Pub Date : 2023-08-27DOI: 10.5121/ijcses.2023.14402
Even Becker, Hans D. Schotten
Sensing location information in indoor scenes requires a high accuracy and is a challenging task, mainly because of multipath and NLoS (non-line-of-sight) propagation. GNSS signals cannot penetrate well in indoor environment. Satellite-based navigation and positioning systems cannot therefore be used for indoor positioning.. Other technologies have been suggested for indoor usage, among them, Wi-Fi (802.11) and 5G NR (New Radio). The primary aim of this study is to discuss the advantages and drawbacks of 5G and Wi-Fi positioning techniques for indoor localization.
{"title":"5G Vs Wi-Fi Indoor Positioning: A Comparative Study","authors":"Even Becker, Hans D. Schotten","doi":"10.5121/ijcses.2023.14402","DOIUrl":"https://doi.org/10.5121/ijcses.2023.14402","url":null,"abstract":"Sensing location information in indoor scenes requires a high accuracy and is a challenging task, mainly because of multipath and NLoS (non-line-of-sight) propagation. GNSS signals cannot penetrate well in indoor environment. Satellite-based navigation and positioning systems cannot therefore be used for indoor positioning.. Other technologies have been suggested for indoor usage, among them, Wi-Fi (802.11) and 5G NR (New Radio). The primary aim of this study is to discuss the advantages and drawbacks of 5G and Wi-Fi positioning techniques for indoor localization.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135181606","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 : 2023-08-27DOI: 10.5121/ijcses.2023.14401
Elizaveta Tereshchenko, Ari Happonen, Victoria Hasheela-Mufeti
Background and context: Even when the modern world is transitioning quickly into the digital age, the gender gap continues to be more acute. Social scientists note the low number of women in Science, Technology, Engineering, and Maths (STEM) as a scientific, creative, economic, and innovative potential loss. The importance of women’s participation in technical sciences and technical production is also recognized as a factor for stable social development. Objective and method: A scoping review has been conducted to study females’ reasonings and society-based explanations for females to choose STEM studies at the Higher Education Institutions (HEI) level. The goal is to understand the reasons for the low number of females in STEM careers related to education in STEM and to reveal the underlying phenomenon. Results: The gender attitudes and stereotypes inherent in boy and girl children’s spare time and school life narrow the children's possibilities from what specific education and career direction they can choose. But only a few genetics and physical differences could postulate and explain this status quo. Humans have formed a particular social framework; in the process, we have socialized childhood and education. When choosing a future specialization, the society in which the child grew up, the family that brought him up, and what traditions they invested in are much more important than his gender. Implications: Based on our results, we summarise the scattered knowledge base and utilize the analyzed summary for recommendations to further the development of HEI programs to make them more fitting for both genders and help reduce the gender gap. The universities should cover the achievements of females, more often in their media channels, related to the previously mentioned interest in STEM, based on the presence of a role model. When choosing a university, girls can see a real example and be inspired to study STEM majors.
{"title":"Barriers for Females to Pursue Stem Careers and Studies at Higher Education Institutions (HEI). A Closer Look at Academic Literature","authors":"Elizaveta Tereshchenko, Ari Happonen, Victoria Hasheela-Mufeti","doi":"10.5121/ijcses.2023.14401","DOIUrl":"https://doi.org/10.5121/ijcses.2023.14401","url":null,"abstract":"Background and context: Even when the modern world is transitioning quickly into the digital age, the gender gap continues to be more acute. Social scientists note the low number of women in Science, Technology, Engineering, and Maths (STEM) as a scientific, creative, economic, and innovative potential loss. The importance of women’s participation in technical sciences and technical production is also recognized as a factor for stable social development. Objective and method: A scoping review has been conducted to study females’ reasonings and society-based explanations for females to choose STEM studies at the Higher Education Institutions (HEI) level. The goal is to understand the reasons for the low number of females in STEM careers related to education in STEM and to reveal the underlying phenomenon. Results: The gender attitudes and stereotypes inherent in boy and girl children’s spare time and school life narrow the children's possibilities from what specific education and career direction they can choose. But only a few genetics and physical differences could postulate and explain this status quo. Humans have formed a particular social framework; in the process, we have socialized childhood and education. When choosing a future specialization, the society in which the child grew up, the family that brought him up, and what traditions they invested in are much more important than his gender. Implications: Based on our results, we summarise the scattered knowledge base and utilize the analyzed summary for recommendations to further the development of HEI programs to make them more fitting for both genders and help reduce the gender gap. The universities should cover the achievements of females, more often in their media channels, related to the previously mentioned interest in STEM, based on the presence of a role model. When choosing a university, girls can see a real example and be inspired to study STEM majors.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135181396","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 : 2021-04-30DOI: 10.5121/IJCSES.2021.12201
Omar Mohammed, B. Mahmood
Image restoration is the process of restoring the original image from a degraded one. Images can be affected by various types of noise, such as Gaussian noise, impulse noise, and affected by blurring, which is happened during image recordings like motion blur, Out-of-Focus Blur, and others. Image restoration techniques are used to reverse the effect of noise and blurring. Restoration of distorted images can be done using some information about noise and the blurring nature or without any knowledge about the image degradation process. Researchers have proposed many algorithms in this regard; in this paper, different noise and degradation models and restoration methods will be discussed and review some researches in this field.
{"title":"Advance in Image and Audio Restoration and their Assessments: A Review","authors":"Omar Mohammed, B. Mahmood","doi":"10.5121/IJCSES.2021.12201","DOIUrl":"https://doi.org/10.5121/IJCSES.2021.12201","url":null,"abstract":"Image restoration is the process of restoring the original image from a degraded one. Images can be affected by various types of noise, such as Gaussian noise, impulse noise, and affected by blurring, which is happened during image recordings like motion blur, Out-of-Focus Blur, and others. Image restoration techniques are used to reverse the effect of noise and blurring. Restoration of distorted images can be done using some information about noise and the blurring nature or without any knowledge about the image degradation process. Researchers have proposed many algorithms in this regard; in this paper, different noise and degradation models and restoration methods will be discussed and review some researches in this field.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128032442","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 : 2021-02-28DOI: 10.5121/IJCSES.2021.12101
Santosh Giri, Basanta Joshi
ANN is a computational model that is composed of several processing elements (neurons) that tries to solve a specific problem. Like the human brain, it provides the ability to learn from experiences without being explicitly programmed. This article is based on the implementation of artificial neural networks for logic gates. At first, the 3 layers Artificial Neural Network is designed with 2 input neurons, 2 hidden neurons & 1 output neuron. after that model is trained by using a backpropagation algorithm until the model satisfies the predefined error criteria (e) which set 0.01 in this experiment. The learning rate (α) used for this experiment was 0.01. The NN model produces correct output at iteration (p)= 20000 for AND, NAND & NOR gate. For OR & XOR the correct output is predicted at iteration (p)=15000 & 80000 respectively.
{"title":"Multilayer Backpropagation Neural Networks for Implementation of Logic Gates","authors":"Santosh Giri, Basanta Joshi","doi":"10.5121/IJCSES.2021.12101","DOIUrl":"https://doi.org/10.5121/IJCSES.2021.12101","url":null,"abstract":"ANN is a computational model that is composed of several processing elements (neurons) that tries to solve a specific problem. Like the human brain, it provides the ability to learn from experiences without being explicitly programmed. This article is based on the implementation of artificial neural networks for logic gates. At first, the 3 layers Artificial Neural Network is designed with 2 input neurons, 2 hidden neurons & 1 output neuron. after that model is trained by using a backpropagation algorithm until the model satisfies the predefined error criteria (e) which set 0.01 in this experiment. The learning rate (α) used for this experiment was 0.01. The NN model produces correct output at iteration (p)= 20000 for AND, NAND & NOR gate. For OR & XOR the correct output is predicted at iteration (p)=15000 & 80000 respectively.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125906294","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 : 2020-06-30DOI: 10.5121/ijcses.2020.11301
Egba Anwaitu Fraser, Okonkwo, R. Obikwelu
Artificial Intelligence systems (especially computer-aided diagnosis and artificial neural networks) are increasingly finding many uses in medical diagnosis application in recent times. These methods are adaptive learning algorithms that are capable of handling multiple and heterogeneous types of clinical data with a view of integrating them into categorized outputs. In this study, we briefly review and discuss the concept, capabilities, and applicability of artificial neural network techniques to medical diagnosis, through consideration of some selected physical and mental diseases. The study focuses on scholarly researches within the years, 2010 to 2019. Findings show that no electronic online clinical database exists in Nigeria and the Sub-Saharan countries, most review researches in this area focused mainly on physical diseases without considering mental illnesses, the application of ANN in mental and comorbid disorders have not been thoroughly studied, ANN models and algorithms consider mainly homogeneous input data sources and not heterogeneous input data sources, and ANN models on multi-objective output systems are few as compared to single output ANN models.
{"title":"Artificial Neural Networks for Medical Diagnosis: A Review of Recent Trends","authors":"Egba Anwaitu Fraser, Okonkwo, R. Obikwelu","doi":"10.5121/ijcses.2020.11301","DOIUrl":"https://doi.org/10.5121/ijcses.2020.11301","url":null,"abstract":"Artificial Intelligence systems (especially computer-aided diagnosis and artificial neural networks) are increasingly finding many uses in medical diagnosis application in recent times. These methods are adaptive learning algorithms that are capable of handling multiple and heterogeneous types of clinical data with a view of integrating them into categorized outputs. In this study, we briefly review and discuss the concept, capabilities, and applicability of artificial neural network techniques to medical diagnosis, through consideration of some selected physical and mental diseases. The study focuses on scholarly researches within the years, 2010 to 2019. Findings show that no electronic online clinical database exists in Nigeria and the Sub-Saharan countries, most review researches in this area focused mainly on physical diseases without considering mental illnesses, the application of ANN in mental and comorbid disorders have not been thoroughly studied, ANN models and algorithms consider mainly homogeneous input data sources and not heterogeneous input data sources, and ANN models on multi-objective output systems are few as compared to single output ANN models.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121980921","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 : 2020-04-30DOI: 10.5121/ijcses.2020.11201
S. Vyas
Research under the field of Brain Computer Interfaces is adapting various Machine Learning and Deep Learning techniques in recent times. With the advent of modern BCI, the data generated by various devices is now capable of detecting brain signals more accurately. This paper gives an overview of all the steps involved in the process of applying Machine Learning as well as Deep Learning methods from Data Acquisition to application of algorithms. It aims to study techniques currently employed to extract data, features from brain data, different algorithms employed to draw insights from the extracted features, and how it can be used in various BCI applications. By this study, I aim to put forward current Machine Learning and Deep Learning Trends in the field of BCI.
{"title":"Brain Computer Interfaces Employing Machine Learning Methods : A Systematic Review","authors":"S. Vyas","doi":"10.5121/ijcses.2020.11201","DOIUrl":"https://doi.org/10.5121/ijcses.2020.11201","url":null,"abstract":"Research under the field of Brain Computer Interfaces is adapting various Machine Learning and Deep Learning techniques in recent times. With the advent of modern BCI, the data generated by various devices is now capable of detecting brain signals more accurately. This paper gives an overview of all the steps involved in the process of applying Machine Learning as well as Deep Learning methods from Data Acquisition to application of algorithms. It aims to study techniques currently employed to extract data, features from brain data, different algorithms employed to draw insights from the extracted features, and how it can be used in various BCI applications. By this study, I aim to put forward current Machine Learning and Deep Learning Trends in the field of BCI.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131787733","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 : 2019-10-31DOI: 10.5121/ijcses.2019.10501
Solomon Orduen Yese, Abdulhakeem Abdulazeez, Aminu Mohammed, M. Umar, Zaharadden Yusuf Yeldu
{"title":"A Survey on Call Admission Control Schemes in LTE","authors":"Solomon Orduen Yese, Abdulhakeem Abdulazeez, Aminu Mohammed, M. Umar, Zaharadden Yusuf Yeldu","doi":"10.5121/ijcses.2019.10501","DOIUrl":"https://doi.org/10.5121/ijcses.2019.10501","url":null,"abstract":"","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123087260","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 : 2019-06-29DOI: 10.5121/IJCSES.2019.10301
Swayanshu Shanti Pragnya, S. Priyadarshi
{"title":"The Implication of Statistical Analysis and Feature Engineering for Model Building Using Machine Learning Algorithms","authors":"Swayanshu Shanti Pragnya, S. Priyadarshi","doi":"10.5121/IJCSES.2019.10301","DOIUrl":"https://doi.org/10.5121/IJCSES.2019.10301","url":null,"abstract":"","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"361 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114768202","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 : 2019-04-01DOI: 10.5121/IJCSES.2019.10102
Nesma Abd El-mawla, M. Badawy, Hesham A. Arafat
Wireless sensor networks (WSNs) have turned to be the backbone of most present-day information technology, which supports the service-oriented architecture in a major activity. Sensor nodes and its restricted and limited resources have been a real challenge because there’s a great engagement with sensor nodes and Internet Of things (IoT). WSN is considered to be the base stone of IoT which has been widely used recently in too many applications like smart cities, industrial internet, connected cars, connected health care systems, smart grids, smart farming and it's widely used in both military and civilian applications now, such as monitoring of ambient conditions related to the environment, precious species and critical infrastructures. Secure communication and data transfer among the nodes are strongly needed due to the use of wireless technologies that are easy to eavesdrop, in order to steal its important information. However, is hard to achieve the desired performance of both WSNs and IoT and many critical issues about sensor networks are still open. The major research areas in WSN is going on hardware, operating system of WSN, localization, synchronization, deployment, architecture, programming models, data aggregation and dissemination, database querying, architecture, middleware, quality of service and security. In This paper we discuss in detail all about Wireless Sensor Networks, its classification, types, topologies, attack models and the nodes and all related issues and complications. We also preview too many challenges about sensor nodes and the proposed solutions till now and we make a spot ongoing research activities and issues that affect security and performance of Wireless Sensor Network as well. Then we discuss what’s meant by security objectives, requirements and threat models. Finally, we make a spot on key management operations, goals, constraints, evaluation metrics, different encryption key types and dynamic key management schemes.
{"title":"SECURITY AND KEY MANAGEMENT CHALLENGES OVER WSN (A SURVEY)","authors":"Nesma Abd El-mawla, M. Badawy, Hesham A. Arafat","doi":"10.5121/IJCSES.2019.10102","DOIUrl":"https://doi.org/10.5121/IJCSES.2019.10102","url":null,"abstract":"Wireless sensor networks (WSNs) have turned to be the backbone of most present-day information technology, which supports the service-oriented architecture in a major activity. Sensor nodes and its restricted and limited resources have been a real challenge because there’s a great engagement with sensor nodes and Internet Of things (IoT). WSN is considered to be the base stone of IoT which has been widely used recently in too many applications like smart cities, industrial internet, connected cars, connected health care systems, smart grids, smart farming and it's widely used in both military and civilian applications now, such as monitoring of ambient conditions related to the environment, precious species and critical infrastructures. Secure communication and data transfer among the nodes are strongly needed due to the use of wireless technologies that are easy to eavesdrop, in order to steal its important information. However, is hard to achieve the desired performance of both WSNs and IoT and many critical issues about sensor networks are still open. The major research areas in WSN is going on hardware, operating system of WSN, localization, synchronization, deployment, architecture, programming models, data aggregation and dissemination, database querying, architecture, middleware, quality of service and security. In This paper we discuss in detail all about Wireless Sensor Networks, its classification, types, topologies, attack models and the nodes and all related issues and complications. We also preview too many challenges about sensor nodes and the proposed solutions till now and we make a spot ongoing research activities and issues that affect security and performance of Wireless Sensor Network as well. Then we discuss what’s meant by security objectives, requirements and threat models. Finally, we make a spot on key management operations, goals, constraints, evaluation metrics, different encryption key types and dynamic key management schemes.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129388367","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 : 2019-02-28DOI: 10.5121/ijcses.2019.10101
Sanusi Mohammed Bunu, Murtala Muhammad, Hamid A. Adamu
Telecommunication network infrastructure determines the strength of a country for successful communication with other parts of the world. Due to the rapid increase of internet usage and mobile communication in every part of the world, specifically the third world countries, Nigeria is among the countries that is advancing in the used of telecommunication contraptions. The Nigerian Telecommunication Industries play a vital role in boosting the social and economic infrastructure of the country. This paper is aimed at investigating the Telecommunication Network infrastructure in the Northwestern part of Nigerian and propose some technologies that increase data bandwidth and internet penetration in the region. Problems and future solutions to the existing network infrastructure in the province were discussed and basic analysis is conducted to justify the importance of the study. Mobile market analysis, current infrastructure, parameters evaluation and the way forward to the problems are discussed. Comparative analysis between the existing network infrastructure that is 3G networks and the proffer solution to the existing standard which is 4G network is also conducted. This paper also conducts an analysis on the existing Network providers in the region with their draw backs and the quality of services they provide to the customers within the region. The paper concludes with a future plan of coming up with an analytical solution in order to study the implementation process of a full 4G network in the Northwest region of Nigeria and to use a simulated environment to test the proposed model for viability.
{"title":"REVIEW AND ANALYSIS ON TELECOMMUNICATION NETWORKS INFRASTRUCTURE IN THE NORTHWEST PROVINCE OF NIGERIA FOR OPTIMISATION: PROBLEMS AND SOLUTIONS","authors":"Sanusi Mohammed Bunu, Murtala Muhammad, Hamid A. Adamu","doi":"10.5121/ijcses.2019.10101","DOIUrl":"https://doi.org/10.5121/ijcses.2019.10101","url":null,"abstract":"Telecommunication network infrastructure determines the strength of a country for successful communication with other parts of the world. Due to the rapid increase of internet usage and mobile communication in every part of the world, specifically the third world countries, Nigeria is among the countries that is advancing in the used of telecommunication contraptions. The Nigerian Telecommunication Industries play a vital role in boosting the social and economic infrastructure of the country. This paper is aimed at investigating the Telecommunication Network infrastructure in the Northwestern part of Nigerian and propose some technologies that increase data bandwidth and internet penetration in the region. Problems and future solutions to the existing network infrastructure in the province were discussed and basic analysis is conducted to justify the importance of the study. Mobile market analysis, current infrastructure, parameters evaluation and the way forward to the problems are discussed. Comparative analysis between the existing network infrastructure that is 3G networks and the proffer solution to the existing standard which is 4G network is also conducted. This paper also conducts an analysis on the existing Network providers in the region with their draw backs and the quality of services they provide to the customers within the region. The paper concludes with a future plan of coming up with an analytical solution in order to study the implementation process of a full 4G network in the Northwest region of Nigeria and to use a simulated environment to test the proposed model for viability.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126523848","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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