Search results for: dispersed region growing algorithm (DRGA)

Authors: Michael A. Tabug, Arvin C. Diesmos

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The foraging ecology of the Philippine endemic Draco spilopterus was studied through a combination of in-situ field observations and laboratory examinations of specimens of the species. A total of four populations of the species were studied across the Luzon Biogeographic Region between June 2017 and March 2019. Of the 59 lizards captured, gut contents of 54 individuals were studied. A total of 2933 food items were sorted into seven types, such as Formicidae (ants) (96%), Araneae (spiders) (0.034%), Coleoptera (beetles) (0.579%), Hemiptera (scale insects) (0.102%), Isoptera (termites) (2.796%), Lepidoptera (larvae) (0.307%), and Diplopoda (millipede) (0.102%). Diet analysis revealed that D. spilopterus fed mainly on insect arthropods and were dominated by ants (Formicidae). Of the four populations studied, lizards consumed a relatively high proportion of ants (96%), which strongly implies that D. spilopterus is a specialist predator and a sit-and-wait active forager. The observed feeding activities of D. spilopterus also show that it is diurnal forager and actively hunts for prey from 0830 hr to 1658 hr, with decreasing activity during midday. Draco spilopterus lizards were also observed to use a wide spectrum of perch heights while foraging, regardless of the dimension of trees.

Keywords: ant specialists, diet analysis, flying lizards, foraging ecology, Luzon Biogeographic Region

Procedia PDF Downloads 164

Authors: N. Saranya

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The difference in characteristic behavior of clay minerals for different electrolyte solution is dictated by the corresponding variation occurring at its diffused double layer thickness (DDL). The diffused double layer of clay mineral has two distinct regions; the inner region is termed as ‘Stern layer’ where ions are strongly attached to the clay surface. In the outer region, the ions are not strongly bonded with the clay surface, and this region is termed as ‘diffuse layer’. Within the diffuse layer, there is a plane that forms a boundary between the moving ions and the ions attached to the clay surface, which is termed as slipping or shear plane, and the potential of this plane is defined as zeta potential (ζ). Therefore, the variation in diffused double layer properties of clay mineral for different electrolyte solutions can be modeled if the corresponding variation in surface charge, surface potential, and zeta potential are computed. In view of this, the present study has attempted to characterize the diffused double layer properties of three different clay minerals interacting with different pore fluids by measuring the corresponding variation in surface charge, surface potential, and zeta potential. Further, the obtained variation in the diffused double layer property is compared with the Gouy-Chapman model, which is the widely accepted theoretical model to characterize the diffused double layer properties of clay minerals.

Keywords: DDL, surface charge, surface potential, zeta potential

Procedia PDF Downloads 167

Authors: Foad Nazari, Seyed Mahmood Hosseini, Mohammad Hossein Abolbashari, Mohammad Hassan Abolbashari

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The present study is concerned with the optimal design of functionally graded plates using particle swarm optimization (PSO) algorithm. In this study, meshless local Petrov-Galerkin (MLPG) method is employed to obtain the functionally graded (FG) plate’s natural frequencies. Effects of two parameters including thickness to height ratio and volume fraction index on the natural frequencies and total mass of plate are studied by using the MLPG results. Then the first natural frequency of the plate, for different conditions where MLPG data are not available, is predicted by an artificial neural network (ANN) approach which is trained by back-error propagation (BEP) technique. The ANN results show that the predicted data are in good agreement with the actual one. To maximize the first natural frequency and minimize the mass of FG plate simultaneously, the weighted sum optimization approach and PSO algorithm are used. However, the proposed optimization process of this study can provide the designers of FG plates with useful data.

Keywords: optimal design, natural frequency, FG plate, hybrid meshless method, MLPG method, ANN approach, particle swarm optimization

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Authors: Senol Dogan, Gunay Karli

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Identification of relevant publications based on a Medline query is time-consuming and error-prone. An all based process has the potential to solve this problem without any manual work. To the best of our knowledge, our study is the first to investigate the ability of machine learning to identify relevant articles accurately. 5 different machine learning algorithms were tested using 23 predictors based on several metadata fields attached to publications. We find that the Boosted model is the best-performing algorithm and its overall accuracy is 96%. In addition, specificity and sensitivity of the algorithm is 97 and 93%, respectively. As a result of the work, we understood that we can apply the same procedure to understand cancer gene expression big data.

Keywords: prediction of publications, machine learning, algorithms, bariatric surgery, comparison of algorithms, boosted, tree, logistic regression, ANN model

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Authors: C. Fornacelli, P. Colomban, E. Mugnaioli, I. Memmi Turbanti

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When semiconductor particles are reduced in scale to nanometer dimension, their optical and electro-optical properties strongly differ from those of bulk crystals of the same composition. Since sampling is often not allowed concerning cultural heritage artefacts, the potentialities of two non-invasive techniques, such as Raman and Fiber Optic Reflectance Spectroscopy (FORS), have been investigated and the results of the analysis on some original glasses of different colours (from yellow to orange and deep red) and periods (from the second decade of the 20th century to present days) are reported in the present study. In order to evaluate the potentialities of the application of non-invasive techniques to the investigation of the structure and distribution of nanoparticles dispersed in a glass matrix, Scanning Electron Microscopy (SEM) and energy-disperse spectroscopy (EDS) mapping, together with Transmission Electron Microscopy (TEM) and Electron Diffraction Tomography (EDT) have also been used. Raman spectroscopy allows a fast and non-destructive measure of the quantum dots composition and size, thanks to the evaluation of the frequencies and the broadening/asymmetry of the LO phonons bands, respectively, though the important role of the compressive strain arising from the glass matrix and the possible diffusion of zinc from the matrix to the nanocrystals should be taken into account when considering the optical-phonons frequency values. The incorporation of Zn has been assumed by an upward shifting of the LO band related to the most abundant anion (S or Se), while the role of the surface phonons as well as the confinement-induced scattering by phonons with a non-zero wavevectors on the Raman peaks broadening has been verified. The optical band gap varies from 2.42 eV (pure CdS) to 1.70 eV (CdSe). For the compositional range between 0.5≤x≤0.2, the presence of two absorption edges has been related to the contribution of both pure CdS and the CdSxSe1-x solid solution; this particular feature is probably due to the presence of unaltered cubic zinc blende structures of CdS that is not taking part to the formation of the solid solution occurring only between hexagonal CdS and CdSe. Moreover, the band edge tailing originating from the disorder due to the formation of weak bonds and characterized by the Urbach edge energy has been studied and, together with the FWHM of the Raman signal, has been assumed as a good parameter to evaluate the degree of topological disorder. SEM-EDS mapping showed a peculiar distribution of the major constituents of the glass matrix (fluxes and stabilizers), especially concerning those samples where a layered structure has been assumed thanks to the spectroscopic study. Finally, TEM-EDS and EDT were used to get high-resolution information about nanocrystals (NCs) and heterogeneous glass layers. The presence of ZnO NCs (< 4 nm) dispersed in the matrix has been verified for most of the samples, while, for those samples where a disorder due to a more complex distribution of the size and/or composition of the NCs has been assumed, the TEM clearly verified most of the assumption made by the spectroscopic techniques.

Keywords: CdSxSe1-x, EDT, glass, spectroscopy, TEM-EDS

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Authors: Naushad Mamode Khan

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The Com-Poisson (CMP) model is one of the most popular discrete generalized linear models (GLMS) that handles both equi-, over- and under-dispersed data. In longitudinal context, an integer-valued autoregressive (INAR(1)) process that incorporates covariate specification has been developed to model longitudinal CMP counts. However, the joint likelihood CMP function is difficult to specify and thus restricts the likelihood based estimating methodology. The joint generalized quasilikelihood approach (GQL-I) was instead considered but is rather computationally intensive and may not even estimate the regression effects due to a complex and frequently ill conditioned covariance structure. This paper proposes a new GQL approach for estimating the regression parameters (GQLIII) that are based on a single score vector representation. The performance of GQL-III is compared with GQL-I and separate marginal GQLs (GQL-II) through some simulation experiments and is proved to yield equally efficient estimates as GQL-I and is far more computationally stable.

Keywords: longitudinal, com-Poisson, ill-conditioned, INAR(1), GLMS, GQL

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Authors: Abasse Kamarchou, Ahmed Abdelhafid Bebba, Ali Douadi

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The objective of this work is the preparation of an activated carbon from waste date palm from El Oued region, namely the date stones and its use in the treatment of wastewater in this region. The study of the characteristics of this coal has the following results: specific surface 125.86 m2 / g, pore volume 0.039 cm3 / g, pore diameter of 16.25 microns, surface micropores 92.28 m2 / g, the outer surface 33,57 m2 /g, methylene blue number of 13.6 mg / g, iodine number 735.2 mg /g, the functional groups are the number of 4.10-2 mol / g. The optimum conditions for pH, stirring speed, initial concentration, contact time were determined. For organic pollutants, the best conditions are: pH > 8 and pH < 5, a contact time of 5 minutes and an agitation rate of 200 - 300 rpm.

Keywords: date palm, activated carbon, wastewater, El-Oued

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Authors: Martins Y. Otache, John J. Musa, Abayomi I. Kuti, Mustapha Mohammed

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The performance of an artificial neural network (ANN) is contingent on a host of factors, for instance, the network optimisation scheme. In view of this, the study examined the general implications of the ANN training optimisation algorithm on its forecast performance. To this end, the Bayesian regularisation (Br), Levenberg-Marquardt (LM), and the adaptive learning gradient descent: GDM (with momentum) algorithms were employed under different ANN structural configurations: (1) single-hidden layer, and (2) double-hidden layer feedforward back propagation network. Results obtained revealed generally that the gradient descent with momentum (GDM) optimisation algorithm, with its adaptive learning capability, used a relatively shorter time in both training and validation phases as compared to the Levenberg- Marquardt (LM) and Bayesian Regularisation (Br) algorithms though learning may not be consummated; i.e., in all instances considering also the prediction of extreme flow conditions for 1-day and 5-day ahead, respectively especially using the ANN model. In specific statistical terms on the average, model performance efficiency using the coefficient of efficiency (CE) statistic were Br: 98%, 94%; LM: 98 %, 95 %, and GDM: 96 %, 96% respectively for training and validation phases. However, on the basis of relative error distribution statistics (MAE, MAPE, and MSRE), GDM performed better than the others overall. Based on the findings, it is imperative to state that the adoption of ANN for real-time forecasting should employ training algorithms that do not have computational overhead like the case of LM that requires the computation of the Hessian matrix, protracted time, and sensitivity to initial conditions; to this end, Br and other forms of the gradient descent with momentum should be adopted considering overall time expenditure and quality of the forecast as well as mitigation of network overfitting. On the whole, it is recommended that evaluation should consider implications of (i) data quality and quantity and (ii) transfer functions on the overall network forecast performance.

Keywords: streamflow, neural network, optimisation, algorithm

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Authors: Sweeti, Anoop Kant Godiyal, Neha Singh, Sneh Anand, B. K. Panigrahi, Jayasree Santhosh

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This work is about developing a tool for visualization and segmentation of Electroencephalograph (EEG) signals based on frequency domain features. Change in the frequency domain characteristics are correlated with change in mental state of the subject under study. Proposed algorithm provides a way to represent the change in the mental states using the different frequency band powers in form of segmented EEG signal. Many segmentation algorithms have been suggested in literature having application in brain computer interface, epilepsy and cognition studies that have been used for data classification. But the proposed method focusses mainly on the better presentation of signal and that’s why it could be a good utilization tool for clinician. Algorithm performs the basic filtering using band pass and notch filters in the range of 0.1-45 Hz. Advanced filtering is then performed by principal component analysis and wavelet transform based de-noising method. Frequency domain features are used for segmentation; considering the fact that the spectrum power of different frequency bands describes the mental state of the subject. Two sliding windows are further used for segmentation; one provides the time scale and other assigns the segmentation rule. The segmented data is displayed second by second successively with different color codes. Segment’s length can be selected as per need of the objective. Proposed algorithm has been tested on the EEG data set obtained from University of California in San Diego’s online data repository. Proposed tool gives a better visualization of the signal in form of segmented epochs of desired length representing the power spectrum variation in data. The algorithm is designed in such a way that it takes the data points with respect to the sampling frequency for each time frame and so it can be improved to use in real time visualization with desired epoch length.

Keywords: de-noising, multi-channel data, PCA, power spectra, segmentation

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Authors: A. Cherifi, B. Bouazza, A. O. Dahmane, B. Yagoubi

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Transmission over Optical channels will introduce inter-symbol interference (ISI) as well as inter-channel (or inter-carrier) interference (ICI). To decrease the effects of ICI, this paper proposes equalizer for the Optical OFDM system based on the fractional Fourier transform (FrFFT). In this FrFT-OFDM system, traditional Fourier transform is replaced by fractional Fourier transform to modulate and demodulate the data symbols. The equalizer proposed consists of sampling the received signal in the different time per time symbol. Theoretical analysis and numerical simulation are discussed.

Keywords: OFDM, (FrFT) fractional fourier transform, optical OFDM, equalization algorithm

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Authors: A. Mansouri, F. Krim

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This paper presents two techniques for DC motor parameters identification. We propose a numerical method using the adaptive extensive recursive least squares (AERLS) algorithm for real time parameters estimation. This algorithm, based on minimization of quadratic criterion, is realized in simulation for parameters identification of DC motor autoregressive moving average with extra inputs (ARMAX). As advanced technique, we use genetic algorithms (GA) identification with biased estimation for high dynamic performance speed regulation. DC motors are extensively used in variable speed drives, for robot and solar panel trajectory control. GA effectiveness is derived through comparison of the two approaches.

Keywords: ARMAX model, DC motor, AERLS, GA, optimization, parameter identification, PID speed regulation

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Authors: Kashif Mahmood, Tehreem Fatima, Adeel Hassan

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Firms are always concerned with their performance which is directly linked to employees’ performance. In the thrive of this goal, number of researches have been conducted where Organizational Citizenship Behavior (OCB) and Counterproductive Work Behavior (CPWB) is among those studies. This study is aimed at investigating the role OCB by considering altruism and conscientiousness in an employee’s job performance with the mediating role of CPWB by considering sabotage and withdraw among the employees of hotel industry in Pakistan. A quantitative method was used by following deductive approach in positivist paradigm where survey was conducted through self-administered questionnaires and data was collected from the employees working in hotel industry of Pakistan. Top 10 hotels from the region of Lahore, Punjab was selected as population, and 500 questionnaires were distributed among their employees by using stratified random sampling technique. There is a positive impact of OCB is found on job performance of an employee whereas full mediation of CPWB is also found between OCB and job performance. The study is important for the practitioners in a way that hotel industry is growing at an enormous rate where employee behavior is always a concern specifically in emerging markets due to the exploitation of employees at the workplace, so the findings of the study can be helpful for practitioners and policy makers.

Keywords: organizational citizenship behavior, counterproductive work behavior, employee performance, altruism, conscientiousness, sabotage, withdraw, hotel industry

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Authors: Manpreet Kaur

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When legitimate credit card users are mistakenly labelled as fraudulent in numerous financial delated applications, there are numerous ethical problems. The innovative machine learning approach we have suggested in this research outperforms the current models and shows how to model a data set for credit card fraud detection while minimizing false positives. As a result, we advise using random forests as the best machine learning method for predicting and identifying credit card transaction fraud. The majority of victims of these fraudulent transactions were discovered to be credit card users over the age of 60, with a higher percentage of fraudulent transactions taking place between the specific hours.

Keywords: automated fraud detection, isolation forest method, local outlier factor, ML algorithm, credit card

Procedia PDF Downloads 114

Authors: N. D'Amico, E. Grossi, B. Colombo, F. Rigiroli, M. Buscema, D. Fazzini, G. Cornalba, S. Papa

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Purpose: To characterize, through a radiomic approach, the nature of nodules considered non-specific by expert radiologists, recognized in magnetic resonance mammography (MRm) with T1-weighted (T1w) sequences with paramagnetic contrast. Material and Methods: 47 cases out of 1200 undergoing MRm, in which the MRm assessment gave uncertain classification (non-specific nodules), were admitted to the study. The clinical outcome of the non-specific nodules was later found through follow-up or further exams (biopsy), finding 35 benign and 12 malignant. All MR Images were acquired at 1.5T, a first basal T1w sequence and then four T1w acquisitions after the paramagnetic contrast injection. After a manual segmentation of the lesions, done by a radiologist, and the extraction of 150 radiomic features (30 features per 5 subsequent times) a machine learning (ML) approach was used. An evolutionary algorithm (TWIST system based on KNN algorithm) was used to subdivide the dataset into training and validation test and to select features yielding the maximal amount of information. After this pre-processing, different machine learning systems were applied to develop a predictive model based on a training-testing crossover procedure. 10 cases with a benign nodule (follow-up older than 5 years) and 18 with an evident malignant tumor (clear malignant histological exam) were added to the dataset in order to allow the ML system to better learn from data. Results: NaiveBayes algorithm working on 79 features selected by a TWIST system, resulted to be the best performing ML system with a sensitivity of 96% and a specificity of 78% and a global accuracy of 87% (average values of two training-testing procedures ab-ba). The results showed that in the subset of 47 non-specific nodules, the algorithm predicted the outcome of 45 nodules which an expert radiologist could not identify. Conclusion: In this pilot study we identified a radiomic approach allowing ML systems to perform well in the diagnosis of a non-specific nodule at MR mammography. This algorithm could be a great support for the early diagnosis of malignant breast tumor, in the event the radiologist is not able to identify the kind of lesion and reduces the necessity for long follow-up. Clinical Relevance: This machine learning algorithm could be essential to support the radiologist in early diagnosis of non-specific nodules, in order to avoid strenuous follow-up and painful biopsy for the patient.

Keywords: breast, machine learning, MRI, radiomics

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Authors: Qiong Rao, Xiongqi Peng

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In this work, multi-walled carbon nanotubes (MWCNTs) and graphene nanoplates (GNPs) were dispersed into epoxy adhesive to investigate their synergy effects on the shear properties, mode I and mode II fracture toughness of unidirectional composite bonded joints. Testing results showed that the incorporation of MWCNTs and GNPs significantly improved the shear strength, the mode I and mode II fracture toughness by 36.6%, 45% and 286%, respectively. In addition, the fracture surfaces of the bonding area as well as the toughening mechanism of nanofillers were analyzed. Finally, a nonlinear cohesive/friction coupled model for delamination analysis of adhesive layer under shear and normal compression loadings was proposed and implemented in ABAQUS/Explicit via user subroutine VUMAT.

Keywords: nanofillers, adhesive joints, fracture toughness, cohesive zone model

Procedia PDF Downloads 133

Authors: Aruna Bommareddi

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The journey of the novel is well examined in Indian academia as an offshoot of the novel in English. There have been many attempts to understand aspects of the early novel in India which shared a commonality with the English novel. The regional novel has had an entirely different trajectory which is mapped in the paper. The main focus of the paper would be to look at the historical emergence of the genre of the regional novel in Indian Literatures with specific reference to Kannada, Hindi, and Bengali. The selection of these languages is guided not only by familiarity with these languages as also based on the significance that these languages enjoy in the sub-continent and for the emergence of the regional novel as a specific category in these languages. The regional novels under study are Phaneeswaranath Renu’s Maila Anchal, Tarashankar Bandopadhyaya’s Ganadevata, and Kuvempu’s House of Kanuru for exploration of the themes of its emergence and some aspects of the regional novel common to and different from each other. The paper would explore the various movements that have shaped the genre regional novel in these Literatures. Though Phaneeswarnath Renu’s Maila Anchal is published in 1956, the novel is set in pre-Independent India and therefore shares a commonality of themes with the other two novels, House of Kanuru and Ganadevata. All three novels explore themes of superstition, ignorance, poverty, and the interventions of educated youth to salvage the crises in these backward regional worlds. In fact, it was Renu who assertively declared that he was going to write a regional novel and hence the tile of the first regional novel in Hindi is Maila Anchal meaning the soiled border. In Hindi, anchal also means the region therefore, the title is suggestive of a dirty region as well. The novel exposes the squalor, ignorance, and the conflict ridden life of the village or region as opposed to the rosy image of the village in literature. With this, all such novels which depicted conflicts of the region got recognized as regional novels even though they may have been written prior to Renu’s declaration. All three novels under study succeed in bringing out the complexity of rural life at a given point of time in its history.

Keywords: bengali, hindi, kannada, regional novel, telugu

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Authors: Hassan S. Hussein, Rania A. Abul Seoud, Amr M. Refaat

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Scientific researchers face in the analysis of very large data sets that is increasing noticeable rate in today’s and tomorrow’s technologies. Hadoop and Spark are types of software that developed frameworks. Hadoop framework is suitable for many Different hardware platforms. In this research, a scientific Linux cluster for Big Data analysis (SLBD) is presented. SLBD runs open source software with large computational capacity and high performance cluster infrastructure. SLBD composed of one cluster contains identical, commodity-grade computers interconnected via a small LAN. SLBD consists of a fast switch and Gigabit-Ethernet card which connect four (nodes). Cloudera Manager is used to configure and manage an Apache Hadoop stack. Hadoop is a framework allows storing and processing big data across the cluster by using MapReduce algorithm. MapReduce algorithm divides the task into smaller tasks which to be assigned to the network nodes. Algorithm then collects the results and form the final result dataset. SLBD clustering system allows fast and efficient processing of large amount of data resulting from different applications. SLBD also provides high performance, high throughput, high availability, expandability and cluster scalability.

Keywords: big data platforms, cloudera manager, Hadoop, MapReduce

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Authors: Yazan Khalid Abed-Allah Migdadi

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The aim of this study is identifying the effective operations competitive advantages of mobile phone service providers across countries. All Arab countries in the Middle East region were surveyed except Syria, and 27 out of 31 service providers were surveyed. Data collected from corporations’ annual reports, websites and other professional institutions published sources. Multiple linear regression analysis test was used to identify the relationship between operations competitive advantages and market share. The effective operations competitive advantages were; diversity of offers and service accessibility

Keywords: competitive advantage, mobile telecommunication operations, Middle East, service provider

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Authors: Sukhveer Singh, Sandeep Singh

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A bi-objective fuzzy transportation problem with the objectives to minimize the total fuzzy cost and fuzzy time of transportation without according priorities to them is considered. To the best of our knowledge, there is no method in the literature to find efficient solutions of the bi-objective transportation problem under uncertainty. In this paper, a bi-objective transportation problem in an uncertain environment has been formulated. An algorithm has been proposed to find efficient solutions of the bi-objective transportation problem under uncertainty. The proposed algorithm avoids the degeneracy and gives the optimal solution faster than other existing algorithms for the given uncertain transportation problem.

Keywords: uncertain transportation problem, efficient solution, ranking function, fuzzy transportation problem

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Authors: Wenjiang Deng, Tian Mou, Yudi Pawitan, Trung Nghia Vu

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Estimation of isoform-level gene expression from RNA-seq data depends on simplifying assumptions, such as uniform reads distribution, that are easily violated in real data. Such violations typically lead to biased estimates. Most existing methods provide a bias correction step(s), which is based on biological considerations, such as GC content–and applied in single samples separately. The main problem is that not all biases are known. For example, new technologies such as single-cell RNA-seq (scRNA-seq) may introduce new sources of bias not seen in bulk-cell data. This study introduces a method called XAEM based on a more flexible and robust statistical model. Existing methods are essentially based on a linear model Xβ, where the design matrix X is known and derived based on the simplifying assumptions. In contrast, XAEM considers Xβ as a bilinear model with both X and β unknown. Joint estimation of X and β is made possible by simultaneous analysis of multi-sample RNA-seq data. Compared to existing methods, XAEM automatically performs empirical correction of potentially unknown biases. XAEM implements an alternating expectation-maximization (AEM) algorithm, alternating between estimation of X and β. For speed XAEM utilizes quasi-mapping for read alignment, thus leading to a fast algorithm. Overall XAEM performs favorably compared to other recent advanced methods. For simulated datasets, XAEM obtains higher accuracy for multiple-isoform genes, particularly for paralogs. In a differential-expression analysis of a real scRNA-seq dataset, XAEM achieves substantially greater rediscovery rates in an independent validation set.

Keywords: alternating EM algorithm, bias correction, bilinear model, gene expression, RNA-seq

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Authors: Abderrahman Hassi, Omar Bacadi, Khaoula Zitouni

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Abdelkader El Mouaziz is a Moroccan long-distance runner with a career-best time of 2:06:46 in the Chicago Marathon. El Mouaziz is a winner of the Madrid Marathon in 1994, the London Marathon in 1999 and 2001, as well as the New York Marathon in 2001. While he was playing for the Moroccan national team, he used to train in the Ifrane-Azrou region owing to its altitude, fresh forests, non-polluted air and quietness. After winning so many international competitions and retiring, he left his native Casablanca and went back to the Ifrane-Azrou region and started a business that employs ten people. In March 2010, El Mouaziz opened a bed and breakfast called Tourtite with a nice view on the mountain near the city of Ifrane in the way to Azrou. He wanted to give back to the region that helped him become a sport legend. His management style is not different than his sport style: performance and competitiveness combined with fair play. The objective of the present case study is to further enhance the understanding of the dynamics of transferring athletic championship-winning principles to entrepreneurial activities. The case study is a real-life situation and experience designed to provoke and stimulate reflections about a particular approach of management, especially for start-up businesses.

Keywords: sport, winning principles, entrepreneurship, Abdelkader El Mouaziz

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

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

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

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Authors: Mustafa Yıldız, Ali Ulvi Uzer, Murat Olgun

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In this study, geotechnical and mineralogical properties of gypsum containing clay basis which form the ground of Second Organized Industrial Zone in Konya province have been researched through comprehensive field and laboratory experiments. Although sufficient geotechnical research has not been performed yet, an intensive structuring in the region continues at present. The study area consists of mid-lake sediments formed by gypsum containing soft silt-clay basis which evolves to a large area. To determine the soil profile and geotechnical specifications; 18 drilling holes were opened and disturbed / undisturbed soil samples have been taken through shelby tubes within 1.5m intervals. Tests have been performed on these samples to designate the index and strength properties of soil. Besides, at all drilling holes Standart Penetration Tests have been done within 1.5m intervals. For the purpose of determining the mineralogical characteristics of the soil; all rock and X-RD analysis have been carried out on 6 samples which were taken from various depths through the soil profile. Strength and compressibility characteristics of the soil were defined with correlations using laboratory and field test results. Unconfined compressive strength, undrained cohesion, compression index varies between 16 kN/m2 and 405.4 kN/m2, 6.5 kN/m2 and 72 kN/m2, 0.066 and 0.864, respectively.

Keywords: Konya second organized industrial region, strength, compressibility, soft clay

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Authors: Ahmed Fradi

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In a digital world in perpetual evolution and acceleration, data more and more voluminous, rich and varied, the new software solutions emerged with the Big Data phenomenon offer new opportunities to the company enabling it not only to optimize its business and to evolve its production model, but also to reorganize itself to increase competitiveness and to identify new strategic axes. Design and manufacturing industrial companies, like the others, face these challenges, data represent a major asset, provided that they know how to capture, refine, combine and analyze them. The objective of our paper is to propose a solution allowing geometric and topological information extraction from 3D CAD model (precisely STEP files) databases, with specific algorithm based on the programming paradigm MapReduce. Our proposal is the first step of our future approach to 3D CAD object retrieval.

Keywords: Big Data, MapReduce, 3D object retrieval, CAD, STEP format

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Authors: Rohit Mittal, Bright Keswani, Amit Mithal

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This paper provides a sense about the application of computational intelligence techniques used to develop computer games, especially car racing. For the deep sense and knowledge of artificial intelligence, this paper is divided into various sections that is optimization, imitation, innovation and combining approach of optimization and imitation. This paper is mainly concerned with combining approach which tells different aspects of using fitness measures and supervised learning techniques used to imitate aspects of behavior. The main achievement of this paper is based on modelling player behaviour and evolving new game content such as racing tracks as single car racing on single track.

Keywords: evolution algorithm, genetic, optimization, imitation, racing, innovation, gaming

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Authors: Xu Han, Shanxiong Chen, Shiyu Zhu, Xiaoyu Lin, Fujia Zhao, Dingwang Wang

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Character detection is an important issue for character recognition of ancient Yi books. The accuracy of detection directly affects the recognition effect of ancient Yi books. Considering the complex layout, the lack of standard typesetting and the mixed arrangement between images and texts, we propose a character detection method for ancient Yi books based on connected components and regressive character segmentation. First, the scanned images of ancient Yi books are preprocessed with nonlocal mean filtering, and then a modified local adaptive threshold binarization algorithm is used to obtain the binary images to segment the foreground and background for the images. Second, the non-text areas are removed by the method based on connected components. Finally, the single character in the ancient Yi books is segmented by our method. The experimental results show that the method can effectively separate the text areas and non-text areas for ancient Yi books and achieve higher accuracy and recall rate in the experiment of character detection, and effectively solve the problem of character detection and segmentation in character recognition of ancient books.

Keywords: CCS concepts, computing methodologies, interest point, salient region detections, image segmentation

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Authors: Jimoh Abiodun Alaba

Abstract:

Context: In many traditional African societies, sex education is often considered a taboo topic. However, the importance of sex education is becoming increasingly evident. This study aims to investigate the challenges faced in teaching sex education in selected secondary schools in the Akoko region of Ondo state, Nigeria. Research Aim: The aim of this study is to identify and examine the problems confronting the teaching of sex education in selected secondary schools in the Akoko region of Ondo state, Nigeria. Methodology: The study utilized a multi-stage sampling method. The first stage involved a purposive selection of ten (10) secondary schools in the Akoko region of Ondo State, while the second stage was a random selection of twenty (20) students, each in the selected secondary schools of the study area. This makes a total of two (200) hundred students that were considered for the survey. Descriptive analysis using percentages was employed to analyze the collected data. Factor analysis was also used to identify the most significant problems. Findings: The study revealed that sex education has been neglected in the sampled secondary schools due to traditional African beliefs that do not support the teaching and learning of this subject. Furthermore, there was evidence to suggest that parents also displayed reluctance towards the teaching of sex education, fearing that it might expose students to inappropriate behavior. Consequently, students were deprived of this essential aspect of education necessary for self-awareness and development. Theoretical Importance: This study contributes to the understanding of the challenges faced in teaching sex education in traditional African societies, specifically in the selected secondary schools in the Akoko region of Ondo state, Nigeria. Data Collection: Data were collected through the administration of 200 questionnaires in ten selected secondary schools. Additionally, information was gathered from federal, state, and local government authorities. Analysis Procedures: The collected data were analyzed using descriptive analysis, employing percentage calculations for better interpretation. Furthermore, factor analysis was conducted to isolate the most significant problems identified. Conclusion: The study concludes that sex education in the sampled secondary schools in the Akoko region of Ondo state, Nigeria, has suffered neglect due to traditional African beliefs and parental concerns. Consequently, students are denied an important aspect of education necessary for their self-awareness and development. Recommendations are made to change the negative perception of sex education, enrich the curriculum, and employ qualified personnel for its teaching. Additionally, it is suggested that sex education should be integrated with moral instruction.

Keywords: African traditional belief, sex, sex education, sexual misdemeanor, morality

Procedia PDF Downloads 85

Authors: Clare S. Sullivan

Abstract:

The high desert of central Oregon, USA is a challenging growing environment: short growing season (70-100 days); average annual precipitation of 280 mm; drastic swings in diurnal temperatures; possibility of frost any time of year; and sandy soils low in organic matter. Despite strong demand, there is almost no fruit grown in central Oregon due to potential yield loss caused by early and late frosts. Elsewhere in the USA, protected culture (i.e., high tunnels) has been used to extend fruit production seasons and improve yields. In central Oregon, high tunnels are used to grow multiple high-value vegetable crops, and farmers are unlikely to plant a perennial crop in a high tunnel unless proven profitable. In May 2019, two berry trials were established on a farm in Alfalfa, OR, to evaluate raspberry and strawberry yield, season length, and fruit quality in protected (high tunnels) vs. unprotected culture (open field). The main objective was to determine whether high tunnel berry production is a viable enterprise for the region. Each trial was arranged using a split-plot design. The main factor was the production system (high tunnel vs. open field), and the replicated, subplot factor was berry variety. Four day-neutral strawberry varieties and four primocane-bearing raspberry varieties were planted for the study and were managed using organic practices. Berries were harvested once a week early in the season, and twice a week as production increased. Harvested berries were separated into ‘marketable’ and ‘unmarketable’ in order to calculate percent cull. First-year results revealed berry yield and quality differences between varieties and production systems. Strawberry marketable yield and berry fruit size increased significantly in the high tunnel compared to the field; percent yield increase ranged from 7-46% by variety. Evie 2 was the highest yielding strawberry, although berry quality was lower than other berries. Raspberry marketable yield and berry fruit size tended to increase in the high tunnel compared to the field, although variety had a more significant effect. Joan J was the highest yielding raspberry and out-yielded the other varieties by 250% outdoor and 350% indoor. Overall, strawberry and raspberry yields tended to improve in high tunnels as compared to the field, but data from a second year will help determine whether high tunnel investment is worthwhile. It is expected that the production system will have more of an effect on berry yield and season length for second-year plants in 2020.

Keywords: berries, high tunnel, local food, organic

Procedia PDF Downloads 118

Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao

Abstract:

Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.

Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization

Procedia PDF Downloads 128

Authors: H. E. Budak, B. Arslan-Ilkiz, N. Cakmakci, I. Gocek, U. K. Sahin, H. Acikgoz-Tufan, M. H. Arslan

Abstract:

The aim of this study is to design a novel laundry algorithm for colored textiles which have significant decoloring problem. During the experimental work, bleached knitted single jersey fabric made of 100% cotton and dyed with reactive dyestuff was utilized, since according to a conducted survey textiles made of cotton are the most demanded textile products in the textile market by the textile consumers and for coloration of textiles reactive dyestuffs are the ones that are the most commonly used in the textile industry for dyeing cotton-made products. Therefore, the fabric used in this study was selected and purchased in accordance with the survey results. The fabric samples cut out of this fabric were dyed with different dyeing parameters by using Remazol Brilliant Red 3BS dyestuff in Gyrowash machine at laboratory conditions. From the alternative reactive-dyed cotton fabric samples, the ones that have high tendency to color loss were determined and examined. Accordingly, the parameters of the dyeing process used for these fabric samples were evaluated and the dyeing process which was chosen to be used for causing high tendency to color loss for the cotton fabrics was determined in order to reveal the level of improvement in color loss during this study clearly. Afterwards, all of the untreated fabric samples cut out of the fabric purchased were dyed with the dyeing process selected. When dyeing process was completed, an experimental design was created for the laundering process by using Minitab® program considering temperature, time and mechanical action as parameters. All of the washing experiments were performed in domestic washing machine. 16 washing experiments were performed with 8 different experimental conditions and 2 repeats for each condition. After each of the washing experiments, water samples of the main wash of the laundering process were measured with UV spectrophotometer. The values obtained were compared with the calibration curve of the materials used for the dyeing process. The results of the washing experiments were statistically analyzed with Minitab® program. According to the results, the most suitable washing algorithm to be used in terms of the parameters temperature, time and mechanical action for domestic washing machines for minimizing fabric color loss was chosen. The laundry algorithm proposed in this study have the ability of minimalizing the problem of color loss of colored textiles in washing machines by eliminating the negative effects of the parameters of laundering process on color of textiles without compromising the fundamental effects of basic cleaning action being performed properly. Therefore, since fabric color loss is minimized with this washing algorithm, dyestuff residuals will definitely be lower in the grey water released from the laundering process. In addition to this, with this laundry algorithm it is possible to wash and clean other types of textile products with proper cleaning effect and minimized color loss.

Keywords: color loss, laundry algorithm, textiles, domestic washing process

Procedia PDF Downloads 358