Nagwa Badr

Ain Shams University · Department of Information Systems

Cloud computing is a major trend in Information Technology (IT), which has witnessed high adaption rate for cloud solutions. Software-as-a-Service (SaaS) providers compete to address nearly every business and IT application needs. Heterogeneous cloud service advertisements make it difficult for potential users to discover the required service offer...

Web search engines provide users with a huge number of results for a submitted query. However, not all returned results are relevant to the user's needs. Personalized search aims at solving this problem by modeling search interests of the user in a profile and exploiting it to improve the search process. One of the challenges in search personalizat...

With the proliferation of Software-as-a-Service (SaaS) in the cloud environ- ment, it is di�cult for users to search for the right service that satis�es all their needs. In addition, services may provide the same functionality but di�er in their characteristics or Quality of Service attributes (QoS). In this chapter, we present a comprehensive surv...

A crucial field in software development and testing is Software Defect Prediction (SDP) because the quality, dependability, efficiency, and cost of the software are all improved by forecasting software defects at an earlier stage. Many existing models predict defects to facilitate software testing process for testers. A comprehensive review of thes...

The most dangerous disease in recent decades is lung cancer. The most accurate method of cancer diagnosis, according to research, is through the use of histopathological images that are acquired by a biopsy. Deep learning techniques have achieved success in bioinformatics, particularly medical imaging. In this paper, we present an innovative method...

The most dangerous disease in recent decades is lung cancer. The most accurate method of cancer diagnosis, according to research, is through the use of histopathological images that are acquired by a biopsy. Deep learning techniques have achieved success in bioinformatics, particularly medical imaging. In this paper, we present an innovative method...

Nowadays, there is an enormous number of mobile applications that are continuously being launched to the market. As a result of this rapid process, there is a need to increase the speed of testing process using enhanced approaches. This research aims to increase the effectiveness of the graphical user interface testing process of mobile application...

Dialect identification is considered a subtask of the language identification problem and it is thought to be a more complex case due to the linguistic similarity between different dialects of the same language. In this paper, a novel approach is introduced for identifying three of the most used Arabic dialects: Egyptian, Levantine, and Gulf dialec...

Scene classification is one of the most complex tasks in computer-vision. The accuracy of scene classification is dependent on other subtasks such as object detection and object classification. Accurate results may be accomplished by employing object detection in scene classification since prior information about objects in the image will lead to a...

Named entity recognition has been regarded as an important task in natural language processing. Extracting biomedical entities such as RNAs, DNAs, cell lines, proteins, and cell types has been recognized as a challenging task. Most of the existing research focuses on the extraction of flat named entities only and ignores the nested entities. Nested...

Phonemes are defined as the smallest unit of sound that make a semantic change within language words. By capturing and recognizing the distinctive phonemes within the signal, we would be able to recognize the words uttered in the given sample. In this research, we present a new methodology for recognizing Arabic phonemes using a classification appr...

Protein analysis relevance in predicting protein function cannot be ignored. The ability to accurately classify proteins based on their sequences is important for the analysis process. Several feature extraction approaches are used to extract features from protein sequences, either 2D or 3D. The objective of this paper is to investigate the impact...

The Hidden Markov Model (HMM) lies at the heart of the modern speech recognition systems as it provides a simple, effective and straight forward frame work to model the time varying acoustic features of the speech signals. The basic process of building HMM based speech recognition systems is a straight forward process. Nevertheless, the proper para...

A fast-growing worldwide interest is directed toward green energies. Due to the huge costs of wind farms establishment, the location for wind farms should be carefully determined to achieve the optimum return of investment. Consequently, researches have been conducted to investigate land suitability prior to wind plants development. The generated d...

Stemming algorithms (stemmers) are used to convert the words to their root form (stem); this process is used in the pre-processing stage of the Information Retrieval Systems. The Stemmers affect the indexing time by reducing the size of index file and improving the performance of the retrieval process. There are several stemming algorithms; the mos...

Cloud computing is considered as a technology paradigm shift as it enables users to save both development and deployment time. It also reduces the operational costs of using and maintaining systems and applications by using only what you want. Moreover, it allows usage of any resources with elasticity instead of predicting workloads. There are many...

An efficient way to improve the performance of database systems is the distributed processing. Therefore, the functionality of any distributed database system is highly dependent on its proper design in terms of adopted fragmentation, allocation, and replication methods. As a result, fragmentation including its allocation and replication is conside...

Cloud computing is an emerging computing paradigm that is rapidly gaining attention as an alternative to other traditional hosted application models. The cloud environment provides on-demand, elastic and scalable services, moreover, it can provide these services at lower costs. However, this new paradigm poses new security issues and threats becaus...

Many modern applications in several domains such as sensor networks, financial applications, web logs and click-streams operate on continuous, unbounded, rapid, time-varying streams of data elements. These applications present new challenges that are not addressed by traditional data management techniques. For the query processing of continuous dat...

Internet users are overwhelmed with a large number of choices, consequently, there is a need to filter and prioritize relevant information. Recommender System (RS) solves this problem by searching through information provided by users similar to the active user. Precise determination of similar users is the keystone to accuracy of personalized reco...

Due to the huge costs associated with wind energy development, this makes wind farms maintenance and production reliability are of high necessity to ensure sustainability. The continuous evolution of turbines industry has a serious impact on the operation and maintenance costs. Thus, monitoring wind turbines performance and early deterioration pred...

Community detection has become a crucial task in social network mining. Detecting communities summarizes interactions between members for gaining deep understanding of interesting characteristics shared between members of the same community. In this research, we propose a novel community detection algorithm for the purpose of revealing and analyzin...

Petroleum exploration and production is an industry that provides researchers with multi-variant challenging "real world" properties. Recently, some petroleum soft computing techniques have gained a greater interest in prediction within the oil industry. This paper is interested in the analysis, classifying, mining and predictions, based on fuzzy a...

Understanding business behaviors requires acquiring huge amounts of data from diverse field studies. Location Based Social Networks can provide such large amounts of data that can be used in urban analysis to understand business behaviors. Towards more insight for business behavior, a novel analytical prespective that exploits data collected from L...

Large amounts of data are generated daily, according to the wide usage of social media websites and scientific data. These data need to be stored and analyzed to help decision makers but the traditional database concepts are insufficient. Data warehouse and OLAP are useful technologies in the storage and analysis of big data. Using MapReduce will h...

Internet users are overwhelmed with a large number of choices, consequently, there is a need to filter and prioritize relevant information. Recommender System (RS) solves this problem by searching through information provided by users similar to the active user. Precise determination of similar users is the keystone to accuracy of personalized reco...

Abstract. One of the major challenges in building Hidden Markov Models (HMMs) for continuous speech recognition systems is the balance between the available training set and the recognition performance. For large vocabulary recognition systems, context dependent models are usually required to obtain higher recognition accuracy. This is crucial as m...

The design of a distributed database is one of the major research issues within the distributed database system area. The main challenges facing distributed database systems (DDBS) design are fragmentation, allocation and replication. In this paper, we present an enhanced distributed database design over the cloud environment. It minimizes the exec...

Along with the widespread interest in cloud computing, there are still concerns that hinder the proliferation and the adoption of cloud services. One of the main concerns is data security in cloud storage environments. Numerous research problems belonging to cloud storage security have been studied intensively before. However, addressing the three...

Cloud users are overwhelmed with great numbers of cloud services. Service recommender systems evaluate the services that provide same functionalities according to the user requirements. A key enabler to accurate recommendation in recommender systems is the appropriate determination of similar users. This paper contributes to the personalized cloud...

Regression testing repeatedly executes test cases of previous builds to validate that the original features are not affected with any new changes. In recent years, regression testing has seen a remarkable progress with the increasing popularity of agile methods, which stress the central role of regression testing in maintaining software quality. Th...

In this paper, we propose the Software-as-a-Service (SaaS) Recommender (SaaSRec), a personalized reputation-based QoS-aware recommender system (RS) for SaaS services. SaaSRec semantically processes user requests in order to find business-oriented matching services, which are then filtered to satisfy the user QoS requirements and service characteris...

With the proliferation of cloud storage services, data integrity verification becomes increasingly significant in order to guarantee the availability and correctness of the outsourced data. Recently, many auditing schemes have been proposed to verify data integrity without possessing or downloading the outsourced data files. However, such schemes i...

Emergence of social networks facilitates individuals to communicate, share opinions and form communities. Organizations benefit from social networks in monitoring customers’ behavior. Social networks mining and analysis aims to segment customers and determine the most influential actors for viral marketing. In this article, we propose a novel socia...

Recently big data have become a buzzword, which forced the researchers to expand the existing data mining techniques to cope with the evolved nature of data and to develop new analytic techniques. Big data analytic techniques are serving many domains. In this paper, we provide a detailed comprehensive analysis and discussion of the data mining tech...

Software testing is accounted to be an important phases in software development life cycle in terms of cost and manpower. Consequently, many studies have been conducted to minimize the associated cost and human effort to fix bugs and errors, and to improve the testing process's quality by generating test cases at early stages. However, most of them...

Phoneme is the basic unit that makes up the words in speech signals. The recognition of the spoken phonemes in audio signals is considered a crucial process in recognizing speech, as it will affect the recognition accuracy of the overall system. The challenges in recognizing phonemes in general and Arabic in particular require a good knowledge of t...

Cloud computing has become the most essential technology for recent business organizations. It is an emerging distributed environment that uses internet and central remote servers to maintain data and applications. The performance and efficiency of traditional distributed database applications are dependent on proper data fragmentation, allocation...

Community detection in real-world social networks has gained significant attention in the last decade. With the increase of rich attribute information associated with nodes, identifying meaningful communities becomes more challenging. In this paper, we propose a new algorithm for detecting communities that considers the structure of the network as...

The number of software providers offering their applications as a Software-as-a-Service (SaaS) to exploit the benefits of cloud computing is increasing. New challenges to the cloud services discovery are imposed due to the SaaS services unique characteristics such as various and dynamic service offerings, and the lack of standard description langua...

The vast use of Location-Based Social Networks over the last decade results in a considerably large amount of data transactions accumulated over time. Data mining researchers exploit these large amounts of data produced by location-based social networks users to predict useful information. One of the highly recommended methods for prediction is lea...

Traditional authentication techniques such as static passwords are vulnerable to replay and guessing attacks. Recently, many studies have been conducted on keystroke dynamics as a promising behavioral biometrics for strengthening user authentication, however, current keystroke based solutions suffer from a numerous number of features with an insuff...

Software testing is accounted to be an essential part in software development life cycle in terms of cost and manpower, where its total cost is considerable high. Consequently, many studies [78] have been conducted to minimize the associated cost and human effort to fix bugs and errors, and to improve the quality of testing process by automatically...

Cloud computing is a promising computing model that provides a combination of parallel and distributed computing paradigms. It has the characteristics of on demand provisioning of a shared pool of configurable computing resources as a service. It provides a cost effective paradigm of computational, storage and database resources to users over the i...

Despite of the cost effectiveness and high reliability of the cloud storage service, it has several security and privacy issues. As important as the service; it is vulnerable to attacks or outages which would bring irretrievable losses to data owners. It is a crucial requirement for the cloud service provider to provide data security practices to c...

Cloud computing has become a powerful distributed computing mode. A Cloud system has a characteristics strength such as scalability and heterogeneity against the traditional distributed paradigm. These characteristics lead to increased numbers of clients needs to access and process data from multiple distributed resources over a cloud environment w...

Over the years, several achievements on the improvement of web personalized searching based on user's interests, preferences and contextual information have been made, unfortunately, most of them are concerned with the static profile approach, preferences or weight values and not changed once the user preference profile is created and this might be...

Most of the recent applications such as sensor networks applications, financial applications and click-streams applications generate continuous, rapid, unbounded and time varying datasets that are called data streams. In this paper we proposed a multiple queries optimization for data streams processing on cloud computing (MQODS) frameworks that eff...

Regression testing is the type of software testing that seeks to uncover new software bugs in existing areas of a system after changes have been made to them. The significance of regression testing have grown in the past decade with the amplified adoption of agile development methodologies, which requires the execution of regression testing at the...

Requirements-based testing is a testing approach in which test cases are derived from requirements. Requirements represent the initial phase in software developments life cycle. Requirements are considered the basis of any software project. Therefore, any ambiguity in natural language requirements leads to major errors in the coming phases. Moreove...

User authentication is a crucial requirement for cloud service providers to prove that the outsourced data and services are safe from imposters. Keystroke dynamics is a promising behavioral biometrics for strengthening user authentication, however, current keystroke based solutions designed for certain datasets, for example, a fixed length text typ...

The growing use of Location Based Social Networks especially in recent years provides large amount of data transactions. These data transactions attract many data mining researchers to infer various information from them. In this paper, a geographic business prediction technique is proposed, which infers business usage by exploiting data published...

There are billions of web pages available on the Internet. Search Engines always have a challenge to find the best ranked list to the user’s query from those huge numbers of pages. A lot of search results that correspond to a user’s query are not relevant to the user’s needs. Most of the page ranking algorithms use Link-based ranking (web structure...

Many recent applications in several domains such as sensor networks, financial applications, network monitoring and click-streams generate continuous, unbounded, rapid, time varying datasets which are called data streams. In this paper we propose the optimized and elastic query mesh (OEQM) framework for data streams processing based on cloud comput...

There are billions of web pages available on the Internet. Search Engines always have a challenge to find the best ranked list to the user's query from those huge numbers of pages. A lot of search results that corresponding to a user's query are not relevant to the user need. Most of the page ranking algorithms use Link - based ranking (web structu...

Cloud computing is an information technology delivery model accessed over the Internet. Its adoption rate is dramatically increasing. Diverse cloud service advertisements introduce more challenges to cloud users to locate and identify required service offers. These challenges highlight the need for a consistent cloud service registry to serve as a...

Most of query optimizers choose a single query plan for processing all the data based on the average data statistics. But this plan is usually not efficient with the uncertain stream datasets of modern applications as network monitoring, sensor networks and financial applications; where these data have continuous variations over time. In this paper...

Due to the existence of the 'database as a service' (DaaS) model on a cloud computing environment, several challenges have been made, such as query scheduling. Using an efficient query scheduler can improve the queries response time submitted from various clients in a DaaS model. Scheduling the queries in a cost aware way has an economic impact on...

The intelligent system has the ability to predict the future depending on dataset and rules relations. Petroleum prediction using computational intelligence techniques aims at enhancing the petroleum industry. Using test cases processes, we are able to discover information, more effective for different classes of and prove strictness prediction res...

Cloud Storage Service (CSS) is a vital service of cloud computing which relieves the burden of storage management, cost and maintenance. However, Cloud storage introduces new security and privacy challenges that make data owners worry about their data. It is essential to have an auditing service to verify the integrity of outsourced data and to pro...

Most search engine systems mainly focusing on developing Western languages such as English so these search engine systems have a high performance on these languages but they don't have the same performance when they are used for Eastern languages such as Arabic. Furthermore, Arabic is a highly inflected language that has a complex morphological str...

Regression testing is a part of the software testing activity, which is an important activity of the software development life cycle and the maintenance process. It is carried out to ensure that changes made in the fixes or any enhancement changes are not influencing the previously working functionality. Regression testing is mostly done by re-runn...

Crude oil represents the most important energy source as a life engine. Nowadays, oil industries are trying to find a way to reduce its costs and make a better use of the crude oil prediction process. In addition, multiple computational intelligence techniques are used to apply prediction systems on petroleum field. Uncertainty qualification of pet...

Stemming algorithms (stemmers) are used to convert the words to their root form (stem), this process is used in the pre-processing stage of the Information Retrieval Systems. The Stemmers affect the indexing time by reducing the size of index file and improving the performance of the retrieval process. There are several stemming algorithms, the mos...

An efficient way to improve the performance of database systems is the distributed processing. Therefore, the functionality of any distributed database system is highly dependent on its proper design in terms of adopted fragmentation, allocation, and replication methods. As a result, fragmentation, its allocation and replication is considered as a...

Workload management for concurrent queries is one of the challenging aspects of executing queries over the cloud computing environment. The core problem is to manage any unpredictable load imbalance with respect to varying resource capabilities and performances. Key challenges raised by this problem are how to increase control over the running reso...

Regression testing is an important and expensive activity that is undertaken every time a program is modified to ensure that the changes do not introduce new bugs into previously validated code. Instead of re-running all test cases, different approaches were studied to solve regression testing problems. Data mining techniques are introduced to solv...

in the era of endless connectivity and an emerging semantic web, the demand on portable data is increasing day after day. People rely on their mobile devices more and more on a daily basis. And, with the help of technology, mobile devices aid as powerful personal computers on the go especially with promising location-based services. On the other ha...

The goal of personalized search is to provide user with results that accurately satisfy their specific goal of the search. In this paper, a hybrid personalized search re-ranking approach is proposed to provide users with results reordered according to their interests. User preferences are automatically learned into a concept-based user profile. Thi...

With the proliferation of Software-as-a-Service in the cloud environment, users find it tiresome and time consuming to search for the right service that satisfies all their requirements. In addition, services may provide the same functionality but differ in their characteristics or the Quality of Service attributes (QoS) they offer. In this paper,...

With the proliferation of Software-as-a-Service in the cloud environment, users find it tiresome and time consuming to search for the right service that satisfies all their requirements. In addition, services may provide the same functionality but differ in their characteristics or the Quality of Service attributes (QoS) they offer. In this paper,...

Abstract—This paper provides a novel framework for accelerating the solution of the pairwise DNA sequence alignment problem using CUDA parallel paradigm available on the NVIDIA GPU. The main idea is to implement a new algorithm that assigns different nucleotide weights using GPU architectures then merge the subsequences of match using CPU to get th...

Cloud computing is becoming increasingly popular as it enables users to save both development and deployment time. It also reduces the operational costs of using and maintaining the systems. Moreover, it allows the use of any resources with elasticity instead of predicting workload which may be not accurate, as the data warehousing environments can...

Cloud computing is the latest evolution of computing. It provides services to numerous remote users with different requests. Managing the query workload in cloud environment is a challenge to satisfy the cloud users. Improving the overall performance and response time of the query execution can lead to users’ satisfaction. In this paper, we examine...