Search results for: Performance evaluation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7403

Search results for: Performance evaluation

3353 The Influence of Audio on Perceived Quality of Segmentation

Authors: Silvio R. R. Sanches, Bianca C. Barbosa, Beatriz R. Brum, Cléber G.Corrêa

Abstract:

In order to evaluate the quality of a segmentation algorithm, the researchers use subjective or objective metrics. Although subjective metrics are more accurate than objective ones, objective metrics do not require user feedback to test an algorithm. Objective metrics require subjective experiments only during their development. Subjective experiments typically display to users some videos (generated from frames with segmentation errors) that simulate the environment of an application domain. This user feedback is crucial information for metric definition. In the subjective experiments applied to develop some state-of-the-art metrics used to test segmentation algorithms, the videos displayed during the experiments did not contain audio. Audio is an essential component in applications such as videoconference and augmented reality. If the audio influences the user’s perception, using only videos without audio in subjective experiments can compromise the efficiency of an objective metric generated using data from these experiments. This work aims to identify if the audio influences the user’s perception of segmentation quality in background substitution applications with audio. The proposed approach used a subjective method based on formal video quality assessment methods. The results showed that audio influences the quality of segmentation perceived by a user.

Keywords: Background substitution, influence of audio, segmentation evaluation, segmentation quality.

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3352 Evaluation of Microleakage of a New Generation Nano-Ionomer in Class II Restoration of Primary Molars

Authors: Ghada Salem, Nihal Kabel

Abstract:

Objective: This in vitro study was carried out to assess the microleakage properties of nano-filled glass ionomer in comparison to resin-reinforced glass ionomers. Material and Methods: 40 deciduous molar teeth were included in this study. Class-II cavity was prepared in a standard form for all the specimens. The teeth were randomly distributed into two groups (20 per group) according to the restorative material used either nano-glass ionomer or Photac Fill glass ionomer restoration. All specimens were thermocycled for 1000 cycles between 5 and 55 °C. After that, the teeth were immersed in 2% methylene blue dye then sectioned and evaluated under a stereomicroscope. Microleakage was assessed using linear dye penetration and on a scale from zero to five. Results: Two way ANOVA test revealed a statistically significant lower degree of microleakage in both occlusal and gingival restorations (0.4±0.2), (0.9±0.1) for nano-filled glass ionomer group in comparison to resin modified glass ionomer (2.3±0.7), (2.4±0.5). No statistical difference was found between gingival and occlusal leakage regarding the effect of the measured site. Conclusion: Nano-filled glass ionomer shows superior sealing ability which enables this type of restoration to be used in minimum invasive treatment.

Keywords: Microleakage, nano-ionomer, resin-reinforced glass ionomer, proximal cavity preparation.

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3351 Fast Extraction of Edge Histogram in DCT Domain based on MPEG7

Authors: Minyoung Eom, Yoonsik Choe

Abstract:

In these days, multimedia data is transmitted and processed in compressed format. Due to the decoding procedure and filtering for edge detection, the feature extraction process of MPEG-7 Edge Histogram Descriptor is time-consuming as well as computationally expensive. To improve efficiency of compressed image retrieval, we propose a new edge histogram generation algorithm in DCT domain in this paper. Using the edge information provided by only two AC coefficients of DCT coefficients, we can get edge directions and strengths directly in DCT domain. The experimental results demonstrate that our system has good performance in terms of retrieval efficiency and effectiveness.

Keywords: DCT, Descriptor, EHD, MPEG7.

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3350 Cognitive Relaying in Interference Limited Spectrum Sharing Environment: Outage Probability and Outage Capacity

Authors: Md Fazlul Kader, Soo Young Shin

Abstract:

In this paper, we consider a cognitive relay network (CRN) in which the primary receiver (PR) is protected by peak transmit power ¯PST and/or peak interference power Q constraints. In addition, the interference effect from the primary transmitter (PT) is considered to show its impact on the performance of the CRN. We investigate the outage probability (OP) and outage capacity (OC) of the CRN by deriving closed-form expressions over Rayleigh fading channel. Results show that both the OP and OC improve by increasing the cooperative relay nodes as well as when the PT is far away from the SR.

Keywords: Cognitive relay, outage, interference limited, decode-and-forward (DF).

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3349 Mechanical Properties of Hybrid Cement Based Mortars Containing Two Biopolymers

Authors: Z. Abdollahnejad, M. Kheradmand, F. Pacheco-Torgal

Abstract:

The use of bio-based admixtures on construction materials is a recent trend that is gaining momentum. However, to our knowledge, no studies have been reported concerning the use of biopolymers on hybrid cement based mortars. This paper reports experimental results regarding the study of the influence of mix design of 43 hybrid cement mortars containing two different biopolymers on its mechanical performance. The results show that the use of the biopolymer carrageenan is much more effective than the biopolymer xanthan concerning the increase in compressive strength. An optimum biopolymer content was found.

Keywords: Waste reuse, fly ash, waste glass, hybrid cement, biopolymers, mechanical strength.

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3348 Microbial Evaluation of Geophagic and Cosmetic Clays from Southern and Western Nigeria: Potential Natural Nanomaterials

Authors: Mary A. Bisi-Johnson, Hamzat A. Oyelade, Kehinde A. Adediran, Saheed A. Akinola

Abstract:

Geophagic and cosmetic clays are among potential nanomaterial which occur naturally and are of various forms. The use of these nanoclays is a common practice in both rural and urban areas mostly due to tradition and medicinal reasons. These naturally occurring materials can be valuable sources of nanomaterial by serving as nanocomposites. The need to ascertain the safety of these materials is the motivation for this research. Physical Characterization based on the hue value and microbiological qualities of the nanoclays were carried out. The Microbial analysis of the clay samples showed considerable contamination with both bacteria and fungi with fungal contaminants taking the lead. This observation may not be unlikely due to the ability of fungi species to survive harsher growth conditions than bacteria. ‘Atike pupa’ showed no bacterial growth. The clay with the largest bacterial count was Calabash chalk (Igbanke), while that with the highest fungal count was ‘Eko grey’. The most commonly isolated bacteria in this study were Clostridium spp. and Corynebacterium spp. while fungi included Aspergillus spp. These results are an indication of the need to subject these clay materials to treatments such as heating before consumption or topical usage thereby ascertaining their safety.

Keywords: Nanomaterial, clay, microorganism, quality.

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3347 The Adsorption of SDS on Ferro-Precipitates

Authors: R.Marsalek

Abstract:

This paper present a new way to find the aerodynamic characteristic equation of missile for the numerical trajectories prediction more accurate. The goal is to obtain the polynomial equation based on two missile characteristic parameters, angle of attack (α ) and flight speed (ν ). First, the understudied missile is modeled and used for flow computational model to compute aerodynamic force and moment. Assume that performance range of understudied missile where range -10< α <10 and 0< ν <200. After completely obtained results of all cases, the data are fit by polynomial interpolation to create equation of each case and then combine all equations to form aerodynamic characteristic equation, which will be used for trajectories simulation.

Keywords: ferro-precipitate, adsorption, SDS, zeta potential

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3346 Reducing Greenhouse Gas Emissions by Recyclable Material Bank Project of Universities in Central Region of Thailand

Authors: Ronbanchob Apiratikul

Abstract:

This research studied recycled waste by the Recyclable Material Bank Project of 4 universities in the central region of Thailand for the evaluation of reducing greenhouse gas emissions compared with landfilling activity during July 2012 to June 2013. The results showed that the projects collected total amount of recyclable wastes of about 911,984.80 kilograms. Office paper had the largest amount among these recycled wastes (50.68% of total recycled waste). Groups of recycled waste can be prioritized from high to low according to their amount as paper, plastic, glass, mixed recyclables, and metal, respectively. The project reduced greenhouse gas emissions equivalent to about 2814.969 metric tons of carbon dioxide. The most significant recycled waste that affects the reduction of greenhouse gas emissions is office paper which is 70.16% of total reduced greenhouse gasses emission. According to amount of reduced greenhouse gasses emission, groups of recycled waste can be prioritized from high to low significances as paper, plastic, metals, mixed recyclables, and glass, respectively.

Keywords: Recycling, garbage bank, waste management, recyclable wastes, greenhouse gasses.

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3345 An Intelligent Text Independent Speaker Identification Using VQ-GMM Model Based Multiple Classifier System

Authors: Cheima Ben Soltane, Ittansa Yonas Kelbesa

Abstract:

Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.

Keywords: Feature Extraction, Speaker Modeling, Feature Matching, Mel Frequency Cepstrum Coefficient (MFCC), Gaussian mixture model (GMM), Vector Quantization (VQ), Linde-Buzo-Gray (LBG), Expectation Maximization (EM), pre-processing, Voice Activity Detection (VAD), Short Time Energy (STE), Background Noise Statistical Modeling, Closed-Set Tex-Independent Speaker Identification System (CISI).

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3344 Deep Learning for Renewable Power Forecasting: An Approach Using LSTM Neural Networks

Authors: Fazıl Gökgöz, Fahrettin Filiz

Abstract:

Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: Deep learning, long-short-term memory, energy, renewable energy load forecasting.

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3343 MIMO-OFDM Coded for Digital Terrestrial Television Broadcasting Systems

Authors: El Miloud A.R. Reyouchi, Kamal Ghoumid, Koutaiba Amezian, Otman Mrabet

Abstract:

This paper proposes and analyses the wireless telecommunication system with multiple antennas to the emission and reception MIMO (multiple input multiple output) with space diversity in a OFDM context. In particular it analyses the performance of a DTT (Digital Terrestrial Television) broadcasting system that includes MIMO-OFDM techniques. Different propagation channel models and configurations are considered for each diversity scheme. This study has been carried out in the context of development of the next generation DVB-T/H and WRAN.

Keywords: MIMO, MISO, OFDM, DVB-/H/T2, WRAN.

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3342 Survey on Jamming Wireless Networks: Attacks and Prevention Strategies

Authors: S. Raja Ratna, R. Ravi

Abstract:

Wireless networks are built upon the open shared medium which makes easy for attackers to conduct malicious activities. Jamming is one of the most serious security threats to information economy and it must be dealt efficiently. Jammer prevents legitimate data to reach the receiver side and also it seriously degrades the network performance. The objective of this paper is to provide a general overview of jamming in wireless network. It covers relevant works, different jamming techniques, various types of jammers and typical prevention techniques. Challenges associated with comparing several anti-jamming techniques are also highlighted.

Keywords: Channel, Cryptography, Frequency, Jamming, Legitimate, Security, Wavelength.

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3341 Parallelization and Optimization of SIFT Feature Extraction on Cluster System

Authors: Mingling Zheng, Zhenlong Song, Ke Xu, Hengzhu Liu

Abstract:

Scale Invariant Feature Transform (SIFT) has been widely applied, but extracting SIFT feature is complicated and time-consuming. In this paper, to meet the demand of the real-time applications, SIFT is parallelized and optimized on cluster system, which is named pSIFT. Redundancy storage and communication are used for boundary data to improve the performance, and before representation of feature descriptor, data reallocation is adopted to keep load balance in pSIFT. Experimental results show that pSIFT achieves good speedup and scalability.

Keywords: cluster, image matching, parallelization and optimization, SIFT.

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3340 A Genetic Algorithm for Optimum Design of PID Controller in Load Frequency Control

Authors: T. Hussein

Abstract:

In this paper, determining the optimal proportionalintegral- derivative (PID) controller gains of an single-area load frequency control (LFC) system using genetic algorithm (GA) is presented. The LFC is notoriously difficult to control optimally using conventionally tuning a PID controller because the system parameters are constantly changing. It is for this reason the GA as tuning strategy was applied. The simulation has been conducted in MATLAB Simulink package for single area power system. the simulation results shows the effectiveness performance of under various disturbance.

Keywords: Load Frequency Control (LFC), PID controller and Genetic Algorithm (GA).

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3339 A New Image Psychovisual Coding Quality Measurement based Region of Interest

Authors: M. Nahid, A. Bajit, A. Tamtaoui, E. H. Bouyakhf

Abstract:

To model the human visual system (HVS) in the region of interest, we propose a new objective metric evaluation adapted to wavelet foveation-based image compression quality measurement, which exploits a foveation setup filter implementation technique in the DWT domain, based especially on the point and region of fixation of the human eye. This model is then used to predict the visible divergences between an original and compressed image with respect to this region field and yields an adapted and local measure error by removing all peripheral errors. The technique, which we call foveation wavelet visible difference prediction (FWVDP), is demonstrated on a number of noisy images all of which have the same local peak signal to noise ratio (PSNR), but visibly different errors. We show that the FWVDP reliably predicts the fixation areas of interest where error is masked, due to high image contrast, and the areas where the error is visible, due to low image contrast. The paper also suggests ways in which the FWVDP can be used to determine a visually optimal quantization strategy for foveation-based wavelet coefficients and to produce a quantitative local measure of image quality.

Keywords: Human Visual System, Image Quality, ImageCompression, foveation wavelet, region of interest ROI.

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3338 A Robust Audio Fingerprinting Algorithm in MP3 Compressed Domain

Authors: Ruili Zhou, Yuesheng Zhu

Abstract:

In this paper, a new robust audio fingerprinting algorithm in MP3 compressed domain is proposed with high robustness to time scale modification (TSM). Instead of simply employing short-term information of the MP3 stream, the new algorithm extracts the long-term features in MP3 compressed domain by using the modulation frequency analysis. Our experiment has demonstrated that the proposed method can achieve a hit rate of above 95% in audio retrieval and resist the attack of 20% TSM. It has lower bit error rate (BER) performance compared to the other algorithms. The proposed algorithm can also be used in other compressed domains, such as AAC.

Keywords: Audio Fingerprinting, MP3, Modulation Frequency, TSM

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3337 Profitability Assessment of Granite Aggregate Production and the Development of a Profit Assessment Model

Authors: Melodi Mbuyi Mata, Blessing Olamide Taiwo, Afolabi Ayodele David

Abstract:

The purpose of this research is to create empirical models for assessing the profitability of granite aggregate production in Akure, Ondo state aggregate quarries. In addition, an Artificial Neural Network (ANN) model and multivariate predicting models for granite profitability were developed in the study. A formal survey questionnaire was used to collect data for the study. The data extracted from the case study mine for this study include granite marketing operations, royalty, production costs, and mine production information. The following methods were used to achieve the goal of this study: descriptive statistics, MATLAB 2017, and SPSS16.0 software in analyzing and modeling the data collected from granite traders in the study areas. The ANN and Multi Variant Regression models' prediction accuracy was compared using a coefficient of determination (R2), Root Mean Square Error (RMSE), and mean square error (MSE). Due to the high prediction error, the model evaluation indices revealed that the ANN model was suitable for predicting generated profit in a typical quarry. More quarries in Nigeria's southwest region and other geopolitical zones should be considered to improve ANN prediction accuracy.

Keywords: National development, granite, profitability assessment, ANN models.

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3336 A Software Tool Design for Cerebral Infarction of MR Images

Authors: Kyoung-Jong Park, Woong-Gi Jeon, Hee-Cheol Kim, Dong-Eog Kim, Heung-Kook Choi

Abstract:

The brain MR imaging-based clinical research and analysis system were specifically built and the development for a large-scale data was targeted. We used the general clinical data available for building large-scale data. Registration period for the selection of the lesion ROI and the region growing algorithm was used and the Mesh-warp algorithm for matching was implemented. The accuracy of the matching errors was modified individually. Also, the large ROI research data can accumulate by our developed compression method. In this way, the correctly decision criteria to the research result was suggested. The experimental groups were age, sex, MR type, patient ID and smoking which can easily be queries. The result data was visualized of the overlapped images by a color table. Its data was calculated by the statistical package. The evaluation for the utilization of this system in the chronic ischemic damage in the area has done from patients with the acute cerebral infarction. This is the cause of neurologic disability index location in the center portion of the lateral ventricle facing. The corona radiate was found in the position. Finally, the system reliability was measured both inter-user and intra-user registering correlation.

Keywords: Software tool design, Cerebral infarction, Brain MR image, Registration

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3335 Emotional Learning based Intelligent Robust Adaptive Controller for Stable Uncertain Nonlinear Systems

Authors: Ali Reza Mehrabian, Caro Lucas

Abstract:

In this paper a new control strategy based on Brain Emotional Learning (BEL) model has been introduced. A modified BEL model has been proposed to increase the degree of freedom, controlling capability, reliability and robustness, which can be implemented in real engineering systems. The performance of the proposed BEL controller has been illustrated by applying it on different nonlinear uncertain systems, showing very good adaptability and robustness, while maintaining stability.

Keywords: Learning control systems, emotional decision making, nonlinear systems, adaptive control.

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3334 Evaluation of the Hepatitis C Virus and Classical and Modern Immunoassays Used Nowadays to Diagnose It in Tirana

Authors: Stela Papa, Klementina Puto, Migena Pllaha

Abstract:

HCV is a hepatotropic RNA virus, transmitted primarily via the blood route, which causes progressive disease such as chronic hepatitis, liver cirrhosis, or hepatocellular carcinoma. HCV nowadays is a global healthcare problem. A variety of immunoassays including old and new technologies are being applied to detect HCV in our country. These methods include Immunochromatography assays (ICA), Fluorescence immunoassay (FIA), Enzyme linked fluorescent assay (ELFA), and Enzyme linked immunosorbent assay (ELISA) to detect HCV antibodies in blood serum, which lately is being slowly replaced by more sensitive methods such as rapid automated analyzer chemiluminescence immunoassay (CLIA). The aim of this study is to estimate HCV infection in carriers and chronic acute patients and to evaluate the use of new diagnostic methods. This study was realized from September 2016 to May 2018. During this study period, 2913 patients were analyzed for the presence of HCV by taking samples from their blood serum. The immunoassays performed were ICA, FIA, ELFA, ELISA, and CLIA assays. Concluding, 82% of patients taken in this study, resulted infected with HCV. Diagnostic methods in clinical laboratories are crucial in the early stages of infection, in the management of chronic hepatitis and in the treatment of patients during their disease.

Keywords: CLIA, ELISA, hepatitis C virus, immunoassay.

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3333 Application of Adaptive Genetic Algorithm in Function Optimization

Authors: Panpan Xu, Shulin Sui

Abstract:

The crossover probability and mutation probability are the two important factors in genetic algorithm. The adaptive genetic algorithm can improve the convergence performance of genetic algorithm, in which the crossover probability and mutation probability are adaptively designed with the changes of fitness value. We apply adaptive genetic algorithm into a function optimization problem. The numerical experiment represents that adaptive genetic algorithm improves the convergence speed and avoids local convergence.

Keywords: Genetic algorithm, Adaptive genetic algorithm, Function optimization.

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3332 Thermographic Tests of Curved GFRP Structures with Delaminations: Numerical Modelling vs. Experimental Validation

Authors: P. D. Pastuszak

Abstract:

The present work is devoted to thermographic studies of curved composite panels (unidirectional GFRP) with subsurface defects. Various artificial defects, created by inserting PTFE stripe between individual layers of a laminate during manufacturing stage are studied. The analysis is conducted both with the use finite element method and experiments. To simulate transient heat transfer in 3D model with embedded various defect sizes, the ANSYS package is used. Pulsed Thermography combined with optical excitation source provides good results for flat surfaces. Composite structures are mostly used in complex components, e.g., pipes, corners and stiffeners. Local decrease of mechanical properties in these regions can have significant influence on strength decrease of the entire structure. Application of active procedures of thermography to defect detection and evaluation in this type of elements seems to be more appropriate that other NDT techniques. Nevertheless, there are various uncertainties connected with correct interpretation of acquired data. In this paper, important factors concerning Infrared Thermography measurements of curved surfaces in the form of cylindrical panels are considered. In addition, temperature effects on the surface resulting from complex geometry and embedded and real defect are also presented.

Keywords: Active thermography, finite element analysis, composite, curved structures, defects.

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3331 Capacity Building of Extension Agents for Sustainable Dissemination of Agricultural Information and Technologies in Developing Countries

Authors: Michael T. Ajayi, Oluwakemi E. Fapojuwo

Abstract:

Farmers are in need of regular and relevant information relating to new technologies. Production of extension materials has been found to be useful in facilitating the process. Extension materials help to provide information to reach large numbers of farmers quickly and economically. However, as good as extension materials are, previous materials produced are not used by farmers. The reasons for this include lack of involvement of farmers in the production of the extension materials, most of the extension materials are not relevant to the farmers’ environments, the agricultural extension agents lack capacity to prepare the materials, and many extension agents lack commitment. These problems led to this innovative capacity building of extension agents. This innovative approach involves five stages. The first stage is the diagnostic survey of farmers’ environment to collect useful information. The second stage is the development and production of draft extension materials. The third stage is the field testing and evaluation of draft materials by the same famers that were involved at the diagnostic stage. The fourth stage is the revision of the draft extension materials by incorporating suggestions from farmers. The fifth stage is the action plans. This process improves the capacity of agricultural extension agents in the preparation of extension materials and also promotes engagement of farmers and beneficiaries in the process. The process also makes farmers assume some level of ownership of the exercise and the extension materials.

Keywords: Capacity building, dissemination, extension agents, information/technologies.

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3330 The Impact of Leadership Style and Sense of Competence on the Performance of Post-Primary School Teachers in Oyo State, Nigeria

Authors: Babajide S. Adeokin, Oguntoyinbo O. Kazeem

Abstract:

The not so pleasing state of the nation's quality of education has been a major area of research. Many researchers have looked into various aspects of the educational system and organizational structure in relation to the quality of service delivery of the staff members. However, there is paucity of research in areas relating to the sense of competence and commitment in relation to leadership styles. Against this backdrop, this study investigated the impact of leadership style and sense of competence on the performance of post-primary school teachers in Oyo state Nigeria. Data were generated across public secondary schools in the city using survey design method. Ibadan as a metropolis has eleven local government areas contained in it. A systematic random sampling technique of the eleven local government areas in Ibadan was done and five local government areas were selected. The selected local government areas are Akinyele, Ibadan North, Ibadan North-East, Ibadan South and Ibadan South-West. Data were obtained from a range of two – three public secondary schools selected in each of the local government areas mentioned above. Also, these secondary schools are a representation of the variations in the constructs under consideration across the Ibadan metropolis. Categorically, all secondary school teachers in Ibadan were clustered into selected schools in those found across the five local government areas. In all, a total of 272 questionnaires were administered to public secondary school teachers, while 241 were returned. Findings revealed that transformational leadership style makes room for job commitment when compared with transactional and laissez-faire leadership styles. Teachers with a high sense of competence are more likely to demonstrate more commitment to their job than others with low sense of competence. We recommend that, it is important an assessment is made of the leadership styles employed by principals and school administrators. This guides administrators and principals in to having a clear, comprehensive knowledge of the style they currently adopt in the management of the staff and the school as a whole; and know where to begin the adjustment process from. Also to make an impact on student achievement, being attentive to teachers’ levels of commitment may be an important aspect of leadership for school principals.

Keywords: Leadership style, sense of competence, teachers, public secondary schools, Ibadan.

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3329 An Approach on the Design of a Solar Cell Characterization Device

Authors: Christoph Mayer, Dominik Holzmann

Abstract:

This paper presents the development of a compact, portable and easy to handle solar cell characterization device. The presented device reduces the effort and cost of single solar cell characterization to a minimum. It enables realistic characterization of cells under sunlight within minutes. In the field of photovoltaic research the common way to characterize a single solar cell or a module is, to measure the current voltage curve. With this characteristic the performance and the degradation rate can be defined which are important for the consumer or developer. The paper consists of the system design description, a summary of the measurement results and an outline for further developments.

Keywords: Solar cell, photovoltaics, PV, characterization.

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3328 Connected Objects with Optical Rectenna for Wireless Information Systems

Authors: Chayma Bahar, Chokri Baccouch, Hedi Sakli, Nizar Sakli

Abstract:

Harvesting and transport of optical and radiofrequency signals are a topical subject with multiple challenges. In this paper, we present a Optical RECTENNA system. We propose here a hybrid system solar cell antenna for 5G mobile communications networks. Thus, we propose rectifying circuit. A parametric study is done to follow the influence of load resistance and input power on Optical RECTENNA system performance. Thus, we propose a solar cell antenna structure in the frequency band of future 5G standard in 2.45 GHz bands.

Keywords: Antenna, Rectenna, solar cell, 5G, optical RECTENNA.

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3327 Educational Experiences in Engineering in the COVID-19 Era and Their Comparative Analysis: Spain, March-June 2020

Authors: Borja Bordel, Ramón Alcarria, Marina Pérez

Abstract:

In March 2020, in Spain, a sanitary and unexpected crisis caused by COVID-19 was declared. All of a sudden, all degrees, classes and evaluation tests and projects had to be transformed into online activities. However, the chaotic situation generated by a complex operation like that, executed without any well-established procedure, led to very different experiences and, finally, results. In this paper, we are describing three experiences in two different Universities in Madrid. On the one hand, the Technical University of Madrid, a public university with little experience in online education was considered. On the other hand, Alfonso X el Sabio University, a private university with more than five years of experience in online teaching was involved. All analyzed subjects were related to computer engineering. Professors and students answered a survey and personal interviews were also carried out. Besides, the professors’ workload and the students’ academic results were also compared. From the comparative analysis of all these experiences, we are extracting the most successful strategies, methodologies, and activities. The recommendations in this paper will be useful for courses during the next months when the sanitary situation is still affecting an educational organization. While, at the same time, they will be considered as input for the upcoming digitalization process of higher education.

Keywords: educational experience, online education, higher education digitalization, COVID, Spain

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3326 Data-driven Multiscale Tsallis Complexity: Application to EEG Analysis

Authors: Young-Seok Choi

Abstract:

This work proposes a data-driven multiscale based quantitative measures to reveal the underlying complexity of electroencephalogram (EEG), applying to a rodent model of hypoxic-ischemic brain injury and recovery. Motivated by that real EEG recording is nonlinear and non-stationary over different frequencies or scales, there is a need of more suitable approach over the conventional single scale based tools for analyzing the EEG data. Here, we present a new framework of complexity measures considering changing dynamics over multiple oscillatory scales. The proposed multiscale complexity is obtained by calculating entropies of the probability distributions of the intrinsic mode functions extracted by the empirical mode decomposition (EMD) of EEG. To quantify EEG recording of a rat model of hypoxic-ischemic brain injury following cardiac arrest, the multiscale version of Tsallis entropy is examined. To validate the proposed complexity measure, actual EEG recordings from rats (n=9) experiencing 7 min cardiac arrest followed by resuscitation were analyzed. Experimental results demonstrate that the use of the multiscale Tsallis entropy leads to better discrimination of the injury levels and improved correlations with the neurological deficit evaluation after 72 hours after cardiac arrest, thus suggesting an effective metric as a prognostic tool.

Keywords: Electroencephalogram (EEG), multiscale complexity, empirical mode decomposition, Tsallis entropy.

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3325 Skin Lesion Segmentation Using Color Channel Optimization and Clustering-based Histogram Thresholding

Authors: Rahil Garnavi, Mohammad Aldeen, M. Emre Celebi, Alauddin Bhuiyan, Constantinos Dolianitis, George Varigos

Abstract:

Automatic segmentation of skin lesions is the first step towards the automated analysis of malignant melanoma. Although numerous segmentation methods have been developed, few studies have focused on determining the most effective color space for melanoma application. This paper proposes an automatic segmentation algorithm based on color space analysis and clustering-based histogram thresholding, a process which is able to determine the optimal color channel for detecting the borders in dermoscopy images. The algorithm is tested on a set of 30 high resolution dermoscopy images. A comprehensive evaluation of the results is provided, where borders manually drawn by four dermatologists, are compared to automated borders detected by the proposed algorithm, applying three previously used metrics of accuracy, sensitivity, and specificity and a new metric of similarity. By performing ROC analysis and ranking the metrics, it is demonstrated that the best results are obtained with the X and XoYoR color channels, resulting in an accuracy of approximately 97%. The proposed method is also compared with two state-of-theart skin lesion segmentation methods.

Keywords: Border detection, Color space analysis, Dermoscopy, Histogram thresholding, Melanoma, Segmentation.

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3324 Reducing Greenhouse Gasses Emissions by Recyclable Material Bank Project in Universities of Thailand

Authors: Ronbanchob Apiratikul

Abstract:

This research studied recycled wastes by Recyclable Material Bank project of 17 universities of Thailand for evaluation of reducing greenhouse gasses emission compared with landfilling activity during January 2011 to December 2011. The results showed that the projects collected total amount of recyclable wastes about 1,626.917 metric ton. The office paper has the largest amount among these recycled wastes (55.61 % of total recycled wastes). Groups of recycled waste can be prioritized from high to low according to their amount as paper, plastic, glass, mixed recyclables and metal, respectively. The project reduced greenhouse gasses emission equivalent to about 5,263.481 metric ton of carbon dioxide. The most significant recycled waste that affects the reduction of greenhouse gasses emission is office paper which is 73.45% of total reduced greenhouse gasses emission. According to amount of reduced greenhouse gasses emission, groups of recycled waste can be prioritized from high to low significances as paper, plastic, metal, mixed recyclables and glass, respectively.

Keywords: recycling, garbage bank, waste management, recyclable wastes, greenhouse gasses

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