Search results for: 3D plant data
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 27260

Search results for: 3D plant data

20540 Subcritical and Supercritical Water Gasification of Xylose

Authors: Shyh-Ming Chern, Te-Hsiu Tang

Abstract:

Hemicellulose is one of the major constituents of all plant cell walls, making up 15-25% of dry wood. It is a biopolymer from many different sugar monomers, including pentoses, like xylose, and hexoses, like mannose. In an effort to gasify real biomass in subcritical and supercritical water in a single process, it is necessary to understand the gasification of hemicellulose, in addition to cellulose and lignin, in subcritical and supercritical water. In the present study, xylose is chosen as the model compound for hemicellulose, since it has the largest amount in most hardwoods. Xylose is gasified in subcritical and supercritical water for the production of higher-valued gaseous products. Experiments were conducted with a 16-ml autoclave batch-type reactor. Hydrogen peroxide is adopted as the oxidant in an attempt to promote the gasification yield. The major operating parameters for the gasification include reaction temperature (400 - 600°C), reaction pressure (5 - 25 MPa), the concentration of xylose (0.05 and 0.30 M), and level of oxidant added (0 and 0.25 chemical oxygen demand). 102 experimental runs were completed out of 46 different set of experimental conditions. Product gases were analyzed with a GC-TCD and determined to be mainly composed of H₂ (10 – 74 mol. %), CO (1 – 56 mol. %), CH₄ (1 – 27 mol. %), CO₂ (10 – 50 mol. %), and C₂H₆ (0 – 8 mol. %). It has been found that the gas yield (amount of gas produced per gram of xylose gasified), higher heating value (HHV) of the dry product gas, and energy yield (energy stored in the product gas divided by the energy stored in xylose) all increase significantly with rising temperature and moderately with reducing pressure. The overall best operating condition occurred at 873 K and 10 MPa, with a gas yield of 54 mmol/g of xylose, a gas HHV of 440 kJ/mol, and an energy yield of 1.3. A seemingly unreasonably energy yield of greater than unity resulted from the external heating employed in the experiments to drive the gasification process. It is concluded that xylose can be completely gasified in subcritical and supercritical water under proper operating conditions. The addition of oxidant does not promote the gasification of xylose.

Keywords: gasification, subcritical water, supercritical water, xylose

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20539 Analyzing the Results of Buildings Energy Audit by Using Grey Set Theory

Authors: Tooraj Karimi, Mohammadreza Sadeghi Moghadam

Abstract:

Grey set theory has the advantage of using fewer data to analyze many factors, and it is therefore more appropriate for system study rather than traditional statistical regression which require massive data, normal distribution in the data and few variant factors. So, in this paper grey clustering and entropy of coefficient vector of grey evaluations are used to analyze energy consumption in buildings of the Oil Ministry in Tehran. In fact, this article intends to analyze the results of energy audit reports and defines most favorable characteristics of system, which is energy consumption of buildings, and most favorable factors affecting these characteristics in order to modify and improve them. According to the results of the model, ‘the real Building Load Coefficient’ has been selected as the most important system characteristic and ‘uncontrolled area of the building’ has been diagnosed as the most favorable factor which has the greatest effect on energy consumption of building. Grey clustering in this study has been used for two purposes: First, all the variables of building relate to energy audit cluster in two main groups of indicators and the number of variables is reduced. Second, grey clustering with variable weights has been used to classify all buildings in three categories named ‘no standard deviation’, ‘low standard deviation’ and ‘non- standard’. Entropy of coefficient vector of Grey evaluations is calculated to investigate greyness of results. It shows that among the 38 buildings surveyed in terms of energy consumption, 3 cases are in standard group, 24 cases are in ‘low standard deviation’ group and 11 buildings are completely non-standard. In addition, clustering greyness of 13 buildings is less than 0.5 and average uncertainly of clustering results is 66%.

Keywords: energy audit, grey set theory, grey incidence matrixes, grey clustering, Iran oil ministry

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20538 Maximizing the Role of Companion Teachers for the Achievement of Professional Competencies and Pedagogics Workshop Activities of Teacher Professional Participants in the Faculty of Teaching and Education of Mulawarman University

Authors: Makrina Tindangen

Abstract:

The problems faced by participants of teacher profession program in Faculty of teaching and education Mulawarman University is professional and pedagogic competence. Professional competence related to the mastery of teaching materials, while pedagogic competence related with the ability to plan and to implement learning. Based on the problems, the purpose of the research is to maximize the role of companion teacher for the achievement of professional and pedagogic competencies in the workshop of the participants of teacher professional education in the Faculty of Teaching and Education of Mulawarman University. Qualitative research method with interview guidance and document to get in-depth data on how to maximize the role of companion teachers in the achievement of professional and pedagogic competencies in the workshop participants of professional education participants. Location of this research is on the Faculty of Teaching and Education of Mulawarman University, Samarinda City, East Kalimantan Province. Research respondents were 12 teachers of workshop facilitator. Descriptive data analysis is through interpretation of interview data. The conclusion of the research result, how to maximize the role of assistant teachers in workshop activities for the professional competence and pedagogic competence of professional teacher training program participants, through facilitation activities conducted by teachers of companion related to real problems faced by students in school, so that the workshop participants have professional competence and pedagogic as an initial competence before carrying out practical activities of field experience in school.

Keywords: companion teacher, professional and pedagogical competence, activities, workshop participants

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20537 Radar Cross Section Modelling of Lossy Dielectrics

Authors: Ciara Pienaar, J. W. Odendaal, J. Joubert, J. C. Smit

Abstract:

Radar cross section (RCS) of dielectric objects play an important role in many applications, such as low observability technology development, drone detection, and monitoring as well as coastal surveillance. Various materials are used to construct the targets of interest such as metal, wood, composite materials, radar absorbent materials, and other dielectrics. Since simulated datasets are increasingly being used to supplement infield measurements, as it is more cost effective and a larger variety of targets can be simulated, it is important to have a high level of confidence in the predicted results. Confidence can be attained through validation. Various computational electromagnetic (CEM) methods are capable of predicting the RCS of dielectric targets. This study will extend previous studies by validating full-wave and asymptotic RCS simulations of dielectric targets with measured data. The paper will provide measured RCS data of a number of canonical dielectric targets exhibiting different material properties. As stated previously, these measurements are used to validate numerous CEM methods. The dielectric properties are accurately characterized to reduce the uncertainties in the simulations. Finally, an analysis of the sensitivity of oblique and normal incidence scattering predictions to material characteristics is also presented. In this paper, the ability of several CEM methods, including method of moments (MoM), and physical optics (PO), to calculate the RCS of dielectrics were validated with measured data. A few dielectrics, exhibiting different material properties, were selected and several canonical targets, such as flat plates and cylinders, were manufactured. The RCS of these dielectric targets were measured in a compact range at the University of Pretoria, South Africa, over a frequency range of 2 to 18 GHz and a 360° azimuth angle sweep. This study also investigated the effect of slight variations in the material properties on the calculated RCS results, by varying the material properties within a realistic tolerance range and comparing the calculated RCS results. Interesting measured and simulated results have been obtained. Large discrepancies were observed between the different methods as well as the measured data. It was also observed that the accuracy of the RCS data of the dielectrics can be frequency and angle dependent. The simulated RCS for some of these materials also exhibit high sensitivity to variations in the material properties. Comparison graphs between the measured and simulation RCS datasets will be presented and the validation thereof will be discussed. Finally, the effect that small tolerances in the material properties have on the calculated RCS results will be shown. Thus the importance of accurate dielectric material properties for validation purposes will be discussed.

Keywords: asymptotic, CEM, dielectric scattering, full-wave, measurements, radar cross section, validation

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20536 IT-Aided Business Process Enabling Real-Time Analysis of Candidates for Clinical Trials

Authors: Matthieu-P. Schapranow

Abstract:

Recruitment of participants for clinical trials requires the screening of a big number of potential candidates, i.e. the testing for trial-specific inclusion and exclusion criteria, which is a time-consuming and complex task. Today, a significant amount of time is spent on identification of adequate trial participants as their selection may affect the overall study results. We introduce a unique patient eligibility metric, which allows systematic ranking and classification of candidates based on trial-specific filter criteria. Our web application enables real-time analysis of patient data and assessment of candidates using freely definable inclusion and exclusion criteria. As a result, the overall time required for identifying eligible candidates is tremendously reduced whilst additional degrees of freedom for evaluating the relevance of individual candidates are introduced by our contribution.

Keywords: in-memory technology, clinical trials, screening, eligibility metric, data analysis, clustering

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20535 The Influence of Learning Styles on Learners Grade Achievement in E-Learning Environments: An Empirical Study

Authors: Thomas Yeboah, Gifty Akouko Sarpong

Abstract:

Every learner has a specific learning style that helps him/her to study best. This means that any learning method (e-learning method or traditional face-to-face method) a learner chooses should address the learning style of the learner. Therefore, the main purpose of this research is to investigate whether learners’ grade achievement in e-learning environment is improved for learners with a particular learning style. In this research, purposive sampling technique was employed for selecting the sample size of three hundred and twenty (320) students studying a course UGRC 140 Science and Technology in our Lives at Christian Service University College. Data were analyzed by using, percentages, T -test, and one-way ANOVA. A thorough analysis was done on the data collected and the results revealed that learners with the Assimilator learning style and the converger learning style obtained higher grade achievement than both diverger learning style and accommodative learning style. Again, the results also revealed that accommodative learning style was not good enough for e-learning method.

Keywords: e-learning, learning style, grade achievement, accomodative, divergent, convergent, assimilative

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20534 Azaridachta indica (Neem) Seed Oil Effect in Experimental Arthritis: Biochemical Parameters Assessment

Authors: Sasan Khademnematolahi, Kevine Kamga Silihe, Katarína Pružinská, Martina Chrastina, Elisabeth Louise Ndjengue Mindang, František Dráfi, Katarína Bauerová

Abstract:

Background: In ethnomedicine, plant parts and compounds are traditionally utilized to treat many disorders. Azadirachta indica, known as Neem, has been traditionally used in medicinal practices. Due to the presence of bioactive substances such as nimbolide, azadirachtin, and gedunin, Neem offers a variety of medicinal properties, including anti-inflammatory and antioxidant properties. Through its effect on pathological inflammatory processes, supplementation with it could alleviate the symptoms of rheumatoid arthritis (RA). Methods: This research aimed to assess Neem seed oil's impact on rats with adjuvant arthritis. Three doses in monotherapy and two in combination with methotrexate (MTX) have been studied, and their effect was compared. Neem p.o. doses of 100, 200, and 300 mg/kg and MTX p.o. doses of 0.3 mg/kg were examined. After clinical parameters assessment, biochemical analysis was performed in plasma. Results: During the acute phase of the experimental arthritis (Day21), levels of MMP-9, MCP-1, and cytokines IL-1beta and IL-17A were measured. The positive results of inflammatory mediators evaluation in plasma encourage additional analysis also in related tissues to prove if Neem seed oil can be used as an adjuvant therapy for RA. Conclusion: In this study, the combination therapy of Neem with MTX was the most effective of all therapies investigated. Acknowledgement: SAIA PROJECT of Kevine Kamga Silihe, Slovakia-Cameroon 2023: “The effect of Crocus sativus L (Saffron), Azadirachta indica (Neem) and their main bioactives compounds in combinatory treatment with methotrexate on experimental arthritis”, VEGA 2/0079/24, VEGA 2/0136/20, VEGA 2/0126/23 and VEGA 2/0091/23.

Keywords: adjuvant, Neem, methotrexate, arthritis

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20533 Feasibility Study of MongoDB and Radio Frequency Identification Technology in Asset Tracking System

Authors: Mohd Noah A. Rahman, Afzaal H. Seyal, Sharul T. Tajuddin, Hartiny Md Azmi

Abstract:

Taking into consideration the real time situation specifically the higher academic institutions, small, medium to large companies, public to private sectors and the remaining sectors, do experience the inventory or asset shrinkages due to theft, loss or even inventory tracking errors. This happening is due to a zero or poor security systems and measures being taken and implemented in their organizations. Henceforth, implementing the Radio Frequency Identification (RFID) technology into any manual or existing web-based system or web application can simply deter and will eventually solve certain major issues to serve better data retrieval and data access. Having said, this manual or existing system can be enhanced into a mobile-based system or application. In addition to that, the availability of internet connections can aid better services of the system. Such involvement of various technologies resulting various privileges to individuals or organizations in terms of accessibility, availability, mobility, efficiency, effectiveness, real-time information and also security. This paper will look deeper into the integration of mobile devices with RFID technologies with the purpose of asset tracking and control. Next, it is to be followed by the development and utilization of MongoDB as the main database to store data and its association with RFID technology. Finally, the development of a web based system which can be viewed in a mobile based formation with the aid of Hypertext Preprocessor (PHP), MongoDB, Hyper-Text Markup Language 5 (HTML5), Android, JavaScript and AJAX programming language.

Keywords: RFID, asset tracking system, MongoDB, NoSQL

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20532 Small Target Recognition Based on Trajectory Information

Authors: Saad Alkentar, Abdulkareem Assalem

Abstract:

Recognizing small targets has always posed a significant challenge in image analysis. Over long distances, the image signal-to-noise ratio tends to be low, limiting the amount of useful information available to detection systems. Consequently, visual target recognition becomes an intricate task to tackle. In this study, we introduce a Track Before Detect (TBD) approach that leverages target trajectory information (coordinates) to effectively distinguish between noise and potential targets. By reframing the problem as a multivariate time series classification, we have achieved remarkable results. Specifically, our TBD method achieves an impressive 97% accuracy in separating target signals from noise within a mere half-second time span (consisting of 10 data points). Furthermore, when classifying the identified targets into our predefined categories—airplane, drone, and bird—we achieve an outstanding classification accuracy of 96% over a more extended period of 1.5 seconds (comprising 30 data points).

Keywords: small targets, drones, trajectory information, TBD, multivariate time series

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20531 Impact of Climate Change on Sea Level Rise along the Coastline of Mumbai City, India

Authors: Chakraborty Sudipta, A. R. Kambekar, Sarma Arnab

Abstract:

Sea-level rise being one of the most important impacts of anthropogenic induced climate change resulting from global warming and melting of icebergs at Arctic and Antarctic, the investigations done by various researchers both on Indian Coast and elsewhere during the last decade has been reviewed in this paper. The paper aims to ascertain the propensity of consistency of different suggested methods to predict the near-accurate future sea level rise along the coast of Mumbai. Case studies at East Coast, Southern Tip and West and South West coast of India have been reviewed. Coastal Vulnerability Index of several important international places has been compared, which matched with Intergovernmental Panel on Climate Change forecasts. The application of Geographic Information System mapping, use of remote sensing technology, both Multi Spectral Scanner and Thematic Mapping data from Landsat classified through Iterative Self-Organizing Data Analysis Technique for arriving at high, moderate and low Coastal Vulnerability Index at various important coastal cities have been observed. Instead of data driven, hindcast based forecast for Significant Wave Height, additional impact of sea level rise has been suggested. Efficacy and limitations of numerical methods vis-à-vis Artificial Neural Network has been assessed, importance of Root Mean Square error on numerical results is mentioned. Comparing between various computerized methods on forecast results obtained from MIKE 21 has been opined to be more reliable than Delft 3D model.

Keywords: climate change, Coastal Vulnerability Index, global warming, sea level rise

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20530 The Effect of Emotional Support towards Quality of Work Life on Balinese Working Women

Authors: I. Ketut Yoga Adityawira, Putu Ayu Novia Viorica, Komang Rahayu Indrawati

Abstract:

In addition to work and take care of the family, Balinese women also have a role to participate in social activities in Bali. So this will have an impact on the quality of work life of Balinese women. One way to reduce the impact of the fulfillment of the role of Balinese women namely through emotional support. The aim of this research is to find out the effect of emotional support towards the quality of work life on Balinese working women. Data were retrieved by quasi-experimental method with pretest-posttest design. Data were analyzed by Analysis of Variance (ANOVA) through SPSS 17.0 for Windows. The number of subjects in this research is 30 people with the criteria: Balinese Women, aged 27 to 55 years old, have a minimum of two years experience of work and has been married. The analysis showed that there is no effect of emotional support towards the quality of work life on Balinese working women, with information there is no significant of probability value p = 0.304 (p > 0.05).

Keywords: Balinese women, emotional support, quality of work life, working women

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20529 Research on Internet Attention of Tourism and Marketing Strategy in Northeast Sichuan Economic Zone in China Based on Baidu Index

Authors: Chuanqiao Zheng, Wei Zeng, Haozhen Lin

Abstract:

As of March 2020, the number of Chinese netizens has reached 904 million. The proportion of Internet users accessing the Internet through mobile phones is as high as 99.3%. Under the background of 'Internet +', tourists have a stronger sense of independence in the choice of tourism destinations and tourism products. Tourists are more inclined to learn about the relevant information on tourism destinations and other tourists' evaluations of tourist products through the Internet. The search engine, as an integrated platform that contains a wealth of information, is highly valuable to the analysis of the characteristics of the Internet attention given to various tourism destinations, through big data mining and analysis. This article uses the Baidu Index as the data source, which is one of the products of Baidu Search. The Baidu Index is based on big data, which collects and shares the search results of a large number of Internet users on the Baidu search engine. The big data used in this article includes search index, demand map, population profile, etc. The main research methods used are: (1) based on the search index, analyzing the Internet attention given to the tourism in five cities in Northeast Sichuan at different times, so as to obtain the overall trend and individual characteristics of tourism development in the region; (2) based on the demand map and the population profile, analyzing the demographic characteristics and market positioning of the tourist groups in these cities to understand the characteristics and needs of the target groups; (3) correlating the Internet attention data with the permanent population of each province in China in the corresponding to construct the Boston matrix of the Internet attention rate of the Northeast Sichuan tourism, obtain the tourism target markets, and then propose development strategies for different markets. The study has found that: a) the Internet attention given to the tourism in the region can be categorized into tourist off-season and peak season; the Internet attention given to tourism in different cities is quite different. b) tourists look for information including tour guide information, ticket information, traffic information, weather information, and information on the competing tourism cities; with regard to the population profile, the main group of potential tourists searching for the keywords of tourism in the five prefecture-level cities in Northeast Sichuan are youth. The male to female ratio is about 6 to 4, with males being predominant. c) through the construction of the Boston matrix, it is concluded that the star market for tourism in the Northeast Sichuan Economic Zone includes Sichuan and Shaanxi; the cash cows market includes Hainan and Ningxia; the question market includes Jiangsu and Shanghai; the dog market includes Hubei and Jiangxi. The study concludes with the following planning strategies and recommendations: i) creating a diversified business format that integrates cultural and tourism; ii) creating a brand image of niche tourism; iii) focusing on the development of tourism products; iv) innovating composite three-dimensional marketing channels.

Keywords: Baidu Index, big data, internet attention, tourism

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20528 Innovative Communication for Promoting Tourism in Southern Thailand

Authors: Pitimanus Bunlue

Abstract:

This research aim (1) to determine the content of communication, social capital and cultural capital to promote tourism in the province to create awareness, motivation and desire to tourists visiting Thailand (2) to evaluate the performance of innovation communication social capital and cultural capital to promote tourism southern of Thailand. This research is a qualitative research. A research synthesis projects on social capital and cultural capital by use focus group discussions with media professionals and academics to communicate using a random sample specific. The result show that (1) Innovative communication, social capital and cultural capital and effective communication innovations after everyone wants to travel to Ranong province is the very highest level. (2) Information and experience about Ranong at a high level. (3) The data shows the strengths of each of the attractions at a high level. (4) The data shows a lifestyle that is unique to the province is moderate.

Keywords: innovative communication, promoting tourism, southern of Thailand, social capital

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20527 Evidence Theory Based Emergency Multi-Attribute Group Decision-Making: Application in Facility Location Problem

Authors: Bidzina Matsaberidze

Abstract:

It is known that, in emergency situations, multi-attribute group decision-making (MAGDM) models are characterized by insufficient objective data and a lack of time to respond to the task. Evidence theory is an effective tool for describing such incomplete information in decision-making models when the expert and his knowledge are involved in the estimations of the MAGDM parameters. We consider an emergency decision-making model, where expert assessments on humanitarian aid from distribution centers (HADC) are represented in q-rung ortho-pair fuzzy numbers, and the data structure is described within the data body theory. Based on focal probability construction and experts’ evaluations, an objective function-distribution centers’ selection ranking index is constructed. Our approach for solving the constructed bicriteria partitioning problem consists of two phases. In the first phase, based on the covering’s matrix, we generate a matrix, the columns of which allow us to find all possible partitionings of the HADCs with the service centers. Some constraints are also taken into consideration while generating the matrix. In the second phase, based on the matrix and using our exact algorithm, we find the partitionings -allocations of the HADCs to the centers- which correspond to the Pareto-optimal solutions. For an illustration of the obtained results, a numerical example is given for the facility location-selection problem.

Keywords: emergency MAGDM, q-rung orthopair fuzzy sets, evidence theory, HADC, facility location problem, multi-objective combinatorial optimization problem, Pareto-optimal solutions

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20526 Intrusion Detection in Cloud Computing Using Machine Learning

Authors: Faiza Babur Khan, Sohail Asghar

Abstract:

With an emergence of distributed environment, cloud computing is proving to be the most stimulating computing paradigm shift in computer technology, resulting in spectacular expansion in IT industry. Many companies have augmented their technical infrastructure by adopting cloud resource sharing architecture. Cloud computing has opened doors to unlimited opportunities from application to platform availability, expandable storage and provision of computing environment. However, from a security viewpoint, an added risk level is introduced from clouds, weakening the protection mechanisms, and hardening the availability of privacy, data security and on demand service. Issues of trust, confidentiality, and integrity are elevated due to multitenant resource sharing architecture of cloud. Trust or reliability of cloud refers to its capability of providing the needed services precisely and unfailingly. Confidentiality is the ability of the architecture to ensure authorization of the relevant party to access its private data. It also guarantees integrity to protect the data from being fabricated by an unauthorized user. So in order to assure provision of secured cloud, a roadmap or model is obligatory to analyze a security problem, design mitigation strategies, and evaluate solutions. The aim of the paper is twofold; first to enlighten the factors which make cloud security critical along with alleviation strategies and secondly to propose an intrusion detection model that identifies the attackers in a preventive way using machine learning Random Forest classifier with an accuracy of 99.8%. This model uses less number of features. A comparison with other classifiers is also presented.

Keywords: cloud security, threats, machine learning, random forest, classification

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20525 Normal or Abnormal: A Case Study of Jihadi Salafism in the Middle East

Authors: Yusef Karimi, Masoomeh Esmaeily, Razgar Mohammadi

Abstract:

Following the events of September 11th, one of the most important concerns of governments, politicians and, researchers has been to answer the question that why does an ordinary person become fundamentalism? One of the major controversies in past researches was about as to whether a fundamentalist person is normal or abnormal. In this regard, the purpose of this research is to investigate whether a Salafi-jihadi individual is normal or abnormal. The participants included 6 Jihadi Salafism individuals who were living in the Middle East and had been purposefully selected. This research is a qualitative study which examines these people′s retrospective experience of their lives. The data were collected through collaborative observation and interview. This continued till data saturation. Unlike the introduced concepts of fundamentalist personality in the previous studies such as self-fascination, aggression, paranoid personality and psychopathic, participants in this study had no abnormal symptoms of mental disorders. Hence, in the context of recognizing the fundamentalist personality, we must seek other personality and positional variables.

Keywords: abnormal, fundamentalism, normal, personality, Salafi

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20524 Global Healthcare Village Based on Mobile Cloud Computing

Authors: Laleh Boroumand, Muhammad Shiraz, Abdullah Gani, Rashid Hafeez Khokhar

Abstract:

Cloud computing being the use of hardware and software that are delivered as a service over a network has its application in the area of health care. Due to the emergency cases reported in most of the medical centers, prompt for an efficient scheme to make health data available with less response time. To this end, we propose a mobile global healthcare village (MGHV) model that combines the components of three deployment model which include country, continent and global health cloud to help in solving the problem mentioned above. In the creation of continent model, two (2) data centers are created of which one is local and the other is global. The local replay the request of residence within the continent, whereas the global replay the requirements of others. With the methods adopted, there is an assurance of the availability of relevant medical data to patients, specialists, and emergency staffs regardless of locations and time. From our intensive experiment using the simulation approach, it was observed that, broker policy scheme with respect to optimized response time, yields a very good performance in terms of reduction in response time. Though, our results are comparable to others when there is an increase in the number of virtual machines (80-640 virtual machines). The proportionality in increase of response time is within 9%. The results gotten from our simulation experiments shows that utilizing MGHV leads to the reduction of health care expenditures and helps in solving the problems of unqualified medical staffs faced by both developed and developing countries.

Keywords: cloud computing (MCC), e-healthcare, availability, response time, service broker policy

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20523 An Application of Extreme Value Theory as a Risk Measurement Approach in Frontier Markets

Authors: Dany Ng Cheong Vee, Preethee Nunkoo Gonpot, Noor Sookia

Abstract:

In this paper, we consider the application of Extreme Value Theory as a risk measurement tool. The Value at Risk, for a set of indices, from six Stock Exchanges of Frontier markets is calculated using the Peaks over Threshold method and the performance of the model index-wise is evaluated using coverage tests and loss functions. Our results show that 'fat-tailedness' alone of the data is not enough to justify the use of EVT as a VaR approach. The structure of the returns dynamics is also a determining factor. This approach works fine in markets which have had extremes occurring in the past thus making the model capable of coping with extremes coming up (Colombo, Tunisia and Zagreb Stock Exchanges). On the other hand, we find that indices with lower past than present volatility fail to adequately deal with future extremes (Mauritius and Kazakhstan). We also conclude that using EVT alone produces quite static VaR figures not reflecting the actual dynamics of the data.

Keywords: extreme value theory, financial crisis 2008, value at risk, frontier markets

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20522 Tectono-Thermal Evolution of Ningwu-Jingle Basin in North China Craton: Constraints from Apatite (U–Th-Sm)/He and Fission Track Thermochronology

Authors: Zhibin Lei, Minghui Yang

Abstract:

Ningwu-Jingle basin is a structural syncline which has undergone a complex tectono-thermal history since Cretaceous. It stretches along the strike of the northern Lvliang Mountains which are the most important mountains in the middle and west of North China Craton. The Mesozoic units make up of the core of Ningwu-Jingle Basin, with pre-Mesozoic units making up of its flanks. The available low-temperature thermochronology implies that Ningwu-Jingle Basin has experienced two stages of uplifting: 94±7Ma to 111±8Ma (Albian to Cenomanian) and 62±4 to 75±5Ma (Danian to Maastrichtian). In order to constrain its tectono-thermal history in the Cenozoic, both apatite (U-Th-Sm)/He and fission track dating analysis are applied on 3 Middle Jurassic and 3 Upper Triassic sandstone samples. The central fission track ages range from 74.4±8.8Ma to 66.0±8.0Ma (Campanian to Maastrichtian) which matches well with previous data. The central He ages range from 20.1±1.2Ma to 49.1±3.0Ma (Ypresian to Burdigalian). Inverse thermal modeling is established based on both apatite fission track data and (U-Th-Sm)/He data. The thermal history obtained reveals that all 6 sandstone samples cross the high-temperature limit of fission track partial annealing zone by the uppermost Cretaceous and that of He partial retention zone by the uppermost Eocene to the early Oligocene. The result indicates that the middle and west of North China Craton is not stable in the Cenozoic.

Keywords: apatite fission track thermochronology, apatite (u–th)/he thermochronology, Ningwu-Jingle basin, North China craton, tectono-thermal history

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20521 Polygenetic Iron Mineralization in the Baba-Ali and Galali Deposits, Further Evidences from Stable (S, O, H) Isotope Data, NW Hamedan, Iran

Authors: Ghodratollah Rostami Paydar

Abstract:

The Baba-Ali and Galali iron deposits are located in northwest Hamedan and the Iranian Sanandaj-Sirjan geological structural zone. The host rocks of these deposits are metavolcanosedimentary successions of Songhor stratigraphic series with permo-trriassic age. Field investigation, ore geometry, textures and structures and paragenetic sequence of minerals, all indicate that the ore minerals are crystallized in four stages: primary volcanosedimentary stage, secondary regional metamorphism with formation of ductile shear zones, contact metamorphism and metasomatism stage and the finally late hydrothermal mineralization within uplift and exposure. Totally 29 samples of sulfide, oxide-silicate and carbonate minerals of iron orees and gangue has been purified for stable isotope analysis. The isotope ratio data assure that occurrence of dynamothermal metamorphism in these areas typically involves a lengthy period of time, which results in a tendency toward isotopic homogenization specifically in O and H stable isotopes and showing the role of metamorphic waters in mineralization process. Measurement of δ34S (CDT) in first generation of pyrite is higher than another ones, so it confirms the volcanogenic origin of primary iron mineralization. δ13C data measurements in Galali carbonate country rocks show a marine origin. δ18O in magnetite and skarn forming silicates, δ18O and δ13C in limestone and skarn calcite and δ34S in sulphides are all consistent with the interaction of a magmatic-equilibrated fluid with Galali limestone, and a dominantly magmatic source for S. All these data imply skarn formation and mineralisation in a magmatic-hydrothermal system that maintained high salinity to relatively late stages resulting in the formation of the regional Na metasomatic alteration halo. Late stage hydrothermal quartz-calcite veinlets are important for gold mineralization, but the economic evaluation is required to detailed geochemical studies.

Keywords: iron, polygenetic, stable isotope, BabaAli, Galali

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20520 Channel Estimation/Equalization with Adaptive Modulation and Coding over Multipath Faded Channels for WiMAX

Authors: B. Siva Kumar Reddy, B. Lakshmi

Abstract:

WiMAX has adopted an Adaptive Modulation and Coding (AMC) in OFDM to endure higher data rates and error free transmission. AMC schemes employ the Channel State Information (CSI) to efficiently utilize the channel and maximize the throughput and for better spectral efficiency. This CSI has given to the transmitter by the channel estimators. In this paper, LSE (Least Square Error) and MMSE (Minimum Mean square Error) estimators are suggested and BER (Bit Error Rate) performance has been analyzed. Channel equalization is also integrated with with AMC-OFDM system and presented with Constant Modulus Algorithm (CMA) and Least Mean Square (LMS) algorithms with convergence rates analysis. Simulation results proved that increment in modulation scheme size causes to improvement in throughput along with BER value. There is a trade-off among modulation size, throughput, BER value and spectral efficiency. Results also reported the requirement of channel estimation and equalization in high data rate systems.

Keywords: AMC, CSI, CMA, OFDM, OFDMA, WiMAX

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20519 Ontology-Driven Knowledge Discovery and Validation from Admission Databases: A Structural Causal Model Approach for Polytechnic Education in Nigeria

Authors: Bernard Igoche Igoche, Olumuyiwa Matthew, Peter Bednar, Alexander Gegov

Abstract:

This study presents an ontology-driven approach for knowledge discovery and validation from admission databases in Nigerian polytechnic institutions. The research aims to address the challenges of extracting meaningful insights from vast amounts of admission data and utilizing them for decision-making and process improvement. The proposed methodology combines the knowledge discovery in databases (KDD) process with a structural causal model (SCM) ontological framework. The admission database of Benue State Polytechnic Ugbokolo (Benpoly) is used as a case study. The KDD process is employed to mine and distill knowledge from the database, while the SCM ontology is designed to identify and validate the important features of the admission process. The SCM validation is performed using the conditional independence test (CIT) criteria, and an algorithm is developed to implement the validation process. The identified features are then used for machine learning (ML) modeling and prediction of admission status. The results demonstrate the adequacy of the SCM ontological framework in representing the admission process and the high predictive accuracies achieved by the ML models, with k-nearest neighbors (KNN) and support vector machine (SVM) achieving 92% accuracy. The study concludes that the proposed ontology-driven approach contributes to the advancement of educational data mining and provides a foundation for future research in this domain.

Keywords: admission databases, educational data mining, machine learning, ontology-driven knowledge discovery, polytechnic education, structural causal model

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20518 The Gastroprotective Potential of Clematis Flammula Leaf Extracts

Authors: Dina Atmani-Kilani, Farah Yous, Djebbar Atmani

Abstract:

The etiology of peptic ulcer is closely related to stress, excessive consumption of nonsteroidal anti-inflammatory drugs, or ethanol. Clematis flammula (Ranunculaceae) is a medicinal plant widely used by rural populations to treat inflammatory disorders. This study was designed to assess the gastroprotective potential of C. flammula extracts. Gastric ulcer was induced by stress, indomethacin, HCl / ethanol, and absolute ethanol on NMRI-type mice. The antioxidant potency of the ethanolic extract of Clematis flammula (EECF) was evaluated on catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GPx) activities. Glutathione (GSH) and malonaldehyde (MDA) levels were also quantified. The anti-inflammatory potential was evaluated through the effect of EECF on myeloperoxidase activity (MPO) and vascular permeability. Complementary tests concerning the quantification of mucus levels, gastric motility, inhibition of ATPase H+/K+activity, as well as a histopathological study were also undertaken to explore the mechanism of action of the EECF. The EECF exhibited a significant (p <0.001) and optimal (100 mg/kg) gastroprotective effect by elevating SOD, CAT, and GSH levels, thereby minimizing the production of MDA and lowering the activity of MPO and vascular permeability. EECF also increased the rate of mucus production, decreased gastric motility, and completely suppressed the H+/K+ ATPase activity. Histopathological study confirmed the effectiveness of the extract in the prevention of peptic ulcer. The results obtained in this study demonstrated the gastro-protective effect of EECF via acidic antioxidant, anti-inflammatory, cytoprotective and anti-secretory mechanisms, which may justify its use as a substitute in peptic ulcer treatment.

Keywords: clematis flammula, superoxide dismutase, myeloperoxidase, ATPase, pump

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20517 Hydraulic Performance of Three Types of Imported Drip Emitters Used in Gezira Clay Soils, Sudan

Authors: Hisham Mousa Mohammed Ahmed, Ahmed Wali Mohamed Salad, Yousif Hamed Dldom Gomaa

Abstract:

A drip or Trickle irrigation system is designed to apply a precise amount of water near the plant with a certain degree of uniformity. This study was conducted at the Experimental Farm of the Faculty of Agricultural Sciences, University of Gezira, in March 2018. The study aimed to design and evaluate the hydraulic performance of three drip emitter types using: average discharge (Qavg), discharge variation (Qvar %), coefficient of uniformity (CU %), coefficient of manufacturer variation (CV %), distribution uniformity (DU %), statistical uniformity (Us %), clogging (%) wetted diameter (cm) and wetted depth (cm). The emitter types used are regular gauges (RG), high compensating pressure (HCP) and low compensating pressure (LCP). The treatments were laid out in a randomized complete block design (RCBD) with four replications. Results showed that there were significant differences (P≤0.05) in all tested parameters except clogging, wetted diameter and wetted depth. Discharge variation (Qvar %) values were 12.71, 15.57 and 19.17 for RG, LCP, and HCP, respectively. The variation is quite good and within the acceptable range. Results of coefficient of manufacture variation (CV %) were 10.9, 27.8 and 52.7 for RG, LCP and HCP, respectively. It is considered within the unacceptable range except for RG type, which is excellent. Statistical uniformity (Us %) values were 89.1, 72.2 and 45.7 for RG, LCP and HCP, respectively. It is considered good, acceptable and unacceptable, respectively. Results of the coefficient of uniformity (CU %) were 91.3, 77.7 and 56.7 for RG, LCP and HCP, respectively. It is considered excellent, fair and unacceptable, respectively. Distribution uniformity (DU %) was 90.2, 67.9 and 36.5 for RG, LCP and HCP, respectively. It is considered excellent, poor and poor, respectively. The study recommended regular gauges (RG) type emitters under the heavy clay soil conditions of the Gezira State, Sudan.

Keywords: drip irrigation, uniformity, clogging, coefficient, performance

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20516 Hierarchically Modeling Cognition and Behavioral Problems of an Under-Represented Group

Authors: Zhidong Zhang, Zhi-Chao Zhang

Abstract:

This study examines adolescent psychological and behavioral problems. The Achenbach systems of empirically based assessment (ASEBA) were used as the instrument. The problem framework consists of internal, external and social behavioral problems which are theoretically developed based on about 113 items plus relevant background variables. In this study, the sample consist of 1,975 sixth and seventh grade students in Northeast China. Stratified random sampling method was used to collect the data, meaning that samples were from different school districts, schools, and classes. The researchers looked at both macro and micro effect. Therefore, multilevel analysis techniques were used in the data analysis. The parts of the research results indicated that the background variables such as extracurricular activities were directly related to students’ internal problems.

Keywords: behavioral problems, anxious/depressed problems, internalizing problems, mental health, under-represented groups, empirically-based assessment, hierarchical modeling, ASEBA, multilevel analysis

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20515 Short-Term Forecast of Wind Turbine Production with Machine Learning Methods: Direct Approach and Indirect Approach

Authors: Mamadou Dione, Eric Matzner-lober, Philippe Alexandre

Abstract:

The Energy Transition Act defined by the French State has precise implications on Renewable Energies, in particular on its remuneration mechanism. Until then, a purchase obligation contract permitted the sale of wind-generated electricity at a fixed rate. Tomorrow, it will be necessary to sell this electricity on the Market (at variable rates) before obtaining additional compensation intended to reduce the risk. This sale on the market requires to announce in advance (about 48 hours before) the production that will be delivered on the network, so to be able to predict (in the short term) this production. The fundamental problem remains the variability of the Wind accentuated by the geographical situation. The objective of the project is to provide, every day, short-term forecasts (48-hour horizon) of wind production using weather data. The predictions of the GFS model and those of the ECMWF model are used as explanatory variables. The variable to be predicted is the production of a wind farm. We do two approaches: a direct approach that predicts wind generation directly from weather data, and an integrated approach that estimâtes wind from weather data and converts it into wind power by power curves. We used machine learning techniques to predict this production. The models tested are random forests, CART + Bagging, CART + Boosting, SVM (Support Vector Machine). The application is made on a wind farm of 22MW (11 wind turbines) of the Compagnie du Vent (that became Engie Green France). Our results are very conclusive compared to the literature.

Keywords: forecast aggregation, machine learning, spatio-temporal dynamics modeling, wind power forcast

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20514 Modeling Route Selection Using Real-Time Information and GPS Data

Authors: William Albeiro Alvarez, Gloria Patricia Jaramillo, Ivan Reinaldo Sarmiento

Abstract:

Understanding the behavior of individuals and the different human factors that influence the choice when faced with a complex system such as transportation is one of the most complicated aspects of measuring in the components that constitute the modeling of route choice due to that various behaviors and driving mode directly or indirectly affect the choice. During the last two decades, with the development of information and communications technologies, new data collection techniques have emerged such as GPS, geolocation with mobile phones, apps for choosing the route between origin and destination, individual service transport applications among others, where an interest has been generated to improve discrete choice models when considering the incorporation of these developments as well as psychological factors that affect decision making. This paper implements a discrete choice model that proposes and estimates a hybrid model that integrates route choice models and latent variables based on the observation on the route of a sample of public taxi drivers from the city of Medellín, Colombia in relation to its behavior, personality, socioeconomic characteristics, and driving mode. The set of choice options includes the routes generated by the individual service transport applications versus the driver's choice. The hybrid model consists of measurement equations that relate latent variables with measurement indicators and utilities with choice indicators along with structural equations that link the observable characteristics of drivers with latent variables and explanatory variables with utilities.

Keywords: behavior choice model, human factors, hybrid model, real time data

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20513 Shield Tunnel Excavation Simulation of a Case Study Using a So-Called 'Stress Relaxation' Method

Authors: Shengwei Zhu, Alireza Afshani, Hirokazu Akagi

Abstract:

Ground surface settlement induced by shield tunneling is addressing increasing attention as shield tunneling becomes a popular construction technique for tunnels in urban areas. This paper discusses a 2D longitudinal FEM simulation of a tunneling case study in Japan (Tokyo Metro Yurakucho Line). Tunneling-induced field data was already collected and is used here for comparison and evaluating purposes. In this model, earth pressure, face pressure, backfilling grouting, elastic tunnel lining, and Mohr-Coulomb failure criterion for soil elements are considered. A method called ‘stress relaxation’ is also exploited to simulate the gradual tunneling excavation. Ground surface settlements obtained from numerical results using the introduced method are then compared with the measurement data.

Keywords: 2D longitudinal FEM model, tunneling case study, stress relaxation, shield tunneling excavation

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20512 In vivo Genotoxicity Testing of Sesbania Grandiflora (Katuray) Flower Methanolic Extract

Authors: Levylee Bautista, Dawn Grace Santos, Aishwarya Veluchamy, Jesusa Santos, Ghafoor, Jr. I Haque, Rodolfo Rafael

Abstract:

The booming interest in using natural compounds as an alternative to conventional medications has paved way to focus the attention on plants that provide rich sources of bioactive phytochemicals. For regulatory purposes, evaluation of the genotoxic effects of such alternatives is therefore empirical as part of the plant’s hazard assessment. Sesbania grandiflora is among the plants used as a traditional remedy in folk medicine and a subject of research for its medicinal benefits. This study aimed to evaluate the genotoxic potential induced by S. grandiflora flower methanol extract (SGFME) in terms of the frequency of micronucleus (MN) in polychromatic erythrocyte (PCE) (MNPCE) and PCE ratio employing the micronucleus assay. The frequency of MN was examined in bone marrow cells (BMCs) obtained from male Swiss albino mice exposed in vivo to four different concentrations (11.25, 22.5, 40, and 90 mg/kg) of SGFME and MMC (70 mg/kg; positive control) and sacrificed 24 hours post-intraperitoneal injection. Results showed a significant (p < 0.01) rate of MNPCEs for 11.25 and 22.5 tested concentrations of SGFME and is comparable with the MMC-treated mice. Although PCE ratio values in all doses of SGFME-treated mice were over 0.20, it is worth noting that 40 and 90 tested concentrations of SGFME-treated mice exhibited the lowest value, i.e., 0.22 and 0.28, respectively. The present study has demonstrated that S. grandiflora possesses genotoxic potential for murine BMCs. Such activity could be ascribed from the bioactive compounds present in S. grandiflora that require further isolation and characterization of the active molecules. Likewise, findings of this study warrant a caution of the use of S. grandiflora insomuch as further investigations do not demonstrate their safety.

Keywords: genotoxicity, micronucleus, phytochemicals, Sesbania grandiflora

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20511 The Significance of Muslim Families Awareness on Islamic Business Ethics in Promoting Business for Economic Development in Sokoto State, Nigeria

Authors: Hassan Malami Alkanchi

Abstract:

Acquiring the knowledge of Islamic business ethics nowadays for the conduct of business activities and other business transactions has become one of the best strategies for promoting lawful business as well as a successful business for economic development. The idea of infusing the significance of Islamic business ethics into the minds of Muslim individuals has spurred much enthusiasm in the last few decades. Putting this idea into practice posed significant impacts on the life of Muslim individuals for the development of business. The main objective of this paper is to explore the significant role of Muslim families' awareness in promoting Islamic business ethics for successful business economic development. The methodology adopted for the conduct of this study is qualitative research. The study employed a purposive sampling technique and considered it the most suitable method for data collection. The data collection techniques employed for this study were interviews and focus group discussions. The study used semi-structured interviews and focus group discussions for the data collection. The standard used for selecting the participants was strictly based on professionalism, relevance, expertise and the willingness of the participants to participate in the study. The participants interviewed include Muslim family experts, Islamic scholars, and media workers, comprising five (5) participants for each research subject. Twelve (15) participants were sampled for the study. The method of data analysis used is thematic and theoretical explanations. This paper analytically discusses the new and emerging ethical issues in relation to business activities as well as new strategies for the development of successful businesses for economic prosperity, growth, and development. The study findings revealed that the awareness of Muslim families in promoting Islamic business ethics has significantly contributed to changing the negative attitudes of some Muslim individuals' in relation to their business. Furthermore, findings of unveiled Muslim individuals immensely benefited towards understanding and having knowledge in relation to ethical business guidelines enshrined by the sharia in the conduct of pure business as well as strengthening Islamic business ethics through the teachings of the noble Quran and Sunnah.

Keywords: Muslim family, awareness, business ethics, economic development

Procedia PDF Downloads 64