silica fume and fly ash.

Keywords: BAUT, High Strength Concrete, High Performance Concrete, Fine BAUT Aggregate, Coarse BAUT Aggregate, metal aggregates, cutting edge technology

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Authors: Hanan K. Hassanein

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Task-based language teaching (TBLT) and focus on form instruction (FFI) methods were proven to improve quality and quantity of immediate language production. However, studies that compare between the effectiveness of the language production when using TBLT versus FFI are very little with results that are not consistent. Moreover, teaching Arabic using TBLT is a new field with few research that has investigated its application inside classrooms. Furthermore, to the best knowledge of the researcher, there are no prior studies that compared teaching Arabic as a foreign language in a classroom setting using computer-assisted task-based language teaching (CATBLT) with computer-assisted form focused language instruction (CAFFI). Accordingly, the focus of this presentation is to display CATBLT and CAFFI tools when teaching Arabic as a foreign language as well as demonstrate an experimental study that aims to identify whether or not CATBLT is a more effective instruction method. The effectiveness will be determined through comparing CATBLT and CAFFI in terms of accuracy, lexical complexity, and fluency of language produced by students. The participants of the study are 20 students enrolled in two intermediate-level Arabic as a foreign language classes. The experiment will take place over the course of 7 days. Based on a study conducted by Abdurrahman Arslanyilmaz for teaching Turkish as a second language, an in-house computer assisted tool for the TBLT and another one for FFI will be designed for the experiment. The experimental group will be instructed using the in-house CATBLT tool and the control group will be taught through the in-house CAFFI tool. The data that will be analyzed are the dialogues produced by students in both the experimental and control groups when completing a task or communicating in conversational activities. The dialogues of both groups will be analyzed to understand the effect of the type of instruction (CATBLT or CAFFI) on accuracy, lexical complexity, and fluency. Thus, the study aims to demonstrate whether or not there is an instruction method that positively affects the language produced by students learning Arabic as a foreign language more than the other.

Keywords: computer assisted language teaching, foreign language teaching, form-focused instruction, task based language teaching

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Authors: Bruno Biagianti, Angela Tseng, Kathy Wannaviroj, Allison Corlett, Megan DuBois, Kyu Lee, Suma Jacob

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Background: ASD is characterized by pervasive Sensory Processing Abnormalities (SPA) and social cognitive deficits that persist throughout the course of the illness and have been linked to functional abnormalities in specific neural systems that underlie the perception, processing, and representation of sensory information. SPA and social cognitive deficits are associated with difficulties in interpersonal relationships, poor development of social skills, reduced social interactions and lower academic performance. Importantly, they can hamper the effects of established evidence-based psychological treatments—including PEERS (Program for the Education and Enrichment of Relationship Skills), a parent/caregiver-assisted, 16-weeks social skills intervention—which nonetheless requires a functional brain capable of assimilating and retaining information and skills. As a matter of fact, some adolescents benefit from PEERS more than others, calling for strategies to increase treatment response rates. Objective: We will present interim data on CICADAS (Care Improving Cognition for ADolescents on the Autism Spectrum)—a clinician-assisted, closed-loop technology mobile application for adolescents with ASD. Via ten mobile assessments, CICADAS captures data on sensory processing abnormalities and associated cognitive deficits. These data populate a machine learning algorithm that tailors the delivery of ten neuroplasticity-based social cognitive training (NB-SCT) exercises targeting sensory processing abnormalities. Methods: In collaboration with the Autism Spectrum and Neurodevelopmental Disorders Clinic at the University of Minnesota, we conducted a fully remote, three-arm, randomized crossover trial with adolescents with ASD to document the acceptability of CICADAS and evaluate its potential as a stand-alone treatment or as a treatment enhancer of PEERS. Twenty-four adolescents with ASD (ages 11-18) have been initially randomized to 16 weeks of PEERS + CICADAS (Arm A) vs. 16 weeks of PEERS + computer games vs. 16 weeks of CICADAS alone (Arm C). After 16 weeks, the full battery of assessments has been remotely administered. Results: We have evaluated the acceptability of CICADAS by examining adherence rates, engagement patterns, and exit survey data. We found that: 1) CICADAS is able to serve as a treatment enhancer for PEERS, inducing greater improvements in sensory processing, cognition, symptom reduction, social skills and behaviors, as well as the quality of life compared to computer games; 2) the concurrent delivery of PEERS and CICADAS induces greater improvements in study outcomes compared to CICADAS only. Conclusion: While preliminary, our results indicate that the individualized assessment and treatment approach designed in CICADAS seems effective in inducing adaptive long-term learning about social-emotional events. CICADAS-induced enhancement of processing and cognition facilitates the application of PEERS skills in the environment of adolescents with ASD, thus improving their real-world functioning.

Keywords: ASD, social skills, cognitive training, mobile app

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Authors: Dhawal Ladani

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Shell and tube type heat exchangers are predominantly used in heat exchange between two fluids and other applications. This paper projects the optimal design of the pipe used in the heat exchanger in such a way to minimize the vibration occurring in the pipe. Paper also consists of the comparison of the different design of the pipe to get the maximize the heat transfer rate by converting laminar flow into the turbulent flow. By the updated design the vibration in the pipe due to the flow is also decreased. Computational Fluid Dynamics and Thermal Heat Transfer analysis are done to justifying the result. Currently, the straight pipe is used in the shell and tube type of heat exchanger where as per the paper the pipe consists of the curvature along with the pipe. Hence, the heat transfer area is also increased and result in the increasing in heat transfer rate. Curvature type design is useful to create turbulence and minimizing the vibration, also. The result will give the output comparison of the effect of laminar flow and the turbulent flow in the heat exchange mechanism, as well as, inverse effect of the boundary layer in heat exchanger is also justified.

Keywords: heat exchanger, heat transfer rate, laminar and turbulent effect, shell and tube

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Authors: Sergey Svita, Valeriy Astapenko

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The presentation is devoted to the theoretical analysis of ultrashort electromagnetic pulses (USP) scattering on metallic nanospheres in a dielectric medium in the vicinity of surface plasmon resonance due to excitation of dipole and quadrupole surface plasmons.

Keywords: surface plasmon, scattering, metallic nanosphere

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Authors: A. Kebbeb, M. Mostefai, F. Benmerzoug, Y. Chahir

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The multimodal biometric identification is the combination of several biometric systems. The challenge of this combination is to reduce some limitations of systems based on a single modality while significantly improving performance. In this paper, we propose a new approach to the construction and the protection of a multimodal biometric database dedicated to an identification system. We use a topological watermarking to hide the relation between face image and the registered descriptors extracted from other modalities of the same person for more secure user identification.

Keywords: biometric databases, multimodal biometrics, security authentication, digital watermarking

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Authors: Masood Otarod, Ronald M. Supkowski

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This abstract discusses a method that reduces the general dispersion model in cylindrical coordinates to a second order linear ordinary differential equation with constant coefficients so that it can be utilized to conduct kinetic studies in packed bed tubular catalytic reactors at a broad range of Reynolds numbers. The model was tested by 13CO isotope transient tracing of the CO adsorption of Boudouard reaction in a differential reactor at an average Reynolds number of 0.2 over Pd-Al2O3 catalyst. Detailed experimental results have provided evidence for the validity of the theoretical framing of the model and the estimated parameters are consistent with the literature. The solution of the general dispersion model requires the knowledge of the radial distribution of axial velocity. This is not always known. Hence, up until now, the implementation of the dispersion model has been largely restricted to the plug-flow regime. But, ideal plug-flow is impossible to achieve and flow regimes approximating plug-flow leave much room for debate as to the validity of the results. The reduction of the general dispersion model transpires as a result of the application of a factorization theorem. Factorization theorem is derived from the observation that a cross section of a catalytic bed consists of a solid phase across which the reaction takes place and a void or porous phase across which no significant measure of reaction occurs. The disparity in flow and the heterogeneity of the catalytic bed cause the concentration of reacting compounds to fluctuate radially. These variabilities signify the existence of radial positions at which the radial gradient of concentration is zero. Succinctly, factorization theorem states that a concentration function of axial and radial coordinates in a catalytic bed is factorable as the product of the mean radial cup-mixing function and a contingent dimensionless function. The concentration of adsorbed compounds are also factorable since they are piecewise continuous functions and suffer the same variability but in the reverse order of the concentration of mobile phase compounds. Factorability is a property of packed beds which transforms the general dispersion model to an equation in terms of the measurable mean radial cup-mixing concentration of the mobile phase compounds and mean cross-sectional concentration of adsorbed species. The reduced model does not require the knowledge of the radial distribution of the axial velocity. Instead, it is characterized by new transport parameters so denoted by Ωc, Ωa, Ωc, and which are respectively denominated convection coefficient cofactor, axial dispersion coefficient cofactor, and radial dispersion coefficient cofactor. These cofactors adjust the dispersion equation as compensation for the unavailability of the radial distribution of the axial velocity. Together with the rest of the kinetic parameters they can be determined from experimental data via an optimization procedure. Our data showed that the estimated parameters Ωc, Ωa Ωr, are monotonically correlated with the Reynolds number. This is expected to be the case based on the theoretical construct of the model. Computer generated simulations of methanation reaction on nickel provide additional support for the utility of the newly conceptualized dispersion model.

Keywords: factorization, general dispersion model, isotope transient kinetic, partial differential equations

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Authors: Sunil Kumar Singal, Manoj Sood, Upendra Bajpai

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Instream technology is the upcoming sustainable approach in the hydro sector for energy harnessing. With well-known cross-sections and regulated supply, open channels are the most prominent locations for the installation of hydrokinetic turbines. The fluctuation in generated torque varies with site condition (flow depth and flow velocity), as well as with the type of turbine. The present experimental study aims to investigate the torque/power fluctuations of crossflow hydrokinetic turbines operating at different flow velocities and water depths. The flow velocity is varied from 1.0 m/s to 2.0 m/s. The complete assembly includes an open channel having dimensions of 0.3 m (depth) x 0.71 m (width) x 4.5 m (length), along with a lifting mechanism for varying the channel slope, a digital transducer for monitoring the torque, power, and rpm, a digital handheld water velocity meter for measuring the flow velocity. Further, a time series of torque, power, and rpm is plotted for a duration of 30 minutes showing the continuous operation of the turbine. A comparison of Savonius, Darrieus, and their improved twisted and helical blades is also presented in the study. A correlation has also been developed for assessing the hydropower generation from the installed turbine. The developed correlations will be very useful in the decision-making process for development at a site.

Keywords: darrieus turbine, flow velocity, open channel, savoinus turbine, water depth, hydropower

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Authors: Emanuel Koseos

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Data-Driven Decision Making (DDDM) refers to making decisions that are based on historical data in order to inform practice, develop strategies and implement policies that benefit organizational settings. In educational technology, DDDM facilitates the implementation of differential educational learning approaches such as Educational Data Mining (EDM) and Competency-Based Education (CBE), which commonly target university classrooms. There is a current need for DDDM models applied to middle and secondary schools from a concern for assessing the needs, progress and performance of students and educators with respect to regional standards, policies and evolution of curriculums. To address these concerns, we propose a DDDM reference model developed using educational key process initiatives as inputs to a machine learning framework implemented with statistical software (SAS, R) to provide a best-practices, complex-free and automated approach for educators at their regional level. We assessed the efficiency of the model over a six-year period using data from 45 schools and grades K-12 in the Langley, BC, Canada regional school district. We concluded that the model has wider appeal, such as business learning systems.

Keywords: competency-based learning, data-driven decision making, machine learning, secondary schools

Procedia PDF Downloads 160

Authors: Khaled Alshamari

Abstract:

Synthesized partially phosphorylated polyvinyl phosphate derivative (PPVP) was functionalized to extract Zirconium (IV) from Egyptian zircon sand. The specifications for the PPVP composite were approved effectively via different techniques, namely, FT-IR, XPS, BET, EDX, TGA, HNMR, C-NMR, GC-MS, XRD and ICP-OES analyses, which demonstrated a satisfactory synthesis of PPVP and zircon dissolution from Egyptian zircon sand. Factors controlling parameters, such as pH values, shaking time, initial zirconium concentration, PPVP dose, nitrate ions concentration, co-ions, temperature and eluting agents, have been optimized. At 25 ◦C, pH 0, 20 min shaking, 0.05 mol/L zirconium ions and 0.5 mol/L nitrate ions, PPVP has an exciting preservation potential of 195 mg/g, equivalent to 390 mg/L zirconium ions. From the extraction–distribution isotherm, the practical outcomes of Langmuir’s modeling are better than the Freundlich model, with a theoretical value of 196.07 mg/g, which is more in line with the experimental results of 195 mg/g. The zirconium ions adsorption onto the PPVP composite follows the pseudo-second-order kinetics with a theoretical capacity value of 204.08 mg/g. According to thermodynamic potential, the extraction process was expected to be an exothermic, spontaneous and beneficial extraction at low temperatures. The thermodynamic parameters ∆S (−0.03 kJ/mol), ∆H (−12.22 kJ/mol) and ∆G were also considered. As the temperature grows, ∆G values increase from −2.948 kJ/mol at 298 K to −1.941 kJ/mol at 338 K. Zirconium ions may be eluted from the working loaded PPVP by 0.025M HNO₃, with a 99% efficiency rate. It was found that zirconium ions revealed good separation factors towards some co-ions such as Hf⁴+ (28.82), Fe³+ (10.64), Ti⁴+ (28.82), V⁵+ (86.46) and U⁶+ (68.17). A successful alkali fusion technique with NaOH flux followed by the extraction with PPVP is used to obtain a high-purity zirconia concentrate with a zircon content of 72.77 % and a purity of 98.29%. As a result of this, the improved factors could finally be used.

Keywords: zirconium extraction, partially phosphorylated polyvinyl phosphate (PPVP), acidic medium, zircon

Procedia PDF Downloads 46

Authors: W. Sriwattanapongse, S. Prasitwattanaseree, S. Wongtrangan

Abstract:

The transportation accidents mortality is a major problem that leads to loss of human lives, and economic. The objective was to identify patterns of statistical modeling for estimating mortality rates due to transportation accidents in Thailand by using data from 2000 to 2009. The data was taken from the death certificate, vital registration database. The number of deaths and mortality rates were computed classifying by gender, age, year and region. There were 114,790 cases of transportation accidents deaths. The highest average age-specific transport accident mortality rate is 3.11 per 100,000 per year in males, Southern region and the lowest average age-specific transport accident mortality rate is 1.79 per 100,000 per year in females, North-East region. Linear, poisson and negative binomial models were chosen for fitting statistical model. Among the models fitted, the best was chosen based on the analysis of deviance and AIC. The negative binomial model was clearly appropriate fitted.

Keywords: transportation accidents, mortality, modeling, analysis of deviance

Procedia PDF Downloads 232

Authors: M. Ezzat, Y. Zaghloul, T. Sorour, A. Hefny, M. Eid

Abstract:

Ultimate capacity of large diameter bored piles is usually determined from pile loading tests as recommended by several international codes and foundation design standards. However, loading of this type of piles till achieving apparent failure is practically seldom. In this paper, numerical analyses are carried out to simulate load test of a large diameter bored pile performed at the location of Alzey highway bridge project (Germany). Test results of pile load settlement relationship till failure as well as results of the base and shaft resistances are available. Apparent failure was indicated in this test by the significant increase of the induced settlement during the last load increment applied on the pile head. Measurements of this pile load test are used to assess the quality of the numerical models investigated. Three different material soil models are implemented in the analyses: Mohr coulomb (MC), Soft soil (SS), and Modified Mohr coulomb (MMC). Very good agreement is obtained between the field measured settlement and the calculated settlement using the MMC model. Results of analysis showed also that the MMC constitutive model is superior to MC, and SS models in predicting the ultimate base and shaft resistances of the large diameter bored pile. After calibrating the numerical model, behavior of large diameter bored piles under axial loads is discussed and the formation of the plastic zone around the pile is explored. Results obtained showed that the plastic zone below the base of the pile at failure extended laterally to about four times the pile diameter and vertically to about three times the pile diameter.

Keywords: ultimate capacity, large diameter bored piles, plastic zone, failure, pile load test

Procedia PDF Downloads 135

Authors: Janusz Bobulski, Kamila Pasternak

Abstract:

Despite many years of effort and research, the problem of waste management is still current. So far, no fully effective waste management system has been developed. Many programs and projects improve statistics on the percentage of waste recycled every year. In these efforts, it is worth using modern Computer Vision techniques supported by artificial intelligence. In the article, we present a method of identifying plastic waste based on the asymmetry analysis of the histogram of the image containing the waste. The method is simple but effective (94%), which allows it to be implemented on devices with low computing power, in particular on microcomputers. Such de-vices will be used both at home and in waste sorting plants.

Keywords: waste management, environmental protection, image processing, computer vision

Procedia PDF Downloads 103

Authors: Jinhee Kang, Kwangman Park, Ruhee Song, Suhee Kim, Do-Hyeon Yu, Kyoungseong Choi, Jinho Park

Abstract:

Statement of the Problem: Animal blood components maintain homeostasis when animals are healthy, and changes in chemical composition of the blood and body fluids can be observed if animals have a disease. In particular, newborn calves are susceptible to disease and therefore hematologic tests and serum chemistry tests could become an important guideline to the diagnosis and the treatment of diseases. Diarrhea in newborn calves is the most damaging to cattle ranch, whether dairy or cattle fattening, and is a large part of calf atrophy and death. However, since the study on calf electrophoresis was not carried out, a survey analysis was conducted on it. Methodology and Theoretical Orientation: The calves were divided into healthy calves and disease (diarrhea) calves, and calves were classified by 1-14d, 15-28d, and more than 28d, respectively. The fecal state was classified by solid (0-value), semi-solid (1-value), loose (2-value) and watery (3-value). In the solid (0-value) and semi-solid (1-value) feces valuable pathogen was not detected, but loose (2-value) and watery (3-value) feces were detected. Findings: ALB, α-1, α-2, α-SUM, β and γ (Gamma) were examined by electrophoresis analysis of healthy calves and diarrhea calves. Test results showed that there were age differences between healthy calves and diarrheic calves. When we look at the γ-globulin at 1-14 days of age, we can see that the average calf of healthy calves is 16.8% and the average of diarrheal calves is 7.7%, when we look at the figures for the α-2 at 1-14 days, we found that healthy calves average 5.2% and diarrheal calves 8.7% higher than healthy cows. On α-1, 15-28 days, and after 28 days, healthy calves average 10.4% and diarrheal calves average 7.5% diarrhea calves were 12.6% and 12.4% higher than healthy calves. In the α-SUM, the healthy calves were 21.6%, 16.8%, and 14.5%, respectively, after 1-14 days, 15-28 days and 28 days. diarrheal calves were 23.1%, 19.5%, and 19.8%. Conclusion and Significance: In this study, we examined the electrophoresis results of healthy calves and diseased (diarrhea) calves, gamma globulin at 1-14 days of age were lower than those of healthy calves (diarrhea), indicating that the calf was unable to consume colostrum from the mother when it was a new calf. α-1, α-2, α-SUM may be associated with an acute inflammatory response as a result of increased levels of calves with diarrhea (diarrhea). Further research is needed to investigate the effects of acute inflammatory responses on additional calf-forming proteins. Information on the results of the electrophoresis test will be provided where necessary according to the item.

Keywords: alpha, electrophoretogram, serum protein, γ, gamma

Procedia PDF Downloads 127

Authors: Nadjib Melkemi, Salah Belaidi

Abstract:

Quantitative Structure-Activity Relationship (QSAR) studies have been performed on nineteen molecules of 1,2-dithiole-3-thione analogues. The compounds used are the potent inducers of enzymes involved in the maintenance of reduced glutathione pools as well as phase-2 enzymes important to electrophile detoxication. A multiple linear regression (MLR) procedure was used to design the relationships between molecular descriptor and detoxication properties of the 1,2-dithiole-3-thione derivatives. The predictivity of the model was estimated by cross-validation with the leave-one-out method. Our results suggest a QSAR model based of the following descriptors: qS2, qC3, qC5, qS6, DM, Pol, log P, MV, SAG, HE and EHOMO for the specific activity of quinone reductase; qS1, qS2, qC3, qC4, qC5, qS6, DM, Pol, logP, MV, SAG, HE and EHOMO for the production of growth hormone. To confirm the predictive power of the models, an external set of molecules was used. High correlation between experimental and predicted activity values was observed, indicating the validation and the good quality of the derived QSAR models.

Keywords: QSAR, quinone reductase activity, production of growth hormone, MLR

Procedia PDF Downloads 338