To scrutinize the uniqueness of software quality model it is crucial to compare it with existing ones. Quality is generally apprehended in a model that illustrates the features and their interactions. Numerous models for measuring quality of software processes have been recommended to assess particular type of software products. Numerous methodologies and practices have been suggested to perform the specific or general scope based comparisons among eminent models. These comparisons are leak. The Suggested comparison lacks the clear differentiation and in depth analysis. Consequently, a prescribed method of comparison among software quality models has been defined. The suggested technique is applied on an inclusive comparison among renowned software quality models. The consequence of suggested technique demonstrates the power and faintness of quality models.

Today in software world the qualifying criterion for a software product is to be of high quality. Quality enables a software product to conform to customer’s expectations. It is another name for best available services and is made acceptable through many practices like reviews, inspections and testing. Among these software inspection is the one which is cost efficient and easy to implement technique. Software inspection is composed of many activities to result in improving the underlying document better and creates consistent understanding. This research presents the different activities in the inspection and practicing of these activities in the software industry of Pakistan. This research is carried out through questionnaires. The answers demonstrate that software inspection is source of better quality products and customer satisfaction without using any proper framework of inspection.

Pioneering ideas from the software engineering discipline have factually affected every sphere of life. Agile software development approach has been promoted since its commencement and stipulates strategies that improve the quality of software product. To consummate fast and reliable development processes, several agile approaches are charted and are quite popular. For quality improvement and to achieve defect free system, the concept of Cleanroom Software Engineering (CSE) is ingrained into agile development life cycle. For embedding users concerns, it is important to distinguish three approaches to quality: Quality of Service (QoS), User-perceived QoP, and Quality of Experience (QoE). QoS is technology centered approach, so by using Incremental Planning of CSE, it shall facilitate the customer’s clarification of system requirements and will control the technical complexity. Usage Specification and Usage Modelling will be used during the Certification phase of CSE which will help to achieve QoP and QoE, being user centered approaches. Results collected from Survey conducted, explains above mentioned factors improvement.

Vehicle Make and Model Recognition (VMMR) has emerged as a significant element of vision based systems because of its application in access control systems, traffic control and monitoring systems, security systems and surveillance systems, etc. So far a number of techniques have been developed for vehicle recognition. Each technique follows different methodology and classification approaches. The evaluation results highlight the recognition technique with highest accuracy level. In this paper we have pointed out the working of various vehicle make and model recognition techniques and compare these techniques on the basis of methodology, principles, classification approach, classifier and level of recognition After comparing these factors we concluded that Locally Normalized Harris Corner Strengths (LHNS) performs best as compared to other techniques. LHNS uses Bayes and K-NN classification approaches for vehicle classification. It extracts information from frontal view of vehicles for vehicle make and model recognition.

Gait analysis is basically referred to study of human locomotion. From the surveillance point of view behavioral biometrics and recognition at a distance are becoming more popular in researchers rather than interactive and Physiological biometrics. In this paper, a time efficient Human gait identification system is proposed. Initially Human silhouettes are extracted by using temporal median background subtraction on video frames, which successfully removes shadows and models even complex background, proposed gait algorithm extracts contours from foreground silhouettes images and then three bounding boxes are drawn around contoured human image 1) upper part for arms movement 2) middle part for thigh and knee angles 3) Lower part for legs movement, knee and ankle angles. Gait cycles are extracted to find gait period and to take final decision for gait features selection, which is used for training. Thigh, Knee, Ankle angles and bounding boxes' widths are used as gait signatures but middle portion of human contains less variations of width in gait cycle hence computing efficiency can be achieved by ignoring width factor of middle part. SVM based training and identification is performed on extracted gait features. The proposed system is assessed using publicly available gait datasets and some indoor experimental videos created for this research work. The results reveal that the proposed algorithm is able to achieve an outstanding recognition rate.

Security has always been the most dominant factor in all domains of everyday life. Companies are spending more and more in this domain as security have become an international issue especially after war on terror era. Not only national departments have become victim of it but general public has also suffered a huge deal due to the lack of security measures in the recent past. This is one of the main reasonfor investment in this domain. From traffic monitoring and security purposes, a vehicle number plate recognition system can play a very useful role in monitoring the vehicle’s movement and consequently providing information about the vehicle. Different countries have their own system of issuing number plates. Similarly different algorithms are designed for number plate recognition in different countries. The proposed system constitutes an algorithm which is designed for the vehicles residing in Pakistan. Digital image processing techniques are the basis of the proposed system including the image enhancement and filtering techniques for noise and other weather effects reduction. Hough transform is used to segment the characters and consequently recognize the character. A very large data set has been used to test the system which shows quite immaculate results.

A modern and well established education system is a backbone of any nation’s success. High reputation in international platform can only be achieved when best and deserving students represent your country and earn reputation on their ability and dedication. For this purpose an education system must be a cheating free system so that non-deserving students should not get the positions which they don’t deserve. This research aims to develop such a system which can be used in exam halls to avoid the cheating based on student’s eye movement. The algorithm detects the human from the scene followed by the face detection and recognition. The next phase involves eye detection followed by eye's movement tracking to analyze and decide about whether the student is involved in cheating or not. The system can be used on a large scale in educational institutions as well as in corporate sector wherever exams have been conducted.

Managing risks in Software Process Improvement (SPI) is a key point of software success. A software risk is considered as an essential characteristic of software development process which if ignored will increase the chance of project failure. For this purpose different risk management approaches are developed. These approaches lead to the identification, assessment and control of risk occurrence in software projects. Collaborative Practice Research (CPR) is one of the action research approaches for managing risk in SPI. In this approach the focus is on gathering information regarding SPI and acknowledging risk management in process development by developing risk assessment strategies and models. The main challenge of this action research approach is to validate the developed risk approach. This paper has a critical review on the existing research approach i.e. CPR. It also provides an enhanced form of CPR which modifies the current CPR approach by including a risk validation activity.

Recent proliferation of mobile market has swiftly increased the competition in mobile software market, new technology and new devices are emerging at phenomenal speed. As the number of mobile applications is increasing at daily rate, quality is becoming major issue. So mobile software organization need some quality model as guideline to improve and maintain quality of application under development. Mobile application mainly depends on user response and user acceptance so they need maintainability, usability, suitability etc. This research paper presents mobile application quality model focusing on key quality characteristics mainly extracted from ISO 9126 quality model, which effect quality of mobile applications. Furthermore some responsibilities of QA team in mobile application development are also discussed and lastly focused on the issue of ‘tracking the quality of mobile applications after deployment’.

Automated Vehicle detection and classification is an important component of intelligent transport system. Due to significant importance in various fields such as traffic accidents avoidance, toll collection, congestion avoidance, terrorist activities monitoring, security and surveillance systems, intelligent transport system has become important field of study. Various technologies have been used for detecting and classifying vehicles automatically. Automated vehicle detection is broadly divided into two types- Hardware based and software based detection. Various algorithms have been implemented to classify different vehicles from videos. In this paper an efficient and economical solution for automatic vehicle detection and classification is proposed. The proposed system first isolates the object through background subtraction followed by vehicle detection using ontology. Vehicle detection is based on low level features such as shape, size, and spatial location. Finally system classifies vehicles into one of the known classes of vehicle based on size.

Cost is the main driving factor for all projects. When it is done correctly, it helps in the successful completion of the project. In this research we have discussed various factors that affect the estimation procedure. These include team structure, team culture, managerial style, project type (Core application or integrated application), client’s working environment. Accurate estimation is far difficult in developing countries where most of the organizations follow local standards. These inaccurate estimations lead to late delivery, less profit or in worst case complete failure.
Software requirement gathering, development, maintenance, quality assurance and cost of poor quality are major groups responsible for overall cost in software production process. The exact proportion among them varies significantly in consecutive software releases, which is caused by many factors. The ever increasing need for the reliability of the software systems, especially mission critical applications in the public safety domain, raises the bar for the accuracy of prediction and estimation techniques. The accuracy of estimations in many areas brings about more concerns regarding techniques already used in the software industry. Widely deployed techniques, such as Wideband Delphi method, stress the engineering and technical aspects of the process of how estimates are prepared.

Quality is key term to be considered when developing the Web applications. If this is not adequately measured; there will be little to force users to use web applications. The focus of Web2.0 is to enhance the interactions between the application and end users and among users. The main challenge of this research is to identify the key quality attributes that gain the end user attention towards the Web applications. There are many Quality Models available for measuring the W2A (Web2.0 Applications). This paper has a critical review of the previously defined quality models. It defines a theoretical quality model containing essential attributes to assess the quality of W2A.

Video analytics refers to process the videos intelligently. Video analytics has its most important usage in the field of the surveillance. Surveillance has been used in various areas and one of them is the detection of unintentional fall of patients, senior citizens and children which can cause serious injuries and health threats to children as well as to old persons. Developed countries are progressing in the Surveillance and activity monitoring. But there are limitation and facing problems under certain circumstances. Advancement in the field of computer vision and the prominent decrease in the prices of digital cameras assisted and motivated researchers to propose very useful algorithms for fall detection. The proposed research work is based on the combination of motion history images and eclipse centroid calculation to detect the fall efficiently. The proposed system provides very effective and efficient results on the video sequences of simulated falls.

Normally, the inspection process is seemed to be just finding defects in software during software development process lifecycle. Software inspection is considered as a most cost effective technique, but if these defects are not properly corrected or handled it would cost you more than double later in the project. This paper focus on the last phase of inspection meeting process showing the importance of Follow-Up Stage in software inspection meeting process. This paper also suggests a set of activities that should be performed during the Rework and Follow-Up Stages so to get inspection meeting results productive and efficient. In this paper we focus on the over the shoulder reviews so to ensure the software quality having less impact on the total software cost.

The purpose of the proposed research work is to develop a computer system that can recognize a person by comparing the characteristics of face to those of known individuals. The main focus is on frontal two dimensional images that are taken in a controlled environment i.e. the illumination and the background will be constant. All the other methods of person's identification and verification like iris scan or finger print scan require high quality and costly equipment's but in face recognition we only require a normal camera giving us a 2-D frontal image of the person that will be used for the process of the person's recognition. Principal Component Analysis technique has been used in the proposed system of face recognition. The purpose is to compare the results of the technique under the different conditions and to find the most efficient approach for developing a facial recognition system

The proposed framework shows the customized approach that improves the software development process by using the Agile techniques. The proposed research work blends the CMMI practices according to Agile methods of development (specially Scrum, because Scrum is extremely used by Pakistani firms)
CMMI is a model for the process improvement within organization, but it is too expensive to implement all practices of CMMI for each level. So for small size organizations, at level 2, 3 there are some practices which are helpful in managing and defining their software development process. By implementing the proposed framework, organizations can improve their maturity and capability level.
There are several problems while working on Agile, many management areas can be neglected. In SCXTREME there are eight process area selected from CMMI and fit them according to Agile, so agile can be suitable for Pakistani organization by implementing some process area at level 2 and level 3.

In last few years’ different textile companies aim to produce the quality fabrics. Major loss of any textile oriented company occurs due to defective fabrics. So the detection of faulty fabrics plays an important role in the success of any company. Till now most of the inspection is done using human visual. This way is too much time consuming, cumbersome and prone to human errors. In past, many advances are made in developing automated and computerized systems to reduce cost and time whereas, increasing the efficiency of the process. This paper aims at comparing some of these techniques on the basis of classification methods and accuracy.

Satellite imagery can produce maps including roads, railway tracks, buildings, bridges, oceans, lakes, rivers, etc. In developed countries like USA, Canada, Australia, Europe, images produced by Google map are of high resolution and good quality. On the other hand, mostly images of the third world countries like Pakistan, Asian and African countries are of poor quality and not clearly visible. Similarly railway tracks of these countries are hardly visible in Google map. We have developed an efficient algorithm for railway track detection from a low quality image of Google map. This would lead to detect damaged railway track, railway crossings and help to schedule/divert locomotive movements in order to avoid catastrophe.

During past few years, brain tumor segmentation in magnetic resonance imaging (MRI) has become an emergent research area in the field of medical imaging system. Brain tumor detection helps in finding the exact size and location of tumor. An efficient algorithm is proposed in this paper for tumor detection based on segmentation and morphological operators. Firstly quality of scanned image is enhanced and then morphological operators are applied to detect the tumor in the scanned image.

Vehicle classification has emerged as a significant field of study because of its importance in variety of applications like surveillance, security system, traffic congestion avoidance and accidents prevention etc. So far numerous algorithms have been implemented for classifying vehicle. Each algorithm follows different procedures for detecting vehicles from videos. By evaluating some of the commonly used techniques we highlighted most beneficial methodology for classifying vehicles. In this paper we pointed out the working of several video based vehicle classification algorithms and compare these algorithms on the basis of different performance metrics such as classifiers, classification methodology or principles and vehicle detection ratio etc. After comparing these parameters we concluded that Hybrid Dynamic Bayesian Network (HDBN) Classification algorithm is far better than the other algorithms due to its nature of estimating the simplest features of vehicles from different videos. HDBN detects vehicles by following important stages of feature extraction, selection and classification. It extracts the rear view information of vehicles rather than other information such as distance between the wheels and height of wheel etc.