Search results for: open queueing network

Authors: Menaahyl Seraj, Gokce Ozdemir

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Tourism at destinations is dependent on various resources such as archeology and architecture. The need to preserve those resources is of the utmost importance when long-term tourism development is aimed. Shahi Guzargah (Royal Trail) was subject to a preservation project that is a linear historical passage within the Walled City of Lahore. Even though Lahore with its congested streets, lacks proper infrastructure and economically weak but yet it has the potential of transforming it into a tourist destination. This study highlights the potential hidden in the preservation of cultural resources through proper and concrete planning of living heritage city, and how it improves socio-economic standards of the community and affects tourism. Semi-structured open-ended interview question-forms were used to collect qualitative data from 14 respective stakeholders of the walled city and 10 concerned officials. The results of the study show that the preservation of cultural resources impacts and accelerates positively the development process of a destination. All opinions and gathered information reflect the importance of cultural preservation and its effect on increasing tourism.

Keywords: cultural tourism, cultural resources, destination, preservation

Procedia PDF Downloads 171

Authors: John Hang Leung, Shyh-Yau Wang, Hei-Tung Yip, Fion, Ho Tsung-chin, Agnes LF Chan

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Objectives: Platinum-resistant ovarian cancer has a short overall survival of 9–12 months and limited treatment options. The combination of immunotherapy and targeted therapy appears to be a promising treatment option for patients with ovarian cancer, particularly to patients with platinum-resistant recurrent ovarian cancer (PRrOC). However, there are no direct head-to-head clinical trials comparing their efficacy and toxicity. We, therefore, used a network to directly and indirectly compare seven newer immunotherapies or targeted therapies combined with chemotherapy in platinum-resistant relapsed ovarian cancer, including antibody-drug conjugates, PD-1 (Programmed death-1) and PD-L1 (Programmed death-ligand 1), PARP (Poly ADP-ribose polymerase) inhibitors, TKIs (Tyrosine kinase inhibitors), and antiangiogenic agents. Methods: We searched PubMed (Public/Publisher MEDLINE), EMBASE (Excerpta Medica Database), and the Cochrane Library electronic databases for phase II and III trials involving PRrOC patients treated with immunotherapy or targeted therapy plus chemotherapy. The quality of included trials was assessed using the GRADE method. The primary outcomes compared were progression-free survival, the secondary outcomes were overall survival and safety. Results: Seven randomized controlled trials involving a total of 2058 PRrOC patients were included in this analysis. Bevacizumab plus chemotherapy showed statistically significant differences in PFS (Progression-free survival) but not OS (Overall survival) for all interested targets and immunotherapy regimens; however, according to the heatmap analysis, bevacizumab plus chemotherapy had a statistically significant risk of ≥grade 3 SAEs (Severe adverse effects), particularly hematological severe adverse events (neutropenia, anemia, leukopenia, and thrombocytopenia). Conclusions: Bevacizumab plus chemotherapy resulted in better PFS as compared with all interested regimens for the treatment of PRrOC. However, statistical differences in SAEs as bevacizumab plus chemotherapy is associated with a greater risk for hematological SAE.

Keywords: platinum-resistant recurrent ovarian cancer, network meta-analysis, immune checkpoint inhibitors, target therapy, antiangiogenic agents

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Authors: Anuphan Suttimarn, Natcha Wattanaprapa, Suwaree Yordchim

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The aim of this study is to develop the online journal system using a web application to manage the journal service of Suan Sunandha Rajabhat University in order to improve the journal management of the university. The main structures of the system process consist of 1. journal content management system 2. membership system of the journal and 3. online submission or review process. The investigators developed the system based on a web application using open source OJS software and phpMyAdmin to manage a research database. The system test showed that this online system 'Online Journal System (OJS)' could shorten the time in the period of submission article to journal and helped in managing a journal procedure efficiently and accurately. The quality evaluation of Suan Sunandha Rajabhat online journal system (SSRUOJS) undertaken by experts and researchers in 5 aspects; design, usability, security, reducing time, and accuracy showed the highest average value (X=4.30) on the aspect of reducing time. Meanwhile, the system efficiency evaluation was on an excellent level (X=4.13).

Keywords: online journal system, Journal management, Information system development, OJS

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Authors: Shervin Alaei, Reza Moradi

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Trading in financial markets is subject to risks due to their high volatilities. Here, using an LSTM neural network, and by doing some risk-based feature engineering tasks, we developed a method that can accurately predict trends of the Tehran stock exchange market index from a few days ago. Our test results have shown that the proposed method with an average prediction accuracy of more than 94% is superior to the other common machine learning algorithms. To the best of our knowledge, this is the first work incorporating deep learning and risk factors to accurately predict market trends.

Keywords: deep learning, LSTM, trend prediction, risk management, artificial neural networks

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Authors: Revant Nayar

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In this work, we recast the equations describing large scale structure, and by extension all nonlinear fluids, in the path integral formalism. We first calculate the well known two and three point functions using Schwinger Keldysh formalism used commonly to perturbatively solve path integrals in non- equilibrium systems. Then we include EFT corrections due to pressure, viscosity, and noise as effects on the time-dependent propagator. We are able to express results for arbitrary two and three point correlation functions in LSS in terms of differential operators acting on a triple K master intergral. We also, for the first time, get analytical results for more general initial conditions deviating from the usual power law P∝kⁿ by introducing a mass scale in the initial conditions. This robust field theoretic formalism empowers us with tools from strongly coupled QFT to study the strongly non-linear regime of LSS and turbulent fluid dynamics such as OPE and holographic duals. These could be used to capture fully the strongly non-linear dynamics of fluids and move towards solving the open problem of classical turbulence.

Keywords: quantum field theory, cosmology, effective field theory, renormallisation

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Authors: Furkan Ozkan, M. Selcuk Arslan, Hatice Mercan

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Electric vehicles are becoming increasingly popular asa sustainable alternative to traditional combustion engine vehicles. However, to fully realize the potential of EVs in reducing environmental impact and energy consumption, efficient control strategies are essential. This study explores the application of green wave control using model predictive control for electric vehicles, coupled with energy consumption modeling using neural networks. The use of MPC allows for real-time optimization of the vehicles’ energy consumption while considering dynamic traffic conditions. By leveraging neural networks for energy consumption modeling, the EV's performance can be further enhanced through accurate predictions and adaptive control. The integration of these advanced control and modeling techniques aims to maximize energy efficiency and range while navigating urban traffic scenarios. The findings of this research offer valuable insights into the potential of green wave control for electric vehicles and demonstrate the significance of integrating MPC and neural network modeling for optimizing energy consumption. This work contributes to the advancement of sustainable transportation systems and the widespread adoption of electric vehicles. To evaluate the effectiveness of the green wave control strategy in real-world urban environments, extensive simulations were conducted using a high-fidelity vehicle model and realistic traffic scenarios. The results indicate that the integration of model predictive control and energy consumption modeling with neural networks had a significant impact on the energy efficiency and range of electric vehicles. Through the use of MPC, the electric vehicle was able to adapt its speed and acceleration profile in realtime to optimize energy consumption while maintaining travel time objectives. The neural network-based energy consumption modeling provided accurate predictions, enabling the vehicle to anticipate and respond to variations in traffic flow, further enhancing energy efficiency and range. Furthermore, the study revealed that the green wave control strategy not only reduced energy consumption but also improved the overall driving experience by minimizing abrupt acceleration and deceleration, leading to a smoother and more comfortable ride for passengers. These results demonstrate the potential for green wave control to revolutionize urban transportation by enhancing the performance of electric vehicles and contributing to a more sustainable and efficient mobility ecosystem.

Keywords: electric vehicles, energy efficiency, green wave control, model predictive control, neural networks

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Authors: Pipop Chatrabhuti, S. Visessri, T. Charinpanitkul

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Precision irrigation (PI) technology has emerged as a solution to optimize water usage in agriculture, aiming to maximize crop yields while minimizing water waste. Developing a new PI for commercialization requires developers to research, synthesize, evaluate, and select appropriate technologies and make use of such information to produce innovative products. The objective of this review is to facilitate innovators by providing them with a summary of existing knowledge and the identification of gaps in research linking to the innovative development of PI. This paper reviews and synthesizes technologies and components relevant to precision irrigation, highlighting its potential benefits and challenges. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) framework is used for the review. The study is intended to contribute to innovators who apply for collaborative approach to problem-solving and idea generation that involves seeking external input and resources from a diverse range of individuals and organizations.

Keywords: innovation synthesis, technology assessment, precision irrigation technologies, precision irrigation components, new product development

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Authors: Fathi Abid, Bilel Kaffel

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The olive tree, the olive harvest during winter season and the production of olive oil better known by professionals under the name of the crushing operation have interested institutional traders such as olive-oil offices and private companies such as food industry refining and extracting pomace olive oil as well as export-import public and private companies specializing in olive oil. The major problem facing producers of olive oil each winter campaign, contrary to what is expected, it is not whether the harvest will be good or not but whether the sale price will allow them to cover production costs and achieve a reasonable margin of profit or not. These questions are entirely legitimate if we judge by the importance of the issue and the heavy complexity of the uncertainty and competition made tougher by a high level of indebtedness and the experience and expertise of speculators and producers whose objectives are sometimes conflicting. The aim of this paper is to study the formation mechanism of olive oil prices in order to learn about speculators’ behavior and expectations in the market, how they contribute by their industry knowledge and their financial alliances and the size the financial challenge that may be involved for them to build private information hoses globally to take advantage. The methodology used in this paper is based on two stages, in the first stage we study econometrically the formation mechanisms of olive oil price in order to understand the market participant behavior by implementing ARMA, SARMA, GARCH and stochastic diffusion processes models, the second stage is devoted to prediction purposes, we use a combined wavelet- ANN approach. Our main findings indicate that olive oil market participants interact with each other in a way that they promote stylized facts formation. The unstable participant’s behaviors create the volatility clustering, non-linearity dependent and cyclicity phenomena. By imitating each other in some periods of the campaign, different participants contribute to the fat tails observed in the olive oil price distribution. The best prediction model for the olive oil price is based on a back propagation artificial neural network approach with input information based on wavelet decomposition and recent past history.

Keywords: olive oil price, stylized facts, ARMA model, SARMA model, GARCH model, combined wavelet-artificial neural network, continuous-time stochastic volatility mode

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Authors: M. Pramila Devi, N. V. N. Indra Kiran

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Control charts, predominantly in the form of X-bar chart, are important tools in statistical process control (SPC). They are useful in determining whether a process is behaving as intended or there are some unnatural causes of variation. A process is out of control if a point falls outside the control limits or a series of point’s exhibit an unnatural pattern. In this paper, a study is carried out on four training algorithms for CCPs recognition. For those algorithms optimal structure is identified and then they are studied for type I and type II errors for generalization without early stopping and with early stopping and the best one is proposed.

Keywords: control chart pattern recognition, neural network, backpropagation, generalization, early stopping

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Authors: M. B. Abdullahi, S. M. Gumel

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This study was carried out to analyze and describe biodiversity changes in representative communities around Maladumba Lake and Forest Reserve (MLFR), Bauchi, Nigeria. Primary and secondary data were collected through formal and informal interviews of key informants and survey of local communities and government records. There has been a change in biodiversity; some of the cropping systems have become nonexistent whereas others have developed. The main aspect of the changes has been the decline of species diversity due to degradation and over utilization. The changes have also been positive through the introduction and intensification of cropping system. Options have been open for people to manipulate the cropping systems in order to efficiently use the limited resources. Farmers have opted not only to intensify agricultural practices but also to deliberately restore some of the lost species. Reduction in the number of animals per household, adoption of new techniques of land management, changes in the type of crops cultivated and intensive use of the available resources are some of the indicators describing farmers’ efforts to cope with the changes. Sustainability of the farming system and biodiversity has been enhanced through peoples’ efforts that include planting trees and use of fertilizers.

Keywords: cropping systems, historical trends, household, land management, sustainability

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Authors: Mongezi Nene, Emma Ayesu-Koranteng, Christopher Amoah, Ayo Adeniran

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Although its use has been criticized over the years as being unencouraging, the green building concept is quickly overtaking other concepts, particularly in the construction of commercial properties. The goal of the study is to identify the variables influencing the use of green building practices when developing residential structures. A qualitative methodology, using interviews with semi-structured open-ended questions to 35 property practitioners operating residential apartments in Bloemfontein, South Africa, was used to collect primary data which was analysed using thematic content analysis. The findings show that while respondents have a good understanding of green building principles, they are not being used in the construction of residential buildings in South Africa due to issues with green building approval procedures, the potential for tenant rent increases, the cost of materials, technical issues, contractual issues, and a lack of awareness, among others. This paper recommends among others an urgent need to implement measures by stakeholders towards enhancing the adoption of green building concepts in the construction of residential buildings as well as incentivising its construction through lowered property rates.

Keywords: green building, residential apartments, construction, South Africa

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Authors: Huang Yajing

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Context: Computer-aided language learning (CALL) in China has undergone significant development over the past few decades, with distinct stages marking its evolution. This paper aims to provide a comprehensive review of the practice and research in this field in China, tracing its journey from the early stages of audio-visual education to the current multimedia network integration stage. Research Aim: The study aims to analyze the historical progression of CALL in China, identify key developments in the field, and provide recommendations for enhancing CALL practices in the future. Methodology: The research employs document analysis and literature review to synthesize existing knowledge on CALL in China, drawing on a range of sources to construct a detailed overview of the evolution of CALL practices and research in the country. Findings: The review highlights the significant advancements in CALL in China, showcasing the transition from traditional audio-visual educational approaches to the current integrated multimedia network stage. The study identifies key milestones, technological advancements, and theoretical influences that have shaped CALL practices in China. Theoretical Importance: The evolution of CALL in China reflects not only technological progress but also shifts in educational paradigms and theories. The study underscores the significance of cognitive psychology as a theoretical underpinning for CALL practices, emphasizing the learner's active role in the learning process. Data Collection and Analysis Procedures: Data collection involved extensive review and analysis of documents and literature related to CALL in China. The analysis was carried out systematically to identify trends, developments, and challenges in the field. Questions Addressed: The study addresses the historical development of CALL in China, the impact of technological advancements on teaching practices, the role of cognitive psychology in shaping CALL methodologies, and the future outlook for CALL in the country. Conclusion: The review provides a comprehensive overview of the evolution of CALL in China, highlighting key stages of development and emerging trends. The study concludes by offering recommendations to further enhance CALL practices in the Chinese context.

Keywords: English education, educational technology, computer-aided language teaching, applied linguistics

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Authors: Abigail Rosenberg, Jennifer Duan, Michael Poteuck, Chunshui Yu

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The Barry M. Goldwater Range, West in southwestern Arizona encompasses 2,808 square kilometers of Sonoran Desert. The hyper-arid range has an annual rainfall of less than 10 cm with an average high temperature of 41 degrees Celsius in July to an average low of 4 degrees Celsius in January. The range shares approximately 60 kilometers of the international border with Mexico. A majority of the range is open for recreational use, primarily off-highway vehicles. Because of its proximity to Mexico, the range is also heavily patrolled by U.S. Customs and Border Protection seeking to intercept and apprehend inadmissible people and illicit goods. Decades of off-roading and Border Patrol activities have negatively impacted this sensitive desert ecosystem. To assist the range program managers, this study is developing a model to identify erosion prone areas and calibrate the model’s parameters using the Automated Geospatial Watershed Assessment modeling tool.

Keywords: arid lands, automated geospatial watershed assessment, erosion modeling, sedimentation modeling, watershed modeling

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Authors: Jamaludin Sallim, Rozlina Mohamed, Roslina Abdul Hamid

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In this paper, we proposed an Ant Colony Optimization (ACO) algorithm together with Traveling Salesman Problem (TSP) approach to investigate the clustering problem in Protein Interaction Networks (PIN). We named this combination as ACOPIN. The purpose of this work is two-fold. First, to test the efficacy of ACO in clustering PIN and second, to propose the simple generalization of the ACO algorithm that might allow its application in clustering proteins in PIN. We split this paper to three main sections. First, we describe the PIN and clustering proteins in PIN. Second, we discuss the steps involved in each phase of ACO algorithm. Finally, we present some results of the investigation with the clustering patterns.

Keywords: ant colony optimization algorithm, searching algorithm, protein functional module, protein interaction network

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Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

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The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

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Authors: M. Olmedilla, M. R. Martinez-Torres, S. L. Toral

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Electronic Word-Of-Mouth (eWOM) communities represent today an important source of information in which more and more customers base their purchasing decisions. They include thousands of reviews concerning very different products and services posted by many individuals geographically distributed all over the world. Due to their massive audience, eWOM communities can help users to find the product they are looking for even if they are less popular or rare. This is known as the long tail effect, which leads to a larger number of lower-selling niche products. This paper analyzes the long tail effect in a well-known eWOM community and defines a tool for finding niche products unavailable through conventional channels.

Keywords: eWOM, online user reviews, long tail theory, product categorization, social network analysis

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Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

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Diabetic nephropathy (DN) is a major complication of diabetes, with fibrosis and propionate metabolism playing critical roles in its progression. Identifying biomarkers linked to these pathways may provide novel insights into DN diagnosis and treatment. This study aims to identify biomarkers associated with fibrosis and propionate metabolism in DN. Analyze the biological pathways and regulatory mechanisms of these biomarkers. Develop a machine learning model to predict DN-related biomarkers and validate their functional roles. Publicly available transcriptome datasets related to DN (GSE96804 and GSE104948) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/gds), and 924 propionate metabolism-related genes (PMRGs) and 656 fibrosis-related genes (FRGs) were identified. The analysis began with the extraction of DN-differentially expressed genes (DN-DEGs) and propionate metabolism-related DEGs (PM-DEGs), followed by the intersection of these with fibrosis-related genes to identify key intersected genes. Instead of relying on traditional models, we employed a combination of deep neural networks (DNNs) and ensemble methods such as Gradient Boosting Machines (GBM) and XGBoost to enhance feature selection and biomarker discovery. Recursive feature elimination (RFE) was coupled with these advanced algorithms to refine the selection of the most critical biomarkers. Functional validation was conducted using convolutional neural networks (CNN) for gene set enrichment and immunoinfiltration analysis, revealing seven significant biomarkers—SLC37A4, ACOX2, GPD1, ACE2, SLC9A3, AGT, and PLG. These biomarkers are involved in critical biological processes such as fatty acid metabolism and glomerular development, providing a mechanistic link to DN progression. Furthermore, a TF–miRNA–mRNA regulatory network was constructed using natural language processing models to identify 8 transcription factors and 60 miRNAs that regulate these biomarkers, while a drug–gene interaction network revealed potential therapeutic targets such as UROKINASE–PLG and ATENOLOL–AGT. This integrative approach, leveraging deep learning and ensemble models, not only enhances the accuracy of biomarker discovery but also offers new perspectives on DN diagnosis and treatment, specifically targeting fibrosis and propionate metabolism pathways.

Keywords: diabetic nephropathy, deep neural networks, gradient boosting machines (GBM), XGBoost

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Authors: Shaimaa M. Mohamed, Haitham S. Hamza, Imane A. Saroit

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Many wireless sensor network applications require K-coverage of the monitored area. In this paper, we propose a scalable harmony search based algorithm in terms of execution time, K-Coverage Enhancement Algorithm (KCEA), it attempts to enhance initial coverage, and achieve the required K-coverage degree for a specific application efficiently. Simulation results show that the proposed algorithm achieves coverage improvement of 5.34% compared to K-Coverage Rate Deployment (K-CRD), which achieves 1.31% when deploying one additional sensor. Moreover, the proposed algorithm is more time efficient.

Keywords: Wireless Sensor Networks (WSN), harmony search algorithms, K-Coverage, Mobile WSN

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Authors: Sabyasachi Mukhopadhyay, Joseph Ogutu, Gundula Bartzke, Hans-Peter Piepho

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Rainfall is a critical component of climate governing vegetation growth and production, forage availability and quality for herbivores. However, reliable rainfall measurements are not always available, making it necessary to predict rainfall values for particular locations through time. Predicting rainfall in space and time can be a complex and challenging task, especially where the rain gauge network is sparse and measurements are not recorded consistently for all rain gauges, leading to many missing values. Here, we develop a flexible Bayesian model for predicting rainfall in space and time and apply it to Narok County, situated in southwestern Kenya, using data collected at 23 rain gauges from 1965 to 2015. Narok County encompasses the Maasai Mara ecosystem, the northern-most section of the Mara-Serengeti ecosystem, famous for its diverse and abundant large mammal populations and spectacular migration of enormous herds of wildebeest, zebra and Thomson's gazelle. The model incorporates geographical and meteorological predictor variables, including elevation, distance to Lake Victoria and minimum temperature. We assess the efficiency of the model by comparing it empirically with the established Gaussian process, Kriging, simple linear and Bayesian linear models. We use the model to predict total monthly rainfall and its standard error for all 5 * 5 km grid cells in Narok County. Using the Monte Carlo integration method, we estimate seasonal and annual rainfall and their standard errors for 29 sub-regions in Narok. Finally, we use the predicted rainfall to predict large herbivore biomass in the Maasai Mara ecosystem on a 5 * 5 km grid for both the wet and dry seasons. We show that herbivore biomass increases with rainfall in both seasons. The model can handle data from a sparse network of observations with many missing values and performs at least as well as or better than four established and widely used models, on the Narok data set. The model produces rainfall predictions consistent with expectation and in good agreement with the blended station and satellite rainfall values. The predictions are precise enough for most practical purposes. The model is very general and applicable to other variables besides rainfall.

Keywords: non-stationary covariance function, gaussian process, ungulate biomass, MCMC, maasai mara ecosystem

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Authors: Ashish Kumar Singh, Preeti Tiwari, Shubham Srivastava, Rajiv Prakash, Herman Terryn, Gopal Ji

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Corrosion inhibition potential of azo dyes namely Allura red (AR), Sunset Yellow (SY) and Amaranth (AN) have been investigated in 0.5 M H2SO4 solutions by electrochemical impedance spectroscopy (EIS), Tafel polarization curves, linear polarization curves, open circuit potential (ocp) curves, UV-Visible spectroscopy, Fourier Transform Infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) techniques. Amaranth dye is found to provide highest corrosion inhibition (90 %) against mild steel corrosion in sulfuric acid solutions among all the tested dyes; while SY and AR dye shows 80% and 78% corrosion inhibition efficiency respectively. The electrochemical measurements and surface morphology analysis reveal that molecular adsorption of dyes at metal acid interface is accountable for inhibition of mild steel corrosion in H2SO4 solutions. The adsorption behavior of dyes has been investigated by various isotherms models, which verifies that it is in accordance with Langmuir isotherm.

Keywords: mild steel, Azo dye, EIS, Langmuir isotherm

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Authors: Radha H. R., Krupakara P. V.

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Metal matrix composites are attracting today's manufacturers of many automobile parts so that they lost longer and their properties can be tailored according to the requirement. In this paper an attempt has been made to study the corrosion characteristics of Aluminium 6061 / quartz metal matrix composites in alkali medium like sodium hydroxide solutions. Metal matrix composites are heterogeneous mixtures of a matrix and reinforcement. In this work the matrix selected is Aluminium 6061 alloy which is commercially available and the reinforcement selected is quartz particulates of 50-80 micron size which is available in plenty in and around Bangalore district, India. Composites containing Aluminium 6061 with 2, 4 and 6 weight percent of quartz are manufactured by liquid melt metallurgy technique using vortex method. Corrosion tests like static weight loss and open circuit potential tests are conducted in different concentrated solutions of sodium hydroxide. To compare the results the matrix Aluminium 6061 is also casted in the same way. Specimens for the test are prepared according to ASTM standards. In all the tests the metal matrix composites showed better corrosion resistance than matrix alloy.

Keywords: aluminium 6061, corrosion, quartz, vortex

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Authors: Joo-Hyung Oh

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The number of service users of 4G VoLTE (voice over LTE) using LTE data networks is rapidly growing. VoLTE based on all-IP network enables clearer and higher-quality voice calls than 3G. It does, however, pose new challenges; a voice call through IP networks makes it vulnerable to security threats such as wiretapping and forged or falsified information. And in particular, stealing other users’ phone numbers and forging or falsifying call request messages from outgoing voice calls within VoLTE result in considerable losses that include user billing and voice phishing to acquaintances. This paper focuses on the threats of caller phone number spoofing in the VoLTE and countermeasure technology as safety measures for mobile communication networks.

Keywords: LTE, 4G, VoLTE, phone number spoofing

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Authors: Jing Ma, Xindong An

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Green infrastructure, the most important aspect of improving the quality of life, has been a crucial element of the liveability measurement. With demanding of more liveable urban environment from increasing population in city area, access to green infrastructure in walking distance should be taken into consideration. This article exemplifies the study on accessibility measurement of green infrastructure in central Auckland (New Zealand), using network analysis tool on the basis of GIS, to verify the accessibility levels of green infrastructure. It analyses the overall situation of green infrastructure and draws some conclusions on the city’s different levels of accessibility according to the categories and facilities distribution, which provides valuable references and guidance for the future facility improvement in planning strategies.

Keywords: quality of life, green infrastructure, GIS, accessibility

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Authors: Neda Rezvanisanijouybari

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Cities are living and dynamic organisms that can play an essential role in meeting people's psychological and mental needs. The green and blue spaces, including parks, play an important role in meeting those needs, and therefore they should be prioritised in urban planning and designing. Sari city had several city designs and planning projects to expand the green spaces. These included adding more parks and open spaces with new urban furniture in the city and were an important step forward in creating a pleasant urban landscape in the north of Iran. This research used quantitative and qualitative methods to examine whether the citizens of Sari were satisfied with green and blue spaces and new urban furniture in the city or not. From a questionnaire of 120 Sari citizens, it was found that the citizens were generally satisfied with the green and blue spaces and new urban furniture in Sari. It was also found that the favourite park was Mellal park, and the least favourite was Azadegan park. Accessibility, safety, design, facilities, and water source were the most important reason to visit the parks.

Keywords: satisfaction, green, blue, urban furniture

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Authors: Paul C. Njoku, Archana Swati Njoku

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The study deals with the development of a mathematical model to characterize the oil production in Nigeria. This is calculated by initiating the dynamics of oil production in million barrels revenue plan cost of oil production in million nairas and unit cost of production from 1974-1982 in the contest of the federal Republic of Nigeria. This country export oil to other countries as well as importing specialized crude. The transport network from origin/destination tij to pairs is taking into account simulation runs, optimization have been considered in this study.

Keywords: mathematical oil model development dynamics, Nigeria, characterization barrels, dynamics of oil production

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Authors: Ahmedou Moulaye Idriss, Yahya Tfeil

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Medical imaging technology has become an indispensable tool in many branches of the biomedical, health area, and research and is vitally important for the training of professionals in these fields. It is not only about the tools, technologies, and knowledge provided but also about the community that this training project proposes. In order to be able to raise the level of anatomy teaching in the medical school of Nouakchott in Mauritania, it is necessary and even urgent to facilitate access to modern technology for African countries. The role of technology as a key driver of justifiable development has long been recognized. Anatomy is an essential discipline for the training of medical students; it is a key element for the training of medical specialists. The quality and results of the work of a young surgeon depend on his better knowledge of anatomical structures. The teaching of anatomy is difficult as the discipline is being neglected by medical students in many academic institutions. However, anatomy remains a vital part of any medical education program. When anatomy is presented in various planes medical students approve of difficulties in understanding. They do not increase their ability to visualize and mentally manipulate 3D structures. They are sometimes not able to correctly identify neighbouring or associated structures. This is the case when they have to make the identification of structures related to the caudate lobe when the liver is moved to different positions. In recent decades, some modern educational tools using digital sources tend to replace old methods. One of the main reasons for this change is the lack of cadavers in laboratories with poorly qualified staff. The emergence of increasingly sophisticated mathematical models, image processing, and visualization tools in biomedical imaging research have enabled sophisticated three-dimensional (3D) representations of anatomical structures. In this paper, we report our current experience in the Faculty of Medicine in Nouakchott Mauritania. One of our main aims is to create a local learning community in the fields of anatomy. The main technological platform used in this project is called 3D Slicer. 3D Slicer platform is an open-source application available for free for viewing, analysis, and interaction with biomedical imaging data. Using the 3D Slicer platform, we created from real medical images anatomical atlases of parts of the human body, including head, thorax, abdomen, liver, and pelvis, upper and lower limbs. Data were collected from several local hospitals and also from the website. We used MRI and CT-Scan imaging data from children and adults. Many different anatomy atlases exist, both in print and digital forms. Anatomy Atlas displays three-dimensional anatomical models, image cross-sections of labelled structures and source radiological imaging, and a text-based hierarchy of structures. Open and free online anatomical atlases developed by our anatomy laboratory team will be available to our students. This will allow pedagogical autonomy and remedy the shortcomings by responding more fully to the objectives of sustainable local development of quality education and good health at the national level. To make this work a reality, our team produced several atlases available in our faculty in the form of research projects.

Keywords: anatomy, education, medical imaging, three dimensional

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Authors: Marco Ferretti, Marcello Risitano, Maria Cristina Pietronudo, Lina Ozturk

Abstract:

A green port is the result of a sustainable long-term strategy adopted by an entire port infrastructure, therefore by the set of actors involved in port activities. The strategy aims to realise the development of sustainable port infrastructure focused on the reduction of negative environmental impacts without jeopardising economic growth. Green technology represents the core tool to implement sustainable solutions, however, they are not a magic bullet. Ports have always been integrated in the local territory affecting the environment in which they operate, therefore, the sustainable strategy should fit with the entire local systems. Therefore, adopting a sustainable strategy means to know how to involve and engage a wide stakeholders’ network (industries, production, markets, citizens, and public authority). The existing research on the topic has not well integrated this perspective with those of sustainability. Research on green ports have mixed the sustainability aspects with those on the maritime industry, neglecting dynamics that lead to the development of the green port phenomenon. We propose an analysis of green ports adopting the lens of ecosystem studies in the field of management. The ecosystem approach provides a way to model relations that enable green solutions and green practices in a port ecosystem. However, due to the local dimension of a port and the port trend on innovation, i.e., sustainable innovation, we draw to a specific concept of ecosystem, those on local innovation systems. More precisely, we explore if a green port is a local innovation system engaged in developing sustainable innovation with a large impact on the territory or merely an innovation adopter. To address this issue, we adopt a comparative case study selecting two innovative ports in Europe: Rotterdam and Genova. The case study is a research method focused on understanding the dynamics in a specific situation and can be used to provide a description of real circumstances. Preliminary results show two different approaches in supporting sustainable innovation: one represented by Rotterdam, a pioneer in competitiveness and sustainability, and the second one represented by Genoa, an example of technology adopter. The paper intends to provide a better understanding of how sustainable innovations are developed and in which manner a network of port and local stakeholder support this process. Furthermore, it proposes a taxonomy of green ports as developers and adopters of sustainable innovation, suggesting also best practices to model relationships that enable the port ecosystem in applying a sustainable strategy.

Keywords: green port, innovation, sustainability, local innovation systems

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Authors: Prachi Buche Marathe

Abstract:

Karanja Laad is a city located in the Vidarbha region in the state of Maharashtra, India. It has a huge amount of tangible and intangible heritage in the form of monuments, precincts, a group of structures, festivals and procession route, which is neglected and lost with time. Three different religions Hinduism, Islam and Jainism along with associations of being a birthplace of Swami Nrusinha Saraswati, an exponent of Datta Sampradaya sect and the British colonial layer have shaped the culture and society of the place over the period. The architecture of the town Karanja Laad has enhanced its unique historic and cultural value with a combination of all these historic layers. Karanja Laad is also a traditional trading historic town with unique hybrid architectural style and has a good potential for developing as a tourist place along with the present image of a pilgrim destination of Datta Sampradaya. The aim of the research is to prepare a conservation proposal for the historic town along with the management framework. Objectives of the research are to study the evolution of Karanja town, to identify the cultural resources along with issues of the historic core of the city, to understand Datta sampradaya, and contribution of Saint Nrusinha Saraswati in the religious sect and his association as an important personality with Karanja. The methodology of the research is site visits to the Karanja city, making field surveys for documentation and discussions and questionnaires with the residents to establish heritage and identify potential and issues within the historic core thereby establishing a case for conservation. Field surveys are conducted for town level study of land use, open spaces, occupancy, ownership, traditional commodity and community, infrastructure, streetscapes, and precinct activities during the festival and non-festival period. Building level study includes establishing various typologies like residential, institutional commercial, religious, and traditional infrastructure from the mythological references like waterbodies (kund), lake and wells. One of the main issues is that the loss of the traditional footprint as well as the traditional open spaces which are getting lost due to the new illegal encroachments and lack of guidelines for the new additions to conserve the original fabric of the structures. Traditional commodities are getting lost since there is no promotion of these skills like pottery and painting. Lavish bungalows like Kannava mansion, main temple Wada (birthplace of the saint) have a huge potential to be developed as a museum by adaptive re-use which will, in turn, attract many visitors during festivals which will boost the economy. Festival procession routes can be identified and a heritage walk can be developed so as to highlight the traditional features of the town. Overall study has resulted in establishing a heritage map with 137 heritage structures identified as potential. Conservation proposal is worked out on the town level, precinct level and building level with interventions such as developing construction guidelines for further development and establishing a heritage cell consisting architects and engineers for the upliftment of the existing rich heritage of the Karanja city.

Keywords: built heritage, conservation, Datta Sampradaya, Karanja Laad, Swami Nrusinha Saraswati, procession route

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Authors: Sunandapriya Bhikkhu, Shimo Sraman

Abstract:

The main objective of this research is to analytically study the concept of Lyotard’s different that rejects the monopoly criteria and single rule with the incommensurable, which can explain about conceptual problems of beauty in the philosophy of contemporary art. In Lyotard’s idea that basic value judgment of human should be a value like a phrase that is a small unit and an individual such as the aesthetic value that to explain the art world. From the concept of the anti-war artist that rejects the concept of the traditional aesthetic which cannot be able to explain the changing in contemporary society but emphasizes the meaning of individual beauty that is at the beginning of contemporary art today. In the analysis of the problem, the researcher supports the concept of Lyotard’s different that emphasizes the artistic expression which opens the space of perception and beyond the limitations of language process. Art is like phrase or small units that can convey a sense of humanity through the aesthetic value of the individual, not social criteria or universal. The concept of Lyotard’s different awakens and challenge us to the rejection of the single rule that is not open the social space to minorities by not accepting the monopoly criteria.

Keywords: difference, Jean-Francois Lyotard, postmodern, beauty, contemporary art

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Authors: A. Bahar Ganiyeva, M. Sabuhi Tanriverdiyev

Abstract:

The article analyzes state support and policy mechanisms aimed at driving tourism as one of the vibrant and rapidly developing economies. State programs and long-range strategic roadmaps and previous programs execution, results and their impact on the particular countries economy have been raised during the research. This theme provides a useful framework for discussions with a wider range of stakeholders as the implications arising are of importance both for academics and practitioners engaged in hospitality and tourism development and research. The impact that tourism has on sustainable regional development in emerging markets is highly substantial. For Azerbaijan, Turkey, Georgia, and Russia, with their rich natural resources and cultural heritage, tourism can be an important basis for economic expansion, and a way to form an acceptable image of the countries as safe, open, hospitable, and complex.

Keywords: Sustainable tourism, hospitality, destination, strategic roadmap, tourism, economy, growth, state support, mechanism, policy formation, state program

Procedia PDF Downloads 163