Pub Date : 2022-01-01DOI: 10.1504/ijiids.2021.10041195
Radhakrishna Bhat, K. Kumar, N. Sunitha
{"title":"A novel recursive privacy-preserving information retrieval approach for private retrieval","authors":"Radhakrishna Bhat, K. Kumar, N. Sunitha","doi":"10.1504/ijiids.2021.10041195","DOIUrl":"https://doi.org/10.1504/ijiids.2021.10041195","url":null,"abstract":"","PeriodicalId":39658,"journal":{"name":"International Journal of Intelligent Information and Database Systems","volume":"9 1","pages":"267-294"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86047821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-30DOI: 10.11648/J.IJIIS.20211005.11
Konan-Marcelin Kouamé, H. Mcheick
The technology of machine learning has been widely applied in several domains and complex medical problems, specifically in chronic obstructive pulmonary disease (COPD). Researchers in the field of respiratory diseases confirm that people who suffer from COPD have high risks when exposed to COVID-19. The most common oncoming COPD exacerbations and COPD symptoms of COVID-19 are congruent. The distinction between COPD exacerbations and COVID-19 with COPD is nearly impossible without testing. This paper proposes a new powerful model for classifying COPD patients with exacerbations and those with COVID-19 using machine learning and deep learning algorithms. The major contribution of this research is the dynamic classification process based on the patient context that can help detect exacerbations or COVID-19 per period. Indeed, Five Machine Learning algorithms are trained, tested and a performant classification model is identified. This prediction model is then associated with a dynamic COPD patient context for monitoring the patient's health status. This model based on the dynamic adaptation mechanism combined with a classification contributes to identifying dynamically COPD exacerbations and COVID-19 symptoms for COPD patients. Indeed, periodically, data on a new patient is injected into the prediction model. At the output of the model, the patient is either classified in the exacerbation category, or classified in the COVID-19 category, or no category. By period. A dynamic dashboard of classified patients is available to help medical staff take appropriate decisions. This approach helps to follow the evolution of COPD patient comorbidities (exacerbation, COVID-19). Finally, classification would allow healthcare stakeholders to provide healthcare service according to the patient’s status. The methodology of research consists of designing and implementing a dynamic model for classifying COPD patients. Since early intervention is associated with improved prognosis, with our solution, healthcare staff can identify COPD patients who are most at risk of developing exacerbation or COVID-19. Consequently, upon admission, this will ensure that these patients receive appropriate care as soon as possible.
{"title":"Designing Adaptive Mechanism for COVID-19 and Exacerbation in Cases of COPD Patients Using Machine Learning Approaches","authors":"Konan-Marcelin Kouamé, H. Mcheick","doi":"10.11648/J.IJIIS.20211005.11","DOIUrl":"https://doi.org/10.11648/J.IJIIS.20211005.11","url":null,"abstract":"The technology of machine learning has been widely applied in several domains and complex medical problems, specifically in chronic obstructive pulmonary disease (COPD). Researchers in the field of respiratory diseases confirm that people who suffer from COPD have high risks when exposed to COVID-19. The most common oncoming COPD exacerbations and COPD symptoms of COVID-19 are congruent. The distinction between COPD exacerbations and COVID-19 with COPD is nearly impossible without testing. This paper proposes a new powerful model for classifying COPD patients with exacerbations and those with COVID-19 using machine learning and deep learning algorithms. The major contribution of this research is the dynamic classification process based on the patient context that can help detect exacerbations or COVID-19 per period. Indeed, Five Machine Learning algorithms are trained, tested and a performant classification model is identified. This prediction model is then associated with a dynamic COPD patient context for monitoring the patient's health status. This model based on the dynamic adaptation mechanism combined with a classification contributes to identifying dynamically COPD exacerbations and COVID-19 symptoms for COPD patients. Indeed, periodically, data on a new patient is injected into the prediction model. At the output of the model, the patient is either classified in the exacerbation category, or classified in the COVID-19 category, or no category. By period. A dynamic dashboard of classified patients is available to help medical staff take appropriate decisions. This approach helps to follow the evolution of COPD patient comorbidities (exacerbation, COVID-19). Finally, classification would allow healthcare stakeholders to provide healthcare service according to the patient’s status. The methodology of research consists of designing and implementing a dynamic model for classifying COPD patients. Since early intervention is associated with improved prognosis, with our solution, healthcare staff can identify COPD patients who are most at risk of developing exacerbation or COVID-19. Consequently, upon admission, this will ensure that these patients receive appropriate care as soon as possible.","PeriodicalId":39658,"journal":{"name":"International Journal of Intelligent Information and Database Systems","volume":"134 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79071701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-31DOI: 10.11648/J.IJIIS.20211004.16
Zheni Mincheva, Nikola Vasilev, Ventsislav Nikolov, A. Antonov
Nowadays, the amount of information in the web is tremendous. Big part of it is presented as articles, descriptions, posts and comments i.e. free text in natural language and it is really hard to make use of it while it is in this format. Whereas, in the structured form it could be used for a lot of purposes. So, the main idea that this paper proposes is an approach for extracting data which is given as a free text in natural language into a structured data for example table. The structured information is easy to search and analyze. The structured data is quantitative, while the unstructured data is qualitative. Overall such tool that enables conversion of a text into a structured data will not only provide automatic mechanism for data extraction but will also save a lot of resources for processing and storing of the extracted data. The data extraction from text will also provide automation of the process of extracting useful insights from data that is usually processed by people. The efficiency of the process as well as its accuracy will increase and the probability of human error will be minimized. The amount of the processed data will no longer be limited by the human resources.
{"title":"Extracting Structured Data from Text in Natural Language","authors":"Zheni Mincheva, Nikola Vasilev, Ventsislav Nikolov, A. Antonov","doi":"10.11648/J.IJIIS.20211004.16","DOIUrl":"https://doi.org/10.11648/J.IJIIS.20211004.16","url":null,"abstract":"Nowadays, the amount of information in the web is tremendous. Big part of it is presented as articles, descriptions, posts and comments i.e. free text in natural language and it is really hard to make use of it while it is in this format. Whereas, in the structured form it could be used for a lot of purposes. So, the main idea that this paper proposes is an approach for extracting data which is given as a free text in natural language into a structured data for example table. The structured information is easy to search and analyze. The structured data is quantitative, while the unstructured data is qualitative. Overall such tool that enables conversion of a text into a structured data will not only provide automatic mechanism for data extraction but will also save a lot of resources for processing and storing of the extracted data. The data extraction from text will also provide automation of the process of extracting useful insights from data that is usually processed by people. The efficiency of the process as well as its accuracy will increase and the probability of human error will be minimized. The amount of the processed data will no longer be limited by the human resources.","PeriodicalId":39658,"journal":{"name":"International Journal of Intelligent Information and Database Systems","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90033785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-31DOI: 10.11648/J.IJIIS.20211004.15
A. Ibitoye, R. Famutimi, D. O. Olanloye, Ehisuoria Akioyamen
In more recent time, depression as a lingering mental illness as continued to affect the way people act, and behave consciously or otherwise. Though it remained an undiagnosed disease globally without prejudice to age, gender, color or race; a lot of people never know implicitly or explicitly when they are depressed until it begins to affect their health conditions. While depression can be deciphered through text analysis in opinion mining, oftentimes, changes in human body also provides a convincing status of a depressed individual. No doubt, each data source can independently predict human depression status; however, the exclusive mutual relationship between both data sources has not been studied for depression detection. Therefore, in identifying meaningful correlations between clinical and behavioural data, this research detected depression by analyzing and matching mined patterns in users’ behavioural opinion through tweets with trackable changes in clinical body vitals using wearable device for effective therapy in depressed patient management. Thus, by using a 5-fold cross validation on the clustered data, Random Forest ensemble model was used to build the Social-Health Depression Detection Model (SH2DM) after data preprocessing and optimal feature extraction. The dual data sourced user-centric model produced a better predictive result in accuracy, precision and recall values when compared and evaluated with single data depression detection instances of clinical and behavioural records.
{"title":"User Centric Social Opinion and Clinical Behavioural Model for Depression Detection","authors":"A. Ibitoye, R. Famutimi, D. O. Olanloye, Ehisuoria Akioyamen","doi":"10.11648/J.IJIIS.20211004.15","DOIUrl":"https://doi.org/10.11648/J.IJIIS.20211004.15","url":null,"abstract":"In more recent time, depression as a lingering mental illness as continued to affect the way people act, and behave consciously or otherwise. Though it remained an undiagnosed disease globally without prejudice to age, gender, color or race; a lot of people never know implicitly or explicitly when they are depressed until it begins to affect their health conditions. While depression can be deciphered through text analysis in opinion mining, oftentimes, changes in human body also provides a convincing status of a depressed individual. No doubt, each data source can independently predict human depression status; however, the exclusive mutual relationship between both data sources has not been studied for depression detection. Therefore, in identifying meaningful correlations between clinical and behavioural data, this research detected depression by analyzing and matching mined patterns in users’ behavioural opinion through tweets with trackable changes in clinical body vitals using wearable device for effective therapy in depressed patient management. Thus, by using a 5-fold cross validation on the clustered data, Random Forest ensemble model was used to build the Social-Health Depression Detection Model (SH2DM) after data preprocessing and optimal feature extraction. The dual data sourced user-centric model produced a better predictive result in accuracy, precision and recall values when compared and evaluated with single data depression detection instances of clinical and behavioural records.","PeriodicalId":39658,"journal":{"name":"International Journal of Intelligent Information and Database Systems","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80367421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-24DOI: 10.11648/J.IJIIS.20211004.14
Khaled Mili
Higher education institutions are considered one of the most important pillars and the greatest starting points from which the wheels of development and civilized advancement are launched, as well as their important role in instilling the values of society and preserving its moral and value system. In performing the role entrusted to it in achieving sustainable development and the comprehensive renaissance of society in various field and sectors. Thus; the accreditation systems are frequently used to verify which institutions are recognized and authorized to giveeducational or professional skills. However, these systems are not always efficient in countries where recognized higher education establishments cannot rally the demand for certified professionals required by the employment market. This generates a fertile argument for the “certificate factories” to sell false diplomas to unskilled people who are trying to catchbenefit of this deficit. In this regard, the digitization of diploma granting’s and verification’s processes, is becomingincreasingly important in order to guarantee the identity of diplomas, and that companies recruit the right qualified people. For that reason, an efficient management system for the control of diploma creation processes is immediatelymandatory. The Blockchain methodology provides efficient ways to examine the data information management systems. It is designed to make confidence techniques that can revolutionize information management methods. The major purpose of this paper is to develop a “BlockDipls” system based on Blockchain technology. This BlockDipls system is planned to support diploma traceability and smart contract functions, and can be used to address the problems of diploma falsification and diploma record fraud.
{"title":"Blockchain Traceability to Ensure the Veracity of Diplomas","authors":"Khaled Mili","doi":"10.11648/J.IJIIS.20211004.14","DOIUrl":"https://doi.org/10.11648/J.IJIIS.20211004.14","url":null,"abstract":"Higher education institutions are considered one of the most important pillars and the greatest starting points from which the wheels of development and civilized advancement are launched, as well as their important role in instilling the values of society and preserving its moral and value system. In performing the role entrusted to it in achieving sustainable development and the comprehensive renaissance of society in various field and sectors. Thus; the accreditation systems are frequently used to verify which institutions are recognized and authorized to giveeducational or professional skills. However, these systems are not always efficient in countries where recognized higher education establishments cannot rally the demand for certified professionals required by the employment market. This generates a fertile argument for the “certificate factories” to sell false diplomas to unskilled people who are trying to catchbenefit of this deficit. In this regard, the digitization of diploma granting’s and verification’s processes, is becomingincreasingly important in order to guarantee the identity of diplomas, and that companies recruit the right qualified people. For that reason, an efficient management system for the control of diploma creation processes is immediatelymandatory. The Blockchain methodology provides efficient ways to examine the data information management systems. It is designed to make confidence techniques that can revolutionize information management methods. The major purpose of this paper is to develop a “BlockDipls” system based on Blockchain technology. This BlockDipls system is planned to support diploma traceability and smart contract functions, and can be used to address the problems of diploma falsification and diploma record fraud.","PeriodicalId":39658,"journal":{"name":"International Journal of Intelligent Information and Database Systems","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85992856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-24DOI: 10.11648/J.IJIIS.20211004.13
E. Bryndin
The intellectual robotization of industry and the social sphere takes on an international scale. The creation of smart robots for various spheres of human life is associated with high technology and artificial intelligence. Currently, the development of artificial intelligence for industrial and social robotics is carried out by information technology, cognitive robots, digital twins and artificial intelligence systems. The ensembles of intelligent mobile diversifiable agents with strong artificial intelligence are central to the development of artificial intelligence for industrial and social robotics through the recurring development of professional skills, increasing their visual, sound, subject, spatial and temporal sensitivity. Working with big data, diversify and transform the high-tech industry and the social sphere. The cognitive ensembles of mobile diversifiable agents, technology platforms and analytical systems allow you to quickly and efficiently solve the tasks of collecting, analyzing and visualizing large amounts of data. Effective collection and analysis of big data, their rapid updating using strong artificial intelligence will accelerate industrial and social robotics by teaching new skills. Intelligent robotization based on large ensembles of intelligent agents processing big data requires faster supercomputers. Communication and control of the robot through the mental neurointerface accelerates the training of industrial and social communicative-associative robots, the development of their intelligence, and makes them natural assistants in improving the life of society. Rapid technological development and rapid change of professions requires a client of project-oriented training of personnel.
{"title":"Development of Artificial Intelligence for Industrial and Social Robotization","authors":"E. Bryndin","doi":"10.11648/J.IJIIS.20211004.13","DOIUrl":"https://doi.org/10.11648/J.IJIIS.20211004.13","url":null,"abstract":"The intellectual robotization of industry and the social sphere takes on an international scale. The creation of smart robots for various spheres of human life is associated with high technology and artificial intelligence. Currently, the development of artificial intelligence for industrial and social robotics is carried out by information technology, cognitive robots, digital twins and artificial intelligence systems. The ensembles of intelligent mobile diversifiable agents with strong artificial intelligence are central to the development of artificial intelligence for industrial and social robotics through the recurring development of professional skills, increasing their visual, sound, subject, spatial and temporal sensitivity. Working with big data, diversify and transform the high-tech industry and the social sphere. The cognitive ensembles of mobile diversifiable agents, technology platforms and analytical systems allow you to quickly and efficiently solve the tasks of collecting, analyzing and visualizing large amounts of data. Effective collection and analysis of big data, their rapid updating using strong artificial intelligence will accelerate industrial and social robotics by teaching new skills. Intelligent robotization based on large ensembles of intelligent agents processing big data requires faster supercomputers. Communication and control of the robot through the mental neurointerface accelerates the training of industrial and social communicative-associative robots, the development of their intelligence, and makes them natural assistants in improving the life of society. Rapid technological development and rapid change of professions requires a client of project-oriented training of personnel.","PeriodicalId":39658,"journal":{"name":"International Journal of Intelligent Information and Database Systems","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90866621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Security is a very vital concern in information system in this modern day. The protection of confidential files and integrity of information kept in the database are also of great important, the security model play an important role in protecting the privacy and integrity of messages in the database from unlawful users is a formal method to verify and describe intricate information system. An access Control mechanism is a main strategy for prevention and protection of the classified files in a database; this is carried out by restricting rights of access for different approved users of these files. This paper proposes a novel access control mechanism based on Chinese remainder theorem II which implements a single-key-lock system to encrypt one key called a secret key which is used for both encryption and decryption in the electronic information system for accessing the database. The key to be used in the decryption process must be exchanged between the entities in communication using symmetric encryption for the users to have access to the database. This method represents flocks and keys which is highly efficient and proficient. Also, this implementation can be achieved using the Chinese remainder theorem which executes faster operations and enables simpler construction of keys and locks to be provide for user to have access to control.
{"title":"Novel Access Control Mechanism Based New Chinese Remainder Theorem II (New Crt II)","authors":"Aremu Idris Aremu, Ibitoye Akinfola Akinrinnola, Nwaocha Vivian Ogochukwu","doi":"10.11648/j.ijiis.20211003.12","DOIUrl":"https://doi.org/10.11648/j.ijiis.20211003.12","url":null,"abstract":"Security is a very vital concern in information system in this modern day. The protection of confidential files and integrity of information kept in the database are also of great important, the security model play an important role in protecting the privacy and integrity of messages in the database from unlawful users is a formal method to verify and describe intricate information system. An access Control mechanism is a main strategy for prevention and protection of the classified files in a database; this is carried out by restricting rights of access for different approved users of these files. This paper proposes a novel access control mechanism based on Chinese remainder theorem II which implements a single-key-lock system to encrypt one key called a secret key which is used for both encryption and decryption in the electronic information system for accessing the database. The key to be used in the decryption process must be exchanged between the entities in communication using symmetric encryption for the users to have access to the database. This method represents flocks and keys which is highly efficient and proficient. Also, this implementation can be achieved using the Chinese remainder theorem which executes faster operations and enables simpler construction of keys and locks to be provide for user to have access to control.","PeriodicalId":39658,"journal":{"name":"International Journal of Intelligent Information and Database Systems","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76927512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The advent of the internet made it possible to have access to unlimited e-learning resources for knowledge acquisition. Presently, there is an interest to introduce Knowledge Management (KM) into e-Learning with the hope that KM can facilitate an improved e-Learning system. The integration of an e-Learning system with KM is usually referred to as knowledge resource repository, with the KM methods implemented to increase the effectiveness of knowledge dissemination. The importance of KM cannot be over emphasized in any economy and that informs why it is acknowledged as a simplified tool for distributing and utilizing knowledge in a way that directly influence performance in any organization. Also, the potentials and necessity of e-learning in building and developing human capacity cannot be overstressed. Researchers have designed many models for integrating knowledge management into the e-learning system. Some were practically implemented while some were not. Despite the various models, researchers are still looking for a more interactive, efficient, and effective methods that could be used to quickly identify the most relevant information (knowledge) and distribute them to meet the specific needs of users. This work reviewed different literature on e-learning, Knowledge Management and their integration. It also implemented the integration of e-learning and Knowledge Management in a portable interactive system.
{"title":"An Efficient Integration of Knowledge Management and E-learning in a Portable Interactive System","authors":"Folasade Olubusola Isinkaye, Jumoke Soyemi, Adedoyin Olayinka Ajayi, Amonatullahi Akorede Ismail","doi":"10.11648/j.ijiis.20211003.11","DOIUrl":"https://doi.org/10.11648/j.ijiis.20211003.11","url":null,"abstract":"The advent of the internet made it possible to have access to unlimited e-learning resources for knowledge acquisition. Presently, there is an interest to introduce Knowledge Management (KM) into e-Learning with the hope that KM can facilitate an improved e-Learning system. The integration of an e-Learning system with KM is usually referred to as knowledge resource repository, with the KM methods implemented to increase the effectiveness of knowledge dissemination. The importance of KM cannot be over emphasized in any economy and that informs why it is acknowledged as a simplified tool for distributing and utilizing knowledge in a way that directly influence performance in any organization. Also, the potentials and necessity of e-learning in building and developing human capacity cannot be overstressed. Researchers have designed many models for integrating knowledge management into the e-learning system. Some were practically implemented while some were not. Despite the various models, researchers are still looking for a more interactive, efficient, and effective methods that could be used to quickly identify the most relevant information (knowledge) and distribute them to meet the specific needs of users. This work reviewed different literature on e-learning, Knowledge Management and their integration. It also implemented the integration of e-learning and Knowledge Management in a portable interactive system.","PeriodicalId":39658,"journal":{"name":"International Journal of Intelligent Information and Database Systems","volume":"158 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85346182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-03DOI: 10.11648/j.ijiis.20211002.12
Hao Wang, Yan Tao Yang, Qing Shen, Qian Zhang, Bin Yin
The virtual disassembly and assembly system based on computer virtual reality technology has been rapidly developed and applied. However, the current virtual disassembly system and assembly based on the hierarchy model and association model does not consider the problem of selective disassembly, which leads to inconsistency between virtual disassembly and actual disassembly. Aiming to solve the problem, introduces the concept of skipping disassembly path on the basis of the original disassembly system based on the hierarchical relationship and the association relationship model, and perfects and optimizes the disassembly and assembly structure model based on the hierarchical relationship model and the association relationship model. The sequence planning of the disassembly model after introducing the shipping disassembly path was carried out．And the combination and reduction of disassembling units in the course of disassembly decision was described. Finally, a selective disassembly algorithm based on the association relationship model is established. With the marine oil separator for example verification. The results show that the model can better solve the actual problem of selective disassembly which improved the authenticity and user experience of the virtual disassembly and assembly system, and has great influence on the application development of the virtual disassembly and assembly system.
{"title":"Modeling of Virtual Assembly and Disassembly Process Based on Selective Disassembly","authors":"Hao Wang, Yan Tao Yang, Qing Shen, Qian Zhang, Bin Yin","doi":"10.11648/j.ijiis.20211002.12","DOIUrl":"https://doi.org/10.11648/j.ijiis.20211002.12","url":null,"abstract":"The virtual disassembly and assembly system based on computer virtual reality technology has been rapidly developed and applied. However, the current virtual disassembly system and assembly based on the hierarchy model and association model does not consider the problem of selective disassembly, which leads to inconsistency between virtual disassembly and actual disassembly. Aiming to solve the problem, introduces the concept of skipping disassembly path on the basis of the original disassembly system based on the hierarchical relationship and the association relationship model, and perfects and optimizes the disassembly and assembly structure model based on the hierarchical relationship model and the association relationship model. The sequence planning of the disassembly model after introducing the shipping disassembly path was carried out．And the combination and reduction of disassembling units in the course of disassembly decision was described. Finally, a selective disassembly algorithm based on the association relationship model is established. With the marine oil separator for example verification. The results show that the model can better solve the actual problem of selective disassembly which improved the authenticity and user experience of the virtual disassembly and assembly system, and has great influence on the application development of the virtual disassembly and assembly system.","PeriodicalId":39658,"journal":{"name":"International Journal of Intelligent Information and Database Systems","volume":"335 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85109464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-14DOI: 10.11648/J.IJIIS.20211002.11
A. J. Ibrahim, P. Zira, Nuraini Abdulganiyyi
In digital libraries and other e-commerce sites, recommender system is the solution that supports the users in information search and decision making. Some of these recommender systems will make predictions by matching the content of an item against the user profile otherwise known as Content-Based recommendation approach. Other recommenders will provide recommendation based on ratings of items from current user and other users and then use it to recommend similar items the current user has not seen, this is known as Collaborative-Based recommender approach. There exist several other approaches that are used in recommending articles and other items to users of different search engines. Over the years several researchers have tried combining these approaches in an attempt to design more efficient recommendations in search engines. This research proposed and designed a prototype of a Hybrid recommender called Zira, which is a model that combines both the Collaborative filtering, Content-based filtering, attribute-based approach to look at contextual information as well as an item-based approach that will solve the issues associated with cold-start problems all working concurrently to complement one another. The proposed system supports multi-criteria ratings, provide more flexible and less intrusive types of recommendations to ensure the improvement in recommendations of e-learning materials to users of digital libraries.
{"title":"Hybrid Recommender for Research Papers and Articles","authors":"A. J. Ibrahim, P. Zira, Nuraini Abdulganiyyi","doi":"10.11648/J.IJIIS.20211002.11","DOIUrl":"https://doi.org/10.11648/J.IJIIS.20211002.11","url":null,"abstract":"In digital libraries and other e-commerce sites, recommender system is the solution that supports the users in information search and decision making. Some of these recommender systems will make predictions by matching the content of an item against the user profile otherwise known as Content-Based recommendation approach. Other recommenders will provide recommendation based on ratings of items from current user and other users and then use it to recommend similar items the current user has not seen, this is known as Collaborative-Based recommender approach. There exist several other approaches that are used in recommending articles and other items to users of different search engines. Over the years several researchers have tried combining these approaches in an attempt to design more efficient recommendations in search engines. This research proposed and designed a prototype of a Hybrid recommender called Zira, which is a model that combines both the Collaborative filtering, Content-based filtering, attribute-based approach to look at contextual information as well as an item-based approach that will solve the issues associated with cold-start problems all working concurrently to complement one another. The proposed system supports multi-criteria ratings, provide more flexible and less intrusive types of recommendations to ensure the improvement in recommendations of e-learning materials to users of digital libraries.","PeriodicalId":39658,"journal":{"name":"International Journal of Intelligent Information and Database Systems","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91281904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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