Dr.Reshmy Krishnan | Muscat College (original) (raw)
Papers by Dr.Reshmy Krishnan
The authors have requested that this preprint be removed from Research Square.
Advances in Science, Technology & Innovation, 2019
Students in middle east are having innovative skills in multimedia and Human Computer Interaction... more Students in middle east are having innovative skills in multimedia and Human Computer Interaction (HCI) and hence self-learning and critical thinking can be enhanced through the teaching of this subject through proper design of the course. To achieve cognitive learning objectives in students, revised bloom taxonomy can be embedded while designing the curriculum. Teaching activities should be aligned to achieve self-learning and critical thinking in students according to the revised bloom taxonomy. Through a Project Based Learning (PBL) method in multimedia and HCI course, the above cognitive learning objectives can be developed in classroom. In this paper the design and practice of a multimedia and HCI curriculum which is taught in Muscat College, Sultanate of Oman is described and demonstrates how cognitive skills are achieved through the embedding of revised bloom taxonomy. The design of the course took the students to the various concepts of graphics techniques and practicals give them the exposure towards realization of those techniques. The final project is developed through the integration of all these practical and tutorial experiences. The observation shows students have applied their creativity with revised bloom taxonomy to obtain the goal in a wonderful way.
Sustainability, 2022
In the current COVID-19 pandemic era, Learning Management Systems (LMS) are commonly used in e-le... more In the current COVID-19 pandemic era, Learning Management Systems (LMS) are commonly used in e-learning for various learning activities in Higher Education. Learning Analytics (LA) is an emerging area of LMS, which plays a vital role in tracking and storing learners’ activities in the online environment in Higher Education. LA treats the collections of students’ digital footprints and evaluates this data to improve teaching and learning quality. LA measures the analysis and reports learners’ data and their activities to predict decisions on every tier of the education system. This promising area, which both teachers and students can use during this pandemic outbreak, converges LA, Artificial Intelligence, and Human-Centered Design in data visualization techniques, semantic and educational data mining techniques, feature data extraction, etc. Different learning activities of learners for each course are analyzed with the help of LA plug-ins. The progression of learners can be monitor...
Smart Technologies and Innovation for a Sustainable Future, 2019
Learning style is one of the major factors of student performance in any learning environment. De... more Learning style is one of the major factors of student performance in any learning environment. Determining the learning style of students enhances the performance of learning process. This paper proposes an approach to classify students learning style automatically based on their learning behavior. One of the best widely used classifier algorithm is decision tree which is proposed in this paper. The main concern in decision tree classifier is the construction of significant rules which are required for accurately identifying learning styles. Lack of significant rules would result in misclassification of learning style. Hence, the main focus of this paper is to construct most significant rules which would strengthen the existing decision tree classifier to precisely and accurately detect the learning style of students. The student behavior is obtained from the web log files and then mapped with three learning dimensions of standard Felder Silverman learning style model. Subsequently, by employing significant rules in decision tree classifier, the student behavior has been automatically classified with high accuracy. This approach was experimented on 100 students for the online course created in Moodle Learning Management System. The evaluation result is obtained using inference engine with forward reasoning searches of the rules until the correct learning style is determined. The result is then analyzed with a confusion matrix of actual class and predicted class which shows that processing dimension shows variance whereas perception and input dimension were detected correctly with an average accuracy of 87%.
Keyword extraction is one of the most important themes in E-Learning environments. In this paper ... more Keyword extraction is one of the most important themes in E-Learning environments. In this paper a model which could improve the extraction of keywords from the frequently visited documents using WordNet are employed. First of all, learner’s words are selected using TFIDF algorithm. Then the related words are semantically represented using WordNet and then updated to the learner profile using semantic similarity using WordNet. The experiment shows the successful extraction and updating of learner interest to the learner profile. Keywords—E-Learning; Keyword extraction; WordNet
One of the goals of modern health care systems is to collect complete, accurate and correct patie... more One of the goals of modern health care systems is to collect complete, accurate and correct patient medical history. Simple patient history collection systems fail to collect relevant information from patients. This results in non-availability of full medical history of a patient at the time of doctor diagnosis. This leaves medical experts in a great challenge in order to make correct medical diagnosis. So in addition to the conventional face-to-face consultation, the process of collecting patient history needs automation, more precisely in an intelligent manner. We here propose a model for gathering the patient medical history based on dynamic questionnaire ontology. Ontology is among the most powerful tools to encode medical knowledge semantically. It is an abstract model which represents a common and shared understanding of a domain. The model is explained and implemented for diabetes domain.
The success of E-Learning system depends on the retrieval of relevant learning contents of learne... more The success of E-Learning system depends on the retrieval of relevant learning contents of learner. The best method to acquire learner needs is to construct an efficient learner profile which has to comply with the Semantic Web. Semantic Web relies heavily on formal ontologies to structure data.
Keyword extraction is one of the most important themes in E-Learning environments. In this paper ... more Keyword extraction is one of the most important themes in E-Learning environments. In this paper a model which could improve the extraction of keywords from the frequently visited documents using WordNet are employed. First of all, learner's words are selected using TFIDF algorithm. Then the related words are semantically represented using WordNet and then updated to the learner profile using semantic similarity using WordNet. The experiment shows the successful extraction and updating of learner interest to the learner profile.
Proceedings of the 2018 International Conference on Data Science and Information Technology - DSIT '18, 2018
Learning style is an important factor that accounts for the individual student learning in any le... more Learning style is an important factor that accounts for the individual student learning in any learning environment. Every student has a different learning style and different ways to percept, process, retain and understand new information. In this paper, a new approach is proposed to classify students learning style automatically and dynamically depending on their learning behavior in a learning management system (LMS). There have been several approaches proposed for automatic learning style detection. One of the widely accepted and frequently used classification techniques is the decision tree classifier. The decision tree classifier mainly depends on the construction of strong decision rules which are required to identify learning styles accurately. The lack of strong decision rules would lead to the misclassification of individual students learning style. Hence, this paper mainly focuses on the construction of strong decision rules to strengthen the existing decision tree classifier to accurately and precisely classify students learning style thereby improving the classification accuracy. The proposed approach has experimented with an average of 300 students enrolled for the online courses in Moodle LMS. Initially, the students' behavior are extracted from the web log files of LMS and then preprocessed to build decision tree classifier using strong decision rules based on the three learning dimensions of standard Felder Silverman learning style model (FSLSM). The evaluation result is obtained using the inference engine with forward reasoning searches of the rules until the correct learning style is determined. Based on the result obtained, the prediction of learning style is done for the new students automatically and accurately using the significant rules built in the decision tree classifier. The experimental result proved that the processing dimension shows variance in classification whereas perception and input dimension shows less variance with an average accuracy of 87%.
Today massive amount of information is stored on the Web and on large document repositories. Peop... more Today massive amount of information is stored on the Web and on large document repositories. People use search engines such as Yahoo, Google, MSN etc to find and share this information. But since search engines are limited to grasp the meanings of the user needs, sometimes it is difficult to get the exact information of search. Now the potential solution to this problem is to have a meaningful search. Ontologies were introduced as the conceptual framework of semantic search in late 90’s. They are the backbone of Semantic Web and they include the descriptions of classes, properties and their instances. Nowadays ontologies are being applied in a number of information retrieval systems to enhance the performance of such systems. In this paper we present seafood ontology to retrieve precise information about seafood. The different steps involved in the development process of the particular ontology are explained and classes, properties of classes and instances are described. Protege 4, ...
The vision of Semantic Web is to make web resources more accessible to automated resources. Here ... more The vision of Semantic Web is to make web resources more accessible to automated resources. Here the role of ontology is to provide vocabulary for metad ata description with computer-understandable semant ics. The main components of ontology are concepts, relat ions and individuals. The most common type of relation is binary relation that maps between a sin gle subject and a value. Sometimes there exist n-ar y relations in ontology. W3C provides several pattern s to represent n-ary relations. In this paper we di scuss the issues in n-ary relations, the concept of RDF r eification and provide an appropriate pattern to re present the n-ary relations. The examples of n-ary relation s are taken from Seafood Ontology we developed earl ier.
Foreword Z.Arat 1. The Relationship between Nationalism and Human Rights: An Introduction to the ... more Foreword Z.Arat 1. The Relationship between Nationalism and Human Rights: An Introduction to the Dimensions of the Debate G.Cheng 2. Human Rights as a Security Challenge: An Examination of Turkish Nationalist Discourse on Minority Rights Reformations B.?.Tekin 3. All in the Name of Human Rights: Australian Nationalism and Multiculturalism, 1980-1990 T.Whitford 4. Migrants at Home: The Impact of Israeli Land Policy and Patrilocal Residence on Palestinian Women in Israel L.Abou-Tabickh 5. National Rights, Minority Rights, and Ethnic Cleansing O.Dahbour 6. Cosmopolitan Citizenship as a Thin Concept: Who is Willing to Die for Humanity? F.Kartal 7. The Contradictions of Human Rights and Sovereignty: Contemporary Dilemmas of Postwar Historical Practice G.Cheng 8. Taming the Nation-State: Human Rights and Peoples M.Avila 9. Conclusion: Nationalism versus Human Rights F.Turkmen
In any health care system, the patient medical history is crucial to help the doctors for further... more In any health care system, the patient medical history is crucial to help the doctors for further patient diagnosis. History of the patient is collected mainly through face-to-face interaction when the patient visits the hospital. If the medical staff is not well experienced, it results in failure of collecting the patient history. So in most of the cases, effective patient risk analysis cannot be done. This paper proposes an ontology based system to collect the patient history and to assess the patient risk factorsdue to smoking history, alcohol history, erectile dysfunction history, and cardiovascular history. According to the patient history, a total score is calculated for each of the above factors. According to the score, the ontology performs the risk assessment on a patient profile and predicts the potential risks and complications of the patient.Ontology is among the most powerful tools to encode medical knowledge semantically.
Information and Communication Technology for Competitive Strategies (ICTCS 2020), 2021
Advances in Intelligent Systems and Computing, 2020
The learners’ interest forms the essential characteristics of the learner profile in various appl... more The learners’ interest forms the essential characteristics of the learner profile in various applications, such as information retrieval, classification, and recommender systems. This paper proposes a method to improve learner interest extraction from the frequently used documents of the learner by exploring the concept of WordNet. Initially, the web log files of each learner are obtained from the learning management system, and then the frequently visited documents of each learner are downloaded and processed to identify domain-related words. The learner’s interest is then extracted initially using the standard vector space model and then improved using the semantic-based representation of WordNet. The WordNet identifies a set of semantic concepts related to the document words. To select the appropriate meaning of a word from a set of concepts, “Word Sense Disambiguation (WSD)” semantic similarity algorithm is used. The experiments were performed in NetBeans IDE using Java language and WordNet 2.1. The effect of the proposed method is examined with classification experiments, and the result proved that the use of WordNet concepts in learner interest retrieval shows better classification performance than compared to the existing method of term representation, thereby obtaining a classification accuracy of 89%.
Fourth Industrial Revolution and Business Dynamics, 2021
Seventh International Conference On Advances in Computing, Electronics and Electrical Technology - CEET 2017, Jul 2, 2017
Basic requirements to process historic data are finding, collecting, structuring and retrieving. ... more Basic requirements to process historic data are finding, collecting, structuring and retrieving. Key challenges facing by historians during transformation are heterogeneous data format, data exchange, cross platform, multiple languages etc. Conversion between source and recipient database is also a difficulty. During the transformation, data sharing and data security are the key concerns faced by historians. Data exchange, compatibility, extendibility and reuse of data becomes progressively important while collecting and processing data. Here combination of Java with XML is checked to resolve above concerns. How the features of Java and XML can be supportive for data sharing, data extension and cross platform issues are being discussed here. These paper insights into the historians everyday practices to manage constraints and concerns in the areas of data access, collection, sharing and security. This paper reveals how the usability of XML and Java can reduce the challenges and enhance data sharing and data security.
International Journal of Business Management and Economic Review, 2020
This study is to test The Effect of Knowledge Sharing and Motivation on Individual Competency and... more This study is to test The Effect of Knowledge Sharing and Motivation on Individual Competency and Employee Performance. The object of this research is at PT Bank Negara Indonesia (Persero) TbkLhokseumawe Branch and its all employees are the respondents. The population is 150 people. the sample also amounted to 150 respondents that is taken by census method, which is the number of sample is as same as population. The data is analyzed using structural equation modeling (SEM) analysis with the AMOS software. The test is in the form of causality test. The result describes that knowledge sharing effects employee performance significantly, motivation effects employee performance significantly, knowledge sharing effects individual competence significantly, motivation effects individual competence significantly, individual competence effects employee performance significantly, knowledge sharing has an indirect effect on employee performance through the individual competence, and motivation has an indirect effect on employee performance through individual competence of employees of PT Bank Negara Indonesia (Persero) TbkLhokseumawe Branch. This model contributes to the realm of science that enrich the causality theories especially in management and social science field. This also can be a reference for the next research. The originality is in the integration of previous models, and uses SEM as a statistical approach. The limitation lies in the amount of variables and object. .
International Journal of Engineering and Advanced Technology, 2019
Education molds the future society. Student profile analysis in higher education system in sultan... more Education molds the future society. Student profile analysis in higher education system in sultanate of Oman reveals that drop out cases of students are tremendously increasing for the last few years. Learning environment plays a vital role in providing appropriate teaching methodologies to motivate the skills of the students. Variations in academic performance can be observed based on different educational indicators such as gender, social, economical, cultural and community characteristics. This paper tries to conduct an analysis on the existing data based on educational data mining and tries to make a classification based on gender which helps to adapt necessary teaching methodology to improve the student performance. A data set of 400 students from three colleges in Sultanate of Oman in three consecutive years is taken as case study for this analysis. Since student’s performance is classified as per the data model based on their gender, equal number of male and female data are c...
The authors have requested that this preprint be removed from Research Square.
Advances in Science, Technology & Innovation, 2019
Students in middle east are having innovative skills in multimedia and Human Computer Interaction... more Students in middle east are having innovative skills in multimedia and Human Computer Interaction (HCI) and hence self-learning and critical thinking can be enhanced through the teaching of this subject through proper design of the course. To achieve cognitive learning objectives in students, revised bloom taxonomy can be embedded while designing the curriculum. Teaching activities should be aligned to achieve self-learning and critical thinking in students according to the revised bloom taxonomy. Through a Project Based Learning (PBL) method in multimedia and HCI course, the above cognitive learning objectives can be developed in classroom. In this paper the design and practice of a multimedia and HCI curriculum which is taught in Muscat College, Sultanate of Oman is described and demonstrates how cognitive skills are achieved through the embedding of revised bloom taxonomy. The design of the course took the students to the various concepts of graphics techniques and practicals give them the exposure towards realization of those techniques. The final project is developed through the integration of all these practical and tutorial experiences. The observation shows students have applied their creativity with revised bloom taxonomy to obtain the goal in a wonderful way.
Sustainability, 2022
In the current COVID-19 pandemic era, Learning Management Systems (LMS) are commonly used in e-le... more In the current COVID-19 pandemic era, Learning Management Systems (LMS) are commonly used in e-learning for various learning activities in Higher Education. Learning Analytics (LA) is an emerging area of LMS, which plays a vital role in tracking and storing learners’ activities in the online environment in Higher Education. LA treats the collections of students’ digital footprints and evaluates this data to improve teaching and learning quality. LA measures the analysis and reports learners’ data and their activities to predict decisions on every tier of the education system. This promising area, which both teachers and students can use during this pandemic outbreak, converges LA, Artificial Intelligence, and Human-Centered Design in data visualization techniques, semantic and educational data mining techniques, feature data extraction, etc. Different learning activities of learners for each course are analyzed with the help of LA plug-ins. The progression of learners can be monitor...
Smart Technologies and Innovation for a Sustainable Future, 2019
Learning style is one of the major factors of student performance in any learning environment. De... more Learning style is one of the major factors of student performance in any learning environment. Determining the learning style of students enhances the performance of learning process. This paper proposes an approach to classify students learning style automatically based on their learning behavior. One of the best widely used classifier algorithm is decision tree which is proposed in this paper. The main concern in decision tree classifier is the construction of significant rules which are required for accurately identifying learning styles. Lack of significant rules would result in misclassification of learning style. Hence, the main focus of this paper is to construct most significant rules which would strengthen the existing decision tree classifier to precisely and accurately detect the learning style of students. The student behavior is obtained from the web log files and then mapped with three learning dimensions of standard Felder Silverman learning style model. Subsequently, by employing significant rules in decision tree classifier, the student behavior has been automatically classified with high accuracy. This approach was experimented on 100 students for the online course created in Moodle Learning Management System. The evaluation result is obtained using inference engine with forward reasoning searches of the rules until the correct learning style is determined. The result is then analyzed with a confusion matrix of actual class and predicted class which shows that processing dimension shows variance whereas perception and input dimension were detected correctly with an average accuracy of 87%.
Keyword extraction is one of the most important themes in E-Learning environments. In this paper ... more Keyword extraction is one of the most important themes in E-Learning environments. In this paper a model which could improve the extraction of keywords from the frequently visited documents using WordNet are employed. First of all, learner’s words are selected using TFIDF algorithm. Then the related words are semantically represented using WordNet and then updated to the learner profile using semantic similarity using WordNet. The experiment shows the successful extraction and updating of learner interest to the learner profile. Keywords—E-Learning; Keyword extraction; WordNet
One of the goals of modern health care systems is to collect complete, accurate and correct patie... more One of the goals of modern health care systems is to collect complete, accurate and correct patient medical history. Simple patient history collection systems fail to collect relevant information from patients. This results in non-availability of full medical history of a patient at the time of doctor diagnosis. This leaves medical experts in a great challenge in order to make correct medical diagnosis. So in addition to the conventional face-to-face consultation, the process of collecting patient history needs automation, more precisely in an intelligent manner. We here propose a model for gathering the patient medical history based on dynamic questionnaire ontology. Ontology is among the most powerful tools to encode medical knowledge semantically. It is an abstract model which represents a common and shared understanding of a domain. The model is explained and implemented for diabetes domain.
The success of E-Learning system depends on the retrieval of relevant learning contents of learne... more The success of E-Learning system depends on the retrieval of relevant learning contents of learner. The best method to acquire learner needs is to construct an efficient learner profile which has to comply with the Semantic Web. Semantic Web relies heavily on formal ontologies to structure data.
Keyword extraction is one of the most important themes in E-Learning environments. In this paper ... more Keyword extraction is one of the most important themes in E-Learning environments. In this paper a model which could improve the extraction of keywords from the frequently visited documents using WordNet are employed. First of all, learner's words are selected using TFIDF algorithm. Then the related words are semantically represented using WordNet and then updated to the learner profile using semantic similarity using WordNet. The experiment shows the successful extraction and updating of learner interest to the learner profile.
Proceedings of the 2018 International Conference on Data Science and Information Technology - DSIT '18, 2018
Learning style is an important factor that accounts for the individual student learning in any le... more Learning style is an important factor that accounts for the individual student learning in any learning environment. Every student has a different learning style and different ways to percept, process, retain and understand new information. In this paper, a new approach is proposed to classify students learning style automatically and dynamically depending on their learning behavior in a learning management system (LMS). There have been several approaches proposed for automatic learning style detection. One of the widely accepted and frequently used classification techniques is the decision tree classifier. The decision tree classifier mainly depends on the construction of strong decision rules which are required to identify learning styles accurately. The lack of strong decision rules would lead to the misclassification of individual students learning style. Hence, this paper mainly focuses on the construction of strong decision rules to strengthen the existing decision tree classifier to accurately and precisely classify students learning style thereby improving the classification accuracy. The proposed approach has experimented with an average of 300 students enrolled for the online courses in Moodle LMS. Initially, the students' behavior are extracted from the web log files of LMS and then preprocessed to build decision tree classifier using strong decision rules based on the three learning dimensions of standard Felder Silverman learning style model (FSLSM). The evaluation result is obtained using the inference engine with forward reasoning searches of the rules until the correct learning style is determined. Based on the result obtained, the prediction of learning style is done for the new students automatically and accurately using the significant rules built in the decision tree classifier. The experimental result proved that the processing dimension shows variance in classification whereas perception and input dimension shows less variance with an average accuracy of 87%.
Today massive amount of information is stored on the Web and on large document repositories. Peop... more Today massive amount of information is stored on the Web and on large document repositories. People use search engines such as Yahoo, Google, MSN etc to find and share this information. But since search engines are limited to grasp the meanings of the user needs, sometimes it is difficult to get the exact information of search. Now the potential solution to this problem is to have a meaningful search. Ontologies were introduced as the conceptual framework of semantic search in late 90’s. They are the backbone of Semantic Web and they include the descriptions of classes, properties and their instances. Nowadays ontologies are being applied in a number of information retrieval systems to enhance the performance of such systems. In this paper we present seafood ontology to retrieve precise information about seafood. The different steps involved in the development process of the particular ontology are explained and classes, properties of classes and instances are described. Protege 4, ...
The vision of Semantic Web is to make web resources more accessible to automated resources. Here ... more The vision of Semantic Web is to make web resources more accessible to automated resources. Here the role of ontology is to provide vocabulary for metad ata description with computer-understandable semant ics. The main components of ontology are concepts, relat ions and individuals. The most common type of relation is binary relation that maps between a sin gle subject and a value. Sometimes there exist n-ar y relations in ontology. W3C provides several pattern s to represent n-ary relations. In this paper we di scuss the issues in n-ary relations, the concept of RDF r eification and provide an appropriate pattern to re present the n-ary relations. The examples of n-ary relation s are taken from Seafood Ontology we developed earl ier.
Foreword Z.Arat 1. The Relationship between Nationalism and Human Rights: An Introduction to the ... more Foreword Z.Arat 1. The Relationship between Nationalism and Human Rights: An Introduction to the Dimensions of the Debate G.Cheng 2. Human Rights as a Security Challenge: An Examination of Turkish Nationalist Discourse on Minority Rights Reformations B.?.Tekin 3. All in the Name of Human Rights: Australian Nationalism and Multiculturalism, 1980-1990 T.Whitford 4. Migrants at Home: The Impact of Israeli Land Policy and Patrilocal Residence on Palestinian Women in Israel L.Abou-Tabickh 5. National Rights, Minority Rights, and Ethnic Cleansing O.Dahbour 6. Cosmopolitan Citizenship as a Thin Concept: Who is Willing to Die for Humanity? F.Kartal 7. The Contradictions of Human Rights and Sovereignty: Contemporary Dilemmas of Postwar Historical Practice G.Cheng 8. Taming the Nation-State: Human Rights and Peoples M.Avila 9. Conclusion: Nationalism versus Human Rights F.Turkmen
In any health care system, the patient medical history is crucial to help the doctors for further... more In any health care system, the patient medical history is crucial to help the doctors for further patient diagnosis. History of the patient is collected mainly through face-to-face interaction when the patient visits the hospital. If the medical staff is not well experienced, it results in failure of collecting the patient history. So in most of the cases, effective patient risk analysis cannot be done. This paper proposes an ontology based system to collect the patient history and to assess the patient risk factorsdue to smoking history, alcohol history, erectile dysfunction history, and cardiovascular history. According to the patient history, a total score is calculated for each of the above factors. According to the score, the ontology performs the risk assessment on a patient profile and predicts the potential risks and complications of the patient.Ontology is among the most powerful tools to encode medical knowledge semantically.
Information and Communication Technology for Competitive Strategies (ICTCS 2020), 2021
Advances in Intelligent Systems and Computing, 2020
The learners’ interest forms the essential characteristics of the learner profile in various appl... more The learners’ interest forms the essential characteristics of the learner profile in various applications, such as information retrieval, classification, and recommender systems. This paper proposes a method to improve learner interest extraction from the frequently used documents of the learner by exploring the concept of WordNet. Initially, the web log files of each learner are obtained from the learning management system, and then the frequently visited documents of each learner are downloaded and processed to identify domain-related words. The learner’s interest is then extracted initially using the standard vector space model and then improved using the semantic-based representation of WordNet. The WordNet identifies a set of semantic concepts related to the document words. To select the appropriate meaning of a word from a set of concepts, “Word Sense Disambiguation (WSD)” semantic similarity algorithm is used. The experiments were performed in NetBeans IDE using Java language and WordNet 2.1. The effect of the proposed method is examined with classification experiments, and the result proved that the use of WordNet concepts in learner interest retrieval shows better classification performance than compared to the existing method of term representation, thereby obtaining a classification accuracy of 89%.
Fourth Industrial Revolution and Business Dynamics, 2021
Seventh International Conference On Advances in Computing, Electronics and Electrical Technology - CEET 2017, Jul 2, 2017
Basic requirements to process historic data are finding, collecting, structuring and retrieving. ... more Basic requirements to process historic data are finding, collecting, structuring and retrieving. Key challenges facing by historians during transformation are heterogeneous data format, data exchange, cross platform, multiple languages etc. Conversion between source and recipient database is also a difficulty. During the transformation, data sharing and data security are the key concerns faced by historians. Data exchange, compatibility, extendibility and reuse of data becomes progressively important while collecting and processing data. Here combination of Java with XML is checked to resolve above concerns. How the features of Java and XML can be supportive for data sharing, data extension and cross platform issues are being discussed here. These paper insights into the historians everyday practices to manage constraints and concerns in the areas of data access, collection, sharing and security. This paper reveals how the usability of XML and Java can reduce the challenges and enhance data sharing and data security.
International Journal of Business Management and Economic Review, 2020
This study is to test The Effect of Knowledge Sharing and Motivation on Individual Competency and... more This study is to test The Effect of Knowledge Sharing and Motivation on Individual Competency and Employee Performance. The object of this research is at PT Bank Negara Indonesia (Persero) TbkLhokseumawe Branch and its all employees are the respondents. The population is 150 people. the sample also amounted to 150 respondents that is taken by census method, which is the number of sample is as same as population. The data is analyzed using structural equation modeling (SEM) analysis with the AMOS software. The test is in the form of causality test. The result describes that knowledge sharing effects employee performance significantly, motivation effects employee performance significantly, knowledge sharing effects individual competence significantly, motivation effects individual competence significantly, individual competence effects employee performance significantly, knowledge sharing has an indirect effect on employee performance through the individual competence, and motivation has an indirect effect on employee performance through individual competence of employees of PT Bank Negara Indonesia (Persero) TbkLhokseumawe Branch. This model contributes to the realm of science that enrich the causality theories especially in management and social science field. This also can be a reference for the next research. The originality is in the integration of previous models, and uses SEM as a statistical approach. The limitation lies in the amount of variables and object. .
International Journal of Engineering and Advanced Technology, 2019
Education molds the future society. Student profile analysis in higher education system in sultan... more Education molds the future society. Student profile analysis in higher education system in sultanate of Oman reveals that drop out cases of students are tremendously increasing for the last few years. Learning environment plays a vital role in providing appropriate teaching methodologies to motivate the skills of the students. Variations in academic performance can be observed based on different educational indicators such as gender, social, economical, cultural and community characteristics. This paper tries to conduct an analysis on the existing data based on educational data mining and tries to make a classification based on gender which helps to adapt necessary teaching methodology to improve the student performance. A data set of 400 students from three colleges in Sultanate of Oman in three consecutive years is taken as case study for this analysis. Since student’s performance is classified as per the data model based on their gender, equal number of male and female data are c...