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A great number of visual simultaneous localization and mapping (VSLAM) systems need to assume static features in the environment. However, moving objects can vastly impair the performance of a VSLAM system which relies on the static-world assumption. To cope with this challenging topic, a real-time and robust VSLAM system based on ORB-SLAM2 for dynamic environments was proposed. To reduce the influence of dynamic content, we incorporate the deep-learning-based object detection method in the visual odometry, then the dynamic object probability model is added to raise the efficiency of object detection deep neural network and enhance the real-time performance of our system. Experiment with both on the TUM and KITTI benchmark dataset, as well as in a real-world environment, the results clarify that our method can significantly reduce the tracking error or drift, enhance the robustness, accuracy and stability of the VSLAM system in dynamic scenes.

Cloud computing is a technology to store, process, and manage the data virtually over remote data centers through the internet. Due to the rapid growth of cloud services, the content distribution network broadly uses them to deliver data all over the globe. Due to the rapid generation of the data, delivering on the network is a challenging problem. As the number of replicas increases, the storage cost will be increased. This is a major issue in cloud-based content delivery networks. To overcome this issue, the authors developed a new model for cloud-based CDN with cost optimization algorithm STLM (storage, traffic, latency, cost minimization) to reduce the number of replicas in order to optimize the cost of storage and cost of content delivery. The authors have compared their proposed STLM algorithm with other existing algorithms. They adopt simulation with YouTube e-learning data retrieval. The proposed algorithm is used to place the contents in an efficient way to the geologically dispersed proxy servers in the cloud to encounter quality of service (QoS) and quality of experience (QoE).

This research project was done by Assosa University College of Computing And Informatics. Developing Dynamic Website for Benishangul Gumuz Regional State of Educational Bureau, provides a simple and efficient way of facilitating education service. Since the redundancy and collection of relevant malfunctioned material information can be very time-consuming, it is difficult to achieve this objective using manual systems. All these challenges had been minimized by automating the manual system.This document contains the introduction, methodology that uses tools like Notepad++,HTML, wampserver and MYSQL, data sources like site observation, interview and document analysis, and for design methodology we use object-oriented. For analysis model we use sequence and activity diagram. For system design we include state diagram and use case diagram. To develop the real website, designs had been made that covers the website architecture, user interfaces and database designs.

The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) has been measuring climate and ice sheet properties since 2007. Currently, the PROMICE automatic weather station network includes 25 instrumented sites in Greenland. Accurate measurements of the surface and near-surface atmospheric conditions in a changing climate are important for reliable present and future assessment of changes in the Greenland Ice Sheet. Here, we present the PROMICE vision, methodology, and each link in the production chain for obtaining and sharing quality-checked data. In this paper, we mainly focus on the critical components for calculating the surface energy balance and surface mass balance. A user-contributable dynamic web-based database of known data quality issues is associated with the data products at https://github.com/GEUS-Glaciology-and-Climate/PROMICE-AWS-data-issues/ (last access: 7 April 2021). As part of the living data option, the datasets presented and described here are available at https://doi.org/10.22008/promice/data/aws (Fausto et al., 2019).

Information technology is growing very fast, along with human needs that are also growing, with the internet then we will get millions of information, even we can do business sales through the Internet. therefore it is necessary to use a dynamic website in the sales business as a marketing tool to increase sales. with the website will be easier in introducing its products, as well as conducting various buying and selling transactions.The purpose of this research is to produce a web-based clothing sales information system e-commerce in distro threefive, helping distro threefive in promoting and selling products to consumers. Methodology carried out in data collection related to the preparation or completion of this final task is interviews, observations and literature studies. The results of this study explain the design of the system. which includes ERD, normalization, HIPO structure, program flowchart as well as program performance design. While in the implementation there is a relationship between the table, database structure and application program used and input design (input) and output design (output).

The monitoring information system is one of the main functions in managing student data in Generasi Cerdas private lesson. This study provides the results of an analysis and design of a monitoring information system that can be used to facilitate services to students in monitoring including grades and student absence. This application developed using UML Design and PHP Programming with CodeIgniter Framework and use MySQL Database. CodeIgniter is an open source framework in the form of a PHP framework with an MVC model (Model, View, Controller) for building dynamic websites. The resulting application has been able to provide information of teacher, student, student value and student absence data to assist in processing student and teacher data in the Generasi Cerdas private lesson, so that the institution has a faster, more efficient monitoring information system and easier to use.

The web servers (WSGI-Python) and (PHP-Apache) are in middleware tier architecture. Middleware architecture is between frontend tier and backend tier, otherwise it’s a connection between frontend tier and backend tier for three tier architecture. The ELearning systems are designed by two different dynamic web technologies. First is by Python-WSGI and the second is by Personal Home Page (PHP-Apache). The two websites were designed with different open source and cross platform web technologies programming language namely; Python and PHP in the same structure and weight will evaluate perform over two different operating systems (OSs): 1) Windows-16 and 2) Linux-Ubuntu 20.4. Both systems run over the same computer architecture (64bit) as a server side with a common backend MySQL web database for both of them. Nevertheless, the middleware for PHP is a cross Apache MySQL PHP Perl (XAMPP), but the middleware for Python is Pycharm and the web server gateway interface (WSGI). WSGI and Apache are both web servers and this paper will show which of them has a better response time (RT). On the one hand, the experimental results demonstrate that the Python-WSGI is even weightier in Mbyte than PHP-Apache, on the other hand Python is still faster and more accurate than PHP. The designed SPG is by handwriting codes: one time designed the SPG by PHP source code and the other time designed by Python source code. Both Python-WSGI and PHP-Apache results are targeted to compare by the least time in milliseconds and take in to account enhanced performance.

With the development of network technology, many online educational resource platforms have emerged, and the number of resources on these platforms is increasing dramatically. Compared with the traditional resources, the interactive educational resources (IERs) have hidden interactive information and dynamic content. Only when the users perform interactive operations correctly can they acquire the knowledge conveyed by the resources, which makes it a challenge to help the users understand the general content of resources and find the resources that they are interested in. Therefore, in this paper, we propose a method for generating picture previews of IERs. Firstly, we analyze the file that stores interactive resource information, obtain the interactive elements’ information, extract the dependencies, and generate an operation sequence. Secondly, we execute the operation sequence using an automated software tool to mimic the interaction process between the user and the resource and save the screenshots in the process to generate a picture preview of an IER. We apply this method to a dynamic geometry platform, NetPad, and conduct experiments. Experimental results demonstrate that the method can effectively extract interactive semantic information and simulate the interactive process, and the generated picture previews are of great help to the users to understand the content of IERs.

[EN] In this paper, a scalable hardware and software architecture for low-cost tiled display systems (a.k.a. videowalls), customizable through a dynamic web-based management and configuration service is presented and evaluated both objectively and subjectively. It has been designed for both stored and live broadcast/broadband content, in mosaic or warp distributions. The videowalls can be dynamically configured via web in different ways: the displays can create a single screen of a larger size, or they can be configured in a customized way in order to playout different media contents in different display combinations. As display renderers, low-cost devices are proposed as the main hardware element to obtain affordable videowall systems. As a proof of concept, two prototypes have been implemented, including an accurate synchronization mechanism. To evidence the good performance of the prototypes and configuration service, Both objective and subjective evaluations have been conducted regarding synchronization accuracy and usability of the configuration service, obtaining satisfactory results., This work has been funded by the Generalitat Valenciana, through the R&D Program "Grants for research groups to be consolidated, AICO/2017" under Project AICO/2017/059.

In this paper, we design dynamic probabilistic caching for the scenario when the instantaneous content popularity may vary with time while it is possible to predict the average content popularity over a time window. Based on the average content popularity, optimal content caching probabilities can be found, e.g., from solving optimization problems, and existing results in the literature can implement the optimal caching probabilities via static content placement. The objective of this work is to design dynamic probabilistic caching that: i) converge (in distribution) to the optimal content caching probabilities under time-invariant content popularity, and ii) adapt to the time-varying instantaneous content popularity under time-varying content popularity. Achieving the above objective requires a novel design of dynamic content replacement because static caching cannot adapt to varying content popularity while classic dynamic replacement policies, such as LRU, cannot converge to target caching probabilities (as they do not exploit any content popularity information). We model the design of dynamic probabilistic replacement policy as the problem of finding the state transition probability matrix of a Markov chain and propose a method to generate and refine the transition probability matrix. Extensive numerical results are provided to validate the effectiveness of the proposed design.

The dynamic behavior of web services is critical for researchers to determine their performance at different times. Many existing studies present the static information of web services that are not so effective for estimating web services' future performance. This research article reveals the acquisition of throughput metric dataset for thirty timestamps by a simulation technique. A simulated setup has been proposed to acquire the dynamic throughput data of benchmark web services from workload modeling. The proposed method is aimed to collect dynamic web services metrics data of five web services (WS1–WS5), which are randomly selected from WS-Dream dataset. Additionally, the collected data has been verified by measuring computer resource usage metrics in four experiments. Experiment results indicate that the varying ‘Central Processing Unit’ (CPU) resource usage metrics do not show changes in the collected ‘Quality of Service’ QoS metric values. The experiment results showed that the proposed method achieves the consistent average response time and throughput metric values. The collected simulated data can be further applied to improve the quality of web services.

Modelling is considered as a universal approach to define and simplify real-world applications through appropriate abstraction. Model-driven system engineering identifies and integrates appropriate concepts, techniques, and tools which provide important artefacts for interdisciplinary activities. In this paper, we show how we used a model-driven approach to design and improve a Digital Humanities dynamic web application within an interdisciplinary project that enables history students and volunteers of history associations to transcribe a large corpus of image-based data from the General Register Office (GRO) records. Our model-driven approach generates the software application from data, workflow and GUI abstract models, ready for deployment.

Average Bangladeshis spend a significant amount of income on medicine. A reliable and fast online medicine delivery system is not ubiquitous. Most people buy medicine from the local Pharmacies. They need to go to medicine stores to buy the specific medicine prescribed by the specialized doctors. Sometimes all prescribed medicines are not available in local Pharmacies therefore people need to go to other areas to buy the medicines. It is very time consuming and people need to spend money as well for this. In our country, traffic jams are a very big problem. People waste longer time on the road due to traffic jams. Here most of the pharmacies are closed at night time but sometimes in an emergency situation medicine is very essential. In this case an online web based e-commerce medicine delivery system is needed very much. In addition, currently the whole world is suffering due to COVID-19 pandemic. Coronavirus is very contagious which we all know. In this pandemic time it is not risk free to go out to buy medicine from the pharmacies. Due to COVID-19, medicine scarcity is also an important issue. In this situation, an online medicine delivery system can play an important role. By considering the above mentioned facts, a reliable and fast online solution is proposed. This paper presents the development of a web based online medicine delivery system. A reliable, fast, safe and user-friendly online based e-commerce web application has been developed in this paper. Medicine delivery system has also been included with this proposed system. This platform is a dynamic web application built in Hypertext Preprocessor (PHP) based Laravel framework with a powerful back end. It is hosted on a dedicated Virtual Private Server (VPS). This system is lightning fast and optimized very well for searching engines. With the help of the developed platform, drugs will be available at one’s doorstep very fast, safely and reliably. In this system, users can choose a medicine section of their choices and go through all the items that the system provides. Users can then select the desired drug items, add them to cart and then proceed to payment. It has payment integration of Cash on Delivery (COD) systems. After developing the system it has been tested and it works fine. It is a one-stop solution where people can find various medicines including COVID-19 related medicines and other items in this online platform. Besides medicine, here you can also find other health care products like food supplements, birth control products, hair care products, skincare products, beauty products, etc. People can order their required medicines or other medical related available items from online and the delivery support will provide the products door to door for the users. Using this system now users can get their needed medicine without leaving home. They can save money and they do not need to go out in this pandemic situation to buy medicine. In this crucial situation, the online medicine delivery system is very helpful and it will act as a blessing for the people.

Transient machining conditions often occur during the milling process, especially when complex toolpath layouts are deployed. Although modern CAM-aided toolpath generation algorithms aim at keeping the cutter engagement conditions as constant as possible and avoid sudden changes, this can not always be ensured. These transients are accompanied by temporary peak excursions in cutting forces and changing dynamic content of the excitation forces. This may have the potential to excite unwanted vibrations in the machining process and even may initiate chatter. Using a virtual process simulation environment it is possible to predict resultant dynamic forces along a complete NC tool path with high time and angular resolution and gain insights into the dynamics of transient events during machining operations. This simulation environment has the capability to use an analytical cutting force model, which spares extensive testing and parameter identification beforehand. Besides, well known empirical cutting formulations can be used as well. The results of the dynamic force prediction is compared against experimental results for different toolpath layouts and the dynamic behavior of the machine tool under cutting conditions will be discussed.

The problem of automatic requests classification, as well as the problem of determining the routing rules for the requests on the server side, is directly connected with analysis of the user interface of dynamic web pages. This problem can be solved at the browser level, since it contains complete information about possible requests arising from interaction interaction between the user and the web application. In this paper, in order to extract the classification features, using data from the request execution context in the web client is suggested. A request context or a request trace is a collection of additional identification data that can be obtained by observing the web page JavaScript code execution or the user interface elements changes as a result of the interface elements activation. Such data, for example, include the position and the style of the element that caused the client request, the JavaScript function call stack, and the changes in the page's DOM tree after the request was initialized. In this study the implementation of the Chrome Developer Tools Protocol is used to solve the problem at the browser level and to automate the request trace selection.

Recent advances in machine learning show the superior behavior of temporal convolutional networks (TCNs) and especially their combination with residual networks (TC-ResNet) for intelligent sensor signal processing in comparison to classical CNNs and LSTMs. In this article, we propose UltraTrail, a configurable, ultralow-power TC-ResNet AI accelerator for sensor signal processing and its application to efficient keyword spotting (KWS). Following a strict hardware/model co-design approach, we have derived an optimized low-power hardware architecture for generalized TC-ResNet topologies consisting of a configurable array of processing elements and a distributed memory with dynamic content reallocation. We additionally extend the network with conditional computing to reduce the number of operations during inference and to provide the possibility for power-gating. The final accelerator implementation in Globalfoundries’ 22FDX technology achieves a power consumption of 8.2 $\mu \text{W}$ for the task of always-on KWS meeting the real-time requirement of 100 ms per inference with an accuracy of 93% on the Google Speech Command Dataset.

PurposeThere have been many challenges in crawling deep web by search engines due to their proprietary nature or dynamic content. Distributed Information Retrieval (DIR) tries to solve these problems by providing a unified searchable interface to these databases. Since a DIR must search across many databases, selecting a specific database to search against the user query is challenging. The challenge can be solved if the past queries of the users are considered in selecting collections to search in combination with word embedding techniques. Combining these would aid the best performing collection selection method to speed up retrieval performance of DIR solutions.Design/methodology/approachThe authors propose a collection selection model based on word embedding using Word2Vec approach that learns the similarity between the current and past queries. They used the cosine and transformed cosine similarity models in computing the similarities among queries. The experiment is conducted using three standard TREC testbeds created for federated search.FindingsThe results show significant improvements over the baseline models.Originality/valueAlthough the lexical matching models for collection selection using similarity based on past queries exist, to the best our knowledge, the proposed work is the first of its kind that uses word embedding for collection selection by learning from past queries.

The example application in the previous chapter contains a simple template that was displayed to the user and that contained a data binding that showed how many objects were in the data model. In this chapter, I describe the basic data bindings that Angular provides and demonstrate how they can be used to produce dynamic content. In later chapters, I describe more advanced data bindings and explain how to extend the Angular binding system with custom features. Table 12-1 puts data bindings in context.

With the widespread adoption of mobile technologies, mobile-assisted learning is gaining lots of momentum. This new learning paradigm promotes education across different contexts, which is a key factor that contributes to enhancing learning irrespective of the conditions and location of the learner. Therefore, it creates an authentic learning setting whereby students can make meaningful connections to the real world while learning takes place. Previous research works in the field of mobile learning showed that improper design of learning elements is still present in mobile systems and consequently results in poor dynamic content adaptation. Some attempts to adapt learning contents with appropriate instructional design principles are conducted, but with moderate exploitation of smart technological assets in mobile learning systems and limited pedagogical reflections and cognitive factors. In this paper, a learning efficiency model chart is derived using important learning factors that can be considered to enhance mobile learning experiences. Some popular learning theories are analysed and compared with the proposed learning efficiency model chart. This investigation is considered to significantly reduce complexities that exist in mobile learning platforms and promote an enhanced mobile learning experience.

This paper studies the problem of joint edge cache placement and content delivery in cache-enabled small cell networks in the presence of spatio-temporal content dynamics unknown a priori . The small base stations (SBSs) satisfy users’ content requests either directly from their local caches, or by retrieving from other SBSs’ caches or from the content server. In contrast to previous approaches that assume a static content library at the server, this paper considers a more realistic non-stationary content library, where new contents may emerge over time at different locations. To keep track of spatio-temporal content dynamics, we propose that the new contents cached at users can be exploited by the SBSs to timely update their flexible cache memories in addition to their routine off-peak main cache updates from the content server. To take into account the variations in traffic demands as well as the limited caching space at the SBSs, a user-assisted caching strategy is proposed based on reinforcement learning principles to progressively optimize the caching policy with the target of maximizing the weighted network utility in the long run. Simulation results verify the superior performance of the proposed caching strategy against various benchmark designs.

Recent developments in technologies such as MEC and AI contribute significantly in accelerating the deployment of VCPS. Techniques such as dynamic content caching, efficient resource allocation, and data sharing play a crucial role in enhancing the service quality and user driving experience. Meanwhile, data leakage in VCPS can lead to physical consequences such as endangering passenger safety and privacy, and causing severe property loss for data providers. The increasing volume of data, the dynamic network topology, and the availability of limited resources make data leakage in VCPS an even more challenging problem, especially when it involves multiple users and multiple transmission channels. In this article, we first propose a secure and intelligent architecture for enhancing data privacy. Then we present our new privacy-preserving federated learning mechanism and design a two-phase mitigating scheme consisting of intelligent data transformation and collaborative data leakage detection. Numerical results based on a real-world dataset demonstrate the effectiveness of our proposed scheme and show that our scheme achieves good accuracy, efficiency, and high security.

Purpose This paper aims to investigate the nature and dynamics of the interaction between university spin-offs (USOs) and academia. Design/methodology/approach The theoretical framework is grounded in an interactive view based on the industrial marketing and purchasing literature on USOs and their development. The concepts of activity links, resource ties and actor bonds are used as a starting point for capturing the content and dynamics of the interaction. The empirical part of the paper consists of four case studies captured through interviews as the main data source and analysed to conclude how the interaction between the USO and academia developed over time. Findings The study identifies a multi-faceted and dynamic content of the interaction. The paper discerns and discusses research and development links, knowledge and equipment ties and social, legal, financial and organizational bonds with inventors, other academic partners and innovation support organizations. The dynamics are manifested both through changes within individual relationships and by adding/ending relationships. One main conclusion regards the existence of wave-like patterns of interaction with academic partners driven by the USOs’ needs and the establishment of customer relationships. Originality/value Most of the previous research has described a linear process in which the USO leaves academia once the idea has been transferred to a company. This paper contrasts this view by developing and using an analytical framework to capture the dynamic and continuous interaction between USO and academia.

Production House 8Production films is one of the production houses enganged in services that include multimedia, video shooting and photography in Palembang. The creation of this final project, entitled “Production House Information System In 8Production Films Based on Website”. Because currently the production process include visual shooting and shooting, visual image editing and photos are still not well scheduled, only initiative, and no scheduling systematically. In addition, the management of internal operational information in the processing data from the order receipt is only stored in the form of .doc files and some are still handwritten, so that the same data recording and processing (double storage), and acces to information is slow. The System development method used in this research is Prototype. Based on the problem that have been analyzed through exixting business process observation methods. Then the system is designed by making UML (Unifield Modeling Languange). And using PHP as a programming language that will be used to create the website PHP has the extension of PHP Hypertext Preprocessor, a programming language that is anabled to build a dynamic website. While MySQL is an RDBMS software (or database server) that can manage databases very quickly. Thw result of this study are a web-based 8Production Films Production House Information System that makes ordering users easy and makes it easier for 8Production films staff to perform member absences, managing filming schedules and weekly agendas to be more effective, and making monthly reports of transactions at web-based 8Production films production houses

Precision medicine promises to revolutionize treatment, shifting therapeutic approaches from the classical one-size-fits-all to those more tailored to the patient’s individual genomic profile, lifestyle and environmental exposures. Yet, to advance precision medicine’s main objective—ensuring the optimum diagnosis, treatment and prognosis for each individual—investigators need access to large-scale clinical and genomic data repositories. Despite the vast proliferation of these datasets, locating and obtaining access to many remains a challenge. We sought to provide an overview of available patient-level datasets that contain both genotypic data, obtained by next-generation sequencing, and phenotypic data—and to create a dynamic, online catalog for consultation, contribution and revision by the research community. Datasets included in this review conform to six specific inclusion parameters that are: (i) contain data from more than 500 human subjects; (ii) contain both genotypic and phenotypic data from the same subjects; (iii) include whole genome sequencing or whole exome sequencing data; (iv) include at least 100 recorded phenotypic variables per subject; (v) accessible through a website or collaboration with investigators and (vi) make access information available in English. Using these criteria, we identified 30 datasets, reviewed them and provided results in the release version of a catalog, which is publicly available through a dynamic Web application and on GitHub. Users can review as well as contribute new datasets for inclusion (Web: https://avillachlab.shinyapps.io/genophenocatalog/; GitHub: https://github.com/hms-dbmi/GenoPheno-CatalogShiny).

Databases are widely used by organizations to store business-critical information, which makes them one of the most attractive targets for security attacks. SQL Injection is the most common attack to webpages with dynamic content. To mitigate it, organizations use Intrusion Detection Systems (IDS) as part of the security infrastructure, to detect this type of attack. However, the authors observe a gap between the comprehensive state-of-the-art in detecting SQL Injection attacks and the state-of-practice regarding existing tools capable of detecting such attacks. The majority of IDS implementations provide little or no protection against SQL Injection attacks, with exceptions like the tools Bro and ModSecurity. In this article, the authors compare these tools using the CSIC dataset in order to examine the state-of-practice in database protection from SQL Injection attacks, identifying the main characteristics and implementation details needed for IDSs to successfully detect such attacks. The experiments indicate that signature-based IDS provide the greatest coverage against SQL Injection.

The use of digital devices has increased exponentially in the last decade. Especially, young children spend most of their time surfing for various reasons such as homework. assignments and projects etc. Parental Control is highly important for monitoring the browsing behavior of children. Though several content-based web page classification approaches are available, it requires the entire web page contents for classification purpose. This leads to wastage of bandwidth due to unnecessary downloads. The exponential growth of internet demands URL based classifiers to adapt to the dynamic web, and to make swift decisions on the fly. To address this problem, a deep learning based approach has been proposed in this research that can extract the features only from the URL of a web page. To learn the patterns for Kids-specific web sites automatically, Convolutional Neural Network (CNN) is combined with Bidirectional Gated Recurrent Unit (BGRU) to extract rich context aware features as well as to preserve the sequence information in the URL. By conducting various experiments on the benchmark collection Open Directory Project (ODP), it is shown that an accuracy of 82.04% can be achieved.

Edge computing is a promising infrastructure evolution to reduce traffic loads and support low-latency communications. Furthermore, content-centric networks provide a natural solution to cache contents at edge nodes. However, it is a challenge for edge nodes to handle massive and highly dynamic content requests by users, and if without an efficient content caching strategy, the edge nodes will encounter high traffic load and latency due to increasing retrieval from content providers. This paper formulates a proactive edge caching problem to minimize the content retrieval cost at edge nodes. We exploit the inherent content caching and request aggregation mechanism in the content-centric networks to jointly minimize traffic load and content retrieval delay cost generated by the massive and dynamic content requests. We develop a Q-learning algorithm, which is an online optimal caching strategy, as it is adaptable to dynamic content popularity and content request intensity, and derive the long-term minimization of the content retrieval cost. Simulation results illustrate that the proposed algorithm can achieve a lower content retrieval cost compared with several baseline caching schemes.

Caches are widely applied to improve data delivery performance in distributed systems like edge networks and content delivery networks (CDNs). We consider caching mechanism in those networks that deliver contents to end users. The challenge comes from the dynamic content distribution problem. The distribution of data popularity is highly skewed and changing over time. Besides, the access pattern of the user requests also varies over time. Some learning algorithms for edge caching problems need to rebuild a new model periodically to adapt to system dynamics, where the knowledge learned from the past is discarded. Besides, each model updating needs a large amount of data, leading to outdated models for consecutive user requests. Inspired by the success of incremental learning approaches in processing massive data in real time, we propose an incremental learning based framework at an edge caching server. The incremental learning algorithm is used to preserve valuable knowledge and to adapt to dynamic workloads faster. We implement our incremental learning based cache system prototype and evaluate its performance under various real-world workloads. The experimental results show that our algorithm can boost cache hit ratio for dynamic workloads compared with the state-of-the-art caching algorithms.

The correct creation of the site is responsible for the correct display of the content. The developer must create web-page, that will be displayed correctly in the browser, which will be the closest to the previously created layout design site, pre-designed in the graphic editors. There are many tools for creation websites, for example html, css, and different types of frameworks. There are «hard» (fixed) and «rubber» (adaptive) layout of the site. «Hard» layout makes all elements of the web page of fixed sizes, regardless of the size of the user’s monitor and the screen resolution set. Adaptive layout of the site allows you to resize page elements by adjusting to different sizes and permissions of monitors. The most significant and actively explored area of web development is adaptive layout. Due to the large variety of technologies that allow us to solve a number of problems facing the developer when designing adaptive websites, it’s worth researching the most effective ones. The article explores flexbox technology for adaptive web page development. The main features of the flexbox application are highlighted for solving basic tasks such as moving the blocks accordingly to the width of the screen, automatically determining the center for precise alignment of the containers on the page. The main features of the flexbox are for seeing the main headlines, such as the one for the graphic content of the screen width, which is automatically assigned to the center for the exact virtual container on the web-page. We explored the main advantages and perspectives of using flexbox technology in adaptive web page designing that contain dynamic content, which gives a clear idea of the further introduction of this technology into the web development process. Adaptive layout is used for correct display. To implement the adaptability of the site, additional styles are prescribed, which, in addition to the greater amount of work, entail thinking of the behavior of each element.

In this letter, dynamic content placement of a local cache server that can store a subset of content objects in its cache memory is studied. Contrary to the conventional model in which content placement is optimized based on the time-invariant popularity distribution of content objects, we consider a general time-varying popularity distribution and such a probabilistic distribution is unknown for content placement. A novel learning method for predicting the temporal distribution of future content requests is presented, which utilizes the request histories of content objects whose lifespans are expired. Then we introduce the so-called predictive caching strategy in which content placement is periodically updated based on the estimated future content requests for each update period. Numerical evaluation is performed using real-world datasets reflecting the inherent nature of temporal dynamics, demonstrating that the proposed predictive caching outperforms the conventional online caching strategies.

The continued use of digital devices, such as smartphones and tablets, has substantially changed the way we communicate and acquire knowledge. Museums are a key element in our society and a source of culture. Updating the method of transmission of museum culture is needed, so technologies related to the Internet have been integrated into the exposed elements. One of the most widespread methods among innovation trends in museums is the use of Quick Response (QR) codes for the transmission of additional information to the exposed elements. The case of the Alborania Museum, being a museum of environmental education, has live animals in veterinary treatment, so the information on the available animals is constantly changing. Establishing posters would have an environmental impact that is against the museum's ethics, so QRs are the best way to present dynamic content with low environmental impact. This article proposes an evaluation of an educational innovation project in the Alborania Museum of Malaga through the Contribution Analysis, in order to verify the value of QR codes as an improvement in the transmission of environmental education. The results show a very good acceptance and usability in this museistic context. The conclusions of this study are relevant to the optimisation of environmental museum information. Keywords: QR code, museum, evaluation, contribution analysis, ICT, environmental education.

A huge portion of the organizations have the sites for their business. A huge portion of the clients of the association register their subtleties as client profiles. These client profiles have the individual subtleties and their fascinating propensities for the client. At the point when the client visits our sites the log record is made in the server. By partner the client profiles and web log record we can discover the much of the time visited clients. From the frequently visited client, we can discover when they are visited by grouping the client profiles with web log records. In our work we disclose how to get "who" the clients were, "what" they took a gander at, and "how their interests changed with time, "when" they visit which are all significant inquiries in Customer Relationship Management (CRM). In our examination we present bunching the client profiles. We additionally depict how they found client profiles can be advanced with unequivocal data.

Cricket is one of the most popular sports in the world. It is a dynamic game involving complex rules and strategies. There are many websites like Cricbuzz and Cricinfo that provide live text commentary using journalists who report from the ground or use live telecast of the match. This process of using journalists for typing out live text commentary is both labor and cost intensive. This research presents an approach that uses dynamic web scraping to scrape live scores and associated parameters like run rate, outcome of each ball, etc. which are then fed to a supervised learning algorithm that uses all these parameters and generates a commentary for the current ball event by selecting an appropriate commentary template from a pool of predefined commentary templates. We also compare results between the different supervised learning algorithms, i.e., Neural Network and Random Forest, in terms of accuracy metrics and prove that Random Forest performs better by having an accuracy of 92.7% in generating the appropriate commentary.

Dynamic web sites take on a whole new meaning in combination with a database. Drawing content from a database allows you to present material in ways that would be impractical—if not impossible—with a static web site. Examples that spring to mind are online stores, such as Amazon.com; news sites, such as the BBC (www.bbcnews.com); and the big search engines, including Google and Bing. Database technology allows these web sites to present thousands, often millions, of unique pages. Even if your ambitions are nowhere near as grandiose, a database can increase your web site’s richness of content with relatively little effort.

In this work, we consider the problem of ‘fresh’ caching at distributed (front-end) local caches of content that is subject to ‘dynamic’ updates at the (back-end) database. We first provide new models and analyses of the average operational cost of a network of distributed edge-caches that utilizes wireless multicast to refresh aging content. We attack the problems of what to cache in each edge-cache and how to split the incoming demand amongst them (also called "loadsplitting" in the rest of the paper) in order to minimize the operational cost. While the general form of the problem comes with an NP-hard Knapsack structure, we were able to completely solve the problem by judiciously choosing the number of edge-caches to be deployed over the network. Interestingly, our findings reveal that the optimal caching policy necessitates unequal load-splitting over the edge-caches even when all conditions are symmetric. Moreover, we find that edge- caches with higher load will generally cache fewer but relatively more popular content. We further investigate the tradeoffs between cost reduction and cache savings when employing equal and optimal load-splitting solutions for demand with Zipf(z) popularity distribution. Our analysis reveals that equal load-splitting to edge-caches achieves close-to-optimal for less predictable demand (z 2), optimal load-splitting results in substantial cost gains while decreasing the cache occupancy.

In the hardware technical support domain, scaling technician skills remains a prevalent problem. Given the large portfolio of hardware products service providers need to maintain, it is not possible for every technician to be expert at repairing every product. Augmented reality addresses this problem through virtual procedures, which are interactive 3D visual representations of text-based knowledge articles that describe how to perform step-by-step repair actions. Virtual procedures, thus, equip the technicians with the skills they need to support a wide range of hardware products. In this paper, we present a novel and scalable approach to dynamically construct virtual procedures, and we demonstrate the feasibility of our approach through a real-life implementation.

Real-time environmental measurements are becoming increasingly important as we face climate change. Data with spatial and temporal components are used to feed numerical models, but also presented in near real time on the Internet. In this paper, we highlight some basic principles for web publishing of real-time data. The main goal of data publishing and visualization is to provide the user with an intuitive way to gain insight into the current state of the environment and some trends. Dynamic web pages, the main tool for data presentation, can go beyond static images and provide extensive interactive capabilities.

Now-a-days when everything is going digitalized, internet and web plays a vital role in everyone’s life. When one has to ask something or has any online task to perform, one has to use internet to access relevant web-pages throughout. These web-pages are mainly designed for large screen terminals. But due to mobility, handy and economic reasons most of the persons are using small screen terminals (SST) like mobile phone, palmtop, pagers, tablet computers and many more. Reading a web page which is actually designed for large screen terminal on a small screen is time consuming and cumbersome task because there are many irrelevant content parts which are to be scrolled or there are advertisements, etc. Here main concern is e-business users. To overcome such issues the source code of a web page is organized in tree data-structure. In this paper we are arranging each and every main heading as a root node and all the content of this heading as a child node of the logical structure. Using this structure, we regenerate a web-page automatically according to SST size. Background: DOM and VIPS algorithms are the main background techniques which are supporting the current research. Objective: To restructure a web page in a more user friendly and content presenting format. Method Backtracking: Method Backtracking: Results: web page heading queue generation. Conclusion: Concept of logical structure supports every SST.

Content Caching at the edge of vehicular networks has been considered as a promising technology to satisfy the increasing demands of computation-intensive and latency-sensitive vehicular applications for intelligent transportation. The existing content caching schemes, when used in vehicular networks, face two distinct challenges: 1) Vehicles connected to an edge server keep moving, making the content popularity varying and hard to predict. 2) Cached content is easily out-of-date since each connected vehicle stays in the area of an edge server for a short duration. To address these challenges, we propose a Mobility-aware Proactive edge Caching scheme based on Federated learning (MPCF). This new scheme enables multiple vehicles to collaboratively learn a global model for predicting content popularity with the private training data distributed on local vehicles. MPCF also employs a Context-aware Adversarial AutoEncoder to predict the highly dynamic content popularity. Besides, MPCF integrates a mobility-aware cache replacement policy, which allows the network edges to add/evict contents in response to the mobility patterns and preferences of vehicles. MPCF can greatly improve cache performance, effectively protect users’ privacy and significantly reduce communication costs. Experimental results demonstrate that MPCF outperforms other baseline caching schemes in terms of the cache hit ratio in vehicular edge networks.

Summary Biological data is ever-increasing in amount and complexity. The mapping of this data to biological entities such as nucleotide and amino acid sequences supports biological data analysis, classification and prediction. Sequence alignments and comparison allow the transfer of knowledge to evolutionary-related entities, the mapping of functional domains, the identification of binding and modification sites. To support these types of studies, we developed ProSeqViewer, a tool to visualize annotation on single sequences and multiple sequence alignments. This state-of-the-art multifunctional library was developed as a modular component to be integrated into static or dynamic web resources and support intuitive visualization of sequence features. ProseSeqViewer is extremely lightweight, fast, interactive, dynamic, responsive and works at any screen size. It generates pure HTML which is compatible with any browser and operating system. ProSeqViewer can exchange events with other visualization components and is already used by multiple biological databases. Availability and implementation ProSeqViewer is an open-source TypeScript library compatible with state-of-the-art website environments. The source code and an extensive documentation including use cases are available from the URL: https://github.com/BioComputingUP/ProSeqViewer.

Computational modeling has contributed to hippocampal research in a wide variety of ways and through a large diversity of approaches, reflecting the many advanced cognitive roles of this brain region. The intensively studied neuron type circuitry of the hippocampus is a particularly conducive substrate for spiking neural models. Here we present an online knowledge base of spiking neural network simulations of hippocampal functions. First, we overview theories involving the hippocampal formation in subjects such as spatial representation, learning, and memory. Then we describe an original literature mining process to organize published reports in various key aspects, including: (i) subject area (e.g., navigation, pattern completion, epilepsy); (ii) level of modeling detail (Hodgkin-Huxley, integrate-and-fire, etc.); and (iii) theoretical framework (attractor dynamics, oscillatory interference, self-organizing maps, and others). Moreover, every peer-reviewed publication is also annotated to indicate the specific neuron types represented in the network simulation, establishing a direct link with the Hippocampome.org portal. The web interface of the knowledge base enables dynamic content browsing and advanced searches, and consistently presents evidence supporting every annotation. Moreover, users are given access to several types of statistical reports about the collection, a selection of which is summarized in this paper. This open access resource thus provides an interactive platform to survey spiking neural network models of hippocampal functions, compare available computational methods, and foster ideas for suitable new directions of research.

For the development of web dynamic web pages based on ASP.NET and SQL Server, in order to improve the response speed of web pages when dealing with large amounts of data, a custom paging control is developed. By setting the properties of the paging control and writing a brief calling code, the paging function is realized.

Cybersecurity education and training are essential prerequisites of achieving a secure and privacy-friendly digital environment. Both professionals and the general public widely acknowledge the need for high-quality university education programs and professional training courses. However, guides, recommendations, practical tools, and good examples that could help institutions design appropriate cybersecurity programs are still missing. In particular, a comprehensive method to identify skills needed by cybersecurity work roles offered on the job market is missing. This paper aims to provide practical tools and strategies to help higher education providers design good cybersecurity curricula. First, we analyze the content of 89 existing study programs worldwide, collect recommendations of renowned institutions within and outside the EU, and provide a comprehensive survey accompanied by a dynamic web application called Education Map. Based on the knowledge about the current state in cybersecurity education, we design the SPARTA Cybersecurity Skills Framework that provides the currently missing link between work roles and required expertise and shows how to develop a curriculum that reflects job market requirements. Finally, we provide a practical tool that implements the framework and helps education and training providers design new study programs and analyze existing ones by considering the requirements of cybersecurity work roles.

Nowadays, Health is the most crucial part of one’s life, Health care is one of the prominent sectors which play a vital role in the day-to-day life. This work discusses the automation of the health care sector using noteworthy technologies like Wireless Sensor Networking (WSN), Intranet topologies and Web development. Apart from innovation and automation, In the health care sector, this work shows a unique approach with the help of RSSI, Dual-band frequencies and adaptive n triangle algorithm which are an integral part of WSN. This work is a thoughtful combination of WSN, intranet & web development which ensures a typical Security that protects from intruders. This work proposes both hardware and software-based approach, where the hardware part consists of Single Board Computers and networking devices. In the software part, there are a heap of languages and tools used likewise HTML, CSS, PHP, SaaS, JavaScript and for database management MySQL is used. This is a structural work that creates a webserver using the intranet topologies where a dynamic website is hosted over the SBC. This website consists of appointment booking, doctors scheduling, medical screening, internal navigation in the hospital with the WSN, RSSI and dual-band technologies, medical facilities and many more. Finally, this work shows an adaptive & innovative solution that can amplify the efficiency of the health sector.

Simultaneous Localization and Mapping is a fundamental problem in mobile robotics. However, the majority of Visual SLAM algorithms assume a static scenario, limiting their applicability in real-world environments. Dealing with dynamic content in Visual SLAM is still an open problem, with solutions usually relying on purely geometric approaches. Deep learning techniques can improve the SLAM solution in environments with a priori dynamic objects, providing high-level information of the scene. However, most solutions are not prepared to deal with crowded scenarios. This paper presents Crowd-SLAM, a new approach to SLAM for crowded environments using object detection. The main objective is to achieve high accuracy while increasing the performance, in comparison with other methods. The system is built on ORB-SLAM2, a state-of-the-art SLAM system. The proposed methodology is evaluated using benchmark datasets, outperforming other Visual SLAM methods.

With the development of science and technology, especially the development and application of information technology, computer-aided animation production has gradually become a research hotspot because of its extensive practical needs. Based on the idea of graph structure, this paper proposes a dynamic web crawler model based on state transition, which uses the state transition process to simulate dynamic events to trigger changes to the web page structure. Through the analysis and modeling of the traditional animation storyboard script, the basic elements of the animation storyboard script are extracted. Combined with XML technology to design a standardized animation storyboard script description method, the key technology of the method is given. Schema files are used to set the structure and constraint conditions of animation storyboards, and DOM technology is used to realize the analysis of standardized animation storyboards. Compared with the traditional animation storyboard script edited in Microsoft Word, WPS and other formats, the standardized animation storyboard script adds relevant animation storyboard structure information. This structural information will make the various processing of the animation storyboard script using the computer system more convenient and efficient. Using this feature, it supports the annotation of animation materials and efficient browsing and retrieval.

Logs are an essential part of the development and maintenance of large and complex software systems as they contain rich information pertaining to the dynamic content and state of the system. As such, developers and practitioners rely heavily on the logs to monitor their systems. In parallel, the increasing volume and scale of the logs, due to the growing complexity of modern software systems, renders the traditional way of manual log inspection insurmountable. Consequently, to handle large volumes of logs efficiently and effectively, various prior research aims to automate the analysis of log files. Thus, in this paper, we begin with the hypothesis that log files are natural and local and these attributes can be applied for automating log analysis tasks. We guide our research with six research questions with regards to the naturalness and localness of the log files, and present a case study on anomaly detection and introduce a tool for anomaly detection, called ANALOG, to demonstrate how our new findings facilitate the automated analysis of logs.

The article of record as published may be found at http://dx.doi.org/10.1109/SPW53761.2021.00048 2021 IEEE Symposium on Security and Privacy Workshops Modern web applications rely heavily on dynamic content, i.e., page updates made by the browser using an XMLHttpRequest and more recently the JavaScript Fetch API. These requests are often made on behalf of user actions, such as typing on the keyboard or pointing at an HTML element. As a result, the timings of the user's actions are strongly correlated with the timings of packets that carry these events. In this work, we examine several dynamic web applications and the ability to measure human behavior in encrypted network traffic by using deep temporal features. Our approach relies on the ability to accurately detect a subset of packets that correspond to user actions. Leveraging recent work in keystroke dynamics, we show that user identification can be performed with modest accuracy utilizing the packet timings induced by a user typing into a search engine. While this tool could be used by forensic investigators to perform target identification among encrypted network traffic, it also raises a privacy concern in which an on-path remote adversary able to detect these packets may infer user behaviors. Work done while a student at the Naval Postgraduate School