Intelligent Pattern Research Articles

Study of Emotional Intelligence Patterns with Teachers Working in Public Education

Abstract The data necessary for the empirical research presented it this study were provided by 572 people, from altogether 26 schools. The schools included 18 primary schools, 7 secondary training institutions and 1 primary and secondary school. The major question of the study related to the pedagogues' emotional intelligence, more precisely if the teachers of different institutions showed any individual differences in their emotional intelligence patterns according to the given type of their school's organisational culture. We also examined if the nature of the organizational culture had any influence on the development the individual's emotional intelligence pattern. On the basis of the results we can declare that the teachers of different institutions having their own particular organizational cultures evolve different emotional intelligence patterns. Accordingly, we can come to the conclusion that in the long term the organizational culture affects the evolution of the individual's emotional intelligence pattern and vice versa.

Speech intelligibility across native and non-native accents: Accent similarity and electrophysiological measures of word recognition

The intelligibility of accented speech in noise greatly depends on the pairing of speaker and listener, where two important factors are a listener’s familiarity with a speaker’s accent and the acoustic similarity between their accents. In this study, we present patterns of the intelligibility of standard British English, Glaswegian English and Spanish English accents for British and high and low proficiency Spanish listeners. We predict intelligibility will correlate with acoustic-phonetic similarity across accent pairings, in line with previous findings. As such, findings are expected to provide further support that accent similarity can predict patterns of accent intelligibility, even if listeners have little experience of a speaker’s accent. Electrophysiological measures relating to phonological and semantic integration stages of word recognition will also allow the investigation of the influence of accent on the time course of word recognition, which has not previously been directly compared to accent intelligibility or applied in studies of accent processing by non-native listeners. Findings will be discussed in the context of previous exploratory findings in this field, and in reference to other factors influencing accent intelligibility.

Big Data and Public Sector Information

Public sector organizations, as reliable information publishers, are often unacknowledged but pivotal sources for big data projects using analytics. Big data analytics make sense of diverse unstructured digital collections by transforming them into intelligible patterns and predictions. Big data trends are validated against authoritative sources such as public sector information. Governments need to be aware that their standards, such as zip codes, have a secondary use in big data projects. Data mining and predictive analytics both challenge and enhance our notions of community, accountability, consumers, authorship, markets, firms, nationality, ownership, responsibility, and democracy. Public-sector big data provides unprecedented opportunity to study both organizational strategy and the public response to large-scale information analytics. The January 28th 2014 Online International Forum on Postal Big Data hosted by the USPS Office of Inspector General and the Universal Postal Union (UPU) will provide a starting point for considering this growing research agenda.

(2D)2PCA 알고리즘을 이용한 pRBFNNs 패턴분류기 기반 얼굴인식 시스템 설계

본 연구에서는 (2D)2PCA 알고리즘을 이용한 pRBFNNs 패턴분류기 기반 얼굴인식 시스템을 설계하였다. 기존의 1차원 PCA는 행과 열의 곱으로 표현한 이미지의 차원을 축소한다. 하지만 (2D)2PCA(2-Directional 2-Dimensional Principal Components Analysis)는 이미지의 행과 열에서 각각 차원축소를 수행한다. 그 다음 제안된 지능형 패턴분류기로 축소된 이미지를 사용하여 성능을 평가한다. (pRBFNNs)로 성능 평가를 한다. 제안된 다항식 기반 RBFNNs은 조건부, 결론부, 추론부 세가지의 기능적 모듈로 구성되어 있고 조건는 퍼지 클러스터링을 사용하여 입력 공간을 분할하고, 결론부는 RBFNNs의 연결가중치로 일차 선형식으로 표현한다. 또한 차분진화 알고리즘을 이용하여 제안된 분류기의 파라미터, 즉 입력의 수, 퍼지 클러스터링의 퍼지화 계수를 최적화 한다. 얼굴인식에 많이 사용되는 Yale과 AT&T를 사용하여 인식률을 평가하였다. 실험 평가를 위해 IC&CI 연구실 데이터를 추가하여 실험하였다.<BR><BR>

Upaya Peningkatan Kinerja Inovatif berbasis Pola Kerja Cerdas dalam Konteks Teknologi Informasi

. Reality show superior school supplies the highest graduation rate (branded). However, the academic activities of the learning process of understanding and application of innovative learning models is still less than optimal. Therefore the aim of this study was to develop a model of innovative performance-based teacher enhancement working smart in the context of information technology. The study population was the entire school teacher featured in Pekalongan city of 200 people, Given the limited number of population sampling technique used is the census, meaning the amount equal to the total sample population. Testing the hypothesis using Structural Equation Modeling (SEM) with AMOS 5.0 software. Then efekk moderation of information technology with the data management group. The study shows that in the context of low information technology, innovative performance improvement with an increase in doing working smart . While in the context of high information technology, innovative performance improvement with an increase in do intelligent work patterns built by intrinsic motivation.

Emerging personal intelligence in collective goals: data analysis on the bottom-up approach from PKM to OKM

Purpose – A pattern of personal intelligence is seen emerging from the concept of agent-mediated personal knowledge management (PKM) in achieving collective organisational goals. The purpose of this paper is to present the results of surveys undertaken to prove this emergence. Design/methodology/approach – A quantitative analysis supported by a qualitative analysis was conducted across three main industries in Malaysia, namely manufacturing, service and education. The triangulation of analysis is based on the four proposed hypotheses. Findings – From these analyses, it was discovered that the emergence of personal intelligence is embedded within the collaborative interactions amongst software agents, and between agents and human knowledge workers. All the hypotheses are supported by the results of the surveys which manifest organisational knowledge management (OKM) practices as a consequence of the agent-mediated PKM processes. Research limitations/implications – This research focused on the PKM in Malaysia, where the level of KM implementation varies among the organisations. The results may not reflect other developing countries due to the socio-cultural differences amongst the knowledge workers. Practical implications – The results from this paper can be used either to relook and reanalyse the existing organisational KM system or to plan and design a KM system for organisations that have not implemented any. Originality/value – The focus on personal intelligence and agent-mediated PKM contribute to further development of agent-based system that animates these theories in the real working environment.

Relationship between Female Figure Variable and Coat Pattern Graphics

This study is directed at the shoulder, back and breast of female to sum up its parts variation law and set up the relationship between figure variable of these three parts and pattern graphic, and thus complete the basic study of human figure characteristics corresponding to the digitalized prototype pattern of female coat. It is a basic study for female coat prototype pattern automatic design system of special figure, which sets up the relevant relationship between female figure characteristics and coat prototype structural feature and to guarantee the consistency of figure and pattern design in the process of garment PCAD system pattern intelligent design. It provides the possibility for the study of intelligent female coat pattern design system based on the figure and has a positive effect on changing the traditional pattern design concept and means.

Design of Method Database for Correction System of Intelligent Womens Jacket Pattern

The automatic creation of garment parametric computer aided design (PCAD) pattern to special body size is rarely classified and need to be finished with man machine interface at present. This has become a critical and challenging issue to hinder the intelligence process of the garment computer aided design (CAD). In this paper, the basic research aimed at the automatic correction pattern of the special size on the womens jacket CAD system was investigated. The popular special size of women trunk and pattern amendment was selected as research subject, and the relationship between the body characteristics and coat pattern Fig. were set up. The full-scale constraint was developed and the expertise description about womens jacket patterns were finished with the parametric design method based constraint. The mathematic formula and logical definition relation are used to establish relationship with the formed model characteristics of womens jacket patterns. The system then carry and keep the design of womens jacket pattern and the correction logic, and finish the creation and correction of the geometric model to womens jacket pattern. The expertise knowledge of womens jacket pattern correction is applied by the design of method database. The paper performs the basic research and analysis for the rules database creation in the PCAD system, and makes it possible to the research of intelligent womens jacket pattern design system based body size. It will play an active role to transform traditional design concepts and means.

A Software Application for Smart Home Energy Management System

A cross-platform software application was developed to manage energy generation and consumption intelligently in smart homes. The system model consists of domestic loads, household distributed energy resources and an energy storage component that supports scheduled charging/discharging. The software deals with all these electrical devices as well as their energy information, based on which real-time conditions are presented to the resident and the history can be queried. Whats more, the application fulfills kinds of energy profiling and pricing-related optimization on account of demand response, resulting more monetary benefits and comforts. The software interacts smartly with energy owners by graphical user interface (GUI) and enables an intelligent electricity usage pattern in the context of smart power consumption within the framework of smart grid.

An intelligent pattern recognition model to automate the categorisation of residential water end-use events

The rapid dissemination of residential water end-use (e.g. shower, clothes washer, etc.) consumption data to the customer via a web-enabled portal interface is becoming feasible through the advent of high resolution smart metering technologies. However, in order to achieve this paradigm shift in residential customer water use feedback, an automated approach for disaggregating complex water flow trace signatures into a registry of end-use event categories needs to be developed. This outcome is achieved by applying a hybrid combination of gradient vector filtering, Hidden Markov Model (HMM) and Dynamic Time Warping Algorithm (DTW) techniques on an existing residential water end-use database of 252 households located in South-east Queensland, Australia having high resolution water meters (0.0139 L/pulse), remote data transfer loggers (5 s logging) and completed household water appliance audits. The approach enables both single independent events (e.g. shower event) and combined events (i.e. several overlapping single events) to be disaggregated from flow data into a comprehensive end-use event registry. Complex blind source separation of concurrently occurring water end use events (e.g. shower and toilet flush occurring in same time period) is the primary focus of this present study. Validation of the developed model is achieved through an examination of 50 independent combined events.

Sistema para Rehabilitación del Síndrome del Miembro Fantasma utilizando Interfaz Cerebro-Computador y Realidad Aumentada

In this study, we used a commercial BCI device, the Emotiv EPOC, which is a high-resolution wireless neuroheadset for EEG signal acquisition, to develop a intelligent pattern detection tool parallel to the developer's one to implement an application that combines Augmented Reality (AR). The application was developed as a possible treatment of phantom limb pain (PLP) in amputees patients. The classification engine development has allowed greater control over processing parameters and signal pattern detection, which yielded up to 82.1% of classification. These detected neural signals from a subject, were used to decode its intention of closing or opening a virtual model of a hand or prosthesis attached to the real stump through the AR environment, providing visual feedback to the patient. This, would neurologically help reduce the PLP.

The Impact of Multiple Intellegences on Learning Outcomes in Fencing Curriculum

This research aims to develop an educational program using multiple intelligences in fencing curriculum for students in Faculty of Physical Education for Girls and identify: impact of this program on cognitive achievement; skill performance, and emotional side; all for fourth grade students, Education Division in the fencing curriculum, Identify differences in learning outcomes for fencing curriculum according to intelligence patterns. Researcher used experimental approach. Research sample were (70) student divided randomly into (20) student of pilot study, (25) students of experimental group, (25) students of control group which taught in traditional way. Researcher used multiple intelligences indicator list, cognitive test, skill evaluation form and educational program based on multiple inelegance theory as research tools. Results revealed that: Teaching strategies based on multiple intelligences patterns and to experimental group have positive effect on knowledge acquisition and skills performance and the emotional side of fencing curriculum. Linguistic and kinesthetic intelligence patterns contributed in fencing curriculum cognitive achievement. Kinesthetic and visual spatial intelligence patterns contributed in fencing skill performance. Social intelligence pattern contributed in emotional side of fencing skills

Intelligent Driver Mobility Model and Traffic Pattern Generation based Optimization of Reactive Protocols for Vehicular Ad-hoc Networks

Vehicular Ad-hoc Network (VANET) is the special type of MANET (Mobile Ad Hoc Network) where the mobile nodes are vehicles that move on roads at very high speed following traffic rules; they provide communication between vehicle and vehicle (V2V) and Vehicle and Road side infrastructural unit (V 2 I). A number of mobility models have been presented and their impact on the performance on the routing protocols has been tested by the researchers. In this paper vehicle to vehicle communication is analysed by integrating clustering of different areas and traffic lights into the Intelligent Driver Model with Intersection Management (IDM-IM). The performance of above model using AODV and AOMDV protocols with different traffic patterns is evaluated using VanetMobisim and NS-2.

Process Scheme Based NC Machining Chain Model for Aircraft Structural Parts

Although intelligent NC programming technology has made some progress, the efficiency and practicability were not high. For this reason, we presented the intelligent NC programming pattern based on process scheme (PS). In this pattern, some models and the rules were mainly proposed. Firstly, by analyzing the machining characteristic of aircraft structural parts, we established the tree model of PS and the constructing rules. Secondly, we constructed the extended generalized pocket model by slicing recognition to create the machining volume model (MVM). Thirdly, the machining chain model was put forward based on the PS and MVM. Finally, the developed pattern and model have been applied in the intelligent NC programming system of aircraft structural parts and are validated with high practicability and efficiency through a case study.

Development of Intelligent Pattern for Modeling a Parametric Program for Public Space (Case Study: Isfahan, Mosalla, Iran)

Islamic arts consist of several parts and could be noticed in works such as tiling, plaster works, stalactite work and etc. As well as in windows templates, wooden doors. The geometrical patterns as a part of Islamic arts have a ground for parametric program. This paper studies about the patterns that have emerged from Iranian traditional geometry and possess the ability to be changed into an intelligent pattern; followed by assessing characteristics that would make them parametric. The results were compared with Isfahan Mosalla, as the largest complex of metal shell with the dome-shape special structure that includes single welded mesh layer with nodes works and net pattern of classic wooden window, as a case sample. In conclusion, the reason of using the pattern worked in ceiling structure of the building has been discussed. This building is one of the valuable works that fairly reveal joining local architecture patterns with space-work structures system. Keywords: Intelligent pattern, Modelling, Parametric program, Islamic pattern.

Classification of energy consumption patterns for energy audit and machine scheduling in industrial manufacturing systems

To reduce energy consumption for sustainable and energy-efficient manufacturing, continuous energy monitoring and process tracking of industrial machines are essential. In this paper, we introduce a novel approach to reduce the number of required sensors in process tracking by identifying the operational states based on real-time energy data. Finite-state machines are used to model the engineering processes, and a two-stage framework for online classification of real-time energy measurement data in terms of machine operational states is proposed for energy audit and machine scheduling. The first stage uses advanced signal processing techniques to reduce noise while preserving important features, and the second stage uses intelligent pattern recognition algorithms to cluster energy consumption patterns. Our proposed two-stage framework is evaluated on an industrial injection moulding system using a Savizky–Golay filter and a neural network, and our experimental results show a 95.85% accuracy in identification of machine operational states.

Study on Development Model of Low-Carbon Tourist Scenic Spot

With the development of the tourism industry, tourist attraction is one of the most important core elements. And low-carbon development plays an increasingly important role. Based on analysis of the status of low-carbon tourism, this paper designs a low-carbon development model of tourist scenic spot, including the “four-wheel drive " development strategy model, intelligent design patterns and digital integrated management mode. These models are interrelated to promote the construction of low-carbon tourist attractions, which points out the direction for low-carbon tourist scenic spots.

An Investigation of Variable-Rate Fertilization Controlling System Based on XS-Base270 Platform

The research object is the variable-rate fertilization controlling system with the embedded computer as its core. On the basis of the XSBase270-S development platform and Windows CE operating system, this paper has presented the hardware structure of variable-rate fertilization controlling system, GPS data collection process, GPS data processing procedure, the flow sensor reading program and the controlling system of fertilization device, which are operated in a concurrent execution mode through the synchronic mechanism with the final purpose of achieving the variable-rate fertilization in an automatic and intelligent pattern.

Research on Intelligent Control Pattern of the Vehicle Driving Training

with the higher mobility in many developing country, the vehicle volume, vehicle use frequency are rapidly increasing, driving skill training becomes one key factor for vehicle security and use quality. By the comprehensive application of electron, computer, network technology, the supervision, control and guidance can be done to realize the intelligent dynamic management in driving training and standardized test, which promotes the students to obtain the optimal training effect in the possible shortest time, to provide a method to improve the overall driving quality.

Capacitance–Based Tomography Flow Pattern Classification Using Intelligent Classifiers With Voting Technique

This paper presents a method for Electrical Capacitance Tomography (ECT) flow classification using voting technique, employing Multilayer Perceptrons (MLPs) as the intelligent pattern classifiers. MLP classifiers were trained with a set of simulated ECT data associated to various flow patterns and was tested with untrained data to verify their performances. MLP classifiers which gave high percentage of correct classification were integrated into a voting system and tested over a distinct set of ECT data. The performances of the individually selected classifiers were compared with the voting system. The results showed superiority of the voting system over individual classifiers. Key words: Electrical capacitance tomography; multilayer perceptron; voting; pattern classification; ensemble neural network