An inter-view prediction technique using motion skip for multi-view video coding
Multiview video coding is an extension of H264/AVC. When an Multiview video coding bitstream is decoded, some views (named target views) are to be is played; some other views (named dependent views) may not be displayed but are needed for inter-view prediction of the target views. The original Multiview video coding design requires pictures of the dependent views to be fully decoded and stored. This entails both high decoding complexity and high memory consumption for the pictures in the views which are not intended for display, particularly when the number of dependent views is large. In this paper, a single motion compensation loop decoding scheme is introduced to address these disadvantages. The proposed scheme requires only partial decoding of pictures in dependent views and thus significantly reduces decoding complexity and memory consumption. The proposed method is based on the motion skip, wherein inter-view motion and coding mode prediction is exploited. Simulation results shows that the proposed scheme provides a substantial reduction of complexity and memory size, at the expense of only a minor compression efficiency loss, compared with multiple motion compensation loop decoding schemes for Multiview video coding.
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Analysis and simulation of multilevel inverter system
This paper deals with the simulation of three, five, seven and nine level output using H- bridge inverter. This paper presents H – bridge inverter simulated using MATLAB with different levels (like three, five, seven and nine level). The percentage (%) total harmonic distortion THD is calculated. The harmonic reduction is achieved by selecting appropriate switching angles. The functionality verification of the three level, five level, seven level and nine level output is done using MATLAB.
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Application of neural networks' modeling on optimal analysis and evaluation of e-learning systems' performance (time response approach)
This piece of research addresses an interdisciplinary challenging issue concerned with dynamical evaluation of e-Learning systems' performance. More precisely, it presents an interdisciplinary work integrating neuronal, psychology, cognitive, and computer sciences into educational environment. That's in order to introduce systematic analysis and dynamical evaluation of the adopted study for e-learners' time response (equivalently convergence time) phenomenon. Specifically, this work concentrates on dynamical evaluation of one measuring parameter fore-learning performance namely: time response. In other words, e-learner's response time has been adopted as an appropriate candidate learning parameter applicable for reaching optimal analysis and evaluation of e-learning systems performance. Herein, that time considered as period of time requested in order to reach correctly a pre-assigned (desired) output answer which determined by an e-learner while examined via Multiple Choice Questions (MCQ). At the macro-level, the paper proposed e-learner's response time affected mostly by two basic extrinsic and intrinsic educational factors. Firstly, that associated to effectiveness of e-learning environment such as communication signal to noise ratio, and learning rate value. Secondly, that tightly coupled with gain factor candidates' brain function and structure (synapses, axons, and dendrites).Such as the number of dynamically contributing neurons, and the gain factor of neuronal response function. Consequently, Artificial Neural Networks (ANNs) simulation has been adopted for realistic evaluation of timely dependent candidate's response till reaching desired correct output solution for any arbitrary MCQ exam. After successful timely updating of dynamical state pattern (synaptic weight vector), pre-assigned (desired) correct response is accomplished in accordance with coincidence learning modeling. The presented simulation has been developed towards quantified analysis of the highly specialized neurons' role performed to select correct answers to MCQ. Furthermore, the time response parameter considers individual differences of learners' brain role (considering various number of neurons), while performing selectivity (MCQ) processes. Finally, after running of suggested realistic simulation programs, some interesting conclusive results introduced.
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Assessment and Determination of Seed Corn Combine Harvesting Losses and Energy Consumption
Field evaluation to measuring combine losses was conducted typically on seed corn field because of high economic importance of seed corn in Iran. Because seed corn is alive, harvesting operation should be done precisely with fewer losses. For this purpose data were collected and analyzed for different cylinder and ground speeds. Pre-harvest, gathering, and processing losses were measured. The results showed the total harvesting loss was 9.30% which combine loss was almost 8.56% with feeding rate of 2.48 kg ears per second. The highest losses occur in processing (threshing) (5.39%) because of elimination all cracked seeds (any crack in seeds decrease the seed generation power). The effect of travel speed was significant for gathering and threshing (quality) losses while cylinder speed had a significant effect on threshing (quality and quantity) losses. The lowest total combine loss (7.60%) was measured at 3 km h-1 ground speed with 400 rpm cylinder speed and the highest value (7.19%) belonged to 5 km h-1 ground speed with 600 rpm cylinder speed. Energy consumption during harvesting seed corn was calculated 1.8 GJ ha-1 which the diesel fuel input was the highest energy consumer with almost 1.2 GJ ha-1 that was 70% of total energy use.
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Assessment of natural radioactivity levels in cement samples commonly used for construction in Lagos and Ogun State, Nigeria
The activity concentrations of natural radionuclides 238U, 232Th and 40K in the cement samples used for construction in Lagos and Ogun State Nigeria were measured by gamma spectrometry using a well-type NaI (Tl) detector. Radiological hazard assessments due to these natural radionuclides were carried out. The average activity concentrations of 238U, 232Th and 40K determined in the samples were 2.16, 7.82 and 114.3 Bq/kg respectively. The mean absorbed dose rate, the mean annual effective dose, excess lifetime cancer risk and annual gonadal equivalent dose in the samples analyzed were 9.59 nGy/h, 17.66 µSv/y, 67.99 (MPY)-1 and 69.07 µSv/y respectively. Values of radium equivalent activity (Raeq), external (Hex) and internal (Hin) hazard indices and gamma activity concentration index (I?) were also estimated. The results obtained in all cases are well below the world average. Therefore, cements produced in this part of the country are safe and considered to have negligible radiological impact on the health of the individuals exposed to them.
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Automatic method for enhancement and detection of curvilinear structure in 2-d geophysical image
The identification of linear structures are done in geophysical images. The problem of identification of curvilinear structures in real and synthetic geophysical images is faced for the first time. Here we propose a method for automatic enhancement and detection of curvilinear structures. The accurate identification of line structures in geophysical images plays an important role in geophysical interpretation and the detection of subsurface structures. The method was applied on geophysical images in an effort to recognize the linear patterns of subsurface architectural structures that exist in archaeological sites. The method efficiently combines a rotation and Scale-invariant filter and a pixel-labelling method, providing a robust enhancement and detection of mostly line structures in 2-D gray scale images. Mainly they are used in archaeological sites.
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Awareness and adoption of Indigenous Technical Knowledge in Agroforestry Practices in Kenya’s Maseno Region
Agroforestry does not only provide tree products and services but more importantly has the potential to increase agricultural production. Despite these benefits, its adoption in developing countries, Kenya included, does not match the scientific significance, because, farmers continue to use indigenous technical knowledge (ITK). We examined the adoption of agroforestry technologies in the Maseno region of Kisumu County, Kenya where it has remained low despite the area being sufficiently served by agroforestry extension. The objective was to investigating the potential of integrating the existing indigenous technical knowledge into the current agroforestry technologies. I addition, the study investigated the potential of indigenous technical knowledge in supplementing agroforestry extension. We used purposive and proportional simple random sampling to select a sample of 150 household heads out of 4,070 farm households in the region. We collected primary data from household heads using a structured questionnaire. The results of the study showed that indigenous technical knowledge plays a significant role in the adoption of agroforestry technologies that help in management of fuel wood, fodder, soil and weeds. Gender significantly influenced the dissemination of indigenous technical knowledge related to agroforestry. The level of adoption of recommended agroforestry technologies in the study area was low. There is need to develop new farmer-centred agroforestry technologies that should not be seen by farmers as mere modifications of traditional farming systems. We recommended that further studies on how effectively integrate modern agroforestry and indigenous technical knowledge for sustainability in improving agricultural production.
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Bayesian Analysis of Shape Parameter of Frechet distribution using Non-Informative Prior
In this paper we work on Frechet distribution with Bayesian paradigm. Posterior distribution is obtained by using Uniform, Jeffreys and generalization of non-informative priors. We use the quadrature numerical integration to solve the posterior distribution. Bayes estimator and their risk have been obtaining four loss functions. The performances of Bayes estimators are compared by using Monte Carlo simulation study.
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Bayesian inference for exponential distribution based on progressive type-II censored data with random scheme
In this paper, we propose Bayes estimator of parameter of exponential distri¬bution Under General Entropy Loss Function (GELF) for Progressive Type-II censored data with random scheme. The proposed estimator has been com¬pared with corresponding Bayes estimator under Square Error Loss Function (SELF) and Maximum Likelihood Estimator (MLE) in terms of their risks based on simulated samples from exponential distribution.
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Business strategic Alignment with Information Technology to increase organizational performance: Study on Banking Sector
IT-Business alignment has been consistently rated as one of the top ten IT management concern for last three decades. Theoretically, alignment can be defined as the degree of fit and combination between an organization’s IS (Information System) strategy and business strategy. More precisely, banks operates in a strategic Information System environment, where the alignment between IT and business should be significantly focused on organizational performance. However, this study suggests that technological innovation, strategic alignment, human resources are not an isolated source of improvement, but part of a system which mutually-reinforcing organizational performances. This research followed quantitative approach and survey questionnaire, so therefore, all 46 Bangladeshi bank (excluding foreign banks) were approached, a total number of 40 observations were usable and giving the study repose rate of 87%, which utilized for subsequent analysis. For this research, different type of analysis has been done, such as Factor analysis, Multiple-regression, t-test, ANOVA, where finding of the study is, technological innovation, strategic alignment and qualified human resources on organizational performance was identified to have a significant impact on organizational performances.
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