Mobile Device Environment Research Articles

Service Based Content Sharing in the Environment of Mobile Ad- hoc Networks

The peer-to-peer network is the one of the traditional client server networking model. The file sharing on mobile devices is not easily achieved to the user for limited bandwidth and high cost. The irregular disconnection and IP address changes occur due to network migration. We holds the short range networking technologies as Bluetooth with no cost to the user and it is sufficiently fast to make file transfer very practical. A peer-to-peer model that permits efficient file sharing between mobile smartphones over a low-cost transport. Our paper results that peer-to-peer file transfer between todays mobile devices are practical. But the server limits must be applied on the transfers. These are unique to the mobile device environment. The upload-overdownload ratio should be relatively low, due to higher current drain on transmit. Where the target file system is very slow then the larger file segments “Direct Memory Access” (DMA) mode can be utilized as different to “Program Input Output” (PIO) mode. The use of UDP for content sharing is more ideal than the use of OBEX. We will overcome some of the barriers to acceptance through our design approach. Peer discovery and content distribution occurs automatically without connection from the user. At last the transport is also implemented in the application layer and uses existing standard protocols without modification.

모바일 환경을 고려한 규칙기반 음성인식 오류교정

본 논문에서는 모바일 환경에서 음성인식한 결과에 포함된 오류를 교정하는 규칙기반 접근방법을 제안한다. 제안하는 방법은 처리시간이나 메모리에 제약을 받는 모바일 환경을 고려하여 다음과 같이 구성된다. 오류 교정 속도를 최소화하기 위해서, 음절 해체 및 조합 과정이나 형태소 분석 등의 처리를 줄이고, 최장일치 규칙 선택기준을 바탕으로 오류 발생 추정 지점에서 교정 후보도 하나만 생성한다. 제안하는 방법은 메모리를 효율적으로 사용하기 위해서, 어절사전이나 형태소분석기를 사용하지 않고, 규칙도 유형별로 따로 구분하지 않고 통합하여 저장한다. 제안하는 방법은 모델의 수정 및 유지보수가 용이하도록, 오류교정규칙을 학습말뭉치에서 자동으로 추출하여 구축한다. 실험결과 제안하는 방법은 음성인식 결과에 대하여 정확률을 5.27% 정도 재현율을 5.60% 정도 개선하였다. In this paper, we propose a rule-based model to correct errors in a speech recognition result in the mobile device environment. The proposed model considers the mobile device environment with limited resources such as processing time and memory, as follows. In order to minimize the error correction processing time, the proposed model removes some processing steps such as morphological analysis and the composition and decomposition of syllable. Also, the proposed model utilizes the longest match rule selection method to generate one error correction candidate per point, assumed that an error occurs. For the purpose of deploying memory resource, the proposed model uses neither the Eojeol dictionary nor the morphological analyzer, and stores a combined rule list without any classification. Considering the modification and maintenance of the proposed model, the error correction rules are automatically extracted from a training corpus. Experimental results show that the proposed model improves 5.27% on the precision and 5.60% on the recall based on Eojoel unit for the speech recognition result.

Visual Monitoring System of Multi-Hosts Behavior for Trustworthiness with Mobile Cloud

Recently, security researches have been processed on the method to cover a broader range of hacking attacks at the low level in the perspective of hardware. This system security applies not only to individuals' computer systems but also to cloud environments. "Cloud" concerns operations on the web. Therefore it is exposed to a lot of risks and the security of its spaces where data is stored is vulnerable. Accordingly, in order to reduce threat factors to security, the TCG proposed a highly reliable platform based on a semiconductor-chip, the TPM. However, there have been no technologies up to date that enables a real-time visual monitoring of the security status of a PC that is operated based on the TPM. And the TPB has provided the function in a visual method to monitor system status and resources only for the system behavior of a single host. Therefore, this paper will propose a m-TMS (Mobile Trusted Monitoring System) that monitors the trusted state of a computing environment in which a TPM chip-based TPB is mounted and the current status of its system resources in a mobile device environment resulting from the development of network service technology. The m-TMS is provided to users so that system resources of CPU, RAM, and process, which are the monitoring objects in a computer system, may be monitored. Moreover, converting and detouring single entities like a PC or target addresses, which are attack pattern methods that pose a threat to the computer system security, are combined. The branch instruction trace function is monitored using a BiT Profiling tool through which processes attacked or those suspected of being attacked may be traced, thereby enabling users to actively respond.

RAM: Rate Adaptation in Mobile Environments

Channel asymmetry and high fluctuation of channel conditions are two salient characteristics of wireless channels in mobile environments. Therefore, when using IEEE 802.11 devices in mobile environments, it is critical to have an effective rate adaptation scheme that can deal with these issues. In this paper, we propose a practical rate adaptation scheme called Rate Adaptation in Mobile environments (RAM) and implement it in the MadWifi device driver. RAM uses a receiver-based approach to handle channel asymmetry and a conservative SNR prediction algorithm to deal with high channel fluctuation. More importantly, RAM allows the receiver to convey the feedback information to the transmitter in a creative manner via ACK transmission rate variation, which does not require changes to the device firmware and hence is implementable at the device driver level. In addition, RAM adopts an effective scheme to guarantee that RAM-based and legacy IEEE 802.11 devices can interoperate with each other. The effectiveness of RAM is demonstrated via in-depth experimental evaluation in indoor static and mobile environments as well as outdoor vehicular environments.

Memory bandwidth-scalable motion estimation for mobile video coding

The heavy memory access of motion estimation (ME) execution consumes significant power and could limit ME execution when the available memory bandwidth (BW) is reduced because of access congestion or changes in the dynamics of the power environment of modern mobile devices. In order to adapt to the changing BW while maintaining the rate-distortion (R-D) performance, this article proposes a novel data BW-scalable algorithm for ME with mobile multimedia chips. The available BW is modeled in a R-D sense and allocated to fit the dynamic contents. The simulation result shows 70% BW savings while keeping equivalent R-D performance compared with H.264 reference software for low-motion CIF-sized video. For high-motion sequences, the result shows our algorithm can better use the available BW to save an average bit rate of up to 13% with up to 0.1-dB PSNR increase for similar BW usage.

모바일 클라우드 컴퓨팅에 최적화된 모바일 웹 사용성 개선

최근 클라우드 컴퓨팅이 빠르게 확산되면서 기존의 인터넷 환경 뿐 아니라 모바일 클라우드 컴퓨팅에 관한 관심이 급증하고 있다. 스마트폰을 비롯한 모바일 단말기는 하드웨어를 비롯하여 애플리케이션, 서비스까지 모든 면에서 빠르게 변화하고 있다. 하지만 웹표준 준수 및 모바일 웹에 대한 이해가 부족한 국내 모바일 인터넷 환경에서는 인터넷 접속이 원활하지 않고, 국내 웹사이트의 대부분이 다양한 기능과 화려한 디자인에 주력하여 개발하고 있기 때문에 스마트폰이나 태블릿 PC에서 접속시 사용성 및 접근성을 떨어뜨리는 요인이 된다. 이에 본 연구는 모바일 클라우드 환경에서 사용성과 접근성을 고려한 웹 인터페이스를 제안하고 이를 사용성 평가를 통하여 검증하고자 한다. 우리는 이미 선행 연구를 통하여 모바일 단말기 환경에 최적화된 메인페이지 인터페이스를 제안하고 그 사용성이 개선되었음을 입증하였으나, 이는 웹사이트 전체에 대한 사용성을 보증하지 못한다. 본 연구는 선행 연구를 통하여 제시하였던 웹표준의 준수와 그를 통한 웹 인터페이스 방식이 해당 웹사이트 전체에 걸쳐 사용성을 개선함을 보인다. 우리는 클라우드 컴퓨팅에 최적화된 웹사이트를 선정하여 웹사이트 전체에 대한 사용성 평가를 실시함으로써 실제로 그 접근성 및 사용성이 개선되었음을 검증한다. 또한, 이러한 개선을 통하여 기업이나 개인 모바일 웹사이트 개발자들에게 유저 인터페이스(UI) 디자인 적용을 위한 지침을 제공한다. Recently, sudden interests of mobile cloud computing as well as conventional internet environment are rapidly increased as cloud computing spread out in our web society. Mobile devices including smart phone are rapidly changing in a wholesale way that covers hardwares, applications, and services. However, the Internet access using mobile device is not quite smooth in this local mobile internet environment which suffers from lack of understanding and observance of Web Standards. Although most of domestic web sites are developed focusing on various functions and eye-catching designs, this should became one of the main factors that make the usability and accessability decrease when accessing web with smart phones or table PCs. Therefore, this paper suggested a web interface that considered usability and accessability under mobile cloud environment and we tried to prove it via usability test. It could be found that there was an improvement of usability of interface of the main page that has been optimized to the mobile device environment suggested from the previous research we present, but this paper aimed to prove a usability improvement of total website as a whole by performing the usability test on the entire website. Selecting a special website optimized for mobile cloud computing, we prove an improvement of usability and accessibility. Therefore, we offer a guideline about user interface design applications to developers or companies who want to construct mobile website.

IPA를 활용한 다국어 음성 인식에 관한 연구

최근 다양한 모바일 기기의 사용자 환경과 다양한 음성인식 소프트웨어의 영향으로 음성인식 기술역시 빠르게 발전되고 있다. 그러나 다국어를 대상으로 하는 음성인식의 경우 다국어 혼합음성에 대한 이해 부족과 시스템 성능의 한계로 인하여 원활한 인식율의 개선은 이루어지지 않고 있다. 여러 나라의 혼합 언어로 표현된 음성의 경우 하나의(단일) 음성모델로 구현하는 것이 쉽지 않고, 또한 여러 개의 음성모델을 사용한 시스템의 경우 음성인식 성능의 저하라는 문제점이 있다. 이에 따라 다양한 언어로 구성되어 있는 음성을 하나의 음성모델로 표현할 수 있는 다국어 음성인식 모바일 시스템의 개발 필요성이 증가되고 이에 대한 연구가 필요하다. 본 논문에서는 모바일 시스템에서 다국어 혼합 음성모델을 사용하기 위한 기본연구로써 한국어와 영어 음성을 국제 음성기호(IPA)로 인식하는 통합음성모델 시스템 구축을 연구하였고, 한국어와 영어 음소를 동시에 만족하는 IPA모델을 찾는데 중점을 두어 실험한 결과 우리말 음성은 94.8%, 영어 음성은 95.36%라는 인식률을 얻을 수 있었다. Recently, speech recognition technology has dramatically developed, with the increase in the user environment of various mobile devices and influence of a variety of speech recognition software. However, for speech recognition for multi-language, lack of understanding of multi-language lexical model and limited capacity of systems interfere with the improvement of the recognition rate. It is not easy to embody speech expressed with multi-language into a single acoustic model and systems using several acoustic models lower speech recognition rate. In this regard, it is necessary to research and develop a multi-language speech recognition system in order to embody speech comprised of various languages into a single acoustic model. This paper studied a system that can recognize Korean and English as International Phonetic Language (IPA), based on the research for using a multi-language acoustic model in mobile devices. Focusing on finding an IPA model which satisfies both Korean and English phonemes, we get 94.8% of the voice recognition rate in Korean and 95.36% in English.

LEMONADE: field-trip authoring and classroom reporting for integrated mobile learning scenarios with intelligent agent support

Most existing mobile learning environments for supporting field-trip activities are limited to specific domains or contents and do not support authoring. We present a framework for planning and conducting field trips with mobile devices called learning environment for mobile network capable devices (LEMONADE), which provides full-cycle support for authoring and conducting field trips as well as for post-trip reporting and reflection activities. LEMONADE includes a generic graph-based language for authoring task specifications and for querying and presenting field-trip results. It is fully integrated in the graph-based modelling environment FreeStyler, allowing the students' results to be flexibly used in follow-up activities.

Topic comparison of remote documents using small communication traffic

This paper presents a new method for semantic search solutions designed for mobile device environments. The proposed system aims at helping users by searching for documents which have similar topics to the ones stored on the users own device. The search is performed in background continuously and the user is notified if documents worth for downloading were found. The methods proposed in this paper aim at solving this task while maintaining low communication traffic to make them applicable in the mobile device environment.

HANDWRITTEN SHORTHAND AND ITS FUTURE POTENTIAL FOR FAST MOBILE TEXT ENTRY

Handwritten shorthand systems were devised to enable writers to record information on paper at fast speeds, ideally at the speed of speech. While they have been in existence for many years it is only since the 17th Century that widespread usage appeared. Several shorthand systems flourished in the first half of the 20th century until the introduction and widespread use of electronic recording and dictation machines in the 1970's. Since then, shorthand usage has been in rapid decline, but has not yet become a lost skill. Pitman shorthand has been shown to possess unique advantages as a means of fast text entry which is particularly applicable to hand-held devices in mobile environments. This paper presents progress and critical research issues for a Pitman/Renqun Shorthand Online Recognition System. Recognition and transcription experiments are reported which indicate that a correct recognition and transcription rate of around 90% is currently possible.

An accelerator design for speedup of Java execution in consumer mobile devices

In today’s consumer electronics market, Java has become one of the most important programming languages for the rapid development of mobile applications – spanning from home appliances/controllers, mobile and communication devices, to network-centric applets. However, the demand for high-performance low-power Java-based consumer mobile applications puts forward new challenges to the system design and implementation. This paper analyzes the energy consumption, execution efficiency, and speed issues of Java applications in a typical consumer mobile device environment. By adopting a hardware-assisted approach, we introduce a Java accelerator with a companion Java virtual machine. The accelerator is designed in an asynchronous style, and can be integrated with most existing processors and operating systems. The core architecture, design philosophy, and implementation considerations are presented in detail in this paper.

Improved Topic Identification for Similar Document Search on Mobile Devices

This paper presents a novel, two level classifier ensemble designed to support document topic identification in mobile device environments. The proposed system aims at supporting mobile device users who search for documents located in other mobile devices which have similar topic to the documents on the users own device. Conforming to the environment of mobile devices, the algorithms are designed for slower processor, smaller memory capacity and they maintain small data traffic between the devices in order to keep low the cost of communication. We propose a keyword list based topic comparison, enhanced with a two level classifier ensemble to accelerate the topic identification process. The new technique enables document topic comparison using few communication traffic and it requires few calculations.

Crystallography on mobile phones

The new possibilities offered by mobile phones combined with their widespread dissemination among young people open new paradigms for teaching science. The wide adoption of the Java environment for mobile devices gives the opportunity to develop custom-made applications for educational purposes. The first mobile phone application for crystallography training,Escher Mobile, is now available at http://escher.epfl.ch/mobile/.

A multilevel input system with force-sensitive elements

Force-sensitive multilevel input elements are introduced as the basic building blocks for compact-size input devices in mobile environments. Compared with switch-type keys, multilevel elements can decrease the number of keys on a keyboard while maintaining the input capacity. A multilevel input mechanism using force-sensitive sensor pads is demonstrated in a three-level three-element tactile chording system with multimodal feedback. Two schemes are introduced to segment the output range of the sensor into levels. For relatively unpracticed users, the scheme based on maximum finger forces gives an average error rate of 20.2% and an input time of 2.24 s for a chord of three inputs. Reclassification of the experimental data using Gaussian segmentation shows that significant improvement of the performance can be expected.