Computational based automated pipeline corrosion data assessment

Corrosion is a complex process influenced by the surrounding environment and operational systems which cannot be interpreted by deterministic approach as in the industry codes and standards. The advancement of structural inspection technologies and tools has produced a huge amount of corrosion data. Unfortunately, available corrosion data are still under-utilized. Complicated assessment code, and manual analysis which is tedious and error prone has overburdened pipeline operators. Moreover, the current practices produce a negative corrosion growth data defying the nature of corrosion progress, and consuming a lot of computational time during the reliability assessment. Therefore, this research proposes a computational based automated pipeline corrosion data assessment that provides complete assessment in terms of statistical and computational. The purpose is to improve the quality of corrosion data as well as performance of reliability simulation. To accomplish this, .Net framework and Hypertext Preprocessor (PHP) language is used for an automated matching procedure. The alleviation of deterministic value in corrosion data is gained by using statistical analysis. The corrosion growth rate prediction and comparison is utilized using an Artificial Neural Network (ANN) and Support Vector Machine (SVM) model. Artificial Chemical Reaction Optimization Algorithm (ACROA), Particle Swarm Optimization (PSO), and Differential Evolution (DE) model is used to improve the reliability simulation based on the matched and predicted corrosion data. A computational based automated pipeline corrosion data assessment is successfully experimented using multiple In-Line Inspection (ILI) data from the same pipeline structure. The corrosion data sampling produced by the automated matching is consistent compared to manual sampling with the advantage of timeliness and elimination of tedious process. The computational corrosion growth prediction manages to reduce uncertainties and negative rate in corrosion data with SVM prediction is superior compared to A ^N . The performance value of reliability simulation by ACROA outperformed the PSO and DE models which show an applicability of computational optimization models in pipeline reliability assessment. Contributions from this research are a step forward in the realization of computational structural reliability assessment

A survey on SQL injection prevention methods

Database plays a very important role in everyone’s life including the organizations since everything today is connected via Internet and to manage so many data. There is a need of database which helps organizations to organize, sort and manage the data and to ensure that the data which a user is receiving and sending through the mean of database is secure since the database stores almost everything such as Banking details which includes user id, Password and so. Thus, it means that the data are really valuable and confidential to us and therefore security really matters for database. SQL Injection Attacks on the database are becoming common in this era where the hackers are trying to steal the valuable data of an individual through the mean of SQL Injection Attack by using malicious query on the application. This application reveals the individual data by an efficient and the best SQL Injection Prevention technique is required in order to protect the individual data from being stolen by the hackers. Therefore, this paper will be focusing on reviewing different types of SQL Injection prevention methods and SQL injection types. The initial finding of this paper can make comparison of different types of SQL Injection Prevention methods which will enable the Database Administrator to choose the best and the efficient SQL Injection Prevention Method for their organization. Consequently, Preventing of SQL Injection Attack from happening which would ultimately result in no data loss of an user

Integration of SQL injection prevention methods

In everybody’s life including the organisations, database plays a very important role, since today everything is connected via the Internet. There is a need for a database that helps organisations to organise, sort and manage the data and ensure that the data a user receives and sends via the database mean is secure, since the database stores almost everything such as banking details including user ID and password. Make this data really valuable and confidential for us and therefore security is really important for the database. In this age, SQL Injection database attacks are increasingly common. The hackers attempt to steal an individual’s valuable data through the SQL Injection Attack mean by using malicious query on the application, hence revealing an efficient individual data. Therefore the best SQL Injection Prevention technique is needed to safeguard individual data against hackers being stolen. This paper compares two types of SQL Injection using the SQL pattern matching database system attack (SQLPMDS) and a SQL injection union query attacks prevention using tokenisation technique (SIUQAPTT) that allows Database Administrator to select the best and most effective SQL Injection Prevention method for their organisation. Preventing SQL Injection Attack from occurring that would ultimately lead to no user data loss. The results were obtained by comparing it to the results of the SQL injection attack query on whether the attack was blocked or not by two prevention techniques, SQL pattern matching database system attacks and SQL injecting union query attacks prevention using website tokenisation techniques. The conclusion is that the best method of prevention is the SQL pattern that matches database system attacks

Integration of PSO and K-means clustering algorithm for structural-based alert correlation model

Network-based Intrusion Detection Systems (NIDS) will trigger alerts as notifications of abnormal activities detected in computing and networking resources. As Distributed Denial-of-Service (DDOS) attacks are getting more sophisticated, each attack consists of a series of events which in turn trigger a series of alerts. However, the alerts are produced in a huge amount, of low quality and consist of repeated and false positive alerts. This requires clustering algorithm to effectively correlate the alerts for identifying each unique attack. Soft computing including bio-inspired algorithms are explored to optimally cluster the alerts. Therefore, this study investigates the effects of bio-inspired algorithm in alert correlation (AC) model. Particle Swarming Optimization (PSO) is integrated with K-Means clustering algorithm to conduct structural-based AC. It was tested on the benchmarked DARPA 2000 dataset. The efficiency of the AC model was evaluated using clustering accuracy, error rate and processing time measurements. Surprisingly, the experimental results show that K-Means algorithm works better than the integration of PSO and K-Means. K-Means gives 99.67% clustering accuracy while PSO and K-Means gives 92.71% clustering accuracy. This indicates that a single clustering algorithm is sufficient for optimal structural-based AC instead of integrated PSO and K-Means

The student's perceptions on the usability of industrial training system and its implication

Industrial training refers to placement of students in the industry or organization for a certain period of time in order for them to apply their theoretical knowledge in the actual career world. Industrial training is one of the main components in the Computer Science curriculum in Universiti Teknologi Malaysia (DIM). Meanwhile, Industrial Training Systems (ITS) is a web based system which is developed to manage the industrial training process in DIM. ITS consist of four major modules for students which are student registration, student placement, student online log book and student assessment. Beside the four modules, ITS also facilitated with communication features like email notification and announcements. Hence, ITS become a solution to improve the current process of managing and monitoring the industrial training which were previously being done manually. Indirectly, ITS gives an opportunity for students to utilize internet technology as part of their effective learning tool during industrial training. The aim of this paper is to analyze the satisfaction rate of students towards ITS from the aspect of usability. Usability is used to measures the usable and functional of IT'ss functions from the aspect of learn ability, efficiency, memorability, errors and satisfaction. A survey has been distributed online to undergraduate students who have used ITS during their industrial training period from year 2012 until 2015. The results are derived from satisfactory Likert scales which indicate that students were satisfied with the functionalities provided by ITS

Parallel matching system for digital non text information (fingerprint image)

Ever since we were born, there are few parts of our body have been developed uniquely to represent our identities. Parts like retina patterns, veins, DNA, fingerprints are all unique for every human being. In order to recognize these unique patterns, scientists have spent billions of dollars and years of research and development to produce tools and techniques to identify humans based on their unique body parts. Today, the most highly utilized parts of our body for the identification purposes are fingerprints. Although there are so many readers and applications have been made for the job, there are still weaknesses that need to be addressed especially in the area of fingerprint matching. Therefore, the aim of this research is to find ways to increase the performance of fingerprint matching in response to the increased number of fingerprint records available in the system. This research focuses on developing a parallel matching process in a computer cluster to increase the performance of fingerprint matching, without taking into account additional features such as high throughput and others. The main idea is to minimize processing time with multiple processes executing parallels in several computers. As a proof of concept, a prototype consists of client and server processes has been developed. An interface which been integrated with a fingerprint device on client side enables a request (a fingerprint image) been send to a server process. Upon receiving a fingerprint image, the server process will place the request into a queue before distributing to a cluster of matching server throughout the network. The processing time for fingerprint matching has been improved especially when the amount of records increased. The detailed results of identification, duration of matching and similarity are discussed

Ubiquitous database in mobile healthcare

Ubiquitous Database in Mobile Healthcare (UDMHC) in Emergency Handling System is utilizing the combined benefit of smart card to support mobility coupled with the ubiquitous access of distributed database via web technology, in order to promote a truly mobile and interactive medical information technology. UDMHC provides benefits of storing comprehensive, accurate and up to date medical information while offering the ease of mobility in pocket. In the time of accident or emergency, UDMHC provides medical-related professional the best solution in immediately retrieving accurate, concise and vital victim’s medical record, allergies, and other information necessary for medical treatment decisions. Applet provides flexibility in retrieving the user’s information, user’s medical information and emergency contact list from ubiquitous database in the smart card. It also provides interaction with other distributed hospital database via HTTP protocol in order to retrieve the victims detail information. This provides a convenient way to gather, adapt, and share data from different hospital. Result indicated that network environment is able to be spanned across hospital, clinic and country boundaries, hence provides better ubiquitous medical record management. The Internet technology offers the opportunity for distributed health services to exchange medical knowledge and allow dynamic monitoring of patients health. With the deployment of Java and open card technology, UDMHC can be seamlessly and ubiquitously applied in any platform

Ubiquitous database in mobile healthcare

Ubiquitous Database in Mobile Healthcare (UDMHC) in Emergency Handling System is utilizing the combined benefit of smart card to support mobility coupled with the ubiquitous access of distributed database via web technology, in order to promote a truly mobile and interactive medical information technology. UDMHC provides benefits of storing comprehensive, accurate and up to date medical information while offering the ease of mobility in pocket. In the time of accident or emergency, UDMHC provides medical-related professional the best solution in immediately retrieving accurate, concise and vital victims medical record, allergies, and other information necessary for medical treatment decisions. Applet provides flexibility in retrieving the users information, users medical information and emergency contact list from ubiquitous database in the smart card. It also provides interaction with other distributed hospital database via HTTP protocol in order to retrieve the victims detail information. This provides a convenient way to gather, adapt, and share data from different hospital. Result indicated that network environment is able to be spanned across hospital, clinic and country boundaries, hence provides better ubiquitous medical record management. The Internet technology offers the opportunity for distributed health services to exchange medical knowledge and allow dynamic monitoring of patients health. With the deployment of Java and open card technology, UDMHC can be seamlessly and ubiquitously applied in any platform

Mechanize feature-to-feature matching system utilizing repeated inspection data

The advances of computational methods and tools can greatly support other areas in doing tasks from the most tedious or repetitive to the most complex. In this paper, these advances were manipulated in civil structures maintenance specifically in pipeline corrosion assessment. This paper describes mechanize method developed to automatically detect and quantitY important parameters for future prediction of corrosion growth using In-line inspection (Ill) data. The focal process in this system includes data conversion, data filtering, parameter tolerance or sizing configuration, matching, and data trimming. A sensitivity analysis using linear regression method was used to correlates defects from one inspection to the next. Issues and advantage gain from this mechanize system is threefold~ Firstly, timeliness (manual matching procedure consumed a great deal of time). Secondly, accuracy and consistencies in data sampling (current implementation, different researcher obtain a different number of sample even though the method used in matching were the same), and finally, reduction of data matching error (manual matching was prone to human error due to the masses of inspection data to be match. Furthermore this method is impractical when facing the large amount of real inspection data)