Search results for: Cover%20Image
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 335

Search results for: Cover%20Image

95 Thailand National Biodiversity Database System with webMathematica and Google Earth

Authors: W. Katsarapong, W. Srisang, K. Jaroensutasinee, M. Jaroensutasinee

Abstract:

National Biodiversity Database System (NBIDS) has been developed for collecting Thai biodiversity data. The goal of this project is to provide advanced tools for querying, analyzing, modeling, and visualizing patterns of species distribution for researchers and scientists. NBIDS data record two types of datasets: biodiversity data and environmental data. Biodiversity data are specie presence data and species status. The attributes of biodiversity data can be further classified into two groups: universal and projectspecific attributes. Universal attributes are attributes that are common to all of the records, e.g. X/Y coordinates, year, and collector name. Project-specific attributes are attributes that are unique to one or a few projects, e.g., flowering stage. Environmental data include atmospheric data, hydrology data, soil data, and land cover data collecting by using GLOBE protocols. We have developed webbased tools for data entry. Google Earth KML and ArcGIS were used as tools for map visualization. webMathematica was used for simple data visualization and also for advanced data analysis and visualization, e.g., spatial interpolation, and statistical analysis. NBIDS will be used by park rangers at Khao Nan National Park, and researchers.

Keywords: GLOBE protocol, Biodiversity, Database System, ArcGIS, Google Earth and webMathematica.

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94 Ensemble Learning with Decision Tree for Remote Sensing Classification

Authors: Mahesh Pal

Abstract:

In recent years, a number of works proposing the combination of multiple classifiers to produce a single classification have been reported in remote sensing literature. The resulting classifier, referred to as an ensemble classifier, is generally found to be more accurate than any of the individual classifiers making up the ensemble. As accuracy is the primary concern, much of the research in the field of land cover classification is focused on improving classification accuracy. This study compares the performance of four ensemble approaches (boosting, bagging, DECORATE and random subspace) with a univariate decision tree as base classifier. Two training datasets, one without ant noise and other with 20 percent noise was used to judge the performance of different ensemble approaches. Results with noise free data set suggest an improvement of about 4% in classification accuracy with all ensemble approaches in comparison to the results provided by univariate decision tree classifier. Highest classification accuracy of 87.43% was achieved by boosted decision tree. A comparison of results with noisy data set suggests that bagging, DECORATE and random subspace approaches works well with this data whereas the performance of boosted decision tree degrades and a classification accuracy of 79.7% is achieved which is even lower than that is achieved (i.e. 80.02%) by using unboosted decision tree classifier.

Keywords: Ensemble learning, decision tree, remote sensingclassification.

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93 Statistical Relation between Vegetation Cover and Land Surface Temperature in Phnom Penh City

Authors: Gulam Mohiuddin, Jan-Peter Mund

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This study assessed the correlation between Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) in Phnom Penh City (Cambodia) from 2016 to 2020. Understanding the LST and NDVI can be helpful to understand the Urban Heat Island (UHI) scenario, and it can contribute to planning urban greening and combating the effects of UHI. The study used Landsat-8 images as the data for analysis. They have 100 m spatial resolution (per pixel) in the thermal band. The current study used an approach for the statistical analysis that considers every pixel from the study area instead of taking few sample points or analyzing descriptive statistics. Also, this study is examining the correlation between NDVI and LST with a spatially explicit approach. The study found a strong negative correlation between NDVI and LST (coefficient range -0.56 to -0.59), and this relationship is linear. This study showed a way to avoid the probable error from the sample-based approach in examining two spatial variables. The method is reproducible for a similar type of analysis on the correlation between spatial phenomena. The findings of this study will be used further to understand the causation behind LST change in that area triangulating LST, NDVI and land-use changes.

Keywords: Land Surface Temperature, NDVI, Normalized Difference Vegetation Index, remote sensing, methodological development.

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92 Developing Kazakh Language Fluency Test in Nazarbayev University

Authors: Saule Mussabekova, Samal Abzhanova

Abstract:

The Kazakh Language Fluency Test, based on the IELTS exam, was implemented in 2012 at Nazarbayev University in Astana, Kazakhstan. We would like to share our experience in developing this exam and some exam results with other language instructors. In this paper, we will cover all these peculiarities and their related issues. The Kazakh Language Fluency Test is a young exam. During its development, we faced many difficulties. One of the goals of the university and the country is to encourage fluency in the Kazakh language for all citizens of the Republic. Nazarbayev University has introduced a Kazakh language program to assist in achieving this goal. This policy is one-step in ensuring that NU students have a thorough understanding of the Kazakh language through a fluency test based on the International English Language Testing System (IELTS). The Kazakh Language Fluency Test exam aims to determine student’s knowledge of Kazakh language. The fact is that there are three types of students at Nazarbayev University: Kazakh-speaking heritage learners, Russian-speaking and English-speaking students. Unfortunately, we have Kazakh students who do not speak Kazakh. All students who finished school with Russian language instruction are given Kazakh Language Fluency Test in order to determine their Kazakh level. After the test exam, all students can choose appropriate Kazakh course: Basic Kazakh, Intermediate Kazakh and Upper-Intermediate Kazakh. The Kazakh Language Fluency Test consists of four parts: Listening, Reading, Writing and Speaking. They are taken on the same day in the abovementioned order.

Keywords: Diagnostic language test, Kazakh language, placement test, test result.

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91 Learning to Recognize Faces by Local Feature Design and Selection

Authors: Yanwei Pang, Lei Zhang, Zhengkai Liu

Abstract:

Studies in neuroscience suggest that both global and local feature information are crucial for perception and recognition of faces. It is widely believed that local feature is less sensitive to variations caused by illumination, expression and illumination. In this paper, we target at designing and learning local features for face recognition. We designed three types of local features. They are semi-global feature, local patch feature and tangent shape feature. The designing of semi-global feature aims at taking advantage of global-like feature and meanwhile avoiding suppressing AdaBoost algorithm in boosting weak classifies established from small local patches. The designing of local patch feature targets at automatically selecting discriminative features, and is thus different with traditional ways, in which local patches are usually selected manually to cover the salient facial components. Also, shape feature is considered in this paper for frontal view face recognition. These features are selected and combined under the framework of boosting algorithm and cascade structure. The experimental results demonstrate that the proposed approach outperforms the standard eigenface method and Bayesian method. Moreover, the selected local features and observations in the experiments are enlightening to researches in local feature design in face recognition.

Keywords: Face recognition, local feature, AdaBoost, subspace analysis.

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90 Dual Role of Women and Its Influence on Farmers’ Household Income and Consumption Pattern: Study of Informal Women Workers in the District Mandalle, Pangkep, South Sulawesi Province

Authors: Ida Rosada, Nurliani

Abstract:

Today, the number of women who seek additional income to help her husband is increasing. They do that in order to be able to express themselves in the midst of the family and society. Nonetheless, housewives are in charge of managing family’s income and prepare food for the family. The objective of this research is 1) to analyze the effect of the dual role of women to household income and 2) to analyze the effect of the dual role to consumption patterns. The study used a qualitative approach, data collection techniques are through observation, interviews, and documentation on farming households. The data was analysed qualitative descriptively. The results found that: 1) The revenue contribution of women who play double role in the informal sector amounted to 34.07% (less than 50%). 2) The main reason that the respondents worked in the informal sector is to be able to send their children to school (34%) and to improve household economy condition (28%). 3) After earning additional income, respondents said that they can contribute to increase the family’s income and to cover the family shortage (82%); 4) Respondents’ opinion to changes in food consumption after performing the dual role is the ability to purchase and provide the desired food (44%) and changing patterns of consumption per day (30%).

Keywords: Dual role, the informal sector, consumption patterns, household income.

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89 Implementation of an Improved Secure System Detection for E-passport by using EPC RFID Tags

Authors: A. Baith Mohamed, Ayman Abdel-Hamid, Kareem Youssri Mohamed

Abstract:

Current proposals for E-passport or ID-Card is similar to a regular passport with the addition of tiny contactless integrated circuit (computer chip) inserted in the back cover, which will act as a secure storage device of the same data visually displayed on the photo page of the passport. In addition, it will include a digital photograph that will enable biometric comparison, through the use of facial recognition technology at international borders. Moreover, the e-passport will have a new interface, incorporating additional antifraud and security features. However, its problems are reliability, security and privacy. Privacy is a serious issue since there is no encryption between the readers and the E-passport. However, security issues such as authentication, data protection and control techniques cannot be embedded in one process. In this paper, design and prototype implementation of an improved E-passport reader is presented. The passport holder is authenticated online by using GSM network. The GSM network is the main interface between identification center and the e-passport reader. The communication data is protected between server and e-passport reader by using AES to encrypt data for protection will transferring through GSM network. Performance measurements indicate a 19% improvement in encryption cycles versus previously reported results.

Keywords: RFID "Radio Frequency Identification", EPC"Electronic Product Code", ICAO "International Civil Aviation Organization", IFF "Identify Friend or Foe"

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88 Texture Feature Extraction of Infrared River Ice Images using Second-Order Spatial Statistics

Authors: Bharathi P. T, P. Subashini

Abstract:

Ice cover County has a significant impact on rivers as it affects with the ice melting capacity which results in flooding, restrict navigation, modify the ecosystem and microclimate. River ices are made up of different ice types with varying ice thickness, so surveillance of river ice plays an important role. River ice types are captured using infrared imaging camera which captures the images even during the night times. In this paper the river ice infrared texture images are analysed using first-order statistical methods and secondorder statistical methods. The second order statistical methods considered are spatial gray level dependence method, gray level run length method and gray level difference method. The performance of the feature extraction methods are evaluated by using Probabilistic Neural Network classifier and it is found that the first-order statistical method and second-order statistical method yields low accuracy. So the features extracted from the first-order statistical method and second-order statistical method are combined and it is observed that the result of these combined features (First order statistical method + gray level run length method) provides higher accuracy when compared with the features from the first-order statistical method and second-order statistical method alone.

Keywords: Gray Level Difference Method, Gray Level Run Length Method, Kurtosis, Probabilistic Neural Network, Skewness, Spatial Gray Level Dependence Method.

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87 The Concept of the Aesthetic Features in Architectural Structures of the Museums

Authors: D. Moussazadeh, A. Aytug

Abstract:

The focus of this study is to analyze and elaborate the formal factors in the architectural features of the museums. From aesthetic vantage point, this study has scrutinized the formal aesthetic values and identity-related features of the museums. Furthermore, the importance of the museums as the centers of knowledge, science and arts has gradually increased in the last century, whereby they have shifted from an elite standing to the pluralist approach as to address every sections of the community. This study will focus on the museum structures that are designed with the aesthetic apprehension, and presented as the artistic works on the basis of an objective attitude to elaborate the formal aesthetic factors on the formal aesthetics. It is of great importance to increase such studies for getting some concrete results to perceive the recent term aesthetic approaches and improve the forms in line with such approaches. This study elaborates the aesthetic facts solely on the basis of visual dimensions, but ignores the subjective effects to evaluate it in formal, subjective and conceptual aspects. The main material of this study comprises of the descriptive works on the conceptual substructure, and a number of schedules drawn on such concepts, which are applied on the example museum structures. Such works cover many several existing sources such as the design, philosophy, artistic philosophy, shape, form, design elements and principles as well as the museums.

Keywords: Aesthetics, design principles and elements, Gestalt.

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86 Physicochemistry of Pozzolanic Stabilization of a Class A-2-7 Lateritic Soil

Authors: Ahmed O. Apampa, Yinusa A. Jimoh

Abstract:

The paper examines the mechanism of pozzolan-soil reactions, using a recent study on the chemical stabilization of a Class A-2-7 (3) lateritic soil, with corn cob ash (CCA) as case study. The objectives are to establish a nexus between cation exchange capacity of the soil, the alkaline forming compounds in CCA and percentage CCA addition to soil beyond which no more improvement in strength properties can be achieved; and to propose feasible chemical reactions to explain the chemical stabilization of the lateritic soil with CCA alone. The lateritic soil, as well as CCA of pozzolanic quality Class C were separately analysed for their metallic oxide composition using the X-Ray Fluorescence technique. The cation exchange capacity (CEC) of the soil and the CCA were computed theoretically using the percentage composition of the base cations Ca2+, Mg2+ K+ and Na2+ as 1.48 meq/100 g and 61.67 meq/100 g respectively, thus indicating a ratio of 0.024 or 2.4%. This figure, taken as the theoretical amount required to just fill up the exchangeable sites of the clay molecules, compares well with the laboratory observation of 1.5% for the optimum level of CCA addition to lateritic soil. The paper went on to present chemical reaction equations between the alkaline earth metals in the CCA and the silica in the lateritic soil to form silicates, thereby proposing an extension of the theory of mechanism of soil stabilization to cover chemical stabilization with pozzolanic ash only. The paper concluded by recommending further research on the molecular structure of soils stabilized with pozzolanic waste ash alone, with a view to confirming the chemical equations advanced in the study.

Keywords: Cation exchange capacity, corn cob ash, lateritic soil, soil stabilization.

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85 Medical Image Watermark and Tamper Detection Using Constant Correlation Spread Spectrum Watermarking

Authors: Peter U. Eze, P. Udaya, Robin J. Evans

Abstract:

Data hiding can be achieved by Steganography or invisible digital watermarking. For digital watermarking, both accurate retrieval of the embedded watermark and the integrity of the cover image are important. Medical image security in Teleradiology is one of the applications where the embedded patient record needs to be extracted with accuracy as well as the medical image integrity verified. In this research paper, the Constant Correlation Spread Spectrum digital watermarking for medical image tamper detection and accurate embedded watermark retrieval is introduced. In the proposed method, a watermark bit from a patient record is spread in a medical image sub-block such that the correlation of all watermarked sub-blocks with a spreading code, W, would have a constant value, p. The constant correlation p, spreading code, W and the size of the sub-blocks constitute the secret key. Tamper detection is achieved by flagging any sub-block whose correlation value deviates by more than a small value, ℇ, from p. The major features of our new scheme include: (1) Improving watermark detection accuracy for high-pixel depth medical images by reducing the Bit Error Rate (BER) to Zero and (2) block-level tamper detection in a single computational process with simultaneous watermark detection, thereby increasing utility with the same computational cost.

Keywords: Constant correlation, medical image, spread spectrum, tamper detection, watermarking.

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84 Stability Enhancement of a Large-Scale Power System Using Power System Stabilizer Based on Adaptive Neuro Fuzzy Inference System

Authors: Agung Budi Muljono, I Made Ginarsa, I Made Ari Nrartha

Abstract:

A large-scale power system (LSPS) consists of two or more sub-systems connected by inter-connecting transmission. Loading pattern on an LSPS always changes from time to time and varies depend on consumer need. The serious instability problem is appeared in an LSPS due to load fluctuation in all of the bus. Adaptive neuro-fuzzy inference system (ANFIS)-based power system stabilizer (PSS) is presented to cover the stability problem and to enhance the stability of an LSPS. The ANFIS control is presented because the ANFIS control is more effective than Mamdani fuzzy control in the computation aspect. Simulation results show that the presented PSS is able to maintain the stability by decreasing peak overshoot to the value of −2.56 × 10−5 pu for rotor speed deviation Δω2−3. The presented PSS also makes the settling time to achieve at 3.78 s on local mode oscillation. Furthermore, the presented PSS is able to improve the peak overshoot and settling time of Δω3−9 to the value of −0.868 × 10−5 pu and at the time of 3.50 s for inter-area oscillation.

Keywords: ANFIS, large-scale, power system, PSS, stability enhancement.

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83 Logistics Outsourcing: Performance Models and Financial and Operational Indicators

Authors: Carlos Sanchís-Pedregosa, José A. D. M achuca, María del Mar González-Zamora

Abstract:

The growing outsourcing of logistics services resulting from the ongoing current in firms of costs reduction/increased efficiency means that it is becoming more and more important for the companies doing the outsourcing to carry out a proper evaluation. The multiple definitions and measures of logistics service performance found in research on the topic create a certain degree of confusion and do not clear the way towards the proper measurement of their performance. Do a model and a specific set of indicators exist that can be considered appropriate for measuring the performance of logistics services outsourcing in industrial environments? Are said indicators in keeping with the objectives pursued by outsourcing? We aim to answer these and other research questions in the study we have initiated in the field within the framework of the international High Performance Manufacturing (HPM) project of which this paper forms part. As the first stage of this research, this paper reviews articles dealing with the topic published in the last 15 years with the aim of detecting the models most used to make this measurement and determining which performance indicators are proposed as part of said models and which are most used. The first steps are also taken in determining whether these indicators, financial and operational, cover the aims that are being pursued when outsourcing logistics services. The findings show there is a wide variety of both models and indicators used. This would seem to testify to the need to continue with our research in order to try to propose a model and a set of indicators for measuring the performance of logistics services outsourcing in industrial environments.

Keywords: Logistics, objectives, outsourcing, performancemeasurement systems

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82 Optimal Allocation Between Subprime Structured Mortgage Products and Treasuries

Authors: MP. Mulaudzi, MA. Petersen, J. Mukuddem-Petersen , IM. Schoeman, B. de Waal, JM. Manale

Abstract:

This conference paper discusses a risk allocation problem for subprime investing banks involving investment in subprime structured mortgage products (SMPs) and Treasuries. In order to solve this problem, we develop a L'evy process-based model of jump diffusion-type for investment choice in subprime SMPs and Treasuries. This model incorporates subprime SMP losses for which credit default insurance in the form of credit default swaps (CDSs) can be purchased. In essence, we solve a mean swap-at-risk (SaR) optimization problem for investment which determines optimal allocation between SMPs and Treasuries subject to credit risk protection via CDSs. In this regard, SaR is indicative of how much protection investors must purchase from swap protection sellers in order to cover possible losses from SMP default. Here, SaR is defined in terms of value-at-risk (VaR). Finally, we provide an analysis of the aforementioned optimization problem and its connections with the subprime mortgage crisis (SMC).

Keywords: Investors; Jump Diffusion Process, Structured Mortgage Products, Treasuries, Credit Risk, Credit Default Swaps, Tranching Risk, Counterparty Risk, Value-at-Risk, Swaps-at-Risk, Subprime Mortgage Crisis.

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81 The Evaluation of Heavy Metal Pollution Degree in the Soils around the Zangezur Copper and Molybdenum Combine

Authors: K. A. Ghazaryan, G. A. Gevorgyan, H. S. Movsesyan, N. P. Ghazaryan, K. V. Grigoryan

Abstract:

The heavy metal pollution degree in the soils around the Zangezur copper and molybdenum combine in Syunik Marz, Armenia was assessed. The results of the study showed that heavy metal pollution degree in the soils mainly decreased with increasing distance from the open mine and the ore enrichment combine which indicated that the open mine and the ore enrichment combine were the main sources of heavy metal pollution. The only exception was observed in the northern part of the open mine where pollution degree in the sites (along the open mine) situated 600 meters far from the mine was higher than that in the sites located 300 meters far from the mine. This can be explained by the characteristics of relief and air currents as well as the weak vegetation cover of these sites and the characteristics of soil structure. According to geo-accumulation index (I-geo), contamination factor (Cf), contamination degree (Cd) and pollution load index (PLI) values, the pollution degree in the soils around the open mine and the ore enrichment combine was higher than that in the soils around the tailing dumps which was due to the proper and accurate operation of the Artsvanik tailing damp and the recultivation of the Voghji tailing dump. The high Cu and Mo pollution of the soils was conditioned by the character of industrial activities, the moving direction of air currents as well as the physicochemical peculiarities of the soils.

Keywords: Armenia, Zangezur copper and molybdenum combine, soil, heavy metal pollution degree.

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80 Evaluation of the Internal Quality for Pineapple Based on the Spectroscopy Approach and Neural Network

Authors: Nonlapun Meenil, Pisitpong Intarapong, Thitima Wongsheree, Pranchalee Samanpiboon

Abstract:

In Thailand, once pineapples are harvested, they must be classified into two classes based on their sweetness: sweet and unsweet. This paper has studied and developed the assessment of internal quality of pineapples using a low-cost compact spectroscopy sensor according to the spectroscopy approach and Neural Network (NN). During the experiments, Batavia pineapples were utilized, generating 100 samples. The extracted pineapple juice of each sample was used to determine the Soluble Solid Content (SSC) labeling into sweet and unsweet classes. In terms of experimental equipment, the sensor cover was specifically designed to install the sensor and light source to read the reflectance at a five mm depth from pineapple flesh. By using a spectroscopy sensor, data on visible and near-infrared reflectance (Vis-NIR) were collected. The NN was used to classify the pineapple classes. Before the classification step, the preprocessing methods, which are class balancing, data shuffling, and standardization, were applied. The 510 nm and 900 nm reflectance values of the middle parts of pineapples were used as features of the NN. With the sequential model and ReLU activation function, 100% accuracy of the training set and 76.67% accuracy of the test set were achieved. According to the abovementioned information, using a low-cost compact spectroscopy sensor has achieved favorable results in classifying the sweetness of the two classes of pineapples.

Keywords: Spectroscopy, soluble solid content, pineapple, neural network.

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79 Modelling Dengue Fever (DF) and Dengue Haemorrhagic Fever (DHF) Outbreak Using Poisson and Negative Binomial Model

Authors: W. Y. Wan Fairos, W. H. Wan Azaki, L. Mohamad Alias, Y. Bee Wah

Abstract:

Dengue fever has become a major concern for health authorities all over the world particularly in the tropical countries. These countries, in particular are experiencing the most worrying outbreak of dengue fever (DF) and dengue haemorrhagic fever (DHF). The DF and DHF epidemics, thus, have become the main causes of hospital admissions and deaths in Malaysia. This paper, therefore, attempts to examine the environmental factors that may influence the recent dengue outbreak. The aim of this study is twofold, firstly is to establish a statistical model to describe the relationship between the number of dengue cases and a range of explanatory variables and secondly, to identify the lag operator for explanatory variables which affect the dengue incidence the most. The explanatory variables involved include the level of cloud cover, percentage of relative humidity, amount of rainfall, maximum temperature, minimum temperature and wind speed. The Poisson and Negative Binomial regression analyses were used in this study. The results of the analyses on the 915 observations (daily data taken from July 2006 to Dec 2008), reveal that the climatic factors comprising of daily temperature and wind speed were found to significantly influence the incidence of dengue fever after 2 and 3 weeks of their occurrences. The effect of humidity, on the other hand, appears to be significant only after 2 weeks.

Keywords: Dengue Fever, Dengue Hemorrhagic Fever, Negative Binomial Regression model, Poisson Regression model.

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78 Thermal Analysis of Extrusion Process in Plastic Making

Authors: S. K. Fasogbon, T. M. Oladosu, O. S. Osasuyi

Abstract:

Plastic extrusion has been an important process of plastic production since 19th century. Meanwhile, in plastic extrusion process, wide variation in temperature along the extrudate usually leads to scraps formation on the side of finished products. To avoid this situation, there is a need to deeply understand temperature distribution along the extrudate in plastic extrusion process. This work developed an analytical model that predicts the temperature distribution over the billet (the polymers melt) along the extrudate during extrusion process with the limitation that the polymer in question does not cover biopolymer such as DNA. The model was solved and simulated. Results for two different plastic materials (polyvinylchloride and polycarbonate) using self-developed MATLAB code and a commercially developed software (ANSYS) were generated and ultimately compared. It was observed that there is a thermodynamic heat transfer from the entry level of the billet into the die down to the end of it. The graph plots indicate a natural exponential decay of temperature with time and along the die length, with the temperature being 413 K and 474 K for polyvinylchloride and polycarbonate respectively at the entry level and 299.3 K and 328.8 K at the exit when the temperature of the surrounding was 298 K. The extrusion model was validated by comparison of MATLAB code simulation with a commercially available ANSYS simulation and the results favourably agree. This work concludes that the developed mathematical model and the self-generated MATLAB code are reliable tools in predicting temperature distribution along the extrudate in plastic extrusion process.

Keywords: ANSYS, extrusion process, MATLAB, plastic making, thermal analysis.

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77 Topics of Blockchain Technology to Teach at Community College

Authors: Penn P. Wu, Jeannie Jo

Abstract:

Blockchain technology has rapidly gained popularity in industry. This paper attempts to assist academia to answer four questions. First, should community colleges begin offering education to nurture blockchain-literate students for the job market? Second, what are the appropriate topical areas to cover? Third, should it be an individual course? And forth, should it be a technical or management course? This paper starts with identifying the knowledge domains of blockchain technology and the topical areas each domain has, and continues with placing them in appropriate academic territories (Computer Sciences vs. Business) and subjects (programming, management, marketing, and laws), and then develops an evaluation model to determine the appropriate topical area for community colleges to teach. The evaluation is based on seven factors: maturity of technology, impacts on management, real-world applications, subject classification, knowledge prerequisites, textbook readiness, and recommended pedagogies. The evaluation results point to an interesting direction that offering an introductory course is an ideal option to guide students through the learning journey of what blockchain is and how it applies to business. Such an introductory course does not need to engage students in the discussions of mathematics and sciences that make blockchain technologies possible. While it is inevitable to brief technical topics to help students build a solid knowledge foundation of blockchain technologies, community colleges should avoid offering students a course centered on the discussion of developing blockchain applications.

Keywords: Blockchain, pedagogies, blockchain technologies, blockchain course, blockchain pedagogies.

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76 Assessment of Water Quality Used for Irrigation: Case Study of Josepdam Irrigation Scheme

Authors: M. A. Adejumobi, J. O. Ojediran

Abstract:

The aim of irrigation is to recharge the available water in the soil. Quality of irrigation water is essential for the yield and quality of crops produced, maintenance of soil productivity and protection of the environment. The analysis of irrigation water arises as a need to know the impact of irrigation water on the yield of crops, the effect, and the necessary control measures to rectify the effect of this for optimum production and yield of crops. This study was conducted to assess the quality of irrigation water with its performance on crop planted, in Josepdam irrigation scheme Bacita, Nigeria. Field visits were undertaken to identify and locate water supply sources and collect water samples from these sources; X1 Drain, Oshin, River Niger loop and Ndafa. Laboratory experiments were then undertaken to determine the quality of raw water from these sources. The analysis was carried for various parameters namely; physical and chemical analyses after water samples have been taken from four sources. The samples were tested in laboratory. Results showed that the raw water sources shows no salinity tendencies with SAR values less than 1me/l and Ecvaules at Zero while the pH were within the recommended range by FAO, there are increase in potassium and sulphate content contamination in three of the location. From this, it is recommended that there should be proper monitoring of the scheme by conducting analysis of water and soil in the environment, preferable test should be carried out at least one year to cover the impact of seasonal variations and to determine the physical and chemical analysis of the water used for irrigation at the scheme.

Keywords: Irrigation, Salinity, Raw water quality, Scheme.

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75 Emerging Wireless Standards - WiFi, ZigBee and WiMAX

Authors: Bhavneet Sidhu, Hardeep Singh, Amit Chhabra

Abstract:

The world of wireless telecommunications is rapidly evolving. Technologies under research and development promise to deliver more services to more users in less time. This paper presents the emerging technologies helping wireless systems grow from where we are today into our visions of the future. This paper will cover the applications and characteristics of emerging wireless technologies: Wireless Local Area Networks (WiFi-802.11n), Wireless Personal Area Networks (ZigBee) and Wireless Metropolitan Area Networks (WiMAX). The purpose of this paper is to explain the impending 802.11n standard and how it will enable WLANs to support emerging media-rich applications. The paper will also detail how 802.11n compares with existing WLAN standards and offer strategies for users considering higher-bandwidth alternatives. The emerging IEEE 802.15.4 (ZigBee) standard aims to provide low data rate wireless communications with high-precision ranging and localization, by employing UWB technologies for a low-power and low cost solution. WiMAX (Worldwide Interoperability for Microwave Access) is a standard for wireless data transmission covering a range similar to cellular phone towers. With high performance in both distance and throughput, WiMAX technology could be a boon to current Internet providers seeking to become the leader of next generation wireless Internet access. This paper also explores how these emerging technologies differ from one another.

Keywords: MIMO technology, WiFi, WiMAX, ZigBee.

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74 Design and Construction of the Semi-Automatic Sliced Ginger Machine

Authors: J. Chatthong, W. Boonchouytan, R. Burapa

Abstract:

The purpose of study was to design and construction the semi-automatic sliced ginger machine for reduce production times in sheet and slice ginger procedure furthermore, reduced amount of labor of slides and cutting method. Take consider into clean and safety of workers and consumers. The principle of machines, used 1 horsepower motor, rotation speed of sliced blade 967 rpm, the diameter of sliced dish 310 mm, consists of 2 blades for sheet cutting ginger and the power from motor which transfer to rotate the sliced blade roller, rotation speed 440 rpm. The slice cutter roller was sliced ginger from sheet ginger to line ginger. The conveyer could adjustment level of motors, used to the beginning area that sheet ginger was transference to the roller for sheet and sliced cutting in next process. The cover of sliced cutting had channel for 1 tuber of ginger. The semi-automatic sliced ginger machine could produced sheet ginger 81.8 kg/h (6.2 times of labor) and line ginger 17.9 kg/h (2.5 times of labor) compare with, labor work could produced sheet ginger 13.2 kg/h and line ginger 7.1 kg/h, and when timekeeper, the total times of semi auto machine 30.86 kg/h and labor 4.6 kg/h, there for the semi auto machine was 6.7 times of labor. The semiautomatic sliced ginger machine convenient, easy for use and maintain, in addition to reduce fatigue of body and seriousness from works; must be used high skill, and protection accident in slicing procedure. Beside, machine could used with other vegetables for example potato, carrot .etc

Keywords: Sliced Machine, Sliced Ginger, Line Ginger

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73 Wildfires Assessed by Remote Sense Images and Burned Land Monitoring

Authors: M. C. Proença

Abstract:

The tools described in this paper enable the location of burned areas where took place the annihilation of natural habitats and establishes a baseline for major changes in forest ecosystems during recovery. Moreover, the result allows the follow up of the surface fuel loading, allowing the evaluation and guidance of restoration measures to remote areas by phased time planning. This case study implements the evaluation of burned areas that suffered successive wildfires in Portugal mainland during the summer of 2017, killing more than 60 people. The goal is to show that this evaluation can be done with remote sense data free of charges in a simple laptop, with open-source software, describing the not-so-simple methodology step by step, to make it accessible for local workers in the areas attained, where the availability of information is essential for the immediate planning of mitigation measures, such as restoring road access, allocate funds for the recovery of human dwellings and assess further needs for restoration of the ecological system. Wildfires also devastate forest ecosystems having a direct impact on vegetation cover and killing or driving away the animal population, besides loss of all crops in rural areas that are essential as local resources. The economic interests are also attained, as the pinewood burned becomes useless for the noblest applications, so its value decreases, and resin extraction ends for several years.

Keywords: Image processing, remote sensing, wildfires, burned areas, SENTINEL-2.

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72 Dicotyledon Weed Quantification Algorithm for Selective Herbicide Application in Maize Crops: Statistical Evaluation of the Potential Herbicide Savings

Authors: Morten Stigaard Laursen, Rasmus Nyholm Jørgensen, Henrik Skov Midtiby, Anders Krogh Mortensen, Sanmohan Baby

Abstract:

This work contributes a statistical model and simulation framework yielding the best estimate possible for the potential herbicide reduction when using the MoDiCoVi algorithm all the while requiring a efficacy comparable to conventional spraying. In June 2013 a maize field located in Denmark were seeded. The field was divided into parcels which was assigned to one of two main groups: 1) Control, consisting of subgroups of no spray and full dose spraty; 2) MoDiCoVi algorithm subdivided into five different leaf cover thresholds for spray activation. In addition approximately 25% of the parcels were seeded with additional weeds perpendicular to the maize rows. In total 299 parcels were randomly assigned with the 28 different treatment combinations. In the statistical analysis, bootstrapping was used for balancing the number of replicates. The achieved potential herbicide savings was found to be 70% to 95% depending on the initial weed coverage. However additional field trials covering more seasons and locations are needed to verify the generalisation of these results. There is a potential for further herbicide savings as the time interval between the first and second spraying session was not long enough for the weeds to turn yellow, instead they only stagnated in growth.

Keywords: Weed crop discrimination, macrosprayer, herbicide reduction, site-specific, sprayer-boom.

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71 Hiding Data in Images Using PCP

Authors: Souvik Bhattacharyya, Gautam Sanyal

Abstract:

In recent years, everything is trending toward digitalization and with the rapid development of the Internet technologies, digital media needs to be transmitted conveniently over the network. Attacks, misuse or unauthorized access of information is of great concern today which makes the protection of documents through digital media a priority problem. This urges us to devise new data hiding techniques to protect and secure the data of vital significance. In this respect, steganography often comes to the fore as a tool for hiding information. Steganography is a process that involves hiding a message in an appropriate carrier like image or audio. It is of Greek origin and means "covered or hidden writing". The goal of steganography is covert communication. Here the carrier can be sent to a receiver without any one except the authenticated receiver only knows existence of the information. Considerable amount of work has been carried out by different researchers on steganography. In this work the authors propose a novel Steganographic method for hiding information within the spatial domain of the gray scale image. The proposed approach works by selecting the embedding pixels using some mathematical function and then finds the 8 neighborhood of the each selected pixel and map each bit of the secret message in each of the neighbor pixel coordinate position in a specified manner. Before embedding a checking has been done to find out whether the selected pixel or its neighbor lies at the boundary of the image or not. This solution is independent of the nature of the data to be hidden and produces a stego image with minimum degradation.

Keywords: Cover Image, LSB, Pixel Coordinate Position (PCP), Stego Image.

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70 Comparison of Stationary and Two-Axis Tracking System of 50MW Photovoltaic Power Plant in Al-Kufra, Libya: Landscape Impact and Performance

Authors: Yasser Aldali

Abstract:

The scope of this paper is to evaluate and compare the potential of LS-PV(Large Scale Photovoltaic Power Plant) power generation systems in the southern region of Libya at Al-Kufra for both stationary and tracking systems. A Microsoft Excel-VBA program has been developed to compute slope radiation, dew-point, sky temperature, and then cell temperature, maximum power output and module efficiency of the system for stationary system and for tracking system. The results for energy production show that the total energy output is 114GWh/year for stationary system and 148GWh/year for tracking system. The average module efficiency for the stationary system is 16.6% and 16.2% for the tracking system.

The values of electricity generation capacity factor (CF) and solar capacity factor (SCF) for stationary system were found to be 26% and 62.5% respectively and 34% and 82% for tracking system. The GCR (Ground Cover Ratio) for a stationary system is 0.7, which corresponds to a tilt angle of 24°. The GCR for tracking system was found to be 0.12. The estimated ground area needed to build a 50MW PV plant amounts to approx. 0.55km2 for a stationary PV field constituted by HIT PV arrays and approx. 91MW/ km2. In case of a tracker PV field, the required ground area amounts approx.2.4km2 and approx. 20.5MW/ km2.

Keywords: Large PV power plant, solar energy, environmental impact, Dual-axis tracking system, stationary system.

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69 From Electroencephalogram to Epileptic Seizures Detection by Using Artificial Neural Networks

Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

Abstract:

Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: Artificial Neural Network, Data Mining, Electroencephalogram, Epilepsy, Feature Extraction, Seizure Detection, Signal Processing.

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68 The Use of Artificial Neural Network in Option Pricing: The Case of S and P 100 Index Options

Authors: Zeynep İltüzer Samur, Gül Tekin Temur

Abstract:

Due to the increasing and varying risks that economic units face with, derivative instruments gain substantial importance, and trading volumes of derivatives have reached very significant level. Parallel with these high trading volumes, researchers have developed many different models. Some are parametric, some are nonparametric. In this study, the aim is to analyse the success of artificial neural network in pricing of options with S&P 100 index options data. Generally, the previous studies cover the data of European type call options. This study includes not only European call option but also American call and put options and European put options. Three data sets are used to perform three different ANN models. One only includes data that are directly observed from the economic environment, i.e. strike price, spot price, interest rate, maturity, type of the contract. The others include an extra input that is not an observable data but a parameter, i.e. volatility. With these detail data, the performance of ANN in put/call dimension, American/European dimension, moneyness dimension is analyzed and whether the contribution of the volatility in neural network analysis make improvement in prediction performance or not is examined. The most striking results revealed by the study is that ANN shows better performance when pricing call options compared to put options; and the use of volatility parameter as an input does not improve the performance.

Keywords: Option Pricing, Neural Network, S&P 100 Index, American/European options

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67 Investigating the Demand for Short-shelf Life Food Products for SME Wholesalers

Authors: Yamini Raju, Parminder S. Kang, Adam Moroz, Ross Clement, Ashley Hopwell, Alistair Duffy

Abstract:

Accurate forecasting of fresh produce demand is one the challenges faced by Small Medium Enterprise (SME) wholesalers. This paper is an attempt to understand the cause for the high level of variability such as weather, holidays etc., in demand of SME wholesalers. Therefore, understanding the significance of unidentified factors may improve the forecasting accuracy. This paper presents the current literature on the factors used to predict demand and the existing forecasting techniques of short shelf life products. It then investigates a variety of internal and external possible factors, some of which is not used by other researchers in the demand prediction process. The results presented in this paper are further analysed using a number of techniques to minimize noise in the data. For the analysis past sales data (January 2009 to May 2014) from a UK based SME wholesaler is used and the results presented are limited to product ‘Milk’ focused on café’s in derby. The correlation analysis is done to check the dependencies of variability factor on the actual demand. Further PCA analysis is done to understand the significance of factors identified using correlation. The PCA results suggest that the cloud cover, weather summary and temperature are the most significant factors that can be used in forecasting the demand. The correlation of the above three factors increased relative to monthly and becomes more stable compared to the weekly and daily demand.

Keywords: Demand Forecasting, Deteriorating Products, Food Wholesalers, Principal Component Analysis and Variability Factors.

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66 An Experimental Study on the Effect of Operating Parameters during the Micro-Electro-Discharge Machining of Ni Based Alloy

Authors: Asma Perveen, M. P. Jahan

Abstract:

Ni alloys have managed to cover wide range of applications such as automotive industries, oil gas industries, and aerospace industries. However, these alloys impose challenges while using conventional machining technologies. On the other hand, Micro-Electro-Discharge machining (micro-EDM) is a non-conventional machining method that uses controlled sparks energy to remove material irrespective of the materials hardness. There has been always a huge interest from the industries for developing optimum methodology and parameters in order to enhance the productivity of micro-EDM in terms of reducing machining time and tool wear for different alloys. Therefore, the aims of this study are to investigate the effects of the micro-EDM process parameters, in order to find their optimal values. The input process parameters include voltage, capacitance, and electrode rotational speed, whereas the output parameters considered are machining time, entrance diameter of hole, overcut, tool wear, and crater size. The surface morphology and element characterization are also investigated with the use of SEM and EDX analysis. The experimental result indicates the reduction of machining time with the increment of discharge energy. Discharge energy also contributes to the enlargement of entrance diameter as well as overcut. In addition, tool wears show reduction with the increase of discharge energy. Moreover, crater size is found to be increased in size along with the increment of discharge energy.

Keywords: Micro EDM, Ni alloy, discharge energy, micro-holes.

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