Search results for: morphological operations
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2614

Search results for: morphological operations

2524 Morphological and Molecular Analysis of Selected Fast-Growing Blue Swimming Crab (Portunus pelagicus) in South of Sulawesi

Authors: Yushinta Fujaya, Andi Ivo Asphama, Andi Parenrengi, Andi Tenriulo

Abstract:

Blue Swimming crab (Portunus pelagicus) is an important commercial species throughout the subtropical waters and as such constitutes part of the fisheries resources. Data are lacking on the morphological variations of selected fast-growing crabs reared in a pond. This study aimed to analyze the morphological and molecular character of a selected fast-growing crab reared in ponds in South of Sulawesi. The crab seeds were obtained from local fish-trap and hatchery. A study on the growth was carried out in the population of crabs. The dimensions analyzed were carapace width (CW) measured after 3 months of grow out. Morphological character states were examined based on the pattern of spots on the carapace. Molecular analysis was performed using RAPD (Random Amplified Polymorphic DNA). Genetic distance was analysed using TFPGA (Tools for Population Genetic Analyses) version 1.3. The results showed that there were variations in the growth of crabs. These crabs clustered morphologically into three quite distinct groups. The crab with white spots irregularly spread over its carapace was the largest size while the crab with large white spots scattered over the carapace was the smaller size (3%). The crab with small white spots scattered over the carapace was the smallest size found in this study. Molecular analysis showed that there are morphologically and genetically different between groups of crabs. Genetic distances among crabs ranged from 0.1527 to 0.5856. Thus, this study provides information the use of white spots pattern over carapace as indicators to identify the type of blue swimming crabs.

Keywords: crab, portunus pelagicus, morphology, RAPD, Carapace

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2523 An Advanced Automated Brain Tumor Diagnostics Approach

Authors: Berkan Ural, Arif Eser, Sinan Apaydin

Abstract:

Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.

Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition

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2522 The Emergence of Construction Mafia in South Africa: The Implication on the Construction Industry

Authors: Thandokazi Nyangiwe, Christopher Amoah, Charles P. Mukumba

Abstract:

The South African construction sector is threatened by emerging black business forums called construction mafias. The emergence of the construction mafia has culminated in the disruptions and abandonment of construction sites resulting in the loss of jobs for construction workers. The paper examines the origin of construction mafias and their impact on the construction sector, including the potential ways to cope with their operations. A qualitative research approach was adopted for this study using open-ended interview questions to gather information from 30 key construction industry stakeholders, including contractors, subcontractors, consultants, and the construction project communities. Content and thematic analysis were used to analyse the data collected. The findings suggest that most participants do not fully understand the existence and operations of construction mafias in the construction industry. Construction mafias claim to be part of the local business forums. They disrupt construction projects and demand a certain amount, usually 30% of the construction value. Construction mafias frequently resort to intimidation and violence if their demands are unmet. Their operations have resulted in delayed completion of construction projects, abandonment of projects, and loss of income for the contractor and jobs for the construction workers. The interviews were limited to construction stakeholders. Because of the nature of the mafias’ operations, they could not be accessed for interviews for fear of being identified because of the connotation attached to their role as construction mafias. Construction project owners face disruptions of projects resulting in loss of equipment, materials, and income. Therefore, there is a need to sensitise the construction stakeholders in the construction industry regarding the existence and operations of the construction mafia and the implications on construction project performance and delivery. The findings will give insight into the operations of the construction mafias in the South African construction industry, which has caused disruptions in construction project sites. Stakeholders must find solutions to address the construction mafias’ disruptive actions on construction projects. The study presents an initial inquiry that will come up with how to manage and cope with the growing operations of construction mafias in the South African construction industry.

Keywords: black business forums, construction mafia, emergence, implication

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2521 Contribution to the Study of Phenotypic, Reproduction and Growth Parameters of Sheep in Eastern Algeria

Authors: Mohammed Titaouine, Toufik Meziane, Kahramen Deghnouche, Hanane Mohamdi, Nabil Mohamdi

Abstract:

In order to better understand the morphological characters and the zootechniques measures of sheeps races in the in South-East Algeria, a study that was conducted on 1344 heads, taken from 8 farms in different parts of the region, namely T’kout 1, T’kout 2, Tafrent, Barika, Sidi-Okba, Biskra, Ouled-Djellal and Msila. The results from the present study showed significant differences in the group of 14 morphological studied variables, the body length is the most important variable. Reproduction performance of 160 ewes and growth performances of 56 lambs were analysed. The analyses of the data showed that the ewes have a fertility level of 69%, a prolificacy level of 114% and a fecundity level of 79%. Lambs weigh 3.5kg at birth, 9.38kg at 30d, 13.45kg at 60d, 16.91kg at 90d and 21.51 kg at 120d. The speed of the growth level 0.20kg/d from birth to 30d, 0.14 kg/d between 30d and 60d, 0.12kg/d between 60d and 90d and 0.15kg/d between 90d and 120d. The simple born lambs were more heavy than the double born lambs. By contrast, sex was not significant for all the variables except the weight at 60d, the birth month has a significant effect on the weight at birth, at 30d, at 60d and it was no significant for the weight at 90d and at 120d.The flocks born on September, October, November, and December were more heavy than the flocks born on January, February, and March.

Keywords: morphological characterization, reproduction performance, growth performances, algeria

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2520 Association between Physical Composition, Swimming Performance and Somatotype of Male Competitive Swimmers of Age Group 10-13 Years

Authors: Ranjit Singh

Abstract:

Body fat % lean body mass and body type play vital role in sports performance. A sports person who is having optional body composition can show its performance flawlessly whereas other who is not physical fit may be more prone to injury. Competitive swimming is an association of plethora of aspects like morphological, physiological, biochemical, biomechanical and psychological. The primary key of the present research is to examine the correlation among selected morphological dimensions such as height, weight, body fat%, lean body mass, somatotype and swimming performance. The present study also focused to investigate by potential deficiencies if any and to find out remedial measures to curb the training stresses. Thirty (age group 10-14 years) swimmers undergoing training under skilled and professional coaches were selected in the present study. The morphological variables and performance criterion like 50 meter swimming time and speed were calculated by using standard training methodology. Correlation coefficient among body composition, somatotype and performance variables were assessed by using standard statistical package SPSS. Mean height, weight, fat% and lean body mass of the present group is 150.97±8.68 cm, 44.0±9.34 kg., 15.97±4.42 % and 37.10±8.77 kg respectively. Somatotype of the young swimmers of this research is revealed ectomorphic mesomorph. The analysis of the results Illustrated that swimming performance is significantly correlated (p<0.05) with height, body weight, mesomorphoic component and lean body mass. Body fat is significantly and negatively correlated (p<0.05) with mesomorphic component, lean body mass and swimming speed. From this present study, it can be concluded that along with techniques and tactics other the physical attributes also play significant role in swimming performance which can help the swimmers to excel in higher level of competition and swimmers having improved morphological qualities can ultimately perform well.

Keywords: body fat, mass, mesomorphic component, somatotype

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2519 Diversity and Taxonomy: Malaysian Marine Algae Genus Halimeda (Halimedaceae, Chlorophyta)

Authors: Nur Farah Ain Zainee, Ahmad Ismail, Nazlina Ibrahim, Asmida Ismail

Abstract:

The study of genus Halimeda in Malaysia is in the early stage due to less specific study on its taxonomy. Most of the previous research tend to choose other genus such as Caulerpa and Gracilaria because of the potential of being utilized. The identification of Halimeda is complex by the high morphological variation within individual species due to different types of habitat and the changes in composition of seawater. The study was completed to study the diversity and distribution of Halimeda in Malaysia and to identify the morphological and anatomical differences between Halimeda species. The methods which have been used for this study are collection of Halimeda and seawater, preservation of specimen, identification of the specimen including the preparation of the temporary slide and decalcification of the calcium layer by using diluted hydrochloric acid. The specimen were processed in laboratory and kept as herbarium specimen in Algae Herbarium, Universiti Kebangsaan Malaysia. Environmental parameters were tested by using YSI multiparameter probe and the recorded data were temperature, salinity, pH and dissolved oxygen. The nutrient content of seawater such as nitrate and phosphate were analysed by using Hach kit model DR 2000. In the present study, out of 330 herbarium specimen, ten species were identified as Halimeda cuneata, H. discoidea, H. macroloba, H. macrophysa, H. opuntia, H. simulans, H. stuposa, H. taenicola, H. tuna and H. velasquezii. Of these, five species were new record to Malaysia. They are Halimeda cuneata, H. macrophysa, H. stuposa, H. taenicola and H. velasquezii. H. opuntia was found as the most abundance species with wide distribution in Malaysia coastal area. Meanwhile, from the study of their distribution, two localities in which Pulau Balak Balak, Kudat and Pulau Langkawi, Kedah, were noted having high number of Halimeda species. As a conclusion, this study has successfully identified ten species of Halimeda of Malaysia with full description of morphological characteristics that may assist further researcher to differentiate and identify Halimeda.

Keywords: Distribution, diversity, Halimeda, morphological, taxonomy

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2518 Morpheme Based Parts of Speech Tagger for Kannada Language

Authors: M. C. Padma, R. J. Prathibha

Abstract:

Parts of speech tagging is the process of assigning appropriate parts of speech tags to the words in a given text. The critical or crucial information needed for tagging a word come from its internal structure rather from its neighboring words. The internal structure of a word comprises of its morphological features and grammatical information. This paper presents a morpheme based parts of speech tagger for Kannada language. This proposed work uses hierarchical tag set for assigning tags. The system is tested on some Kannada words taken from EMILLE corpus. Experimental result shows that the performance of the proposed system is above 90%.

Keywords: hierarchical tag set, morphological analyzer, natural language processing, paradigms, parts of speech

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2517 Segmentation of the Liver and Spleen From Abdominal CT Images Using Watershed Approach

Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

Abstract:

The phase of segmentation is an important step in the processing and interpretation of medical images. In this paper, we focus on the segmentation of liver and spleen from the abdomen computed tomography (CT) images. The importance of our study comes from the fact that the segmentation of ROI from CT images is usually a difficult task. This difficulty is the gray’s level of which is similar to the other organ also the ROI are connected to the ribs, heart, kidneys, etc. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to remove the surrounding and connected organs and tissues by applying morphological filters. This first step makes the extraction of interest regions easier. The second step consists of improving the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce these deficiencies by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

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2516 Agro Morphological Characterization of Vicia Faba L. Accessions in the Kingdom of Saudi Arabia

Authors: Zia Amjad, Salem S. Alghamdi

Abstract:

This experiment was carried out at student educational farm College of Food and Agriculture, KSU, kingdom of Saudi Arabia; in order to characterize 154 V. faba accessions based on UPOV and IBPGR descriptors. 24 agro-morphological characters including 11 quantitative and 13 qualitative were observed for genetic variation. All the results were analyzed using multivariate analysis i.e. principle component analysis (PCA). First six principle components (PC) had Eigen-value greater than one; accounted for 72% of available V. faba genetic diversity. However first three components revealed more than 10% of genetic diversity each i.e. 22.36%, 15.86% and 10.89% respectively. PCA distributed the V. faba accessions into different groups based on their performance for the characters under observation. PC-1 which represented 22.36% of the genetic diversity was positively associated with stipule spot pigmentation, intensity of streaks, pod degree of curvature and to some extent with 100 seed weight. PC-2 covered 15.86 of the genetic diversity and showed positive association for average seed weight per plant, pod length, number of seeds per plant, 100 seed weight, stipule spot pigmentation, intensity of streaks (same as in PC-1) and to some extent for pod degree of curvature and number of pods per plant. PC-3 revealed 10.89% of genetic diversity and expressed positive association for number of pods per plant and number of leaflets per plant.

Keywords: agro morphological characterization, diversity, vicia faba, PCA

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2515 Arabic Light Word Analyser: Roles with Deep Learning Approach

Authors: Mohammed Abu Shquier

Abstract:

This paper introduces a word segmentation method using the novel BP-LSTM-CRF architecture for processing semantic output training. The objective of web morphological analysis tools is to link a formal morpho-syntactic description to a lemma, along with morpho-syntactic information, a vocalized form, a vocalized analysis with morpho-syntactic information, and a list of paradigms. A key objective is to continuously enhance the proposed system through an inductive learning approach that considers semantic influences. The system is currently under construction and development based on data-driven learning. To evaluate the tool, an experiment on homograph analysis was conducted. The tool also encompasses the assumption of deep binary segmentation hypotheses, the arbitrary choice of trigram or n-gram continuation probabilities, language limitations, and morphology for both Modern Standard Arabic (MSA) and Dialectal Arabic (DA), which provide justification for updating this system. Most Arabic word analysis systems are based on the phonotactic morpho-syntactic analysis of a word transmitted using lexical rules, which are mainly used in MENA language technology tools, without taking into account contextual or semantic morphological implications. Therefore, it is necessary to have an automatic analysis tool taking into account the word sense and not only the morpho-syntactic category. Moreover, they are also based on statistical/stochastic models. These stochastic models, such as HMMs, have shown their effectiveness in different NLP applications: part-of-speech tagging, machine translation, speech recognition, etc. As an extension, we focus on language modeling using Recurrent Neural Network (RNN); given that morphological analysis coverage was very low in dialectal Arabic, it is significantly important to investigate deeply how the dialect data influence the accuracy of these approaches by developing dialectal morphological processing tools to show that dialectal variability can support to improve analysis.

Keywords: NLP, DL, ML, analyser, MSA, RNN, CNN

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2514 Algorithm for Path Recognition in-between Tree Rows for Agricultural Wheeled-Mobile Robots

Authors: Anderson Rocha, Pedro Miguel de Figueiredo Dinis Oliveira Gaspar

Abstract:

Machine vision has been widely used in recent years in agriculture, as a tool to promote the automation of processes and increase the levels of productivity. The aim of this work is the development of a path recognition algorithm based on image processing to guide a terrestrial robot in-between tree rows. The proposed algorithm was developed using the software MATLAB, and it uses several image processing operations, such as threshold detection, morphological erosion, histogram equalization and the Hough transform, to find edge lines along tree rows on an image and to create a path to be followed by a mobile robot. To develop the algorithm, a set of images of different types of orchards was used, which made possible the construction of a method capable of identifying paths between trees of different heights and aspects. The algorithm was evaluated using several images with different characteristics of quality and the results showed that the proposed method can successfully detect a path in different types of environments.

Keywords: agricultural mobile robot, image processing, path recognition, hough transform

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2513 An Improved Ant Colony Algorithm for Genome Rearrangements

Authors: Essam Al Daoud

Abstract:

Genome rearrangement is an important area in computational biology and bioinformatics. The basic problem in genome rearrangements is to compute the edit distance, i.e., the minimum number of operations needed to transform one genome into another. Unfortunately, unsigned genome rearrangement problem is NP-hard. In this study an improved ant colony optimization algorithm to approximate the edit distance is proposed. The main idea is to convert the unsigned permutation to signed permutation and evaluate the ants by using Kaplan algorithm. Two new operations are added to the standard ant colony algorithm: Replacing the worst ants by re-sampling the ants from a new probability distribution and applying the crossover operations on the best ants. The proposed algorithm is tested and compared with the improved breakpoint reversal sort algorithm by using three datasets. The results indicate that the proposed algorithm achieves better accuracy ratio than the previous methods.

Keywords: ant colony algorithm, edit distance, genome breakpoint, genome rearrangement, reversal sort

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2512 Morphological Characteristics and Bioreactivity of Inhalable Particles during the Temple Fair in Kaifeng

Authors: Qiao Yushuang, Shao Longyi

Abstract:

This paper presents the result of plasmid assay of inhalable particulates PM10 and PM2.5 that were collected during the period of the 11th Hanyuan temple fair of ancestor worship in Kaifeng City. By use of a high-resolution Field Emission Scanning Electron Microscopy (FESEM) and image analysis (IA) technology, the morphological characteristics and Particle Size Distribution (PSD) of each were analyzed and the Bioreactivity of PM10 was evaluated by using plasmid DNA assay. The result shows that, as the dominant component of the samples taken in the urban area of Kaifeng City, the mineral particles, compared with the other components including the soot aggregates, coal ash, and unidentified particles, have a much greater amount and volume. The mineral particles exhibited a decentralized quantity - size distribution, whose presence could be available among the particles sizing 2.5μm or smaller. In contrast, the volume-size distribution of mineral particles is scattered in a relatively narrow range of between1μm and 2.5μm. According to the plasmid assay the TD50 (toxic dose of PM causing 50% of plasmid damage, expressed in μg/ml) of water-soluble PM10 and whole fraction of Kaifeng airborne PM10 was measured respectively at 220-208μg/ml and 300-400μg/ml versus 160μg/ml and 190μg/ml for PM2.5. It can be seen that the whole fraction of airborne particles caused more oxidative damage than the water-soluble fractions, and the PM2.5 has a greater oxidative capacity than the PM10.

Keywords: inhalable particulates (PM10 and PM2.5), morphological features, bioreactivity, Kaifeng

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2511 Enhanced Thermal, Mechanical and Morphological Properties of CNT/HDPE Nanocomposite Using MMT as Secondary Filler

Authors: M. E. Ali Mohsin, Agus Arsad, Othman Y. Alothman

Abstract:

This study explains the influence of secondary filler on the dispersion of carbon nanotube (CNT) reinforced high density polyethylene (HDPE) nanocomposites (CNT/HDPE). In order to understand the mixed-fillers system, Montmorillonite (MMT) was added to CNT/HDPE nanocomposites. It was followed by investigating their effect on the thermal, mechanical and morphological properties of the aforesaid nanocomposite. Incorporation of 3 wt% each of MMT into CNT/HDPE nanocomposite resulted to the increased values for the tensile and flexural strength, as compared to the pure HDPE matrix. The thermal analysis result showed improved thermal stability of the formulated nanocomposites. Transmission electron microscopy (TEM) images revealed that larger aggregates of CNTs were disappeared upon addition of these two components leading to the enhancement of thermo-mechanical properties for such composites.

Keywords: secondary filler, montmorillonite, carbon nanotube, nanocomposite

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2510 Towards Better Quality in Healthcare and Operations Management: A Developmental Literature Review

Authors: Marc Dorval, Marie-Hélène Jobin

Abstract:

This work presents the various perspectives, dimensions, components and definitions given to quality in the operations management (OM) and healthcare services (HCS) literature in time, highlighting gaps and learning opportunities between the two disciplines through a thorough search into their rich and distinct body of knowledge. Greater and new insights about the general nature of quality are obtained with findings such as in OM, quality has been approached in six fairly distinct paradigms (excellence, value, conformity to specifications, attributes, satisfaction and meeting or exceeding customer expectations), whereas in HCS, two approaches are prominent (Donabedian’s structure, process and outcomes model and Lohr and Schroeder’s circumscribed definition). The two disciplines views on quality seem to have progressed much in parallel with little cross-learning from each other. This work then proposes an encompassing definition of quality as a lever and suggests further research and development avenues for a better use of the concept of quality by academics and practitioners alike toward the goals of greater organizational performance and improved management in healthcare and possibly other service domains.

Keywords: healthcare, management, operations, quality, services

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2509 Dynamic Background Updating for Lightweight Moving Object Detection

Authors: Kelemewerk Destalem, Joongjae Cho, Jaeseong Lee, Ju H. Park, Joonhyuk Yoo

Abstract:

Background subtraction and temporal difference are often used for moving object detection in video. Both approaches are computationally simple and easy to be deployed in real-time image processing. However, while the background subtraction is highly sensitive to dynamic background and illumination changes, the temporal difference approach is poor at extracting relevant pixels of the moving object and at detecting the stopped or slowly moving objects in the scene. In this paper, we propose a moving object detection scheme based on adaptive background subtraction and temporal difference exploiting dynamic background updates. The proposed technique consists of a histogram equalization, a linear combination of background and temporal difference, followed by the novel frame-based and pixel-based background updating techniques. Finally, morphological operations are applied to the output images. Experimental results show that the proposed algorithm can solve the drawbacks of both background subtraction and temporal difference methods and can provide better performance than that of each method.

Keywords: background subtraction, background updating, real time, light weight algorithm, temporal difference

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2508 Energy Interaction among HVAC and Supermarket Environment

Authors: Denchai Woradechjumroen, Haorong Li, Yuebin Yu

Abstract:

Supermarkets are the most electricity-intensive type of commercial buildings. The unsuitable indoor environment of a supermarket provided by abnormal HVAC operations incurs waste energy consumption in refrigeration systems. This current study briefly describes significantly solid backgrounds and proposes easy-to-use analysis terminology for investigating the impact of HVAC operations on refrigeration power consumption using the field-test data obtained from building automation system (BAS). With solid backgrounds and prior knowledge, expected energy interactions between HVAC and refrigeration systems are proposed through Pearson’s correlation analysis (R value) by considering correlations between equipment power consumption and dominantly independent variables (driving force conditions). The R value can be conveniently utilized to evaluate how strong relations between equipment operations and driving force parameters are. The calculated R values obtained from field data are compared to expected ranges of R values computed by energy interaction methodology. The comparisons can separate the operational conditions of equipment into faulty and normal conditions. This analysis can simply investigate the condition of equipment operations or building sensors because equipment could be abnormal conditions due to routine operations or faulty commissioning processes in field tests. With systematically solid and easy-to-use backgrounds of interactions provided in the present article, the procedures can be utilized as a tool to evaluate the proper commissioning and routine operations of HVAC and refrigeration systems to detect simple faults (e.g. sensors and driving force environment of refrigeration systems and equipment set-point) and optimize power consumption in supermarket buildings. Moreover, the analysis will be used to further study FDD research for supermarkets in future.

Keywords: energy interaction, HVAC, R-value, supermarket buildings

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2507 Parallel Vector Processing Using Multi Level Orbital DATA

Authors: Nagi Mekhiel

Abstract:

Many applications use vector operations by applying single instruction to multiple data that map to different locations in conventional memory. Transferring data from memory is limited by access latency and bandwidth affecting the performance gain of vector processing. We present a memory system that makes all of its content available to processors in time so that processors need not to access the memory, we force each location to be available to all processors at a specific time. The data move in different orbits to become available to other processors in higher orbits at different time. We use this memory to apply parallel vector operations to data streams at first orbit level. Data processed in the first level move to upper orbit one data element at a time, allowing a processor in that orbit to apply another vector operation to deal with serial code limitations inherited in all parallel applications and interleaved it with lower level vector operations.

Keywords: Memory Organization, Parallel Processors, Serial Code, Vector Processing

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2506 A Review of Fractal Dimension Computing Methods Applied to Wear Particles

Authors: Manish Kumar Thakur, Subrata Kumar Ghosh

Abstract:

Various types of particles found in lubricant may be characterized by their fractal dimension. Some of the available methods are: yard-stick method or structured walk method, box-counting method. This paper presents a review of the developments and progress in fractal dimension computing methods as applied to characteristics the surface of wear particles. An overview of these methods, their implementation, their advantages and their limits is also present here. It has been accepted that wear particles contain major information about wear and friction of materials. Morphological analysis of wear particles from a lubricant is a very effective way for machine condition monitoring. Fractal dimension methods are used to characterize the morphology of the found particles. It is very useful in the analysis of complexity of irregular substance. The aim of this review is to bring together the fractal methods applicable for wear particles.

Keywords: fractal dimension, morphological analysis, wear, wear particles

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2505 Digitalization in Aggregate Quarries

Authors: José Eugenio Ortiz, Pierre Plaza, Josefa Herrero, Iván Cabria, José Luis Blanco, Javier Gavilanes, José Ignacio Escavy, Ignacio López-Cilla, Virginia Yagüe, César Pérez, Silvia Rodríguez, Jorge Rico, Cecilia Serrano, Jesús Bernat

Abstract:

The development of Artificial Intelligence services in mining processes, specifically in aggregate quarries, is facilitating automation and improving numerous aspects of operations. Ultimately, AI is transforming the mining industry by improving efficiency, safety and sustainability. With the ability to analyze large amounts of data and make autonomous decisions, AI offers great opportunities to optimize mining operations and maximize the economic and social benefits of this vital industry. Within the framework of the European DIGIECOQUARRY project, various services were developed for the identification of material quality, production estimation, detection of anomalies and prediction of consumption and production automatically with good results.

Keywords: aggregates, artificial intelligence, automatization, mining operations

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2504 The Strategic Engine Model: Redefined Strategy Structure, as per Market-and Resource-Based Theory Application, Tested in the Automotive Industry

Authors: Krassimir Todorov

Abstract:

The purpose of the paper is to redefine the levels of structure of corporate, business and functional strategies that were established over the past several decades, to a conceptual model, consisting of corporate, business and operations strategies, that are reinforced by functional strategies. We will propose a conceptual framework of different perspectives in the role of strategic operations as a separate strategic place and reposition the remaining functional strategies as supporting tools, existing at all three levels. The proposed model is called ‘the strategic engine’, since the mutual relationships of its ingredients are identical with main elements and working principle of the internal combustion engine. Based on theoretical essence, related to every strategic level, we will prove that the strategic engine model is useful for managers seeking to safeguard the competitive advantage of their companies. Each strategy level is researched through its basic elements. At the corporate level we examine the scope of firm’s product, the vertical and geographical coverage. At the business level, the point of interest is limited to the SWOT analysis’ basic elements. While at operations level, the key research issue relates to the scope of the following performance indicators: cost, quality, speed, flexibility and dependability. In this relationship, the paper provides a different view for the role of operations strategy within the overall strategy concept. We will prove that the theoretical essence of operations goes far beyond the scope of traditionally accepted business functions. Exploring the applications of Resource-based theory and Market-based theory within the strategic levels framework, we will prove that there is a logical consequence of the theoretical impact in corporate, business and operations strategy – at every strategic level, the validity of one theory is substituted to the level of the other. Practical application of the conceptual model is tested in automotive industry. Actually, the proposed theoretical concept is inspired by a leading global automotive group – Inchcape PLC, listed on the London Stock Exchange, and constituent of the FTSE 250 Index.

Keywords: business strategy, corporate strategy, functional strategies, operations strategy

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2503 Tropical Squall Lines in Brazil: A Methodology for Identification and Analysis Based on ISCCP Tracking Database

Authors: W. A. Gonçalves, E. P. Souza, C. R. Alcântara

Abstract:

The ISCCP-Tracking database offers an opportunity to study physical and morphological characteristics of Convective Systems based on geostationary meteorological satellites. This database contains 26 years of tracking of Convective Systems for the entire globe. Then, Tropical Squall Lines which occur in Brazil are certainly within the database. In this study, we propose a methodology for identification of these systems based on the ISCCP-Tracking database. A physical and morphological characterization of these systems is also shown. The proposed methodology is firstly based on the year of 2007. The Squall Lines were subjectively identified by visually analyzing infrared images from GOES-12. Based on this identification, the same systems were identified within the ISCCP-Tracking database. It is known, and it was also observed that the Squall Lines which occur on the north coast of Brazil develop parallel to the coast, influenced by the sea breeze. In addition, it was also observed that the eccentricity of the identified systems was greater than 0.7. Then, a methodology based on the inclination (based on the coast) and eccentricity (greater than 0.7) of the Convective Systems was applied in order to identify and characterize Tropical Squall Lines in Brazil. These thresholds were applied back in the ISCCP-Tracking database for the year of 2007. It was observed that other systems, which were not Squall Lines, were also identified. Then, we decided to call all systems identified by the inclination and eccentricity thresholds as Linear Convective Systems, instead of Squall Lines. After this step, the Linear Convective Systems were identified and characterized for the entire database, from 1983 to 2008. The physical and morphological characteristics of these systems were compared to those systems which did not have the required inclination and eccentricity to be called Linear Convective Systems. The results showed that the convection associated with the Linear Convective Systems seems to be more intense and organized than in the other systems. This affirmation is based on all ISCCP-Tracking variables analyzed. This type of methodology, which explores 26 years of satellite data by an objective analysis, was not previously explored in the literature. The physical and morphological characterization of the Linear Convective Systems based on 26 years of data is of a great importance and should be used in many branches of atmospheric sciences.

Keywords: squall lines, convective systems, linear convective systems, ISCCP-Tracking

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2502 Parkinson’s Disease Hand-Eye Coordination and Dexterity Evaluation System

Authors: Wann-Yun Shieh, Chin-Man Wang, Ya-Cheng Shieh

Abstract:

This study aims to develop an objective scoring system to evaluate hand-eye coordination and hand dexterity for Parkinson’s disease. This system contains three boards, and each of them is implemented with the sensors to sense a user’s finger operations. The operations include the peg test, the block test, and the blind block test. A user has to use the vision, hearing, and tactile abilities to finish these operations, and the board will record the results automatically. These results can help the physicians to evaluate a user’s reaction, coordination, dexterity function. The results will be collected to a cloud database for further analysis and statistics. A researcher can use this system to obtain systematic, graphic reports for an individual or a group of users. Particularly, a deep learning model is developed to learn the features of the data from different users. This model will help the physicians to assess the Parkinson’s disease symptoms by a more intellective algorithm.

Keywords: deep learning, hand-eye coordination, reaction, hand dexterity

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2501 Physical and Morphological Response to Land Reclamation Projects in a Wave-Dominated Bay

Authors: Florian Monetti, Brett Beamsley, Peter McComb, Simon Weppe

Abstract:

Land reclamation from the ocean has considerably increased over past decades to support worldwide rapid urban growth. Reshaping the coastline, however, inevitably affects coastal systems. One of the main challenges for coastal oceanographers is to predict the physical and morphological responses for nearshore systems to man-made changes over multiple time-scales. Fully-coupled numerical models are powerful tools for simulating the wide range of interactions between flow field and bedform morphology. Restricted and inconsistent measurements, combined with limited computational resources, typically make this exercise complex and uncertain. In the present study, we investigate the impact of proposed land reclamation within a wave-dominated bay in New Zealand. For this purpose, we first calibrated our morphological model based on the long-term evolution of the bay resulting from land reclamation carried out in the 1950s. This included the application of sedimentological spin-up and reduction techniques based on historical bathymetry datasets. The updated bathymetry, including the proposed modifications of the bay, was then used to predict the effect of the proposed land reclamation on the wave climate and morphology of the bay after one decade. We show that reshaping the bay induces a distinct symmetrical response of the shoreline which likely will modify the nearshore wave patterns and consequently recreational activities in the area.

Keywords: coastal waves, impact of land reclamation, long-term coastal evolution, morphodynamic modeling

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2500 Concentrated Animal Feeding Operations and Planning in the United States: Evidences from North Carolina

Authors: Asmaa Benbaba

Abstract:

This paper aims to reconsider relationships between animal feeding operations (CAFOs) and planning. It stresses the idea of the necessity for a methodological revolution in order to increase the chances for dialogue between different actors and various planning agencies and create possibilities to manage conflicts. The explored case of North Carolina shows limitations in environmental agencies’ actions and methods. It also calls for a more integrated approach among agencies including the local agencies.

Keywords: CAFOs, North Carolina, planning, United States

Procedia PDF Downloads 382
2499 A New Approach to Interval Matrices and Applications

Authors: Obaid Algahtani

Abstract:

An interval may be defined as a convex combination as follows: I=[a,b]={x_α=(1-α)a+αb: α∈[0,1]}. Consequently, we may adopt interval operations by applying the scalar operation point-wise to the corresponding interval points: I ∙J={x_α∙y_α ∶ αϵ[0,1],x_α ϵI ,y_α ϵJ}, With the usual restriction 0∉J if ∙ = ÷. These operations are associative: I+( J+K)=(I+J)+ K, I*( J*K)=( I*J )* K. These two properties, which are missing in the usual interval operations, will enable the extension of the usual linear system concepts to the interval setting in a seamless manner. The arithmetic introduced here avoids such vague terms as ”interval extension”, ”inclusion function”, determinants which we encounter in the engineering literature that deal with interval linear systems. On the other hand, these definitions were motivated by our attempt to arrive at a definition of interval random variables and investigate the corresponding statistical properties. We feel that they are the natural ones to handle interval systems. We will enable the extension of many results from usual state space models to interval state space models. The interval state space model we will consider here is one of the form X_((t+1) )=AX_t+ W_t, Y_t=HX_t+ V_t, t≥0, where A∈ 〖IR〗^(k×k), H ∈ 〖IR〗^(p×k) are interval matrices and 〖W 〗_t ∈ 〖IR〗^k,V_t ∈〖IR〗^p are zero – mean Gaussian white-noise interval processes. This feeling is reassured by the numerical results we obtained in a simulation examples.

Keywords: interval analysis, interval matrices, state space model, Kalman Filter

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2498 Strabismus Detection Using Eye Alignment Stability

Authors: Anoop T. R., Otman Basir, Robert F. Hess, Ben Thompson

Abstract:

Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. Currently, many children with strabismus remain undiagnosed until school entry because current automated screening methods have limited success in the preschool age range. A method for strabismus detection using eye alignment stability (EAS) is proposed. This method starts with face detection, followed by facial landmark detection, eye region segmentation, eye gaze extraction, and eye alignment stability estimation. Binarization and morphological operations are performed for segmenting the pupil region from the eye. After finding the EAS, its absolute value is used to differentiate the strabismic eye from the non-strabismic eye. If the value of the eye alignment stability is greater than a particular threshold, then the eyes are misaligned, and if its value is less than the threshold, the eyes are aligned. The method was tested on 175 strabismic and non-strabismic images obtained from Kaggle and Google Photos. The strabismic eye is taken as a positive class, and the non-strabismic eye is taken as a negative class. The test produced a true positive rate of 100% and a false positive rate of 7.69%.

Keywords: strabismus, face detection, facial landmarks, eye segmentation, eye gaze, binarization

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2497 Survey Research Assessment for Renewable Energy Integration into the Mining Industry

Authors: Kateryna Zharan, Jan C. Bongaerts

Abstract:

Mining operations are energy intensive, and the share of energy costs in total costs is often quoted in the range of 40 %. Saving on energy costs is, therefore, a key element of any mine operator. With the improving reliability and security of renewable energy (RE) sources, and requirements to reduce carbon dioxide emissions, perspectives for using RE in mining operations emerge. These aspects are stimulating the mining companies to search for ways to substitute fossil energy with RE. Hereby, the main purpose of this study is to present the survey research assessment in matter of finding out the key issues related to the integration of RE into mining activities, based on the mining and renewable energy experts’ opinion. The purpose of the paper is to present the outcomes of a survey conducted among mining and renewable energy experts about the feasibility of RE in mining operations. The survey research has been developed taking into consideration the following categories: first of all, the mining and renewable energy experts were chosen based on the specific criteria. Secondly, they were offered a questionnaire to gather their knowledge and opinions on incentives for mining operators to turn to RE, barriers and challenges to be expected, environmental effects, appropriate business models and the overall impact of RE on mining operations. The outcomes of the survey allow for the identification of factors which favor and disfavor decision-making on the use of RE in mining operations. It concludes with a set of recommendations for further study. One of them relates to a deeper analysis of benefits for mining operators when using RE, and another one suggests that appropriate business models considering economic and environmental issues need to be studied and developed. The results of the paper will be used for developing a hybrid optimized model which might be adopted at mines according to their operation processes as well as economic and environmental perspectives.

Keywords: carbon dioxide emissions, mining industry, photovoltaic, renewable energy, survey research, wind generation

Procedia PDF Downloads 341
2496 Multi-Vehicle Detection Using Histogram of Oriented Gradients Features and Adaptive Sliding Window Technique

Authors: Saumya Srivastava, Rina Maiti

Abstract:

In order to achieve a better performance of vehicle detection in a complex environment, we present an efficient approach for a multi-vehicle detection system using an adaptive sliding window technique. For a given frame, image segmentation is carried out to establish the region of interest. Gradient computation followed by thresholding, denoising, and morphological operations is performed to extract the binary search image. Near-region field and far-region field are defined to generate hypotheses using the adaptive sliding window technique on the resultant binary search image. For each vehicle candidate, features are extracted using a histogram of oriented gradients, and a pre-trained support vector machine is applied for hypothesis verification. Later, the Kalman filter is used for tracking the vanishing point. The experimental results show that the method is robust and effective on various roads and driving scenarios. The algorithm was tested on highways and urban roads in India.

Keywords: gradient, vehicle detection, histograms of oriented gradients, support vector machine

Procedia PDF Downloads 107
2495 Level Set and Morphological Operation Techniques in Application of Dental Image Segmentation

Authors: Abdolvahab Ehsani Rad, Mohd Shafry Mohd Rahim, Alireza Norouzi

Abstract:

Medical image analysis is one of the great effects of computer image processing. There are several processes to analysis the medical images which the segmentation process is one of the challenging and most important step. In this paper the segmentation method proposed in order to segment the dental radiograph images. Thresholding method has been applied to simplify the images and to morphologically open binary image technique performed to eliminate the unnecessary regions on images. Furthermore, horizontal and vertical integral projection techniques used to extract the each individual tooth from radiograph images. Segmentation process has been done by applying the level set method on each extracted images. Nevertheless, the experiments results by 90% accuracy demonstrate that proposed method achieves high accuracy and promising result.

Keywords: integral production, level set method, morphological operation, segmentation

Procedia PDF Downloads 301