Musabe Jean Bosco
Musabe Jean Bosco was born in Huye, Rwanda, in 1985. He received a - Ph.D. and a master's in the research in Computational intelligence, Data mining, and knowledge discovery from Chongqing University of Posts and Telecommunications in China.
A dynamic, talented, international experienced, and committed manager. Extensive experience in Artificial Intelligent, Machine Learning, and Deep Learning with excellent knowledge in Data Science, data-driven, and Information knowledge discovery. My summary profile combines academic and professional experience in research interests such as Big data, data mining, granular computing, Multi-Granularity, cognitive computing, cloud computing, Fuzzy Algorithms, and machine learning algorithms. PhD Degree in Computer Science and Technology. I have more than 10 years of working experience as a research advisor and my research interests were based on the study of computational intelligence within the fields of Multi-granularity Remote Sensing, Land Change Science, Land Cover, and Land Use (LCLU), and Conservation. AI Environmental consultancy specifically in intelligent information processing, data analytics, designing, and managing rigorous, monitoring, training and education, data management, evaluation, and visualization system frameworks. Within such interdisciplinary teams, my particular strengths lie in the remote sensing of vegetation dynamics, land use and land cover change, and protected area management.
I am expertise covers the entire Computational Intelligent Framework (CIF) including exploratory research methods, sampling and measurement designs, research implementation, big data exploration, and visualization and quality assurance as well as qualitative analysis using python for big data analysis, deep learning, ArcGIS, ArcMap, and quantitative data analysis using the following statistical package software such as STATA and SPSS, questionnaire design and questionnaire programming in-field data collection software such as SurveyCTO, kobotoolbox, ODK, ONA, and CsPro, online field data collection monitoring and management, and visited – areas online mapping. I am expert in Data analysis using different methods including Apache Hadoop, Arche Spark, IoT, NoSQL, NewSQL Databases, Microsoft Azure HD Insight, HDFS, MapReduce, YARN, principal component analysis (PCA), multiple correspondence analysis (MCA), factor analysis (FA), cluster analysis, structural equation models (regression analysis (single and multivariate analysis), cross-tabulations and correlations, random forest (RF), support vector machine (SVM), decision tree (DT), multiple linear regression (MLR), logistic regression, k-nearest neighbor (K-NN), K-Mean (K-M), Naïve Bayes, hierarchical clustering, model selection and boosting such ad k-folder cross-validation, parameter tuning, gird search and XGBoost. I have been a consultant in many consultancies financed by Zhongzaisheng Environment Service Co., Chongqing Linkai Technology Co.
Phone: 0788355628
Address: Kigali
Rwanda
Africa
A dynamic, talented, international experienced, and committed manager. Extensive experience in Artificial Intelligent, Machine Learning, and Deep Learning with excellent knowledge in Data Science, data-driven, and Information knowledge discovery. My summary profile combines academic and professional experience in research interests such as Big data, data mining, granular computing, Multi-Granularity, cognitive computing, cloud computing, Fuzzy Algorithms, and machine learning algorithms. PhD Degree in Computer Science and Technology. I have more than 10 years of working experience as a research advisor and my research interests were based on the study of computational intelligence within the fields of Multi-granularity Remote Sensing, Land Change Science, Land Cover, and Land Use (LCLU), and Conservation. AI Environmental consultancy specifically in intelligent information processing, data analytics, designing, and managing rigorous, monitoring, training and education, data management, evaluation, and visualization system frameworks. Within such interdisciplinary teams, my particular strengths lie in the remote sensing of vegetation dynamics, land use and land cover change, and protected area management.
I am expertise covers the entire Computational Intelligent Framework (CIF) including exploratory research methods, sampling and measurement designs, research implementation, big data exploration, and visualization and quality assurance as well as qualitative analysis using python for big data analysis, deep learning, ArcGIS, ArcMap, and quantitative data analysis using the following statistical package software such as STATA and SPSS, questionnaire design and questionnaire programming in-field data collection software such as SurveyCTO, kobotoolbox, ODK, ONA, and CsPro, online field data collection monitoring and management, and visited – areas online mapping. I am expert in Data analysis using different methods including Apache Hadoop, Arche Spark, IoT, NoSQL, NewSQL Databases, Microsoft Azure HD Insight, HDFS, MapReduce, YARN, principal component analysis (PCA), multiple correspondence analysis (MCA), factor analysis (FA), cluster analysis, structural equation models (regression analysis (single and multivariate analysis), cross-tabulations and correlations, random forest (RF), support vector machine (SVM), decision tree (DT), multiple linear regression (MLR), logistic regression, k-nearest neighbor (K-NN), K-Mean (K-M), Naïve Bayes, hierarchical clustering, model selection and boosting such ad k-folder cross-validation, parameter tuning, gird search and XGBoost. I have been a consultant in many consultancies financed by Zhongzaisheng Environment Service Co., Chongqing Linkai Technology Co.
Phone: 0788355628
Address: Kigali
Rwanda
Africa
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Papers by Musabe Jean Bosco
issues with the help of skilled specialists. Existing customers answer
new consumers' inquiries and concerns. These questions may come
from new or existing clients. Call centers are important in Rwanda as
they enable companies to monitor calls. Companies can also analyze
their markets through data acquired through call centers. However,
setting up a call center is expensive. The running costs of a call center
are also large. Businesses that operate call centers spend a lot of
money running them, consequently reducing their profits. Therefore,
this study proposes a cheaper technique for handling call traffic
implemented using free PBX, which is a Linux based web-application
for monitoring call traffic. From the results of the simulations carried
out, a fast connection between mobile phones was observed. Moreover,
it was determined that the capacity of free PBX is unlimited, making it
ideal for use in call centers. The analysis shows that this project can be
implemented in different institutions on chipper prices. The existing
cost of implementing a call center on 50 users using hardware PBX is
100.000 USD, whereas, with the proposed solution using FreePBX
which is a Linux based web-application for monitoring call traffic, the
implementation cost can be between 5000 USD and 10000 USD with
the same range of users. The discounted price as compared to the
existing system can be estimated to be around 90%, which is much
cheaper.
Book Reviews by Musabe Jean Bosco
issues with the help of skilled specialists. Existing customers answer
new consumers' inquiries and concerns. These questions may come
from new or existing clients. Call centers are important in Rwanda as
they enable companies to monitor calls. Companies can also analyze
their markets through data acquired through call centers. However,
setting up a call center is expensive. The running costs of a call center
are also large. Businesses that operate call centers spend a lot of
money running them, consequently reducing their profits. Therefore,
this study proposes a cheaper technique for handling call traffic
implemented using free PBX, which is a Linux based web-application
for monitoring call traffic. From the results of the simulations carried
out, a fast connection between mobile phones was observed. Moreover,
it was determined that the capacity of free PBX is unlimited, making it
ideal for use in call centers. The analysis shows that this project can be
implemented in different institutions on chipper prices. The existing
cost of implementing a call center on 50 users using hardware PBX is
100.000 USD, whereas, with the proposed solution using FreePBX
which is a Linux based web-application for monitoring call traffic, the
implementation cost can be between 5000 USD and 10000 USD with
the same range of users. The discounted price as compared to the
existing system can be estimated to be around 90%, which is much
cheaper.