JINAV: Journal of Information and Visualization
JINAV: Journal of Information and Visualization is an international peer-reviewed open-access journal dedicated to interchange for the results of high-quality research in all aspects of information science and technology, data, knowledge, communication, and their visualization. The journal publishes state-of-art papers in fundamental theory, experiments, and simulation, as well as applications, with a systematic proposed method, sufficient review on previous works, expanded discussion, and concise conclusion. As our commitment to the advancement of science and technology, the JINAV follows the open access policy that allows the published articles freely available online without any subscription.
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<![CDATA[Information on Domestic staff utilisation and household crimes ]]>
<![CDATA[Attah, Frank M.]]>;
<![CDATA[Agba, A. M. Ogaboh]]>;
<![CDATA[Ibiam, Azu A.]]>;
<![CDATA[Kaburise, Phyllis K.]]>;
<![CDATA[Kulo, Collins]]>
<![CDATA[ JINAV: Journal of Information and Visualization Vol. 2 No. 2 (2021) ]]>
Publisher : <![CDATA[Yayasan Ahmar Cendekia Indonesia ]]>
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DOI: 10.35877/454RI.jinav284
<![CDATA[Hiring of domestic staff and its effect on households’ crime has been an issues of great concern in Nigeria. This study is sets to investigate the correlates between domestic staff utilisation and crimes such as kidnapping, stealing and rape. Blocked opportunity theory and structural functionalism theory were adopted. Cross-sectional survey design was used while data was generated view questionnaire. A total sample of 330 respondents were selected from households in Southern Senatorial District of Cross River State, Nigeria. Information retrieved were coded and subjected to statistical analysis. Outcome revealed a significant relationship between the hiring of domestic staff and household crimes (such as kidnapping, stealing and rape). It was recommended among others that house helps should be passably screened through proper employment procedures before they are employed as domestic staff.]]>
<![CDATA[Attitudes of health workers and outpatients’ recovery in public hospitals in Calabar Metropolis, Nigeria: An Information Analysis ]]>
<![CDATA[Agba, A. M. Ogaboh]]>;
<![CDATA[Ojong, Felix E.]]>;
<![CDATA[Akintola, Abayomi I.]]>;
<![CDATA[Maruf, Gbadebo S.]]>;
<![CDATA[Udom, Hannah T.]]>;
<![CDATA[Usung, Essienawan U.]]>
<![CDATA[ JINAV: Journal of Information and Visualization Vol. 2 No. 2 (2021) ]]>
Publisher : <![CDATA[Yayasan Ahmar Cendekia Indonesia ]]>
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DOI: 10.35877/454RI.jinav351
<![CDATA[The study is an information analysis about the assessed awareness of the attitudes of health workers and outpatients’ recovery in public hospitals in Nigeria. Specifically, the study examined negligence and aggressive behaviour by health workers on outpatients’ recovery in public hospitals. The study was carried out in public hospitals in Calabar Metropolis, Nigeria. The cross-sectional design method was adopted to collect empirical data from outpatient in the hospitals for three months. The study adopted the purposive and volunteer sampling techniques in identifying 400 respondents for the study. Data collected were analysed using simple percentages and Chi-squared statistical tools. Results revealed that there is significant relationship between negligence by health workers and outpatients’ recovery (χ2 = 13.45 ≥ 7.815), health workers’ aggression significantly affect outpatients’ recovery (χ2 = 97.09 ≥ 7.815). Based on these findings, it was recommended among others that management of public hospitals should put on measures to curtail attitudes of negligence by staff towards patients, by installing closed-circuit television (CCTV) cameras specifically along service points. Management of public hospitals should impose stiff and stringent penalties on staff found to be aggressive towards patients.]]>
<![CDATA[Python for Automating Machine Learning Tasks ]]>
<![CDATA[Mshvidobadze, Tinatin]]>
<![CDATA[ JINAV: Journal of Information and Visualization Vol. 2 No. 2 (2021) ]]>
Publisher : <![CDATA[Yayasan Ahmar Cendekia Indonesia ]]>
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DOI: 10.35877/454RI.jinav373
<![CDATA[Machine learning is used in a variety of computational tasks where designing and programming explicit algorithms with good performance is not easy. Applications include email filtering, recognition of network intruders or malicious insiders working towards a data breach. In this article we will focus on basics of machine learning, tasks and problems and various machine learning algorithms. The article discusses the Python programming language as the best language for automating machine learning tasks.]]>
<![CDATA[Multi-Agent Bayesian Framework For Parametric Selection In The Detection And Diagnosis of Tuberculosis Contagion In Nigeria ]]>
<![CDATA[Ojugo, Arnold Adimabua]]>;
<![CDATA[Nwankwo, Obinna]]>
<![CDATA[ JINAV: Journal of Information and Visualization Vol. 2 No. 2 (2021) ]]>
Publisher : <![CDATA[Yayasan Ahmar Cendekia Indonesia ]]>
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DOI: 10.35877/454RI.jinav375
<![CDATA[Decision making has become quite a critical factor in our everyday living. The provision of data alongside its consequent processing has further sought to extend and expand our reasoning faculties as well as effectively aid proper decision making. But data is daily, produced at an exponential rapid rate and the volume in amount of data churned out to be processed even more so that we now require data storage optimization techniques to process such humongous volume of data. These have today, necessitated the need for advancement in data mining process. With the tremendous advances made in data mining, machine learning, storage virtualization and optimization – amongst other fields of computing – researchers now seek a new paradigm and platform called data science. This field today has become quite imperative as it seeks to provide beneficial support in constructing models and algorithms that can effectively assist domain experts and practitioners to make comprehensive and sound decisions regarding potential problematic cases. We focus on modeling social graph using implicit suggest algorithm in medical diagnosis to effectively respond to problematic cases of Tuberculosis (TB) in Nigeria. We introduce spectral clustering and Bayesian Network, construct algorithms cum models for predicting potential problematic cases in Tuberculosis as well as compare the algorithms based on data samples collected from an Epidemiology laboratory at the Federal Medical Center Asaba in Delta State of Nigeria. The volume of data was collated and divided into two data sets which are the training dataset and the investigation dataset. The model constructed by this study has shown a high predictive capability strength compared to other models presented on similar studies.]]>
<![CDATA[Migration Pattern As Threshold Parameter In The Propagation of The Covid-19 Epidemic Using An Actor-Based Model for SI-Social Graph ]]>
<![CDATA[Ojugo, Arnold Adimabua]]>;
<![CDATA[Yoro, Rume Elizabeth]]>
<![CDATA[ JINAV: Journal of Information and Visualization Vol. 2 No. 2 (2021) ]]>
Publisher : <![CDATA[Yayasan Ahmar Cendekia Indonesia ]]>
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DOI: 10.35877/454RI.jinav379
<![CDATA[Despite the benefits inherent with social interactions, the case of epidemics cum pandemic outbreaks especially the case of the novel corona virus (covid-19) alongside its set protocols employed to contain the spread therein - has continually left the world puzzled as the disease itself has come to stay. The nature of its rapid propagation on exposure alongside its migration spread pattern of this contagion (with retrospect of other epidemics) on daily basis, has also left experts rethinking the set protocols. Our study involved modelling the covid-19 contagion on a social graph, so as to ascertain if its propagation using migration pattern as a threshold parameter can be minimized via the employment of set protocols. We also employed a design that sought to block or minimize targeted spread of the contagion with the introduction of seedset node(s) using the susceptible-infect framework on a time-varying social graph. Study results showed that migration or mobility pattern has become an imperative factors that must be added when modelling the propagation of contagion or epidemics.]]>
<![CDATA[Information on Domestic staff utilisation and household crimes ]]>
<![CDATA[Frank M. Attah]]>;
<![CDATA[A. M. Ogaboh Agba]]>;
<![CDATA[Azu A. Ibiam]]>;
<![CDATA[Phyllis K. Kaburise]]>;
<![CDATA[Collins Kulo]]>
<![CDATA[ JINAV: Journal of Information and Visualization Vol. 2 No. 2 (2021) ]]>
Publisher : <![CDATA[PT Mattawang Mediatama Solution ]]>
Show Abstract
|
Download Original
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Original Source
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Check in Google Scholar
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DOI: 10.35877/454RI.jinav284
<![CDATA[Hiring of domestic staff and its effect on households’ crime has been an issues of great concern in Nigeria. This study is sets to investigate the correlates between domestic staff utilisation and crimes such as kidnapping, stealing and rape. Blocked opportunity theory and structural functionalism theory were adopted. Cross-sectional survey design was used while data was generated view questionnaire. A total sample of 330 respondents were selected from households in Southern Senatorial District of Cross River State, Nigeria. Information retrieved were coded and subjected to statistical analysis. Outcome revealed a significant relationship between the hiring of domestic staff and household crimes (such as kidnapping, stealing and rape). It was recommended among others that house helps should be passably screened through proper employment procedures before they are employed as domestic staff.]]>
<![CDATA[Attitudes of health workers and outpatients’ recovery in public hospitals in Calabar Metropolis, Nigeria: An Information Analysis ]]>
<![CDATA[A. M. Ogaboh Agba]]>;
<![CDATA[Felix E. Ojong]]>;
<![CDATA[Abayomi I. Akintola]]>;
<![CDATA[Gbadebo S. Maruf]]>;
<![CDATA[Hannah T. Udom]]>;
<![CDATA[Essienawan U. Usung]]>
<![CDATA[ JINAV: Journal of Information and Visualization Vol. 2 No. 2 (2021) ]]>
Publisher : <![CDATA[PT Mattawang Mediatama Solution ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35877/454RI.jinav351
<![CDATA[The study is an information analysis about the assessed awareness of the attitudes of health workers and outpatients’ recovery in public hospitals in Nigeria. Specifically, the study examined negligence and aggressive behaviour by health workers on outpatients’ recovery in public hospitals. The study was carried out in public hospitals in Calabar Metropolis, Nigeria. The cross-sectional design method was adopted to collect empirical data from outpatient in the hospitals for three months. The study adopted the purposive and volunteer sampling techniques in identifying 400 respondents for the study. Data collected were analysed using simple percentages and Chi-squared statistical tools. Results revealed that there is significant relationship between negligence by health workers and outpatients’ recovery (χ2 = 13.45 ≥ 7.815), health workers’ aggression significantly affect outpatients’ recovery (χ2 = 97.09 ≥ 7.815). Based on these findings, it was recommended among others that management of public hospitals should put on measures to curtail attitudes of negligence by staff towards patients, by installing closed-circuit television (CCTV) cameras specifically along service points. Management of public hospitals should impose stiff and stringent penalties on staff found to be aggressive towards patients.]]>
<![CDATA[Python for Automating Machine Learning Tasks ]]>
<![CDATA[Tinatin Mshvidobadze]]>
<![CDATA[ JINAV: Journal of Information and Visualization Vol. 2 No. 2 (2021) ]]>
Publisher : <![CDATA[PT Mattawang Mediatama Solution ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35877/454RI.jinav373
<![CDATA[Machine learning is used in a variety of computational tasks where designing and programming explicit algorithms with good performance is not easy. Applications include email filtering, recognition of network intruders or malicious insiders working towards a data breach. In this article we will focus on basics of machine learning, tasks and problems and various machine learning algorithms. The article discusses the Python programming language as the best language for automating machine learning tasks.]]>
<![CDATA[Multi-Agent Bayesian Framework For Parametric Selection In The Detection And Diagnosis of Tuberculosis Contagion In Nigeria ]]>
<![CDATA[Arnold Adimabua Ojugo]]>;
<![CDATA[Obinna Nwankwo]]>
<![CDATA[ JINAV: Journal of Information and Visualization Vol. 2 No. 2 (2021) ]]>
Publisher : <![CDATA[PT Mattawang Mediatama Solution ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35877/454RI.jinav375
<![CDATA[Decision making has become quite a critical factor in our everyday living. The provision of data alongside its consequent processing has further sought to extend and expand our reasoning faculties as well as effectively aid proper decision making. But data is daily, produced at an exponential rapid rate and the volume in amount of data churned out to be processed even more so that we now require data storage optimization techniques to process such humongous volume of data. These have today, necessitated the need for advancement in data mining process. With the tremendous advances made in data mining, machine learning, storage virtualization and optimization – amongst other fields of computing – researchers now seek a new paradigm and platform called data science. This field today has become quite imperative as it seeks to provide beneficial support in constructing models and algorithms that can effectively assist domain experts and practitioners to make comprehensive and sound decisions regarding potential problematic cases. We focus on modeling social graph using implicit suggest algorithm in medical diagnosis to effectively respond to problematic cases of Tuberculosis (TB) in Nigeria. We introduce spectral clustering and Bayesian Network, construct algorithms cum models for predicting potential problematic cases in Tuberculosis as well as compare the algorithms based on data samples collected from an Epidemiology laboratory at the Federal Medical Center Asaba in Delta State of Nigeria. The volume of data was collated and divided into two data sets which are the training dataset and the investigation dataset. The model constructed by this study has shown a high predictive capability strength compared to other models presented on similar studies.]]>
<![CDATA[Migration Pattern As Threshold Parameter In The Propagation of The Covid-19 Epidemic Using An Actor-Based Model for SI-Social Graph ]]>
<![CDATA[Arnold Adimabua Ojugo]]>;
<![CDATA[Rume Elizabeth Yoro]]>
<![CDATA[ JINAV: Journal of Information and Visualization Vol. 2 No. 2 (2021) ]]>
Publisher : <![CDATA[PT Mattawang Mediatama Solution ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35877/454RI.jinav379
<![CDATA[Despite the benefits inherent with social interactions, the case of epidemics cum pandemic outbreaks especially the case of the novel corona virus (covid-19) alongside its set protocols employed to contain the spread therein - has continually left the world puzzled as the disease itself has come to stay. The nature of its rapid propagation on exposure alongside its migration spread pattern of this contagion (with retrospect of other epidemics) on daily basis, has also left experts rethinking the set protocols. Our study involved modelling the covid-19 contagion on a social graph, so as to ascertain if its propagation using migration pattern as a threshold parameter can be minimized via the employment of set protocols. We also employed a design that sought to block or minimize targeted spread of the contagion with the introduction of seedset node(s) using the susceptible-infect framework on a time-varying social graph. Study results showed that migration or mobility pattern has become an imperative factors that must be added when modelling the propagation of contagion or epidemics.]]>
