Back-end Implementation Research Articles

MelCochleaGram-DeepCNN: Sequentially Fused Spectrogram and the DeepCNN Classifiers-based Audio Spoof Detection System

Automatic Speaker Verification (ASV) systems are crucial in various fields, enabling speaker identification for authentication, fraud detection, and forensic applications. While the simplicity and effectiveness of speech biometrics are driving the demand for ASV systems, their increasing popularity raises concerns about vulnerability to speech attacks. To enhance the security of these systems, the work in this paper proposes a spectrogram-based solution that leverages the robustness of spectrograms in audio analysis and feature extraction. The proposed model consists of two main components: frontend and backend. In the frontend, it introduces a novel spectrogram MelCochleaGram (MCG) by fusing Mel Spectrogram and Cochleagram, sequentially. For the backend implementation, pre-trained deep learning models, including ResNet50, ResNet50V2, and InceptionV3, are employed using the Keras framework. These models are individually paired with MCG to detect deepfake and replay attacks. To validate the effectiveness of the proposed system, thorough experimentation is conducted on two datasets: the DEepfake CROss-lingual (DECRO) evaluation dataset and the Voice Spoofing Detection Corpus (VSDC). The proposed combination of MCG with ResNet50 has achieved an Equal Error Rate (EER) of 0.2%, and 1.2% for deepfake detection over DECRO English and Chinese datasets, respectively. Also, for replay attack detection, the proposed combination has produced an EER of 1.4%.

DietNerd: A Nutrition Question-Answering System That Summarizes and Evaluates Peer-Reviewed Scientific Articles

DietNerd is a large language model-based system designed to enhance public health education in diet and nutrition. The system responds to user questions with concise, evidence-based summaries and assesses the quality and potential biases of cited research. This paper describes the system’s workflow, back-end implementation, and the prompts used. Accuracy and quality-of-response results are presented based on an automated comparison against systematic surveys and against the responses of similar state-of-the-art systems through human feedback from registered dietitians. DietNerd is among the highest-evaluated of these systems and is unique in combining safety features with sophisticated source analysis. Thus, DietNerd could be a tool to bridge the gap between complex scientific literature and public understanding.

Design and Implementation of a Digital Notice Board and Forum Discussion System

Abstract— This research paper explores the development of an educational management system leveraging modern web technologies such as React.js for frontend development, Node.js for backend implementation, and MongoDB for database management. The system comprises two main modules: notice board and forum discussion. A Notice Board and Forum Discussion system for schools serves as a centralized platform for disseminating important information and fostering communication among students, teachers, and parents. This system provides a virtual notice board where announcements, reminders, and event schedules can be posted, ensuring that all stakeholders stay informed in real-time. Additionally, it features a forum discussion section where users can engage in academic discourse, seek clarification on topics, and collaborate on projects. By facilitating seamless communication and collaboration, this system enhances the educational experience within the school community, promoting active participation and knowledge sharing. IndexTerms – Web-Based Application, Notice Creation, Forum Creation and , Forum having comment option using MERN Stack.

Creating and Evaluating School Exams with Marks Obtained

Abstract— This research paper explores the development of an educational management system leveraging modern web technologies such as React.js for frontend development, Node.js for backend implementation, and MongoDB for database management. The system comprises two main modules: exam creation and result display. The primary focus is on designing a user-friendly interface for teachers to create exams and for students to access their results. Additionally, a leaderboard feature is integrated to showcase students’ rankings based on their performance. This paper discusses the technical architecture, research objectives, and the significance of this system in enhancing educational administration. The module is developed using the MERN stack technology. The ultimate goal of this module is to make the educational system more efficient for both teachers and students. Keywords – Educational Management System, Modern Web Technologies, Exam Creation, Technical Architecture, MERN Stack.

Library management database design and application

Under the data-centric business environment, efficient database design is pivotal for efficient data management across various sectors. For libraries and bookstores, a well-tailored database is essential to categorize, index, and swiftly retrieve vast amounts of data, ensuring efficient operations. MySQL is an open-source database management system which facilitates efficient data manipulation. Based on MySQL, this essay delves into the realm of library database design and application, addressing the need for streamlined systems. This research addresses the need for adaptation in the evolving technology landscape and offers practical insights for librarians and researchers aiming to optimize information management in modern libraries. Employing the basic steps for database design, we explore one methodology for designing a library management database based on the design of database requirement, modeling, backend implementation, efficiency optimization and testing using MySQL. Through this approach, the study provides a potential solution that meets the basic requirements of libraries and enhances information management practices.

Integrated Project Development through Combined Theory and Practices of Core Courses focusing on Software Development Skills: Integrated Learning Framework

The National Education Policy promotes moving from the conventional content-heavy and memorization learning practice towards holistic learning/integrated learning. It imparts a creative and multidisciplinary curriculum that focuses equally on curriculum and assessment. All educational establishments assess students using written examinations, quizzes, seminars, term paper writing, and course projects. A semester typically includes 4-5 courses, and students must earn credits for these courses by scoring a good Cumulative Grade Point Average (CGPA). As course projects offer depth knowledge/holistic learning/lifelong learning of a course for the student, many courses include course projects as one of the activities in the course. If all the courses are intended to include course projects as a mandatory pedagogy, it will be difficult for students to acquire in-depth knowledge and required skills while also dealing with stress. So we are proposing an integrated learning framework by applying the theory and practices of two core courses- Software Engineering and Web Technologies to develop a web application. This integrated learning focuses on developing software development and software testing skills in computer science for undergraduate students pursuing a bachelor of engineering degree. This framework alleviated the pressure on students during placement and created job opportunities in software development. The framework consists of three important phases- The first phase includes the identification of the problem as a need for customers, writing requirements and analyzing the same. Students apply modular design principles and break down the codebase into distinct modules. This technique enhances code organization, reusability, and maintainability. The second phase focused on developing the front end by harnessing the power of Angular, a leading web framework, to craft a sleek and interactive user interface. The backend is built using Node.js, which serves as the foundation, enabling the software system to cater to highperformance server environments. These modules communicated seamlessly through well-defined APIs, facilitating the integration of various components within the application, ultimately delivering a seamless and responsive user experience. An industry expert conducted a workshop on Angularsoftware testing workshop was conducted for students by industry experts to expose the students to designing test cases, test plans, and testing strategies. The hands-on experience on testing tools was provided during the workshop. Faculty reviews are conducted on each phase, and rubrics-based assessment is done on each phase. Approximately sixty teams created web-based applications for real-world scenarios. Positive aspects of the framework in feedback indicated that more than 87% of the students agreed that they could apply Software engineering principles and practices such as requirements management. modular design and testing in web applications. Also, more than 85% of students acquire skills from code-to-web design mastery by developing web applications in Angular Node.js and backend implementation. This framework helped to improve teamwork, presentation and communication skills. Confidence in software development improved to a greater extent. The design and implementation of the framework met the stated outcome of the courses. The student's academic performance improved by 10% compared to the previous year when students were not involved in the integrated project development. Keywords— Framework, learning, practices, project, skills, technology, testing, web

PLATO: A Predictive Drug Discovery Web Platform for Efficient Target Fishing and Bioactivity Profiling of Small Molecules.

PLATO (Polypharmacology pLATform predictiOn) is an easy-to-use drug discovery web platform, which has been designed with a two-fold objective: to fish putative protein drug targets and to compute bioactivity values of small molecules. Predictions are based on the similarity principle, through a reverse ligand-based screening, based on a collection of 632,119 compounds known to be experimentally active on 6004 protein targets. An efficient backend implementation allows to speed-up the process that returns results for query in less than 20 s. The graphical user interface is intuitive to give practitioners easy input and transparent output, which is available as a standard report in portable document format. PLATO has been validated on thousands of external data, with performances better than those of other parallel approaches. PLATO is available free of charge (http://plato.uniba.it/ accessed on 13 April 2022).

SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules.

SwissTargetPrediction is a web tool, on-line since 2014, that aims to predict the most probable protein targets of small molecules. Predictions are based on the similarity principle, through reverse screening. Here, we describe the 2019 version, which represents a major update in terms of underlying data, backend and web interface. The bioactivity data were updated, the model retrained and similarity thresholds redefined. In the new version, the predictions are performed by searching for similar molecules, in 2D and 3D, within a larger collection of 376 342 compounds known to be experimentally active on an extended set of 3068 macromolecular targets. An efficient backend implementation allows to speed up the process that returns results for a druglike molecule on human proteins in 15–20 s. The refreshed web interface enhances user experience with new features for easy input and improved analysis. Interoperability capacity enables straightforward submission of any input or output molecule to other on-line computer-aided drug design tools, developed by the SIB Swiss Institute of Bioinformatics. High levels of predictive performance were maintained despite more extended biological and chemical spaces to be explored, e.g. achieving at least one correct human target in the top 15 predictions for >70% of external compounds. The new SwissTargetPrediction is available free of charge (www.swisstargetprediction.ch).

Technological infrastructure supporting the story network principle of the Atlas of the Ageing Society

Atlases have a long tradition of showing and linking information for the exploration of various mostly spatially related topics. The Atlas of the Ageing Society is an interactive platform illustrating age related data. It enables individuals to explore facts and information related to age and the ageing society. To support content representation as well as a diverse audience, we developed the “story network principle”, which embeds annotated visualizations into a network of information in order to allow storytelling with data. Enabling the exploration of such a multifaceted and highly interconnected data landscape, however, posed some technical challenges. This paper describes and discusses a back-end implementation that meets the requirements of the story network principle from a technical perspective. We detail and exemplify the design and implementation of the atlas infrastructure to enable others to benefit from our developments and approaches to the challenges. The story network principle is potentially applicable to a range of applications such as other atlases or digital portfolios.

Extensibility and Composability of a Multi-Stencil Domain Specific Framework

As the computation power of modern high performance architectures increases, their heterogeneity and complexity also become more important. One of the big challenges of exascale is to reach programming models that give access to high performance computing (HPC) to many scientists and not only to a few HPC specialists. One relevant solution to ease parallel programming for scientists is domain specific language (DSL). However, one problem to avoid with DSLs is to mutualize existing codes and libraries instead of implementing each solution from scratch. For example, this phenomenon occurs for stencil-based numerical simulations, for which a large number of languages has been proposed without code reuse between them. The Multi-Stencil Framework (MSF) presented in this paper combines a new DSL to component-based programming models to enhance code reuse and separation of concerns in the specific case of stencils. MSF can easily choose one parallelization technique or another, one optimization or another, as well as one back-end implementation or another. It is shown that MSF can reach same performances than a non component-based MPI implementation over 16,384 cores. Finally, the performance model of the framework for hybrid parallelization is validated by evaluations.

State management in Apache Flink®

Stream processors are emerging in industry as an apparatus that drives analytical but also mission critical services handling the core of persistent application logic. Thus, apart from scalability and low-latency, a rising system need is first-class support for application state together with strong consistency guarantees, and adaptivity to cluster reconfigurations, software patches and partial failures. Although prior systems research has addressed some of these specific problems, the practical challenge lies on how such guarantees can be materialized in a transparent, non-intrusive manner that relieves the user from unnecessary constraints. Such needs served as the main design principles of state management in Apache Flink, an open source, scalable stream processor. We present Flink's core pipelined, in-flight mechanism which guarantees the creation of lightweight, consistent, distributed snapshots of application state, progressively, without impacting continuous execution. Consistent snapshots cover all needs for system reconfiguration, fault tolerance and version management through coarse grained rollback recovery. Application state is declared explicitly to the system, allowing efficient partitioning and transparent commits to persistent storage. We further present Flink's backend implementations and mechanisms for high availability, external state queries and output commit. Finally, we demonstrate how these mechanisms behave in practice with metrics and large-deployment insights exhibiting the low performance trade-offs of our approach and the general benefits of exploiting asynchrony in continuous, yet sustainable system deployments.

Crowdsourcing Phase and Timing of Pre-Timed Traffic Signals in the Presence of Queues: Algorithms and Back-End System Architecture

This paper describes a crowdsourcing-based system for phase and timing estimation of pre-timed traffic signals. The input crowd is a real-time feed of sparse and low-frequency probe vehicle data, and the output is an estimated collection of Signal Phase and Timing (SPaT) information. The estimations could be ultimately fed into a connected vehicle's driver assistant application. Different from the authors' previous work, the approach described in this paper ensures the accuracy of the SPaT estimations even in the presence of queues. This was achieved by investigating the probe data influenced by the heavy traffic and the delay in queues. This paper is also a sequel to the authors' previous work as it provides an in-depth overview of the crowdsourcing algorithms and their back-end implementation. The accuracy of the crowdsourcing algorithm is also experimentally evaluated for a selection of pre-timed traffic lights in San Francisco, CA, USA, by utilizing a real-time data feed of San Francisco's public buses as an example data source.

A high quality compiler tool for application-specific instruction-set processors with library and parallel supports

Developing a high quality compiler tool for application-specific instruction-set processors (ASIPs) including DSP for multimedia application is challenging. The specialization in ASIPs often calls for extensions at the high-level languages to allow the designers to exploit the specialized capabilities. This in turn requires the frontend of the compiler to handle the new syntax and carry the intentions of the designers across to the compiler backend implementations. The backend implementations also require extra efforts for optimized uses of the specialize features of ASIPs. Meanwhile, because of the diversity of the application, it is necessary to make full use of the compiler to complete supports and to make up some shortages of ASIP processors, the corresponding library functions are increased to support of certain operations, such as floating point arithmetic that may not be supported in ASIPs. With the development of the embedded parallelism, the advanced ASIP compilers need the support of parallelism for future application. This paper describes the High-performance C Compiler (HCC) and its specific implementation for an industrial ASIP and its family processors. HCC is a C language compiler extended and retargeted from GCC. A compiler extension framework is proposed processing programming syntax extensions of standard ANSI C for the ASIPs. With target-specific implementation, the adding optimized arithmetic functions library and chips definition file (CDF) as well as the header files for corresponding ASIPs, HCC compiler could be enhanced for the processing capabilities of target processors. Finally, this paper describes a new compiler static allocation and scheduling scheme for loop parallelization based on the OpenMP specification to improve the load imbalance. We have conducted analysis and extensive experiments to verify the correctness and effectiveness of the HCC compiler with the presented ideas. The results show that HCC compiler has a stable performance with excellent codes quality and it has been used in market.

Enabling LTE in TVWS with radio environment maps: From an architecture design towards a system level prototype

This paper reports recent prototyping efforts that show the feasibility of the radio environmental map to enable efficient exploitation of TV white spaces by a cellular LTE system. We describe a flexible REM backend implementation, fully integrated with standard-compliant operational LTE base station equipment. Simulations results indicate that REMs enhance white-space detection by their means to incorporate accurate and local channel propagation information, while experimental laboratory results illustrate the feasibility and performance of transmitter localization capabilities in a REM.

Interferometric direction finding with a metamaterial detector

We present measurements and analysis demonstrating useful direction finding of sources in the S band (2–4 GHz) using a metamaterial detector. An augmented metamaterial absorber that supports magnitude and phase measurement of the incident electric field, within each unit cell, is described. The metamaterial is implemented in a commercial printed circuit board process with off-board back-end electronics. We also discuss on-board back-end implementation strategies. Direction finding performance is analyzed for the fabricated metamaterial detector using simulated data and the standard algorithm, MUtiple SIgnal Classification. The performance of this complete system is characterized by its angular resolution as a function of radiation density at the detector. Sources with power outputs typical of mobile communication devices can be resolved at kilometer distances with sub-degree resolution and high frame rates.

Metrics Based Quality Estimation of Speech Recognition Features

The performance of an automatic speech recognition system heavily depends on the used feature set. Quality of speech recognition features is estimated by classification error, but then the recognition experiments must be performed, including both front-end and back-end implementations. We propose a method for features quality estimation that does not require recognition experiments and accelerate automatic speech recognition system development. The key component of our method is usage of metrics right after front-end features computation. The experimental results show that our method is suitable for recognition systems with back-end Euclidean space classifiers.

SeqWare Query Engine: storing and searching sequence data in the cloud

BackgroundSince the introduction of next-generation DNA sequencers the rapid increase in sequencer throughput, and associated drop in costs, has resulted in more than a dozen human genomes being resequenced over the last few years. These efforts are merely a prelude for a future in which genome resequencing will be commonplace for both biomedical research and clinical applications. The dramatic increase in sequencer output strains all facets of computational infrastructure, especially databases and query interfaces. The advent of cloud computing, and a variety of powerful tools designed to process petascale datasets, provide a compelling solution to these ever increasing demands.ResultsIn this work, we present the SeqWare Query Engine which has been created using modern cloud computing technologies and designed to support databasing information from thousands of genomes. Our backend implementation was built using the highly scalable, NoSQL HBase database from the Hadoop project. We also created a web-based frontend that provides both a programmatic and interactive query interface and integrates with widely used genome browsers and tools. Using the query engine, users can load and query variants (SNVs, indels, translocations, etc) with a rich level of annotations including coverage and functional consequences. As a proof of concept we loaded several whole genome datasets including the U87MG cell line. We also used a glioblastoma multiforme tumor/normal pair to both profile performance and provide an example of using the Hadoop MapReduce framework within the query engine. This software is open source and freely available from the SeqWare project (http://seqware.sourceforge.net).ConclusionsThe SeqWare Query Engine provided an easy way to make the U87MG genome accessible to programmers and non-programmers alike. This enabled a faster and more open exploration of results, quicker tuning of parameters for heuristic variant calling filters, and a common data interface to simplify development of analytical tools. The range of data types supported, the ease of querying and integrating with existing tools, and the robust scalability of the underlying cloud-based technologies make SeqWare Query Engine a nature fit for storing and searching ever-growing genome sequence datasets.

Notice of Violation of IEEE Publication Principles: Joint Redundant Residue Number Systems and Module Isolation for Mitigating Single Event Multiple Bit Upsets in Datapath

In this paper, we propose a joint scheme which combines redundant residue number systems (RRNS) with module isolation (MI) for mitigating single event multiple bit upsets (SEMBUs) in datapath. The proposed hardening scheme employs redundant residues to improve the fault tolerance for datapath and module spacings to guarantee that SEMBUs caused by charge sharing do not propagate among the operation channels of different moduli. The features of RRNS, such as independence, parallel and error correction, are exploited to establish the radiation hardening architecture for the datapath in radiation environments. In the proposed scheme, all of the residues can be processed independently, and most of the soft errors in datapath can be corrected with the redundant relationship of the residues at correction module, which is allocated at the end of the datapath. In the back-end implementation, module isolation technique is used to improve the soft error rate performance for RRNS by physically separating the operation channels of different moduli. The case studies show at least an order of magnitude decrease on the soft error rate (SER) as compared to the NonRHBD designs, and demonstrate that RRNS+MI can reduce the SER from 10-12 to 10-17 when the processing steps of datapath are 106. The proposed scheme can even achieve less area and latency overheads than that without radiation hardening, since RRNS can reduce the operational complexity in datapath.

The Back-End of a Two-Layer Model for a Federated National Datastore for Academic Research VOs that Integrates EGEE Data Management

This paper proposes an architecture for the back-end of a federated national datastore for use by academic research communities, developed by the e-INIS (Irish National e-InfraStructure) project, and describes in detail one member of the federation, the regional datastore at Trinity College Dublin. It builds upon existing infrastructure and services, including Grid-Ireland, the National Grid Initiative and EGEE, Europe’s leading Grid infrastructure. It assumes users are in distinct research communities and that their data access patterns can be described via two properties, denoted as mutability and frequency-of-access. The architecture is for a back-end—individual academic communities are best qualified to define their own front-end services and user interfaces. The proposal is designed to facilitate front-end development by placing minimal restrictions on how the front-end is implemented and on the internal community security policies. The proposal also seeks to ensure that the communities are insulated from the back-end and from each other in order to ensure quality of service and to decouple their front-end implementation from site-specific back-end implementations.

Performance evaluation of a grid resource monitoring and discovery service

The Grid Information Service (GIS) is one of the Grid Common Services which make up the basic functions belonging to Grids. This service offers a resource discovery mechanism, of which an implementation is provided by the Monitoring and Discovery Service (MDS- 2) which is part of the Globus Toolkit. Grid applications are typically the users of this resource discovery mechanism; knowledge is thus obtained about the existence of appropriate resources on which to execute jobs. Since these Grid applications are likely to be influenced by dynamic middleware, it is crucial that they experience a reliable performance for the proper utilisation of resources and for accountability purposes. Consequently, the approach taken in this paper is to investigate and evaluate a level of performance obtainable from the MDS. A better understanding of the performance of the GRIS (Grid Resource Information Service) and subsequently the GIIS (Grid Index Information Service), leads to a more standard way of formalising the performance of a Grid Information Service. This is achieved by defining a number of performance metrics which are analysed against a set of different information gathering methods and GRIS back-end implementations.