University of Colorado Denver
Computer Science And Engineering
Background: Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) of peptides from complex digests with theoretically derived... more
Background: Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) of peptides from complex digests with theoretically derived spectra from a database of protein sequences. Improved discrimination is achieved with theoretical spectra that are based on simulating gas phase chemistry of the peptides, but the limited understanding of those processes affects the accuracy of predictions from theoretical spectra. Results: We employed a robust data mining strategy using new feature annotation functions of MAE software, which revealed under-prediction of the frequency of occurrence in fragmentation of the second peptide bond. We applied methods of exploratory data analysis to pre-process the information in the MS/MS spectra, including data normalization and attribute selection, to reduce the attributes to a smaller, less correlated set for machine learning studies. We then compared our rule building machine learning program, DataSqueezer, with commonly used association rules and decision tree algorithms. All used machine learning algorithms produced similar results that were consistent with expected properties for a second gas phase mechanism at the second peptide bond. Conclusion: The results provide compelling evidence that we have identified underlying chemical properties in the data that suggest the existence of an additional gas phase mechanism for the second peptide bond. Thus, the methods described in this study provide a valuable approach for analyses of this kind in the future.
Different types of encryption techniques are used for many years to secure the information. The purpose of this paper is to construct a new method named as Vigenere-Multiplicative cipher. Here we develop the algorithm and its algebraic... more
Different types of encryption techniques are used for many years to secure the information. The purpose of this paper is to construct a new method named as Vigenere-Multiplicative cipher. Here we develop the algorithm and its algebraic description. In addition, we provide the frequency analysis of this method. Further, implementation of the method, security attacks, comparisons between given cipher and most common ciphers are briefly discussed.
Large amount of money is lost to manipulate traffic system or road congestion worldwide every year. By providing the travel time for a specific road, traffic congestion can be minimized. Many approaches has been taken such Automatic... more
Large amount of money is lost to manipulate traffic
system or road congestion worldwide every year. By providing
the travel time for a specific road, traffic congestion can be
minimized. Many approaches has been taken such Automatic
Vehicle Identification, Loop Detectors etc. But this methods are
costly. In this paper, A system is proposed that provides traffic
intensity level information to the user according to recent traffic
data analysis. To minimize the traffic congestion, the paper
proposal is to use big data concept in this arena. This proposal
develops a structure of a simple XML device which is installed on a vehicle to trace and provide information of traffic intensity. It can estimate travel times in a road network accurately. Further, according to this system anyone can develop application for business process development and increase information transfer to the local user
system or road congestion worldwide every year. By providing
the travel time for a specific road, traffic congestion can be
minimized. Many approaches has been taken such Automatic
Vehicle Identification, Loop Detectors etc. But this methods are
costly. In this paper, A system is proposed that provides traffic
intensity level information to the user according to recent traffic
data analysis. To minimize the traffic congestion, the paper
proposal is to use big data concept in this arena. This proposal
develops a structure of a simple XML device which is installed on a vehicle to trace and provide information of traffic intensity. It can estimate travel times in a road network accurately. Further, according to this system anyone can develop application for business process development and increase information transfer to the local user
- by Sayed Mohsin Reza and +1
- •
- Big Data Technologies
Large amount of money is lost to manipulate traffic system or road congestion worldwide every year. By providing the travel time for a specific road, traffic congestion can be minimized. Many approaches has been taken such Automatic... more
Large amount of money is lost to manipulate traffic system or road congestion worldwide every year. By providing the travel time for a specific road, traffic congestion can be minimized. Many approaches has been taken such Automatic Vehicle Identification, Loop Detectors etc. But this methods are costly. In this paper, A system is proposed that provides traffic intensity level information to the user according to recent traffic
data analysis. To minimize the traffic congestion, the paper
proposal is to use big data concept in this arena. This proposal
develops a structure of a simple XML device which is installed on a vehicle to trace and provide information of traffic intensity. It can estimate travel times in a road network accurately. Further, according to this system anyone can develop application for business process development and increase information transfer to the local user.
data analysis. To minimize the traffic congestion, the paper
proposal is to use big data concept in this arena. This proposal
develops a structure of a simple XML device which is installed on a vehicle to trace and provide information of traffic intensity. It can estimate travel times in a road network accurately. Further, according to this system anyone can develop application for business process development and increase information transfer to the local user.
- by Sayed Mohsin Reza and +1
- •
- Application of Big Data
Software cost models and effort approximations support project supervisors to distribute resources, control budgets and agenda and develop modern practices, leading to projects completed on time and within financial plan. If cost and... more
Software cost models and effort approximations support project supervisors to distribute resources, control budgets and agenda and develop modern practices, leading to projects completed on time and within financial plan. If cost and effort are determined suspicious in software projects, suitable occasions can be missed; whereas expectant predictions can be affected to some resource losing. In the context of web development, these issues are also vital, and very challenging given that web projects have short schedules and very fluidic opportunity. Since software projects are continually changed in nature, earlier projects may not necessarily cover all aspects of a new project when used as a basis for cost estimation. Preliminary software estimation models are constructed on regression analysis or mathematical sources. This paper aims to propose an approach to develop the correctness of software effort and cost estimation using the structure of data set of a web application. All the measures collected, apart from total effort, were introduced using the original web hypermedia applications to ensure that functional measurement types were precisely measured.
This paper proposes a low cost and portable patient monitoring system for e-Health services in Bangladesh. A raspberry pi microcomputer based system has been developed which can be used by paramedics for collecting different sensor data... more
This paper proposes a low cost and portable patient
monitoring system for e-Health services in Bangladesh. A
raspberry pi microcomputer based system has been developed
which can be used by paramedics for collecting different sensor
data such as ECG signal, blood pressure signal, heart beat signal,
Situation of Oxygen in Blood(SPO2), temperature and generating
different signals from a patient and send these signals to specialist
doctor who are in a centre or in a hospital. A web based
application has been developed for both doctor and paramedics
for efficient communicate with each other. It has been found
that the system can be suitable for village health care centre of
Bangladesh.
monitoring system for e-Health services in Bangladesh. A
raspberry pi microcomputer based system has been developed
which can be used by paramedics for collecting different sensor
data such as ECG signal, blood pressure signal, heart beat signal,
Situation of Oxygen in Blood(SPO2), temperature and generating
different signals from a patient and send these signals to specialist
doctor who are in a centre or in a hospital. A web based
application has been developed for both doctor and paramedics
for efficient communicate with each other. It has been found
that the system can be suitable for village health care centre of
Bangladesh.
- by Sayed Mohsin Reza and +1
- •
- Software Engineering
Dense exhale flow through carbon-dioxide spectral imaging introduces a pivotal trajectory within non-contact respiratory analysis that consolidates several pulmonary evaluations into a single coherent monitoring process. Due to technical... more
Dense exhale flow through carbon-dioxide spectral imaging introduces a pivotal trajectory within non-contact respiratory analysis that consolidates several pulmonary evaluations into a single coherent monitoring process. Due to technical limitations and the limited exploration of respiratory analysis through this non-contact technique, this method has not been fully utilized to extract high-level respiratory behaviors through turbulent exhale analysis. In this work, we present a structural foundation for respiratory analysis of turbulent exhale flows through the visualization of dense carbon-dioxide density distributions using precisely refined thermal imaging device to target high-resolution respiratory modeling. We achieve spatial and temporal high-resolution flow reconstructions through the cooperative development of a thermal camera dedicated to respiratory analysis to drastically improve the precision of current exhale imaging methods. We then model turbulent exhale behaviors using a heuristic volumetric flow reconstruction process to generate sparse flow exhale models. Together these contributions allow us to target the acquisition of numerous respiratory behaviors including, breathing rate, exhale strength and capacity, towards insights into lung functionality and tidal volume estimation.
Mining Software Repositories (MSR) has opened up new pathways and rich sources of data for research and practical purposes. This research discipline facilitates mining data from open source repositories and analyzing software defects,... more
Mining Software Repositories (MSR) has opened up new pathways and rich sources of data for research and practical purposes. This research discipline facilitates mining data from open source repositories and analyzing software defects, development activities, processes, patterns, and more. Contemporary mining tools are geared towards data extraction, analysis primarily from textual artifacts and have limitations in representation, ranking and availability. This paper presents ModelMine, a novel mining tool focuses on mining model-based artifacts and designs from open source repositories. ModelMine is designed particularly to mine software repositories, artifacts and commit history to uncover information about software designs and practices in open-source communities. ModelMine supports features that include identification and ranking of open source repositories based on the extent of the presence of model-based artifacts and querying repositories to extract models and design artifacts based on customizable criteria. It supports phase-by-phase caching of intermediate results to speed up the processing to enable efficient mining of data. We compare ModelMine against a state-of-the-art tool named PyDriller in terms of performance and usability. The results show that ModelMine has the potential to become instrumental for cross-disciplinary research that combines modeling and design with repository mining and artifacts extraction. URL: https://www.smreza.com/projects/modelmine/
Software design is fundamental to developing high-quality, sustainable, maintainable software. Design languages, such as UML, have become the defacto standard in software design, but their infiltration in the mainstream practices remains... more
Software design is fundamental to developing high-quality, sustainable, maintainable software. Design languages, such as UML, have become the defacto standard in software design, but their infiltration in the mainstream practices remains vague. Recent studies suggest significant and increasing uptake in mainstream and open source spheres. Mining repositories and the software modeling artifacts often underpin the findings of these studies and focus on counting the instances of modeling artifacts as an indicator for adoption. This study aims to characterize this uptake in greater depth by focusing on analyzing the instances of models in open source projects. The goal is to uncover the profiles of developers who tend to create modeling artifacts, and those developers who maintain them throughout the project life cycle and to uncover the timelines of model creation and manipulation in reference to project evolution. This study sheds light on the nature of modelbased collaboration and in...
Dense exhale flow through CO2 spectral imaging introduces a pivotal trajectory within non-contact respiratory analysis that consolidates several pulmonary evaluations into a single coherent monitoring process. Due to technical limitations... more
Dense exhale flow through CO2 spectral imaging introduces a pivotal trajectory within non-contact respiratory analysis that consolidates several pulmonary evaluations into a single coherent monitoring process. Due to technical limitations and the limited exploration of respiratory analysis through this non-contact technique, this method has not been fully utilized to extract high-level respiratory behaviors through turbulent exhale analysis. In this work, we present a structural foundation for respiratory analysis of turbulent exhale flows through the visualization of dense CO2 density distributions using precisely refined thermal imaging device to target high-resolution respiratory modeling. We achieve spatial and temporal highresolution flow reconstructions through the cooperative development of a thermal camera dedicated to respiratory analysis to drastically improve the precision of current exhale imaging methods. We then model turbulent exhale behaviors using a heuristic volumetric flow reconstruction process to generate sparse flow exhale models. Together these contributions allow us to target the acquisition of numerous respiratory behaviors including, breathing rate, exhale strength and capacity, towards insights into lung functionality and tidal volume estimation.
Bangladesh is one of the most promising developing countries in IT sector, where people from several disciplines and experiences are involved in this sector. However, no direct analysis in this sector is published yet, which covers the... more
Bangladesh is one of the most promising developing countries in IT sector, where people from several disciplines and experiences are involved in this sector. However, no direct analysis in this sector is published yet, which covers the proper guideline for predicting future IT personnel. Hence this is not a simple solution, training data from real IT sector are needed and trained several classifiers for detecting perfect results. Machine learning algorithms can be used for predicting future potential IT personnel. In this paper, four different classifiers named as Naive Bayes, J48, Bagging and Random Forest in five different folds are experimented for that prediction. Results are pointed out that Random Forest performs better accuracy than other experimented classifier for future IT personnel prediction. It is mentioned that the standard accuracy measurement process named as Precision, Recall, F-Measure, ROC Area etc. are used for evaluating the results.
The dataset contains quality, source code metrics information of 60 versions under 10 different repositories. The dataset is extracted into 3 levels: (1) Class (2) Method (3) Package. The dataset is created upon analyzing 9,420,246 lines... more
The dataset contains quality, source code metrics information of 60 versions under 10 different repositories. The dataset is extracted into 3 levels: (1) Class (2) Method (3) Package. The dataset is created upon analyzing 9,420,246 lines of code and 173,237 classes. The provided dataset contains one quality_attributes folder and three associated files: repositories.csv, versions.csv, and attribute-details.csv. The first file (repositories.csv) contains general information(repository name, repository URL, number of commits, stars, forks, etc) in order to understand the size, popularity, and maintainability. File versions.csv contains general information (version unique ID, number of classes, packages, external classes, external packages, version repository link) to provide an overview of versions and how overtime the repository continues to grow. File attribute-details.csv contains detailed information (attribute name, attribute short form, category, and description) about extracted ...