The rapid expansion of healthcare data necessitates scalable, interoperable, and privacy-preserving mobile data management solutions. MedEForm addresses this by integrating the openEHR standard with Google Firebase to deliver a real-time, cloud-based electronic health record (EHR) platform optimized for Android devices. Utilizing Archetype Definition Language (ADL) models from the openEHR Clinical Knowledge Manager (CKM), MedEForm features a GUI generator that dynamically renders context-aware data-entry forms client-side, eliminating the need for app updates. Authentication is securely managed via Firebase Authentication, while encrypted user credentials and EHR data are stored in Firestore, Firebase’s NoSQL document store. A dedicated query module enables role-based execution of single-patient, multi-patient, and cohort-level queries across a 90,000-instance dataset. Firestore’s real-time synchronization, offline support, and fine-grained security rules enforce low-latency access with robust access control. For epidemiological analysis, MedEForm implements anonymization of demographic, clinical, and geospatial data at weekly intervals, storing these de-identified records in a separate Firestore collection. This architecture supports high-quality analytics while upholding stringent privacy guarantees. By unifying open standards, dynamic interface generation, and secure cloud infrastructure, MedEForm offers a modular and interoperable framework for mobile health data collection and analysis.

The music industry is facing challenges in engaging fans and providing transparency, feedback, and rewards. Blockchain technology presents a potential solution by enabling new forms of fan engagement and participation. This paper proposes a blockchain-based music platform that leverages Ethereum’s decentralized platform and smart contract functionality. Ethereum’s Proof of Stake (PoS) consensus algorithm makes it more energy-efficient than the Proof of Work (PoW) algorithm used by Bitcoin. The platform could facilitate investment in up-and-coming artists, feedback mechanisms, and rewards for fans. The scalability and decentralization of Ethereum make it an attractive choice for building a platform that can accommodate a large number of users and transactions without compromising performance. The proposed platform offers a secure, scalable, and decentralized solution that provides novel ways for fans to engage and participate in the music industry while being energy-efficient, sustainable, and accessible to everyone with a stake in the system.

Smartphones, tablets, and other mobile devices have grown exponentially over the last two decades. In the past, people relied on reading paper books or newspapers to learn about the world around them but now have switched to reading from digital text files or the Internet. Consequently, the demand for eBooks has increased significantly. Traditional publishers are now confronted with publishing on the web due to this situation. eBook digital rights and copyright management has become a significant issue. To overcome this issue, we propose an efficient eBook Management system based on Blockchain to prevent piracy of eBooks, protect the digital rights management and stop copyright infringement.

Weighted Frequent Itemset (WFI) mining is an important model in data mining. The popular adoption and successful industrial application of this model has been hindered by the following two obstacles: (i) finding WFIs is a computationally expensiveness process as these itemsets do not satisfy the downward closure property and (ii) lack of parallel algorithms to find WFIs in very large databases (e.g. astronomical data and twitter data). This paper makes an effort to address these two obstacles. Two pattern-growth algorithms, Sequential Weighted Frequent Pattern-growth and Parallel Weighted Frequent Pattern-growth, have been introduced to discover WFIs efficiently. Both algorithms employ three novel pruning techniques to reduce the computational cost effectively. The first pruning technique prunes some of the uninteresting items by employing a criterion known as cutoff weight. The second pruning technique, called conditional pattern base elimination, eliminates the construction of conditional pattern bases if a suffix item is an uninteresting item. The third pruning technique, called pattern-growth termination, defines a new terminating condition for the pattern-growth technique. Experimental results demonstrate that the proposed algorithms are memory and runtime efficient, and highly scalable as well.

Astronomy is a data-intensive science. The large amount of data available in the astronomical domain needs query languages to gain valuable astronomical information. The paper has two goals. First, it presents the challenges for domain-specific query language for managing astronomical data. Second, it proposes a solution of managing such large amount of data through incorporating a multi-stage query language with Workflow Management technique. The paper demonstrates a web based query management system able to handle user queries in single or multi-stage.

In the last decade, cheaper and more powerful computations have favored a sufficient surge in research and development of applications in the fields of machine and deep learning. Though often varying in approach, these activities aim mostly at solving similar tasks such as speech synthesis, emotion detection, image recognition, mathematical computations etc. Usually, the typical scenario of using designed algorithms/applications includes inputting data represented in some predefined formats and launching a corresponding program tool that produces expected output data as well as analyzing obtained results. These applications are numerous, and are created by different research teams and laboratories using different techniques and environments including locations, interfaces and procedures to access, query and use them. In a collaborative working environment, developing independent user interfaces for each deep learning application could entail a lot of additional development efforts. In the presented paper, we propose a standardized and flexible interface to reduce design efforts, based on integration of various Deep Learning services (DL services). We also demonstrate a protocol for communication between the user interface and the heterogeneous services. This platform will enable developers of deep learning models to be concerned solely with developing and tuning their models, which can be easily plugged into the central user interface, conveniently exposing their services to users who will have homogeneous central access to a wide-range of DL services, from a unified interface.

Most keyword searches target precision for finding the most relevant document. However some target recall, finding all relevant documents. Our system supports high recall searches that return hundreds or thousands of relevant results. In particular, it provides a visualization that shows the distribution of search results relative to the distribution of items for the entire corpus. Such relative distributional features include over and under representation, clusters and outliers. The contribution of this paper is efficient visualisation, that is, how to provide the best relative distribution view for a given data cube size. This requirement is translated to: for which limited size meta-data summary cube are search results disambiguated the most in our relative distribution view. We identify metrics and several algorithms for such a summary cube selection.

Due to the Internet advancement, more applications are being developed over heterogeneous technologies and platforms. Thereby, reusability and interoperability are the important aspects for developing and exposing the computational services. That is why the Enterprise Application Integration is an important aspect in order to leverage high reusability and interoperability among disparate applications and services. Pattern based design is an effective way to avoid an expensive process of reinventing, rediscovering as well as revalidating agnostic software artifacts. In this paper, we are proposing a modification of the traditional Model-View-Controller (MVC) design pattern and exploring other composite patterns for an efficient integration of the applications and services. The key point is that the demarcation of a Functional (View) and an Implementation (Model) task can be achieved deliberately by inducing an Integrator (Controller). The Controller capabilities can be significantly enriched by encapsulating certain Non-Functional activities such as security, reliability, scalability, and routing of request. This enhancement enables the separation of Integration Logic from Functional Logic (Client Application) and Implementation Logic (Service). In our approach, the Controller can be considered as the compound design pattern of the Enterprise Service Bus (ESB). To demonstrate how the modified MVC pattern can be used for developing heterogeneous software environment, we are developing an e-Learning Computational Cloud (eLC2) software environment. This paper discusses the peculiarities of the modified MVC design patterns, main components of system architecture as well as how integration of the software components is realized by using the Dependency Injection pattern to achieve higher reusability and interoperability of Service Oriented applications.

We demonstrate a system that integrates a novel OLAP component with a keyword search engine, to support querying over sparse and ragged corpus data. The key contribution of our system is the integration of dynamically selected point sets such as search results with OLAP querying over aggregated data. During the demonstration, participants will be able to enter a keyword search; observe the returned list of result files; observe distributional features such as outliers and clusters of results in the corpus in multiple dimension views; and select and partition corpus slices in the OLAP component to narrow search results. Participants will be able to experience not just the individual querying features of our system, but the way that they work together to facilitate smooth interaction sequences that combine OLAP and keyword search querying.

Information Requirement Elicitation (IRE) is essential in wireless Web service to elicit information requirements through interactive choice prompts. This article presents a design of a high-level user interface for IRE, in the context of banking database queries by a mobile Web user. The prototype is based on the notion of a Query-By-Object approach of building a query using multiple user-level steps. The test prototype system uses the Mobile Information Devices Profile of the Java 2 Platform, Micro Edition, for a wireless front end, and a Java 2 Platform, Enterprise Edition, application server and an Object-Relational Database Management System at the back end. An empirical study conducted on the prototype has demonstrated that the proposed user interface is intuitive and simple to use. The proposed interface aims to eliminate ambiguities in users' communication by virtue of a step-by-step procedure. The main contributions of this interface are its simplicity to express a query and its expressive power.

In the last few years, many GIS applications have appeared on the Web giving users access to both spatial and non-spatial (attribute) data. Web access to GIS resources needs to address the possibility of access via handheld devices such as mobile phones, PDAs or pocket computers. Currently, only a few research studies are available on high-level user interface for spatial queries on such devices. Thus, an important research problem is to design user-friendly interfaces for mobile Web GIS. Query-by-example (QBE) is a user-friendly language developed for a relational database management system (RDBMS). Many RDBMSs have included support for spatial extensions. In this paper, we make an effort to create extensions for QBE to support spatial queries on mobile devices. It is called spatial mQBE. We show that spatial mQBE is a simple and user-friendly interface. The main strengths of this interface are its simplicity to express a query and its expressive power.

Nowadays, a major activity on the Internet is the retrieval and browsing of multimedia information. Yet, today 's search engines are not really up to the task. Users often have to query various search engines and browse many Web sites before finding a satisfactory answer. Once users find such an answer, presentation of the results is very rigid, i.e., not tailored to the users' needs, and it does not enable users to manipulate the data. Thus, this retrieval activity often becomes tedious. To improve user-information interaction, a major issue is to give search-engines the ability to access data semantics. We propose a framework to address the issue. Our framework combines database and multimedia data mining to endow Web-based applications with the ability to let users manipulate the data at different levels of interest. As an experimental testbed, we implemented a holiday planner that supports users in their search for a hotel. By using database technology, Web-based multimedia interaction becomes possible, offering as a side effect more feasible and reliable feedback.

Distributed locking is commonly adopted for performing concurrency control in distributed systems. It incorporates additional steps for handling deadlocks. This activity is carried out by methods based on wait-for-graphs or probes. The present study examines detection of conflicts based on enhanced local processing for distributed concurrency control. In the proposed "edge detection" approach, a graph-based resolution of access conflicts has been adopted. The technique generates a uniform wait-for precedence order at distributed sites for transactions to execute. The earlier methods based on serialization graph testing are difficult to implement in a distributed environment. The edge detection approach is a fully distributed approach. It presents a unified technique for locking and deadlock detection exercises. The technique eliminates many deadlocks without incurring message overheads.

A number of factors contribute to delays in transaction execution. In a real-time database system, delays due to deadlocks, data accessing, and transaction commit must reduce to enable a transaction to complete successfully. In this report, a model of transaction execution is presented that permits execution and commit of any hard real-time transaction. The execution proceeds without the incidence of deadlock, or other blocking delays such as, due to denial of lock or commit approvals. The proposed technique is based on transaction classification and implementation of a precedence management scheme. The scheme provides an instantaneous execution opportunity to a serializable transaction within a hard real-time database system.

Distributed systems depend on consistent global snapshots for process recovery and garbage collection activity. We provide exact conditions for an arbitrary checkpoint based on independent dependency tracking within clusters of nodes. The method permits nodes (within clusters) to independently compute dependency information based on available (local) information. The existing models of global snapshot computations provide the necessary and sufficient conditions. But, these require expensive global computations. The proposed computations can be performed by a node to identify existing global checkpoints. The nodes can also compute conditions to make a checkpoint, or conditions, such that a collection of checkpoints, can belong to a global snapshot.

Consistent recovery from process failures is an essential component of reliable distributed systems. Many existing recovery techniques use asynchronous message logging and checkpoints. Most of the present approaches depend on logged states of non-fail processes for recovery. A model of recovery based on the current active states of processes has been proposed. The algorithm considers recoverable state of the failed process and current states of the non-failed processes. Each process recovers to a consistent system state independently.

Replicated data management systems adopt the 1-copy serializability criteria for processing transactions. In order to achieve this goal, many approaches rely on obtaining votes from other sites for processing update requests. In the proposed approach, a technique for generation of precedence graphs for each transaction execution is analyzed. The transaction data flow graph approach is a fully distributed approach. The proposed technique, is free from deadlocks, and avoids resubmission of transactions.>