Search results for: hyperspectral image classification using tree search algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9599

Search results for: hyperspectral image classification using tree search algorithm

3269 An Examination of Changes on Natural Vegetation due to Charcoal Production Using Multi Temporal Land SAT Data

Authors: T. Garba, Y. Y. Babanyara, M. Isah, A. K. Muktari, R. Y. Abdullahi

Abstract:

The increased in demand of fuel wood for heating, cooking and sometimes bakery has continued to exert appreciable impact on natural vegetation. This study focus on the use of multi-temporal data from land sat TM of 1986, land sat EMT of 1999 and lands sat ETM of 2006 to investigate the changes of Natural Vegetation resulting from charcoal production activities. The three images were classified based on bare soil, built up areas, cultivated land, and natural vegetation, Rock out crop and water bodies. From the classified images Land sat TM of 1986 it shows natural vegetation of the study area to be 308,941.48 hectares equivalent to 50% of the area it then reduces to 278,061.21 which is 42.92% in 1999 it again depreciated to 199,647.81 in 2006 equivalent to 30.83% of the area. Consequently cultivated continue increasing from 259,346.80 hectares (42%) in 1986 to 312,966.27 hectares (48.3%) in 1999 and then to 341.719.92 hectares (52.78%). These show that within the span of 20 years (1986 to 2006) the natural vegetation is depreciated by 119,293.81 hectares. This implies that if the menace is not control the natural might likely be lost in another twenty years. This is because forest cleared for charcoal production is normally converted to farmland. The study therefore concluded that there is the need for alternatives source of domestic energy such as the use of biomass which can easily be accessible and affordable to people. In addition, the study recommended that there should be strong policies enforcement for the protection forest reserved.

Keywords: charcoal, classification, data, images, land use, natural vegetation

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3268 Immunity Boosting and Balanced Diet Prevents Viral Infections with Special Emphasis on COVID-19

Authors: K. R. Padma, K. R. Don

Abstract:

Background and aims: A balanced nutritional diet is essential in maintaining immunity and for deterrence as well as desisting of viral infections. Nevertheless, currently, very less information is available online regarding nutrition consumption during the period of coronavirus infection, i.e. (COVID-19). In our systematic review article, we portrayed and aimed to evaluate evidence from various previous clinical trials, which was based on nutritional interventions for viral diseases and given a concise overview. Methods: A systematic search was carried out employing 3 key medical databases: PubMed®, Web of Science®, and SciVerse Scopus®. Studies were performed and evaluated suitable if clinical trials in humans, appropriate immunological parameters on viral and respiratory infections, need to perform. Basic Clinical trials on nutritional vitamins, minerals, nutraceuticals as well as probiotics were included. Results: We have explored 10 review articles and extracted data for our study. A total of > 2000 participants were included and excluded several other trace elements as well as various vitamins, but in inclusion criteria mainly concentrated on those who have shown propitious immune-modulatory effects against viral respiratory infections. Conclusions: We have encapsulated the potential health benefits of some minerals, vitamins, as well as certain designer foods, nutraceuticals, and probiotics in viral infections. Based on this nutritional interventional strategy available from our present data, it could be promising to abstain and reduce the COVID-19 infection replication and boost our immunity to fight against the virus.

Keywords: COVID-19, immunity, vitamins, nutritional intervention strategy

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3267 Planning Quality and Maintenance Activities in a Closed-Loop Serial Multi-Stage Manufacturing System under Constant Degradation

Authors: Amauri Josafat Gomez Aguilar, Jean Pierre Kenné

Abstract:

This research presents the development of a self-sustainable manufacturing system from a circular economy perspective, structured by a multi-stage serial production system consisting of a series of machines under deterioration in charge of producing a single product and a reverse remanufacturing system constituted by the same productive systems of the first scheme and different tooling, fed by-products collected at the end of their life cycle, and non-conforming elements of the first productive scheme. Since the advanced production manufacturing system is unable to satisfy the customer's quality expectations completely, we propose the development of a mixed integer linear mathematical model focused on the optimal search and assignment of quality stations and preventive maintenance operation to the machines over a time horizon, intending to segregate the correct number of non-conforming parts for reuse in the remanufacturing system and thereby minimizing production, quality, maintenance, and customer non-conformance penalties. Numerical experiments are performed to analyze the solutions found by the model under different scenarios. The results showed that the correct implementation of a closed manufacturing system and allocation of quality inspection and preventive maintenance operations generate better levels of customer satisfaction and an efficient manufacturing system.

Keywords: closed loop, mixed integer linear programming, preventive maintenance, quality inspection

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3266 Channel Estimation for LTE Downlink

Authors: Rashi Jain

Abstract:

The LTE systems employ Orthogonal Frequency Division Multiplexing (OFDM) as the multiple access technology for the Downlink channels. For enhanced performance, accurate channel estimation is required. Various algorithms such as Least Squares (LS), Minimum Mean Square Error (MMSE) and Recursive Least Squares (RLS) can be employed for the purpose. The paper proposes channel estimation algorithm based on Kalman Filter for LTE-Downlink system. Using the frequency domain pilots, the initial channel response is obtained using the LS criterion. Then Kalman Filter is employed to track the channel variations in time-domain. To suppress the noise within a symbol, threshold processing is employed. The paper draws comparison between the LS, MMSE, RLS and Kalman filter for channel estimation. The parameters for evaluation are Bit Error Rate (BER), Mean Square Error (MSE) and run-time.

Keywords: LTE, channel estimation, OFDM, RLS, Kalman filter, threshold

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3265 Water Footprint for the Palm Oil Industry in Malaysia

Authors: Vijaya Subramaniam, Loh Soh Kheang, Astimar Abdul Aziz

Abstract:

Water footprint (WFP) has gained importance due to the increase in water scarcity in the world. This study analyses the WFP for an agriculture sector, i.e., the oil palm supply chain, which produces oil palm fresh fruit bunch (FFB), crude palm oil, palm kernel, and crude palm kernel oil. The water accounting and vulnerability evaluation (WAVE) method was used. This method analyses the water depletion index (WDI) based on the local blue water scarcity. The main contribution towards the WFP at the plantation was the production of FFB from the crop itself at 0.23m³/tonne FFB. At the mill, the burden shifts to the water added during the process, which consists of the boiler and process water, which accounted for 6.91m³/tonne crude palm oil. There was a 33% reduction in the WFP when there was no dilution or water addition after the screw press at the mill. When allocation was performed, the WFP reduced by 42% as the burden was shared with the palm kernel and palm kernel shell. At the kernel crushing plant (KCP), the main contributor towards the WFP 4.96 m³/tonne crude palm kernel oil which came from the palm kernel which carried the burden from upstream followed by electricity, 0.33 m³/tonne crude palm kernel oil used for the process and 0.08 m³/tonne crude palm kernel oil for transportation of the palm kernel. A comparison was carried out for mills with biogas capture versus no biogas capture, and the WFP had no difference for both scenarios. The comparison when the KCPs operate in the proximity of mills as compared to those operating in the proximity of ports only gave a reduction of 6% for the WFP. Both these scenarios showed no difference and insignificant difference, which differed from previous life cycle assessment studies on the carbon footprint, which showed significant differences. This shows that findings change when only certain impact categories are focused on. It can be concluded that the impact from the water used by the oil palm tree is low due to the practice of no irrigation at the plantations and the high availability of water from rainfall in Malaysia. This reiterates the importance of planting oil palm trees in regions with high rainfall all year long, like the tropics. The milling stage had the most significant impact on the WFP. Mills should avoid dilution to reduce this impact.

Keywords: life cycle assessment, water footprint, crude palm oil, crude palm kernel oil, WAVE method

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3264 Introducing Standardized Nursing Language in Reporting Nursing Care in Resource-Limited Care Environments: An Exploratory Study

Authors: Naomi Mutea, Jossete Jones

Abstract:

The project aimed at exploring the views and perceptions of nurse leaders and educators regarding use of International Classification for Nursing Practice (ICNP) in an informal approach which involved face to face discussions, after which a decision would be made on whether to proceed and propose introduction of ICNP project in Kenya as a pilot project which would mean all nurses would use a standard approach to reporting and documenting nursing care. In addition the project was to determine the best approaches/methods that can be used to introduce ICNP in the Kenyan nursing education and practice environment using the findings of the pilot project. Further four cardex reports were reviewed to establish if nurses on the bedside used a standardized language in documenting and reporting care processes. The cardex reports showed that nurses do not use ICNP or any other standardized language. The results of the discussions revealed that this would be a challenge due to several challenges experienced in conducting nursing research in resource-limited environments. The following questions were asked during the informal discussions with the educators/leaders: •What is currently being taught in terms of standardized nursing language? •Are you familiar with ICNP? •Do you view it advantageous to have a standardized language? •What is the greatest need at the moment in terms of curriculum development for BSN regarding use of standardized nursing language? •If you had a wish to change something in your curriculum, what would that be?

Keywords: nursing, standardized language, ICNP, resource-limited care environments

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3263 Solving Optimal Control of Semilinear Elliptic Variational Inequalities Obstacle Problems using Smoothing Functions

Authors: El Hassene Osmani, Mounir Haddou, Naceurdine Bensalem

Abstract:

In this paper, we investigate optimal control problems governed by semilinear elliptic variational inequalities involving constraints on the state, and more precisely, the obstacle problem. We present a relaxed formulation for the problem using smoothing functions. Since we adopt a numerical point of view, we first relax the feasible domain of the problem, then using both mathematical programming methods and penalization methods, we get optimality conditions with smooth Lagrange multipliers. Some numerical experiments using IPOPT algorithm (Interior Point Optimizer) are presented to verify the efficiency of our approach.

Keywords: complementarity problem, IPOPT, Lagrange multipliers, mathematical programming, optimal control, smoothing methods, variationally inequalities

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3262 The Accuracy of Parkinson's Disease Diagnosis Using [123I]-FP-CIT Brain SPECT Data with Machine Learning Techniques: A Survey

Authors: Lavanya Madhuri Bollipo, K. V. Kadambari

Abstract:

Objective: To discuss key issues in the diagnosis of Parkinson disease (PD), To discuss features influencing PD progression, To discuss importance of brain SPECT data in PD diagnosis, and To discuss the essentiality of machine learning techniques in early diagnosis of PD. An accurate and early diagnosis of PD is nowadays a challenge as clinical symptoms in PD arise only when there is more than 60% loss of dopaminergic neurons. So far there are no laboratory tests for the diagnosis of PD, causing a high rate of misdiagnosis especially when the disease is in the early stages. Recent neuroimaging studies with brain SPECT using 123I-Ioflupane (DaTSCAN) as radiotracer shown to be widely used to assist the diagnosis of PD even in its early stages. Machine learning techniques can be used in combination with image analysis procedures to develop computer-aided diagnosis (CAD) systems for PD. This paper addressed recent studies involving diagnosis of PD in its early stages using brain SPECT data with Machine Learning Techniques.

Keywords: Parkinson disease (PD), dopamine transporter, single-photon emission computed tomography (SPECT), support vector machine (SVM)

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3261 Identity and Economics: The Economic Welfare and Behavior of Romani People in Turkey

Authors: Sinem Bagce, Ensar Yilmaz

Abstract:

As a well-known fact, neoclassical economics excludes 'what is humanized' out of the literature for a long time. Rationality is defined in a very narrow context in the mainstream economics. Identity economics is one of the challenges raised against this tradition. The concept of 'identity' has been introduced to economics by Akerlof and Kranton (2000). The identity-based analysis mainly searches the links between economic welfare and decision of the actors in question related to ethnic, racial, gender and immigrant issues. This is more about discrimination and its repercussions on economic decisions of the relevant actors in a social sphere. In this article, we, in the context of identity economics, search the economic welfare and decisions of Romani people in Turkey. It is plainly observed that identity is clearly the major determinant for Romani people in economic and social life. They have their own distinctive rationality in making economic decisions. For a more scrutinized and academic analysis, we aim to trace their economic identity in their real social environment. This study is an extension of surveys conducted on Romani people in Turkey. Using data similar to SILC (Statistics for Income and Living Conditions) conducted on Romani people across the whole Turkey, we look for some questions about the income/welfare distribution among them, consumer preferences/habits, living conditions, occupations, education and as such. For this, by employing econometric and statistical analytical tools, we aim to obtain the answers for these questions. We think these analytic results will provide us to evaluate the links between their economic state and their identity more thoroughly. JEL Codes: D1, J 15, R23.

Keywords: identity economics, Romani people, discrimination, social identity and preferences

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3260 Digital Cinema Watermarking State of Art and Comparison

Authors: H. Kelkoul, Y. Zaz

Abstract:

Nowadays, the vigorous popularity of video processing techniques has resulted in an explosive growth of multimedia data illegal use. So, watermarking security has received much more attention. The purpose of this paper is to explore some watermarking techniques in order to observe their specificities and select the finest methods to apply in digital cinema domain against movie piracy by creating an invisible watermark that includes the date, time and the place where the hacking was done. We have studied three principal watermarking techniques in the frequency domain: Spread spectrum, Wavelet transform domain and finally the digital cinema watermarking transform domain. In this paper, a detailed technique is presented where embedding is performed using direct sequence spread spectrum technique in DWT transform domain. Experiment results shows that the algorithm provides high robustness and good imperceptibility.

Keywords: digital cinema, watermarking, wavelet DWT, spread spectrum, JPEG2000 MPEG4

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3259 Bayesian Structural Identification with Systematic Uncertainty Using Multiple Responses

Authors: André Jesus, Yanjie Zhu, Irwanda Laory

Abstract:

Structural health monitoring is one of the most promising technologies concerning aversion of structural risk and economic savings. Analysts often have to deal with a considerable variety of uncertainties that arise during a monitoring process. Namely the widespread application of numerical models (model-based) is accompanied by a widespread concern about quantifying the uncertainties prevailing in their use. Some of these uncertainties are related with the deterministic nature of the model (code uncertainty) others with the variability of its inputs (parameter uncertainty) and the discrepancy between a model/experiment (systematic uncertainty). The actual process always exhibits a random behaviour (observation error) even when conditions are set identically (residual variation). Bayesian inference assumes that parameters of a model are random variables with an associated PDF, which can be inferred from experimental data. However in many Bayesian methods the determination of systematic uncertainty can be problematic. In this work systematic uncertainty is associated with a discrepancy function. The numerical model and discrepancy function are approximated by Gaussian processes (surrogate model). Finally, to avoid the computational burden of a fully Bayesian approach the parameters that characterise the Gaussian processes were estimated in a four stage process (modular Bayesian approach). The proposed methodology has been successfully applied on fields such as geoscience, biomedics, particle physics but never on the SHM context. This approach considerably reduces the computational burden; although the extent of the considered uncertainties is lower (second order effects are neglected). To successfully identify the considered uncertainties this formulation was extended to consider multiple responses. The efficiency of the algorithm has been tested on a small scale aluminium bridge structure, subjected to a thermal expansion due to infrared heaters. Comparison of its performance with responses measured at different points of the structure and associated degrees of identifiability is also carried out. A numerical FEM model of the structure was developed and the stiffness from its supports is considered as a parameter to calibrate. Results show that the modular Bayesian approach performed best when responses of the same type had the lowest spatial correlation. Based on previous literature, using different types of responses (strain, acceleration, and displacement) should also improve the identifiability problem. Uncertainties due to parametric variability, observation error, residual variability, code variability and systematic uncertainty were all recovered. For this example the algorithm performance was stable and considerably quicker than Bayesian methods that account for the full extent of uncertainties. Future research with real-life examples is required to fully access the advantages and limitations of the proposed methodology.

Keywords: bayesian, calibration, numerical model, system identification, systematic uncertainty, Gaussian process

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3258 Analysis of the 2023 Karnataka State Elections Using Online Sentiment

Authors: Pranav Gunhal

Abstract:

This paper presents an analysis of sentiment on Twitter towards the Karnataka elections held in 2023, utilizing transformer-based models specifically designed for sentiment analysis in Indic languages. Through an innovative data collection approach involving a combination of novel methods of data augmentation, online data preceding the election was analyzed. The study focuses on sentiment classification, effectively distinguishing between positive, negative, and neutral posts while specifically targeting the sentiment regarding the loss of the Bharatiya Janata Party (BJP) or the win of the Indian National Congress (INC). Leveraging high-performing transformer architectures, specifically IndicBERT, coupled with specifically fine-tuned hyperparameters, the AI models employed in this study achieved remarkable accuracy in predicting the INC’s victory in the election. The findings shed new light on the potential of cutting-edge transformer-based models in capturing and analyzing sentiment dynamics within the Indian political landscape. The implications of this research are far-reaching, providing invaluable insights to political parties for informed decision-making and strategic planning in preparation for the forthcoming 2024 Lok Sabha elections in the nation.

Keywords: sentiment analysis, twitter, Karnataka elections, congress, BJP, transformers, Indic languages, AI, novel architectures, IndicBERT, lok sabha elections

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3257 Isolation, Characterization and Screening of Antimicrobial Producing Actinomycetes from Sediments of Persian Gulf

Authors: H. Alijani, M. Jabari, S. Matroodi, H. Zolqarnein, A. Sharafi, I. Zamani

Abstract:

Actinomycetes, Gram-positive bacteria, are interesting as a main producer of secondary metabolites and are important industrially and pharmaceutically. The marine environment is a potential source for new actinomycetes, which can provide novel bioactive compounds and industrially important enzymes. The aims of this study were to isolate and identify novel actinomycetes from Persian Gulf sediments and screen these isolates for the production of secondary metabolites, especially antibiotics, Using phylogenetic (16S rRNA gene sequence), morphological and biochemical analyses. 15 different actinomycete strains from Persian Gulf sediments at a depth of 5-10 m were identified. DNA extraction was done using Cinnapure DNA Kit. PCR amplification of 16S rDNA gene was performed using F27 and R1492 primers. Phylogenetic tree analysis was performed using the MEGA 6 software. Most of the isolated strains belong to the genus namely Streptomyces (14), followed by Nocardiopsis (1). Antibacterial assay of the isolates supernatant was performed using a standard disc diffusion assay with replication (n=3). The results of disk diffusion assay showed that most active strain against Proteus volgaris and Bacillus cereus was AMJ1 (16.46±0.2mm and 13.78±0.2mm, respectively), against Salmonella sp. AMJ7 was the most effective strain (10.13±0.2mm), and AMJ1 and AHA5 showed more inhibitory activity against Escherichia coli (8.04±0.02 mm and 8.2±0.03 ). The AMJ6 strain showed best antibacterial activity against Klebsiella sp. (8.03±0.02mm). Antifungal activity of AMJ2 showed that it was most active strain against complex (16.05±0.02mm) and against Aspergillus flavus strain AMJ1 was most active strain (16.4±0.2mm) and highest antifungal activity against Trichophyton mentagrophytes, Microsporum gyp serum and Candida albicans, were shown by AHA1 (21.03±0.02mm), AHA3 and AHA7 (18±0.03mm), AMJ6 (21.03±0.2mm) respectively. Our results revealed that the marine actinomycetes of Persian Gulf sediments were potent source of novel antibiotics and bioactive compounds and indicated that the antimicrobial metabolites were extracellular. Most of the secondary metabolites and antibiotics are extracellular in nature and extracellular products of actinomycetes show potent antimicrobial activities.

Keywords: antibacterial activity, antifungal activity, marine actinomycetes, Persian Gulf

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3256 Texture Identification Using Vision System: A Method to Predict Functionality of a Component

Authors: Varsha Singh, Shraddha Prajapati, M. B. Kiran

Abstract:

Texture identification is useful in predicting the functionality of a component. Many of the existing texture identification methods are of contact in nature, which limits its measuring speed. These contact measurement techniques use a diamond stylus and the diamond stylus being sharp going to damage the surface under inspection and hence these techniques can be used in statistical sampling. Though these contact methods are very accurate, they do not give complete information for full characterization of surface. In this context, the presented method assumes special significance. The method uses a relatively low cost vision system for image acquisition. Software is developed based on wavelet transform, for analyzing texture images. Specimens are made using different manufacturing process (shaping, grinding, milling etc.) During experimentation, the specimens are illuminated using proper lighting and texture images a capture using CCD camera connected to the vision system. The software installed in the vision system processes these images and subsequently identify the texture of manufacturing processes.

Keywords: diamond stylus, manufacturing process, texture identification, vision system

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3255 The Impact of Stigma on the Course of Mental Illness: A Brief Review

Authors: Mariana Mangas, Yaroslava Martins, Ana Matos Pires

Abstract:

Introduction: Stigmatization is a common problem to overcome for people suffering from chronic diseases. It usually follows mental disorders and complicates the course of illness and reduces quality of life for people with mental illness. Objective: unsystematic review concerning stigma and mental illness, its impact on psychiatric disease and strategies to eradicate stigma. Methods: A search was conducted on PubMed, using keywords 'stigma' and 'mental illness'. Results and Discussion: Stigma is a psychosocial process that identifies individuals by the negative label of their differences. Stigma often brings a loss of occupational success and social support, reduced functioning and lower quality of life. The sense of stigma is common in individuals with mental illness and has considerable negative repercussions: delays treatment achievement, promotes social isolation, stress and maladaptive coping behaviors and it is associated with higher symptom levels, placing these individuals at higher risk for a poorer outcome and prognoses. Conclusion: Given the interrelation between stigma, symptoms, treatment seeking and disease management, stigma is a key construct in mental illness upon which anti-stigma initiatives may have considerable therapeutic potential. It will take multidisciplinary interventions to overcome mental illness stigma, including changes in social policy, attitudes and practices among mental health professionals, liaison between general public and people with a mental illness under conditions of equity and parity, family support, and easy access to evidence-based treatments.

Keywords: discrimination, stigma, mental illness, quality of life

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3254 Research on ARQ Transmission Technique in Mars Detection Telecommunications System

Authors: Zhongfei Cai, Hui He, Changsheng Li

Abstract:

This paper studied in the automatic repeat request (ARQ) transmission technique in Mars detection telecommunications system. An ARQ method applied to proximity-1 space link protocol was proposed by this paper. In order to ensure the efficiency of data reliable transmission, this ARQ method combined these different ARQ maneuvers characteristics. Considering the Mars detection communication environments, this paper analyzed the characteristics of the saturation throughput rate, packet dropping probability, average delay and energy efficiency with different ARQ algorithms. Combined thus results with the theories of ARQ transmission technique, an ARQ transmission project in Mars detection telecommunications system was established. The simulation results showed that this algorithm had excellent saturation throughput rate and energy efficiency with low complexity.

Keywords: ARQ, mars, CCSDS, proximity-1, deepspace

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3253 Factors Affecting eHealth Literacy among Nursing Students in Jordan

Authors: Laila Habiballah, Ahmad Tubaishat

Abstract:

Background: with the development of information and communication technology, using the internet as a source to obtain health information is increasing. Nursing students as future health care providers should have the skills of locating, evaluating and using online health information. This will enable them to help their patients and families to make informed decisions. Aim: this study has a two-fold aim. The first is to assess the eHealth literacy among nursing students in Jordan. The second aim is to explore the factors that have an effect on the eHealth literacy. Methods: this is a descriptive cross-sectional survey that conducted in two universities in Jordan; public and private one. A number of 541 students from both universities were completed the eHEALS scale, which is an instrument designed to measure the eHealth literacy. Some additional personal and demographical variable were collected to explore its effect on eHealth literacy. Results: Students have a high perceived level of e-Health literacy (M=3.62, SD=0.58). They are aware of the available online health resources, know how to search, locate, and use these resources. But, they do not have the skills to evaluate these resources and cannot differentiate between the high and low-quality resources. The results showed as well that type of university, type of students' admission, academic level, students' skills of using the internet, and the perception of usefulness and importance of internet have an effect on the eHealth literacy. While the age, gender, GPA, and the frequency of using the internet was no significant factors. Conclusion: This study represents a baseline reference for the eHealth literacy in Jordan. Students have some skills of eHealth literacy and other skills need to be improved. Nursing educators and administrators should integrate and incorporate the skills of eHealth literacy in the curriculum.

Keywords: eHealth, literacy, nursing, students, Jordan

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3252 Disordered Eating Behaviors Among Sorority Women

Authors: Andrea J. Kirk-Jenkins

Abstract:

Women in late adolescence and young adulthood are particularly vulnerable to disordered eating, and prior research indicates that those within the college and sorority communities may be especially susceptible. Research has primarily involved comparing eating disorder symptoms between sorority women and non-sorority members using formal eating disorder assessments. This phenomenological study examined sorority members’ (N = 10) perceptions of and lived experiences with various disordered eating behaviors within the sorority culture. Data from individual interviews and photographs indicated two structural themes and 11 textural themes related to factors associated with disordered eating behaviors. These findings point to the existence of both positive and negative aspects of sorority culture, normalization of disordered eating behaviors, and pressure to attain or maintain an ideal body image. Implications for university stakeholders, including college counselors, health center staff, and extracurricular program leaders, are discussed. Further research on the identified textural themes as well as a longitudinal study exploring how perceptions change from rush to alumnae status is suggested.

Keywords: eating disorders, disorder eating behaviors, sorority women, sorority culture, college women

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3251 Pastoralist Transhumance and Conflict along the Nigeria-niger Borderlands: Towards New Perspective for Effective Border Management in Africa

Authors: Abubakar Samaila

Abstract:

Pastoralism has been an old practice in the Sahel region of west Africa. In recent years, pastoralists in Nigeria have increasingly been migrating on seasonal transhumance southward from the neighboring countries, especially Niger Republic, in search of better grazing conditions due to mainly, climate change. This has increased pressure on farm lands which instigate farmer-herder conflicts. These conflicts occur mainly between farmers and pastoralists but also between pastoralist groups themselves. However, there has been a shift in these conflicts recently to involve traditional institutions and, in some cases, the local authorities along the borderlands. The involvement of local institutions in the conflict has created an incentive to local actors, particularly pastoralcommunity-based groups, in responding to these violent threats. As pastoralists are mobile, these conflicts became difficult to contain and, thus, spill across borders. Consequently, the conflict has now transformed into an urbanized regional conflicts that involve some major cities along the Nigeria-Niger borderlands; Sokoto, Zamfara, and Katsina on the Nigerian side andDosso, Tahoa andMaradi in Niger republic. These areas are now experiencing unprecedented growing wave of violence that have become complex and escalates into a hydra-social conflict. The aim of this research is to investigate how the fluidities of Nigeria-Niger borderland intensified armed conflicts between the local pastoral organizations and sedentary populationspreading to some urban cities along the borderlands. The paper further suggests alternative approaches towards addressing the perennial crisis in African borderlands.

Keywords: pastoralism, climate change, conflict, nigeria, niger, borderlands

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3250 Density-based Denoising of Point Cloud

Authors: Faisal Zaman, Ya Ping Wong, Boon Yian Ng

Abstract:

Point cloud source data for surface reconstruction is usually contaminated with noise and outliers. To overcome this, we present a novel approach using modified kernel density estimation (KDE) technique with bilateral filtering to remove noisy points and outliers. First we present a method for estimating optimal bandwidth of multivariate KDE using particle swarm optimization technique which ensures the robust performance of density estimation. Then we use mean-shift algorithm to find the local maxima of the density estimation which gives the centroid of the clusters. Then we compute the distance of a certain point from the centroid. Points belong to outliers then removed by automatic thresholding scheme which yields an accurate and economical point surface. The experimental results show that our approach comparably robust and efficient.

Keywords: point preprocessing, outlier removal, surface reconstruction, kernel density estimation

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3249 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: neural network, pineapple, soluble solid content, spectroscopy

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3248 Structure-Based Virtual Screening and in Silico Toxicity Test of Compounds against Mycobacterium tuberculosis 7,8-Diaminopelargonic Acid Aminotransferase (MtbBioA)

Authors: Junie B. Billones, Maria Constancia O. Carrillo, Voltaire G. Organo, Stephani Joy Y. Macalino, Inno A. Emnacen, Jamie Bernadette A. Sy

Abstract:

One of the major interferences in the Philippines’ tuberculosis control program is the widespread prevalence of Mtb strains that are resistant to known drugs, such as the MDR-TB (Multi Drug Resistant Tuberculosis) and XDR-TB (Extensively Drug Resistant Tuberculosis). Therefore, there is a pressing need to search for novel Mtb drug targets in order to be able to combat these drug resistant strains. The enzyme 7,8-diaminopelargonic acid aminotransferase enzyme, or more commonly known as BioA, is one such ideal target, as it is known that humans do not possess this enzyme. BioA primarily plays a key role in Mtb’s lipid biosynthesis pathway; more specifically in the synthesis of the enzyme cofactor biotin. In this study, structure-based pharmacophore screening, docking, and ADMET evaluation of compounds obtained from the DrugBank chemical database were performed against the MtbBioA enzyme. Results of the screening, docking, ADMET, and TOPKAT calculations revealed that out of the 6,516 compounds in the library, only 7 compounds indicated more favorable binding energies as compared to the enzyme’s known inhibitor, amiclenomycin (ACM), as well as good solubility and toxicity properties. Moreover, out of these 7 compounds, Molecule 6 exhibited the best solubility and toxicity properties. In the future, these lead compounds may then be subjected to bioactivity assays in vitro or in vivo for further evaluation of its therapeutic efficacy.

Keywords: 7, 8-diaminopelargonic acid aminotransferase, BioA, pharmacophore, molecular docking, ADMET, TOPKAT

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3247 Synthesis and Characterization of Green Coke-Derived Activated Carbon by KOH Activation

Authors: Richard, Iyan Subiyanto, Chairul Hudaya

Abstract:

Activated carbon has been playing a significant role for many applications, especially in energy storage devices. However, commercially activated carbons generally require complicated processes and high production costs. Therefore, in this study, an activated carbon originating from green coke waste, that is economically affordable will be used as a carbon source. To synthesize activated carbon, KOH as an activator was employed with variation of C:KOH in ratio of 1:2, 1:3, 1:4, and 1:5, respectively, with an activation temperature of 700°C. The characterizations of activated carbon are obtained from Scanning Electron Microscopy, Energy Dispersive X-Ray, Raman Spectroscopy, and Brunauer-Emmett-Teller. The optimal activated carbon sample with specific surface area of 2,024 m²/g with high carbon content ( > 80%) supported by the high porosity carbon image obtained by SEM was prepared at C:KOH ratio of 1:4. The result shows that the synthesized activated carbon would be an ideal choice for energy storage device applications. Therefore, this study is expected to reduce the costs of activated carbon production by expanding the utilization of petroleum waste.

Keywords: activated carbon, energy storage material, green coke, specific surface area

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3246 The Effects of Distribution Channels on the Selling Prices of Hotels in Time of Crisis

Authors: Y. Yılmaz, C. Ünal, A. Dursun

Abstract:

Distribution channels play significant role for hotels. Direct and indirect selling options of hotel rooms have been increased especially with the help of new technologies, i.e. hotel’s own web sites and online booking sites. Although these options emerged as tools for diversifying the distribution channels, vast number of hotels -mostly resort hotels- is still heavily dependent upon international tour operators when selling their products. On the other hand, hotel sector is so vulnerable against crises. Economic, political or any other crisis can affect hotels very badly and so it is critical to have the right balance of distribution channel to avoid the adverse impacts of a crisis. In this study, it is aimed to search the impacts of a general crisis on the selling prices of hotels which have different weights of distribution channels. The study was done in Turkey where various crises occurred in 2015 and 2016 which had great negative impacts on Turkish tourism and led enormous occupancy rate and selling price reductions. 112 upscale resort hotel in Antalya, which is the most popular tourism destination of Turkey, joined to the research. According to the results, hotels with high dependency to international tour operators are more forced to reduce their room prices in crisis time compared to the ones which use their own web sites more. It was also found that the decline in room prices is limited for hotels which are working with national tour operators and travel agencies in crisis time.

Keywords: marketing channels, crisis, hotel, international tour operators, online travel agencies

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3245 A Machine Learning Framework Based on Biometric Measurements for Automatic Fetal Head Anomalies Diagnosis in Ultrasound Images

Authors: Hanene Sahli, Aymen Mouelhi, Marwa Hajji, Amine Ben Slama, Mounir Sayadi, Farhat Fnaiech, Radhwane Rachdi

Abstract:

Fetal abnormality is still a public health problem of interest to both mother and baby. Head defect is one of the most high-risk fetal deformities. Fetal head categorization is a sensitive task that needs a massive attention from neurological experts. In this sense, biometrical measurements can be extracted by gynecologist doctors and compared with ground truth charts to identify normal or abnormal growth. The fetal head biometric measurements such as Biparietal Diameter (BPD), Occipito-Frontal Diameter (OFD) and Head Circumference (HC) needs to be monitored, and expert should carry out its manual delineations. This work proposes a new approach to automatically compute BPD, OFD and HC based on morphological characteristics extracted from head shape. Hence, the studied data selected at the same Gestational Age (GA) from the fetal Ultrasound images (US) are classified into two categories: Normal and abnormal. The abnormal subjects include hydrocephalus, microcephaly and dolichocephaly anomalies. By the use of a support vector machines (SVM) method, this study achieved high classification for automated detection of anomalies. The proposed method is promising although it doesn't need expert interventions.

Keywords: biometric measurements, fetal head malformations, machine learning methods, US images

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3244 Optimal Production and Maintenance Policy for a Partially Observable Production System with Stochastic Demand

Authors: Leila Jafari, Viliam Makis

Abstract:

In this paper, the joint optimization of the economic manufacturing quantity (EMQ), safety stock level, and condition-based maintenance (CBM) is presented for a partially observable, deteriorating system subject to random failure. The demand is stochastic and it is described by a Poisson process. The stochastic model is developed and the optimization problem is formulated in the semi-Markov decision process framework. A modification of the policy iteration algorithm is developed to find the optimal policy. A numerical example is presented to compare the optimal policy with the policy considering zero safety stock.

Keywords: condition-based maintenance, economic manufacturing quantity, safety stock, stochastic demand

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3243 Design and Optimization of a Mini High Altitude Long Endurance (HALE) Multi-Role Unmanned Aerial Vehicle

Authors: Vishaal Subramanian, Annuatha Vinod Kumar, Santosh Kumar Budankayala, M. Senthil Kumar

Abstract:

This paper discusses the aerodynamic and structural design, simulation and optimization of a mini-High Altitude Long Endurance (HALE) UAV. The applications of this mini HALE UAV vary from aerial topological surveys, quick first aid supply, emergency medical blood transport, search and relief activates to border patrol, surveillance and estimation of forest fire progression. Although classified as a mini UAV according to UVS International, our design is an amalgamation of the features of ‘mini’ and ‘HALE’ categories, combining the light weight of the ‘mini’ and the high altitude ceiling and endurance of the HALE. Designed with the idea of implementation in India, it is in strict compliance with the UAS rules proposed by the office of the Director General of Civil Aviation. The plane can be completely automated or have partial override control and is equipped with an Infra-Red camera and a multi coloured camera with on-board storage or live telemetry, GPS system with Geo Fencing and fail safe measures. An additional of 1.5 kg payload can be attached to three major hard points on the aircraft and can comprise of delicate equipment or releasable payloads. The paper details the design, optimization process and the simulations performed using various software such as Design Foil, XFLR5, Solidworks and Ansys.

Keywords: aircraft, endurance, HALE, high altitude, long range, UAV, unmanned aerial vehicle

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3242 Numerical Simulation of Rayleigh Benard Convection and Radiation Heat Transfer in Two-Dimensional Enclosure

Authors: Raoudha Chaabane, Faouzi Askri, Sassi Ben Nasrallah

Abstract:

A new numerical algorithm is developed to solve coupled convection-radiation heat transfer in a two dimensional enclosure. Radiative heat transfer in participating medium has been carried out using the control volume finite element method (CVFEM). The radiative transfer equations (RTE) are formulated for absorbing, emitting and scattering medium. The density, velocity and temperature fields are calculated using the two double population lattice Boltzmann equation (LBE). In order to test the efficiency of the developed method the Rayleigh Benard convection with and without radiative heat transfer is analyzed. The obtained results are validated against available works in literature and the proposed method is found to be efficient, accurate and numerically stable.

Keywords: participating media, LBM, CVFEM- radiation coupled with convection

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3241 Experimental Study of the Behavior of Elongated Non-spherical Particles in Wall-Bounded Turbulent Flows

Authors: Manuel Alejandro Taborda Ceballos, Martin Sommerfeld

Abstract:

Transport phenomena and dispersion of non-spherical particle in turbulent flows are found everywhere in industrial application and processes. Powder handling, pollution control, pneumatic transport, particle separation are just some examples where the particle encountered are not only spherical. These types of multiphase flows are wall bounded and mostly highly turbulent. The particles found in these processes are rarely spherical but may have various shapes (e.g., fibers, and rods). Although research related to the behavior of regular non-spherical particles in turbulent flows has been carried out for many years, it is still necessary to refine models, especially near walls where the interaction fiber-wall changes completely its behavior. Imaging-based experimental studies on dispersed particle-laden flows have been applied for many decades for a detailed experimental analysis. These techniques have the advantages that they provide field information in two or three dimensions, but have a lower temporal resolution compared to point-wise techniques such as PDA (phase-Doppler anemometry) and derivations therefrom. The applied imaging techniques in dispersed two-phase flows are extensions from classical PIV (particle image velocimetry) and PTV (particle tracking velocimetry) and the main emphasis was simultaneous measurement of the velocity fields of both phases. In a similar way, such data should also provide adequate information for validating the proposed models. Available experimental studies on the behavior of non-spherical particles are uncommon and mostly based on planar light-sheet measurements. Especially for elongated non-spherical particles, however, three-dimensional measurements are needed to fully describe their motion and to provide sufficient information for validation of numerical computations. For further providing detailed experimental results allowing a validation of numerical calculations of non-spherical particle dispersion in turbulent flows, a water channel test facility was built around a horizontal closed water channel. Into this horizontal main flow, a small cross-jet laden with fiber-like particles was injected, which was also solely driven by gravity. The dispersion of the fibers was measured by applying imaging techniques based on a LED array for backlighting and high-speed cameras. For obtaining the fluid velocity fields, almost neutrally buoyant tracer was used. The discrimination between tracer and fibers was done based on image size which was also the basis to determine fiber orientation with respect to the inertial coordinate system. The synchronous measurement of fluid velocity and fiber properties also allow the collection of statistics of fiber orientation, velocity fields of tracer and fibers, the angular velocity of the fibers and the orientation between fiber and instantaneous relative velocity. Consequently, an experimental study the behavior of elongated non-spherical particles in wall bounded turbulent flows was achieved. The development of a comprehensive analysis was succeeded, especially near the wall region, where exists hydrodynamic wall interaction effects (e.g., collision or lubrication) and abrupt changes of particle rotational velocity. This allowed us to predict numerically afterwards the behavior of non-spherical particles within the frame of the Euler/Lagrange approach, where the particles are therein treated as “point-particles”.

Keywords: crossflow, non-spherical particles, particle tracking velocimetry, PIV

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3240 Efficient Neural and Fuzzy Models for the Identification of Dynamical Systems

Authors: Aouiche Abdelaziz, Soudani Mouhamed Salah, Aouiche El Moundhe

Abstract:

The present paper addresses the utilization of Artificial Neural Networks (ANNs) and Fuzzy Inference Systems (FISs) for the identification and control of dynamical systems with some degree of uncertainty. Because ANNs and FISs have an inherent ability to approximate functions and to adapt to changes in input and parameters, they can be used to control systems too complex for linear controllers. In this work, we show how ANNs and FISs can be put in order to form nets that can learn from external data. In sequence, it is presented structures of inputs that can be used along with ANNs and FISs to model non-linear systems. Four systems were used to test the identification and control of the structures proposed. The results show the ANNs and FISs (Back Propagation Algorithm) used were efficient in modeling and controlling the non-linear plants.

Keywords: non-linear systems, fuzzy set Models, neural network, control law

Procedia PDF Downloads 214