Pub Date : 2020-10-01DOI: 10.4018/IJSSCI.2020100103
Rinat Galiautdinov
In this article, the author considers the possibility of applying modern IT technologies to implement information processing algorithms in UAV motion control system. Filtration of coordinates and motion parameters of objects under a priori uncertainty is carried out using nonlinear adaptive filters: Kalman and Bayesian filters. The author considers numerical methods for digital implementation of nonlinear filters based on the convolution of functions, the possibilities of neural networks and fuzzy logic for solving the problems of tracking UAV objects (or missiles), the math model of dynamics, the features of the practical implementation of state estimation algorithms in the frame of added additional degrees of freedom. The considered algorithms are oriented on solving the problems in real time using parallel and cloud computing.
{"title":"Information Processing Systems in UAV Based on Bayesian Filtering in Conditions of Uncertainty","authors":"Rinat Galiautdinov","doi":"10.4018/IJSSCI.2020100103","DOIUrl":"https://doi.org/10.4018/IJSSCI.2020100103","url":null,"abstract":"In this article, the author considers the possibility of applying modern IT technologies to implement information processing algorithms in UAV motion control system. Filtration of coordinates and motion parameters of objects under a priori uncertainty is carried out using nonlinear adaptive filters: Kalman and Bayesian filters. The author considers numerical methods for digital implementation of nonlinear filters based on the convolution of functions, the possibilities of neural networks and fuzzy logic for solving the problems of tracking UAV objects (or missiles), the math model of dynamics, the features of the practical implementation of state estimation algorithms in the frame of added additional degrees of freedom. The considered algorithms are oriented on solving the problems in real time using parallel and cloud computing.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124283270","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 : 2020-10-01DOI: 10.4018/IJSSCI.2020100102
Meriem Benadda, Ghalem Belalem
Malaise and sleepiness behind the wheel are considered to be the leading causes of fatal highway accidents. With the body area networks (BANs), a continuous health monitoring of a driver can be performed without any constraint on his/her normal daily life activities. Many of the systems proposed in the literature are intended to prevent traffic accidents but without treating this kind of cause because difficult to highlight in an accident. This paper proposes “HAaaS,” a new vehicular cloud computing service based on BANs to detect, monitor, and manage driver malaise and provide a cooperation support for the driver rescue. The objective is to reduce the number of accidents, the material and human damage as the time and fuel lost in traffic jams. The proposed service has been validated by simulating real-world highway scenarios extracted from Oran city in Algeria. The results show that the service is efficient at a significant rate.
{"title":"Improving Road Safety for Driver Malaise and Sleepiness Behind the Wheel Using Vehicular Cloud Computing and Body Area Networks","authors":"Meriem Benadda, Ghalem Belalem","doi":"10.4018/IJSSCI.2020100102","DOIUrl":"https://doi.org/10.4018/IJSSCI.2020100102","url":null,"abstract":"Malaise and sleepiness behind the wheel are considered to be the leading causes of fatal highway accidents. With the body area networks (BANs), a continuous health monitoring of a driver can be performed without any constraint on his/her normal daily life activities. Many of the systems proposed in the literature are intended to prevent traffic accidents but without treating this kind of cause because difficult to highlight in an accident. This paper proposes “HAaaS,” a new vehicular cloud computing service based on BANs to detect, monitor, and manage driver malaise and provide a cooperation support for the driver rescue. The objective is to reduce the number of accidents, the material and human damage as the time and fuel lost in traffic jams. The proposed service has been validated by simulating real-world highway scenarios extracted from Oran city in Algeria. The results show that the service is efficient at a significant rate.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121132609","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 : 2020-10-01DOI: 10.4018/IJSSCI.2020100105
Houcine Matallah, Ghalem Belalem, K. Bouamrane
The explosion of the data quantities, which reflects the scaling of volumes, numbers, and types, has resulted in the development of new locations techniques and access to data. The final steps in this evolution have emerged new technologies: cloud computing and big data. The new requirements and the difficulties encountered in the management of data classified “big data” have emerged NoSQL and NewSQL systems. This paper develops a comparative study about the performance of six solutions NoSQL, employed by the important companies in the IT sector: MongoDB, Cassandra, HBase, Redis, Couchbase, and OrientDB. To compare the performance of these NoSQL systems, the authors will use a very powerful tool called YCSB: Yahoo! Cloud Serving Benchmark. The contribution is to provide some answers to choose the appropriate NoSQL system for the type of data used and the type of processing performed on that data.
{"title":"Evaluation of NoSQL Databases: MongoDB, Cassandra, HBase, Redis, Couchbase, OrientDB","authors":"Houcine Matallah, Ghalem Belalem, K. Bouamrane","doi":"10.4018/IJSSCI.2020100105","DOIUrl":"https://doi.org/10.4018/IJSSCI.2020100105","url":null,"abstract":"The explosion of the data quantities, which reflects the scaling of volumes, numbers, and types, has resulted in the development of new locations techniques and access to data. The final steps in this evolution have emerged new technologies: cloud computing and big data. The new requirements and the difficulties encountered in the management of data classified “big data” have emerged NoSQL and NewSQL systems. This paper develops a comparative study about the performance of six solutions NoSQL, employed by the important companies in the IT sector: MongoDB, Cassandra, HBase, Redis, Couchbase, and OrientDB. To compare the performance of these NoSQL systems, the authors will use a very powerful tool called YCSB: Yahoo! Cloud Serving Benchmark. The contribution is to provide some answers to choose the appropriate NoSQL system for the type of data used and the type of processing performed on that data.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125066174","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 : 2020-07-01DOI: 10.4018/ijssci.2020070104
F. Al-akashi
The majority of Islamic and Muslim related search engines fail due to non-profit and content filtering issues due to explicit adult, hateful, and harmful content from Muslim perspectives are not addressed. While this is a crucial and noble initiative, it is controversial because it does not deal with all the needs of Muslim demography, including trustworthiness and aspects of life rather than Islam and religion. Custom search engines employ automatic REST API capability to provide results, and this can cause systemic engagement and compromises with their partners to search for and filter output results to cater customer needs. In reality though, this type of approach usually works with a small number of searches, it cannot be commercialized to serve a massive target audience of 1.8 billion Muslims around the world. To overcome this, the authors propose a novel information retrieval approach that uses homogeneous Islamic content available in distributed selective resources over the Internet to meet all Muslim needs. A difficult engagement algorithm is used to compromise highly relevant resources. Promising results were achieved with the proposed mutual approach.
{"title":"An Islamic Distributed Information Retrieval Approach","authors":"F. Al-akashi","doi":"10.4018/ijssci.2020070104","DOIUrl":"https://doi.org/10.4018/ijssci.2020070104","url":null,"abstract":"The majority of Islamic and Muslim related search engines fail due to non-profit and content filtering issues due to explicit adult, hateful, and harmful content from Muslim perspectives are not addressed. While this is a crucial and noble initiative, it is controversial because it does not deal with all the needs of Muslim demography, including trustworthiness and aspects of life rather than Islam and religion. Custom search engines employ automatic REST API capability to provide results, and this can cause systemic engagement and compromises with their partners to search for and filter output results to cater customer needs. In reality though, this type of approach usually works with a small number of searches, it cannot be commercialized to serve a massive target audience of 1.8 billion Muslims around the world. To overcome this, the authors propose a novel information retrieval approach that uses homogeneous Islamic content available in distributed selective resources over the Internet to meet all Muslim needs. A difficult engagement algorithm is used to compromise highly relevant resources. Promising results were achieved with the proposed mutual approach.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124502005","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 : 2020-07-01DOI: 10.4018/ijssci.2020070105
Akhil Gudivada, James Philips, Nasseh Tabrizi
Within the past few years, the medical domain has endeavored to incorporate artificial intelligence, including cognitive computing tools, to develop enriched models for processing and synthesizing knowledge from Big Data. Due to the rapid growth in published medical research, the ability of medical practitioners to keep up with research developments has become a persistent challenge. Despite this challenge, using data-driven artificial intelligence to process large amounts of data can overcome this difficulty. This research summarizes cognitive computing methodologies and applications utilized in the medical domain. Likewise, this research describes the development process for a novel, concept-enriched model using the IBM Watson service and a publicly available diabetes dataset and knowledge-base. Finally, reflection is offered on the strengths and limitations of the model and enhancements for future experiments. This work thus provides an initial framework for those interested in effectively developing, maintaining, and using cognitive models to enhance the quality of healthcare.
{"title":"Developing Concept Enriched Models for Big Data Processing Within the Medical Domain","authors":"Akhil Gudivada, James Philips, Nasseh Tabrizi","doi":"10.4018/ijssci.2020070105","DOIUrl":"https://doi.org/10.4018/ijssci.2020070105","url":null,"abstract":"Within the past few years, the medical domain has endeavored to incorporate artificial intelligence, including cognitive computing tools, to develop enriched models for processing and synthesizing knowledge from Big Data. Due to the rapid growth in published medical research, the ability of medical practitioners to keep up with research developments has become a persistent challenge. Despite this challenge, using data-driven artificial intelligence to process large amounts of data can overcome this difficulty. This research summarizes cognitive computing methodologies and applications utilized in the medical domain. Likewise, this research describes the development process for a novel, concept-enriched model using the IBM Watson service and a publicly available diabetes dataset and knowledge-base. Finally, reflection is offered on the strengths and limitations of the model and enhancements for future experiments. This work thus provides an initial framework for those interested in effectively developing, maintaining, and using cognitive models to enhance the quality of healthcare.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128246423","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 : 2020-07-01DOI: 10.4018/ijssci.2020070101
R. Fiorini
In this article the author discusses main implications of current autonomous system (AS) through the symbiotic autonomous system (SAS) and the symbiotic system science (SSS) towards the incoming super-smart society, by bringing to light SSS fundamental considerations, according to experience and talks gained on scientific system development in the past fifty years, and formulating the proposal for a new understanding of them, at an effective scientific and operative level towards a real super-smart society. SSS is a growing scientific area which is taking a leadership role in fostering consensus on how best to bring about symbiotic relationships between current AS and incoming SAS in a mixed or hybrid society, called super-smart society. In order to achieve an antifragile behavior, next generation human-made system must have a new fundamental component able to address and to face effectively the problem of multiscale ontological uncertainty management, in an instinctively sustainable way: active, practical wisdom by design!
{"title":"Computational Intelligence From Autonomous System to Super-Smart Society and Beyond","authors":"R. Fiorini","doi":"10.4018/ijssci.2020070101","DOIUrl":"https://doi.org/10.4018/ijssci.2020070101","url":null,"abstract":"In this article the author discusses main implications of current autonomous system (AS) through the symbiotic autonomous system (SAS) and the symbiotic system science (SSS) towards the incoming super-smart society, by bringing to light SSS fundamental considerations, according to experience and talks gained on scientific system development in the past fifty years, and formulating the proposal for a new understanding of them, at an effective scientific and operative level towards a real super-smart society. SSS is a growing scientific area which is taking a leadership role in fostering consensus on how best to bring about symbiotic relationships between current AS and incoming SAS in a mixed or hybrid society, called super-smart society. In order to achieve an antifragile behavior, next generation human-made system must have a new fundamental component able to address and to face effectively the problem of multiscale ontological uncertainty management, in an instinctively sustainable way: active, practical wisdom by design!","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125157213","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 : 2020-07-01DOI: 10.4018/ijssci.2020070103
N. Saavedra-Rivano
The focus of this article is an examination of the impact that sentience of AI systems would have on mankind. Although the notion of sentience for AI systems is subject to controversy, we believe that its plausibility confers a sense of urgency to the kind of exercise developed here. For completeness, the article distinguishes the near-future and longer-term impacts of artificial intelligence. While the short-term impact is deemed to be mostly positive, the outlook for longer-term impact is considered to be negative under a variety of scenarios, including the adoption of man-machine symbiosis tools. The main reason for the negative outlook in the latter case is the heterogeneity of the world. This implies that only a privileged minority would benefit from symbiosis, an outcome that makes likely a world dominated by a minority of “superhumans.” These conclusions should not be taken lightly, and this article endeavors to raise the attention of scientists and policymakers. In this connection, the paper offers suggestions as to policy measures which could avert this disastrous outlook.
{"title":"Mankind at a Crossroads: The Future of Our Relation With AI Entities","authors":"N. Saavedra-Rivano","doi":"10.4018/ijssci.2020070103","DOIUrl":"https://doi.org/10.4018/ijssci.2020070103","url":null,"abstract":"The focus of this article is an examination of the impact that sentience of AI systems would have on mankind. Although the notion of sentience for AI systems is subject to controversy, we believe that its plausibility confers a sense of urgency to the kind of exercise developed here. For completeness, the article distinguishes the near-future and longer-term impacts of artificial intelligence. While the short-term impact is deemed to be mostly positive, the outlook for longer-term impact is considered to be negative under a variety of scenarios, including the adoption of man-machine symbiosis tools. The main reason for the negative outlook in the latter case is the heterogeneity of the world. This implies that only a privileged minority would benefit from symbiosis, an outcome that makes likely a world dominated by a minority of “superhumans.” These conclusions should not be taken lightly, and this article endeavors to raise the attention of scientists and policymakers. In this connection, the paper offers suggestions as to policy measures which could avert this disastrous outlook.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"363 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125817737","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 : 2020-04-01DOI: 10.4018/ijssci.2020040104
O. Singh, Mukul Singh
This article aims at solving economic load dispatch (ELD) problem using two algorithms. Here in this article, an implementation of Flower Pollination (FP) and the BAT Algorithm (BA) based optimization search algorithm method is applied. More than one objective is hoped to be achieve in this article. The combined economic emission dispatch (CEED) problem which considers environmental impacts as well as the cost is also solved using the two algorithms. Practical problems in economic dispatch (ED) include both nonsmooth cost functions having equality and inequality constraints which make it difficult to find the global optimal solution using any mathematical optimization. In this article, the ELD problem is expressed as a nonlinear constrained optimization problem which includes equality and inequality constraints. The attainability of the discussed methods is shown for four different systems with emission and without emission and the results achieved with FP and BAT algorithms are matched with other optimization techniques. The experimental results show that conferred Flower Pollination Algorithm (FPA) outlasts other techniques in finding better solutions proficiently in ELD problems.
{"title":"A Comparative Analysis on Economic Load Dispatch Problem Using Soft Computing Techniques","authors":"O. Singh, Mukul Singh","doi":"10.4018/ijssci.2020040104","DOIUrl":"https://doi.org/10.4018/ijssci.2020040104","url":null,"abstract":"This article aims at solving economic load dispatch (ELD) problem using two algorithms. Here in this article, an implementation of Flower Pollination (FP) and the BAT Algorithm (BA) based optimization search algorithm method is applied. More than one objective is hoped to be achieve in this article. The combined economic emission dispatch (CEED) problem which considers environmental impacts as well as the cost is also solved using the two algorithms. Practical problems in economic dispatch (ED) include both nonsmooth cost functions having equality and inequality constraints which make it difficult to find the global optimal solution using any mathematical optimization. In this article, the ELD problem is expressed as a nonlinear constrained optimization problem which includes equality and inequality constraints. The attainability of the discussed methods is shown for four different systems with emission and without emission and the results achieved with FP and BAT algorithms are matched with other optimization techniques. The experimental results show that conferred Flower Pollination Algorithm (FPA) outlasts other techniques in finding better solutions proficiently in ELD problems.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116312997","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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