Rashid Naseem

Rashid Naseem
Pak-Austria Fachhochschule: Institute of Applied Sciences and Technology · Department of IT and Computer Science

PhD in IT (Software Engineering)

About

53
Publications
37,680
Reads
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612
Citations
Citations since 2017
35 Research Items
559 Citations
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2017201820192020202120222023050100150
2017201820192020202120222023050100150
Introduction
Rashid Naseem currently works at the Department of Computer Science, City University of Science and Information Technology. Rashid does research in Software Engineering and Data Mining. Their current projects are 'Mobile Forensic Triage For Damaged Phones Using M_Triage', and 'Software Modularization'.
Additional affiliations
March 2014 - November 2016
Universiti Tun Hussein Onn Malaysia
Position
  • PhD
January 2014 - October 2016
Universiti Tun Hussein Onn Malaysia
Position
  • PhD
January 2012 - March 2014
City University of Science and Information Technology
Position
  • Lecturer
Education
April 2014 - March 2017
Universiti Tun Hussein Onn Malaysia
Field of study
  • Computer Science
February 2009 - September 2011
Quaid-i-Azam University
Field of study
  • Computer Science
September 2004 - September 2008
University of Peshawar
Field of study
  • Computer Science

Publications

Publications (53)
Article
Full-text available
Complex software systems, meant to facilitate organizations, undergo frequent upgrades that can erode the system architectures. Such erosion makes understandability and maintenance a challenging task. To this end, software modularization provides an architectural-level view that helps to understand system architecture from its source code. For modu...
Article
Full-text available
Complex software systems that support organizations are updated regularly, which can erode system architectures. Moreover, documentation is rarely synchronized with the changes to the software system. is creates a slew of issues for future software maintenance. To this goal, information extraction tools use exact approaches to extract entities and...
Article
Full-text available
Software defect prediction (SDP) in the initial period of the software development life cycle (SDLC) remains a critical and important assignment. SDP is essentially studied during few last decades as it leads to assure the quality of software systems. The quick forecast of defective or imperfect artifacts in software development may serve the devel...
Article
Full-text available
The web is being loaded daily with a huge volume of data, mainly unstructured textual data, which increases the need for information extraction and NLP systems significantly. Named-entity recognition task is a key step towards efficiently understanding text data and saving time and effort. Being a widely used language globally, English is taking ov...
Article
Full-text available
Software risk prediction is the most sensitive and crucial activity of Software Development Life Cycle (SDLC). It may lead to the success or failure of a project. The risk should be predicted earlier to make a software project successful. A Model is proposed for the prediction of software requirement risks using requirement risk dataset and machine...
Article
Full-text available
In the recent era, a liver syndrome that causes any damage in life capacity is exceptionally normal everywhere throughout the world. It has been found that liver disease is exposed more in young people as a comparison with other aged people. At the point when liver capacity ends up, life endures just up to 1 or 2 days scarcely, and it is very hard...
Article
Full-text available
The rapidly growing data in many areas, as well as in the biomedical domain, require the assistance of information extraction systems to acquire the much needed knowledge about specific entities such as proteins, drugs, or diseases practically within a short time. Annotated corpora serve the purpose of facilitating the process of building NLP syste...
Article
Software Development Organizations (SDO) develop a massive number of projects per year. One of the elementary and significant features of any SDO is to use a tool that can precisely estimate the software cost. It directly affects nearly all management activities including resource allocation, project planning, and project bidding. Imprecise estimat...
Article
Full-text available
In ongoing time liver disease that isany damage in the liver capacity, are exceptionally normal everywhere throughout the world.It has been found that liver disease is discovered more in youthful people as a contrast with other age people. At the point when liver capacity becomesend up, life enduresjust can be up to 1 or 2 days scarcely.Analysts or...
Chapter
Decision Support System (DSS) is a new trend in technology which provides decisions to users based on the information. Nowadays, it is being used in many fields and, it is becoming an essential part of the dental clinic. Many dental diseases are now detecting with the DSS and many treatments for dental diseases are providing through it. Therefore,...
Article
Full-text available
Auto-encoders (AEs) have been proposed for solving many problems in the domain of machine learning and deep learning since the last few decades. Due to their satisfactory performance, their multiple variations have also recently appeared. First, we introduce the conventional AE model and its different variant for learning abstract features from dat...
Article
Full-text available
Chronic Kidney Disease (CKD) implies that the human kidneys are harmed and unable to blood filter in the manner which they should. The disease is designated "chronic" in light of the fact that harm to human kidneys happen gradually over a significant time. This harm can make wastes to build up in your body. Many techniques and models have been deve...
Chapter
In the recent, the World Wide Web has become a platform for online news publications. Many sources started publishing digital versions of news articles online to vast users through a variety of devices, i.e. television channels, magazines, and newspapers. It is observed that the news articles available can be very huge and recommendation systems ca...
Chapter
Bat algorithm lags behind other modern metaheuristic algorithms in terms of search efficiency, due to premature convergence. Once trapped in any sub-optimal region, the algorithm is unable to escape because of deficiency in population diversity. To address this, an enhanced Bat Algorithm (EBA) is introduced in this paper. The EBA algorithm comes wi...
Article
Full-text available
Assigning accurate and timely priorities to bugs manually is resource consuming and effects addressing important bugs. In the existing work single feature is used which leads to information loss because bugs have a lot of features including “severity”, “component”, “operation system”, “owner”, “status”, “assigned to”, “summary” etc. In this researc...
Conference Paper
Full-text available
Planquarium is a context-aware indoor kitchen garden system, where a user can grow fresh plants and vegetables without prior knowledge. Further, the Planquarium will take care of the plants that are inside it using a Rule-Based Context-Aware environment, that is capable to monitor different aspects of the plant and can provide an ideal environment...
Article
Full-text available
Data mining methods are often impaired by datasets with desperate nature. Such real-world datasets contain imbalanced data distributions among classes, which affects the learning process negatively. In this scenario, the number of samples pertaining to one class (majority class) surpasses adequately the number of samples of other class (minority cl...
Article
Full-text available
The problem of fetal distress usually become one of the major reason of complication during child delivery. Fetal heart rate (FHR) is one of the pivotal ways to identify the occurrence of fetal distress. Cardiotocography (CTG) is the most widely practiced technique to record FHR. Improper analysis of CTG's graph may lead to serious loss. This study...
Article
Full-text available
IEEE 802.15.4 Low data Rate Wireless Personal Area Network (LR-WPAN) standard is mainly designed for low rate, low power consumption, less coverage area and low cost networks which uses fixed duty cycle of the superframe operation. Wireless Body Area Network (WBAN) now-a-days is one of the emerging fields which uses the IEEE 802.15.4 standard. WBAN...
Article
Full-text available
Hierarchical clustering groups similar entities on the basis of some similarity (or distance) association and results in a tree like structure, called dendrogram. Dendrograms represent clusters in a nested manner, where at each step an entity makes a new cluster or merges into an existing cluster. Hierarchical clustering has many applications, ther...
Article
Full-text available
A theoretical approach of asymptote analyzes the algorithms for approximate time complexity. The worst-case asymptotic complexity classifies an algorithm to a certain class. The asymptotic complexity for algorithms returns the degree variable of the algorithmic function while ignores the lower terms. In perspective of programming, asymptote only co...
Article
Full-text available
After the advent of Web 2.0, the people are encouraged to express their views, thoughts and even share information about things happening around them. People like to express themselves about some events, places, leader's decisions, policies, etc. and for this purpose; they use social media, blogs, review sites, news sites, and user's feedback porta...
Article
Full-text available
A swarm-based metaheuristic algorithm, like artificial bee colony (ABC), embraces four key elements of collective intelligence: positive feedback, negative feedback, multiple interactions, and fluctuation. Fluctuation refers to population diversity which can be measured using dimension-wise diversity. This paper performed component-wise analysis of...
Chapter
Swarm-based metaheuristics, inspired from intelligent social behaviors in nature, have achieved wider acceptance among researchers as compared to other population-based methods. The success of any swarm-based algorithm highly depends upon the mechanism of social interaction which maintains the balance between exploration and exploitation. This rese...
Conference Paper
Full-text available
Swarm-based metaheuristics, inspired from intelligent social behaviors in nature, have achieved wider acceptance among researchers as compared to other population-based methods. The success of any swarm-based algorithm highly depends upon the mechanism of social interaction which maintains the balance between exploration and exploitation. This rese...
Article
Full-text available
In literature, benchmark test functions have been used for evaluating performance of metaheuristic algorithms. Algorithms that perform well on a set of numerical optimization problems are considered as effective methods for solving real-world problems. Different researchers choose different set of functions with varying configurations, as there exi...
Article
Various binary similarity measures have been employed in clustering approaches to make homogeneous groups of similar entities in the data. These similarity measures are mostly based only on the presence or absence of features. Binary similarity measures have also been explored with different clustering approaches (e.g., agglomerative hierarchical c...
Article
Full-text available
Sentiment analysis is the process to study of people opinion, emotion and way of considering a matter and take the decision into different categorize like positive, negative and neutral in data mining. The sentiment analysis is used to find out negation within the text using Natural Language Processing rules. Our aim is to detect negation affect on...
Article
Full-text available
Daily large number of bug reports are received in large open and close source bug tracking systems. Dealing with these reports manually utilizes time and resources which leads to delaying the resolution of important bugs. As an important process in software maintenance, bug triaging process carefully analyze these bug reports to determine, for exam...
Conference Paper
Full-text available
This paper presents a Metahybrid algorithm that consists of the dual combination of Wolf Search (WS) and Elman Recurrent Neural Network (ERNN). ERNN is one of the most efficient feed forward neural network learning algorithm. Since ERNN uses gradient descent technique during the training process; therefore, it is not devoid of local minima and slow...
Conference Paper
Different binary similarity measures have been explored with different agglomerative hierarchical clustering approaches for software clustering, to make the software systems understandable and manageable. Similarity measures have strengths and weakness that results in improving and deteriorating clustering quality. Determine whether strengths of th...
Conference Paper
Full-text available
Adaptive Neuro-Fuzzy Inference System (ANFIS) has been widely applied in industry as well as scientific problems. This is due to its ability to approximate every plant with proper number of rules. However, surge in auto-generated rules, as the inputs increase, adds up to complexity and computational cost of the network. Therefore, optimization is r...
Article
Full-text available
Mobile forensics is an exciting new field of research. An increasing number of Open source and commercial digital forensics tools are focusing on less time during digital forensic examination. There is a major issue affecting some mobile forensic tools that allow the tools to spend much time during the forensic examination. It is caused by implemen...
Conference Paper
Sentiment analysis is the process to study of people opinion, emotion and way of considering a matter and take decision into different categorizes like positive, negative and neutral in data mining. The sentiment analysis is used to find out negation within the text using Natural Language Processing rules. Our aim is to detect negation affect on co...
Article
Full-text available
Mobile forensics is an exciting new field of research. An increasing number of Open source and commercial digital forensics tools are focusing on less time during digital forensic examination. There is a major issue affecting some mobile forensic tools that allow the tools to spend much time during the forensic examination. It is caused by implemen...
Article
Full-text available
In the digital forensic, recovery of deleted and damaged video files play an important role in searching for the evidences. In this paper, MP4-Karver tool is proposed to recover and repair the corrupted videos. Moreover, MP4-Karver extracts frames from video for automatically screen-video to detect illegal cases instead of targeting or watching com...
Conference Paper
Clustering is a useful technique to group similar data entities based on their features. Clustering uses similarity or distance measures to find groups among entities. Many clustering algorithms and measures have been proposed in the literature. These algorithms and measures have their own strengths and weaknesses in the software clustering domain....
Conference Paper
Full-text available
Artificial Neural Networks (ANN) performance depends on network topology, activation function, behaviors of data, suitable synapse’s values and learning algorithms. Many existing works used different learning algorithms to train ANN for getting high performance. Artificial Bee Colony (ABC) algorithm is one of the latest successfully Swarm Intellige...
Conference Paper
Full-text available
Many different earning algorithms used for getting high performance in mathematics and statistical tasks. Recently, an Artificial Bee Colony (ABC) developed by Karaboga is a nature inspired algorithm, which has been shown excellent performance with some standard algorithms. The hybridization and improvement strategy made ABC more attractive to rese...
Chapter
Artificial Neural Networks (ANN) performance depends on network topology, activation function, behaviors of data, suitable synapse's values and learning algorithms. Many existing works used different learning algorithms to train ANN for getting high performance. Artificial Bee Colony (ABC) algorithm is one of the latest successfully Swarm Intellige...
Conference Paper
Full-text available
This paper proposes a feature selection technique for software clus-tering which can be used in the architecture recovery of software systems. The recovered architecture can then be used in the subsequent phases of software maintenance, reuse and re-engineering. A number of diverse features could be extracted from the source code of software system...
Conference Paper
Full-text available
Materialized Views usually used in distributed databases for replication and can also be used for well-organized delivery of data to a querying process. The process of data delivery to queries can further be accelerated if materialized views hierarchy is introduced to the existing materialized view. The newly generated sub views of the existing mat...
Conference Paper
Full-text available
Web Applications (WAs) are complex systems and it is difficult to understand their architecture without proper documentation. Due to high pressure of meeting deadlines and short time to market, WAs are liable to be poorly structured and are rarely well documented. Even if documentation is present, it often does not comply with code because code is...
Conference Paper
Full-text available
Restructuring makes large programs highly cohesive and decomposes the statements into meaningful functions. These meaningful functions help the programmer to understand and maintain the code easily. In this paper, we apply agglomerative clustering technique to restructure the program using binary features. Our approach uses Jaccard similarity measu...
Article
Full-text available
Mobility of a mobile node can be achieved by using two IP addresses. The home address, used for identification of the TCP connection, is static and the care-of-address (CoA) changes each time the point of attachment changes [1]. Therefore the CoA can be thought of as the mobile node's topologically significant address. IPv4 and IPv6 will co-exist f...
Conference Paper
Full-text available
Software clustering is a useful technique to recover architecture of a software system. The results of clustering depend upon choice of entities, features, similarity measures and clustering algorithms. Different similarity measures have been used for determining similarity between entities during the clustering process. In software architecture re...

Questions

Questions (3)
Question
For example, if we have a function A and it produces output in the scale [0,1.5]. How to scale function A so that it produces output in [0,1]?
Question
Some one can please give a clear example of how to calculate a CPCC for Hierarchical Clustering. What inputs are required and how CPCC process using these inputs, is needed.  
Question
I am working on software clustering for software module architecture recovery. When convert source code of software system in to facts, contain entities/objects and binary features. It normally contains utilities. Utilities are the entities which have all or not at all or no common features? What is the better way (and why) to detect the utilities using cluster analysis like Complete Linkage, Single linkage?

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Projects

Projects (6)
Project
We explore RF classifier for the early prediction of liver syndromes. 73 We compare the results of RF with nine other ML classifiers including A1DE, NB, MLP, SVM, KNN, CHIRP, CDT, Forest-PA, and J48. 75 We conduct a series of experiments on the liver disease dataset available on UCI repository. 76 To provide insight into the experimental results, evaluation is carried out using RMSE, RRSE, 77 Specificity, Precision, Recall, F-measure, G-measure, MCC, and Accuracy.
Project
IoT for smart homes
Project
To improve Cohesion and Coupling