In this paper, we propose a real-time video playback scheme for the N-Screen service based onWindows Azure. This scheme creates several playback blocks based on the performance of eachnode by non-uniform splitting of the original video. To reduce transcoding-time, it allocates the playback blocks to a corresponding node by transcoding the playback blocks. Through thesimulation, we show that it is more effective to use real-time video playback for the N-screenservice than the previous method. The proposed scheme splits an AVI format 300MB source videowith non-uniform playback blocks. It allocates the playback blocks to the heterogeneous node ofWindows Azure, the commercial cloud system and measures of transcoding-time by transcodingnon-uniform playback blocks to mp4 and Flv format. As a result, the proposed scheme improvesthe performance of the N-screen service based on Windows Azure compared to the previousuniform split strategy.
While safe and convenient, ultrasound imaging analysis is often criticized by its subjectivedecision making nature by field experts in analyzing musculoskeletal system. In this paper, wepropose a new automatic method to extract muscle area using ART2 neural network basedquantization. A series of image processing algorithms such as histogram smoothing and End-insearch stretching are applied in pre-processing phase to remove noises effectively. Muscle areasare extracted by considering various morphological features and corresponding analysis. Inexperiment, our ART2 based Quantization is verified as more effective than other generalquantization methods.
An ensemble classifier system is a widely-used multi-classifier system, which combines theresults from each classifier and, as a result, achieves better classification result than any singleclassifier used. Several methods have been used to build an ensemble classifier including boosting,which is a cascade method where misclassified examples in previous stage are used to boost theperformance in current stage. Boosting is, however, a serial method which does not form acomplete feedback loop. In this paper, proposed is context sensitive SVM ensemble (CASE) whichadopts SVM, one of the best classifiers in term of classification rate, as a basic classifier andclustering method to divide feature space into contexts. As CASE divides feature space and trains SVMs simultaneously, the result from one component can be applied to the other and CASEachieves better result than boosting. Experimental results prove the usefulness of the proposedmethod.
A Power Management System(PMS), which provides the functions of automatic detection andcutoff of home appliances' standby power without user intervention, is presented in this paper. Aclient in this system measures the power consumption of a home appliance plugged in it andtransmits the information to a server in real-time over a wireless network. The server analyzes thefeatures of the power consumption of home appliances and detects if any home appliance consumesstandby power. The detected standby power information is used to create the information of the home appliance and to build a database, which will finally offer the automatic detection and cutoffof the standby power without any configuration through user intervention.
Social emotion is being highlighted as an important factor of human life in terms of quality ofcommunication as a variety of social networks are commonly used. To understand such socialemotion, this study verifies and analyzes the significance of lexical meaning and expression ofemotion basically for understanding of complex meaning of social emotion. The emotionalexpressions represented in SNS text messages, one of the major channel of communication, areexamined in this study to create scales of meaning and expression and to understand thedifferences deeply. As a result of the analysis, it turned out that negative assessment factors were more than positive ones among social emotional factors while positive ones were outstandinglymany in the case of social emotional expression. Social emotional factors were classified by basicemotional elements and valences while emotional expression included complex meaning andespecially positive elements were dominant in general.
Recently, wireless sensor networks(WSNs) are widely used for intrusion detection and ecology,environment, atmosphere, industry, traffic, fire monitoring. In this paper, an energy efficientclustering algorithm is proposed. The proposed algorithm forms clusters uniformly by selectingcluster head that optimally located based on receiving power. Besides, proposed algorithm caninduce uniform energy consumption regardless of location of nodes by multi-hop transmission andMST formation with limited maximum depth. Through the above, proposed algorithm elongates network life time, reduces energy consumption of nodes and induces fair energy consumptioncompared to conventional LEACH and HEED. The results of simulation show that the proposedclustering algorithm elongates network life time through fair energy consumption.
Various Time Synchronization protocols considering for the characteristics of WSN(WirelessSensor Network) have been developed, because a time relationship plays an important role inmany WSN applications, as well. Synchronization accuracy as well as constraints of energy shouldbe considered for WSN Time Synchronization protocols, especially. In this paper, I analyze TimeSynchronization protocols for WSN after classifying these protocols with a new criteria (i.e. powerconsumption). So, this method will contribute to evaluating and comparing WSN TimeSynchronization protocols in respect of power consumption.
Employing PTAS to building minimum spanning tree for a large number of equal distributioninput terminal nodes can be a effective way in execution time. But applying PTAS to building minimum spanning tree for tremendous unequal distribution node may lead to performancedegradation. In this paper, a partial PTAS reflecting the scheme into specific node dense area ispresented. In the environment where 90% of 50,000 input terminal nodes stand close together inspecific area, approximate minimum spanning tree by our proposed scheme can show about 88.49%execution time less and 0.86%tree length less than by existing PTAS, and about 87.57%executiontime less and 1.18% tree length more than by Prim’s naive scheme. Therefore our scheme can gowell to many useful applications where a multitude of nodes gathered around specific area shouldbe connected efficiently as soon as possible.
In this paper, we propose an efficient dynamic workload balancing strategy which improves theperformance of high-performance computing system. The key idea of this dynamic workloadbalancing strategy is to minimize execution time of each job and to maximize the systemthroughput by effectively using system resource such as CPU, memory. Also, this strategydynamically allocates job by considering demanded memory size of executing job and workloadstatus of each node. If an overload node occurs due to allocated job, the proposed scheme migratesjob, executing in overload nodes, to another free nodes and reduces the waiting time and execution time of job by balancing workload of each node. Through simulation, we show that the proposeddynamic workload balancing strategy based on CPU, memory improves the performance ofhigh-performance computing system compared to previous strategies.
The objective of this study is to propose the measurement system implementation method for the evaluation and measurement of the indoor-impulsive over 170 dB noise source. For the purpose of measuring impulse noise, design and implementation constructed followed subsystems of the testing center, microphone, ear simulator, head and torso simulator and so on. Measurement systems for the accuracy and reliability of impulse noise are implemented when measuring 3 ways of measurements method by the simultaneous measurement system design. For the accuracy and reliability of three mutually indoor-impulse noise measurements were compared, three kinds of measuring methods in accordance with the peak sound pressure level and octave band. Comparing the results of data, the indoor-impulse noise by analyzing a frequency characteristic was validated in difference for the statistical significance. Result are determined by the influence of the reflected wave. Therefore, the flexible size of the interior test site while interior impulse noise measurement system was constructed. Throughout this system can be affected by parameters that are the impulse noise source and the corresponding frequency-characteristic analysis to determine the spectrum of the reflected wave. And, in the near future, indoor impulse noise measurement systems for acquisition and analysis are utilized in useful data.
The parallel machine scheduling is to schedule each job to exactly one parallel machine so thatthe total completion time is minimized. It is used in various manufacturing system areas such assteel industries, semiconductor manufacturing and plastic industries. Each job has a setup phaseand a processing phase. A removal phase is needed in some application areas. A processing phaseis performed by a parallel machine alone while a setup phase and a removal phase are performedby both a server and a parallel machine simultaneously. Most of previous researches used a single server and considered only a setup phase and a processing phase. If a single server is used forscheduling, the bottleneck in the server increases the total completion time. Even though thenumber of parallel machines is increased, the total completion time is not reduced significantly. Inthis paper, we have proposed an efficient algorithm for the parallel machine scheduling usingmultiple servers and considering setup, processing and removal phases. We also have investigatedexperimentally how the number of servers and the number of parallel machines affect the totalcompletion time.
A cold storage is a warehouse of a insulated building with cooling installations. It has manydifferent types of cold rooms with temperatures below 0 degrees Celsius, and the sequentialworkflow such as receiving, picking and packing runs in that rooms. Recently, the cold storageshave adopted RFID technology, and consequently, warehouse product management in them arebecoming intelligent and network. However, information inconsistency in warehouses caused by physical and logical errors reduces reliability in the RFID cold storage management system andworsens their work efficiency. Therefore, it is necessary to develop an early detection system toidentify errors. In this paper, we suggest a supervisory system detecting logical errors on businessprocesses of the RFID cold storage. It is composed of a master supervisor and mobile supervisor. Inthe master supervisor, the manager can set the constraints conditions and get alerts, and in themobile supervisor, the workers confirm and deal with these faults directly. The supervisory systemimprove reliability of the RFID cold storage management system by recognizing a failure to identifyphysically and logically using these constraint conditions. This paper shows that the supervisorysystem can reduce the average recovery time to improve reliability by decreasing the time fordetecting and analyzing errors in the RFID cold storage management system.
In this study, the social welfare field training course there is a growing awareness asprofessionals in order to verify the impact was conducted.
G-local four-year university study social work majors by sampling 198 people were examined forthe purpose, through self - survey was conducted.
Materials and analytical methods in order to identify the characteristics of a variable frequency,and technical analysis, T-test, F-test, ANOVA, correlation (correlation), Regression (regression)was used for the SPSS 14.0. The results are as follows. First, the personal factors of the individual physician trainees reflect(β = .197), and then the same about Social Welfare satisfaction (β = .205) of the Social Welfaremajors had significant impact on career identity. Second, the personal factors they chose what tomajor in social work satisfaction (β = - .291), and if you feel you select a parent with a major inSocial Work and Social Welfare major students feel the satisfaction of having a significant effect onthe level of career decision crazy. Third, individual reflect personal physician factors (β = .156) issignificantly influenced the behavior of career preparation
The Electronic contract means creationㆍsignㆍmanagement and storage of contract by online without limitations of the time and space through the electronic signature and encode which based on the Certificate instead of the past that treatment the contract such as creationㆍsignㆍ management and storage of contract by face-to-face. Recently, the remarkable development of information and communication technology with supplying the high-speed Internet services.
Accordingly, the transaction contract made by these also, the steady legal effect occurred by two or more parties by legal action which is the electronic agreement of expression. and it makes agreement improving corporate productivity and it can control the whole process such as contract documents and the actual buyingㆍstoreㆍprovision. Like this it has many benefits so, it suddenly rising as the new axis of economic activity area, it is a reality.
In this change of era, with the establishment of electronic contracts, there are many problems are occurred to the expression of parties which is core of the contract on civil code so, the systematic legal composition is required. Thus, in this study will propose the reasonable improvements about the issue of electronic contract through the consideration.
Much research has been conducted in educational robot, a new instructional technology, for K–12 education. Several studies have shown that educational robot provides effective learningopportunities for students in both content areas of STEM(science, technology, engineering, andmathematics) and critical academic skills, such as collaboration, problem solving andcommunication skills. However, most studies to date on applications of educational robots havebeen conducted outside the formal education setting. This study analyzed the influence of usingrobots in an elementary school science class in Korea with regard to science learning motivation. Atotal of 121 students in fourth and fifth grades participated in the study. The experimental group was taught using robots in the science class, while the control group was taught using traditionalmethods. Analysis of covariance (ANCOVA) was conducted to compare the between-groupdifferences in learning motivation before and after the experiment; an interview was alsoconducted for the experimental group. The study results showed a significant improvement (p<.05)in both learning motivation in the experimental compared with the control group. There was alsopositive response to learning with a robot. This study will play an important role in research onthe use of educational robot in formal education in the future.