Search results for: growth signals

Authors: Dimitrios Triantakonstantis, Demetris Stathakis

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Urban areas have been expanded throughout the globe. Monitoring and modeling urban growth have become a necessity for a sustainable urban planning and decision making. Urban prediction models are important tools for analyzing the causes and consequences of urban land use dynamics. The objective of this research paper is to analyze and model the urban change, which has been occurred from 1990 to 2000 using CORINE land cover maps. The model was developed using drivers of urban changes (such as road distance, slope, etc.) under an Artificial Neural Network modeling approach. Validation was achieved using a prediction map for 2006 which was compared with a real map of Urban Atlas of 2006. The accuracy produced a Kappa index of agreement of 0,639 and a value of Cramer's V of 0,648. These encouraging results indicate the importance of the developed urban growth prediction model which using a set of available common biophysical drivers could serve as a management tool for the assessment of urban change.

Keywords: artificial neural networks, CORINE, urban atlas, urban growth prediction

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Authors: Edwin Forero-Garcia, Jaime Vitola, Brayan Cardenas, Johan Casagua

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This research article presents the integration of electronic and computer systems, which developed an ultrasonic signal processing system that performs the capture, adaptation, and analog-digital conversion to later carry out its processing and visualization. The capture and adaptation of the signal were carried out from the design and implementation of an analog electronic system distributed in stages: 1. Coupling of impedances; 2. Analog filter; 3. Signal amplifier. After the signal conditioning was carried out, the ultrasonic information was digitized using a digital microcontroller to carry out its respective processing. The digital processing of the signals was carried out in MATLAB software for the elaboration of A-Scan, B and D-Scan types of ultrasonic images. Then, advanced processing was performed using the SAFT technique to improve the resolution of the Scan-B-type images. Thus, the information from the ultrasonic images was displayed in a user interface developed in .Net with Visual Studio. For the validation of the system, ultrasonic signals were acquired, and in this way, the non-invasive inspection of the structures was carried out and thus able to identify the existing pathologies in them.

Keywords: acquisition, signal processing, ultrasound, SAFT, HMI

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Authors: Rayhaneh Amooaghaie, Maryam Norouzi

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In this study, the effects of nTiO₂ on seed germination and growth of six plant species (wheat, soybean, tomato, canola, cucumber, and lettuce) were evaluated in petri dish (direct exposure) and in soil in a greenhouse experiment (soil exposure). Data demonstrate that under both culture conditions, low or mild concentrations of nTiO₂ either stimulated or had no effect on seed germination, root growth and vegetative biomass while high concentrations had an inhibitory effect. However, results showed that the impacts of nTiO₂ on plant growth in soil were partially consistent with those observed in pure culture. Based on both experiment sets, among above six species, lettuce and canola were the most susceptible and the most tolerant species to nTiO₂ toxicity. However, results revealed the impacts of nTiO₂ on plant growth in soil were less than petri dish exposure probability due to dilution in soil and complexation/aggregation of nTiO₂ that would lead to lower exposure of plants. The high concentrations of nTiO₂ caused significant reductions in fresh and dry weight of aerial parts and root and chlorophyll and carotenoids contents of all species which also coincided with further accumulation of malondialdehyde (MDA). These findings suggest that decreasing growth might be the result of an nTiO₂-induced oxidative stress and disturbance of photosynthesis systems.

Keywords: chlorophyll, lipid peroxidation, nano TiO₂, seed germination

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Authors: Zehra Aytac, Nurdilek Gulmezoglu

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Safflower has been grown for centuries for many purposes worldwide. Especially it is important for the orange-red dye from its petal and for its high-quality oil obtained from the seeds. The crop is high adaptable to areas with insufficient rainfall and poor soil conditions. The plant has a deep taproot that can draw moisture and plant nutrients from deep to the subsoil. The research was carried out to study the nitrogen (N) uptake of different safflower cultivars and lines at different stages of growth and different plant parts in the experimental field of Faculty of Agriculture, Eskişehir Osmangazi University under semi-arid conditions. Different safflower cultivars and lines of varied origins were used as the material. The cultivars and lines were planted in a Randomized Complete Block Design with three replications. Two different growth stages (flowering and harvest) and three different plant parts (head, stem+leaf and seed) were determined. The nitrogen concentration of different plant parts was determined by the Kjeldahl method. Statistical analysis were performed by analysis of variance for each growth stage and plant parts taking a level of p < 0.05 and p < 0.01 as significant according to the LSD test. As a result, N concentration showed significant differences among different plant parts and different growth stages for different safflower genotypes of varied origins.

Keywords: Carthamus tinctorius L., growth stages, head N, leaf N, N uptake, seed N, Safflower

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Authors: Mohamed Aymen Slim, Afef Abdelkrim, Mohamed Benrejeb

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The handwriting is a physical demonstration of a complex cognitive process learnt by man since his childhood. People with disabilities or suffering from various neurological diseases are facing so many difficulties resulting from problems located at the muscle stimuli (EMG) or signals from the brain (EEG) and which arise at the stage of writing. The handwriting velocity of the same writer or different writers varies according to different criteria: age, attitude, mood, writing surface, etc. Therefore, it is interesting to reconstruct an experimental basis records taking, as primary reference, the writing speed for different writers which would allow studying the global system during handwriting process. This paper deals with a new approach of the handwriting system modeling based on the velocity criterion through the concepts of artificial neural networks, precisely the Radial Basis Functions (RBF) neural networks. The obtained simulation results show a satisfactory agreement between responses of the developed neural model and the experimental data for various letters and forms then the efficiency of the proposed approaches.

Keywords: Electro Myo Graphic (EMG) signals, experimental approach, handwriting process, Radial Basis Functions (RBF) neural networks, velocity modeling

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Authors: HengJiang Cai, RuiJin Zhang, JinSong Gui

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Enhanced UV-B (280-320nm) radiation resulting from ozone depletion was one of the global environmental problems. The effects of enhanced UV-B radiation on marine macro-algae were exposed to be the greatest in shallow intertidal environments because the macro-alga was often at or above the water during low tide. Ulva pertusa Kjellman was belonged to Chlorophyta (Phylum), Ulvales (Order), Ulvaceae (Family) which was widely distributed in the western Pacific coast, and the resources were extremely rich in China. Therefore, the effects of UV-B radiation on the growth of Ulva pertusa seedling were studied in this research. Ulva pertusa seedling appearances were mainly characterized by rod shapes and tadpole shapes. The percentage of rod shapes was 90.68%±2.50%. UV-B radiation could inhibit the growth of Ulva pertusa seedling, and the growth inhibition was more significant with the increased doses of UV-B radiation treatment. The relative inhibition rates of Ulva pertusa seedling length were16.11%, 24.98%and 39.04% respectively on the 30th day at different doses (30.96, 61.92 and 123.84 Jm-2d-1) of UV-B radiation. Ulva pertusa seedling had emerged death under UV-B radiation, and the death rates were increased with the increased doses of UV-B radiation treatment. Physiology and biochemistry of Ulva pertusa seedling could be affected by UV-B radiation treatment. The SOD (superoxide dismutase) activity was increased at low-dose UV-B radiation (30.96 Jm-2d-1), while was decreased at high-dose UV-B radiation (61.92 and 123.84 Jm-2d-1). UV-B radiation could inhibit CAT (catalase) activity all the while. It speculated that the reasons for growth inhibition and death of Ulva pertusa seedling were excess ROS (reactive oxygen species), which produced by UV-B radiation.

Keywords: growth, physiology and biochemistry, Ulva pertusa Kjellman, UV-B radiation

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Authors: Kweon Oh-Sang, Kim Heung-Youl

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Estimating the engineering properties of fires is important to be prepared for the complex and various fire risks of large-scale structures such as super-tall buildings, large stadiums, and multi-purpose structures. In this study, a mock-up of a compartment which was 2.4(L) x 3.6 (W) x 2.4 (H) meter in dimensions was fabricated at the 10MW LSC (Large Scale Calorimeter) and combustible office supplies were placed in the compartment for a real-scale fire test. Maximum heat release rate was 4.1 MW and total energy release obtained through the application of t2 fire growth rate was 6705.9 MJ.

Keywords: fire growth, fire experiment, t2 curve, large scale calorimeter

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Authors: Ademoyegun Olusegun

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The advancement of industry in any given state involves a range of processes that entail entrepreneurship and innovative skill attainment, among others, for the development of an economy. This article studied the impact of innovative and entrepreneurship skill attainment as the panacea of the growth of industry for economic development in Nigeria. Content analysis was employed as an instrument on data obtained from secondary resources which include journals, magazines, Workshop Articles, the Internet, interviewing etc. this is preferred because of the absence of sequential data related to entrepreneurship and innovation on sustainable economic growth in Nigeria. The theory of innovative Entrepreneurship was used as a theoretical framework. Findings revealed that Entrepreneurship skill attainment will induce innovation that will accelerate the growth of Industry for the advancement of the Economy. The study recommended that the government should invest adequately in entrepreneurship skill attainment and create an enabling environment for innovation.

Keywords: entrepreneurship, innovation, skill attainment, panacea, sustainable development

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Authors: Elnaz Lashgari, Emel Demircan

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Electromyography (EMG) is one of the most important interfaces between humans and robots for rehabilitation. Decoding this signal helps to recognize muscle activation and converts it into smooth motion for the robots. Detecting each muscle’s pattern during walking and running is vital for improving the quality of a patient’s life. In this study, EMG data from 10 muscles in 10 subjects at 4 different speeds were analyzed. EMG signals are nonlinear with high dimensionality. To deal with this challenge, we extracted some features in time-frequency domain and used manifold learning and Laplacian Eigenmaps algorithm to find the intrinsic features that represent data in low-dimensional space. We then used the Bayesian classifier to identify various patterns of EMG signals for different muscles across a range of running speeds. The best result for vastus medialis muscle corresponds to 97.87±0.69 for sensitivity and 88.37±0.79 for specificity with 97.07±0.29 accuracy using Bayesian classifier. The results of this study provide important insight into human movement and its application for robotics research.

Keywords: electromyography, manifold learning, ISOMAP, Laplacian Eigenmaps, locally linear embedding

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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: Beatriz Lafuente Alcázar, Yash Wani, Amit J. Nimunkar

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Cardiovascular Diseases (CVDs) are the leading cause of death globally, and around 80% of sudden cardiac deaths are due to arrhythmias or irregular heartbeats. The majority of these pathologies are revealed by either short-term or long-term alterations in the electrocardiogram (ECG) morphology. The ECG is the main diagnostic tool in cardiology. It is a non-invasive, pain free procedure that measures the heart’s electrical activity and that allows the detecting of abnormal rhythms and underlying conditions. A cardiologist can diagnose a wide range of pathologies based on ECG’s form alterations, but the human interpretation is subjective and it is contingent to error. Moreover, ECG records can be quite prolonged in time, which can further complicate visual diagnosis, and deeply retard disease detection. In this context, deep learning methods have risen as a promising strategy to extract relevant features and eliminate individual subjectivity in ECG analysis. They facilitate the computation of large sets of data and can provide early and precise diagnoses. Therefore, the cardiology field is one of the areas that can most benefit from the implementation of deep learning algorithms. In the present study, a deep learning algorithm is trained following a novel approach, using a combination of different databases as the training set. The goal of the algorithm is to achieve the detection of R-peaks in ECG signals. Its performance is further evaluated in ECG signals with different origins and features to test the model’s ability to generalize its outcomes. Performance of the model for detection of R-peaks for clean and noisy ECGs is presented. The model is able to detect R-peaks in the presence of various types of noise, and when presented with data, it has not been trained. It is expected that this approach will increase the effectiveness and capacity of cardiologists to detect divergences in the normal cardiac activity of their patients.

Keywords: arrhythmia, deep learning, electrocardiogram, machine learning, R-peaks

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Authors: Nagini Sabbineni, Rajini T. V. Kanth, B. V. Kiranmayee

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India’s economy primarily depends on agriculture yield growth and their allied agro industry products. The agriculture yield prediction is the toughest task for agricultural departments across the globe. The agriculture yield depends on various factors. Particularly countries like India, majority of agriculture growth depends on rain water, which is highly unpredictable. Agriculture growth depends on different parameters, namely Water, Nitrogen, Weather, Soil characteristics, Crop rotation, Soil moisture, Surface temperature and Rain water etc. In our paper, lot of Explorative Data Analysis is done and various predictive models were designed. Further various regression models like Linear, Multiple Linear, Non-linear models are tested for the effective prediction or the forecast of the agriculture yield for various crops in Andhra Pradesh and Telangana states.

Keywords: agriculture yield growth, agriculture yield prediction, explorative data analysis, predictive models, regression models

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Authors: S. S. Singh, A. Bhattacharya, S. Bhattacharya

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The eukaryotic exosome complex plays a pivotal role in RNA biogenesis, maturation, surveillance and differential expression of various RNAs in response to varying environmental signals. The exosome is composed of evolutionary conserved nine core subunits and the associated exonucleases Rrp6 and Rrp44. Rrp6p is crucial for the processing of rRNAs, other non-coding RNAs, regulation of polyA tail length and termination of transcription. Rrp6p, a 3’-5’ exonuclease is required for degradation of 5’-external transcribed spacer (ETS) released from the rRNA precursors during the early steps of pre-rRNA processing. In the parasitic protist Entamoeba histolytica in response to growth stress, there occurs the accumulation of unprocessed pre-rRNA and 5’ ETS sub fragment. To understand the processes leading to this accumulation, we looked for Rrp6 and the exosome subunits in E. histolytica, by in silico approaches. Of the nine core exosomal subunits, seven had high percentage of sequence similarity with the yeast and human. The EhRrp6 homolog contained exoribonuclease and HRDC domains like yeast but its N- terminus lacked the PMC2NT domain. EhRrp6 complemented the temperature sensitive phenotype of yeast rrp6Δ cells suggesting conservation of biological activity. We showed 3’-5’ exoribonuclease activity of EhRrp6p with in vitro-synthesized appropriate RNAs substrates. Like the yeast enzyme, EhRrp6p degraded unstructured RNA, but could degrade the stem-loops slowly. Furthermore, immunolocalization revealed that EhRrp6 was nuclear-localized in normal cells but was diminished from nucleus during serum starvation, which could explain the accumulation of 5’ETS during stress. Our study shows functional conservation of EhRrp6p in E.histolytica, an early-branching eukaryote, and will help to understand the evolution of exosomal components and their regulatory function.

Keywords: entamoeba histolytica, exosome complex, rRNA processing, Rrp6

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Authors: R. S. Hassani, S. Chikh, L. Tadrist, S. Radev

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A bubbly flow in a vertical miniature tube is analyzed theoretically. The liquid and gas phase are co-current flowing upward. The gas phase is injected via a nozzle whose inner diameter is 0.11mm and it is placed on the axis of the tube. A force balance is applied on the bubble at its detachment. The set of governing equations are solved by use of Mathematica software. The bubble diameter and the bubble generation frequency are determined for various inlet phase velocities represented by the inlet mass quality. The results show different behavior of bubble growth and detachment depending on the tube size.

Keywords: two phase flow, bubble growth, mini-channel, generation frequency

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Authors: Maxime Farin, Emmanuel Moulin, Lynda Chehami, Farouk Benmeddour, Pierre Campistron

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Assessing corrosion is crucial in the petrochemical and marine industry. Usual ultrasonic methods based on guided waves to detect corrosion can inspect large areas but lack precision. We propose a complementary and sensitive ultrasonic method (~ 10 MHz) based on coda wave interferometry to detect and quantify corrosion at the surface of a steel sample. The method relies on a single piezoelectric transducer, exciting the sample and measuring the scattered coda signals at different instants in time. A laboratory experiment is conducted with a steel sample immersed in salted water for 60~h with parallel coda and temperature measurements to correct coda dependence to temperature variations. Micrometric changes to the sample surface caused by corrosion are detected in the late coda signals, allowing precise corrosion detection. Moreover, a good correlation is found between a parameter quantifying the temperature-corrected stretching of the coda over time with respect to a reference without corrosion and the corrosion surface over the sample recorded with a camera.

Keywords: coda wave interferometry, nondestructive evaluation, corrosion, ultrasonics

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Authors: Isabela Romanha de Alcantara, Jose Eustaquio Ribeiro Vieira Filho, Jose Garcia Gasques

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Innovation and technology can be determinant factors to ensure agricultural and sustainable growth, as well as productivity gains. Technical change has contributed considerably to supply agricultural expansion in Brazil. This agricultural growth could be achieved by incorporating more land or capital. If capital is the main source of agricultural growth, it is possible to increase production per unit of land. The objective of this paper is to estimate: 1) total factor productivity (TFP), which is measured in terms of the rate of output per unit of input; and 2) the land-saving effect (LSE) that is the amount of land required in the case that yield rate is constant over time. According to this study, from 1990 to 2019, it appears that 87 percent of Brazilian agriculture product growth comes from the gains of productivity; the rest of 13 percent comes from input growth. In the same period, the total LSE was roughly 400 Mha, which corresponds to 47 percent of the national territory. These effects reflect the greater efficiency of using productive factors, whose technical change has allowed an increase in agricultural production based on productivity gains.

Keywords: agriculture, land-saving effect, livestock, productivity

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Authors: Ogunlana Olarewaju Fatai, Kelani Fatai Adeshina

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The interplay of corruption and institutional quality determines how effective and efficient an economy progresses. An efficient institutional quality is a key requirement for economic stability. Institutional quality in most cases has been used interchangeably with Governance and these have given room for proxies that legitimized Governance as measures for institutional quality. A poorly-tailored institutional quality has a penalizing effect on corruption and economic growth, while defective institutional quality breeds corruption. Corruption is a hydra-headed phenomenon as it manifests in different forms. The most celebrated definition of corruption is given as “the use or abuse of public office for private benefits or gains”. It also denotes an arrangement between two mutual parties in the determination and allocation of state resources for pecuniary benefits to circumvent state efficiency. This study employed Barro (1990) type augmented model to analyze the nexus among corruption, institutional quality and economic growth in Nigeria using annual time series data, which spanned the period 1996-2019. Within the analytical framework of Johansen Cointegration technique, Error Correction Mechanism (ECM) and Granger Causality tests, findings revealed a long-run relationship between economic growth, corruption and selected measures of institutional quality. The long run results suggested that all the measures of institutional quality except voice & accountability and regulatory quality are positively disposed to economic growth. Moreover, the short-run estimation indicated a reconciliation of the divergent views on corruption which pointed at “sand the wheel” and “grease the wheel” of growth. In addition, regulatory quality and the rule of law indicated a negative influence on economic growth in Nigeria. Government effectiveness and voice & accountability, however, indicated a positive influence on economic growth. The Granger causality test results suggested a one-way causality between GDP and Corruption and also between corruption and institutional quality. Policy implications from this study pointed at checking corruption and streamlining institutional quality framework for better and sustained economic development.

Keywords: institutional quality, corruption, economic growth, public policy

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Authors: Sahbi Farhani

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This study investigates the relationship between external debt and military spending in case of India over the period of 1970–2012. In doing so, we have applied the structural break unit root tests to examine stationarity properties of the variables. The Auto-Regressive Distributed Lag (ARDL) bounds testing approach is used to test whether cointegration exists in presence of structural breaks stemming in the series. Our results indicate the cointegration among external debt, military spending, debt servicing, and economic growth. Moreover, military spending and debt servicing add in external debt. Economic growth helps in lowering external debt. The Vector Error Correction Model (VECM) analysis and Granger causality test reveal that military spending and economic growth cause external debt. The feedback effect also exists between external debt and debt servicing in case of India.

Keywords: external debt, military spending, ARDL approach, India

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Authors: Sanusi Abdullahi, Musa Momoh, Abubakar Umar Moreh, Aminu Muhammad Bayawa, Olubunmi Popoola

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Kesterite-type Cu₂ZnSnS₄ (CZTS) thin films were deposited on corning glass from a single quaternary target. In this study, we investigated the growth mechanism and the influence of thin film thickness on the structural and compositional properties of CZTS films. All the four samples (as-deposited inclusive) show peaks corresponding to kesterite-type structure. The diffraction peaks of (112) are sharp and the small characteristics peaks of the kesterite structure such as (220)/ (204) and (312)/ (116) are also clearly observed in X-ray diffraction pattern. These results indicate that the quaternary CZTS would be a potential candidate for solar cell applications.

Keywords: RF sputtering, Cu2ZnSnS4 thin film, annealing, growth mechanism, annealing, growth mechanism, renewable energy

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Authors: O. R. Obalowu, F. B. Akande, T. P Abegunrin

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Maize (Zea may) is mostly grown and consumed by Nigeria farmers using different tillage practices which have a great effect on its growth and yield. In order to maximize output, there is need to recommend a suitable tillage practice for crop production which will increase the growth and yield of maize. This study investigated the effect of tillage practices and planting pattern on the growth and yield of maize. The experiment was arranged in a 4x3x3 Randomized Complete Block Design (RCBD) layout, with four tillage practices consisting of no-tillage (NT), disc ploughing only (Ponly), disc ploughing followed by harrowing (PH), and disc ploughing, harrowing then ridging (PHR). Three planting patterns which include; 65 x 75, 75 x 75 and 85 x 75 cm spacing within and between the rows respectively, were randomly applied on the plots. All treatments were replicated three times. Data which consist of plant height, stem girth, leaf area and weight of maize per plots were taken and recorded. Data gathered were analyzed using Analysis of Variance (ANOVA) in the Minitab Software Package. The result shows that PHR under the third planting pattern has the highest growth rate (216.50 cm) while NT under the first planting pattern has the lowest mean value of growth rate (115.60 cm). Also, Ponly under the first planting pattern gives a better maize yield (19.45 kg) when compared with other tillage practices while NT under first planting pattern recorded the least yield of maize (9.40 kg). In conclusion, considering soil and weather conditions of the research area, plough only under the first planting pattern (65 x 75 cm) is the best alternative for the production of the Swan maize variety.

Keywords: tillage practice, planting pattern, disc ploughing, harrowing, ridging

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Authors: Souvik Phadikar, Nidul Sinha, Rajdeep Ghosh

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In brainwaves research using electroencephalogram (EEG) signals, finding the most relevant and effective feature set for identification of activities in the human brain is a big challenge till today because of the random nature of the signals. The feature extraction method is a key issue to solve this problem. Finding those features that prove to give distinctive pictures for different activities and similar for the same activities is very difficult, especially for the number of activities. The performance of a classifier accuracy depends on this quality of feature set. Further, more number of features result in high computational complexity and less number of features compromise with the lower performance. In this paper, a novel idea of the selection of optimal feature set using a heuristically optimized deep autoencoder is presented. Using various feature extraction methods, a vast number of features are extracted from the EEG signals and fed to the autoencoder deep neural network. The autoencoder encodes the input features into a small set of codes. To avoid the gradient vanish problem and normalization of the dataset, a meta-heuristic search algorithm is used to minimize the mean square error (MSE) between encoder input and decoder output. To reduce the feature set into a smaller one, 4 hidden layers are considered in the autoencoder network; hence it is called Heuristically Optimized Deep Autoencoder (HO-DAE). In this method, no features are rejected; all the features are combined into the response of responses of the hidden layer. The results reveal that higher accuracy can be achieved using optimal reduced features. The proposed HO-DAE is also compared with the regular autoencoder to test the performance of both. The performance of the proposed method is validated and compared with the other two methods recently reported in the literature, which reveals that the proposed method is far better than the other two methods in terms of classification accuracy.

Keywords: autoencoder, brainwave signal analysis, electroencephalogram, feature extraction, feature selection, optimization

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Authors: Toufik Bensana, Slimane Mekhilef, Kamel Tadjine

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Vibration analysis has been frequently applied in the condition monitoring and fault diagnosis of rolling element bearings. Unfortunately, the vibration signals collected from a faulty bearing are generally non stationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA) and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. The results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

Keywords: fault diagnosis, condition monitoring, local mean decomposition, rolling element bearing, vibration analysis

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Authors: Shiksha Jain, Ramesh Mishra

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One of the most widely used complex signals processing operation is filtering. The most important FIR digital filter are widely used in DSP for filtering to alter the spectrum according to some given specifications. Power consumption and Area complexity in the algorithm of Finite Impulse Response (FIR) filter is mainly caused by multipliers. So we present a multiplier less technique (DA technique). In this technique, precomputed value of inner product is stored in LUT. Which are further added and shifted with number of iterations equal to the precision of input sample. But the exponential growth of LUT with the order of FIR filter, in this basic structure, makes it prohibitive for many applications. The significant area and power reduction over traditional Distributed Arithmetic (DA) structure is presented in this paper, by the use of slicing of LUT to the desired length. An architecture of 16 tap FIR filter is presented, with different length of slice of LUT. The result of FIR Filter implementation on Xilinx ISE synthesis tool (XST) vertex-4 FPGA Tool by using proposed method shows the increase of the maximum frequency, the decrease of the resources as usage saving in area with more number of slices and the reduction dynamic power.

Keywords: multiplier less technique, linear phase symmetric FIR filter, FPGA tool, look up table

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Authors: Sarah Jorjani, Afshin Ghelichi, Mazyar Kamali

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The aim of this study was to estimate the effect of addition of ginger and red pepper and their mixture in diet on growth performance, survival rate and body composition of Astronotus ocellatus (Oscar fish). This study had been carried out for 8 weeks. For this reason 132 oscar fishes with intial weight of 2.44±0.26 (gr) were divided into 4 treatments with three replicate as compeletly randomize design test and fed by 100% Biomar diet (T1), Biomar + red pepper (55 mg/kg) (T2), Biomar + ginger (1%) (T3) and Biomar + mixture of red pepper and ginger (T4).The fish were fed in 5% of their body weight. The results showed T2 have significant differences in most of growth parameters in compare with other treatments, such as PBWI, SGR, PER and SR (P < 0.05), but there were no significant differences between treatments in FCR and FE (P > 0.05).

Keywords: red pepper, ginger, oscar fish, growth performance, body composition

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Authors: Manoela Cabo da Silva, Elton Fernandes, Ricardo Pacheco, Heloisa Pires

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This study examined cointegration and causal relationships between economic growth and regular domestic and international passenger air transport in Brazil. Total passengers embarked and disembarked were used as a proxy for air transport activity and gross domestic product (GDP) as a proxy for economic development. The test spanned the period from 2000 to 2015 for domestic passenger traffic and from 1995 to 2015 for international traffic. The results confirm the hypothesis that there is cointegration between passenger traffic series and economic development, showing a bi-directional Granger causal relationship between domestic traffic and economic development and unidirectional influence by economic growth on international passenger air transport demand. Variance decomposition of the series showed that domestic air transport was far more important than international transport to promoting economic development in Brazil.

Keywords: air passenger transport, cointegration, economic growth, GDP, Granger causality

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Authors: E. O. E. Nnadi

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Transportation is a critical factor in the economic growth and development of any nation, region or state. Good transportation network supports every sector of the economy like the manufacturing, transportation and encourages investors thereby affect the overall economic prosperity. The paper evaluates the impact of transportation on the economic growth of Nigeria using south eastern states as a case study. The choice of the case study is its importance as the commercial and industrial nerve of the country. About 200 respondents who are of different professions such as dealers in goods, transporters, contractors, consultants, bankers were selected and a set of questionnaire were administered to using the systematic sampling technique in the five states of the region. Descriptive statistics and relative importance index (RII) technique was employed for the analysis of the data gathered. The findings of the analysis reveal that Nigeria has the least effective ratio per population in Africa of 949.91 km/Person. Conclusion was drawn to improve road network in the area and the country as a whole to enhance the economic activities of the people.

Keywords: economic growth, south-east, transportation, transportation cost, Nigeria

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Authors: Shih-Ming Wang, Chun-Kai Yeh, Ming-Hwang Shie, Tai-Wei Lin, Chieh-Fu Chang

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This paper introduces a FPGA-based baseband signals generator (BSG) of X-band transmitter developed by National Space Organization (NSPO), Taiwan, for earth observation. In order to gain more flexibility for various applications, a number of modulation schemes, QPSK, DeQPSK and 8PSK 4D-TCM are included. For micro satellite scenario, the maximum symbol rate is up to 150Mbsps, and the EVM is as low as 1.9%. For CubeSat scenario, the maximum symbol rate is up to 60Mbsps, and the EVM is less than 1.7%. The maximum data rates are 412.5Mbps and 165Mbps, respectively. Besides, triple modular redundancy (TMR) scheme is implemented in order to reduce single event effect (SEE) induced by radiation. Finally, the theoretical error performance is provided based on comprehensive analysis, especially when BER is lower and much lower than 10⁻⁶ due to low error bit requirement of modern high-resolution earth remote-sensing instruments.

Keywords: X-band transmitter, FPGA (Field-Programmable Gate Array), CubeSat, micro satellite

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Authors: Kiran Nawaz, Waheed Anwar, Sehrish Iftikhar, Muhammad Nasir Subhani, Ahmad Ali Shahid

Abstract:

Plant growth promoting rhizobacteria (PGPR) have been extensively studied and applied for the biocontrol of many soilborne diseases. These rhizobacteria are very efficient against root rot and many other foliar diseases associated with solanaceous plants. These bacteria may inhibit the growth of various pathogens through direct inhibition of target pathogens or indirectly by the initiation of systemic resistance (ISR) which is active all over the complete plant. In the present study, 20 different rhizobacterial isolates were recovered from the root zone of healthy chili plants. All soil samples were collected from various chili-growing areas in Punjab. All isolated rhizobacteria species were evaluated in vitro and in vivo against Phytophthora capsici. Different species of Bacillus and Pseudomonas were tested for the antifungal activity against P. capsici the causal organism of Root rot disease in different crops together with chili. Dual culture and distance culture bioassay were carried out to study the antifungal potential of volatile and diffusible metabolites secreted from rhizobacteria. After seven days of incubation at 22°C, growth inhibition rate was recorded. Growth inhibition rate depended greatly on the tested bacteria and screening methods used. For diffusible metabolites, inhibition rate was 35-62% and 20-45% for volatile metabolites. The screening assay for plant growth promoting and disease inhibition potential of chili associated PGPR indicated 42-100% reduction in disease severity and considerable enhancement in roots fresh weight by 55-87%, aerial parts fresh weight by 35-65% and plant height by 65-76% as compared to untreated control and pathogen-inoculated plants. Pseudomonas flourescene, B. thuringiensis, and B. subtilis were found to be the most efficient isolates in inhibiting P. capsici radial growth, increase plant growth and suppress disease severity.

Keywords: rhizobacteria, chili, phytophthora, root rot

Procedia PDF Downloads 243

Authors: Ella Tyuryumina, Alexey Neznanov

Abstract:

This study is an attempt to obtain reliable data on the natural history of breast cancer growth. We analyze the opportunities for using classical mathematical models (exponential and logistic tumor growth models, Gompertz and von Bertalanffy tumor growth models) to try to describe growth of the primary tumor and the secondary distant metastases of human breast cancer. The research aim is to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoMPaS and corresponding software. We are interested in: 1) modelling the whole natural history of the primary tumor and the secondary distant metastases; 2) developing adequate and precise CoMPaS which reflects relations between the primary tumor and the secondary distant metastases; 3) analyzing the CoMPaS scope of application; 4) implementing the model as a software tool. The foundation of the CoMPaS is the exponential tumor growth model, which is described by determinate nonlinear and linear equations. The CoMPaS corresponds to TNM classification. It allows to calculate different growth periods of the primary tumor and the secondary distant metastases: 1) ‘non-visible period’ for the primary tumor; 2) ‘non-visible period’ for the secondary distant metastases; 3) ‘visible period’ for the secondary distant metastases. The CoMPaS is validated on clinical data of 10-years and 15-years survival depending on the tumor stage and diameter of the primary tumor. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer growth models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. The CoMPaS model and predictive software: a) fit to clinical trials data; b) detect different growth periods of the primary tumor and the secondary distant metastases; c) make forecast of the period of the secondary distant metastases appearance; d) have higher average prediction accuracy than the other tools; e) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoMPaS: the number of doublings for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases. The CoMPaS enables, for the first time, to predict ‘whole natural history’ of the primary tumor and the secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on the primary tumor sizes. Summarizing: a) CoMPaS describes correctly the primary tumor growth of IA, IIA, IIB, IIIB (T1-4N0M0) stages without metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and inception of the secondary distant metastases.

Keywords: breast cancer, exponential growth model, mathematical model, metastases in lymph nodes, primary tumor, survival

Procedia PDF Downloads 326

Authors: Sh. Edrisi, M. Moeeni, A. Farahbakhsh

Abstract:

To study the effect of nitrogenous additive spray solution on the efficacy of three herbicides i.e. pinoxaden (Trade name: Axial), sulfosulfuron+metsulfuron-methyl (Trade name: Total) and sulfosulfuron (Trade name: Apirus) in controlling wild barley (Hordeum spontaneum C. Koch), in different growth stages, a greenhouse experiment as a split plot in a completely randomized design in three replications was conducted. One month after treatments, all plants were harvested and growth parameters were determined. The data were analyzed with computer. The results showed that the herbicide applications with and without nitrogen additive caused significant reductions in growth parameters of wild barley at 2-4 leaf stage. However, the plants were not killed by this herbicide. Plants were killed completely due to applications of the two other herbicides i.e. Apirus and Total at 2-4 leaf. There was no significant difference between the effect of these two herbicides. There was no significant difference between the highest rate of each herbicide used alone and that of the lowest rate with nitrogenous additive.

Keywords: growth stage, herbicide, nitrogen, wild barley

Procedia PDF Downloads 241