Статьи журнала - International Journal of Information Technology and Computer Science
Все статьи: 1195
Retrieval of Complex Named Entities on the Web: Proposals for Similarity Computation
Статья научная
As part of the Cognisearch project, we developed a general architecture dedicated to extracting, indexing and searching for complex Named Entities (NEs) in webpages. We consider complex NEs as NEs represented by a list of properties that can be single values (text, number, etc.), "elementary" NEs and/or other complex NEs. Before the indexing of a new extracted complex NE, it is important to make sure that it is not already indexed. Indeed, the same NE may be referenced on several different web platforms. Therefore, we need to be able to establish similarity to consolidate information related to similar complex NEs. This is the focus of this paper. Two issues mainly arise in the computation of similarity between complex NEs: (i) the same property may be expressed differently in the compared NEs; (ii) some properties may be missing. We propose several generic similarity computation approaches that target any type of complex NEs. The two issues outlined above are tackled in these proposals. We experiment and evaluate these approaches with two examples of complex NEs related to the domain of social events.
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Статья научная
In China, horizontal drilling techniques have been widely used in the exploration of coalbed methane (CBM). The drill-in fluids, especially in unconsolidated coal seams, are typically comprised of cellulose polymers, xanthan polymers and guar gums. However, testing and experience have shown that insufficient degradation of filter cakes resulting from even this “clean” drill-in fluids can significantly impede flow capacity at the wellbore wall. Past approaches to minimizing the damage have been the application of strong acids or oxidative breakers systems. They are often only marginally successful, particularly when applied in extended length intervals. Therefore, this paper introduced an engineered technique incorporating non-toxic, environment friendly and economically attractive bio-degradable drilling fluids (BDF). Extensive lab tests were conducted to evaluate the effects of substrate (polymer) type, substrate concentration, enzyme type and enzyme concentration on the viscosity breaking behaviors of BDFs. We got the conclusions as follows. (1) Power Law model was the best model to matching the rheological properties of BDFs; (2) Compared with konjak, the degradations of Na-CMC and guar gum were easier to be controlled; (3) In the degradation of CMC by enzyme SE-1, the optimal weight concentration ratio of CMC to SE-1 was 3 to 1; (4) Of the three enzymes, enzyme SE-2 had the highest activity and could be used to degrade polymer in shorter time; (5) Higher enzyme concentration could speed up the degradation reaction; (6) Viscosity breaking times fluctuating from 13.5 hours to 74.5 hours and viscosity breaking ratios varying from 20% to 100% could be achieved by modifying the formulations of BDFs.
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Risk-based Decision-making System for Information Processing Systems
Статья научная
The article is dedicated to using the methodology of building a decision support system under threats and risks. This method has been developed by modifying the methods of targeted evaluation of options and is used for constructing a scheme of the decision support system. Decision support systems help to make correct and effective solution to shortage of time, incompleteness, uncertainty and unreliability of information, and taking into account the risks. When we are making decisions taking into account the risks, it is necessary to solve the following tasks: determination of quantitative characteristics of risk; determination of quantitative indicators for the effectiveness of decisions in the presence of risks; distribution of resources between means of countering threats, and means that are aimed at improving information security. The known methods for solving the first problem provide for the identification of risks (qualitative analysis), as well as the assessment of the probabilities and the extent of possible damage (quantitative analysis). However, at the same time, the task of assessing the effectiveness of decisions taking into account risks is not solved and remains at the discretion of the expert. The suggesting method of decision support under threats and risks has been developed by modifying the methods of targeted evaluation of options. The relative efficiency in supporting measures to develop measures has been calculated as a function of time given on a time interval. The main idea of the proposed approach to the analysis of the impact of threats and risks in decision-making is that events that cause threats or risks are considered as a part of the decision support system. Therefore, such models of threats or risks are included in the hierarchy of goals, their links with other system's parts and goals are established. The main functional modules that ensure the continuous and efficient operation of the decision support system are the following subsystems: subsystem for analysing problems, risks and threats; subsystem for the formation of goals and criteria; decision-making subsystem; subsystem of formation of the decisive rule and analysis of alternatives. Structural schemes of functioning are constructed for each subsystem. The given block diagram provides a full-fledged decision-making process.
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Road Rush: A Review on Road Traffic Analytics Systems and A Proposed Alternative
Статья научная
Road traffic congestion is a recurring occurrence causing enormous loss of valuable working hours around the world. It is impossible to eradicate such a problem overnight. Rather it could be handled intelligently with the help of modern technologies. Researchers and practitioners have introduced several algorithms, frameworks, systems to mitigate traffic congestion. This paper presents a systematic literature review on existing research and critically analyze the applications on traffic analytics systems. After designing a review protocol, each work was evaluated based on the five research questions and criteria. After critically and carefully analyzing the existing works, this paper also identified the advantages as well as the limitations of the existing approaches towards solving traffic congestion. Based on the findings, a prototype of a mobile application is proposed that can be considered as an improved alternative to the existing works. Finally, this study provides future research directions and improvement scopes in this field.
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Robust Security System for Critical Computers
Статья научная
Among the various means of available resource protection including biometrics, password based system is most simple, user friendly, cost effective and commonly used, but this system having high sensitivity with attacks. Most of the advanced methods for authentication based on password encrypt the contents of password before storing or transmitting in physical domain. But all conventional cryptographic based encryption methods are having its own limitations, generally either in terms of complexity, efficiency or in terms of security. In this paper a simple method is developed that provide more secure and efficient means of authentication, at the same time simple in design for critical systems. Apart from protection, a step toward perfect security has taken by adding the feature of intruder detection along with the protection system. This is possible by merging various security systems with each other i.e password based security with keystroke dynamic, thumb impression with retina scan associated with the users. This new method is centrally based on user behavior and users related security system, which provides the robust security to the critical systems with intruder detection facilities.
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Robust Sliding Mode Fuzzy Control of a Car Suspension System
Статья научная
Different characteristics can be considered in a suspension system design like: ride comfort, body travel, road handling and suspension travel. No suspension system can optimize all these parameters together but a better tradeoff among these parameters can be achieved in active suspension system. Objective of this paper is to establish a robust control technique of the active suspension system for a quarter-car model. The paper describes also the model and controller used in the study and discusses the vehicle response results obtained from a range of road input simulations. A comparison of robust suspension sliding fuzzy control and passive control is shown using MATLAB simulations.
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Robust monocular visual odometry trajectory estimation in urban environments
Статья научная
Visual SLAM (Simultaneous Localization and Mapping) is widely used in autonomous robots and vehicles for autonomous navigation. Trajectory estimation is one part of Visual SLAM. Trajectory estimation is needed to estimate camera position in order to align the real image locations. In this paper, we present a new framework for trajectory estimation aided by Monocular Visual Odometry. Our proposed method combines the feature points extracting and matching based on ORB (Oriented FAST and Rotated BRIEF) and PnP (Perspective-n-Point). Thus, it was used a Matlab® dynamic model and an OpenCV/C++ computer graphics platform to perform a very robust monocular Visual Odometry mechanism for trajectory estimation in outdoor environments. Our proposed method displays that meaningful depth estimation can be extracted and frame-to-frame image rotations can be successfully estimated and can be translated in large view even texture-less. The best key-points has been extracted from ORB key point detectors depend on their key-point response value. These extracted key points are used to decrease trajectory estimation errors. Finally, the robustness and high performance of our proposed method were verified on image sequences from public KITTI dataset.
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Robust, Secure and High Capacity Watermarking Technique based on Image Partitioning-Merging Scheme
Статья научная
This paper presents secure and high capacity watermarking technique using novel approach of Image Partitioning-Merging Scheme (IPMS). The IPMS is used as reduction method to reduce the size of watermark logically and increases security levels of proposed watermarking technique. The technique effectively uses special properties of Discrete Wavelet Transform (DWT), Fast Walse Hadamrd Transform (FWHT), Singular Value Decomposition (SVD) and proved strongly robust to 14 noise addition and filtering attacks. Fibonacci Lucas Transform (FLT) is used as effective scrambling technique to scramble the watermark to provide additional security in embedding process. Many researchers failed to achieve imperceptibility and robustness under high watermark embedding scenario with strong security provision as these quality parameters conflict each other. The novel technique presented here archives imperceptibility, high capacity watermark embedding, security and robustness against 14 noise addition and filtering attacks. The technique is non-blind and tested with grey scale cover images of size 512x512 and watermark images of size 512x512. The experimental results demonstrate that Lena image gives 75.8446dBs imperceptibility which is measured in terms of Peak signal to noise ratio. The robustness is measured in terms of normalized correlation (NC) equals to 1 showing exact recovery of watermark. The method is found strongly robust against noise addition and filtering attacks with compared to existing watermarking methods under consideration.
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Robustness Analysis of Layered Public Transport Networks Due to Edge Overload Breakdown
Статья научная
The robustness of urban bus-transport networks has important influence on the network performance. This paper proposes the model of layered public bus-transport network which is composed of the logical layer and the physical layer and expounds the relationship between these two layers. We map the bus-transport network into two spaces: space P and space L and take space P as logical layer while space L as physical layer. We define the load of edges in the physical layer according to the traffic flow in the logical layer and assume that a removed edge only leads to a redistribution of the load through it to its neighboring edges. We analysis the robustness of layered public bus-transport networks in the face of cascading failure under the case of removing the edge with the highest load and redistributing of the load. Through the simulation of the public bus-transport networks of three major cities in China, we find that in the layered public bus-transport network the traffic flow in the logical layer affects the distribution of load of edges in the physical layer. The removal of the edge with the highest load may lead to the cascading failures of the physical layer, and the avalanche size decreases with the increase of the tolerance parameter.
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SANB-SEB Clustering: A Hybrid Ontology Based Image and Webpage Retrieval for Knowledge Extraction
Статья научная
Data mining is a hype-word and its major goal is to extract the information from the dataset and convert it into readable format. Web mining is one of the applications of data mining which helps to extract the web page. Personalized image was retrieved in existing systems by using tag-annotation-demand ranking for image retrieval (TAD) where image uploading, query searching, and page refreshing steps were taken place. In the proposed work, both the image and web page are retrieved by several techniques. Two major steps are followed in this work, where the primary step is server database upload. Herein, database for both image and content are stored using block acquiring page segmentation (BAPS). The subsequent step is to extract the image and content from the respective server database. The subsequent database is further applied into semantic annotation based clustering (SANB) (for image) and semantic based clustering (SEB) (for content). The experimental results show that the proposed approach accurately retrieves both the images and relevant pages.
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SASMEDU: security assessment method of software in engineering education
Статья научная
Security and usability of web and mobile applications where users share their personal information have become to be a factor about which users should be careful. Rapid increase of developers, programming at early ages, desire for earning money by working freelance have caused widespread use of web and mobile applications and an increase of codes which contain vulnerabilities. Safe and good software development is also based on software lessons given to the students in high school or college years. This paper presents a developed testing and evaluation software in order to find out the leakages in the web applications which was developed by using asp.net, php and java languages. It is aimed that the developed analysis tool was designed to be used by engineering students as a training tool, in security courses by trainees and by programmers for testing. Within the scope of the study, security tests of web projects were carried out with static code analysis method in input control, metric analysis and style control phases. For testing the developed software tool, student web projects were used which were downloaded from "www.freestudentprojects.com" website. 10 test projects were tested in the stages of input control, metric analysis and style control. According to the results of the analysis, the errors were concentrated on Structural Query Language Injection and Cross Site Scripting attacks, which were developed by the students due to the lack of security audit in the projects.
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SBIoT: Scalable Broker Design for Real Time Streaming Big Data in the Internet of Things Environment
Статья научная
Thanks to the recent development in the technology number of IoT devices increased dramatically. Therefore, industries have been started to use IoT devices for their business processes. Many systems can be done automatically thanks to them. For this purpose, there is a server to process sensors data. Transferring these data to the server without any loss has crucial importance for the accuracy of IoT applications. Therefore, in this thesis a scalable broker for real time streaming data is proposed. Open source technologies, which are NoSql and in-memory databases, queueing, full-text index search, virtualization and container management orchestration algorithms, are used to increase efficiency of the broker. Firstly, it is planned to be used for the biggest airport in Turkey to determine the staff location. Considering the experiment analysis, proposed system is good enough to transfer data produced by devices in that airport. In addition to this, the system can adapt to device increase, which means if number of devices increasing in time, number of nodes can be increased to capture more data.
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Статья научная
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.
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SDRED: smart data retrieval engine for databases
Статья научная
Today computers are continuously betrothed in almost all domains and organizations. Thus, databases act as the heart for storing and retrieving information that contain huge digital data. However, in order to interact with such databases, it is necessary to have knowledge about the Structured Query Language (SQL), which is difficult for non-expert users to understand and manipulate. So, there is an emergent need to develop a smart and a user friendly computational technique to interact with databases. The current work proposed a smart technique that can handle such context. The proposed “Smart Data Retrieval Engine for Databases (SDRED)” provided an environment that allows a non-expert user to write and to execute the database queries easily. Furthermore, it retrieved the data stored in databases without a prior knowledge of the SQL. SDRED, which enables the non-expert user to write database queries in natural language (such as English) and to convert them to their SQL query equivalents. The current work presented a detailed design and evaluation for the proposed system by executing different database queries in English. The results established that SDRED successfully converted the non-expert user’s natural language queries into their equivalent SQL queries, thereby providing an easy and user-friendly environment to interact with databases.
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SQL Versus NoSQL Movement with Big Data Analytics
Статья научная
Two main revolutions in data management have occurred recently, namely Big Data analytics and NoSQL databases. Even though they have evolved with different purposes, their independent developments complement each other and their convergence would benefit businesses tremendously in making real-time decisions using volumes of complex data sets that could be both structured and unstructured. While on one hand many software solutions have emerged in supporting Big Data analytics, on the other, many NoSQL database packages have arrived in the market. However, they lack an independent benchmarking and comparative evaluation. The aim of this paper is to provide an understanding of their contexts and an in-depth study to compare the features of four main NoSQL data models that have evolved. The performance comparison of traditional SQL with NoSQL databases for Big Data analytics shows that NoSQL database poses to be a better option for business situations that require simplicity, adaptability, high performance analytics and distributed scalability of large data. This paper concludes that the NoSQL movement should be leveraged for Big Data analytics and would coexist with relational (SQL) databases.
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SQUIREL: Semantic Querying Interlinked OWL-S traveling Process Models
Статья научная
With the advent of new forms of information and communication technologies, the consumer needs to combine and customize different travel components as a complete travel package, namely: Dynamic Packaging Technology. Nevertheless, disparate tourist offers and services make it difficult for consumer to use them effectively. Therefore, our paper presents an intelligent querying framework of OWL-S travel services, called SQUIREL composition engine. It uses Semantic Web Services (SWSs) technologies combined with the useful of Linked e-tourism Data concept to fulfill the preferences and constraints of the e-tourist any time. This purpose supports SWSs pre-selection through the valuation of the rewritten SPARQL consumer query at runtime that manages dynamic service dependencies extracted from Linked e-tourism Data and returns the SWSs endpoint. Then, SQUIREL catches this endpoint and makes the necessary optimizations to refine it to its relevant atomic processes needed to be composed using matrix computation. However, the experimental results indicate that this method owns both lower computation cost and higher success ratio of fine-grained discovery-based atomic processes composition.
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SSKHOA: Hybrid Metaheuristic Algorithm for Resource Aware Task Scheduling in Cloud-fog Computing
Статья научная
Cloud fog computing is a new paradigm that combines cloud computing and fog computing to boost resource efficiency and distributed system performance. Task scheduling is crucial in cloud fog computing because it decides the way computer resources are divided up across tasks. Our study suggests that the Shark Search Krill Herd Optimization (SSKHOA) method be incorporated into cloud fog computing's task scheduling. To enhance both the global and local search capabilities of the optimization process, the SSKHOA algorithm combines the shark search algorithm and the krill herd algorithm. It quickly explores the solution space and finds near-optimal work schedules by modelling the swarm intelligence of krill herds and the predator-prey behavior of sharks. In order to test the efficacy of the SSKHOA algorithm, we created a synthetic cloud fog environment and performed some tests. Traditional task scheduling techniques like LTRA, DRL, and DAPSO were used to evaluate the findings. The experimental results demonstrate that the SSKHOA outperformed the baseline algorithms in terms of task success rate increased 34%, reduced the execution time by 36%, and reduced makespan time by 54% respectively.
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Sample of Groups: A New Strategy to Find a Representative Point for Each Undisclosed Cluster
Статья научная
Some problems involving the selection of samples from undisclosed groups are relevant in various areas such as health, statistics, economics, and computer science. For instance, when selecting a sample from a population, well-known strategies include simple random and stratified random selection. Another related problem is selecting the initial points corresponding to samples for the K-means clustering algorithm. In this regard, many studies propose different strategies for choosing these samples. However, there is no consensus on the best or most effective ap-proaches, even when considering specific datasets or domains. In this work, we present a new strategy called the Sam-ple of Groups (SOG) Algorithm, which combines concepts from grid, density, and maximum distance clustering algo-rithms to identify representative points or samples located near the center of the cluster mass. To achieve this, we create boxes with the right size to partition the data and select the representatives of the most relevant boxes. Thus, the main goal of this work is to find quality samples or seeds of data that represent different clusters. To compare our approach with other algorithms, we not only utilize indirect measures related to K-means but also employ two direct measures that facili-tate a fairer comparison among these strategies. The results indicate that our proposal outperforms the most common-ly used algorithms.
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ScrumFall: a hybrid software process model
Статья научная
Every software project is unique in its own way. As a consequence, a single software process model cannot be suitable for all types of projects. In the real world, practitioners face different difficulties with the existing process models during development. Still, they cope up with the challenges by tailoring the software development lifecycle according to their needs. Most of these custom-tailored practices are kept inside the walls of the organizations. However, sharing these proven and tested practices as well as acquired knowledge and experience would be highly beneficial for other practitioners as well as researchers. So in this paper, we have presented a software process model which contains the characteristics of both Scrum and Waterfall model and named it “ScrumFall”. This model has been practicing in an Anonymous Software Development Company, Bangladesh to solve the shortcomings of Scrum and Waterfall models. Moreover, we have analyzed the performance and suitability for applying this process model. The result shows that this process model is highly effective for the certain projects.
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ScrumSpiral: An Improved Hybrid Software Development Model
Статья научная
In the lightning-quick world of software development, it is essential to find the most effective and efficient development methodology. This thesis represents "Scrum Spiral" which is an improved hybrid software development model that combines the features of Scrum and Spiral approach to enhance the software development process. This thesis aims to identify the usefulness of "ScrumSpiral" methodology and compare it with other hybrid software development models to encourage its use in software development projects. To develop this hybrid model, we did extensive research on the software engineering domain and decided to create a hybrid model by using Scrum and Spiral, named "Scrum Spiral" which is suitable for complicated projects and also for those projects whose requirements are not fixed. Traditional software development models face numerous challenges in rapidly changing markets. By developing this kind of hybrid model, we want to overcome these kinds of limitations and present the software development community with a novel concept for better project results. Final outcome of this thesis was that we developed a model that should be able to complete the project according to the expected schedule, satisfy customer requirements, and obtain productivity through team coordination. The significance of the hybrid model "Scrum Spiral" is reflected in its ability to offer flexibility towards various size projects, proactive risk management to identify all risks before developing the system, and result in higher-quality outcomes for those projects whose requirements are not properly described initially in the project.
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