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The technology works as a catalyst through which many changes occur in the learning approaches, teaching methodologies, research arena, in the work environment and in the use of information and knowledge. Helping students to learn using technological tools rather than using conventional techniques has become more popular in the 21st century in colleges and schools in the domain of computer science. Integration of technological tools will help teachers to the international requirement to use technology-based teaching and learning tools instead of traditional teaching methods. Most researchers agree on the significance of the use of technological tools in different education systems. However, current state-of-the-art depicts that there is no comprehensive study that provides an analysis of different technological tools e.g. computer-based, games based, mobile based, and multimedia technologies used in education. This paper provides a comprehensive review of several of the most popular teaching methodologies (collaborative, active learning, problem-based, inductive teaching method) and technological tools i.e. computer-based (ICT, CAI, CBI), games based (serious games, web games, micro-games, videos games), mobile based (laptop, PDAs, tablets, mobile phones), online learning tools (flipped classroom, web MOOCs) and multimedia technologies (Videos, MCMs, MAMCM). The purpose of this research paper is to scrutinize the roles and effectiveness of technological tools in teaching and learning process and it provides the definition of each method, along with the similarities and differences among these teaching methodologies and technological tools. Even though the strength of each individual method is something that is met with varying degrees of evidence, teaching with the help of technological tools has been found to be generally more effective or at least equally effective to traditional methods of teaching. The purpose of the use of technology in teaching and learning process is to improve productivity, the effectiveness of current practices and bring pedagogical changes which are beneficial for the betterment of education. We explore the theoretical literature available about the influence of technology and its effectiveness in the field of education. In teaching and learning process, the use of technological tools increases interaction between teachers and students. To incorporate technology, educators and teachers must implement the right technological tools to make the environment more innovative for the students.

Summary: Due to recent developments in location‐based services and mobile computing, the need for indices for moving objects has been strengthened to improve the response time of a query operation. With a single index in place for managing both the update and query operations for moving objects, the index needs to be updated each time the object moves. This deteriorates the performance of concurrent query operations. It is critical to handle the conflicts between continuous update and query operations effectively using appropriate concurrency control protocol otherwise, inconsistent results will be reported. Many indices have been proposed in the literature for moving objects but they lack the support for processing concurrent operations. Further, the consistent indices in the literature are based on tree structure that have computationally expensive split/merge operations that can negatively affect the response time of query processing algorithms. Moreover such tree based indices are proposed for historical and future timeline data. As the scope of this article is on current timeline and concurrent continuous query operations, therefore, we exploit state of the art hash‐based indices in the literature and presented the two consistent versions. The comparative analysis of the indices is performed and meaningful findings are also presented along. [ABSTRACT FROM AUTHOR]

Summary: Sequence alignment is a critical computational problem in various domains, including genomics, proteomics, and natural language processing. The Needleman‐Wunsch (NW) algorithm is a classical dynamic programming approach for finding the optimal global alignment between two sequences. However, its quadratic time and space complexity make it impractical for aligning large‐scale sequences, which are increasingly common in modern applications. In this article, we propose a parallel variation of the NW algorithm that enables scalable global sequence alignment with customizable scoring schemes. Our approach re‐formulates the dependencies in the NW algorithm to enable parallel execution, thereby leveraging the computational power of modern parallel architectures, such as graphics processing unit (GPU). Furthermore, our algorithm supports arbitrary linear scoring schemes, which allows us to use domain‐specific knowledge to improve alignment accuracy. We establish the correctness of our algorithm and evaluate its performance using real DNA and user trajectory sequences on GPUs. Our parallel algorithm has shown impressive results in our experiments, with a peak performance of 27.99 GCUPS (giga cell updates per second) and a maximum speedup of 48.18 times compared to the traditional sequential implementation. Additionally, our algorithm demonstrates remarkable scalability, enabling the alignment of sequences of any length while ensuring balanced work distribution and optimal utilization of resources. Our primary objective is to harness the computational capabilities of a single GPU and fully utilize the processing power of multi‐core CPUs. [ABSTRACT FROM AUTHOR]

Edit distance is the most widely used method to quantify similarity between two strings. We investigate the problem of similarity search under edit distance. Given a collection of sequences, the goal of similarity search under edit distance is to find sequences in the collection that are similar to a given query sequence where the similarity score is computed using edit distance. The canonical method of computing edit distance between two strings uses a dynamic programming-based approach that runs in quadratic time and space, which may not provide results in a reasonable amount of time for large sequences. It advocates for parallel algorithms to reduce the time taken by edit distance computation. To this end, we present scalable parallel algorithms to support efficient similarity search under edit distance. The efficiency and scalability of the proposed algorithms is demonstrated through an extensive set of experiments on real datasets. Moreover, to address the problem of uneven workload across different processing units, which is mainly caused due to the significant variance in the size of the sequences, different data distribution schemes are discussed and empirically analyzed. Experimental results have shown that the speedup achieved by the hybrid approach over inter-task and intra-task parallelism is 18 and 13, respectively. [ABSTRACT FROM AUTHOR]

Summary: Recently, mobile computing has changed the way that spatial data and GIS are processed. Unlike wired and stand‐alone GIS, now the trend has been switched from offline to real‐time data processing using location aware services, such as GPS technology. The increased usage of location aware services in multiuser real‐time environment has made transaction management incredibly significant. If the simultaneous query operations on the same data item are not handled intelligently then this results in data inconsistency issue. Concurrency control protocol is one of the primary aspects that helps in overcoming this issue a in multiuser environment. To the best of our knowledge, the impact of technological advancements on concurrency control has not been thoroughly studied in the literature. In this article, we explored the literature on concurrency control algorithms in depth with respect to real‐time applications and the applications with moving objects. We defined a taxonomy of concurrency control solutions and assessed the maturity of these solutions in the light of characteristics of real‐time and mobile environment. We compared the most recent developments made in the literature and presented meaningful insights. Challenges are also identified and discussed, which can assist in doing research in this domain in future. [ABSTRACT FROM AUTHOR]

The emergence of social media, the worldwide web, electronic transactions, and next-generation sequencing not only opens new horizons of opportunities but also leads to the accumulation of a massive amount of data. The rapid growth of digital data generated from diverse sources makes it inapt to use traditional storage, processing, and analysis methods. These limitations have led to the development of new technologies to process and store very large datasets. As a result, several execution frameworks emerged for big data processing. Hadoop MapReduce, the pioneering framework, set the ground for forthcoming frameworks that improve the processing and development of large-scale data in many ways. This research focuses on comparing the most prominent and widely used frameworks in the open-source landscape. We identify key requirements of a big framework and review each of these frameworks in the perspective of those requirements. To enhance the clarity of comparison and analysis, we group the logically related features, forming a feature vector. We design seven feature vectors and present a comparative analysis of frameworks with respect to those feature vectors. We identify use cases and highlight the strengths and weaknesses of each framework. Moreover, we present a detailed discussion that can serve as a decision-making guide to select the appropriate framework for an application. [ABSTRACT FROM AUTHOR]

The edit distance is the measure that quantifies the difference between two strings. It is an important concept because it has its usage in many domains such as natural language processing, spell checking, genome matching, and pattern recognition. Edit distance is also known as Levenshtein distance. Sequentially, the edit distance is computed by using dynamic programming based strategy that may not provide results in reasonable time when input strings are large. In this work, a distributed algorithm is presented for parallel edit distance computation. The proposed algorithm is both time and space efficient. It is evaluated on a hybrid setup of distributed and shared memory systems. Results suggest that the proposed algorithm achieves significant performance gain over the existing parallel approach. [ABSTRACT FROM AUTHOR]

We are moving towards 'smart' world in which industries, such as healthcare, smart cities, transportation, and agriculture have started using IoT (Internet of Things). These applications involve huge number of sensors and devices that generate high volume of real time data. To perform useful analytics on this data, location and spatial awareness characteristics of devices need to be considered. Wide range of location-based services and sensors in GIS have to manage moving objects that change their position with respect to time. These applications generate voluminous amount of real time geospatial data that demands an effective query processing mechanism to minimize the response time of a query. Indexing is one of the traditional ways to minimize the response time of a query by pruning the search space. In this paper, we performed a detailed survey of the literature regarding the indexing of real time geospatial data generated by IoT enabled devices. Some major challenges relevant to indexing of moving objects are highlighted. Various important index design considerations are also discussed. The goal is to help researchers in understanding the principles, methods, and challenges in the indexing of real time geospatial data. This will also aid in identifying the future research opportunities. [ABSTRACT FROM AUTHOR]

The data model of the classical data warehouse (formally, dimensional model) does not offer comprehensive support for temporal data management. The underlying reason is that it requires consideration of several temporal aspects, which involve various time stamps. Also, transactional systems, which serves as a data source for data warehouse, have the tendency to change themselves due to changing business requirements. The classical dimensional model is deficient in handling changes to transaction sources. This has led to the development of various schemes, including evolution of data and evolution of data model and versioning of dimensional model. These models have their own strengths and limitations, but none fully satisfies the above-stated broad range of aspects, making it difficult to compare the proposed schemes with one another. This paper analyses the schemes that satisfy such challenging aspects faced by a data warehouse and proposes taxonomy for characterizing the existing models to temporal data management in data warehouse. The paper also discusses some open challenges. [ABSTRACT FROM AUTHOR]

Background: Record de-duplication is a process of identifying the records referring to the same entity. It has a pivotal role in data mining applications, which involves the integration of multiple data sources and data cleansing. It has been a challenging task due to its computational complexity and variations in data representations across different data sources. Blocking and windowing are the commonly used methods for reducing the number of record comparisons during record de-duplication. Both blocking and windowing require tuning of a certain set of parameters, such as the choice of a particular variant of blocking or windowing, the selection of appropriate window size for different datasets etc.Methods: In this paper, we have proposed a framework that employs blocking and windowing techniques in succession, such that figuring out the parameters is not required. We have also evaluated the impact of different configurations on dirty and massively dirty datasets. To evaluate the proposed framework, experiments are performed using Febrl (Freely Extensible Biomedical Record Linkage).Results: The proposed framework is comprehensively evaluated using a variety of quality and complexity parameters such as reduction ratio, precision, recall etc. It is observed that the proposed framework significantly reduces the number of record comparisons.Conclusions: The selection of the linkage key is a critical performance factor for record linkage. [ABSTRACT FROM AUTHOR]

Cyber physical system (CPS) applications are widely used to control critical infrastructure of various application domains, eg, medical health care, energy, and power, to name a few. Such applications usually take input data from sensors, estimate current state of the system, and then based on the estimation, make critical decisions to control the underlying infrastructure automatically. Therefore, security and integrity of the (system state) data are critically important to ensure safe operations of CPS. In this paper, we present a review of security of various data management systems used in CPS. Since CPS are composed of systems of (sub)systems that generate a huge amount of data (ie, periodical sensor input data), therefore, recently, NoSQL and NewSQL data management systems have emerged as popular data management systems to support efficient and scalable analysis of unstructured data. Unfortunately, these systems were not initially build for data security and thus are vulnerable to numerous security attacks. Considering flexible data model and efficient access methods in NoSQL and NewSQL, we discuss the security attacks on such data management systems and their corresponding solutions to mitigate them. In particular, we analyze the system and data security of popular NoSQL and NewSQL systems. To analyze that, we defined feature vectors for system and data security and compared the data systems against them. Finally, we propose security solutions for data management systems by identifying various security vulnerabilities in internal security algorithms of such systems. [ABSTRACT FROM AUTHOR]

Summary: Globally, urbanization has increased due to the availability of the facilities, jobs, and better standard of living in cities. Increase in urban population has caused increase in urban commute. The increased pressure on urban settlements has made design and optimization of urban civil infrastructure very challenging especially road transport infrastructure. Domain experts such as transportation managers, engineers, scientist, and academics need effective, easy, and readily usable computational modeling and simulation tools to conduct systematic inquiry for design and optimization of the transportation system. Free and open‐source software (FOSS) community has developed many vehicular traffic simulation software that are cost‐effective and extensible, however are difficult to use. Usually, domain experts do not have hands‐on software skills such as XML‐based interfaces, software source versioning, and build management. To bridge this gap, in our work, an integrated development environment (IDE), namely, integrated vehicular traffic simulation environment (ITE), has been developed. ITE is developed on top of an existing FOSS multimodal open‐source vehicular‐traffic simulator (MovSim). ITE includes a scenario building tool for domain experts. It could be used to model road infrastructure and vehicular traffic in an integrated manner. The tool could be used to build and experiment novel traffic infrastructures and policies. Our work helps in reducing learning curve of domain experts by providing a free and open source, easy and readily usable vehicular traffic simulation tool. [ABSTRACT FROM AUTHOR]