Discovery and Capture of Organizational Knowledge from Unstructured Information

Knowledge of an organization does not merely reside in structured form of information and data; it is also embedded in unstructured form. The discovery of such knowledge is particularly difficult as the characteristic is dynamic, scattered, massive and multiplying at high speed. Conventional methods of managing unstructured information are considered too resource demanding and time consuming to cope with the rapid information growth. In this paper, a Multi-faceted and Automatic Knowledge Elicitation System (MAKES) is introduced for the purpose of discovery and capture of organizational knowledge. A trial implementation has been conducted in a public organization to achieve the objective of decision capture and navigation from a number of meeting minutes which are autonomously organized, classified and presented in a multi-faceted taxonomy map in both document and content level. Key concepts such as critical decision made, key knowledge workers, knowledge flow and the relationship among them are elicited and displayed in predefined knowledge model and maps. Hence, the structured knowledge can be retained, shared and reused. Conducting Knowledge Management with MAKES reduces work in searching and retrieving the target decision, saves a great deal of time and manpower, and also enables an organization to keep pace with the knowledge life cycle. This is particularly important when the amount of unstructured information and data grows extremely quickly. This system approach of knowledge management can accelerate value extraction and creation cycles of organizations.

Developing and Implementing Successful Key Performance Indicators

Measurement and the following evaluation of performance represent important part of management. The paper focuses on indicators as the basic elements of performance measurement system. It emphasizes a necessity of searching requirements for quality indicators so that they can become part of the useful system. It introduces standpoints for a systematic dividing of indicators so that they have as high as possible informative value of background sources for searching, analysis, designing and using of indicators. It draws attention to requirements for indicators' quality and at the same it deals with some dangers decreasing indicator's informative value. It submits a draft of questions that should be answered at the construction of indicator. It is obvious that particular indicators need to be defined exactly to stimulate the desired behavior in order to attain expected results. In the enclosure a concrete example of the defined indicator in the concrete conditions of a small firm is given. The authors of the paper pay attention to the fact that a quality indicator makes it possible to get to the basic causes of the problem and include the established facts into the company information system. At the same time they emphasize that developing of a quality indicator is a prerequisite for the utilization of the system of measurement in management.

Evaluation of The Energy Performance of Shading Devices based on Incremental Costs

Solar shading designs are important for reduction of building energy consumption and improvement of indoor thermal environment. This paper carried out a number of building simulations for evaluation of the energy performance of different shading devices based on incremental costs. The results show that movable shading devices lower incremental costs by up to 50% compared with fixed ones for the same building energy efficiency for residential buildings, and wing panel shadings are much more suitable in commercial buildings than baring screen ones and overhangs for commercial buildings.

Study of Mordenite ZSM-5 and NaY Zeolites,Containing Cr, Cs, Zn, Ni, Co, Li, Mn, to Control Hydrocarbon Cold-Start Emission

The implementation of Super-Ultra Low Emission Vehicle standards requires more efficient exhaust gas purification. To increase the efficiency of exhaust gas purification, an the adsorbent capable of holding hydrocarbons up to 250-300 ОС should be developed. The possibility to design such adsorbents by modification of zeolites of mordenite type, ZSM-5 and NaY, using different metals cations has been studied. It has been shown that introducing Cr, Cs, Zn, Ni, Co, Li, Mn in zeolites results in modification of the toluene TPD and toluene sorption capacity. 5%LiZSM-5 zeolite exhibits the most attractive TPD curve, with toluene desorption temperature ranging from 250 to 350ОС. The sorption capacity of 5%Li-ZSM-5 is 0.4 mmol/g. NaY zeolite has the highest sorption capacity, up to 2 mmol/g, and holds toluene up to 350ОС, but at 120ОС toluene desorption starts, which is not desirable, since the adsorbent of cold start hydrocarbons should retain them until 250-300ОС. Therefore 5%LiZSM-5 zeolite was found to be the most promising to control the cold-start hydrocarbon emissions among the samples studied.

A Study of Visitors, on Service Quality, Satisfaction and Loyal in Ya Tam San Bikeway

The main purpose of this study is to analyze the feelings of tourists for the service quality of the bikeway. In addition, this study also analyzed the causal relationship between service quality and satisfaction to visitor-s lane loyalty. In this study, the Ya Tam San bikeway visitor-s subjects, using the designated convenience sampling carried out the survey, a total of 651 questionnaires were validly. Valid questionnaires after statistical analysis, the following findings: 1. Visitor-s lane highest quality of service project: the routes through the region weather pleasant. Lane "with health and sports," the highest satisfaction various factors of service quality and satisfaction, loyal between correlations exist. 4. Guided tours of bikeways, the quality of the environment, and modeling imagery can effectively predict visitor satisfaction. 5. Quality of bikeway, public facilities, guided tours, and modeling imagery can effectively predict visitor loyalty. According to the above results, the study not only makes recommendations to the government units and the bicycle industry, also asked the research direction for future researchers.

An Effective Method for Audio Translation between IAX and RSW Protocols

Nowadays, Multimedia Communication has been developed and improved rapidly in order to enable users to communicate between each other over the Internet. In general, the multimedia communication consists of audio and video communication. However, this paper focuses on audio streams. The audio translation between protocols is a very critical issue due to solving the communication problems between any two protocols, as well as it enables people around the world to talk with each other at anywhere and anytime even they use different protocols. In this paper, a proposed method for an audio translation module between two protocols has been presented. These two protocols are InterAsterisk eXchange Protocol (IAX) and Real Time Switching Control Protocol (RSW), which they are widely used to provide two ways audio transfer feature. The result of this work is to introduce possibility of interworking together.

Comparison of Imputation Techniques for Efficient Prediction of Software Fault Proneness in Classes

Missing data is a persistent problem in almost all areas of empirical research. The missing data must be treated very carefully, as data plays a fundamental role in every analysis. Improper treatment can distort the analysis or generate biased results. In this paper, we compare and contrast various imputation techniques on missing data sets and make an empirical evaluation of these methods so as to construct quality software models. Our empirical study is based on NASA-s two public dataset. KC4 and KC1. The actual data sets of 125 cases and 2107 cases respectively, without any missing values were considered. The data set is used to create Missing at Random (MAR) data Listwise Deletion(LD), Mean Substitution(MS), Interpolation, Regression with an error term and Expectation-Maximization (EM) approaches were used to compare the effects of the various techniques.

Formal Verification of a Multicast Protocol in Mobile Networks

As computer network technology becomes increasingly complex, it becomes necessary to place greater requirements on the validity of developing standards and the resulting technology. Communication networks are based on large amounts of protocols. The validity of these protocols have to be proved either individually or in an integral fashion. One strategy for achieving this is to apply the growing field of formal methods. Formal methods research defines systems in high order logic so that automated reasoning can be applied for verification. In this research we represent and implement a formerly announced multicast protocol in Prolog language so that certain properties of the protocol can be verified. It is shown that by using this approach some minor faults in the protocol were found and repaired. Describing the protocol as facts and rules also have other benefits i.e. leads to a process-able knowledge. This knowledge can be transferred as ontology between systems in KQML format. Since the Prolog language can increase its knowledge base every time, this method can also be used to learn an intelligent network.

Detecting and Tracking Vehicles in Airborne Videos

In this work, we present an automatic vehicle detection system for airborne videos using combined features. We propose a pixel-wise classification method for vehicle detection using Dynamic Bayesian Networks. In spite of performing pixel-wise classification, relations among neighboring pixels in a region are preserved in the feature extraction process. The main novelty of the detection scheme is that the extracted combined features comprise not only pixel-level information but also region-level information. Afterwards, tracking is performed on the detected vehicles. Tracking is performed using efficient Kalman filter with dynamic particle sampling. Experiments were conducted on a wide variety of airborne videos. We do not assume prior information of camera heights, orientation, and target object sizes in the proposed framework. The results demonstrate flexibility and good generalization abilities of the proposed method on a challenging dataset.

Nanocrystalline Na0.1V2O5.nH2O Xerogel Thin Film for Gas Sensing

Nanocrystalline thin film of Na0.1V2O5.nH2O xerogel obtained by sol gel synthesis was used as gas sensor. Gas sensing properties of different gases such as hydrogen, petroleum and humidity were investigated. Applying XRD and TEM the size of the nanocrystals is found to be 7.5 nm. SEM shows a highly porous structure with submicron meter-sized voids present throughout the sample. FTIR measurement shows different chemical groups identifying the obtained series of gels. The sample was n-type semiconductor according to the thermoelectric power and electrical conductivity. It can be seen that the sensor response curves from 130oC to 150oC show a rapid increase in sensitivity for all types of gas injection, low response values for heating period and the rapid high response values for cooling period. This result may suggest that this material is able to act as gas sensor during the heating and cooling process.

Development of Low-cost OCDMA Encoder Based On Arrayed Waveguide Gratings(AWGs) and Optical Switches

This paper describes the development of a 16-ports optical code division multiple access (OCDMA) encoder prototype based on Arrayed Waveguide Grating (AWG) and optical switches. It is potentially to provide a high security for data transmission due to all data will be transmitted in binary code form. The output signals from AWG are coded with a binary code that given to an optical switch before it signal modulate with the carrier and transmitted to the receiver. The 16-ports encoder used 16 double pole double throw (DPDT) toggle switches to control the polarization of voltage source from +5 V to -5 V for 16 optical switches. When +5 V is given, the optical switch will give code '1' and vice versa. The experimental results showed the insertion loss, crosstalk, uniformity, and optical signal-noise-ratio (OSNR) for the developed prototype are

A Thermal-Shock Fatigue Design of Automotive Heat Exchangers

A method is presented for using thermo-mechanical fatigue analysis as a tool in the design of automotive heat exchangers. Use of infra-red thermography to measure the real thermal history in the heat exchanger reduces the time necessary for calculating design parameters and improves prediction accuracy. Thermal shocks are the primary cause of heat exchanger damage. Thermo-mechanical simulation is based on the mean behavior of the aluminum tubes used in the heat exchanger. An energetic fatigue criterion is used to detect critical zones.

Characterization of Liver Leukocyte Infiltrates and Features of Cytokine Profile under Viral Hepatitis-Induced Immunosuppression

The nature, prevalence, cellular composition of leukocyte infiltrates and immunohistochemical characteristics of their constituent cells in the liver of patients with chronic viral hepatitis B and C were investigated. It was found that the area of distribution and cellular composition of infiltrates depended on the virus type and process activity. The expediency of immunohistochemical study using leukocyte infiltrates from liver biopsies of patients with viral hepatitis aimed at clarifying diagnosis, making prognosis, and choice of optimal treatment with elements of immune correction is emphasized.

The Influence of Doping of Fullerene Derivative (PCBM) on the Optical Properties of Vanadyl Phthalocyanine (VOPc)

This paper presents a spectroscopic study on doping of Vanadyl pathalocyanine (VOPc) by [6,6]-phenyl C61 butyric acid methyl ester (PCBM). The films are characterized by UV/Vis/NIR spectroscopy. A drastic increase in the absorption coefficient has been observed with increasing dopant concentration. Optical properties of VOPc:PCBM films deposited by spin coating technique were studied in detail. Optical band gap decreased with the PCBM incorporation in the VOPc film. Optical band gap calculated from the absorption spectra decreased from 3.32 eV to 3.26 eV with a variation of 0–75 % of PCBM concentration in the VOPC films.

Forest Growth Simulation: Tropical Rain Forest Stand Table Projection

The study on the tree growth for four species groups of commercial timber in Koh Kong province, Cambodia-s tropical rainforest is described. The simulation for these four groups had been successfully developed in the 5-year interval through year-60. Data were obtained from twenty permanent sample plots in the duration of thirteen years. The aim for this study was to develop stand table simulation system of tree growth by the species group. There were five steps involved in the development of the tree growth simulation: aggregate the tree species into meaningful groups by using cluster analysis; allocate the trees in the diameter classes by the species group; observe the diameter movement of the species group. The diameter growth rate, mortality rate and recruitment rate were calculated by using some mathematical formula. Simulation equation had been created by combining those parameters. Result showed the dissimilarity of the diameter growth among species groups.

Developing a Campus Sustainability Assessment Framework for the National University of Malaysia

Campus sustainability is the goal of a university striving for sustainable development. This study found that of 17 popular approaches, two comprehensive campus sustainability assessment frameworks were developed in the context of Sustainability in Higher Education (SHE), and used by many university campuses around the world. Sustainability Tracking Assessment and Rating Systems (STARS) and the Campus Sustainability Assessment Framework (CSAF) approaches are more comprehensive than others. Therefore, the researchers examined aspects and elements used by CSAF and STARS in the approach to develop a campus sustainability assessment framework for Universiti Kebangsaan Malaysia (UKM). Documents analysis found that CSAF and STARS do not focus on physical development, especially the construction industry, as key elements of campus sustainability assessment. This finding is in accordance with the Sustainable UKM Programme which consists of three main components of sustainable community, ecosystem and physical development.

Design, Analysis and Modeling of Dual Band Microstrip Loop Antenna Using Defective Ground Plane

Present wireless communication demands compact and intelligent devices with multitasking capabilities at affordable cost. The focus in the presented paper is on a dual band antenna for wireless communication with the capability of operating at two frequency bands with same structure. Two resonance frequencies are observed with the second operation band at 4.2GHz approximately three times the first resonance frequency at 1.5GHz. Structure is simple loop of microstrip line with characteristic impedance 50 ohms. The proposed antenna is designed using defective ground structure (DGS) and shows the nearly one third reductions in size as compared to without DGS. This antenna was simulated on electromagnetic (EM) simulation software and fabricated using microwave integrated circuit technique on RT-Duroid dielectric substrate (εr= 2.22) of thickness (H=15 mils). The designed antenna was tested on automatic network analyzer and shows the good agreement with simulated results. The proposed structure is modeled into an equivalent electrical circuit and simulated on circuit simulator. Subsequently, theoretical analysis was carried out and simulated. The simulated, measured, equivalent circuit response, and theoretical results shows good resemblance. The bands of operation draw many potential applications in today’s wireless communication.

Quantity and Quality Aware Artificial Bee Colony Algorithm for Clustering

Artificial Bee Colony (ABC) algorithm is a relatively new swarm intelligence technique for clustering. It produces higher quality clusters compared to other population-based algorithms but with poor energy efficiency, cluster quality consistency and typically slower in convergence speed. Inspired by energy saving foraging behavior of natural honey bees this paper presents a Quality and Quantity Aware Artificial Bee Colony (Q2ABC) algorithm to improve quality of cluster identification, energy efficiency and convergence speed of the original ABC. To evaluate the performance of Q2ABC algorithm, experiments were conducted on a suite of ten benchmark UCI datasets. The results demonstrate Q2ABC outperformed ABC and K-means algorithm in the quality of clusters delivered.

Emotion Classification for Students with Autism in Mathematics E-learning using Physiological and Facial Expression Measures

Avoiding learning failures in mathematics e-learning environments caused by emotional problems in students with autism has become an important topic for combining of special education with information and communications technology. This study presents an adaptive emotional adjustment model in mathematics e-learning for students with autism, emphasizing the lack of emotional perception in mathematics e-learning systems. In addition, an emotion classification for students with autism was developed by inducing emotions in mathematical learning environments to record changes in the physiological signals and facial expressions of students. Using these methods, 58 emotional features were obtained. These features were then processed using one-way ANOVA and information gain (IG). After reducing the feature dimension, methods of support vector machines (SVM), k-nearest neighbors (KNN), and classification and regression trees (CART) were used to classify four emotional categories: baseline, happy, angry, and anxious. After testing and comparisons, in a situation without feature selection, the accuracy rate of the SVM classification can reach as high as 79.3-%. After using IG to reduce the feature dimension, with only 28 features remaining, SVM still has a classification accuracy of 78.2-%. The results of this research could enhance the effectiveness of eLearning in special education.

A Dynamic Time-Lagged Correlation based Method to Learn Multi-Time Delay Gene Networks

A gene network gives the knowledge of the regulatory relationships among the genes. Each gene has its activators and inhibitors that regulate its expression positively and negatively respectively. Genes themselves are believed to act as activators and inhibitors of other genes. They can even activate one set of genes and inhibit another set. Identifying gene networks is one of the most crucial and challenging problems in Bioinformatics. Most work done so far either assumes that there is no time delay in gene regulation or there is a constant time delay. We here propose a Dynamic Time- Lagged Correlation Based Method (DTCBM) to learn the gene networks, which uses time-lagged correlation to find the potential gene interactions, and then uses a post-processing stage to remove false gene interactions to common parents, and finally uses dynamic correlation thresholds for each gene to construct the gene network. DTCBM finds correlation between gene expression signals shifted in time, and therefore takes into consideration the multi time delay relationships among the genes. The implementation of our method is done in MATLAB and experimental results on Saccharomyces cerevisiae gene expression data and comparison with other methods indicate that it has a better performance.