Search results for: IF rough relational database
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2034

Search results for: IF rough relational database

1854 Comparison between RILM, JSTOR, and WorldCat Used to Search for Secondary Literature

Authors: Stacy Jarvis

Abstract:

Databases such as JSTOR, RILM and WorldCat have been the main source and storage of literature in the music orb. The Reference Index to Music Literature is a bibliographic database of over 2.6 million citations to writings about music from over 70 countries. The Research Institute produces RILM for the Study of Music at the University of Buffalo. JSTOR is an e-library of academic journals, books, and primary sources. Database JSTOR helps scholars find, utilise, and build upon a vast range of literature through a powerful teaching and research platform. Another database, WorldCat, is the world's biggest library catalogue, assisting scholars in finding library materials online. An evaluation of these databases in the music sphere is conducted by looking into the description and intended use and finding similarities and differences among them. Through comparison, it is found that these aim to serve different purposes, though they have the same goal of providing and storing literature. Also, since each database has different parts of literature that it majors on, the intended use of the three databases is evaluated. This can be found in the description, scope, and intended uses section. These areas are crucial to the research as it addresses the functional or literature differences among the three databases. It is also found that these databases have different quantitative potentials. This is determined by addressing the year each database began collecting literature and the number of articles, periodicals, albums, conference proceedings, music, dissertations, digital media, essays collections, journal articles, monographs, online resources, reviews, and reference materials that can be found in each one of them. This can be found in the sections- description, scope and intended uses and the importance of the database in identifying literature on different topics. To compare the delivery of services to the users, the importance of databases in identifying literature on different topics is also addressed in the section -the importance of databases in identifying literature on different topics. Even though these databases are used in research, they all have disadvantages and advantages. This is addressed in the sections on advantages and disadvantages. This will be significant in determining which of the three is the best. Also, it will help address how the shortcomings of one database can be addressed by utilising two databases together while conducting research. It is addressed in the section- a combination of RILM and JSTOR. All this information revolves around the idea that a huge amount of quantitative and qualitative data can be found in the presented databases on music and digital content; however, each of the given databases has a different construction and material features contributing to the musical scholarship in its way.

Keywords: RILM, JSTOR, WorldCat, database, literature, research

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1853 An Optimized Association Rule Mining Algorithm

Authors: Archana Singh, Jyoti Agarwal, Ajay Rana

Abstract:

Data Mining is an efficient technology to discover patterns in large databases. Association Rule Mining techniques are used to find the correlation between the various item sets in a database, and this co-relation between various item sets are used in decision making and pattern analysis. In recent years, the problem of finding association rules from large datasets has been proposed by many researchers. Various research papers on association rule mining (ARM) are studied and analyzed first to understand the existing algorithms. Apriori algorithm is the basic ARM algorithm, but it requires so many database scans. In DIC algorithm, less amount of database scan is needed but complex data structure lattice is used. The main focus of this paper is to propose a new optimized algorithm (Friendly Algorithm) and compare its performance with the existing algorithms A data set is used to find out frequent itemsets and association rules with the help of existing and proposed (Friendly Algorithm) and it has been observed that the proposed algorithm also finds all the frequent itemsets and essential association rules from databases as compared to existing algorithms in less amount of database scan. In the proposed algorithm, an optimized data structure is used i.e. Graph and Adjacency Matrix.

Keywords: association rules, data mining, dynamic item set counting, FP-growth, friendly algorithm, graph

Procedia PDF Downloads 389
1852 Standard Languages for Creating a Database to Display Financial Statements on a Web Application

Authors: Vladimir Simovic, Matija Varga, Predrag Oreski

Abstract:

XHTML and XBRL are the standard languages for creating a database for the purpose of displaying financial statements on web applications. Today, XBRL is one of the most popular languages for business reporting. A large number of countries in the world recognize the role of XBRL language for financial reporting and the benefits that the reporting format provides in the collection, analysis, preparation, publication and the exchange of data (information) which is the positive side of this language. Here we present all advantages and opportunities that a company may have by using the XBRL format for business reporting. Also, this paper presents XBRL and other languages that are used for creating the database, such XML, XHTML, etc. The role of the AJAX complex model and technology will be explained in detail, and during the exchange of financial data between the web client and web server. Here will be mentioned basic layers of the network for data exchange via the web.

Keywords: XHTML, XBRL, XML, JavaScript, AJAX technology, data exchange

Procedia PDF Downloads 369
1851 Morphological Features Fusion for Identifying INBREAST-Database Masses Using Neural Networks and Support Vector Machines

Authors: Nadia el Atlas, Mohammed el Aroussi, Mohammed Wahbi

Abstract:

In this paper a novel technique of mass characterization based on robust features-fusion is presented. The proposed method consists of mainly four stages: (a) the first phase involves segmenting the masses using edge information’s. (b) The second phase is to calculate and fuse the most relevant morphological features. (c) The last phase is the classification step which allows us to classify the images into benign and malignant masses. In this step we have implemented Support Vectors Machines (SVM) and Artificial Neural Networks (ANN), which were evaluated with the following performance criteria: confusion matrix, accuracy, sensitivity, specificity, receiver operating characteristic ROC, and error histogram. The effectiveness of this new approach was evaluated by a recently developed database: INBREAST database. The fusion of the most appropriate morphological features provided very good results. The SVM gives accuracy to within 64.3%. Whereas the ANN classifier gives better results with an accuracy of 97.5%.

Keywords: breast cancer, mammography, CAD system, features, fusion

Procedia PDF Downloads 566
1850 Using Priority Order of Basic Features for Circumscribed Masses Detection in Mammograms

Authors: Minh Dong Le, Viet Dung Nguyen, Do Huu Viet, Nguyen Huu Tu

Abstract:

In this paper, we present a new method for circumscribed masses detection in mammograms. Our method is evaluated on 23 mammographic images of circumscribed masses and 20 normal mammograms from public Mini-MIAS database. The method is quite sanguine with sensitivity (SE) of 95% with only about 1 false positive per image (FPpI). To achieve above results we carry out a progression following: Firstly, the input images are preprocessed with the aim to enhance key information of circumscribed masses; Next, we calculate and evaluate statistically basic features of abnormal regions on training database; Then, mammograms on testing database are divided into equal blocks which calculated corresponding features. Finally, using priority order of basic features to classify blocks as an abnormal or normal regions.

Keywords: mammograms, circumscribed masses, evaluated statistically, priority order of basic features

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1849 3D-Vehicle Associated Research Fields for Smart City via Semantic Search Approach

Authors: Haluk Eren, Mucahit Karaduman

Abstract:

This paper presents 15-year trends for scientific studies in a scientific database considering 3D and vehicle words. Two words are selected to find their associated publications in IEEE scholar database. Both of keywords are entered individually for the years 2002, 2012, and 2016 on the database to identify the preferred subjects of researchers in same years. We have classified closer research fields after searching and listing. Three years (2002, 2012, and 2016) have been investigated to figure out progress in specified time intervals. The first one is assumed as the initial progress in between 2002-2012, and the second one is in 2012-2016 that is fast development duration. We have found very interesting and beneficial results to understand the scholars’ research field preferences for a decade. This information will be highly desirable in smart city-based research purposes consisting of 3D and vehicle-related issues.

Keywords: Vehicle, three-dimensional, smart city, scholarly search, semantic

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1848 A Dynamic Solution Approach for Heart Disease Prediction

Authors: Walid Moudani

Abstract:

The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

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1847 An Improved Multiple Scattering Reflectance Model Based on Specular V-Cavity

Authors: Hongbin Yang, Mingxue Liao, Changwen Zheng, Mengyao Kong, Chaohui Liu

Abstract:

Microfacet-based reflection models are widely used to model light reflections for rough surfaces. Microfacet models have become the standard surface material building block for describing specular components with varying roughness; and yet, while they possess many desirable properties as well as produce convincing results, their design ignores important sources of scattering, which can cause a significant loss of energy. Specifically, they only simulate the single scattering on the microfacets and ignore the subsequent interactions. As the roughness increases, the interaction will become more and more important. So a multiple-scattering microfacet model based on specular V-cavity is presented for this important open problem. However, it spends much unnecessary rendering time because of setting the same number of scatterings for different roughness surfaces. In this paper, we design a geometric attenuation term G to compute the BRDF (Bidirectional reflection distribution function) of multiple scattering of rough surfaces. Moreover, we consider determining the number of scattering by deterministic heuristics for different roughness surfaces. As a result, our model produces a similar appearance of the objects with the state of the art model with significantly improved rendering efficiency. Finally, we derive a multiple scattering BRDF based on the original microfacet framework.

Keywords: bidirectional reflection distribution function, BRDF, geometric attenuation term, multiple scattering, V-cavity model

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1846 Utilising an Online Data Collection Platform for the Development of a Community Engagement Database: A Case Study on Building Inter-Institutional Partnerships at UWC

Authors: P. Daniels, T. Adonis, P. September-Brown, R. Comalie

Abstract:

The community engagement unit at the University of the Western Cape was tasked with establishing a community engagement database. The database would store information of all community engagement projects related to the university. The wealth of knowledge obtained from the various disciplines would be used to facilitate interdisciplinary collaboration within the university, as well as facilitating community university partnership opportunities. The purpose of this qualitative study was to explore electronic data collection through the development of a database. Two types of electronic data collection platforms were used, namely online questionnaire and email. The semi structured questionnaire was used to collect data related to community engagement projects from different faculties and departments at the university. There are many benefits for using an electronic data collection platform, such as reduction of costs and time, ease in reaching large numbers of potential respondents, and the possibility of providing anonymity to participants. Despite all the advantages of using the electronic platform, there were as many challenges, as depicted in our findings. The findings suggest that certain barriers existed by using an electronic platform for data collection, even though it was in an academic environment, where knowledge and resources were in abundance. One of the challenges experienced in this process was the lack of dissemination of information via email to staff within faculties. The actual online software used for the questionnaire had its own limitations, such as only being able to access the questionnaire from the same electronic device. In a few cases, academics only completed the questionnaire after a telephonic prompt or face to face meeting about "Is higher education in South Africa ready to embrace electronic platform in data collection?"

Keywords: community engagement, database, data collection, electronic platform, electronic tools, knowledge sharing, university

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1845 Optimizing Availability of Marine Knowledge Repository with Cloud-Based Framework

Authors: Ahmad S. Mohd Noor, Emma A. Sirajudin, Nur F. Mat Zain

Abstract:

Reliability is an important property for knowledge repository system. National Marine Bioinformatics System or NABTICS is a marine knowledge repository portal aimed to provide a baseline for marine biodiversity and a tool for researchers and developers. It is intended to be a large and growing online database and also a metadata system for inputs of research analysis. The trends of present large distributed systems such as Cloud computing are the delivery of computing as a service rather than a product. The goal of this research is to make NABTICS a system of greater availability by integrating it with Cloud based Neighbor Replication and Failure Recovery (NRFR). This can be achieved by implementation of NABTICS into distributed environment. As a result, the user can experience minimum downtime while using the system should the server is having a failure. Consequently the online database application is said to be highly available.

Keywords: cloud, availability, distributed system, marine repository, database replication

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1844 Designing a Model for Preparing Reports on the Automatic Earned Value Management Progress by the Integration of Primavera P6, SQL Database, and Power BI: A Case Study of a Six-Storey Concrete Building in Mashhad, Iran

Authors: Hamed Zolfaghari, Mojtaba Kord

Abstract:

Project planners and controllers are frequently faced with the challenge of inadequate software for the preparation of automatic project progress reports based on actual project information updates. They usually make dashboards in Microsoft Excel, which is local and not applicable online. Another shortcoming is that it is not linked to planning software such as Microsoft Project, which lacks the database required for data storage. This study aimed to propose a model for the preparation of reports on automatic online project progress based on actual project information updates by the integration of Primavera P6, SQL database, and Power BI for a construction project. The designed model could be applicable to project planners and controller agents by enabling them to prepare project reports automatically and immediately after updating the project schedule using actual information. To develop the model, the data were entered into P6, and the information was stored on the SQL database. The proposed model could prepare a wide range of reports, such as earned value management, HR reports, and financial, physical, and risk reports automatically on the Power BI application. Furthermore, the reports could be published and shared online.

Keywords: primavera P6, SQL, Power BI, EVM, integration management

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1843 Experiencing the Shattered: Managing Countertransference Experiences with Anorexia Patients in Psychotherapy

Authors: M. Card

Abstract:

Working with anorexia patients can be a challenging experience for mental and health care professionals. The reasons for not wanting to work with this patient population stems from the numerous concerns surrounding the patient’s health – physically and mentally. Many health care professionals reported having strong negative feelings, such as; anger, hopelessness and helplessness when working with anorexia patients. These feelings often impaired their judgement to treatment and affected how they related to the patient. This research focused on psychotherapists who preferred to work with anorexia patients; what countertransference feelings were evoked in them during sessions with patients and most importantly, how they managed the feelings. The research used interpretative phenomenological analysis (IPA) as the theoretical framework and data analysis method. Semi-structured interviews were used with ten experienced psychotherapists to obtain their countertransference experiences with anorexia patients and how they manage it. There were three main themes discovered; (1) the use of supervision, (2) their own personal therapy and finally (3) experience and evolution. The research unearthed that experienced psychotherapists also experienced strong countertransference feelings towards their patients; some positive and some negative. However, these feelings could actually be interpreted as co-transference with their anorexia patients. The psychotherapists were able to own their part in the evocative unconscious nature of a relational therapeutic space, where their personal issues may be entangled in their anorexia patient’s symptomatology.

Keywords: anorexia nervosa, countertransference, co-transference, psychotherapy, relational psychotherapy

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1842 New Approach for Constructing a Secure Biometric Database

Authors: A. Kebbeb, M. Mostefai, F. Benmerzoug, Y. Chahir

Abstract:

The multimodal biometric identification is the combination of several biometric systems. The challenge of this combination is to reduce some limitations of systems based on a single modality while significantly improving performance. In this paper, we propose a new approach to the construction and the protection of a multimodal biometric database dedicated to an identification system. We use a topological watermarking to hide the relation between face image and the registered descriptors extracted from other modalities of the same person for more secure user identification.

Keywords: biometric databases, multimodal biometrics, security authentication, digital watermarking

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1841 Predictive Analysis of Personnel Relationship in Graph Database

Authors: Kay Thi Yar, Khin Mar Lar Tun

Abstract:

Nowadays, social networks are so popular and widely used in all over the world. In addition, searching personal information of each person and searching connection between them (peoples’ relation in real world) becomes interesting issue in our society. In this paper, we propose a framework with three portions for exploring peoples’ relations from their connected information. The first portion focuses on the Graph database structure to store the connected data of peoples’ information. The second one proposes the graph database searching algorithm, the Modified-SoS-ACO (Sense of Smell-Ant Colony Optimization). The last portion proposes the Deductive Reasoning Algorithm to define two persons’ relationship. This study reveals the proper storage structure for connected information, graph searching algorithm and deductive reasoning algorithm to predict and analyze the personnel relationship from peoples’ relation in their connected information.

Keywords: personnel information, graph storage structure, graph searching algorithm, deductive reasoning algorithm

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1840 Loving is Universal, Dating is not: Dating Experiences of International Students in Vancouver

Authors: Nel Jayson Santos

Abstract:

The growing number of international students in post-secondary institutions in Canada has positively contributed to the country’s economy and educational systems while also enriching cultural diversity in the classrooms. However, international students face social and relational challenges as they try to adapt to their host nation’s culture. One specific area of cultural adaptation among international students that has yet to be studied extensively is dating experiences and romantic relationships. Although numerous studies have been done regarding the relational challenges and dating experiences of American international students, only a few studies have focused on international students based in Canada. Hence, this study examines the dating preferences, dating challenges, and dating adaptations of international students based in Vancouver, Canada. Using a social constructivist approach, a semi-structured interview was conducted among fifteen heterosexual international college students. Inductive thematic analysis was then used to analyze the gathered data and identify common themes. Findings suggest that students’ (1) preferences were influenced by racial background and parental approval of dating partners; (2) students experienced language barriers and cultural differences; (3) students adapted through constant communication and being open-minded. Finally, the analysis intends to help counselors and psychologists in various colleges to help understand the issues of international students in terms of intimate and romantic relationships.

Keywords: higher education, international students, dating experiences, cultural adaptation

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1839 Refitting Equations for Peak Ground Acceleration in Light of the PF-L Database

Authors: Matevž Breška, Iztok Peruš, Vlado Stankovski

Abstract:

Systematic overview of existing Ground Motion Prediction Equations (GMPEs) has been published by Douglas. The number of earthquake recordings that have been used for fitting these equations has increased in the past decades. The current PF-L database contains 3550 recordings. Since the GMPEs frequently model the peak ground acceleration (PGA) the goal of the present study was to refit a selection of 44 of the existing equation models for PGA in light of the latest data. The algorithm Levenberg-Marquardt was used for fitting the coefficients of the equations and the results are evaluated both quantitatively by presenting the root mean squared error (RMSE) and qualitatively by drawing graphs of the five best fitted equations. The RMSE was found to be as low as 0.08 for the best equation models. The newly estimated coefficients vary from the values published in the original works.

Keywords: Ground Motion Prediction Equations, Levenberg-Marquardt algorithm, refitting PF-L database, peak ground acceleration

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1838 Application Water Quality Modelling In Total Maximum Daily Load (TMDL) Management: A Review

Authors: S. A. Che Osmi, W. M. F. W. Ishak, S. F. Che Osmi

Abstract:

Nowadays the issues of water quality and water pollution have been a major problem across the country. A lot of management attempt to develop their own TMDL database in order to control the river pollution. Over the past decade, the mathematical modeling has been used as the tool for the development of TMDL. This paper presents the application of water quality modeling to develop the total maximum daily load (TMDL) information. To obtain the reliable database of TMDL, the appropriate water quality modeling should choose based on the available data provided. This paper will discuss on the use of several water quality modeling such as QUAL2E, QUAL2K, and EFDC to develop TMDL. The attempts to integrate several modeling are also being discussed in this paper. Based on this paper, the differences in the application of water quality modeling based on their properties such as one, two or three dimensional are showing their ability to develop the modeling of TMDL database.

Keywords: TMDL, water quality modeling, QUAL2E, EFDC

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1837 The Ultimate Challenge of Teaching Nursing

Authors: Crin N. Marcean, Mihaela A. Alexandru, Eugenia S. Cristescu

Abstract:

By definition, nursing means caring. It is a profession within the health care sector focused on the care of individuals, families, and communities so they may attain, maintain or recover optimal health and quality of life. However, there is a subtle difference between the two: nursing is widely considered as an art and a science, wherein caring forms the theoretical framework of nursing. Nursing and caring are grounded in a relational understanding, unity, and connection between the professional nurse and the patient. Task-oriented approaches challenge nurses in keeping care in nursing. This challenge is on-going as professional nurses strive to maintain the concept, art, and act of caring as the moral centre of the nursing profession. Keeping the care in nursing involves the application of art and science through theoretical concepts, scientific research, conscious commitment to the art of caring as an identity of nursing, and purposeful efforts to include caring behaviours during each nurse-patient interaction. The competencies, abilities, as well as the psycho-motor, cognitive, and relational skills necessary for the nursing practice are conveyed and improved by the nursing teachers’ art of teaching. They must select and use the teaching methods which shape the personalities of the trainers or students, enabling them to provide individualized, personalized care in real-world context of health problems. They have the ultimate responsibility of shaping the future health care system by educating skilful nurses.

Keywords: art of nursing, health care, teacher-student relationship, teaching innovations

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1836 Agile Methodology for Modeling and Design of Data Warehouses -AM4DW-

Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

Abstract:

The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse

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1835 Modelling of Geotechnical Data Using Geographic Information System and MATLAB for Eastern Ahmedabad City, Gujarat

Authors: Rahul Patel

Abstract:

Ahmedabad, a city located in western India, is experiencing rapid growth due to urbanization and industrialization. It is projected to become a metropolitan city in the near future, resulting in various construction activities. Soil testing is necessary before construction can commence, requiring construction companies and contractors to periodically conduct soil testing. The focus of this study is on the process of creating a spatial database that is digitally formatted and integrated with geotechnical data and a Geographic Information System (GIS). Building a comprehensive geotechnical (Geo)-database involves three steps: collecting borehole data from reputable sources, verifying the accuracy and redundancy of the data, and standardizing and organizing the geotechnical information for integration into the database. Once the database is complete, it is integrated with GIS, allowing users to visualize, analyze, and interpret geotechnical information spatially. Using a Topographic to Raster interpolation process in GIS, estimated values are assigned to all locations based on sampled geotechnical data values. The study area was contoured for SPT N-Values, Soil Classification, Φ-Values, and Bearing Capacity (T/m2). Various interpolation techniques were cross-validated to ensure information accuracy. This GIS map enables the calculation of SPT N-Values, Φ-Values, and bearing capacities for different footing widths and various depths. This study highlights the potential of GIS in providing an efficient solution to complex phenomena that would otherwise be tedious to achieve through other means. Not only does GIS offer greater accuracy, but it also generates valuable information that can be used as input for correlation analysis. Furthermore, this system serves as a decision support tool for geotechnical engineers.

Keywords: ArcGIS, borehole data, geographic information system, geo-database, interpolation, SPT N-value, soil classification, Φ-Value, bearing capacity

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1834 Developing a Town Based Soil Database to Assess the Sensitive Zones in Nutrient Management

Authors: Sefa Aksu, Ünal Kızıl

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For this study, a town based soil database created in Gümüşçay District of Biga Town, Çanakkale, Turkey. Crop and livestock production are major activities in the district. Nutrient management is mainly based on commercial fertilizer application ignoring the livestock manure. Within the boundaries of district, 122 soil sampling points determined over the satellite image. Soil samples collected from the determined points with the help of handheld Global Positioning System. Labeled samples were sent to a commercial laboratory to determine 11 soil parameters including salinity, pH, lime, organic matter, nitrogen, phosphorus, potassium, iron, manganese, copper and zinc. Based on the test results soil maps for mentioned parameters were developed using remote sensing, GIS, and geostatistical analysis. In this study we developed a GIS database that will be used for soil nutrient management. Methods were explained and soil maps and their interpretations were summarized in the study.

Keywords: geostatistics, GIS, nutrient management, soil mapping

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1833 Asymptotic Analysis of the Viscous Flow through a Pipe and the Derivation of the Darcy-Weisbach Law

Authors: Eduard Marusic-Paloka

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The Darcy-Weisbach formula is used to compute the pressure drop of the fluid in the pipe, due to the friction against the wall. Because of its simplicity, the Darcy-Weisbach formula became widely accepted by engineers and is used for laminar as well as the turbulent flows through pipes, once the method to compute the mysterious friction coefficient was derived. Particularly in the second half of the 20th century. Formula is empiric, and our goal is to derive it from the basic conservation law, via rigorous asymptotic analysis. We consider the case of the laminar flow but with significant Reynolds number. In case of the perfectly smooth pipe, the situation is trivial, as the Navier-Stokes system can be solved explicitly via the Poiseuille formula leading to the friction coefficient in the form 64/Re. For the rough pipe, the situation is more complicated and some effects of the roughness appear in the friction coefficient. We start from the Navier-Stokes system in the pipe with periodically corrugated wall and derive an asymptotic expansion for the pressure and for the velocity. We use the homogenization techniques and the boundary layer analysis. The approximation derived by formal analysis is then justified by rigorous error estimate in the norm of the appropriate Sobolev space, using the energy formulation and classical a priori estimates for the Navier-Stokes system. Our method leads to the formula for the friction coefficient. The formula involves resolution of the appropriate boundary layer problems, namely the boundary value problems for the Stokes system in an infinite band, that needs to be done numerically. However, theoretical analysis characterising their nature can be done without solving them.

Keywords: Darcy-Weisbach law, pipe flow, rough boundary, Navier law

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1832 Gender Perspective in Peace Operations: An Analysis of 14 UN Peace Operations

Authors: Maressa Aires de Proenca

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The inclusion of a gender perspective in peace operations is based on a series of conventions, treaties, and resolutions designed to protect and include women addressing gender mainstreaming. The UN Security Council recognizes that women's participation and gender equality within peace operations are indispensable for achieving sustainable development and peace. However, the participation of women in the field of peace and security is still embryonic. There are gaps when we think about female participation in conflict resolution and peace promotion spaces, and it does not seem clear how women are present in these spaces. This absence may correspond to silence about representation and the guarantee of the female perspective within the context of peace promotion. Thus, the present research aimed to describe the panorama of the participation of women who are currently active in the 14 active UN peace operations, which are: 1) MINUJUSTH, Haiti, 2) MINURSO, Western Sahara, 3) MINUSCA, Central African Republic, 4) MINUSMA, Mali, 5) MONUSCO, the Democratic Republic of the Congo, 6) UNAMID, Darfur, 7) UNDOF, Golan, 8) UNFICYP, Cyprus, 9) UNIFIL, Lebanon, 10) UNISFA, Abyei, 11) UNMIK, Kosovo, 12) UNMISS, South Sudan, 13) UNMOGIP, India, and Pakistan, and 14) UNTSO, Middle East. A database was constructed that reported: (1) position held by the woman in the peace operation, (2) her profession, (3) educational level, (4) marital status, (5) religion, (6) nationality, (8) number of years working with peace operations, (9) whether the operation in which it operates has provided training on gender issues. For the construction of this database, official reports and statistics accessed through the UN Peacekeeping Resource Hub were used; The United Nations Statistical Commission, Peacekeeping Master Open Datasets, The Armed Conflict Database (ACD), The International Institute for Strategic Studies (IISS) database; Armed Conflict Location & Event Data Project (ACLED) database; from the Evidence and Data for Gender Equality (EDGE) database. In addition to access to databases, peacekeeping operations will be contacted directly, and data requested individually. The database showed that the presence of women in these peace operations is still incipient, but growing. There are few women in command positions, and most of them occupy administrative or human-care positions.

Keywords: women, peace and security, peacekeeping operations, peace studies

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1831 Alphabet Recognition Using Pixel Probability Distribution

Authors: Vaidehi Murarka, Sneha Mehta, Dishant Upadhyay

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Our project topic is “Alphabet Recognition using pixel probability distribution”. The project uses techniques of Image Processing and Machine Learning in Computer Vision. Alphabet recognition is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files etc. Alphabet Recognition based OCR application is sometimes used in signature recognition which is used in bank and other high security buildings. One of the popular mobile applications includes reading a visiting card and directly storing it to the contacts. OCR's are known to be used in radar systems for reading speeders license plates and lots of other things. The implementation of our project has been done using Visual Studio and Open CV (Open Source Computer Vision). Our algorithm is based on Neural Networks (machine learning). The project was implemented in three modules: (1) Training: This module aims “Database Generation”. Database was generated using two methods: (a) Run-time generation included database generation at compilation time using inbuilt fonts of OpenCV library. Human intervention is not necessary for generating this database. (b) Contour–detection: ‘jpeg’ template containing different fonts of an alphabet is converted to the weighted matrix using specialized functions (contour detection and blob detection) of OpenCV. The main advantage of this type of database generation is that the algorithm becomes self-learning and the final database requires little memory to be stored (119kb precisely). (2) Preprocessing: Input image is pre-processed using image processing concepts such as adaptive thresholding, binarizing, dilating etc. and is made ready for segmentation. “Segmentation” includes extraction of lines, words, and letters from the processed text image. (3) Testing and prediction: The extracted letters are classified and predicted using the neural networks algorithm. The algorithm recognizes an alphabet based on certain mathematical parameters calculated using the database and weight matrix of the segmented image.

Keywords: contour-detection, neural networks, pre-processing, recognition coefficient, runtime-template generation, segmentation, weight matrix

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1830 Parallel Fuzzy Rough Support Vector Machine for Data Classification in Cloud Environment

Authors: Arindam Chaudhuri

Abstract:

Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

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1829 Development of a Data-Driven Method for Diagnosing the State of Health of Battery Cells, Based on the Use of an Electrochemical Aging Model, with a View to Their Use in Second Life

Authors: Desplanches Maxime

Abstract:

Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

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1828 Gis Database Creation for Impacts of Domestic Wastewater Disposal on BIDA Town, Niger State Nigeria

Authors: Ejiobih Hyginus Chidozie

Abstract:

Geographic Information System (GIS) is a configuration of computer hardware and software specifically designed to effectively capture, store, update, manipulate, analyse and display and display all forms of spatially referenced information. GIS database is referred to as the heart of GIS. It has location data, attribute data and spatial relationship between the objects and their attributes. Sewage and wastewater management have assumed increased importance lately as a result of general concern expressed worldwide about the problems of pollution of the environment contamination of the atmosphere, rivers, lakes, oceans and ground water. In this research GIS database was created to study the impacts of domestic wastewater disposal methods on Bida town, Niger State as a model for investigating similar impacts on other cities in Nigeria. Results from GIS database are very useful to decision makers and researchers. Bida Town was subdivided into four regions, eight zones, and 24 sectors based on the prevailing natural morphology of the town. GIS receiver and structured questionnaire were used to collect information and attribute data from 240 households of the study area. Domestic wastewater samples were collected from twenty four sectors of the study area for laboratory analysis. ArcView 3.2a GIS software, was used to create the GIS databases for ecological, health and socioeconomic impacts of domestic wastewater disposal methods in Bida town.

Keywords: environment, GIS, pollution, software, wastewater

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1827 Ideological Stance in Political Discourse: A Transitivity Analysis of Nawaz Sharif's Address at 71st UN Assembly

Authors: A. Nawaz

Abstract:

The present study uses Halliday’s transitivity model to analyze and interpret ideological stance in PM Nawaz Sharif’s political discourse. His famous speech at the 71st UN assembly was analyzed qualitatively using clausal analysis approach to investigate the communicative functions of the linguistic choices made in the address. The study discovers that among the six process types under the transitivity model, material, relational and mental processes appear most frequently in the speech, making up almost 86% of the whole. Verbal processes rank 4th, whereas existential and behavioral are the least occurring processes covering only 2 and 1 percent respectively. The dominant use of material processes suggests that Nawaz Sharif and his government are the main actors working on several concrete projects to produce a sense of developmental progression and continuity. Using relational and mental processes the PM, along with establishing proximity with masses and especially Kashmiri, gives guarantees and promises. The linguistic analysis concludes Kashmir dispute as being the central theme of the address, since it covers more than half of the discourse. The address calls for a strong action instead of formal assurances and wishful thoughts. The study establishes that language structures can yield certain connotations and ideologies which are not overt for readers. This is in affirmation to the supposition that language form performs a communicative function and is not merely fortuitous.

Keywords: Hallidian perspective on language, implicit meanings, Nawaz Sharif, political ideologies, political speeches, transitivity, UN Assembly

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1826 Entrepreneurship and Innovation: The Essence of Sustainable, Smart and Inclusive Economies

Authors: Isabel Martins, Orlando Pereira, Ana Martins

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This study aims to highlight that, in changing environments, organisations need to adapt their behaviours to the demands of the new economic reality. The main purpose of this study focuses on the relationship between entrepreneurship, innovation with learning as the mediating factor. It is within this entrepreneurial spirit that literature reveals a concern with the current economic perspective towards knowledge and considers it as both the production factor par excellence and a source of entrepreneurial capacity and innovation. Entrepreneurship is a mind-set focused on identifying opportunities of economic value and translates these into the pursuit of business opportunities through innovation. It connects art and science and is a way of life, as opposed to a simple mode of business creation and profiteering. This perspective underlines the need to develop the global individual for the globalised world, the strategic key to economic and social development. The objective of this study is to explore the notion that relational capital which is established between the entrepreneur and all the other economic role players both inside and outside the organization, is indeed determinant in developing the entrepreneurial capacity. However, this depends on the organizational culture of innovation. In this context, entrepreneurship is an ‘entrepreneurial capital’ inherent in the organization that is not limited to skills needed for work. This study is a critique of extant literature review which will be also be supported by primary data collection gathered to study graduates’ perceptions towards their entrepreneurial capital. Limitations are centered on both the design and of the sample of this study. This study is of added value for both scholars and organisations in the current innovation economy.

Keywords: entrepreneurship, innovation, learning, relational capital

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1825 Local Texture and Global Color Descriptors for Content Based Image Retrieval

Authors: Tajinder Kaur, Anu Bala

Abstract:

An image retrieval system is a computer system for browsing, searching, and retrieving images from a large database of digital images a new algorithm meant for content-based image retrieval (CBIR) is presented in this paper. The proposed method combines the color and texture features which are extracted the global and local information of the image. The local texture feature is extracted by using local binary patterns (LBP), which are evaluated by taking into consideration of local difference between the center pixel and its neighbors. For the global color feature, the color histogram (CH) is used which is calculated by RGB (red, green, and blue) spaces separately. In this paper, the combination of color and texture features are proposed for content-based image retrieval. The performance of the proposed method is tested on Corel 1000 database which is the natural database. The results after being investigated show a significant improvement in terms of their evaluation measures as compared to LBP and CH.

Keywords: color, texture, feature extraction, local binary patterns, image retrieval

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