Top PDF Mobile Searching Engine For Learning Management System

Mobile Searching Engine For Learning Management System

Mobile Searching Engine For Learning Management System

Below are the lists of the objective of the Mobile Search Engine To construct the portable searching engine be able to held To construct a search engine for mobile device like as a searc[r]

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A Mobile Agent Model For Management Information System

A Mobile Agent Model For Management Information System

comprising of backend and frontend engines. The backend engine comprises of the server machine and nodes that are considered to be static. The frontend is the software-based interface, which creates the environment for creating and launching the mobile agent and is dynamic in nature. The architecture of the proposed mobile agent is as conceptualized in Figure 1. The platform for the take-off of the Agent Monitor at the server host and the platform for its landing at the target workstations are their respective operating systems. At the server host, the Agent Monitor is created and equipped with the code, data, and other necessary parameters and dispatched to the target workstations in the network. The Agent Monitor then navigate autonomously through the network from the server end and interact with the host operating system of the target workstations, and it's utility programs as it processes the desired information. The Agent Monitor moves from one workstation to another while carrying along intermediate results. The results obtained by the mobile agent after successful visits to a set of target workstations are transferred to the server, which are displayed on its screen or printed out for the purpose of external analysis, interpretation, policy formulation and decision making by the Network System Administrator.
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Mobile Trillium Engine

Mobile Trillium Engine

The aim of this thesis is to develop a backend system that integrates an existing asset, incident and change management system which is widely used in air transport industry to a mobility platform. The solution enables the field engineers to do limited incident and change management on hand held devices using a mobile application. The business data required by the mobile application is extracted from the legacy incident management system and injected into the mobility platform which makes it readily available for the mobile application. Any updates made by field engineers using the mobile application are synchronized back to the incident management system via this solution.
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Artificial Intelligence for Mobile Learning Interactive System

Artificial Intelligence for Mobile Learning Interactive System

2. Expert system. Once the student has finished the practice, it is sent for evaluation. In order to do that, the practice management agent delivers the information coming from the student to the expert system which, according to a given set of rules, analyzes the information and reports the qualification obtained. Moreover, it notifies to the student the list of errors found, as well as a series of guidelines in order to improve the student's experience. All the events are collected by a trouble-tracking system and saved in a database, together with the answers recorded by the teacher through the management console. This database is the learning repository for the expert system, which can afterwards propose more elaborate answers and guidelines, based on the answers of the students and the difficulties found. The expert system is similar to those found in other intelligent tutoring systems (ITS). As shown in Figure 2, an intelligent tutoring system is composed by three modules, plus an interface. The expert module comprises all the cognitive information, stored in knowledge databases. Here it is possible to find all the specific and detailed knowledge obtained from human experts after several years of teaching.
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Artificial Intelligence for Mobile Learning Interactive System

Artificial Intelligence for Mobile Learning Interactive System

The World Wide Web can be considered as a large distributed information system that provides access to shared data objects. As one of the most popular applications currently running on the Internet, the size of World Wide Web is of an exponential growth, which results in network congestion and server overloading. Web caching has been recognized as one of the effective schemes to alleviate the server bottleneck and reduce the network traffic, thereby minimize the user access latencies. In the upcoming world of Computing, content adaptation is an essential concept to meet the heterogeneous requirements of web users using various web access technologies. However, content adaptation interferes with the effectiveness of web caching. Leveraging the advantages of web caching even in the world of Pervasive Computing is the subject of this paper. We present an approach that joins concepts of web caching and content adaptation in a uniform scheme. We have conceived architecture of hierarchical, independent caching proxies that are aware of the heterogeneous capabilities of the client population. Content adaptation is performed by adaptation services on behalf of the proxies. By this means, the proxies merge their local cache management with the composition of a distributed adaptation path and avoid the interference between content adaptation and web caching.
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Artificial Intelligence for Mobile Learning Interactive System

Artificial Intelligence for Mobile Learning Interactive System

master is then loaded at its originating site and initiates the first phase of the protocol by sending PREPARE (to commit) messages in parallel to all the cohorts. Each cohort that is ready to commit, first force-writes a prepared log record to its local stable storage and then sends a YES vote to the master. At this stage, the cohort has entered a prepared state wherein it cannot unilaterally commit or abort the transaction but has to wait for final decision from the master. On other hand, each cohort that decides to abort force-writes an abort log record and sends a NO vote to the master. Since a NO vote acts like a veto, cohort is permitted unilaterally abort the transaction without waiting for a response from the master. After the master receives the votes from all the cohorts, it initiates the second phase of the protocol. If all the votes are YES, it moves to a committing state by force-writing a commit log record and sending COMMIT messages to all the cohorts. Each cohort after receiving a COMMIT message moves to the committing state, force-writes a commit log record, and sends an acknowledgement (ACK) message to the master. If the master receives even one NO vote, it moves to the aborting state by force writing an abort log record and sends ABORT messages to those cohorts that are in the prepared state. These cohorts, after receiving the ABORT message, move to aborting state, force write an abort log record and send an ACK message to the master. Finally, the master, after receiving acknowledgement from all the prepared cohorts, writes an end log record and then forgets and made free the transaction. The statistics are collected in the Sink [52, 53, 54, 55]. The database is modeled as a collection of DB size pages that are uniformly distributed across all the Num sites. At each site, transactions arrive under Poisson stream with rate Arrival Rate and each transaction has an associated firm deadline. The transactions can be managed in many different ways. In most of the earlier work done simply static or dynamic ways with only database size computing [56, 55]. A new concept is introduced to manage the hybrid transactions management with database size for originating site and remote site rather than database size computing parameters, where the values of the parameters are changes or adjust automatically depending on the requirements during the execution the experiment.
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Artificial Intelligence for Mobile Learning Interactive System

Artificial Intelligence for Mobile Learning Interactive System

A web search engine is a tool designed to search for information on the World Wide Web. The search results are usually presented in a list. The information may consist of web pages, images, information and other types of files. Some search engines also mine data available in databases. Unlike Web directories, which are maintained by human editors, search engines operate algorithmically or are a mixture of algorithmic and human input. The Search Engines often return a large volume of results with possibly a few relevant results. The notion of relevance is subjective and depends on the user and context. The Re-ranking of the results reflects the most relevant results for the user and has become very important in current scenario. In this paper, we propose a novel approach for re-ranking of the search results which would be more efficient and effective of a given user as well as the other users. Our approach is to learn the profiles of the users by making use of past browsing histories including queries posed and documents found relevant or irrelevant.
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A portable document search engine to support off-line mobile learning

A portable document search engine to support off-line mobile learning

Application Development (RAD) on a mobile device. They also remove the need for cross compilation. A  disadvantage of this approach is they require additional software to exist on the device to run even the  smallest script. These dependencies can lead to maintenance issues when various software is updated.  An initial approach taken was to develop the remote search in Ruby on a PC and simply install Ruby on the  mobile device and then use the same scripts. Although there was no problem getting Ruby running on a  selection of Linux­based mobile devices, the iPhone proved to be different. It was possible to cross compile  Ruby and install it to the iPhone, however, running anything other than a basic script caused programs to  crash out with bus errors. Searching the community for a solution proved fruitless. In the end, this approach  was dropped in favour of a hybrid solution involving a mixture of interpreted script code and compiled C  code   (Moore,   2008b).   This   approach   utilised   existing   libraries   and   programs   on   the   device.   All   these  components   could easily  be  found  on  any  Linux  distribution  and  therefore  provide  a  portable   way  of  developing for the iPhone plus other devices.
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A Novel Model for Cloud Based Mobile Learning System

A Novel Model for Cloud Based Mobile Learning System

The proposed model incorporates communication between end-user devices, system server platform, management layer (logical layer), and base layer (infrastructure layer) using cloud computing environment. The users of the system are learners (students), instructors, parents and managers (including system administrators). A user’s device connects to the system through external network/Internet or through the local area network (LAN) in order to perform tasks like learn, communicate, download learning materials, access resources, enroll new students, view the student progress and configure the system. The system server platform, in cloud environment, connects the user’s device with logical layer. The user accesses the system server platform to perform data processing using HPC, data downloading using cloud services and data rendering using GPU. A user needs data to process by HPC cluster infrastructure. The user’s request is sent to the logical layer to map with the needed HPC functions to display the output. The logical layer acts as the brain of the system to complete a request with high performance and smooth flow. The infrastructure contains the basic environment of the system like databases, networks, storages, IT resources, computing, HPC cluster (that builds a massive parallel computer from a set of small machines) and GPU cluster (that is computer cluster in
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Enhancing Interdisciplinary Learning with a Learning Management System

Enhancing Interdisciplinary Learning with a Learning Management System

Constructivism calls for the elimination of standardized curricula, and for the implementation of interventions where learning activities and tools are used to provide students with an opportunity to collaboratively construct meaning (Ashcraft, Treadwell, & Kumar, 2008). It promotes curricula that enable students to make links between the unknown and the students' existing schema, with an emphasis on hands-on problem solving. Teachers focus on making connections between facts and fostering new understanding by scaffolding new ideas and concepts extending the schema. The connections can be facilitated by using digital ICT tools such as LMSs. Peters (2007) argued that LMSs can provide "unique educational affordances" ("m-Learning as a Practical Training Solution in Mobile Workplaces," para. 1), including portability, social interactivity, tailoring for context sensitivity, promoting connectivity, and catering for individuality. While many lecturers can still use LMSs in ways that may not promote constructivist learning, such as archiving slide shows, readings, and posting e-mails, certain features within LMSs offer potentials for interdisciplinary knowledge production by providing opportunities for students to learn independently and via new forms of interactions and communication by personalizing learning experiences (Johnson, Adams, & Cummins, 2012, Park, 2008; Salmon, 2003). Klein and Schneider (2010) extended further that Web 2.0 technologies drive information sharing across the infrastructure of distributed information systems, and are "enabling individuals and networks in dispersed locations to collaborate" (p. 18) for interdisciplinarity. In this way, LMSs can provide a platform for effective communication and interaction between students and students, and between students and teachers for interdisciplinary learning.
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Mobile Learning and Attendance Management System on Android Platform

Mobile Learning and Attendance Management System on Android Platform

ABSTRACT: Education system has become so smart due to the development of the technologies such as VLC, video conferencing and e-Learning. General e-learning is available in the form of web based application, but does not exist in the form of mobile application yet. These applications help the institute to move forward quickly, fulfil their vision and accomplish their goals, E-way. This research project assists teaching-learning process by implementing an Android based application for mobile learning and attendance management system The proposed project will be implemented in applications such as online study material, notices, academic calendar and online reminders of examination, online attendance record, performance record, and parent intimation system, broadcasting of notes to students using Android applications. This system helps teacher to take attendance through smartphone and keep records of students for their progressive assessment. This system gives a prior intimation with SMS to the student as soon as their attendance goes below the specified attendance threshold.
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Implementation of ElasticSearch Search Engine on Order Management System Data

Implementation of ElasticSearch Search Engine on Order Management System Data

Elasticsearch is a search engine, generally searching full-text formatted data. It organizes the data and makes them more accessible. Elasticsearch is built with Java programming language, open-source, and under the Apache license. Elasticsearch is utilized technically by querying searched keywords, which communicated via API. It is installed in a standalone database server using HTTP/JSON protocol, retrieved and stored data in optimized form. It becomes a reliable technology in today’s IT industries that needs optimization in searching full-text formatted data. The bigger size of data, the slower the accessibility, meantime, recent requirements need faster access for very large transaction. The research discussed the influence of adding Elasticsearch in web-based system and the non-adding Elasticsearch. The study implemented Agile Scrum methodology in developing the system. The result of this study is the data access becomes faster by 10.01% when implemented Elasticsearch.
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Smart Search Engine for Efficient Data Searching

Smart Search Engine for Efficient Data Searching

A Web Crawler also known as a robot or a spider is a system for the bulk downloading of web pages. Web crawlers are used for a variety of purposes. Most prominently, they are one of the main components of web search engines, systems that assemble large of web pages, index them, and allow users to issue queries against the index and find the web pages that match the queries Also use in web data mining, where web pages are analyzed for statistical properties, or where data analytics is performed on them. On web deep web is increasing there has been increased interest in techniques that help efficiently locate deep-web interfaces. However, due to the large volume of web resources and the dynamic nature of deep web, achieving wide coverage and high efficiency is a challenging issue. Quality and coverage on relevant deep web sources are also challenging. We propose a two-stage framework, namely Smart Crawler, for efficient harvesting deep web interfaces. In the first stage, Smart Crawlerperforms Link based searching for center pages with the help of search engines, avoiding visiting a large number of pages. In second phase we are going to match form content, then we classifying relevant and irrelevant sites. Here we developer personalized search for efficient results and we are maintaining log for efficient time management.
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THE USE OF EDMODO, VIRTUAL LEARNING MANAGEMENT PLATFORM, IN THE CONTEXT OF PROMOTING MOBILE LEARNING

THE USE OF EDMODO, VIRTUAL LEARNING MANAGEMENT PLATFORM, IN THE CONTEXT OF PROMOTING MOBILE LEARNING

Mobile learning has become particularly popular with the youth. It is felt by many researchers on an intuitive level that there is an intimate connection between mobiles and youth (Goggin, 2013). Bidin and Ziden (2012) state that the newly coined terms such as „digital natives‟ (Prensky, 2001), „new millennium learners‟ (Pedró, 2006), „the net generation‟ (Tapscott, 1999), „the gamer generation‟ (Carstens & Beck, 2005) and „generation M‟ (Rideout, Roberts, & Foehr, 2005), refer to the same generation of learners. Prensky, Pedró and Tapscott (as cited in Bidin & Ziden, 2012) agree that these learners are known as the ones who socialize in media-based world and they share “some common characteristics: think and process information very much different from their predecessors, do multitasks, prefer multimedia to written texts, collaborate and network, want to have fun at work and at school, hence, opt for games than „serious‟ work and for them speed and innovation are a part of life” (p. 721).
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Learning Management System as an Effective Means of E-Learning

Learning Management System as an Effective Means of E-Learning

Besides LMS can be used to develop a variety of training sessions which covered 24 hours in total: LMS is educational products (for example, virtual library of tests, educational environment: its functions; Lesson interactive vocabulary practice programs, grammar administration: user interface, personal page of a teacher; activators, language laboratories etc) to support the Construction of a lesson. Structure and editing elements: needs of particular groups. As far as test master of the theory, video, text, glossary; Tests creation: kinds of test LMS is concerned it has a row of advantages comparing masters in LMS, test bank using; Arranging the to traditional types of checking the results of learning. requirements to the lesson description: rules, Form of testing may be different (multiple choice, fill gaps, requirements, timetable etc.; monitoring students’ marks: substitution, etc.). To avoid guessing or transferring of (projects, grade book, reports, frequency of visits; Forms keys (answers) from group to group “Test Wizard LMS” of interaction of members of the course: aim and types of allows you to use a random selection of numbers of interaction: forum, chat, e mail, announcements.
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Design and Development of a Device-Independent System for Mobile Learning

Design and Development of a Device-Independent System for Mobile Learning

Mobile learning can be employed to establish pervasive learning environments to make learning experience pervasive. In pervasive learning, education will be available for people at all levels, from toddlers to seniors, even people who are hard-to-reach, people in rural areas with limited learning resources or people who have been geographically isolated. Mobile learning utilizes handheld devices such as smart phones, PDAs and other similar mobile phones in learning, although there are some debates on the inclusion of tablet PCs and laptops [7]. However, in mobile learning, given the wide variety of mobile devices available, hardware is considered a solved problem; the challenge is now in developing innovative, usable and affordable software applications and services for these devices [6]. Hence, we have focused on the design and development of new applications and tools for both educators and learners to enhance mobile learning. In this paper, we present our proposed system to generate quizzes, which is part of a larger framework for mobile learning. Our system is called MLQ (Mobile Learning Quiz). MLQ allows educators to create quizzes once and then generate the same content automatically
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Energy Management in Mobile Devices with the Cinder Operating System

Energy Management in Mobile Devices with the Cinder Operating System

There is rich prior work on addressing the visibility problem of attributing consumption to application principals. Control, in contrast, has seen much less effort. Early systems like EcoSystem proposed high level application power limits. Mobile applications today, however, are much more complex: they spawn and invoke other services and have a much richer set of peripherals to manage. We believe that for users and applications to effectively control power, an operating system must provide three mechanisms: isolation, subdivision, and delegation. We motivate these mechanisms through three application examples that we follow through the rest of the paper. Isolation is a fundamental part of an operating system. Memory and IPC isolation provide security, while cpu and disk space isolation ensure that processes cannot starve others by hogging needed resources. As a more concrete example, the energy a phone reserves for an emergency 911 call should be isolated from the rest of the system, so that other programs cannot use it. Web browsers run (sometimes untrusted) plugins. Given that a browser receives a finite amount of power, it might want to protect itself from buggy or poorly written plugins that waste CPU energy. The browser would like to subdivide its energy so that it can give plugins a small fraction, knowing that isolation will prevent them from using its own lion’s share. The ability to subdivide energy is critical for applications to be able
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Evaluating an Intelligent Q&A System for Mobile Cultural Learning

Evaluating an Intelligent Q&A System for Mobile Cultural Learning

experimenter provided a brief explanation about the purpose of the experiment, the participants began the task, which was to uncover information about six locations of the medieval castle and ask questions after the completion of each presentation. They were asked to perform this task once using System A and again using System B. To make it easier for participants to understand the provided information, each presentation was divided into parts and an interactive panoramic representation of each location was integrated in the systems. Participants could interact with the panoramic while listening to a presentation, thus relating the provided information to the actual locations. Half of the participants in each group were told to ask as many questions as they liked per location as long as the total number was not greater than twelve. The other half was restricted to four questions per location. In case the system failed to process one of the questions, participants were asked to rephrase their question as many times as necessary, until they got an answer. Once the system provided an answer, participants were asked to rate thirteen statements on a 10-point scale (1 = no answer 10 = perfect answer). Examples of these statements are clarity and wording of the answers. After the participants had visited all locations, they were asked to write down what they could remember from the presentations (and answers) about each location in total, and freely comment on their overall experience with the systems.
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MANAGEMENT ISSUES AND CHALLENGES IN MOBILE DATABASE SYSTEM

MANAGEMENT ISSUES AND CHALLENGES IN MOBILE DATABASE SYSTEM

Mobile databases typically involve three parties: fixed hosts, mobile units, and base stations. Fixed hosts perform the transaction and data management functions with the help of database servers. Mobile units are portable computers that move around a geographical region that includes the cellular network (or "cells") that these units use to communicate to base stations. Base stations are two-way radios, installations in fixed locations that pass communications with the mobile units to and from the fixed hosts. They are typically low-power devices such as mobile phones, portable phones, or wireless routers. A cellular mobile network is similar to that of Mobile Network Architecture. It consists of Mobile Client (MC) containing data centric applications roaming between wireless cells and accesses a centralized database (fixed host). Some of the fixed hosts called Mobile Support Stations (MSSs), are augmented with wireless interfaces. The wireless channel is separated into two sub-channels: an uplink channel and a downlink channel. The uplink channel is used by MCs to submit queries, while the downlink channel is used by MSSs to answers from the server to target mobile client. 4
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Reading material personalization searching in e learning

Reading material personalization searching in e learning

Personalization can be applied via learning style. In this study, we use the VARK learning style by Fleming and Mill (1992), because it uses sensory modality. Sensory modality involves the merging of perception and memory, with due consideration to the way the mind receives and accumulates information. With the utilization of sensory modality, the elements that constitute the four learning style preferences, which are Visual (for learners who prefer information presented in a visual form), Aural (for learners who prefer information that is listened to or verbalized), Read/write (for learners who prefer information presented in a text form) and Kinesthetic (for learners who prefer learning by example, action, practice and experience), can be differentiated and appropriately mapped to the reading material.
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