Search results for: location based games

Authors: Ibrahim Ilker Ozyigit, Ertugrul Filiz, Ilhan Dogan

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An in silico analysis of Brachypodium distachyon, Triticum aestivum, Festuca arundinacea, Lolium perenne, Hordeum vulgare subsp. vulgare of the Pooideaea was performed based on complete chloroplast genomes including rbcL coding and trnH-psbA intergenic spacer regions alone to compare phylogenetic resolving power. Neighbor-joining, Minimum Evolution, and Unweighted Pair Group Method with arithmetic mean methods were used to reconstruct phylogenies with the highest bootstrap supported the obtained data from whole chloroplast genome sequence. The highest and lowest values from nucleotide diversity (π) analysis were found to be 0.315813 and 0.043495 in rbcL coding region in chloroplast genome and complete chloroplast genome, respectively. The highest transition/transversion bias (R) value was recorded as 1.384 in complete chloroplast genomes. F. arudinacea-L. perenne clade was uncovered in all phylogenies. Sequences of rbcL and trnH-psbA regions were not able to resolve the Pooideae phylogenies due to lack of genetic variation.

Keywords: chloroplast DNA, Pooideae, phylogenetic analysis, rbcL, trnH-psbA

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Authors: Jinan Fiaidhi, Sabah Mohammed

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Diagnosing cataract severity is an important factor in deciding to undertake surgery. It is usually conducted by an ophthalmologist or through taking a variety of fundus photography that needs to be examined by the ophthalmologist. This paper carries out an investigation using a Siamese neural net that can be trained with small anchor samples to score cataract severity. The model used in this paper is based on a triplet loss function that takes the ophthalmologist best experience in rating positive and negative anchors to a specific cataract scaling system. This approach that takes the heuristics of the ophthalmologist is generally called the thick data approach, which is a kind of machine learning approach that learn from a few shots. Clinical Relevance: The lens of the eye is mostly made up of water and proteins. A cataract occurs when these proteins at the eye lens start to clump together and block lights causing impair vision. This research aims at employing thick data machine learning techniques to rate the severity of the cataract using Siamese neural network.

Keywords: thick data analytics, siamese neural network, triplet-loss model, few shot learning

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Authors: Simon Bullem, Ukkpata Mathias Oko

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The trust of this study will investigate the psychological indices and sporting performance among elite athletes in football in 32 teams in the south-south region, of Nigeria. To achieve the aim of the study, five research questions and five hypotheses shall be tested at a 0.05 level of significance that will guide the study. Literature shall be reviewed in line with the sub-independent variables of sporting psychological indices and the dependent variables of elite athlete achievement reactions towards the psychological indices. The ex.post facto survey designed shall be adapted for the study. The population of the study shall be 768 elite athletes from 32 clubs across the south-south region in Nigeria. A sample of 300 elite athletes shall be sampled using a simple random and stratified sampling technique. The questionnaire titled Psychological Indices and Sporting Performance among Elite Athletes in Football (PISPAEAF) will be the mean instrument for data collection. The research question shall be analyzed using the main and standard deviation statistics while the hypotheses shall use the person product moment correlation analysis at 0.5 level of significance finding for implications in sporting psychological indices and elite athletes' performance, which will emanate from the study. Based on the findings, recommendations shall be made.

Keywords: psychological indices, performance, elite athletes, sports, football

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Authors: Shivani Saini

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The effect of vertical throughflow on the onset of convection in Rivlin-Ericksen Elastico-Viscous nanofluid with convective boundary condition is investigated. The flow is stimulated with modified Darcy model under the assumption that the nanoparticle volume fraction is not actively managed on the boundaries. The heat conservation equation is formulated by introducing the convective term of nanoparticle flux. A linear stability analysis based upon normal mode is performed, and an approximate solution of eigenvalue problems is obtained using the Galerkin weighted residual method. Investigation of the dependence of the Rayleigh number on various viscous and nanofluid parameter is performed. It is found that through flow and nanofluid parameters hasten the convection while capacity ratio, kinematics viscoelasticity, and Vadasz number do not govern the stationary convection. Using the convective component of nanoparticle flux, critical wave number is the function of nanofluid parameters as well as the throughflow parameter. The obtained solution provides important physical insight into the behavior of this model.

Keywords: Darcy model, nanofluid, porous layer, throughflow

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Authors: Samir K. Safi

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The purpose of this study was to compare the performance of two types of models, namely MIDAS and MIDAS-GARCH, in predicting the volatility of crude oil returns based on gold price returns and the COVID-19 pandemic. The study aimed to identify which model would provide more accurate short-term and long-term predictions and which model would perform better in handling the increased volatility caused by the pandemic. The findings of the study revealed that the MIDAS model performed better in predicting short-term and long-term volatility before the pandemic, while the MIDAS-GARCH model performed significantly better in handling the increased volatility caused by the pandemic. The study highlights the importance of selecting appropriate models to handle the complexities of real-world data and shows that the choice of model can significantly impact the accuracy of predictions. The practical implications of model selection and exploring potential methodological adjustments for future research will be highlighted and discussed.

Keywords: GARCH-MIDAS, MIDAS, crude oil, gold, COVID-19, volatility

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Authors: Rizka Ardhiyana, Liesbetini Haditjaroko, Sri Mulijani, Reki Ashadi Wicaksono, Raafqi Ranasasmita

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Designing a sensitive, specific and easy to use method to detect pork contamination in the food industry remains a major challenge. In the current study, we developed a sensitive thiol-bond AuNP-Probe biosensor that will change color when detecting pork DNA in the Cytochrome B region. The interaction between the biosensors and DNA sample is measured by spectrophotometer at 540 nm. The biosensor is made by reducing gold with trisodium citrate to produce gold nanoparticle with 39.05 nm diameter. The AuNP-Probe biosensor (gold nanoprobe) achieved 16.04 ng DNA/µl limit of detection and 53.48 ng DNA/µl limit of quantification. The linearity (R2) between color absorbance changes and DNA concentration is 0.9916. The biosensor has a good specificty as it does not cross-react with DNA of chicken and beef. To verify specificity towards the target sequence, PCR was tested to the target sequence and reacted to the PCR product with the biosensor. The PCR DNA isolate resulted in a 2.7 fold higher absorbance compared to pork-DNA isolate alone (without PCR). The sensitivity and specificity of the method show the promising application of the thiol-bond AuNP biosensor in pork-detection.

Keywords: biosensor, DNA probe, gold nanoparticle (AuNP), pork meat, qPCR

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Authors: M. Pomianek, M. Piszczek, M. Maciejewski

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The binocular eye tracking technology is increasingly being used in industry, entertainment and marketing analysis. In the case of virtual reality, eye tracking systems are already the basis for user interaction with the environment. In such systems, the high accuracy of determining the user's eye fixation point is very important due to the specificity of the virtual reality head-mounted display (HMD). Often, however, there are unknown errors occurring in the used eye tracking technology, as well as those resulting from the positioning of the devices in relation to the user's eyes. However, can the virtual environment itself influence estimation errors? The paper presents mathematical analyses and empirical studies of the determination of the fixation point and errors resulting from the change in the size of the pupil in response to the intensity of the displayed scene. The article contains both static laboratory tests as well as on the real user. Based on the research results, optimization solutions were proposed that would reduce the errors of gaze estimation errors. Studies show that errors in estimating the fixation point of vision can be minimized both by improving the pupil positioning algorithm in the video image and by using more precise methods to calibrate the eye tracking system in three-dimensional space.

Keywords: eye tracking, fixation point, pupil size, virtual reality

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Authors: Arash Khosravi, Mohamad Nazir Ahmad

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Today’s economy is a knowledge-based economy in which knowledge is a crucial facilitator to individuals, as well as being an instigator of success. Due to the impact of globalization, universities face new challenges and opportunities. Accordingly, they ought to be more innovative and have their own competitive advantages. One of the most important goals of universities is the promotion of students as professional knowledge workers. Therefore, knowledge sharing and transferring at tertiary level between students and supervisors is vital in universities, as it decreases the budget and provides an affordable way of doing research. Knowledge-sharing impact factors can be categorized into three groups, namely: organizational, individual and technical factors. There are some individual barriers to knowledge sharing, namely: lack of time and trust, lack of communication skills and social networks. IT systems such as e-learning, blogs and portals can increase knowledge sharing capability. However, it must be stated that IT systems are only tools and not solutions. Individuals are still responsible for sharing information and knowledge. This paper proposes new research model to examine the effect of individual factors and organisational factors, namely: learning strategy, trust culture, supervisory support, as well as technological factor on knowledge sharing in a research supervision process at the University of Technology Malaysia.

Keywords: knowledge management, knowledge sharing, research supervision, knowledge transferring

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Authors: Himanshi Allahabadi

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Plants have found a widespread use in medicine traditionally, including the treatment of cognitive disorders, especially, neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease. In terms of indigenous medicine, it has been found that many potential drugs can be isolated from plant products, including those for dementia. Plant product is widely distributed in plant kingdom and forms a major antioxidant source in the human diet, is Polyphenols. There are four important groups of polyphenols: phenolic acids, flavonoids, stilbenes, and lignans. Due to their high antioxidant capacity, interest in their study has greatly increased. There are several methods for discovering and characterizing active compounds isolated from plant sources, now available. The results obtained so far seem fulfilling, but additionally, mechanism of functioning of polyphenols at the molecular level, as well as their application in human health need to be researched upon. Also, even though the neuroprotective effects of flavonoids have been much talked about, much of the data in support of this statement has come from animal studies rather than human studies. This review is based on a multi-faceted study of medicinal plants, i.e. phytochemicals, with special focus on flavanones and their relevance in remedy of Parkinson's disease.

Keywords: dementia, parkinson's disease, flavanones, polyphenols, substantia nigra

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Authors: Maman Ali M. Moustapha, Qian Yu, Benjamin Adjei Danquah

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This paper investigates the dynamic interaction between renewable energy consumption (REC) and economic growth using dataset from the Economic Community of West African States (ECOWAS) from 2002 to 2016. For this study the Autoregressive Distributed Lag- Bounds test approach (ARDL) was used to examine the long run relationship between real gross domestic product and REC, while VECM based on Granger causality has been used to examine the direction of Granger causality. Our empirical findings indicate that REC has significant and positive impact on real gross domestic product. In addition, we found that REC and the percentage of access to electricity had unidirectional Granger causality to economic growth while carbon dioxide emission has bidirectional Granger causality to economic growth. Our findings indicate also that 1 per cent increase in the REC leads to an increase in Real GDP by 0.009 in long run. Thus, REC can be a means to ensure sustainable economic growth in the ECOWAS sub-region. However, it is necessary to increase further support and investments on renewable energy production in order to speed up sustainable economic development throughout the region

Keywords: Economic Growth, Renewable Energy, Sustainable Development, Sustainable Energy

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Authors: Diana Katherine Gonzalez Galindo, David Rolando Suarez Mora

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With this study, we used data mining as a new alternative of the solution to evaluate the comments of the customers in order to find a pattern that helps us to determine some behaviors to reduce the deactivation of the partners of the LEVEL app. In one of the greatest business created in the last times, the partners are being affected due to an internal process that compensates the customer for a bad experience, but these comments could be false towards the driver, that’s why we made an investigation to collect information to restructure this process, many partners have been disassociated due to this internal process and many of them refuse the comments given by the customer. The main methodology used in this case study is the observation, we recollect information in real time what gave us the opportunity to see the most common issues to get the most accurate solution. With this new process helped by data mining, we could get a prediction based on the behaviors of the customer and some basic data recollected such as the age, the gender, and others; this could help us in future to improve another process. This investigation gives more opportunities to the partner to keep his account active even if the customer writes a message through the app. The term is trying to avoid a recession of drivers in the future offering improving in the processes, at the same time we are in search of stablishing a strategy which benefits both the app’s managers and the associated driver.

Keywords: agent, driver, deactivation, rider

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Authors: Enyia James Diwa, Isaiah Thank-God Ebi, Dodeye Ina Igbong

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The privatization of utilities has brought about very strong competition in industries such as petrochemical and gas distribution among others, considering the continuous increase in cost of fuel. This has brought about the intense reason for gas turbine owners and operators to reduce and control performance degradation of the engine in other to minimize cost. The most common and very crucial problem of the gas turbine is the fouling of compressor, which is mostly caused by a reduction in flow capacity, compressor efficiency, and pressure ratio, this, in turn, lead to the engine compressor re-matching and output power and thermal efficiency reduction. The content of this paper encompasses a detailed presentation of the major causes, effects and control mechanism of fouling. The major emphasis is on compressor water washing to enable power augmentation. A modelled gas turbine similar to that of GE LM6000 is modelled for the current study, based on TURBOMATCH which is a Cranfield University software specifically made for gas turbine performance simulation and fouling detection. The compounded and intricate challenges of compressor online water washing of large output gas turbine are carried out. The treatment is applied to axial compressor used in the petrochemical and hydrocarbon industry.

Keywords: gas turbine, fouling, degradation, compressor washing

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Authors: Sanat Kumar, Rahul Kumar Tiwari

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At this time when society is becoming increasingly aware of the declining reserves of fossil, it has become apparent that biodiesel is destined to make a substantial contribution to the future energy demands of the domestic and industrial economies. In this regard, the significance of biodiesel is technically and commercially viable alternative to fossil-diesel. There are different potential feed stocks for biodiesel production. This paper analyses the performance, combustion and emission characteristics of biodiesel from different feed stocks. Biodiesel fuel is considered as offering many benefits like reduction of greenhouse gas emissions and many harmful pollutants (PM, HC, CO etc.). This paper critically reviews the effect of injection timing on combustion and emission characteristics. An attempt has been carried out to discuss the effect of biodiesel in terms of combustion, emission and performance based up on composition and properties. The results of the study show that different chemical composition leads to variation in its combustion, performance and emission characteristics. Biodiesel produced from different aspired feed stocks reduces the pollutant emission and resistive to oxidation but exhibit poor atomization. As a conclusion many research needs to be carried out to understand the relationship between the types of biodiesel feed stock, performance conclusion and emission.

Keywords: atomization, biodiesel, greenhouse gas, oxidation

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Authors: Hamed Hossein Afshari, Shahrzad Jalali, Amir Hossein Ghods, Bijan Raahemi

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This paper introduces an automated clustering solution that applies to WiFi/Bluetooth sensing data and is later used for traffic management applications. The paper initially summarizes a number of clustering approaches and thereafter shows their performance for noise removal. In this context, clustering is used to recognize WiFi and Bluetooth MAC addresses that belong to passengers traveling by a public urban transit bus. The main objective is to build an intelligent system that automatically filters out MAC addresses that belong to persons located outside the bus for different routes in the city of Ottawa. The proposed intelligent system alleviates the need for defining restrictive thresholds that however reduces the accuracy as well as the range of applicability of the solution for different routes. This paper moreover discusses the performance benefits of the presented clustering approaches in terms of the accuracy, time and space complexity, and the ease of use. Note that results of clustering can further be used for the purpose of the origin-destination estimation of individual passengers, predicting the traffic load, and intelligent management of urban bus schedules.

Keywords: WiFi-Bluetooth sensing, cluster analysis, artificial intelligence, traffic management

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Authors: Amira M. Attia, Karim H. Youssef, Nabil H. Abbasy

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Energy consumption schedule (ECS) technique shifts usage of loads from on peak hours and redistributes them throughout the day according to residents’ operating time preferences. This technique is used as form of indirect control from utility to improve the load curve and hence its load factor and reduce customer’s total electric bill as well. Similarly, load shifting technique achieves ECS purposes but as direct control form applied from utility. In this paper, ECS is simulated twice as optimal constrained mathematical formula, solved by using CVX program in MATLAB^® R2013b. First, it is utilized for single residential building with ten apartments to determine max allowable energy consumption per hour for each residential apartment. Then, it is used for single apartment with number of shiftable domestic devices, where operating schedule is deduced using previous simulation output results as constraints. The paper ends by giving differences between ECS technique and load shifting technique via literature and simulation. Based on results assessment, it will be shown whether using ECS or load shifting is more beneficial to both customer and utility.

Keywords: energy consumption schedule, load shifting, comparison, demand side mangement

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Authors: Muneesh Kumar, Rajesh Kumar, Sangeeta Devi

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Heavy metals are a major problem because they are toxic and tend to accumulate in living organisms. This study was carried out with the aims of studying on histopathology of Zn(SO4) toxicity on gill and liver tissues of catfish (Clarias batrachus) within the period of 96 h. Totally, 140 fishes with mean weight 50±10 g were stocked in 12 aquariums with capacity of 200 L water and divided in to 3 trails including control, 4 ppm and 8 ppm of Zn with 3 replicates. Tissue samples were fixed by bouin’s solution and sectioned in 7 μm based on histological regular method and stained with Hematoxylin and Eosin (H&E) method for microscopic study within the period of 96 h. Results showed some damaged such as hyperplasia, telangiectasis and edema, necrosis of second filaments, jerky movement, aneurism, hyperemia and fusion of second filaments in gills; and cell atrophy, necrosis, fatty degeneration, hyperemia and bile stagnation at different treatments in comparison with control. Gill and liver tissue damages were severed with the increase of Zn concentration and days. Therefore, Zn had acute toxicity effects on gill and liver tissues in Catfish at 5 and 10 ppm concentrations.

Keywords: gill, liver, histopathology, zinc, Clarias batrachus

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Authors: Anushka Naidoo, Veron Ramsuran, Maxwell Chirehwa, Paolo Denti, Kogieleum Naidoo, Helen McIlleron, Nonhlanhla Yende-Zuma, Ravesh Singh, Sinaye Ngcapu, Nesri Padayatachi

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Background: Despite efforts to introduce new drugs and shorter drug regimens for drug-susceptible tuberculosis (TB), the standard first-line treatment has not changed in over 50 years. Rifampicin, isoniazid, and pyrazinamide are critical components of the current standard treatment regimens. Some studies suggest that microbiologic failure and acquired drug resistance are primarily driven by low drug concentrations that result from pharmacokinetic (PK) variability independent of adherence to treatment. Wide between-patient pharmacokinetic variability for rifampin, isoniazid, and pyrazinamide has been reported in prior studies. There may be several reasons for this variability. However, genetic variability in genes coding for drug metabolizing and transporter enzymes have been shown to be a contributing factor for variable tuberculosis drug exposures. Objective: We describe the pharmacokinetics of first-line TB drugs rifampicin, isoniazid, and pyrazinamide and assess the effect of genetic variability in relevant selected drug metabolizing and transporter enzymes on pharmacokinetic parameters of isoniazid and rifampicin. Methods: We conducted the randomized-controlled Improving retreatment success TB trial in Durban, South Africa. The drug regimen included rifampicin, isoniazid, and pyrazinamide. Drug concentrations were measured in plasma, and concentration-time data were analysed using nonlinear-mixed-effects models to quantify the effects of relevant covariates and single nucleotide polymorphisms (SNP’s) of drug metabolizing and transporter genes on rifampicin, isoniazid and pyrazinamide exposure. A total of 25 SNP’s: four NAT2 (used to determine acetylator status), four SLCO1B1, three Pregnane X receptor (NR1), six ABCB1 and eight UGT1A, were selected for analysis in this study. Genotypes were determined for each of the SNP’s using a TaqMan® Genotyping OpenArray™. Results: Among fifty-eight patients studied; 41 (70.7%) were male, 97% black African, 42 (72.4%) HIV co-infected and 40 (95%) on efavirenz-based ART. Median weight, fat-free mass (FFM), and age at baseline were 56.9 kg (interquartile range, IQR: 51.1-65.2), 46.8 kg (IQR: 42.5-50.3) and 37 years (IQR: 31-42), respectively. The pharmacokinetics of rifampicin and pyrazinamide was best described using one-compartment models with first-order absorption and elimination, while for isoniazid two-compartment disposition was used. The median (interquartile range: IQR) AUC (h·mg/L) and Cmax (mg/L) for rifampicin, isoniazid, and pyrazinamide were; 25.62 (23.01-28.53) and 4.85 (4.36-5.40), 10.62 (9.20-12.25) and 2.79 (2.61-2.97), 345.74 (312.03-383.10) and 28.06 (25.01-31.52), respectively. Eighteen percent of patients were classified as rapid acetylators, and 34% and 43% as slow and intermediate acetylators, respectively. Rapid and intermediate acetylator status based on NAT 2 genotype resulted in 2.3 and 1.6 times higher isoniazid clearance than slow acetylators. We found no effects of the SLCO1B1 genotypes on rifampicin pharmacokinetics. Conclusion: Plasma concentrations of rifampicin, isoniazid, and pyrazinamide were low overall in our patients. Isoniazid clearance was high overall and as expected higher in rapid and intermediate acetylators resulting in lower drug exposures. In contrast to reports from previous South African or Ugandan studies, we did not find any effects of the SLCO1B1 or other genotypes tested on rifampicin PK. However, our findings are in keeping with more recent studies from Malawi and India emphasizing the need for geographically diverse and adequately powered studies. The clinical relevance of the low tuberculosis drug concentrations warrants further investigation.

Keywords: rifampicin, isoniazid pharmacokinetics, genetics, NAT2, SLCO1B1, tuberculosis

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Authors: Jalil Boudjadar

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Dynamic Voltage and Frequency Scaling (DVFS) multicore platforms are promising execution platforms that enable high computational performance, less energy consumption and flexibility in scheduling the system processes. However, the resulting interleaving and memory interference together with per-core frequency tuning make real-time guarantees hard to be delivered. Besides, energy consumption represents a strong constraint for the deployment of such systems on energy-limited settings. Identifying the system configurations that would achieve a high performance and consume less energy while guaranteeing the system schedulability is a complex task in the design of modern embedded systems. This work studies the trade-off between energy consumption, cores utilization and memory bottleneck and their impact on the schedulability of DVFS multicore time-critical systems with a hierarchy of shared memories. We build a model-based framework using Parametrized Timed Automata of UPPAAL to analyze the mutual impact of performance, energy consumption and schedulability of DVFS multicore systems, and demonstrate the trade-off on an actual case study.

Keywords: time-critical systems, multicore systems, schedulability analysis, energy consumption, performance analysis

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Authors: K. Krushnamurty, D. Rasmitha, I. Srikanth, K. Ramji, Ch. Subrahmanyam

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E-glass-epoxy laminated composites having different fiber volume fractions (40, 50, 60 and 70) were fabricated with and without the addition of nanoclay. Flexural strength and tensile strength of the composite laminates were determined. It was observed that, with increasing the fiber volume fraction (Vf) of fiber from 40 to 60, the ability of nanoclay to enhance the tensile and flexural strength of E-glass-epoxy composites decreases significantly. At 70Vf, the tensile and flexural strength of the nanoclay reinforced E-glass-epoxy were found to be lowest when compared to the E-glass-epoxy composite made without the addition of nanoclay. Based on the obtained data and microstructure of the tested samples, plausible mechanism for the observed trends has been proposed. The enhanced mechanical properties for nanoclay reinforced E-glass-epoxy composites for 40-60 Vf, due to higher interface toughness coupled with strong interfilament bonding may have ensured the homogeneous load distribution across all the glass fibers. Results in the decrease in mechanical properties at 70Vf, may be due to the inability of the matrix to bind the nanoclay and glass-fibers.

Keywords: e-glass-epoxy composite laminates, fiber volume fraction, e-glass fiber, mechanical properties, delamination

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Authors: X. Wang, T. J. Craft, H. Iacovides

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When handling the near-wall regions of turbulent flows, it is necessary to account for the viscous effects which are important over the thin near-wall layers. Low-Reynolds- number turbulence models do this by including explicit viscous and also damping terms which become active in the near-wall regions, and using very fine near-wall grids to properly resolve the steep gradients present. In order to overcome the cost associated with the low-Re turbulence models, a more advanced wall function approach has been implemented within OpenFoam and tested together with a standard log-law based wall function in the prediction of flows which involve 2-D shock wave/turbulent boundary layer interactions (SWTBLIs). On the whole, from the calculation of the impinging shock interaction, the three turbulence modelling strategies, the Lauder-Sharma k-ε model with Yap correction (LS), the high-Re k-ε model with standard wall function (SWF) and analytical wall function (AWF), display good predictions of wall-pressure. However, the SWF approach tends to underestimate the tendency of the flow to separate as a result of the SWTBLI. The analytical wall function, on the other hand, is able to reproduce the shock-induced flow separation and returns predictions similar to those of the low-Re model, using a much coarser mesh.

Keywords: SWTBLIs, skin-friction, turbulence modeling, wall function

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Authors: Ngan Nguyen

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The study analyses adjectives collocating with the word ‘education’ in the American language of the Corpus of Global Web-based English using a combination of corpus linguistic and discourse analytical methods to examine not only language patterns but also social political ideologies around the topic. Significant conclusions are deduced: (1) there are a large number of adjectival collocates of the word education which have been identified and classified into four categories representing four different aspects of education: level, quality, forms and types of education; (2) education, as in combination with three first categories, carries the meaning as the act and process of teaching and learning while with the last category having the meaning of a particular kind of teaching or training; (3) higher education is the topic that gains most concerns from the American public; (4) five most significant ideologies are discovered from the corpus: higher education associates with financial affairs, higher education is an industry, monetary policy of the government on higher education, people require greater accessibility to higher education and people value higher education. The study contributes to the field of developing meanings of words through corpus analysis and the field of discourse analysis.

Keywords: adjectival collocation, American context, corpus linguistics, discourse analysis, education

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Authors: Flavia Laffleur, Andreas Bernkop-Schnürch

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Purpose: This study was aimed to investigate preactivated thiomers for their mucoadhesive potential. Methods: Accordingly, chitosan-thioglycolic-mercaptonicotinamide conjugates (chitosan-TGA-MNA) were synthesized by the oxidative S-S coupling of chitosan-thioglycolic acid (chitosan-TGA) with 6-mercaptonicotin amide (MNA). Unmodified chitosan, chitosan-TGA (thiomers) and chitosan-TGA-MNA conjugates were compressed into test discs to investigate cohesive properties, cytotoxicity assays and mucoadhesion studies. Results: Due to the immobilization of MNA, the chitosan-TGA-MNA conjugates exhibit comparatively higher swelling properties and cohesive properties corresponding unmodified chitosan. On the rotating cylinder, discs based on chitosan-TGA-MNA conjugates displayed 3.1-fold improved mucoadhesion time compared to thiolated polymers. Tensile study results were found in good agreement with rotating cylinder results. Moreover, preactivated thiomers showed higher stability. All polymers were found non-toxic over Caco-2 cells. Conclusion: On the basis of achieved results the pre activated thiomeric therapeutic agent seems to represent a promising generation of mucoadhesive polymers which are safe to use for a prolonged residence time to target the mucosa.

Keywords: biomedical application, drug delivery, polymer, thiomer

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Authors: A. Altomi, A. Alhebshi, M. Rasm, B. Osman

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This study explored the application of chitin nanocrystals (ChiNCs), derived from a renewable and environmentally friendly material, as stabilizers for oil-in-water (O/W) emulsions. O/W emulsions are commonly used in various applications but are prone to instability and degradation over time. Instability can occur due to factors such as flocculation, coalescence, and gravitational separation, including creaming and sedimentation, either independently or simultaneously. To produce ChiNCs, chitin powder underwent acid hydrolysis. Transmission electron microscopy (TEM) analysis revealed that ChiNCs exhibited a needle-like morphology, with lengths ranging from 200 to 800 nm and widths ranging from 20 to 80 nm. The surface charge of ChiNCs was negative at pH values above 7 and positive at pH values below 7. The rheological properties of O/W emulsions stabilized by ChiNCs were compared to those stabilized by synthetic surfactants, namely Tween 80 and CTAB. The emulsions stabilized by ChiNCs demonstrated higher yield stress and lower shear viscosity compared to those stabilized by synthetic surfactants. This indicates that ChiNC-stabilized emulsions are more stable and less prone to breakdown. Based on these findings, ChiNCs show promise as an alternative to synthetic surfactants for stabilizing O/W emulsions.

Keywords: chitin nanocrystals, colloidal pickering, emulsion rheology, oil-in-water, synthetic surfactant

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Authors: Feride Eskin Bacaksiz, Arzu K. Harmanci Seren

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The problems about the working hours of nursing personnel, such as overworking, numbers of night or daytime shifts, is stated one of the most complained issues by nurses. Otherwise, besides of nursing shortage, absenteeism of nurses because of sickness, some other health problems, or other reasons enforces nurse managers to make working schedules. In this study, it was aimed to analyse and evaluate the working schedules of nurses working in public hospitals. Working schedule lists of nursing personnel for the months of October and November in two public hospitals were analysed and evaluated. Approvals were acquired from the head nurse managers. Descriptive and comparative analyses were used. Totally 36 lists were analysed from two hospitals. There were totally 416 nurses (manager nurse: 25, nurse: 391) and 6-28 (12.6, SD=5.34) nurses in each list. It was found that nurses were working 8 (42.5%), 12 (27.9%) and 16 (20%) hours, in inpatient clinics (74.8%). Totally 20.2% of the nurses were absent during analysing time due to the annual, paid or unpaid leaves. Nurses were generally working 20-112 hours (80.27, SD=11.92). Most of the nurses over worked 1.5-443 hours (47.436, SD=60.78) the year before that year. It was determined that 11.8% of the nurses (n: 49) were working only night shifts and 42.1% (n: 175) of the nurses were working only daytime shifts. It was found that there were inequities in the working hours of nurses.

Keywords: nurse, public hospitals, working conditions, working schedules

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Authors: Abayomi Olatoke Adejobi

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The study investigated maternal deprivation as predictor of academic performance and psychosocial adjustment of primary school pupils in Abeokuta metropolis. Three null hypotheses were formulated to guide the study. Two hundred public primary school pupils were randomly selected as subjects for the study. The instruments used for data collection were Index of Family Relations (IFR) by Hudson, modified version of Psychosocial Adjustment Scale (PAS) by O’ bailey and Academic records of the pupils from Cumulative Records Folder (CRF). The data collected were statistically treated and the three hypotheses were tested using t-test and Pearson Product Moment Correlation Confident statistical methods at 0.05 alpha level. The results of the analysis showed that there is a significant difference in the academic performance of children who suffered maternal deprivation and those who did not (t – 5.61; df = 198; P < 0.05). Also, there was a significant relationship between psychosocial adjustment of children and maternal deprivation (r = 0.37, df = 10; P < 0.05), while there was no significant difference in academic performance of boys and girls who suffered maternal deprivation (t = 0.32; df = 109; P > 0.05). Based on the results some recommendations were made.

Keywords: maternal deprivation, psychosocial adjustment, academic performance, primary school pupils

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Authors: Khalid Kaddoura, Tarek Zayed

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Sewer networks are constructed to protect the communities and the environment from any contact with the sewer mediums. Pipelines, being laterals or sewer mains, and manholes form the huge underground infrastructure in every urban city. Due to the sewer networks importance, the infrastructure asset management field has extensive advancement in condition assessment and rehabilitation decision models. However, most of the focus was devoted to pipelines giving little attention toward manholes condition assessment. In fact, recent studies started to emerge in this area to preserve manholes from any malfunction. Therefore, the main objective of this study is to propose a condition assessment model for sewer manholes. The model divides the manhole into several components and determines the relative importance weight of each component using the Analytic Network Process (ANP) decision-making method. Later, the condition of the manhole is computed by aggregating the condition of each component with its corresponding weight. Accordingly, the proposed assessment model will enable decision-makers to have a final index suggesting the overall condition of the manhole and a backward analysis to check the condition of each component. Consequently, better decisions are made pertinent to maintenance, rehabilitation, and replacement actions.

Keywords: Analytic Network Process (ANP), condition assessment, decision-making, manholes

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Authors: Golnaz Moghimi, Alireza Afsharghotli, Alireza Rezaei

Abstract:

Construction waste has been gradually increased as a result of upsizing construction projects which are occurred within the lifecycle of buildings. Since waste management is a major priority and has profound impacts on the volume of waste generated in construction stage, the majority of efforts have been attempted to reuse, recycle and reduce waste. However, there is still room to study on lack of sufficient knowledge about waste management in construction industry. This paper intends to provide an insight into the effect of project management knowledge areas on waste management solely on construction stage. To this end, a survey among Iranian building construction industry contractors was conducted to identify the effectiveness of project management knowledge areas on three jobsite key factors including ‘Site activity’, ‘Training’, and ‘Awareness’. As a result, four management disciplines were identified as most influential ones on amount of construction waste. These disciplines were Project Cost Management, Quality Management, Human Resource Management, and Integration Management. Based on the research findings, a new model was presented to develop effective construction waste strategies.

Keywords: awareness, PMBOK, site activity, training, waste management

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Authors: M. Jazouli, S. Elhoufi, A. Majda, A. Zarghili, R. Aalouane

Abstract:

Autism spectrum disorder is a complex developmental disability. It is defined by a certain set of behaviors. Persons with Autism Spectrum Disorders (ASD) frequently engage in stereotyped and repetitive motor movements. The objective of this article is to propose a method to automatically detect this unusual behavior. Our study provides a clinical tool which facilitates for doctors the diagnosis of ASD. We focus on automatic identification of five repetitive gestures among autistic children in real time: body rocking, hand flapping, fingers flapping, hand on the face and hands behind back. In this paper, we present a gesture recognition system for children with autism, which consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using artificial neural network (ANN). The first one uses the Microsoft Kinect sensor, the second one chooses points of interest from the 3D skeleton to characterize the gestures, and the last one proposes a neural connectionist model to perform the supervised classification of data. The experimental results show that our system can achieve above 93.3% recognition rate.

Keywords: ASD, artificial neural network, kinect, stereotypical motor movements

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Authors: Abdelmounaim Zanaz, Sylvie Yotte, Fazia Fouchal, Alaa Chateauneuf

Abstract:

This paper presents a methodology for probabilistic assessment of bearing capacity and prediction of failure mechanism of masonry vaults at the ultimate state with consideration of the natural variability of Young’s modulus of stones. First, the computation model is explained. The failure mode is the most reported mode, i.e. the four-hinge mechanism. Based on this assumption, the study of a vault composed of 16 segments is presented. The Young’s modulus of the segments is considered as random variable defined by a mean value and a coefficient of variation CV. A relationship linking the vault bearing capacity to the modulus variation of voussoirs is proposed. The failure mechanisms, in addition to that observed in the deterministic case, are identified for each CV value as well as their probability of occurrence. The results show that the mechanism observed in the deterministic case has decreasing probability of occurrence in terms of CV, while the number of other mechanisms and their probability of occurrence increase with the coefficient of variation of Young’s modulus. This means that if a significant change in the Young modulus of the segments is proven, taken it into account in computations becomes mandatory, both for determining the vault bearing capacity and for predicting its failure mechanism.

Keywords: masonry, mechanism, probability, variability, vault

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Authors: Fabio Fabris, Alex A. Freitas

Abstract:

Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation.

Keywords: algorithm recommendation, meta-learning, bioinformatics, hierarchical classification

Procedia PDF Downloads 297