A Robust Technique of Brain MRI Classification using Color Features and K-Nearest Neighbors Algorithm

Muhammad Fayaz,Abdul Salam Shah,Fazli Wahid,Asadullah Shah 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.10

The analysis of MRI images is a manual process carried by experts which need to be automated to accurately classify the normal and abnormal images. We have proposed a reduced, three staged model having pre-processing, feature extraction and classification steps. In preprocessing the noise has been removed from grayscale images using a median filter, and then grayscale images have been converted to color (RGB) images. In feature extraction, red, green and blue channels from each channel of the RGB has been extracted because they are so much informative and easier to process. The first three color moments mean, variance, and skewness are calculated for each red, green and blue channel of images. The features extracted in the feature extraction stage are classified into normal and abnormal with K-Nearest Neighbors (k-NN). This method is applied to 100 images (70 normal, 30 abnormal). The proposed method gives 98.00% training and 95.00% test accuracy with datasets of normal images and 100% training and 90.00% test accuracy with abnormal images. The average computation time for each image was .06s.

Investigation on the effect of alkyl chain linked mono-thioureas as Jack bean urease inhibitors, SAR, pharmacokinetics ADMET parameters and molecular docking studies

Larik, Fayaz Ali,Faisal, Muhammad,Saeed, Aamer,Channar, Pervaiz Ali,Korabecny, Jan,Jabeen, Farukh,Mahar, Ihsan Ali,Kazi, Mehar Ali,Abbas, Qamar,Murtaza, Ghulam,Khan, Gul Shahzada,Hassan, Mubashir,Seo, Academic Press 2019 Bioorganic chemistry Vol.86 No.-

<P><B>Abstract</B></P> <P>The increasing resistance of pathogens to common antibiotics, as well as the need to control urease activity to improve the yield of soil nitrogen fertilization in agricultural applications, has stimulated the development of novel classes of molecules that target urease as an enzyme. In this context, the newly developed compounds on the basis of 1-heptanoyl-3-arylthiourea family were evaluated for Jack bean urease enzyme inhibition activity to validate their role as potent inhibitors of this enzyme. 1-Heptanoyl-3-arylthioureas were obtained in excellent yield and characterized through spectral and elemental analysis. All the compounds displayed remarkable potency against urease inhibition as compared to thiourea standard. It was found that novel compounds fulfill the criteria of drug-likeness by obeying Lipinski’s rule of five. Particularly compound <B>4a</B> and <B>4c</B> can serve as lead molecules in 4D (drug designing discovery and development). Kinetic mechanism and molecular docking studies also carried out to delineate the mode of inhibition and binding affinity of the molecules.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A new family of 1-heptanoyl-3-arylthioureas (<B>4a-4j</B>) was synthesized in excellent yield. </LI> <LI> The synthesized 1-heptanoyl-3-arylthiourea family were evaluated for Jack bean urease enzyme inhibition activity. </LI> <LI> Particularly compound <B>4a</B> and <B>4c</B> can serve as lead molecules in 4D (drug designing discovery and development). </LI> <LI> Kinetic mechanism and molecular docking studies also carried out to delineate the mode of inhibition and binding affinity. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

An Evaluation of Automated Tumor Detection Techniques of Brain Magnetic Resonance Imaging (MRI)

Fazli Wahid,Muhammad Fayaz,Abdul Salam Shah 보안공학연구지원센터 2016 International Journal of Bio-Science and Bio-Techn Vol.8 No.2

Image processing is a technique developed by computer and Information technology scientist and being used in all field of research including medical sciences. The focus of this paper is the use of image processing in tumor detection from the brain Magnetic Resonance Imaging (MRI). For the brain tumor detection, Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are the prominent imaging techniques, but most of the experts prefer MRI over CT. The traditional method of tumor detection in MRI images is a manual inspection which provides variations in the results when analyzed by different experts, therefore, in view of the limitations of the manual analysis of MRI, there is a need for an automated system that can produce globally acceptable and accurate results. There is enough amount of published literature available to replace the manual inspection process of MRI images with the digital computer system using image processing techniques. In this paper, we have provided a review of digital image processing techniques in the context of brain MRI processing and critically analyzed them for the identification of the gaps and limitations of the techniques so that the gaps can be filled and limitations of various techniques can be improved for precise and better results.

Critical Analysis of Cloud Computing Software Development Process Models

Ayub Khan,Muhammad Fayaz,Abdul Salam Shah,Fazli Wahid 보안공학연구지원센터 2016 International Journal of Software Engineering and Vol.10 No.11

Nowadays, every vendor and IT service provider wants to switch into a cloud environment for better Quality of Service (QoS), Scalability, Performance and reasonable Cost. Many software developers trying to get the benefits of cloud computing and want to access the cloud environments at low cost and easy access. For this rationale and real-time cloud services, a reliable virtual platform is required. Many issues are encountering in development and deployment of these platforms regarding programming models, application architecture, APIs and services it provided. On the other hand, there are too many issues on the client side, including the limitation of tools, the interaction between client and service provider and user requirements in a specific cloud. As the cloud is inherently distributed environment, so it fabricates gaps in communication and coordination between stack holders. To cope with these obstacles and overcome challenges during software development in Cloud Computing, it is necessary to have a framework which resolves the issues and develop the software process model which meet the user requirement and provide quality of services within a time and budget. In this paper, the literature review mainly focuses on the software process model with their strength and weakness. The literature review also analyzes some attributes for software life cycle including cost, time, scalability and QoS.

Navigation through Citation Network Based on Content Similarity Using Cosine Similarity Algorithm

Abdul Ahad,Muhammad Fayaz,Abdul Salam Shah 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.5

The rate of scientific literature has been increased in the past few decades; new topics and information is added in the form of articles, papers, text documents, web logs, and patents. The growth of information at rapid rate caused a tremendous amount of additions in the current and past knowledge, during this process, new topics emerged, some topics split into many other sub-topics, on the other hand, many topics merge to formed single topic. The selection and search of a topic manually in such a huge amount of information have been found as an expensive and workforce-intensive task. For the emerging need of an automatic process to locate, organize, connect, and make associations among these sources the researchers have proposed different techniques that automatically extract components of the information presented in various formats and organize or structure them. The targeted data which is going to be processed for component extraction might be in the form of text, video or audio. The addition of different algorithms has structured information and grouped similar information into clusters and on the basis of their importance, weighted them. The organized, structured and weighted data is then compared with other structures to find similarity with the use of various algorithms. The semantic patterns can be found by employing visualization techniques that show similarity or relation between topics over time or related to a specific event. In this paper, we have proposed a model based on Cosine Similarity Algorithm for citation network which will answer the questions like, how to connect documents with the help of citation and content similarity and how to visualize and navigate through the document.

Using Probabilistic Classification Technique and Statistical Features for Brain Magnetic Resonance Imaging (MRI) Classification: An Application of AI Technique in Bio-Science

Fazli Wahid,Rozaida Ghazali,Muhammad Fayaz,Abdul Salam Shah 보안공학연구지원센터 2016 International Journal of Bio-Science and Bio-Techn Vol.8 No.6

There are many medical imaging modalities used for the analysis and cure of various diseases. One of the most important of these modalities is Magnetic Resonance Imaging (MRI). MRI is advantageous over other modalities due to its high spatial resolution and the excellent capability of discrimination of soft tissues. In this paper, an automated classification approach of normal and pathological MRI is proposed. The proposed model three simple stages; preprocessing, feature extraction and classification. Two types of features; color moments and texture features have been considered as main features for the description of brain MRI. A probabilistic classifier based on logistic function has been used for the MRI classification. A standard data set consisting of one hundred and fifty images has been used in the experiments, which was divided into 66% training and 34% testing. The proposed approach gave 98% accurate results for training data set and 94% accurate results for the testing data set. For validation of the proposed approach, 10-Fold cross validation was applied, which gave 90.66% accurate results. The classification capability of probabilistic classifier has been compared with the different state of art classifiers, including Support Vector Machine (SVM), Naïve Bayes, Artificial Neural Network (ANN), and Normal densities based linear classifier.

Testing Desktop Application : Police Station Information Management System

Abdul Salam Shah,Muhammad Fayaz,Asadullah Shah,Shahnawaz Shah 보안공학연구지원센터 2016 International Journal of Software Engineering and Vol.10 No.7

The police stations have adequate importance in the society to control the law and order situations of the country. In Pakistan, police stations manage criminal records and information manually. We have previously developed and improved a desktop application for the record keeping of the different registers of the police stations. The data of police stations is sensitive and that need to be handled within secured and fully functional software to avoid any unauthorized access. For the proper utilization of the newly developed software, it is necessary to test and analyze the system before deployment into the real environment. In this paper, we have performed the testing of an application. For this purpose, we have used Ranorex, automated testing tool for the functional and performance testing, and reported the results of test cases as pass or fail.

Risk Management Policy of Telecommunication and Engineering Laboratory

Abdul Salam Shah,Muhammad Fayaz,Asadullah Shah,Shahnawaz Shah 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.4

The Telecommunication laboratory plays an important role in carrying out research in the different fields like Telecommunication, Information Technology, Wireless Sensor Networks, Mobile Networks and many other fields. Every Engineering University has a setup of laboratories for students particularly for Ph.D. scholars to work on the performance analysis of different Telecommunication Networks including WLANs, 3G/4G, and Long Term Evolution (LTE). The laboratories help students to have hand on practice on the theoretical concepts they have learned during the teachings at the university. The technical subjects have a practical part also which boosts the knowledge of students and learning of new ideas. The Telecommunication and Engineering laboratories are equipped with different electronic equipment’s like digital trainers, simulators etc. and some additional supportive devices like computers, air conditioners, projectors, and large screens, with power backup facility that creates the perfect environment for experimentation. The setup of Telecommunication and Engineering laboratories cost huge amount, required to purchase equipment, and maintain the equipment. In any working environment risk factor is involved. To handle and avoid risks there must be risk management policy to tackle with accidents and other damages during working in the laboratory, may it be human or equipment at risk. In this paper, we have proposed a risk management policy for the Telecommunication and Engineering laboratories, which can be generalized for similar type of laboratories in engineering fields of studies.

How Vegetation Spatially Alters the Response of Precipitation and Air Temperature? Evidence from Pakistan

Afed Ullah Khan Waqar Ahmad,Muhammad Far Fayaz Ahmad Khan,Baig Ammar Ahmad,Shah Liaqat Ali,Khan Jehanzeb 한국대기환경학회 2020 Asian Journal of Atmospheric Environment (AJAE) Vol.14 No.2

Precipitation, air temperature and Normalized Difference Vegetation Index (NDVI) data of 32 sites for a period of 1983 to till date in Pakistan were collected with the objective of studying the effects of vegetation on precipitation and air temperature in Pakistan. Spatial trends were assessed for NDVI, precipitation and air temperature (maximum and minimum). Increasing trends were observed at 18, 20, 24 and 26 number of monitoring stations for NDVI, precipitation and maximum and minimum temperature respectively. The trends of NDVI were compared with the trends of precipitation and maximum and minimum temperature in hilly and urban areas. NDVI and precipitation showed parallel trends in hilly areas at 64% of the monitoring stations. Whereas, only 53% of the stations displayed parallel trends in urban areas. 71% of the stations showed opposite NDVI and maximum temperature trends and 79% of the stations showed opposite NDVI and minimum temperature trends in hilly areas. However, in urban areas only 47% and 41% of the stations showed opposite trends of NDVI and maximum temperature and NDVI and minimum temperature respectively. Pearson’s correlation coefficients were calculated to determine the effects of vegetation on precipitation and air temperature (maximum and minimum) in hilly and urban areas. The results showed that there exists positive relationship between NDVI and precipitation and negative relationship between NDVI and temperature (maximum and minimum) in most of the hilly areas. However, in urban areas, the positive relationship between NDVI and precipitation exists only in 47% of the stations and negative relationships between NDVI and maximum temperature and between NDVI and minimum temperature exist only in 47% and 41% of the stations respectively. Results of the current study suggest afforestation practices at country level to reduce climate change effects.

An Offline Signature Verification Technique Using Pixels Intensity Levels

Abdul Salam Shah,M.N.A. Khan,Fazli Subhan,Muhammad Fayaz,Asadullah Shah 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.8

Offline signature recognition has great importance in our day to day activities. Researchers are trying to use them as biometric identification in various areas like banks, security systems and for other identification purposes. Fingerprints, iris, thumb impression and face detection based biometrics are successfully used for identification of individuals because of their static nature. However, people’s signatures show variability that makes it difficult to recognize the original signatures correctly and to use them as biometrics. The handwritten signatures have importance in banks for cheque, credit card processing, legal and financial transactions, and the signatures are the main target of fraudulence. To deal with complex signatures, there should be a robust signature verification method in places such as banks that can correctly classify the signatures into genuine or forgery to avoid financial frauds. This paper, presents a pixels intensity level based offline signature verification model for the correct classification of signatures. To achieve the target, three statistical classifiers; Decision Tree (J48), probability based Naïve Bayes (NB tree) and Euclidean distance based k-Nearest Neighbor (IBk), are used. For comparison of the accuracy rates of offline signatures with online signatures, three classifiers were applied on online signature database and achieved a 99.90% accuracy rate with decision tree (J48), 99.82% with Naïve Bayes Tree and 98.11% with K-Nearest Neighbor (with 10 fold cross validation). The results of offline signatures were 64.97% accuracy rate with decision tree (J48), 76.16% with Naïve Bayes Tree and 91.91% with k-Nearest Neighbor (IBk) (without forgeries). The accuracy rate dropped with the inclusion of forgery signatures as, 55.63% accuracy rate with decision tree (J48), 67.02% with Naïve Bayes Tree and 88.12% (with forgeries).