Server-side Modules Research Articles

Fully Functional Shopping Mall Application – ShopVista

In today's fast-paced world, shopping has become an integral part of daily life for most individuals. However, the demands of busy lifestyles have left limited time for this essential activity, prompting a quest for quicker and more convenient shopping solutions. Shoppers encounter a range of challenges, including uncertainty about product availability, navigating extensive shopping malls, and occasionally forgetting intended purchases. To address these issues, this paper introduces a comprehensive shopping mall application that offers a solution to modern shopping dilemmas. The proposed application offers a wealth of features, including detailed information about every shop within a mall, real-time updates on product availability, the ability to create and manage customer wish lists, and an interactive mall map. This multifaceted system comprises a mobile application designed for the Android platform and a robust server-side module serving as the central database connecting customers and shop owners. Additionally, there is a web service interface that allows administrators to efficiently manage functions within this system. This research paper outlines the conceptualization, development, and implementation of this cutting-edge shopping mall application. By addressing the challenges faced by today's shoppers and harnessing the power of technology, the proposed solution seeks to enhance the shopping experience, offering both shoppers and mall operators a modern and efficient means of engagement.

The QR code intelligent positioning system of the LBS cloud platform in the Internet of things environment

<span>Aiming</span><strong></strong><span>at the problems of long positioning time and poor positioning accuracy in traditional positioning systems, a WeChat applet QR code area positioning system based on the LBS cloud platform is proposed and designed. The overall architecture of the system is divided into three parts: LBS cloud service, central data processing, and QR code positioning terminal for small programs. The hardware is designed from the server-side module, processor and positioning module to provide a basis for system construction. In the software design, the WeChat applet QR code area image is collected, the image edge features are enhanced and filtered, the positioning target is determined according to the processed image edge features, and the WeChat applet QR code area positioning system design is completed. The experimental results show that the positioning time of the system is equivalent to 50% of the traditional system, and the positioning accuracy is always maintained above 99.5%, which has significant advantages.</span>

Calorie Detection of Food Image based on SVM Algorithm

Nowadays, standard intake of healthy food is vital for keeping a diet to avoid obesity within the human body . In this paper, we present a totally unique system supported machine learning that automatically performs accurate classification of food images and estimates food attributes. This paper proposes a machine learning model consisting of a support vector machine that classifies food into specific categories within the training a part of the prototype system. The most purpose of the proposed method is to reinforce the accuracy of the pre-training model. The paper designs a prototype system supported the client server network model. The client sends an image detection request and processes it on the server side. The prototype system is meant with three main software components, including a pre-trained support vector machine training module for classification purposes, a text data training module for attribute estimation models, and a server-side module. We experimented with a selection of food categories, each containing thousands of images, and therefore the machine learning training to understand higher classification accuracy.

Machine Learning Based Approach on Food Recognition and Nutrition Estimation

Abstract Nowadays, standard intake of healthy food is necessary for keeping a balanced diet to avoid obesity in the human body. In this paper, we present a novel system based on machine learning that automatically performs accurate classification of food images and estimates food attributes. This paper proposes a deep learning model consisting of a convolutional neural network that classifies food into specific categories in the training part of the prototype system. The main purpose of the proposed method is to improve the accuracy of the pre-training model. The paper designs a prototype system based on the client server model. The client sends an image detection request and processes it on the server side. The prototype system is designed with three main software components, including a pre-trained CNN model training module for classification purposes, a text data training module for attribute estimation models, and a server-side module. We experimented with a variety of food categories, each containing thousands of images, and through machine learning training to achieve higher classification accuracy.

EPAD: An Image Annotation and Analysis Platform for Quantitative Imaging.

Medical imaging is critical for assessing the response of patients to new cancer therapies. Quantitative lesion assessment on images is time-consuming, and adopting new promising quantitative imaging biomarkers of response in clinical trials is challenging. The electronic Physician Annotation Device (ePAD) is a freely available web-based zero-footprint software application for viewing, annotation, and quantitative analysis of radiology images designed to meet the challenges of quantitative evaluation of cancer lesions. For imaging researchers, ePAD calculates a variety of quantitative imaging biomarkers that they can analyze and compare in ePAD to identify potential candidates as surrogate endpoints in clinical trials. For clinicians, ePAD provides clinical decision support tools for evaluating cancer response through reports summarizing changes in tumor burden based on different imaging biomarkers. As a workflow management and study oversight tool, ePAD lets clinical trial project administrators create worklists for users and oversee the progress of annotations created by research groups. To support interoperability of image annotations, ePAD writes all image annotations and results of quantitative imaging analyses in standardized file formats, and it supports migration of annotations from various propriety formats. ePAD also provides a plugin architecture supporting MATLAB server-side modules in addition to client-side plugins, permitting the community to extend the ePAD platform in various ways for new cancer use cases. We present an overview of ePAD as a platform for medical image annotation and quantitative analysis. We also discuss use cases and collaborations with different groups in the Quantitative Imaging Network and future directions.

Dynamic Load Rebalancing Algorithm for Private Cloud

Infrastructure-As-A-Service (IAAS) provides an environmental setup under any type of cloud. In Distributed file system (DFS), nodes are simultaneously serve computing and storage functions; that is parallel Data Processing and storage in cloud. Here, file is considered as a data or load. That file is partitioned into a number of File chunks (FC) allocated in distinct nodes so that Map Reduce tasks can be performed in parallel over the nodes. Files and Nodes can be dynamically created, deleted, and added. This results in load imbalance in a distributed file system; that is, the file chunks are not distributed as uniformly as possible among the Chunk Servers (CS). Emerging distributed file systems in production systems strongly depend on a central node for chunk reallocation or Distributed node to maintain global knowledge of all chunks. This dependence is clearly inadequate in a large-scale, failure-prone environment because the central load balancer is put under considerable workload that is linearly scaled with the system size, it may thus become the performance bottleneck and the single point of failure and memory wastage in distributed nodes. So, we have to enhance the Client side module with server side module to create, delete and update the file chunks in Client Module. And manage the overall private cloud and apply dynamic load balancing algorithm to perform auto scaling options in private cloud. In this project, a fully distributed load rebalancing algorithm is presented to cope with the load imbalance problem.

CH5M3D: an HTML5 program for creating 3D molecular structures

BackgroundWhile a number of programs and web-based applications are available for the interactive display of 3-dimensional molecular structures, few of these provide the ability to edit these structures. For this reason, we have developed a library written in JavaScript to allow for the simple creation of web-based applications that should run on any browser capable of rendering HTML5 web pages. While our primary interest in developing this application was for educational use, it may also prove useful to researchers who want a light-weight application for viewing and editing small molecular structures.ResultsMolecular compounds are drawn on the HTML5 Canvas element, with the JavaScript code making use of standard techniques to allow display of three-dimensional structures on a two-dimensional canvas. Information about the structure (bond lengths, bond angles, and dihedral angles) can be obtained using a mouse or other pointing device. Both atoms and bonds can be added or deleted, and rotation about bonds is allowed. Routines are provided to read structures either from the web server or from the user’s computer, and creation of galleries of structures can be accomplished with only a few lines of code. Documentation and examples are provided to demonstrate how users can access all of the molecular information for creation of web pages with more advanced features.ConclusionsA light-weight (≈ 75 kb) JavaScript library has been made available that allows for the simple creation of web pages containing interactive 3-dimensional molecular structures. Although this library is designed to create web pages, a web server is not required. Installation on a web server is straightforward and does not require any server-side modules or special permissions. The ch5m3d.js library has been released under the GNU GPL version 3 open-source license and is available from http://sourceforge.net/projects/ch5m3d/.

PhEDEx Data Service

The PhEDEx Data Service provides access to information from the central PhEDEx database, as well as certificate-authenticated managerial operations such as requesting the transfer or deletion of data. The Data Service is integrated with the "SiteDB" service for fine-grained access control, providing a safe and secure environment for operations. A plug-in architecture allows server-side modules to be developed rapidly and easily by anyone familiar with the schema, and can automatically return the data in a variety of formats for use by different client technologies. Using HTTP access via the Data Service instead of direct database connections makes it possible to build monitoring web-pages with complex drill-down operations, suitable for debugging or presentation from many aspects. This will form the basis of the new PhEDEx website in the near future, as well as providing access to PhEDEx information and certificate-authenticated services for other CMS dataflow and workflow management tools such as CRAB, WMCore, DBS and the dashboard. A PhEDEx command-line client tool provides one-stop access to all the functions of the PhEDEx Data Service interactively, for use in simple scripts that do not access the service directly. The client tool provides certificate-authenticated access to managerial functions, so all the functions of the PhEDEx Data Service are available to it. The tool can be expanded by plug-ins which can combine or extend the client-side manipulation of data from the Data Service, providing a powerful environment for manipulating data within PhEDEx.